EVALUATION of MALARIA DIAGNOSTIC METHODS, EFFICACY of ARTEMETHER- LUMEFANTRINE THERAPY and GENETIC DETERMINANTS of Plasmodium Falciparum RESISTANCE

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EVALUATION OF MALARIA DIAGNOSTIC METHODS, EFFICACY OF ARTEMETHER- LUMEFANTRINE THERAPY AND GENETIC DETERMINANTS OF Plasmodium falciparum RESISTANCE

AYOGU, EBERE EMILIA

REG. NO: PG/PhD/10/57517

DEPARTMENT OF CLINICAL PHARMACY AND PHARMACY

MANAGEMENT,

FACULTY OF PHARMACEUTICAL SCIENCES

UNIVERSITY OF NIGERIA, NSUKKA

A THESIS SUBMITTED TO THE SCHOOL OF POST GRADUATE STUDIES OF THE UNIVERSITY OF NIGERIA, NSUKKA FOR THE AWARD OF DEGREE OF DOCTOR OF PHILOSOPHY (IN CLINICAL PHARMACY)

CERTIFICATION

Ebere Emilia Ayogu, a post graduate student in the Department of Clinical Pharmacy and Pharmacy Management with registration number PG/PhD/10/57517 has satisfactorily completed the requirements for the award of the degree of Doctor of Philosophy in Clinical Pharmacy and Pharmacy Management. The work embodied in this thesis is original and has not been submitted in part or full for any diploma or degree in this or any other University.

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Prof. Chinwe V. Ukwe Prof. J.M. Okonta

(Supervisor) (Head of Department)

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Date Date

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DEDICATION

This thesis is dedicated to my husband, Hon. Ayogu, Felix Victor who has laid down all necessary resources to see me through my academic pursuit from undergraduate to present.

ACKNOWLEDGEMENT

I am forever grateful to Almighty God who in His infinite goodness granted me bountiful blessings, good health and wisdom through out the period of this research.

My sincerest thanks go to my supervisor, Prof Chinwe V. Ukwe for supervising my work in and out of academic sessions. I wish to appreciate my Head of Department, Prof J.M Okonta for his encouragement through out my research period. I also thank Prof C Nze Aguwa for his fatherly advice and encouragement from my under graduate days to present.

I am indebted to Dr Emmanuel Nna, CEO Safety Molecular Pathology Laboratory (SMPL) for providing a standard molecular laboratory where all investigations were carried out and for statistically analyzing my results. I also thank all the staff of SMPL for their dedicated contributions to the successful completion of all molecular testing.

I am very grateful to the staff of District Hospital Nsukka, Bishop Shanahan Annex, Enugu Ezike and Cottage Hospital Ugbuawka for allowing me access to the clinic and patients and in a special way the Laboratory Scientist that helped me in sample collection. This study would not have been feasible without the patients that consented to participate. I thank them all especially those who completed their follow up visits.

I can not conclude without mentioning the untiring efforts of my senior colleague, Dr (Mrs) Petra Nnamani, for accepting me as a sister and leaving her doors open for me even at odd times. I also want to appreciate my professional colleagues and staff in the Department of Clinical Pharmacy and Pharmacy Management for their support.

My warmest regard goes to my parents, Sir Titus and Dame Augustina Omeh, my siblings Ngo, Agidi, Equi, Chia, Bukas and Emebroda for being there for me in times of difficulty and happiness. I am also grateful to my brother in-law Hon Kentus Eze, for providing a comfortable accommodation for me through out my stay in Enugu.

Finally, to my kids, NG, Dudu, Mimi, Onyi, Neche and my sister-in-law Amaka. I acknowledge your love and patience especially through out the numerous weeks I was absent from home. To Rev. Frs Norbet Attah and Christopher Ugwuta for their prayers and Mr Kenneth Ugwu, I say thanks a lot. To all others who in one way or the other contributed to the success of this work I say may God reward them all.

LIST OF ABBREVIATIONS

ABBREVIATIONS MEANINGS

A + T Adenine + Thymine AA Amino acids A-A Artesunate-amodiaquine AAH+ Protonated Amino acids ACPR Adequate clinical and parasitological response ACR Adequate clinical response ACTs Artemisinin Combination Therapies AFLPD Amplified fragment length polymorphism detection AL Artemether-lumefantrine Ala/Phe Alanine/Phenylalanine ALRTI Acute lower respiratory tract infection ALS Amyotrophic lateral sclerosis Arg Arginine ART Artemisinin Asn/Thr Asparagine/Threonine ASO Allele specific oligonucleotide BCRR Basic case reproduction rate CD Chlorproguanil- dapsone

CD36 Cluster of differentiation 36 cDNA Complimentary DNA CNV Copy number variation CQ Chloroquine CQH+ Protonated Chloroquine CQR Chloroquine – resistant CQS Chloroquine - sensitive Cys Cystein DARC Duffy antigen receptor for chemokines dATP Deoxyriboadenosine triphosphate

vi dCTP Deoxyribocytosine triphosphate dGTP Deoxyriboguanine triphosphate DHA Dihydro-artemisinin DHFR Dihydrofolate reductase DHP Dihydropteroate DHPPP 2-amino-4-hydroxy-6- hydroxymethyl-7, 8 dihydropteridine pyrophosphate DHPS Dihydropteroate synthase dNTPs Deoxyribonuclease triphosphates dTTP Deoxyribotyrosine triphosphate DV Digestive vacuole EANMAT East African Network for Monitoring Antimalarial Treatment ECs Endothelial cells EEO Electro-endosmosis EIR Entomological inoculation rate ETF Early treatment failure G + C Guanine + Cytosine

G6PD Glucose-6-phosphate dehydrogenase gDNA Genomic DNA GFI Genotype failure index Glu Glutamine Gly Glycine GPI Glycosylphosphatidylinositol Hb Hemoglobin HIV Human immuno-virus HLA Human leukocyte antigen HRP II Histidine rich protein II ICAM-1 Intercellular Adhesion Molecule 1 IE Infected erythrocyte IIe Iso-leucine IPA Isopropanol-acetic acid IPT Intermittent preventive treatment iRBC Infected red blood cell IRS Indoor residual spraying ITNs Insecticide treated nets

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LCF Late clinical failure LD Linkage disequilibrium Leu Leucine LTF Late treatment failure MDGs Millennium Development Goals MLP Multi-locus probe MQ Mefloquine mRNA messenger RNA MSP Merozoite surface proteins msp 1 and 2 Merozoites surface protein 1 and 2 NNATP Nigerian National Antimalarial Treatment Policy NO Nitric oxide npcRNAs Non protein-coding RNAs NPV Negative predictive values NSPM Non-synonymous point mutations p-ABA p-aminobenzoic acid PCR Polymerase chain reaction PCT Parasite clearance time PfATPase b Plasmodium falciparum adenosine triphosphatase b Pfcrt Plasmodium falciparum chloroquine resistance transporter, PFGE Pulsed field gel electrophoresis Pfmdr 1 Plasmodium falciparum multidrug resistant gene1 Pgh1 P-glycoprotein homologue 1 pLDH Plasmodium enzyme lactate dehydrogenase PPM Parasite plasma membrane PPV Positive predictive values PVM Parasitophorous vacuolar membrane QN Quinine RAPD Random amplified polymorphic detection RBM Roll Back Malaria RDT Rapid diagnostic test RFLP Restriction fragment length polymorphism RNA Ribo nucleic acid SAO South-East Asian ovalocytosis

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SDS Sodium docecyl sulphate SERCA2+ Sarco/endoplasmic reticulum Ca2+ SGOT Serum glutamic oxaloacetic transaminase SLP Single locus probe SMPL Safety Molecular Pathology Laboratory SNPs Single nucleotide polymorphisms snRNAs Small nucleolar RNAs SOD1 Superoxide dismutase 1 SP Sulfadoxine – pyrimethamine TAREs Telomere-associated repetitive elements TE Tris EDTA THF Tetrahydrofolate Thr/Ser Threonine/Serine Tm Melting temperature tRNA Transport RNA TV Transport vesicles UNICEF United Nation International Children Emergency Fund UNTH University of Nigeria Teaching Hospital UTL Useful therapeutic life UV Ultraviolet Val Valine WHO World Health Organization

LIST OF FIGURES

Figure 1.1: Lifecycle of Plasmodium falciparum------7 Figure 1.2: The pathophysiology of P. falciparum infection - - - - 16 Figure 1.3: The process of DNA amplification by PCR, showing denaturation, annealing and extension ------61 Figure 1.4: The process of DNA amplification and quantification by Real Time PCR - - 64 Figure 2.1: Preparation of 2 % agarose gel ------89

LIST OF TABLES

Table 1.1: Degree of exposure and pattern of host morbidity - - - - - 25 Table 2.1: Course of AL treatment ------78 Table 2.2 Classification of Treatment responses based on PCT- - - - - 85 Table 2.3 Classification of treatment responses based on therapeutic efficacy- - - 86 Table 3.1: Patients’ characteristics ------98 Table 3.2: Comparison of RDT with microscopy ------99 Table 3.3: Comparison of RDT with PCR ------100 Table 3.4: Comparison of microscopy with PCR ------101 Table 3.5: Cost and turn around time of diagnostic methods - - - - - 102 Table 3.6: Temperature distributions among patients on follow days - - - - 103 Table 3.7: Mean parasite densities on follow up days ------104 Table 3.8: Classification of treatment outcome based on parasite clearance time - - 105 Table 3.9: Clinical and parasitological PCR uncorrected responses on days 14 post treatment - 106 Table 3.10: Clinical and parasitological PCR uncorrected responses on days 28 post treatment - 107 Table 3.11: Distribution of mean parasite clearance time among patients’ characteristics - 108 Table 3.12: Parasite clearance time and treatment outcome - - - - - 109 Table 3.13: Polymorphic gene investigated, mutation sites, primer sequences, PCR conditions and restriction enzymes ------110 Table 3.14: Frequencies of Pfmdr 1 mutations and co-mutations among the patients and their restriction enzymes ------111 Table 3.15: Comparison of prevalence of Pfmdr1 mutations in patients with sensitivity, mild, moderate and severe resistance ------112 Table 3.16: Comparison of prevalence of Pfmdr 1 mutations in patients that failed treatment and those that responded to treatment------113 Table 3.17: Comparison of prevalence of Pfmdr 1 co-mutations in patients with sensitivity, mild, moderate and severe resistance ------114 Table 3.18: Comparison of prevalence of Pfmdr 1 co-mutations in patients that failed treatment and those that responded to treatment------115 Table 3.19: Comparison of prevalence of Pfmdr 1 mutation in pre and post treatment - - 116

ABSTRACT Objectives: The objectives of this study were: to evaluate malaria diagnostic methods, therapeutic efficacy of artemether-lumefantrine (AL), the prevalence of N86Y, Y184F, S1034C and N1042D SNPs in Pfmdr1 gene and their association with AL resistance in Plasmodium falciparum malaria infections in Nigeria. Methods: This study was carried out within 14 months. One hundred and sixty (160) malaria patients that met criteria were recruited through rapid diagnostic testing (RDT) using first response kit and blood film microscopy after which each patient received a 3-day complete dose of AL treatment. Patients were monitored and followed up on days 0, 3, 7, 14 and 28. Body temperature was taken and 2ml of blood was sampled from each patient into labeled EDTA bottle. Genomic DNA was extracted from each sample by saponin heamolysis. Samples were analyzed by nested polymerase chain reaction (PCR) and real time PCR for identification and quantification of Plasmodium falciparum. Genotyping of Pfmdr 1 gene for specific genetic variants: N86Y, Y184F, S1034C and N1042D were done using Restriction Fragment Length Polymorphism (RFLP-PCR). The overall performances of diagnostic methods used were analyzed using sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) obtained (with PCR as the gold standard). Data were analyzed using both Graph Pad (Prism 5) and SPSS (version 16). Descriptive statistics presented as counts, percentages, means, and standard deviations, as appropriate, were used to compare the demographic characteristics of the study population and their initial clinical and biological characteristics (such as temperature and geometric mean parasitaemia). Differences in proportions of treatment outcome and frequency in occurrence of Pfmdr 1 gene mutation in pretreatment and post treatment groups were analyzed using the paired T test, Chi-square test or Fisher’s exact test. While the differences in parasitic densities of the various groups were analyzed using ANOVA and inter group comparison was done using Post Hoc test. Results: Sensitivity, specificity, positive and negative predictive values of 75 %, 75 %, 95 %, 31 % and 92 %, 50 %, 91 %, 55 % were obtained by RDT and microscopy respectively using PCR as gold standard. For therapeutic efficacy, 106 (68.8 %) patients had body temperature of ≥ 37.5 °C with mean temperature of 38.4 °C on day 0 while on day 3, 3.3 % of the patients had temperature of 37.1-38 °C with mean temperature of 36.2 °C. There was significant decrease in temperature from day 0 to day 28 (P < 0.0001). There was significant difference (P < 0.0001) between parasite mean densities on day 0 compared to days 3,7,14 and 28, with high prevalence of delayed parasite clearance. There were 4 cases of late clinical failure for both 14 and 28 day. Adequate clinical and parasitological responses, (PCR uncorrected) were

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80 % and 75 % respectively for day 14 and 28. Out of 60 samples with treatment failure that were successfully genotyped, 26 (24.3 %), 24 (23.0 %) and 9 (7.0 %) had Pfmdr 1 N86Y, Y184F and S1034C respectively. Of the sixty, 59 (98.3 %) had one form of mutation or the other. Of the 56 that had good response, 3 (5.4 %) were mutated. The prevalence of Pfmdr 1 mutation was significantly associated with treatment failure (P < 0.001). There was significant increase (P < 0.001) in the prevalence of Pfmdr 1 N86Y mutation from six (20.0 %) to twenty four (92.3 %), Pfmdr 1 Y184F mutation from eight (5.2 %) to twenty five (92.6 %) and Pfmdr 1 S1034C mutation from four (44 %) to nine (100 %) in pre-treatment compared to post-treatment group respectively. Conclusion: Microscopy is more reliable than first response (RDT) using PCR as standard. Therapeutic efficacy of AL in adults has reduced in Enugu State; South Eastern Nigeria. There is high prevalence of Pfmdr 1 N86Y and F184Y mutation with no incidence of Pfmdr 1 N1042D in Enugu, Nigeria. Presence of individual and multiple mutations in the study population is associated to AL resistance by P. falciparum. The presence of AL drug significantly induced genetic variation in the plasmodial genes.

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TABLE OF CONTENTS TITLE PAGE ------i CERTIFICATION ------ii DEDICATION ------iii ACKNOWLEDGEMENT ------iv LIST OF ABBREVIATIONS ------v LIST OF FIGURES ------ix LIST OF TABLES ------x ABSTRACT ------xi TABLE OF CONTENTS ------xiii CHAPTER ONE ------1 INTRODUCTION AND LITERATURE REVIEW ------1 1.1 Background to the study ------1 1.2 Statement of problem ------3 1.3 Significance of study------4 1.4 Justification of study ------5 1.5 Literature review ------5 1.5.1 Plasmodium falciparum malaria ------5 1.5.2 Lifecycle Plasmodium falciparum ------5 1.5.3 Pathophysiology/Pathogenesis of malaria - - - - - 8 1.5.4 Complications of malaria ------10 1.5.4.1 Intravascular heamolysis------11 1.5.4.2 Heamoglobinuria------11 1.5.4.3 Jaundice ------12 1.5.4.4 Hepatic dysfunction------12 1.5.4.5 Hypoglycemia------13 1.5.4.6 Anemia------13 1.5.4.7 Renal failure------14 1.5.4.8 Pulmonary edema------14 1.5.4.9 Cerebral malaria------14 1.5.5 Prevalence of malaria in Nigeria------17 1.5.6 Epidemiology of malaria------18 1.5.6.1 Human factors ------18 1.5.6.2 Parasite factor ------21

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1.5.6.3 Vector factor ------22 1.5.6.4 Environmental factor ------22 1.5.7 Malaria transmission------22 1.5.7.1 Natural factor------23 1.5.7.2 Man-made factors------23 1.5.7.3 Exposure------23 1.5.8 Malaria infection------26 1.5.9 Diagnosis of malaria------27 1.5.9.1 Clinical (presumptive) diagnosis------27 1.5.9.2 Parasitological diagnosis------28 1.5.9.3 Immunological (antigen detection) diagnosis- - - - 28 1.5.9.4 Molecular diagnosis------29 1.5.10 Goals of antimalarial treatment------29 1.5.11 Treatment of malaria ------30 1.5.11.1 Treatment of malaria in special groups ------31 1.5.11.4 Treatment of uncomplicated malaria------32 1.5.11.3 Antimalarial drug combinations------35 1.5.11.4 Treatment of severe malaria------37 1.5.12 Emergence and spread of P. falciparum resistance- - - - 38 1.5.12.1 Factors influencing rate of spread of P. falciparum resistance- - - 39 1.5.13 Malaria chemotherapy and assessment of antimalarial efficacy- - - 41 1.5.13.1 Antimalarial drug resistance situation in sub-Sahara Africa- - - 42 1.5.13.2 Impact of antimalarial drug resistance------43 1.5.13.3 Mode of action and mechanisms of resistance to antimalarial drugs- - 44 1.5.14 Malaria genome------50 1.5.14.1 Protein target structure------51 1.5.14.2 Telomere structure------51 1.5.14.3 Structural variance and transcriptomics of Plasmodium falciparum- - 52 1.5.14.4 Genetic variations in malaria genome------53 1.5.15 Single nucleotide polymorphism and mutation- - - - - 53 1.5.15.1. Synonymous mutation------55 1.5.15.2 Non-synonymous mutation ------55 1.5.15.3 Missense mutation ------55 1.5.16 Pfmdr 1 gene------57

1.5.16.1 Mechanism by which Pfmdr 1 gene confers resistance to antimalarials - 58 1.5.17 Amplification of genomic DNA------59 1.5.17.1 PCR chemistry------59 1.5.17.2 Nested PCR------62 1.5.18 Quantification of genomic DNA ------63 1.5.18.1 Real time PCR ------63 1.5.18.2 Classification of Real time PCR------65 1.5.18.3 Applications of Real time PCR ------65 1.5.19 DNA extraction ------66 1.5.19.1 Methods of DNA extraction------66 1.5.19.1 Organic method------67 1.5.19.2 Non organic methods------67 1.5.19.3 Chelex extraction------67 1.5.19.4 Filter Paper (FTA™) method ------68 1.5.19.5 Silica based extraction------68 1.5.20 Genotyping of DNA ------69 1.5.20.1 Discrimination of recrudescent from new infections by molecular Genotyping ------69 1.5.21 Restriction fragment length polymorphism- - - - - 70 1.5.21.1 Technique of Restriction fragment length polymorphism- - - 71 1.5.21.2 Applications of Restriction fragment length polymorphism- - - 71 1.5.22 Agarose gel electrophoresis------72 1.5.23 Purpose of study------75

CHAPTER TWO------76 MATERIALS AND METHODS------76 2.1 Study design------76 2.2 Study period------76 2.3 Study area------76 2.4 Sample size and power analysis------77 2.5 Inclusion and exclusion criteria ------77 2.6 Enrolment of patients------77 2.7 Sample collection------79 2.8 Rapid diagnostic test for detection of Plasmodium falciparum- - - 80 2.9 Thick films microscopic detection of Plasmodium falciparum- - - 80

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2.10 Extraction of DNA using saponin hemolysis- - - - - 80 2.10.1 Determination of quality of DNA extracted- - - - - 81 2.11 Validation of processes------82 2.12 Detection and amplification of plasmodial genomic DNA - - - 82 2.12.1 Amplification of genus - Plasmodium by nested PCR- - - - 82 2.12.2 Detection and quantification of Plasmodium falciparum species by Real time PCR ------83 2.13 Treatment responses------84 2.14 Genotyping of parasite genomic DNA for Pfmdr 1 N86Y, Y184F, S1034C and N1042D genes ------87 2.14.1 Amplification of Pfmdr 1 N86Y, Y184F, S1034C and N1042D genes - - 87 2.15 Pfmdr 1 gene enzymes digest by PCR-RFLP methodology- - - 87 2.16 Preparation of agarose gel------87 2.17 Gel electrophoresis of digested genes------90 2.18 Patients’ management------90 2.19 Health research ethics approval ------90 2.20 Data analysis------90

CHAPTER 3 ------92 RESULTS ------92 3.1 Socio-demographic profile of subjects------92 3.2 Result of diagnostic techniques ------92 3.2.1 Comparison of RDT with microscopy------92 3.2.2 Comparison of RDT with PCR ------92 3.2.3 Comparison of microscopy with PCR ------93 3.2.4 Cost and turn around time of diagnostic methods- - - - 93 3.3 Result of treatment outcomes------93 3.3.1 Clinical symptoms------93 3.3.2 Parasitaemia densities on follow-up days- - - - - 93 3.3.3 Parasite clearance time (PCT)------94 3.3.4 Clinical and parasitological PCR uncorrected responses on days 14 post treatment------95 3.3.5 Clinical and parasitological PCR uncorrected responses on days 28 post Treatment------95 3.3.6 Parasite clearance and patients’ characteristics - - - - - 95

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3.3.7 Parasite clearance and treatment outcome. - - - - - 95 3.4 Result of Pfmdr 1 gene genotyping ------95 3.4.1 Summary of genotyping. ------95 3.4.2 Criteria for selection of samples for each group- - - - - 96 3.4.3 Frequencies of Pfmdr 1 gene mutations and co-mutations among patients- 96 3.4.5 Comparison of frequency of Pfmdr 1 gene in patients with sensitive, mild, moderate and severe resistance------96 3.4.6 Comparison of frequency of Pfmdr 1 gene in patients that failed treatment and those that responded to treatment ------97 3.4.7 Comparison of frequencies of Pfmdr 1 co-mutation in patients with sensitive, mild, moderate and severe resistance- - - - - 97 3.4.8 Comparison of frequency of Pfmdr 1 co-mutation in patients that failed treatment and those that responded to treatment - - - - - 97 3.4.9 Comparison of frequencies of Pfmdr 1 mutations in pre and post treatment 97

CHAPTER FOUR------117 DISCUSSION------117 4.1 Diagnostic methods ------117 4.1.1 Comparison of RDT with Microscopy------118 4.1.2 Comparison of RDT with PCR ------118 4.1.3 Comparison of microscopy with PCR ------119 4.1.4 Factors contributing to observed performances by the different diagnostic Methods------120 4.1.5 Cost and turn around time of the different diagnostic methods- - - 122 4.2 Responses following treatment with artemether – lumefantrine- - - 123 4.2.1 Clinical responses with reference to fever clearance- - - - 124 4.2.2 Response based on parasitemia clearance- - - - - 125 4.2.2.1 Patient with total parasite clearance on day 3- - - - - 125 4.2.2.2 Patient with delayed parasite clearance------125 4.2.2.3 Patient with increased parasitaemia level- - - - - 126 4.2.2.4 Patient who did not show any response with respect to parasite clearance on day 3------126 4.2.2.5 Patient with recurrent parasitemia on day 7 and 14- - - - 127 4.2.2.6 Possible factors contributing to high prevalence of patient with presence of parasitaemia post treatment------128

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4.2.2.7 Parasite clearance and treatment response- - - - - 128 4.2.2.8 Parasite clearance time and patients’ characteristics- - - - 128 4.2.3 Therapeutic responses to AL treatment ------130 4.2.3.1 Adequate clinical and parasitological response at days 14 and 28- - 130 4.2.3.2 Early treatment failure------130 4.2.3.3 Late clinical failure and late parasitological failure- - - - 130 4.2.3.4 Patients’ characteristics and therapeutic responses- - - - 131 4.2.3.5 Factors that contributed to low ACPR observed in this study- - - 131 4.3 Genetic variations in Pfmdr 1 alleles------132 4.3.1 Genotyping of Pfmdr 1 gene among study patients- - - - 134 4.3.2 Genotyping of group with treatment failure- - - - - 135 4.3.3 Genotyping of group that responded to AL treatment- - - - 136 4.3.4 The association between Pfmdr 1 point mutation and AL therapeutic efficacy------137 4.3.5 Co-mutation and AL therapeutic response- - - - - 137 4.3.6 The effect of AL on plasmodial gene pre and post treatment - - 138 4.4 Limitations of the study ------140 4.5 Conclusion------140 4.6 Further research------140 4.7 Contribution to knowledge ------141 References ------142 Appendix 1 Consent form ------166 Appendix 2 Ethical Clearance ------166 Appendix 3 Collaboration letter from Bishop Shanahan Hospital, Enugu-Ezike - 167 Appendix 4 Collaboration letter from Safety Molecular Pathology Laboratory, Enugu - 168 Appendix 5 Participants information sheet ------169 Appendix 6 Plan for protection of human life form - - - - - 173 Appendix 7 Patients’ data collection form ------174 Appendix 8 Patients’ compliance form ------175 Appendix 9 SMPL work sheet for routine test - - - - - 176 Appendix 10 SMPL work sheet for 96 well plate - - - - - 177 Appendix 11 SMPL work sheet for 48 well plate - - - - - 178

CHAPTER ONE

INTRODUCTION AND LITERATURE REVIEW

1.1 Background to the study Malaria is the world’s most wide spread parasitic infectious disease. According to the latest estimates, there were about 219 million cases of malaria in 2011 and an estimated 660 000 deaths (WHO, 2012). Between 2000 and 2010, malaria mortality rates fell by 26 % around the world. In the African Region the decrease was 33 %. During this period, an estimated 1.1 million malaria deaths were averted globally, primarily as a result of a scale-up of interventions (World Malaria Report, 2012). Malaria is prevalent in 106 countries of the tropical and semitropical world, with 35 countries in central Africa bearing the highest burden of cases and death (World Malaria Report, 2012). Nineteen countries in Africa; Nigeria inclusive, account for 90 % of all WHO estimated cases in 2006 (UK Aid, 2010). More than half of all estimated malaria cases occurred in Nigeria and India (Hay et al., 2010). Nigeria is known for high prevalence of malaria transmission with at least 50 % of the population suffering from malaria attack every year and accounts for 45 % of out-patient visits in most hospitals (Onwujekwu et al., 2000). In Nigeria, malaria imposes great burden in terms of pain and trauma suffered by its victims as well as loss in output and cost of treatment (Onwujekwu et al., 2004). Malaria also has a devastating economic and social effect as it perpetuates poverty. According to the Nigerian Government, “Malaria impedes human development and is both a cause and consequence of under development (Federal Ministry of Health, 2011). Every year, the nation loses over 132 billion Naira (over $1 billion) from cost of treatment and reduction in work force due to ill-health” (Federal Ministry of health, 2011)

Four species of the protozoan parasite Plasmodium: P. falciparum, P. vivax, P. ovale, and P. malariae cause the disease in human. They differ greatly with respect to their biological and clinical manifestations (Krogstad, 1999). P. falciparum and P. vivax cause the significant majority of the malaria infections with the P. falciparum causing the most severe form of the disease and highest mortality owing to its prevalence, virulence and drug resistance. Approximately 80 % of all P. falciparum malaria cases occur in sub-Saharan Africa, where most people become infected during childhood, and most of the morbidity and mortality are seen among children and young pregnant women (Guyatt et al., 2004, Roca-Feltrer et al., 2008). P.

2 falciparum has also become the predominant malaria species in many parts of the world outside of Africa (Guerra, 2006) and continues to be a major threat to travelers to tropical regions (Mayxay et al., 2004). The estimated global burden of P. vivax malaria is 100 – 300 million cases annually (Baird, 2008). The incidence of clinical P. malariae and P. ovale episodes are low, and when they occur, are relatively mild (Mueller et al., 2007). Recently, a plasmodial species; P. knowlesi has been identified in Southeast Asia (Cox-Singh et al., 2008, McCutchan, 2008, White, 2008) suggesting the advent of a new malaria species in humans.

Over the past years, the surge in malaria attack has arisen from a combination of insecticide resistant mosquito (Hemingway et al., 2000), global climate change, a number of economical and political factors (Stratton, 2008) and most importantly, drug resistant parasites (Wensdorfer et al., 1991). Widespread and increased resistance to antimalarials contributes enormously to the difficulties in controlling malaria, posing considerable intellectual, technical and humanitarian challenges. Chloroquine (CQ) and Sulfadoxine – pyrimethamine (SP) have been the first and second line drugs for treatment of uncomplicated malaria in Nigeria for two decades till evidence from local research showed that the therapeutic efficacy of these drugs are deteriorating due to high levels of P. falciparum resistance in all parts of the country (Ezedinachi et al., 1992, Falade et al., 1997, Ekanem et al., 2000). In response to resistance of Plasmodium falciparum to monotherapies like CQ and SP, Artemisinin Combination Therapies (ACTs) were recommended by the World Health Organization (WHO) as the first line treatment for falciparum malaria in all endemic regions (Nosten et al., 2007, White, 2008). ACTs are currently advocated in Africa as a means of improving treatment efficacy and slowing the spread of resistance. The rationale behind the choice of ACTs is to rapidly reduce the parasite burden with short acting artemisinin compound leaving a longer acting partner drug – lumefantrine- to eliminate the remaining parasite. Most countries in sub-Saharan Africa where malaria is endemic have now adopted either artemether-lumefantrine (AL) or artesunate-amodiaquine (AA) as their first line drug for treatment of uncomplicated malaria.

Recent genomic advances have paved way for discoveries into the origins and spread of antimalarial drug resistance and the underlying molecular mechanisms. Genetic approaches have also been designed to predict determinants of in vivo resistance to new antimalarials such as the artemisinins. Antimalarial drug resistance has been associated with specific point mutations in

3 several genes of the Plasmodium falciparum. An important gene, Plasmodium falciparum multidrug resistant gene1 (Pfmdr1) encoded by Pfmdr 1 on chromosome 5, which shows similarity to the P-glycoprotein product of the human multidrug resistance gene mdr is strongly associated with resistant to antimalarial drugs (Rohrbach et al., 2006, Duraisingh et al., 2005, Uhlemann, 2005, Thomsen et al., 2011). Transfection methodologies have defined the role of determinants such as Plasmodium falciparum chloroquine resistance transporter (Pfcrt), Pfmdr1 and Dihydrofolate reductase (dhfr) in antimalarial drug resistance.

1.2 Statement of problem In 2005, Nigerian National Antimalarial Treatment Policy (NNATP) adopted AL as the first line drug for treatment of uncomplicated malaria in Nigeria. Prior to the adoption of AL, the levels of therapeutic efficacy for CQ and SP ranged from 4 % - 77 % and 9 % - 94 % respectively in the South-South, Northeast and Southeast zones (Federal Republic of Nigeria, 2005), while that of AL and AA were 87 % - 100 % and 82.5 % - 100 % respectively (Federal Republic of Nigeria, 2005). Although, several studies (Yeka et al., 2008, Falade, 2005, Zurovac et al., 2008) have shown very good efficacy and effectiveness data confirming the usefulness of AL, it is not clear whether AL will be successful in preventing the selection of resistant parasites in Africa especially Nigeria, where Plasmodium falciparum transmission rate and risk of new infection soon after treatment are generally much higher than they are in South East Asia. This is evident by recent reports from Africa that showed some evidence of clinical and parasitological failure after treatment with AL (Yang et al., 2003; Huong, 2001; Jambou et al., 2005; Noedl et al., 2008).

Elucidating genetic variations that cause AL resistance is critical in the global surveillance of antimalarial resistance to ACTs. Studies have shown that genetic variations like single nucleotide polymorphism (SNPs)/point mutations and copy number variations (CNV) in some resistance associated genes like Pfmdr 1 alter the respective protein structural conformation in the Plasmodium, hence reducing drug binding or altering molecular transport system leading to parasite surviving the drug effect (Duraisingh et al., 2005, Uhlemann et al., 2005, Thompsen et al., 2011). SNPs or non-synonymous point mutations (NSPM) at various positions (N86Y, Y184F, S1034C, N1042D, and D1246Y) on the Pfmdr 1 gene have been shown to be associated with resistance to chloroquine, mefloquine, quinine, halofantrine, lumefantrine and artemisinins

(Dokomajilar et al., 2006; Sisowath et al., 2005; Humfrey et al., 2007). Importantly, amplification of Pfmdr 1 to copy-numbers of up to five appears to be a primary mechanism whereby parasites become resistant to these drugs (Price, 2004; Sidhu et al., 2006; Alker, 2007; Uhlemann et al., 2007; Rich 2009).

An important factor that has been identified to associate with treatment failure in malaria is wrong diagnosis of malaria. In a Tanzanian study of 4,474 severely ill patients at 10 hospitals, 54 % had a negative malaria slide (Reyburn et al., 2004). Two thirds of slide-negative patients were not treated with antimalarial, and a greater proportion of these patients died (12 %) compared with those with a positive slide (7 %) (Reyburn et al., 2006). Similarly, in Ghanaian and Nigerian studies, higher mortality was again observed among the slide-negative patients (Evans et al., 2004, Okubadejo et al., 2004). Significant over-diagnosis has also been reported among adults with a clinical diagnosis of cerebral malaria (Makani et al., 2003; Kumar, 2003).

The emergence of resistance to this novel drug AL, as a result of development of changes in genetic structure by the Plasmodium falciparum genes and a high rate of malarial wrong diagnosis constitute a major problem in the treatment of malaria in Nigeria; hence this research work was designed to address these problems.

1.3 Significance of study 1. This study is designed to provide health decision\policy makers, physicians and other health care givers with information on the reliable diagnostic methods most suitable in the area of study. 2. This study will bring to limelight the present AL therapeutic efficacy in adult patients and this information will inform the health care givers on therapeutic strategies to apply in order to achieve the desired goal in malarial treatment. 3. It would also suggest possible mutation patterns on different codons of the Pfmdr 1 gene that are associated with AL therapeutic failure, and thereby paving way for more insight to the mechanism of AL resistance by Plasmodium falciparum. 4. Data that will be generated from this study are key factors considered in the development of new effective therapies and molecular markers for systematic monitoring of resistance to AL and ACTs in general and inform appropriate use of ACTs in the interim

1.4 Justification of study This study has justified some studies carried out with the intentions of: 1. Assessing the cost-effectiveness of AL, artesunate amodiaquine and dihydroartemisinin- piperaquine in the treatment of uncomplicated malaria in a Nigerian hospital (Ukwe et al., 2010). 2. Evaluating the analytical reliability of blood film microscopy, rapid diagnostic test and polymerase chain reaction methods in malaria diagnosis in Enugu State, Nigeria. (Unpublished). 3. Ascertaining the selection of Plasmodium falciparum multidrug resistant gene 1 allele in asexual stages and gametocytes by artemether-lumefantrine in Nigerian children with uncomplicated falciparum malaria (Happi et al., 2009).

1.5 Literature review

1.5.1 Plasmodium falciparum malaria Malaria is a protozoan infection of red blood cells by the parasite of the genus Plasmodium. Studies have shown that five species of Plasmodium cause malaria infection in human. They are P. falciparum, P. vivax, P. malariae, P. ovale and P. Knowlesi (Guyatt et al., 2004; Roca-Feltrer et al., 2008; Cox-Singh et al., 2008). Plasmodium falciparum has it origin traced to Eukarya Domain of Chromalveolata kingdom in Apicomplexa phylum, class of Aconoidasida, order of Haemosporida, and family of Plasmodiidae. Plasmodium falciparum is a protozoan parasite, one of the species of Plasmodium that cause malaria in humans. It is transmitted by the female Anopheles mosquito. Malaria caused by this species is also called malignant (Rich et al., 2009; Perlmann, 2000) or falciparum (Perkins, 2011) malaria. It is the most dangerous form of malaria with the highest rates of complications and mortality. Almost every malarial death is caused by P. falciparum (World Malaria Report, 2008).

1.5.2 Lifecycle of Plasmodium falciparum The life cycle of the protozoan parasite involves two hosts: female mosquito exclusively of the genus Anopheles and humans. The life cycle of all Plasmodium species is complex. Infection in humans begins with the bite of an infected female Anopheles mosquito. Sporozoites released from the salivary glands of the mosquito enter the bloodstream during feeding, quickly invading

6 liver cells (hepatocytes). Sporozoites are cleared from the circulation within 30 minutes. During the next 14 days in the case of P. falciparum, the liver-stage parasites differentiate and undergo asexual multiplication, resulting in tens of thousands of merozoites which burst from the hepatocyte as shown in figure 1.1. Individual merozoites invade red blood cells (erythrocytes) and undergo an additional round of multiplication, producing 12-16 merozoites within a schizont (Baer et. al., 2007). The length of this erythrocytic stage of the parasite life cycle depends on the parasite species: irregular cycle for P. falciparum, 48 hours for P. vivax and P. ovale, and 72 hours for P. malariae. The clinical manifestations of malaria, fever and chills, are associated with the synchronous rupture of the infected erythrocytes. The released merozoites go on to invade additional erythrocytes. Not all of the merozoites divide into schizonts; some differentiate into sexual forms, male and female gametocytes. These gametocytes are taken up by a female Anopheles mosquito during a blood meal. Within the mosquito midgut, the male gametocyte undergoes a rapid nuclear division, producing eight flagellated microgametes which fertilize the female macrogamete. The resulting ookinete traverses the mosquito gut wall and encysts on the exterior of the gut wall as an oocyst. Soon, the oocyst ruptures, releasing hundreds of sporozoites into the mosquito body cavity, where they eventually migrate to the mosquito salivary glands as shown in figure 1.1.

Figure 1.1: Lifecycle of Plasmodium falciparum (Baer et. al., 2007) [Life cycle of P. falciparum showing the development of merozoites from sporozoites, erythrocyte invasion, sexual/asexual stage and gametocytogenesis]

1.5.3 Pathophysiology / Pathogenesis of Malaria All the manifestations of malarial illness are caused by the infection of the red blood cells by the asexual forms of the malaria parasite and the involvement of the red cells makes malaria a potentially multisystem disease, as every organ of the body is reached by the blood (Brian et al., 2008, Fakhreldin et al., 2003).

At the completion of the schizogony within the red cells, each cycle lasting 24-72 hours depending on the species of the infecting parasite, newly developed merozoites are released by the lysis of infected erythrocytes and along with them, numerous known and unknown waste substances, such as red cell membrane products, hemozoin pigment, and other toxic factors such as glycosylphosphatidylinositol (GPI) are also released into the blood. These products, particularly the GPI, activate macrophages and endothelial cells to secrete cytokines and inflammatory mediators such as tumor necrosis factor, interferon-γ, interleukin-1, IL-6, IL-8, macrophage colony-stimulating factor, and lymphotoxin, as well as superoxide and nitric oxide (NO). Many studies have implicated the GPI tail, common to several merozoite surface proteins such as MSP-1, MSP-2, and MSP-4, as a key parasite toxin(Claire et al., 2004, Srabasti et al., 2008).

The systemic manifestations of malaria such as headache, fever and rigors, nausea and vomiting, diarrhea, anorexia, tiredness, aching joints and muscles, thrombocytopenia, immunosuppression, coagulopathy, and central nervous system manifestations have been largely attributed to the various cytokines released in response to these parasite and red cell membrane products (Clark et al., 2006). In addition to these factors, the plasmodial DNA is also highly pro-inflammatory and can induce cytokinemia and fever. The plasmodial DNA is presented by hemozoin (produced during the parasite development within the red cell) to interact intracellularly with the Toll-like receptor-9, leading to the release of pro-inflammatory cytokines that in turn induce COX-2- upregulating prostaglandins leading to the induction of fever (Peggy et al., 2007, Ralf et al., 2007). Hemozoin has also been linked to the induction of apoptosis in developing erythroid cells in the bone marrow, thereby causing anemia (Lamikanra et al., 2009; Gordon et al., 2007).

Several pathophysiological factors such as the parasite biomass; 'malaria toxin(s)' and inflammatory response; cytoadherence, rosetting and sequestration; altered deformability and

9 fragility of parasitized erythrocytes; endothelial activation, dysfunction and injury; and altered thrombostasis have been found to be involved in the development of severe malaria. All these phenomena are more profound and wide spread in P. falciparum infection compared to non- falciparum infections. As a result, except for severe anemia, complications such as cerebral malaria, hypoglycemia, metabolic acidosis, renal failure, and respiratory distress are more commonly seen in P. falciparum infections (Louis et al., 2002; Qijun et al., 2000).

1). Parasite biomass With its wide array of receptor families and highly redundant, alternate invasion pathways, P. falciparum has the ability to invade RBCs of all ages, and with repeated cycles of development within the red cells, the parasite numbers exponentially grow into very high parasite burdens if the infection is uninhibited by treatment or host immunity. On the contrary, P. vivax preferentially infects only young RBCs, thus limiting its reproductive capacity and resultant parasite loads. Thus, the parasite load in P. falciparum infections can be very high, even exceeding 20-30 %, whereas in P vivax malaria it rarely exceeds 2 %, even in case of severe disease (Louis et al., 2002).

2). Cytoadherence, Sequestration and Rosetting Structural changes in the infected red cells and the resulting increase in their rigidity and adhesiveness are major contributors to the virulence for P. falciparum malaria. Owing to the increased adhesiveness, the red cells infected with late stages of P. falciparum (during the second half of the 48 hour life cycle) adhere to the capillary and post capillary venular endothelium in the deep microvasculature (cytoadherence). The infected red cells also adhere to the uninfected red cells, resulting in the formation of red cell rosettes (rosetting). Cytoadherence leads to sequestration of the parasites in various organs such as the heart, lung, brain, liver, kidney, intestines, adipose tissue, subcutaneous tissues, and placenta (Louis et al., 2002). Sequestration of the growing P. falciparum parasites in these deeper tissues provides them the microaerophilic venous environment that is better suited for their maturation and the adhesion to endothelium allows them to escape clearance by the spleen and to hide from the immune system (Louis et al., 2002). These factors help the falciparum parasites to undergo unbridled multiplication, thereby increasing the parasite load to very high numbers. Due to the sequestration of the growing parasites in the deeper vasculature, only the ring-stage trophozoites of P. falciparum are seen

10 circulating in the peripheral blood, while the more mature trophozoites and schizonts are bound in the deep microvasculature, hence seldom seen on peripheral blood examination. If the cytoadherence-rosetting-sequestration of infected and uninfected erythrocytes in the vital organs goes on uninhibited, it ultimately blocks blood flow, limits the local oxygen supply, hampers mitochondrial ATP synthesis, and stimulates cytokine production - all these factors contributing to the development of severe disease (Clark et al., 2006; Qijun et al., 2000).

3). Red cell membrane rigidity and deformability Altered red cell membrane rigidity and deformability also contribute to the pathogenesis of severe malaria. In patients with severe falciparum malaria, the entire red cell mass, comprising mostly of unparasitized red cells and also parasitized red cells, becomes rigid (Yong et al., 2008, Forradee et al., 2007). Several mechanisms such as hemin-induced oxidative damage of the red cell membrane, alterations in the phospholipids’ bilayer and attached spectrin network by the proteins transported to the red cell membrane, thermally driven membrane fluctuations due to fever, and inhibition of the Na+/K+ pump on the red cell membrane, possibly by nitric oxide (NO) may be responsible for the increase in rigidity and reduction in deformability of the red cells in falciparum malaria (Yong et al., 2008, Forradee et al., 2007). Reduced red cell deformability leads to increased splenic clearance and loss of red cells, causing anemia. Hemolysis, suppression of erythropoesis by cytokines, and hemozoin-induced apoptosis in developing erythroid cells also contribute to the development of anemia in severe malaria (Clark et al., 2006; Forradee et al., 2007). However, malaria if not diagnosed and treated quickly, there is progression from uncomplicated malaria to complicated or severe malaria.

1.5.4 Complications of malaria Uncomplicated malaria when not treated, progresses to catalogue of complications which have their cumulative effect as death. Most common complications of malarial infection include: intravascular hemolysis, hemoglobinuria, jaundice, hepatic dysfunction, hypoglycemia, anemia, renal failure, pulmonary oedema and cerebral malaria.

1.5.4.1 Intravascular hemolysis This can be due to non-immune destruction of parasitized red cells in case of high parasitemia or due to immune mediated destruction of parasitized as well as non-parasitized red cells. The changes in the red cell antigen structure brought about by the parasitic invasion stimulate the production of antibodies against the red cell. This triggers the immune mediated red cell lysis. Sensitivity to quinine may play a role in some patients who have been treated with quinine earlier, but now it seems to be rare. Patients with deficiency of glucose 6-phosphate dehydrogenase enzyme may develop hemolysis when treated with oxidant drugs like primaquine. Hemolysis can occur so rapidly that the hemoglobin may drop significantly within a few hours and it may recur periodically at intervals of hours or days (Bruneel et al., 2001). Patient presents with head ache, nausea, vomiting and severe pain in the loins and prostration. Fever up to 39.4 0C with a rigor is also seen. Urine is dark red to almost black. Patient may have tender hepatosplenomegaly. The urine becomes darker and the output slowly drops. Renal failure and peripheral circulatory failure are the usual causes of death in these patients.

1.5.4.2 Hemoglobinuria Hemoglobinuria in P. falciparum malaria is due to massive intravascular hemolysis. It is usually seen in non-immune or semi-immune individuals. Immune individuals who have lost their immunity due to stay in a non-malarious area may also develop the complication if they happen to get malaria on their return to malarious area. It results from increased release of hemoglobin into the circulation which leads to the urine appearing dark brown or black ('Black water fever') (Delacollette et al., 1995). Due to hemoglobinuria, the hemoglobin estimation may be unreliable. Similarly the parasite count may not represent the actual parasite load. There is methemoglobinuria and heavy albuminuria. Renal function gets affected and the urea and creatinine levels rise. There is increase in the levels of unconjugated and conjugated bilirubin as well. Hepatic failure can occur in severely ill patients and is of grave prognosis. Treatment is directed towards anemia and renal failure.

1.5.4.3 Jaundice This is common in malaria caused by P. falciparum. Most often it is caused by hemolysis and accordingly there is elevation of unconjugated bilirubin levels. Hemolysis can also elevate levels of aspartate aminotransferase and serum glutamic oxaloacetic transaminase (SGOT). These findings alone therefore do not imply severe hepatic dysfunction in malaria. The mild elevation in serum bilirubin level usually returns to normal within 3-5 days of effective antimalarial treatment. It does not warrant any special dietary restrictions nor does it require any treatment by 'traditional methods'.

1.5.4.4 Hepatic dysfunction Hepatic dysfunction may also be seen in cases of severe P. falciparum malaria. Such patients have conjugated hyperbilirubinemia, marked elevations of aspartate aminotransferase and alanine aminotransferase and prolongation of prothrombin time (Shahnaz et al., 2009). Massive hemolysis disseminated intravascular coagulation and hepatic dysfunction may all contribute to this picture. A term 'malarial hepatitis' has been used to describe this entity but is not well accepted. Clinical signs of liver failure are never due to malaria and in such cases, other associated hepatic diseases, like viral hepatitis, should be considered. Serum bilirubin and serum transaminases should be done in all cases of falciparum malaria who have icterus and pallor and who are sick and require admission. Prothrombin time and serum protein estimation may be needed also. In most patients, the bilirubin and enzyme levels return to normal within days of antimalarial treatment. No other specific treatment is needed.

1.5.4.5 Hypoglycemia This is one of the tricky complications of P. falciparum malaria and may often go unnoticed, adding to the morbidity and mortality. Hypoglycemia in malaria may be asymptomatic. On the other hand, most of the clinical manifestations of hypoglycemia are caused by malaria itself or by some of its other complications. Therefore, hypoglycemia, which is easily treatable, may be missed. Added to this, hypoglycemia can occur repeatedly and hence continuous monitoring of blood glucose levels is needed. It can be caused by decreased consumption of glucose by the host and the growing parasites, failure of hepatic gluconeogenesis and glycogenolysis as a result of impaired liver function and acidemia and hyperinsulinemia and stimulation of pancreatic insulin secretion by drugs like quinine (Miller et al., 2013). More than one of these factors may be at play in a given patient.

It occurs commonly in the following three situations: Severe falciparum infection, especially in young children, Pregnancy with falciparum malaria and treatment with quinine (or quinidine), as a result of drug induced hyperinsulinemia.

1.5.4.6 Anemia Anemia is a common manifestation of all types of malaria. It is more common and poses more problems in pregnancy and children. Anemia in malaria is multifactorial. The causes include obligatory destruction of red cells at merogony, accelerated destruction of non-parasitized red cells (major contributor in anemia of severe malaria), bone marrow dysfunction that can persist for weeks, shortened red cell survival and increased splenic clearance (Qijun et al., 2000). Massive gastrointestinal haemorrhage can also contribute to the anemia of malaria. Patients with anemia can present with tiredness, prostration, and breathlessness or even severe left ventricular failure and pulmonary oedema. In pregnancy, anemia can cause premature labour, still birth and high perinatal and maternal mortality. Anemia and fever tend to increase the cardiac output and this combination can prove fatal for patients with pre-existing cardiac disease.

1.5.4.7 Renal failure This is a sensitive prognostic indicator in severe P. falciparum malaria. Renal failure is more common in adults and rarely, if ever, seen in children. Usually there is a reversible dysfunction, which may progress to acute tubular necrosis and acute renal failure. It carries a high mortality. Renal dysfunction in P. falciparum malaria can be due to many factors: Renal failure in malaria is caused by renal cortical vasoconstriction and resultant hypo-perfusion, sequestration and resultant acute tubular necrosis due to micro vascular obstruction and due to massive intravascular hemolysis in black water fever (Gobbi et al., 2005). Renal failure in malaria usually manifests as oliguria with urine output less than 400 ml in 24 hours. However in very few cases it may be non-oliguric or polyuric.

1.5.4.8 Pulmonary Oedema Pulmonary Oedema occurs as malaria complication, resulting from fluid over load from treatment of oliguria from renal impairment.

1.5.4.9 Cerebral malaria Cerebral malaria is one of a number of clinical syndromes associated with infection by human malaria parasites of the genus Plasmodium. The etiology of cerebral malaria derives from sequestration of parasitized red cells in brain microvasculature and is thought to be enhanced by the pro-inflammatory status of the host and virulence characteristics of the infecting parasite variant. When Plasmodium falciparum merozoites invade red blood cells they remodel the host cell extensively through changes to the cytoskeleton and insertion of parasite-derived proteins into and onto the erythrocyte membrane (Maier et al., 2009). One such protein, thought to be a major virulence factor in Plasmodium falciparum, is the major variant surface antigen Plasmodium falciparum erythrocyte membrane protein (PfEMP1). Owing to its expression on the surface of the infected erythrocyte (IE), this protein must undergo antigenic variation to escape host defense mechanisms and a complex mechanism (i.e., antigenic variation) exists to support this (Dzikowski et al., 2009). This presentation of variant PfEMP1 proteins to the host results in differences in the host immune responses they provoke and in the repertoire of host receptors that erythrocytes infected with different variants can bind to each other (as well as the affinity of this binding) (Rowe et al., 2009)This leads to obstruction of the microcirculation and

15 results in dysfunction of multiple organs, typically the brain which results in cerebral malaria (Dondorp, 2004).

The malaria complications and their resultant effect to death are shown in figure 1.2

Figure 1. 2: The pathophysiology of P. falciparum infection. (Hall, 1977)

[Pathophysiology of malaria showing the progression of malaria infection starting from erythrocyte invasion with its consequent complications and eventual death]

1.5.5 The prevalence of malaria in Nigeria The term ‘prevalence’ of malaria usually refers to the estimated population of people who are managing malaria at any given time. The term 'incidence' of malaria refers to the annual diagnosis rate, or the number of new cases of malaria diagnosed each year. It is estimated that each year, 300 to 500 million people develop malaria and 1.5 to 3 million, mostly children die world wide, according to the World Health Organization (WHO 2008).

Incidence of malaria varies by weather, which affects the ability of the main carrier of malaria parasites, Anophelex mosquitoes, to survive or otherwise. Tropical areas including Nigeria have the best combination of adequate rainfall, temperature and humidity allowing for breeding and survival of Anophelex mosquitoes (National Malaria Control Plan of Action, 2001). Country- specific evidence shows that Nigeria has the largest population at risk of malaria in Africa. The disease, malaria, is a major health problem in the country, with stable transmission throughout the country. It accounts for about 50 percent of out-patient consultation, 15 per cent of hospital admission, and also prime among the top three causes of death in the country (National Malaria Control Plan of Action, 2001). Approximately 50 % of the Nigerian population experience at least one episode per year. However, official estimate suggests as much as four bouts per person per year on the average (WHO, 2002). The magnitude of prevalence and death due to malaria is a multiple of all other tropical diseases put together. It is responsible for over 90 % of reported cases of tropical disease in Nigeria (Alaba, 2005; Olumuyiwa, 2003). The above suggests that malaria could be the largest contributor to total disease burden and productivity losses resulting from major tropical diseases in the country. Evidence on Nigeria given by the 2005 malaria report shows that malaria incidence throughout the country had been on the increase over the years ranging between 1.12 million at the beginning of 1990 and 2.25 million by the turn of the millennium 2000 and 2.61 million in 2003 (WHO, 2005).

The disease carries with it two categories of costs; morbidity and mortality costs. Malaria morbidity affects households’ welfare (through families’ allocation to treatment and prevention of the disease), and decline in productivity, through lost time. In the case of mortality, losses to households include loss of future income and cumulative investment on the dead due to malaria. More importantly, it is a social and economic problem, which consumes about US$3.5 million in

18 government funding and US$2.3 million from other stakeholders in various control attempts in 2003 (WHO, 2005)

1.5.6 Epidemiology of malaria The epidemiology of malaria is a complex outcome of variable disease transmission patterns that mainly depend on intricate relationship between the 4 epidemiological factors: Human/host factor, parasite factor, vectorial factor and environmental factor However, the transmission pattern of malaria may vary from locality to locality and even within a city.

1.5.6.1 Human factors Human factors that affect the transmission of malaria are: 1. Genetic factor 2. Behavioural factor 3. Nutritional factor 4. Immune factor

1. Genetic factor (a) Sickle cell In the merozoite stage of its life cycle, the malaria parasite lives inside red blood cells, and its metabolism changes the internal chemistry of the red blood cell. Infected cells normally survive until the parasite reproduces, but if the red cell contain a mixture of sickle and normal haemoglobin, it is likely to become deformed and be destroyed before the daughter parasite emerge (Hebbel et al., 2003). Thus, individuals heterozygous for the mutated allele, known as sickle-cell trait, may have a low level of anaemia and a greatly reduced chance of serious malaria infection (Williams et al., 2005). This is a classic example of heterozygote advantage.

(b) Thalassaemias Some mutations found in the human genome associated with malaria are those involved in causing blood disorder known as Thalassaemias. It has long been known that a kind of anemia, termed thalassaemia, has a high frequency in some Mediterranean populations, including Greeks and Southern Italians (Ingram et al., 1959). The name is derived from the Greek words for sea

(thalassa), meaning the Mediterranean Sea, and blood (haima). In the common Mediterranean variant, mutations decrease production of the β-chain (β thalassaemia). In α-thalassaemia, which is relatively frequent in Africa and several other countries, production of the α-chain of Hb is impaired, and there is relative over-production of the β-chain. Individuals homozygous for β- thalassaemia have severe anemia and the parasite are unlikely to survive and reproduce, so selection against the gene is strong. Those homozygous for α thalassaemia also suffer from anemia and there is some degree of selection against the gene. There is evidence that the persons with α-thalassaemia and β thalassaemia have some degree of protection against the parasite.

(c) Duffy Antigens These are antigens expressed on red blood cells. P. vivax malaria uses the Duffy antigen to enter blood cells (Ménard et al., 2010). The malaria parasite Plasmodium vivax is estimated to infect 75 million people annually. P. vivax has a wide distribution in tropical countries, but is absent or rare in a large region in West and Central Africa, as recently confirmed by PCR species typing. This gap in distribution has been attributed to the lack of expression of the Duffy antigen receptor for chemokines (DARC) on the red cells of many sub-Saharan Africans. Duffy negative individuals are homozygous for a DARC allele, carrying a single nucleotide mutation (DARC 46 T → C), which impairs promoter activity by disrupting a binding site for the hGATA1 erythroid lineage transcription factor. Miller et al., 2013 reported that the Duffy blood group is the receptor for P. vivax and that the absence of the Duffy blood group on red cells is the resistance factor to P. vivax in persons of African descent. This genotype confers complete resistance to P. vivax infection. The genotype is rare in European, Asian and American populations but is found in West and Central Africa (Van Geertruyden 2004).

(d) Glucose-6-phosphate dehydrogenase

Glucose-6-phosphate dehydrogenase (G6PD) is an important enzyme in red cells, metabolizing glucose through the pentose phosphate pathway and maintaining a reducing environment. G6PD is present in all human cells but is particularly important to red blood cells. Since mature red blood cells lack nuclei and cytoplasmic RNA, they cannot synthesize new enzyme molecules to replace genetically abnormal or ageing ones. All proteins, including enzymes, have to last for the entire lifetime of the red blood cell, which is normally 120 days. When Malaria in G6PD- deficient subjects was analyzed, in both cases parasite counts were significantly lower in G6PD

20 deficient persons than in those with normal red cell enzymes (Beutler, 2008). However a genetic deficiency in this enzyme results in increased protection against severe malaria

(e) South-East Asian ovalocytosis Ovalocytosis is an inherited condition in which erythrocytes have an oval instead of a round shape. In most populations ovalocytosis is rare, but South-East Asian ovalocytosis (SAO) occurs in as many as 15 % of the indigenous people of Malaysia and of Papua New Guinea (Allen, 2008). Several abnormalities of SAO erythrocytes have been reported, including increased red cell rigidity and reduced expression of some red cell antigens (Liu et al., 1995). SAO is caused by a mutation in the gene encoding the erythrocyte band 3 protein. There is a deletion of codons 400-408 in the gene, leading to a deletion of 9 amino-acids at the boundary between the cytoplasmic and transmembrane domains of band 3 protein.

SAO is associated with protection against cerebral malaria in children because it reduces sequestration of erythrocytes parasitized by P. falciparum in the brain microvasculature. Adhesion of P. falciparum-infected red blood cells to cluster of differentiation 36 (CD36) is enhanced by the cerebral malaria-protective SAO trait. Higher efficiency of sequestration via CD36 in SAO individuals could determine a different organ distribution of sequestered infected red blood cells. These provide a possible explanation for the selective advantage conferred by SAO against cerebral malaria.

(f) HLA and Interleukin - 4 Human leukocyte antigen (HLA) HLA-B53 and HLA-DRBI 1302 are associated with low risk of severe malaria though this is limited to specific population (Van Geertruyden et al., 2004, Hill, 1996).

2. Behavioural factor Human behaviour has immense effect on the transmission and epidemiology of malaria. The three important aspects that directly influence malaria transmission are (Lucas 2003): a) Sleeping behaviour with regard to infant, children and adult has direct bearing upon the man-vector contact.

b) Occupational aspect – working time and place are intimately related to malaria transmission. c) Population migration: Migration of labour forces from areas of high endemicity to areas of low endemicity can result in the spread of malaria. Other factors are subsistence agriculture, wood gathering and rapid urbanization.

3. Nutritional factor It has been observed that malaria and malnutrition frequently coexist. Drug absorption maybe reduced owing to diarrhoea and vomiting, rapid gut transit and atrophy of the bowel mucosa. Absorption from intramuscular mass and possibly intra-rectal drugs may be slower and diminished muscle mass may make it difficult to administer repeated intramuscular injections. Hypo-albuminaemia, resulting from decreased synthesis as dietary deficiency occurs, could lead to an increase in the concentration of unbound drug. This may increase metabolic clearance, but hepatic dysfunction may reduce the metabolism of some drugs. Severe malnutrition (Kwashiorkor) may be antagonistic to malaria. In contrast, mild to moderate malnutrition is a risk factor for severe malaria. This paradox could be explained by postulating that in severe malnutrition a specific nutrient crucial to parasite growth is absent (Lucas, 2003).

4. Immune factor Urban population generally may be non-immune or may have low grade immunity to malaria parasite and therefore all age groups show high parasitaemia in peripheral blood. A symptomatic parasite carrier is not usually seen in these areas. Infants born by immune mothers in areas of stable malaria are partially protected from clinical malaria for 4-6 months due to a combination of passive immunity via maternal antibodies and high level of haemoglobin F as well as haemoglobin A, which does not sustain parasite growth. In areas of unstable malaria, antigenic stimulation is neither strong nor consistent enough for the development of a substantial immunity

1.5.6.2 Parasite factor In the parasite the environmental factors like temperature, and relative humidity, on the susceptibility of the vector to infection and mosquito’s physiological properties affect the metabolism and survival of the parasite. The time from infection to appearance of parasitaemia is short in P. falciparum 6-25 days, and longest in P. malariae. Duration of infection is one year for P. falciparum, five years for P. vivax and P. ovale, and fifty years for P. malariae, after

22 acquiring the original infection. P. vivax and P. ovale relapse because of the presence of intra- hepatic parasite with retarded development. P. falciparum and P. malariae only recrudesce if parasitological cure has not been achieved.

1.5.6.3 Vector factor Only female mosquitoes feed on blood, thus males do not transmit the disease. The female of the Anopheles genus of mosquito prefer to feed at night. They usually start searching for a meal at dusk, and will continue throughout the night. The important mosquito (vector) factors that aid the transmission of malaria include: a) Adequate vector density b) Adequate vector longevity to complete sporogony c) Degree of man – vector contact d) Susceptibility of vector to malaria infection. High vector density is required for effective transmission.

1.5.6.4 Environmental factor Environmental factors that influence malaria transmission are • Environmental temperature: P. falciparum requires a minimum temperature of 20 oC to develop in a female mosquito, while the other species of human malaria parasite can develop in temperature as low as 16 oC. • Environmental humidity: A relatively high humidity is required for survival of adult vectors. • Rainfall is essential to provide breeding site. • Sunlight • Permanent/temporary breeding places • Soil condition • Physico-chemical condition of breeding places • Vegetation : Bushy environs encourage breeding of mosquito • Availability of hosts.

1.5.7 Malaria transmission The transmission of P. falciparum in a certain region depends on many factors, such as the natural environment, vector and parasite population and behavioral and social situation of man.

1.5.7.1 Natural factors. These factors limit the area of transmission of malaria: it is restricted to the habitat of Anopheles species that is located at altitudes below 2200-2500 meter over sea-level and at places where open water pools provide breeding sites. At temperatures below 17 ˚C, the life cycle of the parasite will not be completed in the mosquito and will therefore terminate malaria cycle. These factors limit the area of transmission to 91 countries where 2460 million people or about 40 % of the total world population live (WHO, 1997).

1.5.7.2 Man-made factors These include environmental, social, economic and demographic factors. Their influences are felt in two ways; • they influence the density of the vector (e.g. additional man-made breeding sites) • Availability of the host (e.g. migration behavior, urban setting or the amount of money which can be spending for preventive measures like mosquito nets).

1.5.7.3 Exposure The level of exposure is regarded as the key factor shaping the presentation of malaria in the human host. The degree of exposure shapes the pattern of host morbidity and host immunity. This pattern can be used to describe area as holoendemic or hypoendemic as shown in Table 1.1. Exposure can be characterized by the yearly entomological inoculation rate (EIR) and the basic case reproduction rate (BCRR). Whereas the EIR is determined also by host availability, the BCRR is determined by the mosquito only (population density, feeding behavior, longevity, duration of sporogony). The BCRR gives a good estimate for transmission stability in malaria area, and subsequently for endemicity, describing the average number of secondary cases to which a malaria case will give rise after one passage through one mosquito.

A moderate EIR often results in parasite prevalences and densities, which undergo significant changes throughout one year. These changes are often due to the availability of surface water and humidity, resulting in the lowest vector density at the end of the dry season. Under these

24 circumstances, malaria transmission is seasonal but stable. A high EIR is often correlated with a year round stable malaria transmission. Under such conditions, the prevalence of falciparum malaria infection and the respective parasite density peak during early infancy at the individual level.

Table 1:1 Degree of exposure and pattern of host morbidity

Level Prevalence Holo-endemic Parasite rate in the one year age group constantly over 75 %, spleen rate in adults high (New Guinea type) or low (African type), parasite density declining rapidly between 2-5 years of live and then slowly

Hyper-endemic Parasite rate in children of 2-9 years constantly over 50 %

Meso-endemic Parasite rate in children of 2-9 years as a rule 11-50 % (may be higher during part of the year).

Hypo-endemic Parasite rate in children of 2-9 years as a rule less than 10 % (may be higher during part of the year).

Adapted from Molineaux, 1988 [A table showing classification of malaria transmission pattern as holo-endemic, hyper-endemic, meso- endemic and hypo-endemic with their respective parasite prevalence]

1.5.8 Malaria infection The symptoms of all human malaria infections are manifold and may include distinct attacks of fever often associated with headache, myalgia, malaise, chills, sweating, nausea and vomiting. If present the attacks of fever are correlated with the asexual intra-erythrocytic life cycle of the parasite. Fever occurs at the time of rupture of infected red blood cell (iRBC) (approximately every 48 h in P. falciparum malaria) leading to the classical sequence: cold stage, then hot stage then sweating stage. Rigors are common and splenomegaly is always a consequence. In areas where infection with P. falciparum constantly occur (holoendemic), it appears that only a small proportion of the infected people fall ill. Therefore it will be useful to differentiate between malaria as an infection and malaria as disease: the proportion of P. falciparum infection developing from asymptomatic to uncomplicated symptomatic to severe and finally fatal disease for children under 5years is illustrated in figure 1.5. In semi-immune adults, the ratio of asymptomatically: symptomatically infected would rather be 10:20 than 2. The clinical outcome of an infection (i.e. a first infection without considering the influence of the history of previous P. falciparum infections) in an individual person may depend on a wide range of factors, arising from the parasite, the host and the environment.

The progression of malaria infection to mortality is caused by different factors such as; Factors arising from the parasite which include virulence factors like growth and multiplication rate, genetic variations (like mutation, single nucleotide polymorphism and copy number variation), expression of cyto-adherent phenotype, toxin production, immune evasion ability and more important, drug resistance.

Factors arising from the host can be dependent on the ‘genotype’ which codes for red cell polymorphism, G6PD, and polymorphism in endothelial receptors like the Kilifi-mutant of Intercellular Adhesion Molecule 1 (ICAM-1), or can be dependent on the actual ‘phenotype’, as defined by acute hormonal disposition (pregnancy), by the nutritional status (e.g. iron supplementation), by concomitant disease, and finally by the presence of another simultaneous P. falciparum infections appear to be protective against clinical malaria in young children.

Factors arising from the environment could be related to the level of knowledge about malaria and its prevention (bed nets) or availability of health care in the community.

All these factors might influence the outcome of malaria but no correlation between any of these factors and the severity of disease could be established.

1.5.9 Diagnosis of malaria Malaria particularly, pernicious malaria (P. falciparum malaria), poses a diagnostic dilemma at early stage as the disease can mimic many other conditions (Warrell, 1990). Malaria must be recognized promptly in order to treat the patient on time and to prevent further spread of infection in the society. In diagnosing a malaria patient, some factors pose problem in accurate diagnosis and malaria management. They include: v Wrong diagnosis due to technical reasons like inadequate smear, faulty microscope, faulty staining and inadequate technical hand. v Malaria may be missed clinically in the presence of epidemics of dengue, meningitis, viral hepatitis, heat hyperpyrexia, and alcohol liver disease (National Malaria Eradication Program, 1998). v Where malaria is not endemic any more (such as United States) clinicians consulting a malaria patient may forget to consider malaria among the potential diagnosis. v In some areas where malaria is endemic, (such as Africa) a large proportion of the population is infected but not made ill by the parasites. Such carriers have developed enough immunity to protect them from malaria illness but not from malaria infection. In that situation, the presence of parasitemia in an ill person does not imply that the illness is as a result of the parasite. v In malaria endemic countries lack of resource is a major setback to reliable and timely diagnosis. Diagnosis of malaria can be clinical, parasitological, immunological and molecular.

1.5.9.1 Clinical (Presumptive) diagnosis This type of diagnosis is based on the first symptoms of malaria (most often fever, chills, headache, muscle pain, nausea and vomiting. Although reliable diagnosis of malaria cannot be made on the basis of signs and symptoms alone because of the non-specific nature of clinical malaria, clinical diagnosis of malaria is common in areas where malaria is endemic. Clinical diagnosis offers the advantages of ease and low cost. In area where malaria is prevalent, clinical

28 diagnosis usually results to all patients with fever and no apparent other cause to be treated for malaria. This method can identify most patients who truly need antimalarial treatment, but it is also likely to wrongly diagnose many who do not have malaria (Olivar, 1991). Wrong diagnosis contributes to misuse of antimalarial drugs. Considerable overlap exists between the sign and symptoms of malaria and other prevalent disease, especially acute lower respiratory tract infection (ALRTI), and this greatly increases the frequency of wrong diagnosis and wrong treatment (Redd, 1992)

1.5.9.2 Parasitological diagnosis A preferred and reliable diagnosis of malaria is microscopic examination of blood film because each of the four major parasite species has distinguishing characteristics. Two types of blood film are traditionally used – thick and thin film. Thin films are similar to usual blood films and allow species identification because the parasite’s appearance is best preserved in this preparation. Thick films allow the microscopes to screen a larger volume of blood and are about eleven times more sensitive than the thin film, so picking up low levels of infection is easier to pick up in the thick film, but the appearance of the parasite is much more distorted and therefore distinguishing between the different species can be much more difficult. With the pros and cons of both thick and thin smear taken into consideration, it is imperative to utilize both smears when making a definite diagnosis (Kwiatkowski, 2005).

However, microscopic diagnosis can be difficult because the early trophozoites (ring forms) of all four species look identical and it is never possible to diagnose species on the basis of a single ring form; species identification is based on several trophozoites.

1.5.9.3 Immunological (Antigen detection) diagnosis A third diagnostic approach involves the rapid detection of parasite antigen using rapid immunochromatographic techniques. This method is also known as rapid diagnostic test (RDT). Multiple experimental tests have been developed targeting a variety of parasite antigen (Fortier, 1987, Khusmith, 2002). It is of great importance in areas where microscopy is not available. It requires only a drop of blood (Carter et al., 2002). The commonest antigens currently targeted in malaria RDTs are histidine rich protein 2 (HRP-2), Plasmodium lactate dehydrogenase (PLDH) and Plasmodium aldolase. A number of commercially available kits (paracheck – PF®, Becton –

Dickson, malaquick®, first response®), are based on the detection of histidine rich protein II(HRP – II) while OPTIMAL® and flow Inc. Portland are based on detection of a specific plasmodium enzyme lactate dehydrogenase (pLDH).

Advantages of this technology are that: a. No special equipment is required. b. Minimal training is needed. c. The test and reagents are stable at ambient temperatures and d. No electricity needed The principal disadvantages are a currently high per-test cost and an inability to quantify the density of infection. Furthermore for test based on HRP-II detection antigen can persist for days after adequate treatment and cure therefore, the test cannot adequate distinguish a resolving infection from treatment failure due to drug resistance especially early after treatment. (WHO, 1996)

1.5.9.4 Molecular diagnosis A most recent method of diagnosis is by detection of parasite genetic material through polymerase chain reaction (PCR) technique. PCR technique is a sensitive technique of molecular genetics in which the DNA of a single cell, treated with polymerase enzyme is induced to replicate many times. One important use of this new technology is in detecting mixed infections or differentiating between infecting species when microscopic examination is inconclusive (Beck, 1994). In addition, improved PCR techniques could prove useful for conducting molecular epidemiological investigations of malaria clusters or epidemics (Freeman, 1998). However, the technique is not without shortcomings which include: a. Overall high cost b. High degree of training required c. Need for special equipment and d. Absolute requirement for electricity

1.5.10 Goals of antimalarial treatment In accordance with the millennium development goals (MDGs) and Abuja Declaration on Roll Back Malaria (RBM) in Africa, the goals contained in the outcome document of the United

Nation Special Session on Children: “A world fit for children and updated targets contained in the Roll Back Malaria strategic plan 2005 -2015, United Nation International Children Emergency Fund (UNICEF) aims at ensuring that:

By 2010, Particularly in the lowest two economic quintiles: v 80 % of people at risk of malaria are protected, thanks to locally appropriate vector control method such as insecticide treated nets (ITNs), and where appropriate, indoor residual spraying (IRS) and biological measures; v 80 % of malaria patients are diagnosed and treated with effective antimalarial medicines, e.g. artemisinin based combination therapy (ACTs) within one day of the onset of illness; in areas where transmission is stable 80 % of pregnant women receive intermittent preventive treatment (IPT); malaria burden is reduced by 50 % compared to 2000 levels.

And by 2015: v Malaria morbidity and mortality are reduced by 75 % in comparison to 2005, not only by rational aggregate but particularly among the poorest groups across all affected countries; v Malaria – related MDGs are achieved, not only by national aggregate but also among the poorest groups, across all affected countries. v Universal and equitable coverage with effective interventions.

1.5.11 Treatment of malaria For effective malarial treatment, laboratory tests should be performed and diagnosis of malaria disease confirmed before treatment is commenced. However, in situations where clear suspicion of a very extreme case is determined and there is lack of facilities treatment is advised. Treatment is determined by three specifications (1) The species of infecting parasites. (a) P. falciparum causes severe and quickly progressing illness or death; while the other three species are rarely severe. (b) P. vivax and P ovale demand treatment for forms that remain dormant and can induce repeated infections.

(c) P. falciparum and P. vivax are known for different resistance level in different geographical areas where infections occur. For P. falciparum, rapid beginning of treatment is extremely necessary.

(2) The physical state of the infected person. (3) The resistance level of the parasite is determined by the place the person was when infected. (4) In addition other factors to consider are (a) Other ailments the patient has such as HIV (b) Pregnancy (c) Drug allergies and sensitivities. (d) Genetic factors that predispose one to malarial attack such as sickle cell trait and (e) Hemoglobin related disorders and other blood cell dyscrasias such as hemoglobin C, the

thalassaemia and G6PD deficiency.

1.5.11.1 Treatment of malaria in special groups (a) Children less than 3 months (<5kg) Malaria incidence amongst children less than 3 months (<5kg) is increasing. However, enough studies are not available to support the use of ACTs in this group. Quinine is recommended for the treatment of malaria in this group.

(b) Malaria in pregnancy During first or second trimester, protective immunity against malaria tends to diminish without disappearing completely. Together with changes in pharmacokinetics (apparent increases in the volume of distribution with a resulting reduction in plasma drug concentration), this fall in immunity is responsible for a higher treatment failure rate than in other women of the same age (White, 1998). Hence pregnant women are more prone to develop multiple complication of malaria (Mishra et al., 1998). Other factors that make pregnant women more vulnerable to malaria and its complications including mortality are: v Malaria parasites are preferentially sequestrated in the placenta. v Frequency of heavy parasitemia is more during pregnancy than in the non-pregnant state. The use of ACTs during the second and third trimester has not been associated with teratogenic or mutagenic effect. The safety of its use in the first trimester cannot be guaranteed.

1.5.11.2 Treatment of uncomplicated malaria Uncomplicated malaria is a general attack of malaria which usually continues for 6 -10 hours without any complication like organ damage. There are three phases to this and it usually returns every 2 to 3 days depending upon the type of parasite. (A) The cold phase (shivering, feeling cold) (B) The hot phase (vomiting, fever, headache convulsion in children) (C) The sweating phase (sweating with normal temperature, sleepiness). However, more frequently the patient usually has the following signs and symptoms: chills, fever, nausea and vomiting, headache, general discomfort (malaise) and body aches.

1. Chloroquine - CQ Chloroquine is a 4–amino-quinolone with rapid antipyretic and anti parasitic effects. It is inexpensive and is gametocytocidal. Its main symptomatic adverse effect is pruritis, which is most pronounced in dark skinned people and may be because of the high affinity of chloroquine for melanocytes. In the eye this contributes to retinal toxicity which may be seen after long term high dose therapy. Adult dose is 1000mg (4 tablets) 1st dose, 500mg (2 tablets) for the 2nd, 3rd and 4th doses. 1st dose of chloroquine should always be larger to obtain sufficient blood levels, in view of large volume of distribution. Treatment with chloroquine is less effective in children aged <5 years who are co-infected by the virus (Kamya, 2001).

2. Amodiaquine - AQ AQ is a 4–amino-quinolone, with potent schizonticidal activity. It is active against erythrocytic stage of all the four species of Plasmodium even in areas of CQ resistance. Like other 4–aminoquinolones, amodiaquine acts by blocking the enzyme synthesis of DNA and RNA in both mammalian and protozoal cells, forming a complex with DNA that prevents replication or transcription to RNA. High drug concentrations are found in malaria parasite’s digestive vacuoles. It is now being used in combination with SP or artesunate in treatment of uncomplicated malaria in many countries. Adverse effects include gastrointestinal disorders, dizziness, insomnia, asthenia anorexia, headache and allergic reactions. There is concern that if it is used as a treatment with doses taken several times a year, serious adverse reactions may be seen, this concern arises because of the immunogenicity of the drug. Amodiaquine is taken 50mg twice daily for children 7-13 years and 100mg twice daily for adults.

3. Sulfadoxine – pyrimethamine (SP) The combination of two drugs Sulfadoxine and pyrimethamine is not combination therapy as the component drug act on the same target - parasite folate biosynthesis. SP has replaced CQ as a first line treatment for uncomplicated malaria in many countries. In Africa unfortunately, resistance has quickly developed, facilitated by its long half life. SP is inexpensive and is taken as a single dose. In Nigeria it is the drug of choice for intermittent preventive treatment (IPT) of malaria in pregnancy. In a study of intermittent preventive treatment, sulfadoxine-pyrimethamine had to be given in monthly doses for the first trimester of pregnancy to women co–infected with HIV but at only two doses to sero-negative women to achieve the same result (Praise, 1998).

4. Chlorproguanil- dapsone (CD) CD is an antifolate combination like SP. It is effective against SP resistant parasites in Africa. The dose is chlorproguanil 2 mg/kg and dapsone 2.5 mg/kg once daily, taken over 3days. Both drugs have short half lives so the selective pressure for resistance is less than for SP. CD is inexpensive and can be used as part of an ACT regimen with artesunate as “CDA” which is still under development. As with any new drug, CD (and CDA in due course) will need to be monitored closely now that it is widely used. Its disadvantage is that dapsone induces methaglobinaemia and hemolysis in patients with G6PD deficiency.

5. Mefloquine Mefloquine is a potent drug against P. falciparum resistance to 4–aminoquinolone and antifolate combinations. It is also active against P. ovale, P. vivax and P. malaria. It is costly and has frequent symptomatic side effects. It is recently used as part of ACTs.

6. Artemisinin (ART) Artemisinin (qinghaosu) is a sesquiterpene lactone endoperoxide. Artemisinin is insoluble, some analogs have been synthesized to increase solubility and improve antimalarial efficacy. The most important of these analogs are artesunate (water soluble), dihydroartemisinin and artemether (lipid soluble). These analogs come in combinations according to WHO’s guideline for treating uncomplicated malaria. Artemether comes in combination with lumefantrine, artesunate is co packed with amodiaquine, while dihydroartemisinin is formulated in combination with dihydro-

34 piperaquine as WAIPA(R). Two other newer analogs are arteether and artelinic acid. The artemisinin and its analogs are rapidly absorbed with plasma level occurring in 1-2 hours and half lives of 1-3 hours after oral administration. They are very rapidly acting blood schizonticides against all human malaria parasites. They have no effect on hepatic stage. The antimalarial activity of artemisinin probably results from the production of free radicals that follow the iron-catalyzed cleavage of the artemisinin endoperoxide. Commonly reported adverse effects include nausea vomiting and diarrhea.

7. Halofantrine / Lumefantrine Halofantrine hydrochloride, a phenanthrene-methanol related to quinine, is effective against all malaria species, but because of its high cost and serious cardiac side effect, it is often used in treatment of uncomplicated malaria. Lumefantrine is an aryl alcohol related to halofantrine, it is available in fixed dose combination with artemether as coartem(R), or lonart(R) in some countries. Lumefantrine is effective against erythrocytic (but not other) stages of all four human malaria species. The half life when used in combination is 4.5 hours. As with halofantrine oral absorption is highly variable and improved when taken with food (fatty food). Lumefantrine does not appear to cause the cardiac toxicity seen with halofantrine. The mechanism of action of halofantrine and lumefantrine is unclear.

8. Atovaquone-Proguanil (malarone(R)) Malarone provides effective treatment against multidrug resistant malaria and as a prophylaxis. It is very expensive and so is likely to be used only in richer countries. It is not a combination therapy, the drugs work synergistically. It has good safety and tolerability in children and adults. Its dose is atovaquone 20mg/kg and proguanil 8mg/kg once daily for 3 days.

9. Primaquine Primaquine is used clinically to clear the hypnozoites of P. ovale and P. vivax and to prevent relapse, and not as a therapy for uncomplicated malaria. Primaquine may cause acute intravascular hemolysis in patients with G6PD deficiency and is contraindicated in pregnancy and children under 4 years old.

10. Antibiotics A number of antibiotics in addition to the folate antagonist and sulfonamides are modestly antimalarial. The mechanisms of action of these drugs are unclear. None of the antibiotics should be used as single agent for the treatment of malaria because their action is much slower than that of a standard antimalarial. Tetracycline and doxycycline are active against erythrocytic schizonts of all human malaria parasites. They are not active against hepatic stage. Other antibiotics used are clindamycin which can be used in conjunction with quinine or quinidine in those for whom tetracycline and doxycycline are not recommended such as in children and pregnant women. Azithromycin is another alternative drug that is under study (Arrow et al., 2004).

1.5.11.3 Antimalarial drug combination therapy Due to spread of resistance to CQ and SP monotherapies, the use of artemisinin based combination therapies (ACT) is now highly advocated (Arrow et al., 2004, WHO, 2006). However, for an effective combination therapy, both partner drugs must be reasonably efficacious and must be deployed preferably prior to their use as monotherapies (Watkins et al., 2005). Indeed the high background of CQ and SP failure rates observed in various countries made these drugs unsuitable partner in ACT (Obonyo et al., 2003, Sirima et al., 20003, Gill et al., 2003). In 2001 the WHO issued a statement that has led to a major change in the treatment of malaria. WHO stated that “Malaria endemic countries which are experiencing resistance to currently used antimalarial monotherapies (chloroquine, amodiaquine) and SP, to change treatment policies to combination therapies, preferably the highly effective artemisinin based combination therapies - ACTs”

WHO’s definition of Antimalarial Combination Treatment. This is the simultaneous use of two or more blood shizonticidal drugs with independent modes of action and different biochemical targets in the parasite. However, antimalarial medicines with a drug that enhance its action (e.g. CQ plus chlorpheniramine) or use of a blood schizonticidal drug with a gametocytocidal drug (e.g. SP, chlorproguanil - dapsone, atovaquone - proguanil) are not regarded as antimalarial combination therapy.

Basis of combination therapy (multiple drug therapy) Concept is based on the synergistic or additive potentials of 2 or more drugs to: v Improve treatment efficacy, and v Retard the development of resistance to the individual components of the combination.

Recommended ACT for uncomplicated malaria: v Artemether-lumefantrine (AL) is the recommended ACT for treatment of uncomplicated malaria in Nigeria. In the rare case of a patient not responding to ACT oral quinine is recommended. Other ACTs available include: v Artesunate (4 mg/kg) + amodiaquine (10 mg/kg) daily for 3 days v Artesunate (4 mg/kg) for 3 days + Mefloquine (25 mg/kg on day 1, 15mg/kg on day 2, then10 mg/kg on day 3) v Dihydroartemisinin (300 mg/kg) + piperaquine (225 mg/kg) 4 tablets daily for 3 days, adult dose v Artesunate + SP (in areas where SP efficacy remains high) v Dihydroartemisinin(32 mg) + piperaquine (320 mg) + trimetoprim (90 mg)

Factors favoring artemisinin based combination therapy The choice of artemisinin derivatives is due to the fact that they produce the following effects: v Rapid and sustained reduction of the parasite biomass v Rapid resolution of clinical symptoms. v Reduction of gametocyte carriage. v Duration of treatment is 2-3 day in combination (As against 5-7 days in monotherapies) v Broad stage specificity. v An advantage of AL combination is that lumefantrine is not available as a monotherapy, and it has never been used by itself for the treatment of malaria

Limitations of ACT use v There may be potential for misuse of artemisinin derivatives in view of their value in the treatment of severe malaria.

v There may be problems of compliance with non co-formulated combinations, particularly at the house hold level. v Artemisinin derivatives cost higher v There is no evidence for ACT delaying resistance in areas of high transmission. v Effort and cost of changing current drug policy to ACTs are high.

Challenges with malaria treatment v Quality of many antimalarial drugs found in endemic countries are questionable v The efficacy of (affordable) traditional antimalarial drugs has been declining due to drug resistance v 60-90 % of the population seeks initial treatment from non-public sector, i.e. street vendors, kiosks where quality is uncontrolled. v Supply of drugs is often inefficient and unreliable. v Pharmacovigilance is very weak in most affected countries

1.5.11.4 Treatment of severe (complicated) P. falciparum malaria A patient is said to be suffering from severe malaria when there is presence of P. falciparum asexual parasitemia and one or more of the following clinical or laboratory symptoms: clinical manifestation, impaired consciousness, respiratory distress, multiple convulsion, circulatory collapse, jaundice, hemoglobinuria etc. Severe malaria is a medical emergency unlike uncomplicated malaria. In most cases there is a risk of organ damage in an affected patient. The main treatment objective is to prevent the patient from dying; secondary objectives are prevention of recrudescence, transmission or emergence of resistance and prevention of disabilities.

The recommended therapies are parenteral quinine, and parenteral or rectal artemisinin derivatives (artesunate, artemether and artemotil). Although there are a few areas where chloroquine is still effective, parenteral chloroquine is no longer recommended for the treatment of severe malaria because of wide spread resistance. Intramuscular SP is also not recommended. Artemisinin is formulated as suppository for rectal administration. Artemether and artemotil are formulated in oil and given by intramuscular injection they are both absorbed erratically, particularly in very severely ill patients. Artesunate is soluble in water and can be given either by

38 intravenous or intramuscular injection. There are also rectal formulations of artesunate, artemether and dihydroartemisinin. Artemisinin combination therapies are not recommended for treatment of severe malaria

Criteria for antimalarial treatment policy change The main determinant of antimalarial treatment policy is the therapeutic efficacy of the antimalarial medicines in use. Other important determinants include: changing patterns of malaria-associated morbidity and mortality; consumer and provider dissatisfaction with the current policy; and the availability of alternative medicines, strategies and approaches. Therapeutic efficacy monitoring involves the assessment of clinical and parasitological outcomes of treatment over at least 28 days following the start of adequate treatment to monitor for the reappearance of parasites in the blood. Reappearance of the same genotype indicates reduced parasite sensitivity to the treatment drug.

1.5.12 Emergence and spread of P. falciparum resistance It has been proposed that (i) there are a few origins of resistant alleles (ii) in vivo mutations are less important than migration for introducing resistance alleles into parasite population and (iii) selective sweep or gene flow is a primary mode of spread of resistance (Anderson et al., 2005). For a resistant allele to spread it must be found in parasite lineages that are committed to become gametocytes. Less than 1 % of asexual parasites are committed to become gametocytes. In addition, parasites expressing a predominant var gene are targeted for clearance by the immune system. Only mutations borne by proliferating parasites expressing newly switched var genes will escape clearance and achieve transmission. As a result, the “effective population” in terms of transmission and spread of resistant alleles is usually lower than the actual population of parasites infecting humans. Secondly, resistance involves multiple mutations occuring in the same allele during a single replication. This process presents sequential bottlenecks in the population of resistant alleles. It is hypothesized that the African parasites lack the genetic traits that would confer the ability to bear the dhfr 164 mutation (Nzila et al., 2005).

1.5.12.1 The factors influencing the rate of spread of P. falciparum resistance The factors influencing the rate of spread of antimalarial drug resistance, once it has emerged or been introduced in a given area, are still not well defined. However some factors that are known to play important role in the rate of spread of P. falciparum resistance include: 1. De novo mutation 2. Human population movement and infection among migrants. 3. Drug use and 4. Malaria transmission intensity

a) De novo mutation This is an alteration in a gene that is present for the first time in one family member as a result of a mutation in a germ cell (egg or sperm) of one of the parents or in the fertilized egg itself or new mutation which has occurred due to an error in the copying of genetic material or an error in cell division. This may result in a family member being the first member in a family to have a genetic condition as a result of a mutation in a gamete (egg or sperm) of one of the parents or in the fertilized egg itself or developing fetus. Theoretically, parasite resistance can emerge for any antimalarial drug, and the occurrence of de novo mutations and drug selection pressure (frequent drug use and long drug elimination half-life) are critical and essential prerequisites. Nevertheless, vector, parasite, and human host factors probably play an important role.

b) Human population movement and infection among migrants The quantification of parasite movements can provide valuable information for control strategy planning across all transmission intensities. Mobile parasite carrying individuals can instigate transmission in receptive areas, spread drug resistant strains and reduce the effectiveness of control strategies. The identification of mobile demographic groups, their routes of travel and how these movements connect differing transmission zones potentially enables limited resources for interventions to be efficiently targeted over space, time and populations.

c) Drug use More than any other issue, poverty and inadequate access to drugs continue to be major force in the development of resistance. In many developing nations drugs are freely available; but only to those who can afford them. This means that most patients are forced to resort to poor quality

40 counterfeit, or truncated treatment courses that invariably lead to more rapid selection of resistant organisms. Treatment with second and third-line drugs is costly, more often toxic to the patient, and increasingly ineffective owing to the speed with which mutant organisms develop resistance. At the other end of the spectrum, patient demand for antimalarial as a result of TV, internet, magazine or newspaper advertising. This in turn spurs the development of resistance.

d) Malaria transmission intensity Transmission intensity can influence the spread of drug resistance by affecting the frequency of drug use and the risk of selecting resistant parasites. It has been observed that community drug use was inversely related to intensity of transmission; a surprising finding considering that one would have expected a higher number of clinical/fever episodes in high rather than in low transmission areas. This can be explained by the acquisition of immunity and the dramatic reduction, after 10 years of age, of the risk for peripheral parasitaemia to result to a clinical attack.

e) Transmission intensity and intra-host competition In areas of high transmission, intrahost competition between co-infecting parasite clones (intrahost dynamics) is probably an important factor. The generalized immunity model of intrahost competition predicts that resistance could spread faster in areas of high transmission. If intrahost competition plays an important role, the mutant parasite sub-population with the ability to survive drug treatment replaces the susceptible ones and this process is boosted by the highly polyclonal infections found in areas of intense transmission. The intrahost competition hypothesis is indirectly supported by field data from Uganda, Zimbabwe, and Tanzania on CQ and SP resistance (clinical and molecular markers) because this was high where transmission was intense or where there were no malaria interventions that interrupt transmission (IRS or ITNs).

f) Malaria Transmission Intensity and Parasite Biomass The emergence of drug resistance is primarily dependent on the de novo emergence of mutations whose probability is a function of the parasite biomass. A large parasite biomass is more likely to occur in areas of low transmission because of the lower host immunity. This is the likely explanation for the origin and rapid rise of multi-drug resistance in Southeast Asia. However,

41 besides the observation that CQ and SP resistance seems to have originated at a few foci in areas of low transmission and spread through selective sweeps across the world, there is no other empirical evidence to support this theory. Parasite biomass is statistically attractive, but its measurement in field studies is difficult because of the multi-organ sequestration of parasites.

1.5.13 Malaria chemotherapy and assessment of antimalarial efficacy Correct diagnosis and prompt treatment with effective antimalarial drug is of paramount importance in determining the outcome of malaria treatment. In a situation where mosquito vector is insecticide resistant (Hemingway et al., 2000, Greenwood et al., 2008), and effective vaccine is not yet available (Greenwood et al., 2008, Girard et al., 2007), chemotherapy and chemoprophylaxis remain the principal means of combating malaria infection. Various drugs are used for management of malaria including antifolates (e.g. SP, proguanil, chlorproguanil and trimethoprim), quinolones (e.g. mefloquine, halofantrine, lumefantrine, amodiaquine, piperaquine, chloroquine, tafenoquine, quinine and quinidine), artemisinin (e.g. Dihydro- artemisinin, artemether, artesunate), atovaquone (falls into its own class with specific mode of action) and several antibacterial drugs (e.g. tetracycline clindamycin) also has weak antiplasmodial activities (Arrow et al., 2004).

Shortly after the first report of CQ resistance in 1965, standardized in vivo antimalarial drug efficacy testing systems were developed, used and updated in 1972. These protocols remained in use until 1996, when specific protocol for intense transmission areas was developed (WHO, 1996). In this protocol, in vivo treatment responses were assessed for 14 days and classified on the bases of either clearance of clinical signs or symptoms as adequate clinical response (ACR), early treatment failure (ETF) and late treatment failure (LTF). Experience gained showed that a 14 day follow up underestimates treatment failure rates. This led to the suggestion that post treatment follow up should be long enough to detect recrudescent infections emerging later after the initial parasite clearance. Hence the 1996 protocol was revised in 2002 incorporating in vitro parasite susceptibility testing and drug resistance molecular markers assessment protocols as supporting methods (WHO, 2002). This new protocol recommends that assessment of response should be done for 28 – 63 days depending on the half life of the drug under study. In addition, the protocol combines clinical and parasitological observations in assessing treatment responses. Therefore treatment outcomes are classified as adequate clinical and parasitological response

(ACPR), ETF, late clinical failure (LCF), and late parasitological failure. Thus it is redundant now to report clinical and parasitological responses separately (Ringwald, 2004).

However, longer follow up periods pose difficulties in interpreting drug efficacy outcomes, particularly in high transmission areas, because new infections occurring during follow up may be wrongly interpreted as treatment failures. Therefore the WHO 2002 protocol emphasizes that molecular genotyping must be used to distinguish between new and recrudescent infections. Distinction of recrudescence from new infection is done by genotyping the high polymorphic P. falciparum merozoites surface protein 1 and 2 (MSP 1 and 2) and P. falciparum glutaryl rich protein (glurp) genes using PCR coupled with restriction fragment length polymorphism (RFLP) and subsequent comparison on admission (day 0) and recurrent infection allelic profile (Snounou et al., 1998; Viriyakosol et al., 1995; Beck, 1999; Greenwood, 2002). Recently, analysis of immunologically neutral microsatellite markers has been suggested to complement MSP (Nyacielo et al., 2005), whereas fluorescent labeled PCR and sizing of fragment by gene scan was found to be more precise than PCR-RFLP (Falk et al., 2006)

In vitro efficacy tests and molecular genotyping of resistant markers (mutations in resistance conferring genes) are supplementary methods used in the assessment of P. falciparum resistance to antimalarial drugs. The former involves testing the susceptibility of parasite to drug in culture while the latter measures the SNPs at various positions in resistance-associated genes. If reliable evidence on their in-vivo resistance predictive value is established, the two methods may replace the former method which is labor and time intensive. In order to fully exploit markers of antimalarial drug resistance, we need a better understanding of how drugs work and how resistance comes about.

1.5.13.1 Antimalarial drug resistance situation in sub-Saharan Africa Drug resistance is defined as the ability of a parasite to survive and/or multiply despite the administration and absorption of drug given in doses equal to or higher than those usually recommended, but within the limits of tolerance of the subject (WHO, 1973). It should be noted that anti-malarial medicine resistance is not necessarily the same as malaria treatment failure, which is defined as the failure to clear malaria parasitemia and/or resolve clinical symptoms despite the administration of antimalarial medicines. While drug resistance may lead to treatment

43 failure, not all treatment failures are caused by drug resistance. Other causes of treatment failure are: incorrect dosing, problems of treatment compliance, poor drug quality, interaction with other drugs, compromised drug absorptions and wrong diagnosis of the patient.

Resistance to antimalarials is a major drawback in effective malaria control in sub-Saharan Africa. In this region, P. falciparum has developed resistance to cheap antimalarial such as CQ and SP. In the 1900s, efficacy data collected in Nigeria showed development of CQ resistance (Ezedinachi et al., 1992; Falade et al., 1997). Recent data in the 20th century have shown high level of CQ resistance in Nigeria, with failure rate of 39 % at day 14 (Ekanem et al., 2000, Sowunmi et al., 2005) which is above the critical value of total treatment failure of 25 % (Talisuna et al., 2004). Efficacy data collected in southern Africa (Tanzania, Kenya, Uganda, and Rwanda) showed high clinical failure rate to CQ (10 % - 71 %) (East African Network for Monitoring Antimalarial Treatment EANMAT 2003), with most of the regions being above the critical value. However SP and amodiaquine (AQ) both showed high ACR ranging from 71.8 % - 93 %. Thus around 2000 most southern African countries replaced CQ with either SP monotherapies, AQ+AS (artesunate) or non artemisinin combination therapies (non-ACTs) such as SP+AQ as the first line malaria treatment drug (East African Network for Monitoring Antimalarial Treatment [EANMAT], 2003). In contrary, within the same period CQ was efficacious in Western Africa (Nigeria, Mali, Senegal, Ghana, Ivory Coast and Gambia) (Evan et al., 2005, Happi et al., 2005). Only Nigeria and Ghana had CQ treatment failure rate above the critical value (Sowunmi et al., 2005, Talisuna et al., 2004). Recently, Sarr et al., 2005 has shown a treatment failure rate of 21 % at day 28 in Senegal, while Koram et al 2005 showed a treatment failure rate of 25 % at day 28 PCR corrected, in Ghana.

1.5.13.2 Impact of antimalarial drug resistance Therapeutic impact • Mortality: Resistant infections are more often fatal. • Morbidity: The impact of antimalarial drug resistance is insidious initially. The initial symptoms of the infection resolve and the patient is better for weeks. When symptoms re- occur, usually more than two weeks later, anaemia has worsened, and there is greater probability of carrying gametocytes (which in turn carry the resistant genes) and transmitting malaria. But the patient and the doctor or dispenser may interpret this as

newly acquired infection. At this stage unless drug trials are conducted, resistance may be unrecognized. As resistance worsens the interval between primary infection and recrudescence shortens, until eventually the symptoms fail to resolve. At this stage mortality begins to rise. In the interim, there is prolonged illness and greater chance for resistant organism to spread to other people.

Economic impact Resistance to antimalarial drugs has increased the global cost of controlling the disease and investigations on newer and more expensive drugs. Therapeutic failure necessitates consultation at a health facility for further diagnosis and treatment, resulting in loss of working days for adults and absence from school for children.

Limited solutions There are fewer new drugs on the horizon for malarial treatment.

1.5.13.3 Mode of action and mechanisms of resistance to antimalarial drugs It is believed that the selection of parasites harboring polymorphisms, particularly point mutations, which are associated with reduced drug sensitivity, is the primary basis of drug resistance in malaria parasites. Drug-resistant parasites are more likely to be selected if parasite populations are exposed to sub-therapeutic drug concentrations through unregulated drug use, the use of inadequate drug regimens and the use of long half-life drugs (Winstanley et al., 2002). In recent years, significant progress has been made to understand genetic/molecular mechanisms underlying drug resistance in malaria parasites (Hyde, 2007; Ekland, 2007; Kidgell, 2006).

I. Antifolates Prokaryotic and eukaryotic cells require reduced folate cofactors for the biosynthesis of many cellular components. In plants and most microorganisms folate must be synthesized in vivo through the folate biosynthesis pathway. However, higher eukaryotic cells including mammal cannot synthesize folate in vivo and are totally dependent on exogenous (dietary supplied) folate as the only source for tetrahydrofolate (THF) production by dihydrofolate reductase (DHFR). These differences in folate biosynthesis capacity between mammals and microorganisms make the pathway an attractive antimicrobial target (Bermingham et al., 2002; Djappa et al., 2006). In normal physiological state, the parasite’s dihydropteroate synthase (DHPS) catalyses the

45 condensation of p-aminobenzoic acid (p-ABA) with 2-amino-4-hydroxy-6- hydroxymethyl-7, 8 dihydropteridine pyrophosphate (DHPPP) to form dihydropteroate (DHP). Subsequently the dihydrofolate synthase (DHFS) adds a glutamate to DHP to form dihydrofolate (DHF) which is finally reduced by DHFR to form THF. THF and its derivatives are used as cofactors in biosynthesis of amino acids (e.g. serine, methionine, glycine and histidine) and purines and thymidylate for normal cell growth and function. Sulfa drugs and p-ABA show high degree of structural similarities, thus competitively bind to (dihydropteroate synthetase) DHPS. Therefore, by binding to DHPS sulfa drugs competitively inhibits the activity of this enzyme. Pyrimethamine selectively binds with several folds higher affinity to DHFR of the parasite than the human host, preventing its activity of DHP. Hence sulfadoxine and pyrimethamine exert their parasitocidal effect by synergistically inhibiting the parasite’s folic acid biosynthesis pathway. On the other hand, it was earlier shown that DHPS catalyses the formation of sulfa-DHP (Dieckmann et al., 1986). This complex was thought to play a role in parasitocidal effect of sulfadoxine (Mberu et al., 2002) and was recently confirmed to be inhibitory to parasite growth. Therefore, point mutations at the amino acid position in the dhfr 16 Val, 15 IIe, 59 Arg, 108 Asn/Thr and 164 Leu (Cowmann et al., 1988; Peterson et al., 1988) and dhps 436 Ala/Phe, 437 Gly, 540 Glu, 581 Gly and 613 Thr/Ser (Triglia et al., 1997) result in structural changes on the two proteins’ active site cavities and subsequently reduced binding affinity, consequently inhibiting folic acid synthesis. Accumulation of mutations, in a stepwise fashion is incriminated for increased resistance to antifolate (Winstanley et al., 2002, Hayton et al., 2004). These mutations are considered as molecular markers for surveillance of antifolate resistance. Several studies have shown their association with SP treatment failure (Happi et al., 2005; Kyabinze et al., 2003; Kublin et al., 2002).

II. 4-aminoquinolones This class includes chloroquine (CQ) and amodiaquine (AQ). Many studies have been done to elucidate the parasitocidal activity of these quinolones. However, to date their modes of action remain largely unclear. Nonetheless, a large body of knowledge accumulated for over 30 years shows that the drugs act primarily in the parasite digestive vacuole (DV) by interfering with detoxification of heme, a by-product of hemoglobin digestion (Zhang et al., 1999). In this compartment CQ is considered to have several target sites including heme dimerization activity, aspartic and cysteine protease activity and intravesicular pH.

In order to comprehend the current and widely accepted mode of CQ action, it is important to understand some P. falciparum ultra-structures and feeding processes. The intraerythrocytic parasites are surrounded by a parasitophorous vacuolar membrane (PVM). Thus together with the parasite plasma membrane (PPM), intraerythrocytic parasites are surrounded by a double membrane layer. The parasites feed on the hemoglobin found in the host RBC via a cytostome by forming a localized invagination of the PVM and PPM. The double membrane hemoglobin- laden endocytic vesicles transport vesicles (TV) are then pinched off from the cytostome. The first formed TV matures into DV whose PVM is digested leaving only the PPM (Hempelmann et al., 2003). The DV is an equivalent of lysosomes in other eukaryotic cells, hence sometime called secondary lysosomes. In the DV (Hempelmann et al., 2003) and/or TV hemoglobin is broken down by several enzymes including cysteine and aspartic proteases, into peptides and/or amino acids ferrous protoporphyrin (FeIII IX) which is quickly oxidized to ferric protoporphyrin (FeII IX) (heme). The amino acids (AA) are believed to undergo protonation (AAH+) and exported into the cytosol where they are utilized for protein synthesis and parasite growth. The heme is membrane-toxic, it rapidly intercalate with lipid bilayers and interferes with electron transport chains, leading to per-oxidative damage to unsaturated lipids and/or membrane- embedded proteins (Zhang et al., 1999). The parasite lacks a heme oxygenase pathway but protects itself from heme toxicity by crystalizing free heme into non-toxic hemozoin (malaria pigment) which accumulates in the DV. Chemically hemozoin is identical to synthetic β-hematin linked by hydrogen bonds (Pagola et al., 2000). It is believed that heme dimerization process is promoted mainly by the lipid (linoleic acid) fraction of the erythrocyte membrane of endocytic vesicles (Hempelmann et al., 2003; Orjih, 2001) and the acid environment (pH around 5) inside the vesicles (Orjih, 2001).

Treatment with CQ or AQ results in swelling of the DV as a result of drug accumulation. Further studies showed that CQ- resistant (CQR) parasites accumulate fewer drugs than CQ-sensitive (CQS) (Salibu et al 1998). In the DV, these drugs bind to heme preventing its detoxification. Search for genetic determinants of CQ resistance mapped CQR to a 36 kb region that contains 8 putative genes and identified cgl and cg2 genes as responsible for CQ resistance (Su et al., 1997). These genes were shortly shown to have no role in resistance and it was proposed that other nearby genes may be more important in CQ resistance. Further screening of the region identified

47 a P. falciparum CQ resistance transporter gene (Pfcrt)on chromosome 7 as the most important determinant of CQ resistance and mutations were identified and associated with increased CQ resistance in vitro and in vivo (Hayton et al., 2004). Earlier on the phenomena of reduced drug accumulation and resistance reversibility shared between multi-drug resistant cancer cells and CQR P. falciparum prompted the search and subsequent discovery of P. falciparum multi drug resistance 1 (Pfmdr l) gene in chromosome 5 which was linked to CQ resistance (Karcz et al., 1991). The Pfcrt encodes for the chloroquine resistance transporter (Pfcrt) protein and the Pfmdr 1 a P-glycoprotein homologue 1 (PGH1) protein. Both Pfcrt and Pfmdr 1 are located on the parasite’s DV membrane and currently regarded as the primary mediators of CQ resistance (Fidock et al., 2000b; Djimde et al., 2001a) despite their being on different chromosome.

A model of CQ effect on heme detoxification by wild-type and mutant parasite in the DV was suggested by Warhurst 2001, the lysosome of a chloroquine-sensitive parasite, hydrogen ions enters through the proton pump, acidifying the lysosomal environment (pH 5.5). This process is probably regulated by the PGH1 protein, which releases anions into the lysosome to optimize the difference in the trans-membrane charge. During the digestion of hemoglobin (Hb), protonated basic amino acids (AAH+) are released together with toxic ferri-protoporphyrin IX (Fp9). Ferri- protoporphyrin IX is detoxified by polymerization to crystalline hemozoin. The weak base chloroquine, present in the cytoplasm (pH 7.4), dissolves in the lysosomal membrane and enters the acidic environment, undergoing protonation to a form CQH+ that is insoluble in the membrane and that quickly becomes concentrated. CQH+ binds to ferri-protoporphyrin IX and thus inhibits its polymerization, which leads to the accumulation of ferri-protoporphyrin IX, causing membrane damage. The protonated basic amino acids exit the lysosome by means of the trans-membrane protein Pfcrt. The Pfcrt protein probably has a limited affinity for CQH+ and exports some of the drug from chloroquine-sensitive parasites. The mutant Pfcrt probably has an increased affinity for CQH+ and exports large amounts of the drug, enabling the polymerization of ferri-protoporphyrin IX to proceed normally. Concomitantly, the mutant Pfcrt would have a reduced affinity for AAH+, which may reduce the efficiency of the export of AAH+ and, in the absence of chloroquine, result in the accumulation of more protons (H+) in the lysosome. The presence of mutant Pgh1 may partially prevent this accumulation of protons, increasing the fitness of parasites with Pfcrt and Pfmdr 1 mutations. The mutation in Pfmdr 1 also increases the

48 sensitivity of the parasite to mefloquine and artemisinin, probably as a result of the partial inactivation of the ability of mutant Pgh1 to export these drugs.

Accumulation of mutations in the Pfcrt at position 72 Ser, 74IIe, 75 Glu, 76 Thr, 220 Ser, 271 Glue, 326 Ser, 356 Thr and 371 IIe (Fidock et al., 2000b) and Pfmdr l at position 86 Asn/Thr, 184 Phe, 1034 Cys, 1042 Asp and 1246 Tyr (Foote et al., 1990) are associated with increased resistance to CQ. These two genes are believed to interact synergistically (Adagut et al., 2001). The Pfcrt 76 mutation is strongly associated with CQ resistance and the genotype failure index (GFI) calculated using this marker were stable (Tinto et al., 2005). Nonetheless, mutations in Pfmdr l only modulate CQ susceptibility of Pfcrt mutant parasite but are, by themselves, incapable of conferring CQ resistance (Djimde et al., 2001a; Adagut et al., 2001). The Pfmdr l 86 Tyr is the most important modulator of CQ resistance. Thus Pfcrt 76 Thr and Pfmdr l 86 Tyr mutations are recommended for use as markers for in vivo CQ resistance.

Studies have shown also that CQ treatment induces masking of the lipid fraction of the erythrocyte membrane that promotes ferri-protoporphyrin dimerization (Fitch et al., 2003a) and reduces the activity of neutral amino-peptidase, an enzyme required for normal processing of hemoglobin-laden endocytic vesicles (Fitch et al., 2003b).

III. Quinoline-4-methanols This class includes quinine (QN), mefloquine (MQ), lumefantrine and halofantrine. Similarly, the precise mode of action of these quinolines is not known. However, there is evidence of binding of these drugs to targets other than the ferri-protoporphyrin IX. Exposure of CQR parasites to quinine and mefloquine does not lead to accumulation and aggregation of hemoglobin-laden endocytic vesicles, increased masking of the linoleic acid (Fitch et al., 2003a) or excess accumulation of undimerized ferri-protoporphyrin. Mefloquine, quinine and other quinoline-4-methanol subclass bind with high affinity to phospholipids targets in malaria parasites. The drugs also inhibit and reverse vesicular docking in the endolysosomal system, either by impairing membrane function directly or indirectly by inhibiting calcium release from acid stores (Fitch et al., 2004). Mefloquine and quinine antagonize CQ-induced abnormalities in malaria parasites, primarily by inhibition of hemoglobin ingestion and secondarily they inhibit membrane recycling, leading to killing of the parasite. However, the binding of CQ-FP complex to phospholipids is an agonist for vesicular docking in malaria parasites (Fitch et al., 2004)

The inverse effects of 4-aminoquinolines and quinoline-methanol on parasite morphological abnormalities are consistent with observations made on the role of the two membrane transport genes on resistance to these antimalarial drugs. Similar to CQ resistance to mefloquine and/or quinine is also influenced by Pfcrt (Bray et al., 2005) and Pfmdr 1 genotype, and/or copy number/over expression of the Pfmdr 1 gene (Price et al., 2004; Duraisingh et al., 2005). However, in contrast to CQ, mutations in Pfcrt have been associated with increased susceptibility to mefloquine and quinine and the wild type Pfmdr 1 allele further augments resistance to mefloquine and artemether-lumefantrine (coartem®) (Sisowath et al., 2005). Bray et al., 2005 in another study associated the mutants Pfcrt with QN resistance. In addition to Pfmdr 1and Pfcrt, 9 more genes have been found to be associated with P. falciparum sensitivity to CQ and QN (Mu et al., 2003). In general, these observations show that drug resistance is a complex phenotype involving interaction of many different genes.

IV. Artemisinins Originally the mode of action of artemisinins was considered to be similar to CQ; inhibition of heme polymerization (Pandey et al., 1999). However, it was later shown that artemisinins kill parasites by heme-depended activation of the endoperoxide bridge (Meschnick, 1994). The cleavage of the bridge activates a series of reactions culminating into the formation of an oxygen-centered free radical, carbon-centered free radical and finally an epoxide. Carbon- centered radicals and epoxide are highly active alkylating agents and may kill parasites by alkylating some, unidentified targets (Olliaro et al., 2001; Jefford, 2001). However, this theory was not universally accepted. It was proposed that the antimalarial activity of artemisinins is conferred by the 1,2,4 trioxane pharmacophore (the group of atoms in the molecule of a drug responsible for the drug’s action) within artemisinins (Olliaro et al., 2001). The trioxane structure is now being exploited in developing synthetic peroxide antimalarials (Vernnestrom et al., 2004). However, the theory of heme dependent activation of the endoperoxide bridge contrast the mode of action of most bioactive molecules where activity is mediated by binding to an active site. The observations that artemisinins localize to parasite and not food vacuole membranes (Ellis et al., 1985), are capable of killing tiny rings lacking hemozoin (ter Kulie et al., 1993) and do not inhibit hemozoin formation (Haynes et al., 2003) have ruled out food vacuole as the site for artemisinin action.

Thapsigargin, a plant-derived sesquiterpene lactone, is a highly specific inhibitor of sarco/endoplasmic reticulum Ca2+ (SERCA). Since thapsigargin and artemisinins show structural similarities, it was hypothesized and later proven that artemisinins can specifically and selectively inhibit Plasmodium falciparum adenosine triphosphatase b (PfATPaseb), the only SERCA-type Ca2+ATPase in P. falciparum genome, after activation by iron (Eckstein-Ludwig et al., 2003). The interaction of artemisinins with thapsigargin-binding cleft of susceptible SERCAs was confirmed (Uhlemann et al., 2005), pointing out those mutations which modulate its sensitivity to artemisinins may mark emergence of resistance. Subsequent in vitro studies showed that P. falciparum with elevated IC50 values for artemisinins share particular mutation i.e. PfATPaseb 769, 623 and 431 (Jambou et al., 2005).

However, the development of stable artemisinin resistant P. chabaudi lacking mutations or amplification of the ATPaseb gene failed to establish the role of this gene in resistance to artemisinin (Afonso et al., 2006). P. falciparum sensitivity to artemisinins is also considered to be influenced by the Pfmdr1 genotype and amplification (Price et al., 2004). While the mode of action of artemisinin is still controversial and unclear, mutations in the PfATPase and Pfmdr 1 are the only currently available markers that may be used as warning signals for emergence of in vivo resistance to artemisinins. Uncontrolled use of artemisinins monotherapies or in combination with ineffective partners might lead to faster selection of resistance resulting into reduction of presumed long useful therapeutic life (UTL) of the ACTs (Duffy et al., 2005).

1.5.14 Malaria parasite genome Malaria Genome Sequencing Consortium was established in 1997 to sequence the entire genome of P. falciparum as a collaborative venture. Genome is the entirety of an organism’s hereditary information. Different parasite clones were obtained such as W2, D6, HB3, FCR and 3D7. By 2002 the sequencing of P. falciparum chromosome 12 (clone 3D7) was successfully completed (Gardner et al., 2002). P. falciparum has about 23 mega bases divided between 14 chromosomes, which range in size from 0.7 to 3.5MB, and encodes 5300 genes. Sequencing this genome shows a biased nucleotide composition of its DNA, with an overall adenine + thymine (A + T) content estimated at 82 % and guanine + cytosine (G + C) at 18 %.

1.5.14.1 Protein targeting Structure P. falciparum contains two organellar genomes, thought to have been acquired as a result of multiple endosymbiotic events. The mitochondrial genome is a 5.9kb linear molecule present as multiple tanderm repeats. A second genome, 35kb circular DNA molecule is located with the apicoplast (Wilson et al., 1996).This is an organelle of plastid origin, thought to be unique to apicomplexan parasites, which apparently provides metabolic function (Soldati, 1999). Three predicted protein on chromosome 3 have N-terminal sequence and implies biological function indicating mitochondrial import (PFC0170C, PFC0225C, and PFCO275W). Two predicted protein have been pre-sequences that indicate targeting to the apicoplast (PFC0050C, PFC0310C). P. falciparum also directs several proteins to the cytoplasm, cytoskeleton and plasma membrane of the infected red blood cell. The protein implicated as receptor in cytoadherence fall into this category; however the sequence responsible for targeting these molecules remains unidentified. (Bowman et al., 1999)

1.5.14.2 Telomere structure The ends of all 14 P. falciparum chromosomes share a common and conserved organization; the telomere repeat units (GGGTTTA) and the non protein-coding subtelomeric domain of 15–30 kb are followed by members of the var, rif and stevor multigene families. The conserved arrangement of P. falciparum chromosome ends is thought to mediate chromosome-end alignment and clustering in a manner that promotes recombination in telomere associated genes located at the end of heterologous chromosomes (ectopic recombination). This has been demonstrated to occur in var genes resulting in gene conversion events. This process of ectopic recombination in var genes, which is also likely to occur in other subtelomeric gene family, allows the rapid generation of diverse antigenic and adherence phenotype which encode determinants of virulence and pathology, such as the var-encoded immuno-variant adhesion PfEMP (Gardner et al., 2002, Freitas-Junior et al., 2000). The subtelomeric domains consist of six different telomere-associated repetitive elements (TAREs 1–6). TAREs 1–5 are located toward the telomeres, whereas TARE-6, originally known as rep20, is situated upstream of the multigene family clusters.

1.5.14.3 Structural variance and transcriptomics of Plasmodium falciparum Transcriptomics refers to the set of all RNA molecules including mRNA, rRNA, tRNA and non- coding RNA produced in one or more population. Nonprotein-coding RNAs (npcRNAs) represent an important class of regulatory molecules that act in many cellular pathways. Plasmodium genomes typically encode two different types of RNA molecules: messenger RNAs (mRNAs) and various classes of nonprotein-coding RNAs (npcRNAs). The mRNAs provide templates for protein synthesis, whereas the npcRNAs do not code for proteins but rather perform various regulatory functions exerted by the RNA itself or in complexes with proteins (RNPs). npcRNAs participate in the regulation of diverse biochemical pathways, including chromosome modification, transcription and translation, splicing, developmental timing, cell differentiation, proliferation, apoptosis and organ development (Moazed 2009, Cam et al 2009, Prasanth et al., 2007, Royo et al., 2006, Brosius, 2005).

Although the small npcRNA transcriptome has been experimentally identified and successfully verified in several model organisms, very few systematic attempts to uncover the diversity and functions of small npcRNAs in pathogenic organisms have been undertaken to date. Recently, a number of structural RNAs based mainly on comparative genomics, were detected in Plasmodium (Chakrabarti et al., 2007). They include telomerase RNA, 35 small nucleolar RNAs (snRNAs), spliceosomal small nuclear RNAs (snRNAs), MRP RNA and RNase P RNA. In addition, the authors described six new npcRNAs, as of yet, unknown functions. Similarly, Mourier et al., 2008 performed computational screens in intronic and intergenic regions of P. falciparum to identify conserved RNA secondary structures between distantly related Plasmodium species, yielding a set of 604 putative npcRNAs; 33 of which they verified experimentally. Notably, 29 RNAs from this dataset overlapped with those of the aforementioned set reported by Chakrabarti et al., 2007. Li et al., 2008 reported centromeric expression of small npcRNA candidates (75 and 175) in P. falciparum. Their data suggested bi- directional promoter activities within the centromers of the parasite. This subclass of npcRNA candidates is localized within the nucleus and appears to associate with the centromeric chromatin.

1.5.14.4 Genetic variations in malaria genome Genetic variation also referred to as genetic diversity, describes natural occurring genetic differences among individuals of the same species. This variation permits flexibility and survival of a population in the face of changing environmental circumstances. Consequently, genetic variation is often considered an advantage, as it is a form of preparation for the unexpected. There are three primary sources of genetic variation,

1. Mutations are changes in the DNA. A single mutation can have a large effect, but in many cases, evolutionary change is based on the accumulation of many mutations. 2. Gene flow is any movement of genes from one population to another and is an important source of genetic variation. 3. Sex can introduce new gene combinations into a population. This genetic shuffling is another important source of genetic variation.

Genes involved in antigenic variations are concentrated in the subtelomeric regions of the chromosomes. Compared to the genome of free living eukaryotic microbes, this genome of this intracellular parasite encodes fewer enzyme and transporter but a large proportion of genes are devoted to immune evasion and host-parasite interaction.

1.5.15 Single nucleotide polymorphism and mutation Polymorphisms are often terminologically distinguished from mutations by an arbitrary frequency criterion: The different forms of the polymorphism (termed “alleles”) are observed more often in the general population than mutations, with a population frequency of <1 % often used as a cutoff value. The most common polymorphism in the human genome is the single- nucleotide polymorphism, better known as the SNP. In samples of the size usually relevant to biomedical research, the vast majority of SNPs have two alleles, which represent a substitution of one base for another (e.g., C to T or A to G). For an individual SNP, one is designated the “major” allele and the other the “minor” allele based on their observed frequency in the general population.

The sequencing and annotation of the 23 Mb P. falciparum genome in 2002 provided a superb resource for localizing and identifying gene candidates within a particular locus (Gardner 2002). Linking a specific locus with a given phenotype such as drug resistance, however, requires the

54 ability to compare the genotypes of resistant and sensitive parasites. Rather than sequencing the entire genome of each resistant or sensitive clone, recent advances have exploited the presence of conserved polymorphisms in the genome as surrogate markers for the resistance determinant(s). Polymorphisms can include microsatellites (consisting of repeats of a short nucleotide sequence), single nucleotide polymorphisms (SNPs), or small insertions or deletions (indels).

A trio of papers, published in Nature Genetics in early 2007, moved the field substantially closer to a comprehensive polymorphism map for the P. falciparum genome (Jeffares et al., 2007, Mu et al., 2007, and Volkman et al., 2007). These papers described the sequencing of the entire genome, or selected regions, from multiple P. falciparum strains. The authors estimate the number of SNPs in the P. falciparum genome as ranging from about 25,000 to 50,000, corresponding to one SNP every 400 to 800 base pairs. In P. falciparum, as in humans, these SNPs do not segregate randomly. Instead they tend to cluster in “blocks,” called haplotype blocks, delimited by recombination hotspots. Association studies thus need only to track a signature set of SNP tags that identify a particular haplotype block. Studies indicate that recombination rates vary substantially between different strains of P. falciparum, with ones in Africa demonstrating the highest rates (Mu et al., 2005).

The number of polymorphisms varies for different gene classes and for different regions within chromosomes. This presumably reflects the influence of diversifying selection exerted on genes by factors such as host immunity and drug selection (Jeffares et al., 2007, Mu et al., 2007, Volkman et al., 2007, Mu et al., 2005). High rates of recombination, such as that observed among African P. falciparum strains (Mu et al., 2005), will tend to obscure the linkage between ancestral traits. The phenomenon of drug resistance, however, is a relatively recent evolutionary event. Consequently, the use of linkage disequilibrium (LD) is ideally suited for tracking the spread of a resistance gene throughout a population.

It is important to note that not all gene mutations affect health and development; only a small percentage of mutations cause genetic disorders—most have no impact on health or development. For example, some mutations alter a gene’s DNA sequence but do not change the function of the protein made by the gene.

1.5.15.1 Types of mutations 1.5.15.1 Synonymous mutation A synonymous mutation is a mutation that occurs when there is a change in the genetic sequence of DNA, but the change results in the same genetic output. An example of synonymous mutation can be found in amino acid chains, which form many different types of proteins. Amino acids are formed by codons, which are made up of 3 base pairs.

1.5.15.2 Non-synonymous Non-synonymous mutation is one that, obviously, changes the output entirely, creating an authentic, observable mutation. However, if the original amino acid were, Histidine (CAC), and a mutation of the last letter became a G, that would change the amino acid completely to Glutamine (CAG). This creation of a different amino acid makes for an observable mutation, which is non-synonymous (different) from the original.

1.5.15.3 Missense mutation In genetics, a missense mutation (a type of non synonymous mutation) is a point mutation in which a single nucleotide change results in a codon that code for a different amino acid. This can render the resulting protein nonfunctional (Minde et al., 2011). Such mutations are responsible for diseases such as Epidermolysis bullosa, sickle-cell disease, and superoxide dismutase 1 (SOD 1) mediated amyotrophic lateral sclerosis (ALS)

For example, in the most common variant of sickle-cell disease, the 20th nucleotide of the gene for the beta chain of hemoglobin found on chromosome 11 is erroneously changed from the codon GAG (for glutamic acid) to GUG (which codes valine). Thus, the 6th amino acid is incorrectly substituted (after the initial methionine amino acid is removed) and the protein is significantly altered to cause the sickle-cell disease. Not all missense mutations lead to appreciable protein changes. An amino acid may be replaced by an amino acid of very similar chemical properties, in which case, the protein may still function normally; this is termed a neutral, "quiet", "silent" or conservative mutation. Alternatively, the amino acid substitution could occur in a region of the protein which does not significantly affect the protein secondary structure or function. When an amino acid may be encoded by more than one codon (so-called "degenerate coding") a mutation in a codon may not produce any change in translation; this

56 would be a synonymous mutation (a form of silent mutation) and not a missense mutation. A special type of missense mutation that results in truncation of code is the nonsense mutation.

Natural selection Natural selection is the gradual process by which biological traits become either more or less common in a population as a function of the effect of inherited traits on the differential reproductive success of organisms interacting with their environment. It is a key mechanism of evolution. The term "natural selection" was popularized by Charles Darwin who intended it to be compared with artificial selection, which is now called selective breeding. Charles Darwin and Alfred Russel Wallace noted that organisms which were better adapted to their environment tended to survive longer. Better adapted organisms also tend to reproduce more than less well- adapted organisms. They predicted that over time favorable traits which are inheritable would become more common.

Natural selection acts on the phenotype, or the observable characteristics of an organism, but the genetic (heritable) basis of any phenotype that gives a reproductive advantage may become more common in a population. Over time, this process can result in populations that specialize for particular ecological niches and may eventually result in the emergence of new species. In other words, natural selection is an important process (though not the only process) by which evolution takes place within a population of organisms. According to the Theory of evolution, it is through a combination of natural selection and mutation that biological complexity and adaptation arise from earlier generations of life. The prevailing theory in biology is that natural selection is the mechanism by which allele frequency within a population changes over time due to genetic variation and selection pressures.

Selection pressure Selection pressure can be regarded as a force that causes a particular organism to evolve in a certain direction. It is not a physical force, but an interaction between natural variation in a species and factors in its environment that cause a certain form to have an advantage over the others. This can be thought of as a “pressure” that pushes the evolution of that organism toward a greater prevalence of this variation

The cells in a multicellular organism have nominally identical DNA sequences (and therefore the same genetic instruction sets), yet maintain different terminal phenotypes. This non-genetic cellular memory, which records developmental and environmental cues (and alternative cell states in unicellular organisms), is the basis of epigenetics.

1.5.16 Pfmdr 1 gene The phenomena of reduced drug accumulation and resistance reversibility shared between multidrug resistant cancer cells and chloroquine resistance P. falciparum, prompted the search and subsequent discovery of P. falciparum multi drug resistance 1 (Pfmdr l) gene in chromosome 5. The gene encoding Pfmdr 1 is an ortholog of P-glycoproteins found in mammals that mediate multidrug resistance in cancer cells. Plasmodium falciparum multidrug resistance gene 1 (Pfmdr1) is an adenosine triphosphate-binding cassette protein located on the parasite’s food vacuole (Cowman, 1991). Mutations in the Pfmdr-1 coding gene leading to amino acid changes in Pfmdr1 have different consequences on parasite’s sensitivity to anti-malarial drugs

Genetic variations in this gene have played vital role in malaria chemotherapy. Mutations (N86Y, Y184F, S1034C, N1042D, and D1246Y) in the Pfmdr 1 gene have been associated with resistance to chloroquine, quinine, mefloquine, lumefantrine and artemisinin (Price et al., 2006, Sidhu et al., 2005, Sisowath et al., 2007). Increased sensitivity to dihydro-artemisinin in the presence of wild type codon 86 in Pfmdr 1 and in-vivo selection of Pfmdr 1 86N during AL treatment has been reported (Dokomajilar et al., 2006, Sisowath et al., 2005, Duraisingh et al., 2000). This ability of Pfmdr 1 to influence sensitivity of parasites to aminoquinolones, arylaminoalcohols and artemisinins provides evidence of contribution of Pfmdr 1 to multi-drug resistance (Duraisingh et al., 2005). Multi-drug resistance is said to have occurred when cells selected for resistance to one agent, are rendered resistant to a number of structurally unrelated drug.

Differences in Pfmdr 1 copy number are linked to changes in clinical efficacy of several drugs. Increases in copy number are associated with increased risk of treatment failure after treatment with mefloquine, artesunate-mefloquine, or artemether-lumefantrine. Relating copy number to in vitro susceptibility testing has been difficult because copy number can change during the process of culture adaptation of field isolates, a process that is necessary for reliable assessment of drug

58 sensitivity. Sidhu et al., have succeeded in altering Pfmdr 1 copy number and have demonstrated increases in susceptibility to mefloquine, quinine, halofantrine, and artemisinin with lower copy number (Sidhu et al., 2006).

1.5.16.1 Mechanism by which Pfmdr 1 gene confers resistance to antimalarials How Pfmdr 1 confers resistance to antimalarial drugs has remained a subject of controversy and only recently have data accumulated in favor of Pfmdr 1 acting as an active drug transporter. Much of the uncertainty concerning Pfmdr 1’s role in drug resistance came from the finding that Pfmdr1 is present on the parasite’s digestive vacuolar membrane – very little Pfmdr1 is present at the parasite plasma membrane (Cowman et al., 1991) – and that the topology of the protein leaves its ATP-binding domain facing the cytoplasm (Karcz et al., 1993). Vectorial transport by Pfmdr 1 is, therefore, predicted to be inwardly directed, that is, into and not out of the digestive vacuole. In comparison, mammalian P-glycoproteins reside within the plasma membrane, their nucleotide binding domains face the cytoplasm and they export drugs out of the cell (Higgins, 2007). Consistent with an import function of Pfmdr 1, a recent study has demonstrated, by live cell imaging, that Pfmdr1 transports the fluorophore Fluo-4 into the parasite’s digestive vacuole (Rohrbach et al., 2006). The Pfmdr 1-mediated Fluo-4 transport phenotype was restricted to polymorphic forms of Pfmdr 1 associated with altered drug responses and transport could be competed for by mefloquine, halofantrine, quinine, and artemisinin (Rohrbach et al., 2006), suggesting that Pfmdr1 can act on several antimalarial drugs.

Further evidence for Pfmdr 1 being a transporter has come from heterologous expression studies (van Es et al., 1994) demonstrated an increased CQ accumulation and susceptibility in mammalian Pfmdr 1. Pfmdr 1 itself may be a target of antimalarial drugs, including quinine and mefloquine, as demonstrated in competition studies (Rubio et al., 1996; Rohrbach et al., 2006; Sanchez et al., 2008a), which suggest that some of the drugs with which Pfmdr 1 interacts may function as both substrates and inhibitors. An analogous finding has been reported for human P- glycoprotein (Weaver et al., 1993; Hayeshi et al., 2006), where it was shown that the common drug binding site can accommodate several substrates of the same or different type, at the same time (Loo, 2005). A plausible model for Pfmdr1 is that quinine and possibly other antimalarial drugs occupy the common drug binding site of Pfmdr 1, thereby inhibiting transport of other

59 solutes. Inhibition of Pfmdr 1 by drugs such as quinine, halofantrine, and mefloquine may explain the finding that amplification of non wild- type Pfmdr 1 enhances resistance to these drugs in P. falciparum (Cowman et al., 1994; Sidhu et al., 2006). How effectively a drug inhibits Pfmdr 1 activity may depend upon polymorphisms within this protein.

1.5.17 Amplification of genomic DNA This is a selective increase in the number of copies of a gene coding for a specific protein without a proportional increase in other genes. It occurs naturally via the excision of a copy of the repeating sequence from the chromosome and its extra chromosomal replication in a plasmid, or via the production of an RNA transcript of the entire repeating sequence of ribosomal RNA followed by the reverse transcription of the molecule to produce an additional copy of the original DNA sequence. Laboratory techniques have been introduced for inducing disproportional replication by unequal crossing over, uptake of DNA from lysed cells, or generation of extra chromosomal sequences from rolling circle replication. Cellsin all organisms regulate gene expression by turnover of gene transcripts (messenger RNA, mRNA): The amount of an expressed gene in a cell can be measured by the number of copies of an mRNA transcript of that gene present in a sample. In order to robustly detect and quantify gene expression from small amount of RNA, amplification of the gene transcript is necessary.

1.5.17.1 PCR chemistry The advent of Polymerase Chain Reaction was developed by Kary B. Mullis in 1984. PCR is a powerful method used to amplify specific sequences of DNA from a large complex mixture of DNA; for mRNA-based PCR, the RNA sample is first reverse transcribed to cDNA with reverse transcriptase. From a single template molecule, over 1 billion copies of the PCR product can be duplicated very quickly. PCR is a process that uses three items:

a. Primer: This is a strand of nucleic acid that serves as starting point for DNA synthesis. They are required for DNA replication because the enzyme that catalyze this process; DNA polymerase, can only add new nucleotides to an existing strand of DNA. DNA primers are usually short, chemically synthesized oligonucleotides, with a length of about 20 bases. They are hybridized to a target DNA, which is then copied by the polymerase.

b. The Master Mix: This solution contains the entire component necessary for DNA replication as is obtainable in vivo. First is all four deoxyribonuclease triphosphates (dNTPs) in equal amount; they are deoxyriboadenosine triphosphate dATP, deoxyriboguanine triphosphate dGTP, deoxyribocytosine triphosphate dCTP, and deoxyribotyrosine triphosphate dTTP. Second is buffer (KCl and MgCl) to keep the solution at the proper pH for the reaction.

c. A heat stable DNA polymerase: Usually Taq DNA polymerase which is a polymerase from thermophilic bacterium- Thermus aquaticus- which lives in hot spring.

The PCR process generally consists of three phases.

a. Denaturation or separation: This involves the strand separation. The two strands of the parent DNA molecule are separated by heating the solution to 95 ˚C for 15 seconds

b. Hybridization or annealing of two oligonucleotide primers (one is a reverse primer and the other is a forward primer). The solution is quickly cooled to 50-60 ˚C for the primer to anneal to the DNA strand. One primer anneals to 3’end of target (template strand) while the other primer anneals to the 5’ end of the complementary target strand. Then each copy forms the template in the next cycle. Primer annealing depends on the melting temperature (Tm) of the primer.

c. DNA synthesis or elongation or extension: In this last phase, the temperature is heated to 68-72 ˚C (usually 72 ˚C which is the optimal temperature for Taq DNA polymerase). The polymerase elongates both primers in the direction of the target sequence. DNA sequence continues on both strands and continues beyond the target sequence (Rychlyk et al., 1990). The process is shown in figure 1.3.

Figure 1.3: The process of DNA amplification by PCR, showing denaturation, annealing and extension. (Adapted from Rychlyk et al 1990)

All three steps above are considered as one cycle: It takes about 25 - 40 cycles in order to amplify DNA template. The number of cycles depends on the amount of DNA available and the quantity of PCR product needed while the temperatures and timing depend on a wide variety of parameters, such as the enzyme used to synthesize the DNA, the concentration of divalent ions and dNTPs in the reaction and bonding temperature of the primer. PCR is carried out in a thermal cycler that is programmed with a protocol that goes through all three steps of a cycle. It is important to note that standard PCR does not quantify the PCR product.

1.5.17.2 Nested PCR The capacity to amplify over one billion fold of specific sequence of DNA by PCR method, also increases the possibility of amplifying the wrong DNA sequence over one billion times. The specificity of PCR is determined by the specificity of the PCR primers. If a primer binds to more than one locus, then more than one segment of DNA will be amplified. To control for these possibilities, investigators often employ nested primers to ensure specificity. Nested polymerase chain reaction is a modification of polymerase chain reaction intended to reduce non-specific binding in products due to the amplification of unexpected primer binding sites.

Nested PCR means that two pairs of PCR primers were used for a single locus. The first pair amplified the locus as seen in any PCR experiment. The second pair of primers (nested primers) binds within the first PCR product and produces a second PCR product that will be shorter than the first one. The logic behind this strategy is that if the wrong locus were amplified by mistake, the probability is very low that it would also be amplified a second time by a second pair of primers in the following orders:

1. The first pair of PCR primers binds to the outer pair of primer binding sites and amplify all the DNA in between the two sites. 2. Second pair of nested primers binds to the first PCR product. The binding sites for the second pair of primers are a few bases "internal" to the first primer binding sites. 3. Final PCR product after second round of PCR. The length of the product is defined by the location of the internal primer binding sites

When a complete genome sequence is known, it is easier to be sure you will not amplify the wrong locus but since very few of the world's genomes have been sequenced completely, nested primers will continue to be an important control for many experiments.

1.5.18 Quantification of genomic DNA 1.5.18.1 Real time PCR Real time PCR is a technique used to monitor the progress of a PCR reaction in real time and at the same time, the amount of PCR product (DNA, cDNA or RNA) can be quantified. Real time PCR is based on the detection of the fluorescence produced by a reporter molecule which increases as the reaction proceeds. This occurs due to the accumulation of the PCR product with each cycle of amplification. These fluorescent reporter molecules include dyes that bind to the double stranded DNA (SYBER® Green) or sequence specific probes (molecular beacons or TaqMan® Probes). Real time PCR facilitates the monitoring of the reaction as it progresses. A reaction can be started with minimal amount of nucleic acid and quantify the end product accurately. The fluorescence based real time PCR techniques have revolutionized the approach to PCR based quantification of DNA and RNA. They are easy to perform, have high sensitivity, more specificity and provide scope for automation. The forward and the reverse primer anneal to the target DNA (in red and blue colour), the probe (green colour) which has +ve and –ve charge transmits light as the reaction proceeds. The amount of light produced is directly proportional to the amount of DNA copies amplified as shown in figure 1.4.

Figure 1.4: The process of DNA amplification and quantification by Real Time PCR (www.probes.com 2003)

1.5.18.2 Classification of Real time PCR Based on the molecule used for the detection, the technique is classified into: a. Non-specific detection using DNA binding dyes

b. Specific detection using target specific (hybridization) probes.

Non-specific detection using DNA binding dyes This technique uses DNA fluorescent dyes as fluorescent reporters to monitor the reaction. The fluorescence of the reporter increases as the product accumulates with each successive cycle of amplification. By recording the amount of fluorescence emission at each cycle, it is possible to monitor the PCR reaction during exponential phase. If a graph is drawn between the log of the starting amount of template and the corresponding increase in the fluorescence of the reporter dye, during real time PCR, a linear relationship is observed.

SYBER® Green is the most widely used double stranded DNA dye reporter for real time PCR. It binds to the minor grove of the DNA double helix and remains stable under PCR condition. Ethidium bromide can also be used for detection but its carcinogenic nature renders its use restrictive. Although these double stranded DNA-binding dyes provide the simplest and cheapest option for real time PCR, the principal set back to intercalation based detection of PCR product accumulation is that both specific and non-specific product generate signal.

Specific detection using target specific (hybridization) probes. Specific detection of real time PCR is done with some oligonucleotide probes labeled with both a reporter fluorescent dye and a quencher dye. Probes based on different chemistries are available for real time PCR, these include: a. Molecular beacons b. TaqMan® probes c. FRET® hybridization probes d. Scorpion® primers

1.5.18.3 Applications of Real time PCR The technique is applied in (Julie et al, 2009):

a. Quantitative mRNA expression studies b. DNA copy number measurements in genomic or viral DNAs c. Allelic discrimination assay or SNP genotyping. d. Verification of microarray results e. Drug therapy efficacy f. DNA damage measurement

Real time PCR versus standard PCR Real time PCR allows for the detection and quantification of PCR product during the early phase of the reaction. This ability of measuring the reaction kinetics provides a distinct advantage over standard PCR detection. Standard PCR uses gel electrophoresis for the detection of PCR amplification

1.5.19 DNA extraction Since DNA is the blueprint for life, everything living contains DNA.DNA isolation is one of the most basic and essential techniques in the study of molecular biology. The extraction of DNA from cells and its purification are of primary importance to the field of biotechnology and forensics. Simply put, DNA Extraction is the removal of deoxyribonucleic acid (DNA) from the cells or viruses in which it normally resides. Extraction of DNA is often an early step in many diagnostic processes used to detect bacteria and viruses in the environment as well as diagnosing disease and genetic disorders. The most basic of all procedures in molecular biology is the purification of DNA.

1.5.19.1 Methods of DNA extraction The most commonly used DNA extraction methods include (Chem et al, 2008): a. Organic (Phenol-Chloroform) extraction b. Non-organic (proteinase K and salting out) extraction c. Chelex (Ion exchange resin) extraction d. FTA™ paper (collection, storage and isolation) e. Silica based (silica exchange resin-qiagen)

The method utilized may be sample dependant, technique dependant or analyst preference dependant.

1.5.19.1 Organic extraction This method makes use of organic reagents like phenol and chloroform. The key step in this method is removal of proteins. This is carried out by extracting aqueous solutions of nucleic acids with phenol and /or chloroform. Pros

§ It yields relatively pure high molecular weight DNA. § DNA produce is double stranded, hence good for RFLP Cons

§ It is time consuming § Requires samples to be transferred to multiple tubes thereby increasing risk of contamination § It involves use of hazardous chemicals

1.5.19.2 Non-organic DNA extraction This method does not use organic reagents such as phenol or chloroform as in organic extraction, and digested proteins are removed by salting out with high concentration of LiCl. Cell membrane are lysed by lysis buffer and protein digested by proteinase K.

Limitations If salts are not adequately removed, problems could occur with the RFLP procedure due to alteration of DNA mobility.

1.5.19.3 Chelex extraction Pros § It is relatively fast § It can extract directly from cloth (stain) § It minimizes contamination as it uses a single tube § It advantageous for PCR based typing methods because it removes inhibitors of PCR

Cons § It denatures double stranded DNA and results in a single stranded DNA, thus cannot be used for RFLP procedure § Care should be taken not to have any residual Chelex with the DNA extract, since Mg2+ is required for the Taq Polymerase

1.5.19.4 Filter Paper (FTA™) method This is unique method of DNA collection, extraction and storage using a special filter paper. The filter paper is prepared with a unique mixture of strong buffer. The buffer denatures protein, acts as chelating agent and also absorbs free radicals. Drop of blood samples are collected with FTA filter paper. The filter paper act by: • Destruction of blood borne pathogens or contacts • Immobilize DNA within the matrix • Protect DNA from degradation • Allows for long term storage at room temperature Pros § Very fast § Small amount (drops) of blood needed § Useful for both collection, extraction and storage Cons § It is not suitable for RFLP § Risk of potential contamination

1.5.19.5 Silica based extraction Silica based extraction is a method of DNA separation that is based on DNA molecules binding to silica surfaces in the presence of certain salts and under certain pH conditions. It is very fast and highly purified, however, the method involves multiple sample transfer hence increase risk of contamination. A typical example is magnetic bead extraction.

Magnetic bead extraction method Magnetic beads are coated with DNA antibodies to bind to DNA.

Pros § It is very fast § Method may be automated § Results in highly purified DNA § It is excellent for liquid blood Cons § It cannot be used directly on stain § It is very expensive

1.5.20 Genotyping of DNA Genotyping is the process of determining differences in the genetic make-up (genotype) of an individual by examining the individual's DNA sequence using biological assays and comparing it to another individual's sequence or a reference sequence. It reveals the alleles an individual has inherited from their parents. Traditionally, genotyping is the use of DNA sequences to define biological populations by use of molecular tools. It does not usually involve defining the genes of an individual.

Current methods of genotyping include restriction fragment length polymorphism identification (RFLPI) of genomic DNA, random amplified polymorphic detection (RAPD) of genomic DNA, amplified fragment length polymorphism detection (AFLPD), polymerase chain reaction (PCR), DNA sequencing, allele specific oligonucleotide (ASO) probes, and hybridization to DNA microarrays or beads. Genotyping is important in research of genes and gene variants associated with disease. Due to current technological limitations, almost all genotyping is partial. That is, only a small fraction of an individual’s genotype is determined.

1.5.20.1 Discrimination of recrudescent from new infections by molecular genotyping Many Plasmodium falciparum genes show extensive genetic polymorphism which can be used for genetic finger printing. High polymorphism has been shown in merozoite surface protein msp l, msp 2 and glurp genes in different geographical locations in malaria endemic areas (Aubouy et al., 2003). These loci have been used in many trials to distinguish recrudescence from new infections. Because of their extensive polymorphism, it is highly unlikely for a patient in areas of intense transmission to become newly infected with a parasite possessing an identical genotype

70 during follow-up because this probability is the product of individual allele frequencies of each allele of the three genes. Therefore, by comparing the genotypes of these three loci together at baseline and at the time of parasite recurrence, recrudescent can be distinguished reliably from new infections. However, there is variation not only in the sample analysis but also in interpretation of genotyping data, limiting comparison of data from various sites. Recurrent parasites can be potentially classified into four categories based on the degree of allelic matching: (i) all alleles in the baseline and recurrent parasites are identical, (ii) some alleles are missing in the recurrent parasites (iii) recurrent parasites contain alleles identical to those at baseline with additional/new ones not observed at baseline (iv) alleles in the baseline and recurrent parasite samples are different. It is generally accepted that categories (i – iii) represent recrudescent and (iv) new infection (Happi et al., 2004). Some investigators (Kyabinze et al., 2003) consider that category (iii) represents a new infection because of the appearance of new alleles. It is believed that, resolution of symptoms and parasite clearance are regarded as the most accurate measures of the intrinsic resistance of the parasites to a drug. The controversy surrounding category (iii) has not been resolved and the need for standardized genotyping protocol has been recognized. Interpretation of genotyping data may be complicated by (i) re-infections with new parasites possessing identical genotypes to those present on Day 0 may lead to an erroneous diagnosis of recrudescence, (ii) inability of PCR to detect all clones present on Day 0 whose reappearance may therefore be regarded as a new infection and (iii) micro-epidemics in which the same parasite(s) circulates over and over again in the same small population e.g. a household. However, the first possibility is negligibly low when two or more discriminatory markers are being used. The second possibility is also low because it has been shown that symptomatic infections are less complex than asymptomatic ones. Therefore, single time-point samples may reliably represent all subpopulations present on Day 0. Nonetheless, these weaknesses point to the need for some caution in interpreting PCR- adjusted treatment outcomes.

1.5.21 Restriction fragment length polymorphism In molecular biology, restriction fragment length polymorphism (RFLP) is a technique that exploits variations in homologous DNA sequences. It refers to a difference between samples of homologous DNA molecules that come from differing locations of restriction enzyme sites, and to a related laboratory technique by which these segments can be illustrated. In RFLP analysis,

71 the DNA sample is broken into pieces (digested) by restriction enzymes and the resulting restriction fragments are separated according to their lengths by gel electrophoresis. RFLP analysis was the first DNA profiling technique inexpensive enough to see widespread application. In addition to genetic fingerprinting, RFLP was an important tool in genome mapping, localization of genes for genetic disorders, determination of risk for disease, and paternity testing

1.5.21.1 Technique of Restriction Fragment Length Polymorphism The basic technique for detecting RFLPs involves fragmenting a sample of DNA by a restriction enzyme, which can recognize and cut DNA wherever a specific short sequence occurs, in a process known as a restriction digest. The resulting DNA fragments are then separated by length through a process known as agarose gel electrophoresis, and transferred to a membrane via the Southern blot procedure. Hybridization of the membrane to a labeled DNA probe then determines the length of the fragments which are complementary to the probe. An RFLP occurs when the length of a detected fragment varies between individuals. Each fragment length is considered an allele, and can be used in genetic analysis.

RFLP analysis may be subdivided into single locus probe (SLP) and multi-locus probe (MLP) paradigms. Usually, the SLP method is preferred over MLP because it is more sensitive, easier to interpret and capable of analyzing mixed-DNA samples. Moreover, data can be generated even when the DNA is degraded (e.g. when it is found in bone remains.)

1.5.21.2 Applications of RFLP Analysis of RFLP variation in genomes was a vital tool in genome mapping and genetic disease analysis. If researchers were trying to initially determine the chromosomal location of a particular disease gene, they would analyze the DNA of members of a family afflicted by the disease, and look for RFLP alleles that show a similar pattern of inheritance as that of the disease. Once a disease gene was localized, RFLP analysis of other families could reveal who was at risk for the disease, or who was likely to be a carrier of the mutant genes.

RFLP analysis was also the basis for early methods of Genetic fingerprinting, useful in the identification of samples retrieved from crime scenes, in the determination of paternity, and in the characterization of genetic diversity or breeding patterns in animal populations.

1.5.22 Agarose gel electrophoresis This is a method of gel electrophoresis used in biochemistry, molecular biology, and clinical chemistry to separate a mixed population of DNA or proteins in a matrix of agarose. The proteins may be separated by charge and or size (IEF agarose, essentially size independent), and the DNA and RNA fragments by length (Kryjdushkin et al., 2003). Biomolecules are separated by applying an electric field to move the negatively charged molecules through an agarose matrix, and the biomolecules are separated by size in the agarose gel matrix (Sambrook, 2001)

Agarose gels are easy to cast and is particularly suitable for separating larger DNA of size range most often encountered in laboratories, which accounts for the popularity of its use. The separated DNA may be viewed with stain, most commonly under UV light, and it can be extracted from the gel with relative ease. Most agarose gels used are between 0.7 – 2 % dissolved in a suitable electrophoresis buffer.

The agarose polymer contains charged groups, in particular pyruvate and sulphate. These negatively-charged groups create a flow of water in the opposite direction to the movement of DNA in a process called electroendosmosis (EEO), and can therefore retard the movement of DNA and cause blurring of bands. Higher concentration gel would have higher electro-osmotic flow. Low EEO agarose is therefore generally preferred for use in agarose gel electrophoresis of nucleic acids, but high EEO agarose may be used for other purposes. The lower sulphate content of low EEO agarose, particularly low-melting point agarose, is also beneficial in cases where the DNA extracted from gel is to be used for further manipulation as the presence of contaminating sulphate may affect some subsequent procedures, such as ligation. Zero EEO agaroses however are undesirable as they may be made by adding positively-charged group and such groups can affect subsequent enzyme reactions.

A number of factors can affect the migration of nucleic acids: the dimension of the gel pores (gel concentration), size of DNA being electrophoresed, the voltage used, the ionic strength of the

73 buffer, and the concentration intercalating dye such as ethidium bromide if used during electrophoresis (Lucotte, 1993). Smaller molecules travel faster than larger molecule in gel, and double-stranded DNA moves at a rate that is inversely proportional to the log10 of the number of base pairs. This relationship however breaks down with very large DNA fragments, and separation of very large DNA fragments requires the use of pulsed field gel electrophoresis (PFGE).

For standard agarose gel electrophoresis, larger molecules are resolved better using a low concentration gel while smaller molecules separate better at high concentration gel. High concentrations gel however requires longer run times (sometimes days). The movement of the DNA may be affected by the conformation of the DNA molecule, for example, supercoiled DNA usually moves faster than relaxed DNA because it is tightly coiled and hence more compact. In a normal plasmid DNA preparation, multiple forms of DNA may be present (Richard, 1994). The rate at which the various forms move however can change using different electrophoresis conditions, and the mobility of larger circular DNA may be more strongly affected than linear DNA by the pore size of the gel (Aaij et al., 1972)

Ethidium bromide which intercalates into circular DNA can change the charge, length, as well as the superhelicity of the DNA molecule; therefore its presence in gel during electrophoresis can affect its movement. Agarose gel electrophoresis can be used to resolve circular DNA with different supercoiling topology (Donald et al., 1995). The rate of migration of the DNA is proportional to the voltage applied, i.e. the higher the voltage, the faster the DNA moves. The resolution of large DNA fragments however is lower at high voltage. The mobility of DNA may also change in an unsteady field - in a field that is periodically reversed, the mobility of DNA of a particular size may drop significantly at a particular cycling frequency (Zimm et al., 1992). This phenomenon can result in band inversion in field inversion gel electrophoresis (FIGE), whereby larger DNA fragments move faster than smaller ones.

The negative charge of its phosphate backbone moves the DNA towards the positively-charged anode during electrophoresis. However, the migration of DNA molecules in solution, in the absence of a gel matrix, is independent of molecular weight during electrophoresis (Zimm et al., 1992). The gel matrix is therefore responsible for the separation of DNA by size during

74 electrophoresis, and a number of models exist to explain the mechanism of separation of biomolecules in gel matrix. A widely accepted one is the Ogston model which treats the polymer matrix as a sieve. A globular protein or a random coil DNA moves through the interconnected pores, and the movement of larger molecules is more likely to be impeded and slowed down by collisions with the gel matrix, and the molecules of different sizes can therefore be separated in this sieving process (Zimm et a., 1992)

Since DNA is not visible in natural light, the progress of the electrophoresis is monitored using colored dyes. Xylene cyanol (light blue color) co-migrates large DNA fragments, while Bromophenol blue (dark blue) comigrates with the smaller fragments. Less commonly-used dyes include Cresol Red and Orange G which migrate ahead of bromophenol blue. A DNA marker is also run together for the estimation of the molecular weight of the DNA fragments. However, the size of a circular DNA like plasmids cannot be accurately measured using standard markers unless it has been linearized by restriction digest, alternatively a supercoiled DNA marker may be used.

DNA as well as RNA is normally visualized by staining with ethidium bromide, which intercalates into the major grooves of the DNA and fluoresces under UV light. The ethidium bromide may be added to the agarose solution before it gels, or the DNA gel may be stained later after electrophoresis. Destaining of the gel is not necessary but may produce better images. Other methods of staining are available, examples are SYBR Green, GelRed, methylene blue, brilliant cresyl blue, Nile blue sulphate, and crystal violet (Sameh, 2012). SYBR Green, GelRed and other similar commercial products are sold as safer alternatives to ethidium bromide as it has been shown to be mutagenic, although the carcinogenicity of ethidium bromide has not actually been established. SYBR Green requires the use of a blue-light transilluminator. DNA stained with crystal violet can be viewed under natural light without the use of a UV transilluminator which is an advantage; however it may not produce a strong band.

When stained with ethidium bromide, the gel is viewed with an ultraviolet (UV) transilluminator. Standard transilluminator use wavelengths of 302/312-nm (UV-B), however exposure of DNA to UV radiations for as little as 45 seconds can produce damages to DNA and affect subsequent procedures, for example reducing the efficiency of transformation, in vitro transcription, and

PCR (Brody, 2004) Exposure of the DNA to UV radiations therefore should be limited. Using higher wavelength of 365 nm (UV-A range) causes less damage to the DNA but also produces much weaker fluorescence with ethidium bromide. Where multiple wavelengths can be selected in the transilluminator, the shorter wavelength would be used to capture images, while the longer wavelength should be used when it is necessary to work on the gel for any extended period of time. The transilluminator apparatus may also contain image capture devices, such as a digital or polaroid camera, that allow an image of the gel to be taken or printed.

Applications of Gel electrophoresis

• Estimation of the size of DNA molecules following restriction enzyme digestion, e.g. in restriction mapping of cloned DNA. • Analysis of PCR products, e.g. in molecular genetic diagnosis or genetic fingerprinting

• Separation of restricted genomic DNA prior to Southern transfer or of RNA prior to Northern transfer.

1.5.23 Purpose of study The general objective of this study was to evaluate malaria diagnostic methods, assess the efficacy of AL and investigate genetic variations in a selected gene (Pfmdr 1 - Plasmodium falciparum multi-drug resistant) of Plasmodium falciparum in patients treated with AL drug for uncomplicated malaria in Nigeria.

The specific objectives of the study were: 1. To determine the sensitivity and specificity of malaria diagnostic methods used in Nigeria, 2. To evaluate the present clinical and parasitological therapeutic efficacy of artemether- lumefantrine (AL) against uncomplicated P. falciparum malaria in Enugu, Nigeria 3. To determine the prevalence of mutation in Pfmdr 1 gene (N86Y, Y184F, S1034C, N1042D and D1246Y) in patients. 4. To compare the prevalence of mutation in Pfmdr 1 gene in patients with AL treatment failure and those with AL good response 5. To evaluate the selection for genetic variation in Plasmodium falciparum in the presence of AL therapy

CHAPTER TWO

MATERIALS AND METHODS 2.1 Study design The study employed an experimental and prospective design. The study had 2 phases; Phase 1 was controlled and carried out in the hospital setting over a period of 10 months. This phase was prospective as patients were monitored over a period of 28 days. Phase 2 was carried out in the laboratory were all sample analysis were done. This phase was experimental.

2.2 Study period The study was carried out for a period of 15 months from January 2012 to March 2013.

2.3 Study area The study was conducted in three Local Government Areas, in Enugu State: Nsukka, Igbo-Eze North and Nkanu East. Enugu State is located in the South Eastern Nigeria. It was created in 1991 with its capital in Enugu. It was formerly known as Anambra North. Enugu and Nsukka are its major towns. It is made up of 17 local government areas. The State is predominantly agricultural with yam tubers, palm produce and rice being their main produce. The State has a population of 2,101,016 (992,104 males and 1,108,912 females) within a total area of 7,618 sq. km. It has a population density of 268 persons per sq. km which is high compared with the average national persons per sq. km. Enugu is in the malaria endemic zone and can be characterized by a stable perennial transmission of malarial infection throughout the year (Federal Ministry of Health, 2005).

The study was conducted in three selected hospitals: District Hospital Nsukka, Bishop Shanahan Hospital, Enugu-Ezike, and Cottage Hospital Ugbuawka. Bishop Shanahan Hospital and Cottage Hospital Ugbuawka are situated in rural area while District Hospital Nsukka is situated in an urban area. District Hospital Nsukka and Bishop Shanahan Hospital are secondary health facilities with functional laboratory units which have two laboratory assistants headed by a Laboratory Scientist with over ten years working experience. Cottage Hospital Ugbuawka is a primary health facility with two laboratory technicians having over eight years working experience. They carry out all laboratory investigations requested by the clinicians.

2.4 Sample size and power analysis For the purpose of this research work, sample size was calculated thus: Sample size for comparing two proportions. Expected proportions “success” in the control group = 0.5 Significance level (alpha) = 0.05 (two tailed) N = 150 and power = 90 %. Sample size was calculated to be 150.

2. 5 Inclusion and exclusion criteria v Out – patients from six years and above presenting with symptoms compatible with acute uncomplicated malaria, a body temperature of ≥ 37˚C or history of fever in the 24 – 48h preceding presentation, were enrolled (Noedl et al., 2008). v Informed consent was obtained from parents for children and from patients in case of an adult patient before enrolment. Hence a consent form designed for the study was signed by each patient or their parents (Appendix 1) v Patients with history of antimalarial use in the past 2weeks before presentation and infants and young children below 6 years were excluded v Patients with complicated malaria, sickle cell, known allergy to study drug, and HIV positive were also excluded.

2.6 Enrolment of patients According to the guidelines for malarial treatment with ACTs, any patient presenting with fever or history of fever, (in the past 48 h) in the absence of danger signs and prior use of ACTs, should be presumptively treated with recommended first line treatment for uncomplicated malaria. Two hundred (200) patients were approached for participation in the study while 160 gave consent. One hundred and sixty patients (160), who presented with symptoms such as headache and fever, to the study hospitals, were examined using RDT kit. Patients’ demographic information, body temperature readings, presence of clinical symptoms and duration of illness were captured using patients’ data collection form designed for the study (Appendix 7) taken and recorded. Each patient that tested positive by RDT kit (Premier Medical Corporation, Nigeria) PLDH/ HRP2 combo cassette test or negative but were highly symptomatic, received tablets of AL in the following order (Dokomajilar et al., 2006) as shown in table 2.1

Table 2.1: Course of AL treatment

Body Age (yr) Duration (Days / Time) weight 1 2 3 (kg) 0 h 8 h 24h 36h 48h 72h

5 - 14 < 3 1 taba 1 tab 1 tab 1 tab 1 tab 1 tab

15 - 24 > 3 – 8 2 tab 2 tab 2 tab 2 tab 2 tab 2 tab

25 - 34 > 9 – 14 3 tab 3 tab 3 tab 3 tab 3 tab 3 tab

> 34 > 14 4 tab 4 tab 4 tab 4 tab 4 tab 4 tab

a = each tablet of AL contains 20mg of artemether and 120mg of lumefantrine

Each tablet of AL contains 20mg of artemether and 120mg of lumefantrine. Patients who tested negative by first response but were symptomatic with body temperature of ≥ 37 °C were also enrolled and treated with AL tablets. Since many hospitals in Nigeria treat uncomplicated malaria infection by administering AL without fatty foods; the study was designed to represent this scenario. Hence AL drug was not taken with fatty meal, even though it has been shown that fatty meal improves absorption (Zurovac et al., 2008). A compliance form (Appendix 8) designed to help the patient take appropriate dose at the right time was given to each patient along with drug and was submitted on the next follow up visit. This was used to assess patient compliance.

During the follow up days participants received incentives which include: free blood pressure check and treatment for adults, patient counseling on general health care, free snacks and soft drinks.

2.7 Sample collection Finger prick blood was obtained for rapid diagnostic testing by first response. About 2 ml of venous blood samples was collected into EDTA bottle which was carefully labeled and identified, from patient that tested positive by first response and others who were symptomatic on day 0 before treatment with AL. The blood samples were transported in a cold chain to Safety Molecular Pathology Laboratory, Enugu (SMPL) within five hours of collection, where all laboratory testing were carried out. Patients were then monitored and followed up for 28 days. Follow up blood samples, body temperature and blood pressure readings were obtained on days 3, 7, 14 and 28 post treatment (Sisowath et al., 2005) for microscopy and molecular analysis.

Prior to patient testing, safety precautions taken were • Gloves and Lab coats were worn. • Working benches and pipettes were cleaned with 70 % IPA (Isopropanol-acetic acid), kits and reagents were all set on bench • Liquid waste for disposing blood plasma was prepared and treated with 70 % IPA. • All sharps were disposed into the sharp bin. • Spillage was avoided but on occurrence was cleaned immediately to avoid contamination.

• Work sheet for each reaction was prepared and kept ready for recording results as soon as it is ready to avoid error.

2.8 Rapid diagnostic test for detection of Plasmodium falciparum Ten RDT kits were randomly picked and validated with known positive malaria samples before use. All RDT kits used for this study were supplied by the study team to the three study sites for uniformity and reliability of result. Each kit was labeled with patient’s number. Patients’ index finger was swabbed and pierced with a sterile lancet provided with the kit. 5 µl of blood was scooped with a loop by the laboratory assistant, added to the sample well in a cassette followed by three drops of sample diluent. Results were read within 20 min. The procedure was carried out according to the manufacturer’s instructions. The tests were considered positive when the antigen and control lines were visible in their respective windows, negative when only the control line is visible and invalid when the control line was not visible. Faint test lines were considered positive.

2.9 Thick films microscopic detection of Plasmodium falciparum About 20 µl of blood was used in preparing thick smear of blood in a clean slide, which was dried and stained with Giemsa stain. Dried slides were viewed at x100 with oil immersion by certified Medical Laboratory Scientists. Parasitemia was estimated assuming 8000 white blood cells/µl of blood for each patient (Humphrey et al., 2007). The pictures of the slides were captured and results recorded electronically. Slides were stored in a secure slide box and were re- confirmed by a senior scientist with over ten years of microscopic examination experience. The laboratory personnel were blinded of the first response results. The readings from the senior scientist were taken as final.

2.10 Extraction of DNA using saponin hemolysis P. falciparum genomic DNA was extracted from blood collected in EDTA bottle on arrival to SMPL by saponin hemolysis (Orijih et al., 2008). Saponin powder (Sigma Life Science, Germany) was dissolved in physiological saline, pH 7.4, to obtain a 0.5 % solution. It was prepared every day the test was performed, and kept refrigerated or on ice when not in use. Unless stated otherwise, all centrifugation procedures in this study were done at 4000rpm, using

81 a bench-top centrifuge. After DNA extraction, genomic yield and purity of each sample were carefully recorded using SMPL work sheet for routine test (Appendix 9).

Protocol for extraction of DNA using saponin hemolysis About 1 ml of the test blood sample was transferred to a sterile 15 ml plastic tube, capped with a screw cap, and centrifuged in a 15 ml centrifuge (JENELAB, England) for 10 min to remove the plasma. The pellet, which contained both erythrocytes and leukocytes, was washed twice with 5 ml of sterile saline (Invitrogen, USA). The volume of the pellet after the washing was usually 0.3-0.6 ml. It was loosened by vortexing (gentle agitation) on a vortex mixer (BioCote, UK) before 2 ml of cold saponin solution was added to the tube, and quickly mixed by inverting and tapping at the bottom of the tube repeatedly until all the cells had been suspended. The tube was placed on ice and allowed to stand for 20 min, mixing occasionally to keep the cells in suspension, and at the same time monitor the progress of hemolysis. After 20 min, the tube was centrifuged for 5 min and the supernatant was discarded. The process was repeated with 1 ml saponin solution, and incubated on ice for 15 min. The process is aimed at hastening red blood cell lysis. The suspension was centrifuged for 5 min to obtain pellet. 500 µl of 1x phosphate buffer saline (PBS) (Invitrogen, USA) was added to the pellet, vortexed and centrifuged for 5mins to dissolve the DNA from the pellet. The supernatant was discarded and the step repeated. This was followed by addition of 50 µl of AE buffer (Invitrogen, USA) (a mild alkaline buffer used for DNA elution because of its ability to stabilize DNA). Solution was vortexed and incubated in heating block (TECHNE, England) at 99 ˚C for 10 min. The solution was centrifuged after boiling at 8000 rpm for 1min and the DNA rich supernatant was collected in a 2 ml tube. The extracted DNA was used immediately for nested PCR detection of P. falciparum and the remaining was stored at -20 ˚C in appropriately labeled storage 1.5 ml tubes.

2.10.1 Determination of quality of DNA extracted After DNA extraction, the yield and purity of the DNA was determined using BioPhotometer Plus® (eppendorf, Germany). Steps 100 µl of AE buffer was transferred into a cuvette (Alpha lab, UK) and used to blank the machine with absorbance of 0 given. Then,

5 µl of the gDNA + 95 µl of AE buffer were transferred to a cuvette and placed on the spectrophotometer and absorbance read. Samples with absorbance values between 1.7–2.0 were accepted; otherwise rejected and DNA extraction repeated.

2.11 Validation of processes Prior to the molecular testing of the samples, ten samples were used for the optimization of condition such as temperature and time. The condition that gave optimum yield was used for the molecular testing.

2.12 Detection and amplification of plasmodial genomic DNA

2.12.1 Amplification of genus – Plasmodium by nested PCR PCR was used to amplify (multiply) more copies of Plasmodium genomic DNA. PCR testing was done in two rounds; Round one was done using a forward and reverse primer pair (rPLU5 and rPLU6 amplicon size 1200) as R1 for detection of genus; Plasmodium malaria. The PCR product from round one was used in round two in the Real time PCR, which also used a forward and reverse primer pair (rFal 1 and rFal 2 amplicon size 205 bp) as R2 for detection and quantification of the species of the Plasmodium; falciparum (Price et al., 2004). Reaction volume was 25 µl. The thermo-cycling conditions were determined after validation of processes. Reagent and materials • Purified Primer mix for Plasmodium detection. R1 comprised of rPLU5 forward primer5’-CCTGTTGTTGCCTTAAACTTC and rPLU6 backward primer - 5’- TTAAAATTGTTGCAGTTAAAAC • Commercially optimized Hot Start PCR master mix (Thermo scientific, Germany) • PCR tubes (VHbio) and pipettes (eppendorf, Germany ) • Ultra-pure water (Fermentas, Germany) for control • Working bench was cleaned with virkon (70 % Isopropanol), sample, primer and master mixes were equilibrated at room temperature.

Protocol for First Round PCR A work sheet was prepared using SMPL work sheet for 96 well plate (Appendix 10) to guide sample loading into each well.

Into each well of a labeled 96 well PCR plate the following reagent were added; 12.5 µl of PCR master mix, 7.5 µl of primer mix R1, and 5 µl of sample (gDNA). The reaction volume was 25µl. All reaction was done in duplicate.

The plate was capped properly and transferred to thermal cycler (Applied Biosystem 2720, Singapore) and ran with the program mal-g. Thermal profile for mal-g was 95 °C for 10 min 94 °C for 45 sec, 58 °C for 30 sec, 72 °C for 30 sec, 58 °C for 30 sec and 72 °C for 45 sec. The whole process ran for 35 cycles. Step “1 & 2” are referred to as denaturing or separation phase in the DNA, step “3 & 4” are referred to as annealing phase while step “5 & 6” are referred to as extension or amplification phase. At the end of the 35 cycles, the sample was prepared for Round two testing using Real Time PCR.

Reagent and materials • Syber Green master mix specific for quantification • Primer mix for falciparum detection: R2, rFAL 1 is forward primer 5’ TTAAACTGGTTTGGGAAAACC and rFAL 2 is backward primer 5’ACACAATGAACTCAATCATGA • PCR tubes and pipettes

2.12.2 Detection and quantification of Plasmodium falciparum species by Real time PCR Protocol for Round two by Real Time PCR A work sheet was prepared using SMPL work sheet for 48 well plate (Appendix 11) to guide sample loading into each well.

48 well PCR plate was labeled. Into each well, the following were added: 12.5 µl of Syber green master mix, 7.5 µl of R2 Primer mix and 5 µl of sample, (the product of the Round one PCR) The reaction volume was 25 µl, the same protocol as above was observed and samples were transferred to the real time cycler. Thermal profile for real time was 95 °C for 20sec, 95 °C for 30 sec, 60 °C for 30 sec,95 °C for 15 sec, 60 °C for 1min and 95 °C for 15 sec

2.13 Treatment responses Classification of treatment responses based on parasite clearance time (PCT) (Beshir et al., 2012) Response to drug treatment based on parasite clearance was assessed using WHO criteria (WHO, 1973) as shown in table 2.2

Table 2.2 Classification of Treatment responses based on PCT

Varibles Definition This is the time elapsing from drug Parasite clearance time (PCT) administration until there was no patent parasitaemia for at least 72 h.

In this study, this was defined as an incomplete Delayed parasite clearance parasite clearance after 72 h (day 3) instead of 48 h (day 2) since patients were not monitored after 48 h.

A patient is classified as sensitive to the drug Sensitive (S) when there is clearance of parasitaemia on day

3 without recurrence.

A patient is classified as having mild resistance Mild resistance (RI) to the drug when there is disappearance of

parasitaemia on day 3 which reappears within 7 to 14 days.

Moderate resistance (RII) A patient is classified as having moderate resistance to the drug when there is decrease of parasitaemia but no complete clearance from peripheral blood.

Severe resistance (RIII) A patient is classified as having severe resistance to the drug when there is no pronounced decrease or an increase in parasitaemia at 72 h after treatment.

Table 2.3 Classification of treatment responses based on therapeutic efficacy (WHO 2002)

Varibles Definition

This is the ability of a parasite strain to survive Parasite Resistance and/or multiply despite the administration and absorption of a drug in doses equal to or higher than those usually recommended but within the limits of tolerance of the subjects.

It is the development of danger signs for severe Early treatment failure (ETF) malaria on days 1, 2, or 3 in the presence of parasitemia: parasitemia on day 2 higher than day 0 count irrespective of axillary temperature; parasitemia on day 3 with axillary temperature ≥ 37.5 °C; parasitemia on day 3 ≥ 25 % of count on day 0.

It is the development of danger signs for severe Late Clinical Failure (LCF) malaria after day 3 in the presence of parasitemia, without previously meeting any of the criteria of ETF; presence of parasitemia and axillary temperature ≥ 37.5 °C or history of fever on any day from day 4 to day 28, without previously meeting any of the criteria of ETF.

It is the presence of parasitemia on any day Late Parasitological Failure (LPF) from day 7 to day 28 and axillary temperature < 37.5 °C, without previously meeting any of the criteria of early treatment failure or late clinical failure.

This is the absence of parasitemia on day 28 Adequate Clinical and Parasitological irrespective of axillary temperature without Response (ACPR) previously meeting any of the criteria of ETF, LTF, or LPF.

2.14 Genotyping of parasite genomic DNA for Pfmdr 1 N86Y, Y184F, S1034C and N1042D genes

Genotyping was based on the standardized PCR reaction and restriction fragment length polymorphism (RFLP). For amplification of the Pfmdr 1 gene coding region, a nested PCR protocol was adopted followed by RFLP. The PCR ran in two rounds. Round one was done with a primer pair for amplification of each Pfmdr 1 N86Y, Y184F, S1034C and N1042Dgenes. In Round 2, the same primers were used to amplify more specific copies of Pfmdr 1 N86Y, Y184F, S1034C and N1042D genes, where resistance - associated mutations are said to occur.

2.14.1 Amplification of Pfmdr 1 N86Y, Y184F, S1034C and N1042D genes Protocol for first and second round reaction About 6.3 µl of PCR master mix, 3.7 µl of primer for each mutation Pfmdr 1 (N86Y, Y184F, S1034C and N1042D) and 2.5 µl gDNA were transferred into 96 well PCR plate and capped properly. The plate was placed in a thermal cycler and reaction started. The reaction volume was 12.5 µl.

2.15 Pfmdr 1 gene enzyme digests by PCR-RFLP methodology The PCR-RFLP methodology was designed in order to identify wild type and mutant alleles of Pfmdr 1.The PCR product from previous reaction was used for the RFLP. Site specific restriction enzymes were used to digest the PCR amplicons. The enzymes were designed to cut the mutant allele of Pfmdr 1 gene while the wild type remains uncut. Four different restriction enzymes were used in this study. The primer sequences and PCR conditions were shown in Table 3.14.

Protocol for PCR-RFLP At the end of the round two of the nested PCR amplification of each Pfmdr 1 mutation, 5.5 µl of enzyme specific for each mutation, was added into 12.5 µl of Round two product. The plate was properly capped and placed in an incubator (DNP 9022A, SANFA) for 16 h for normal digest and 45 min for fast digest

2.16 Preparation of 2 % agarose gel Step 1 2 g of agarose (Topvision, USA) powder was weighed on an electronic weighing balance (Scout™ Pro, China) into a 500 ml conical flask. 100 ml of 1x TBE (Tris borate EDTA) buffer

(Fermentas, Germany) was measured using 500 ml measuring cylinder into the conical flask. The mixture was swirled till powder dissolved and microwaved for 60 sec to get a clear liquid (which was removed and checked at interval to avoid spilling over of mixture). 10 µl of ethidium bromide (USA) was added to the mixture and swirled gently. Ethidium bromide aids in making the band visible to human eyes. Step 2 About 60 ml of 1x TBE buffer was poured into buffer reservoir of the electrophoresis tank (BIO- RAD, Belgium) allowing slight spill over the gel sliding panel as shown in step 2 of figure 2.1 above. The buffer reservoir on the ends bears the positive and negative electrode. Biomolecules are separated by applying an electric field to move the negatively charged molecules through the agarose matrix, and the biomolecules are separated by size in the agarose gel matrix. Step 3 The gel mould (Embi Tech) was assembled by fixing the comb to fix firmly on the gel mould observing a space between mould plate and the bottom of the comb as shown in figure 2.1. The comb creates well (open holes) where samples are loaded for electrophoresis. If care is not taken and the wells are cracked, the sample will leak out leading to false result. Step 4 The hot TBE agarose mixture was poured into the gel mould up to a level marked in the mould and allowed to cool forming a tender clear gel. The gel when formed was gently removed from the gel mould and placed on the gel panel of the electrophoresis tank ready for use as shown in figure 2.1

Figure 2.1: Preparation of 2 % agarose gel (http://sciencefair.math.iit.edu/techniques/gelelectrophoresis)

2.17 Gel electrophoresis of digested gene All Nested PCR amplicons were electrophoresed on 2 % agarose gel. Electrophoresis of restriction digest was also done on 2 % agarose gel at a constant of 100 v/cm for 20-30 min. 5 µl of 50 bp DNA (ladder) was loaded in the first lane as the marker, while 5 µl of each sample was loaded in the remaining wells. After electrophoresis gel was visualized under ultra-violet (UV) light on a UV Trans-illuminator (Vilber Lourmart, France). The bands were viewed with UV radiation blocking spectacles (USA). Bands were snapped with camera and bracket (GenoMini, Leuven) and electronically stored.

2.18 Patients’ management Patients/guardians were given participant’s information sheet (Appendix 5) were a detailed explanation of the nature of the study was given. A form showing plan for protection of life of participants and the risk/benefits they will encounter was adopted (Appendix 6). These were all done before patients gave their consent.

2.19 Health research ethics approval The research methods of this study were screened and approved by the State Ethical Committee. Subsequently, ethical clearance was obtained from the Ethical Committee of University of Nigeria Teaching Hospital (UNTH) Ituku-Ozara. The reference number is NHREC/05/01/2008B-FWA00002458-IRB00002323 (Appendix 2) and management approval was obtained from the hospital administrations of the study hospitals (Appendix 3). This approval was gotten prior to patients sampling. A collaboration letter was also obtained from Safety Molecular Pathology Laboratory, Enugu (SMPL) were laboratory testing was done (Appendix 4)

2.20 Data analysis Data generated were summarized in Excel and analyzed using both Graph Pad (Prism 5) and SPSS (version 16). Measures of diagnostic accuracy of the different diagnostic techniques were determined by computing the sensitivity, specificity, positive and negative predictive values. Descriptive statistics presented as counts, percentages, means, and standard deviations, as

92 appropriate, were used to compare the demographic characteristics of the study population and their initial clinical and biological characteristics (such as temperature and geometric mean parasitaemia). Differences in proportions of treatment outcome and frequency in occurrence of Pfmdr 1 gene mutation in pretreatment and post treatment groups were analyzed using the Chi-Square test or Fisher’s exact test, while the differences in parasitic densities of the various groups were analyzed using ANOVA.

For analysis purposes, each isolate was coded on the basis of the presence or the absence of resistance-associated alleles (N86, F184, S1034 or N1042, where N is asparagine, F is phenylalanine, Y is thyrosine, S is serine, C is cystein and D is aspartate). Genotyping data at all four Pfmdr 1 loci were combined to determine whether the Pfmdr 1 N 86Y-Y184F-1034C- 1042D allele was present in pre- and post treatment samples.

CHAPTER 3 RESULTS 3.1 Socio-demographic profile of patients A total of 160 patients were recruited, two withdrew consent while four patients were non- compliant with drug administration and were excluded, remaining 154 patients which were sampled. Fifty four (35.1 %) were males while one hundred (64.9 %) were females. Age range was between 6 and 60 years, their mean age was 29.65±16.35 years. Twenty eight (18.2 %), twenty three (14.2 %), forty one (26.6 %) and sixty two (40.3 %) were between the ages of 6-11, 12-18, 19-30 and above 30 years. The mean duration of illness was 3.78±1.97 days. The patients’ characteristics are shown in Table 3.1.

3.2 Result of diagnostic techniques 3.2.1 Comparison of RDT with Microscopy Ten RDT kits that were tested for re-validation of kit all tested positive. One hundred and six (68.8 %) tested positive for both RDT and microscopy, while twenty five (16.2 %) patients tested negative in both RDT and microscopy. RDT had no false positive but twenty three (14.9 %) of the samples were false negative. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 82.17 %, 100.00 %, 100.00 % and 34.29 % respectively. Test of Significance (Chi Square test) showed statistical significant difference when RDT was compared to microscopy method (P ≤ 0.05), Table 3.2.

3.2.2 Comparison of RDT with PCR One hundred and one (65.6 %) of the patients tested positive for both RDT and PCR, while fifteen (9.7 %) patients tested negative in both RDT and PCR. Samples that were RDT positive but PCR negative were five (3.2 %) while those of first response negative but PCR positive were thirty three (21.4 %). Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 75.37 %, 75.00 %, 95.28 % and 31.25 % Test of significance (Chi Square test) showed statistical significant difference when RDT was compared to PCR method (P ≤ 0.05), Table 3.3.

3.2.3 Comparison of Microscopy with PCR Of the 154 patients, one hundred and twenty (77.9 %) tested positive for P. falciparum in both microscopy and PCR method while twelve (7.8 %) tested negative in both methods. Samples that tested positive by microscopy but negative by PCR were twelve (7.8 %) while microscopy negative, PCR positive were ten (6.5 %). The sensitivity, specificity, PPV and NPV were 92.31 %, 50.00 %, 90.91 % and 54.55 %. Test of significance (Chi square test) showed a significant difference between microscopy and PCR method (P ≤ 0.05), Table 3.4.

3.2.4 Cost and turn around time The cost (Naira) and turnaround time (minutes) for each diagnostic method in SMPL was 300, 500, 6000and 20, 45, 1440 for RDT, microscopy and PCR respectively. Table 3.5.

3.3. Result of treatment outcomes 3.3.1 Clinical symptoms A total of 7, 10, 14, and 14 patients were lost to follow up treatment on days 3,7,14 and 28 respectively. The demographic data and number lost to follow up are shown in Table 3.5. Clinical symptoms like headache and fever, reduced significantly with drug treatment. The highest body temperature recorded was 40 °C while the least was 36.7 °C on day 0. The total number of patients that had body temperature of 37.1- 40 °C was one hundred and ten (71.4 %) while forty four (28.6 %) had body temperature of 36.7 – 37 °C on day 0. On day 3, none of the patients had fever of ≥ 38 °C but seven (4.8 %) patients had body temperature of 37.1 - 37.6 °C. Four (3.7 %) patients on day 7, had body temperature of 38 °C. The distribution of temperature readings on the follow up days were shown in Table 3.6. A mean temperature of 37.40 °C, 36.28 °C, 36.28 °C, 36.21 °C and 36.11 °C were gotten on days 0, 3, 7, 14 and 28 as displayed in table 3.8. There was significant difference in the decrease in temperature from day 0 to day 28 (P < 0.0001).

3.3.2 Parasitemia densities on follow-up days The Real time PCR result showed that out of the 154 patients sampled, one hundred and twenty one (78.6 %) were infected with Plasmodium falciparum, while thirty three (21.4 %) were not. Mean parasite densities of 409±223, 190±315, 237±556, 135±318 and 193±371 for Days 0, 3,7,14 and 28 respectively. A comparison of the mean densities on follow up days showed that there were significant difference between day 0 and days 3,7,14 and 28 (P < 0.0001) while there

95 were no significant difference between day 3 compared to day 7 and day 14 compared to day 28 (P > 0.05) Tables 3.7.

3.3.3 Parasite clearance time (PCT) The study showed that sixty five (58.0 %) patients had delayed parasite clearance with PCT of more than 3 days on days 3 and 7, while forty seven (42.0 %) had total parasite clearance on days 3 with PCT of ≤ 3 days and were classified as sensitive (S) group. Out of the 65 patients twenty one (18.2 %), twenty two (19.6), and twenty two (19.6 %) were classified as RI, RII and RIII respectively. Of the 22 patients in RIII, four (6.06 %) had no change in parasite density. The classification of treatment outcome based on parasite clearance is shown in Table 3.8.

3.3.4 Clinical and parasitological PCR uncorrected responses on days 14 post treatment The study showed that on day 14 post treatment, of the 121 patients that were positive, eight (6.6 %) were lost to follow up treatment while 113 were eligible. The study did not record any early treatment failure (ETF), but four (3.5 %), nineteen (16.8 %), and ninety (80.0 %) had late clinical failure (LCF), late parasitological failure (LPF) and adequate clinical and parasitological response (ACPR). Out of the 35 patients of age ranges between 6 and 15 years, thirty two (91.4 %) had ACPR while three (8.5 %) failed treatment, whereas 51 patients with age ranges between 16 and 30 years had forty one (80.3 %) ACPR and ten (19.6 %) treatment failure. Thirty two (72.7 %) and fifty eight (84.0 %) of the patients with ACPR were resident in urban and rural areas respectively. The clinical and parasitological PCR uncorrected responses on days 14 post treatment were shown in Table 3.9

3.3.5 Clinical and parasitological PCR uncorrected responses on days 28 post treatment For 28 days post treatment, 14 patients were lost to follow up resulting to one hundred and seven (88.7 %) eligible patient. There was no early treatment failure as in day 14, while four (3.4 %), twenty three (21.4 %), and eighty (75 %) had late clinical failure (LCF), late parasitological failure (LPF) and adequate clinical and parasitological response (ACPR). Out of the 21.4 % patients with LPF, three (2.1 %) did not show any response, in terms of parasitaemia clearance/parasitological response as the parasite density remained the same after 3 days of treatment, while twenty (16.5 %) of the population had sub-optimal response with decreased parasitemia density on days 3 and 7. Younger patients with age range between 6 and 15

96 contributed 87.8 % of patients with ACPR. Other age ranges and their contribution to each treatment group with their area of habitation were shown in Table 3.10.

3.3.6 Parasite clearance and patients’ characteristics The study showed that patients with age ranges of 12-18 years had the least mean PCT of 4.21±2.80, while that of older patients with age ranges above 30 years was 9.28±8.06. Patients with temperature ≥ 37 ºC at day 0 had mean PCT of 6.46±3.26, while that of patients with absence of fever was 4.76±3.26. Patients with duration of illness ≤ 3 days had mean PCT of 5.02±3.76, while that of patients with duration of illness > 3 days was 7.33±5.66. Parasitemia level ≤ 500 resulted in mean PCT of 4.22±3.53, while levels > 500 resulted in mean PCT of 8.01± 6.93. Other patient demographic data and their mean PCT are shown in Table 3.11 There were significant differences among the mean PCT of the different age ranges, presence of fever, duration of illness and parasitemia level.

3.3.7 Parasite clearance and treatment outcome Forty seven patients classified as sensitive group, had mean PCT of 3±.000, while those classified as mild, moderate or severe resistance had mean PCT of, 9.66±7.18, 6.34±4.20 and 8.75±6.62 respectively. Delayed Parasite clearance or increased PCT significantly contributed to treatment outcome. (P < .0001). Patients that had good response post treatment had mean PCT of 5.15±3.75, while that of patients with treatment failure was 8.54±8.15. There was significant difference between the mean PCT of the two groups (P < .0001). The summary data is shown in Table 3.12.

3.4 Result of Pfmdr 1 gene genotyping The different mutation points, primer sequences for each SNP, PCR conditions and the enzyme used in digesting each mutation used in genotyping processes were all shown in Table 3.13.

3.4.1 Summary of genotyping One hundred and twenty one patients were genotyped, one hundred and sixteen (95.9 %) were successfully genotyped while five (4.1 %) failed. Sixty two (53.4 %) of the 116, had one form of mutation or another while fifty four (46.6 %) were wild types. The 121 patients were grouped into 2, they are; Patients that failed treatment and those that responded to treatment.

3.4.2 Criteria for selection of samples for each group Treatment failure group Twenty seven samples with late parasitological and clinical failure on day 28 post treatment, fourteen samples with increased parasitemia on day 3 and 7, and twenty four samples with mildly decreased parasitemia on day 3 were classified under this group. All were selected for genotyping resulting to a total of sixty five (53.7 %) samples under this group. The fifty samples in this group were the samples with delayed parasite clearance. Out of the 65 samples in this group, sixty (92.3 %) were successfully genotyped while five (7.7 %) failed.

Group that responded to treatment Fifty six (46.3 %) samples that had total parasitemia clearance on days 3 and 7 post treatment without parasitemia recurrence were selected under this group. Of the Fifty six samples, forty seven (83.9 %) were those classified as sensitive (S) based on parasite clearance; while nine (16.1 %) were from mild (RI) and moderate (RII) resistance groups. All samples were successfully genotyped.

3.4.3 Frequencies of Pfmdr 1 gene mutations and co-mutations among patients Twenty six (24.3 %), Twenty four (23.0 %) and nine (7.0 %) patients had N86Y, Y184F and S1034C mutations respectively, while eighteen (15.9 %), five (4.5 %) and three (2.8 %) patients were co-mutated with N86Y+Y184F, N86Y+S1034C and Y184F+S1034C co-mutations respectively. There was no patient with N1042D mutation. The frequencies are shown in Table 3.14.

3.4.5 Comparison of frequency of Pfmdr 1 gene in patients with sensitive, mild, moderate and severe resistance None of the patients in the sensitive group had N86Y mutation but three (13.6 %) and one (12.5 %) had Y184F and S1034C mutations respectively. Nine (34.6 %), seven (31.8 %) and one (12.5 %) patients with severe resistance had N86Y, Y184F and S1034C mutations respectively. The distributions of the mutations among other groups are shown in Table 3.15. There were significant differences in the frequencies of N86Y (P < 0.0001) and Y184F (P < 0.01) mutations among the treatment groups. There was no significant difference in the frequency of S1034D mutation among the treatment groups (P < 0.12).

3.4.6 Comparison of frequency of Pfmdr 1 gene in patients that failed treatment and those that responded to treatment The genotype result showed that twenty one (80.8 %), twenty five (96.2 %) and nine (15 %) of patients with treatment failure had N86Y, Y184F and S1034C mutations respectively, while in the group with good response, five (19.2 %) and one (3.8 %) had N86Y and Y184F mutations respectively. There was no patient with S1034D and N1042D mutation in good response group. Fifty nine (98.3 %) out of sixty samples in the treatment failure group had one form of mutation or another. The comparison was shown in Table 3.16. The cumulative effects of the three mutations were significantly associated with treatment failure (P < 0.001).

3.4.7 Comparison of frequencies of Pfmdr 1 co-mutation in patients with sensitive, mild, moderate and severe resistance Patients that were sensitive to AL treatment did not have N86Y+Y184F, N86Y+S1034C co- mutations but one (20.0 %) patient had Y184F+S1034C mutation. Seven (38.9 %), five (27.8 %) and six (33.3 %) patients in the mild, moderate and severe resistance groups had N86Y+Y184F co-mutation. There was significant difference in the frequency of N86Y+Y184F co-mutation among the treatment groups. (P < 0.0001). The frequencies of the mutations displayed in Table 3.17

3.4.8 Comparison of frequency of Pfmdr 1 co-mutation in patients that failed treatment and those that responded to treatment Three (16.7 %) and two (40.0 %) patients with good response had N86Y+Y184F and N86Y+S1034C co-mutations respectively, while fifteen (83.3 %), three (60.0 %) and three (100 %) of those with treatment failure had N86Y+Y184F, N86Y+S1034C and Y184F+S1034C co- mutations respectively. There were significant differences between the frequencies of N86Y+Y184F (P < 0.0001) and Y184F+S1034C (P < 0.04) among the treatment groups. The summarized data is shown in Table 3.18.

3.4.9 Comparison of frequencies of Pfmdr 1 mutations in pre and post treatment Prevalence of N86Y, Y184F and S1034C increased significantly from six (20 %) to twenty four (92.3 %), eight (5.2 %) to twenty five (92.6 %) and four (44.4 %) to nine (100.0 %) respectively in pre-treatment compared to post-treatment group (P < 0.001). The frequency distributions are displayed in Table 3.19.

Table 3.1: Patients’ characteristics

Patients’ characteristics Frequency (%) Mean ± SD Sex Male 54 (35.1) Female 100 (64.9) Age (Years) 6 – 11 (Children) 28 (18.2) 12 – 18 (Adolescence) 23 (14.9)

19 – 30 (Young adult) 41 (26.6) 29±16.35 Above 30 (Older adult) 62 (40.3) Residence Urban 71 (46.1) Rural 83 (53.1) Duration of illness (Days) ≤ 3 63 (40.9) >3 91 (59.1) 3.7±1.97

100

Table 3.2: Comparison of the performance of RDT with microscopy

Parameters Values (%)

Sensitivity 82.17

Specificity 100.00

Positive Predictive Value 100.00

Negative Predictive Value 34.29

RDT data analyzed

True positive 106 (68.8)

False positive 0 (0 )

True negative 25(16.2 )

False negative 23 (14.9 )

Total 154

(Table showing the statistical parameters (sensitivity, specificity, positive predictive value and negative predictive value in percentages) used to assess the performance of RDT when compared to microscopy and the data analyzed to get the parameters).

101

Table 3.3: Comparison of the performance of RDT with PCR Parameters Values (%)

Sensitivity 75.37

Specificity 75.00

Positive Predictive Value 95.25

Negative Predictive Value 31.25

Microscopy data analyzed

True positive 101 (65.6 )

False positive 5 (3.2 )

True negative 15 (9.7 )

False negative 33 (21.4 )

Total 154

102

Table 3.4: Comparison of the performance of microscopy with PCR

Parameters Values (%)

Sensitivity 92.3

Specificity 50.0

Positive Predictive Value 90.91

Negative Predictive Value 54.55

RDT data analyzed

True positive 120 (77.9 )

False positive 12 (7.8 )

True negative 12 (7.8 )

False negative 10 (6.5 )

Total 154

(Table showing the statistical parameters (sensitivity, specificity, positive predictive value and negative predictive value in percentages) used to assess the performance of microscopy when compared to PCR and the data analyzed to get the parameters).

103

Table 3.5: Cost and turnaround time of diagnostic methods

Diagnostic methods Cost (Naira) Time (minutes) RDT 300 20 Microscopy 500 45 PCR 6000 1440

104

Table 3.6: Temperature frequency distributions among patients on follow up days

Temperature ºC Day 0 Day 3 Day 7 Day 14 Day 28

≤ 36 0 29 (24.0) 46 (41.4) 62 (43.0) 54 (50.46)

36.1–37 44 (28.6) 88 (73.0) 63 (56.7) 58 (54.2) 52 (48.5)

37.1-38 65 (42.2) 4 (3.3) 1 (0.9) 3 (2.8) 1 (0.9)

38.1-39 36 (23.4) 0 (0) 4 (3.6) 0 (0) 0 (0)

39.1-40 9 (5.8) 0 (0) 0 (0) 0 (0) 0 (0)

Total (N) 154 121 121 121 121

Loss to follow up 0 8 10 8 14

Eligibility (n) 154 113 111 113 107

(A table showing different temperature ranges showed by patents and the number of patients having the temperatures during the follow up days)

105

Table 3.7: Mean parasite densities on follow up days

Follow Total Number of Mean densities Minimum Maximum up days parasite patients values values (± SD) densities

Day 0 49225 154 409.79±223.69 143 1475

Day 3 23492 113 190.17±315.26 0 600

Day 7 22871 111 237.27±556.36 0 1317

Day 14 14038 113 135.77±318.39 0 1839

Day 28 19834 107 193.75±371.08 0 1293

SD: Standard deviation

106

Table 3.8: Classification of treatment outcome based on parasite clearance time (n=121)

Variables Frequency (%) Classification of patients

Patients with delayed parasite 65 (58.0) RI, RII, or RIII clearance

Patients with total parasite 47 (42.0) S clearance on day 3 without recurrence

Parasite clearance on day 3 with 21 (18.8) RI recurrence on day 7 and 14

Decrease in parasitemia on day 3 22 (19.6) RII

Increase in parasitemia level on 22 (19.6) RIII day 3

(Table showing different levels of treatment outcome; S: Sensitive, RI: mild resistance, RII: moderate resistance, RIII: severe resistance, and the number of patients making up each group)

107

Table 3.9: Clinical and parasitological PCR uncorrected responses on days 14 post treatment

Parameters Total (%) Age (Years) Residence

6 - 15 16 - 30 ≥ 31 Urban Rural

No of patients 121 38 (31.4) 53 (43.8) 30 (24.8) 50 (41.3) 71 (58.7)

Lost to follow up 8 (6.6) 3 (37.5) 2 (25.0) 3 (37.5) 6 (75.0) 2 (25.0)

Eligibility 113 (93.3) 35 (31.0) 51 (45.1) 27 (24.0) 44 (88.0) 69 (97.2)

ETF 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

LCF 4 (3.5) 1 (2.8) 3 (5.8) 0 (0) 0 (0) 4 (100)

LPF 19 (16.8) 2 (10.5) 7 (13.7) 10 (37.0) 12 (27.2) 7 (10.1)

Total failure 23 (20.3) 3 (8.5) 10 (19.6) 10 (37.0) 12 (27.2) 11 (16.0)

ACPR 90 (80.0) 32 (91.4) 41 (80.3) 17 (63.0) 32 (72.7) 58 (84.0)

(ACPR, adequate clinical and parasitological response; PR, parasite resistance; LPF, late parasitological failure; LCF, late clinical failure; ETF, early treatment failure)

108

Table 3.10: Clinical and parasitological PCR uncorrected responses on days 28 post treatment

Parameters Total (%) Age (Years) Residence

6 - 15 16 - 30 ≥ 31 Urban Rural

No of patients 121 38 (31.4) 53 (43.8) 30 (24.8) 50 (41.3) 71 (58.7)

Lost to follow up 14 (11.5) 5 (37.5) 5 (35.7) 4 (28.5) 10 (71.4) 4 (28.6)

Eligibility 107 (88.4) 33 (30.8) 48 (44.8) 26 (24.3) 40 (37.4) 67 (62.6)

ETF 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

LCF 4 (3.4) 1 (3.0) 3 (6.2) 0 (0) 0 (0) 4 (6.0)

LPF 23 (21.4) 3 (9.1) 7 (14.6) 13 (50.0) 13 (32.5) 10 (15.0)

Total failure 27 (25.5) 4 (12.1) 10 (20.8) 13 (50.0) 13 (32.5) 14 (20.9)

ACPR 80 (75.0) 29 (87.9) 38 (79.2) 13 (50.0) 27 (67.5) 53 (79.1)

ACPR, adequate clinical and parasitological response; PR, parasite resistance; LPF, late parasitological failure; LCF, late clinical failure; ETF, early treatment failure.

109

Table 3.11: Distribution of mean parasite clearance time among patients’ characteristics Variables Frequency Parasite clearance time (days) Age (Years) Mean (±SD)

6-11 25 4.68±3.23

11-18 21 4.21±2.80

19-30 27 5.22±3.99

> 30 35 9.28±8.06

Gender

Male 33 6.09±7.38

Female 73 6.32±4.95

Fever ≥ 37.5ºC

Absent 34 4.76±3.26

Present 79 6.43±5.28

Duration of illness

≤ 3 36 5.02±3.73

>3 77 7.33±5.66

Parasitemia level

≤ 500 53 4.22±3.53

> 500 60 8.01±6.93

Residential area

Urban 44 6.71±6.03

110

Rural 69 6.25±5.78

Table 3.12: Parasite clearance time and treatment outcome

Treatment outcome Frequency Mean PCT (± SD) P – Value

(n) (day)

Based on PCT

Sensitivity 47 3.00±.000

Mild resistance 21 9.66±5.18

a Moderate resistance 21 6.34±4.20 0.0001

Severe Resistance 16 8.75±6.62

Based on ACPR

Good response 56 5.15±3.75

Treatment failure 65 8.54±8.15 0.0001b

(A table comparing PCT value between the two treatment groups; a = P. value for the different treatment responses based on PCT, b = P. value for the different treatment responses based on ACPR. ACPR = adequate clinical and parasitological response).

111

Table 3.13: Polymorphic gene investigated, mutation sites, primer sequences, PCR conditions and restriction enzymes

Gene Mutatio Primer sequence PCR Enzyme n conditions digest Pfmdr N86Y 5’ATGGGTAAAGAGCAGAAAG 94 °C-10 Dra Ia 1 AG3’ min,94 °C-1 5’CGTACCAATTCCTGAACTCA min, 72 °C-10 C3’ min, 50 °C-1 min, 72 °C-1 min, 4 °C-hold Y84F 5’CAAGAAGGAAGTAAGTATCC 94 °C-10 Dra IIa AAAAATGG3’ min,94 °C-1 5’CTGAAGGCATCTAACATGGA min, 72 °C-10 TATAGC3’ min, 50 °C-1 min, 72 °C-1

min, 4 °C-hold S1034C 5’CAAGAAGGAAGTAAGTATCC 94 °C-10 Hae IIIb AAAAATGG3’ min,94 °C-1 5’CTGAAGGCATCTAACATGGA min, 72 °C-10 TATAGC3’ min, 50 °C-1 min, 72 °C-1 min, 4 °C-hold N1042D 5’TATGTCAAGCGGAGTTTTTG 94 °C-10 Hin FIb C3’ min,94 °C-1 5’TCTGAATCTCCTTTTAAGGAC min, 72 °C-10 3’ min, 50 °C-1 min, 72 °C-1 min, 4 °C-hold a Normal Digest

112 b Fast Digest

Table 3.14: Frequencies of Pfmdr 1 mutations and co-mutations among the patients and their restriction enzymes

Frequency (%)

Pfmdr 1 mutations Restriction enzymes Negative Positive

N86Y Dra I 81 (75.5) 26 (24.3)

Y184F Dra II 87 (77.0) 24 (23.0)

S1034C Hae III 106 (93.0) 9 (7.0)

N1042D Hin Fl 116 (100) 0 (0)

Co-mutations

N86Y+Y184F 95 (84.1) 18 (15.9)

N86Y+S1034C 106 (95.5) 5 (4.5)

Y184F+S1034C 106 (97.2) 3 (2.8)

113

Table 3.15: Comparison of prevalence of Pfmdr 1 mutations in patients with sensitivity, mild, moderate and severe resistance

Parameter Sensitive Mild (%) Moderate Severe P - (%) (%) (%) Value

N86Y Negative 47 (50.0) 8(9.9) 15 (18.5) 11 (13.6)

Positive 0 (0) 10 (38.5) 7 (26.9) 9 (34.6) 0.0001

Y184F Negative 28 (54.3) 8 (11.4) 13 (18.5) 11 (15.7)

Positive 3 (13.6) 5 (22.7) 7 (31.8) 7 (31.8) 0.01

S1034C Negative 46 (47.4) 14 (47.4) 19(19.6) 18 (18.6)

Positive 1 (12.5) 3 (37.5) 3 (37.5) 1 (12.5) 0.12

114

Table 3.16: Comparison of prevalence of Pfmdr 1 mutations in patients that failed treatment and those that responded to treatment

Pfmdr 1 mutations Good responsea Treatment failure P - Value N86Y Negative 65 (80.2) 16 (19.8)

Positive 5 (19.2) 21 (80.8) 0.001

Y184F Negative 52 (75.4) 17 (24.6)

Positive 1 (3.8) 25 (96.2) 0.0001

S1034C Negative 67 (69.1) 30 (30.9)

Positive 0 (0) 9 (100) 0.019

a refer to patients that responded to AL treatment

115

Table 3.17: Comparison of prevalence of Pfmdr 1 co-mutations in patients with sensitivity, mild, moderate and severe resistance

Pfmdr1 Co-mutations Sensitive (%) Mild (%) Moderate (%) Severe (%) P-Value

N86Y+Y184F

Negative 45 (45.5) 15 (15.2) 20 (20.2) 19 (19.2)

Positive 0 (0) 1 (20.0) 2 (40.0) 2 (40.0) 0.647

N86Y+S1034C

Negative 47 (54.0) 9 (10.3) 17 (19.5) 14 (16.1)

Positive 0 (0) 7 (38.9) 5 (27.8) 6 (33.3) 0.0001

Y184F+S1034C

Negative 44 (44.4) 14 (14.1) 22 (22.2) 19 (19.2)

Positive 0 (0) 2 (66.7) 0 (0) 1 (33.3) 0.06

116

Table 3.18: Comparison of prevalence of Pfmdr 1 co-mutations in patients that failed treatment and those that responded to treatment

Pfmdr 1 Co-mutations Good response Treatment failure P – Value

N86Y+Y184F

Negative 65 (74.4) 22 (25.3)

Positive 3 (16.4) 15 (83.3) 0.0001

N86Y+S1034C

Negative 65(65.7) 34 (34.3)

Positive 2 (40.0) 3 (60.0) 0.242

Y184F+S1034C

Negative 65(65.7) 34 (34.3)

Positive 0 (0) 3 (100) 0.020

117

Table 3.19: Comparison of prevalence of Pfmdr 1 mutation in pre and post treatment

Pfmdr 1 mutations Pre-treatment Post-treatment

Negative (%) Positive (%) Negative (%) Positive (%)

N86Y 24 (80.0) 6 (20.0) 2 (7.7) 24 (92.3)

Y184F 19 (70.4) 8 (5.2) 2 (7.4) 25 (92.6)

S1034C 5 (55.6) 4 (44.4) 0 (0) 9 (100)

118

119

CHAPTER FOUR DISCUSSION 4.1 Diagnostic methods Correct and prompt malaria diagnosis remains the fulcrum of successful malaria control globally, whereas, wrong diagnosis of malaria forms another symptom of weak public health systems in industrialized and developing nations. The importance of accurate diagnosis is emphasized by the need for physicians and healthcare workers, who are ill-equipped to deal with the large number of patients visiting hospital and clinic, to be guided by laboratory results. This will help to avoid or minimize "defensive" and unnecessary prescriptions as a means of forestalling potential complications. A dearth of proper diagnostic facilities and laboratories in poorer nations will leave physicians and healthcare workers with no other option than to engage in the kind of symptom-based guesswork that often leads to wrong diagnosis and increased likelihood of wrong prescription.

The new treatment guideline for malaria in Nigeria relies on the 3Ts (Test, Treat and Track), with the intention of slowing and/or preventing resistance to the recommended drug, artemisinin combination therapy - ACT (artemether-lumefantrine) for treatment of uncomplicated malaria. Hence, for a complete handling of a case of malaria, each patient must be tested before treatment while appropriate records are kept for surveillance purpose. Key factors that influence malaria testing include analytical reliability of diagnostic method, cost of test/affordability, accessibility and turnaround time.

Presently, RDT, microscopy and PCR are the three diagnostic methods used in Nigeria, each with its respective shortcomings. Since RDTs might not be very sensitive in detecting malaria especially in areas with varying transmission intensities as shown by some studies (Hopkins et al., 2008, Wongsrichanalai et al., 2007) and both RDTs and microscopy have their limitations in detecting malaria infections (Hopkins et al., 2008; Bell et al., 2005; Mens et al., 2007), there is need to use a more accurate diagnostic method such as PCR in assessing the accuracies and reliability of these diagnostic methods, even though most evaluations of RDTs have used microscopy as gold standard (Ruiz et al., 2002; Mc Morrow et al., 2008). Hence in this study, the reliability of RDT and microscopy were assessed using PCR as gold standard and for a balanced

120 comparison, a sub-analysis using microscopy was performed on RDT. PCR assay was used because it has the ability to detect malaria parasites in patients with low levels of parasitaemia. Infections with ≤ 5 parasites per μl can be detected with 100 % sensitivity and specificity (Snounou et al., 1993). Plasmodium falciparum was also preferred because this species causes most malaria morbidity in Nigeria.

4.1.1 Comparison of RDT with microscopy When microscopy was used as gold standard, the specificity and PPV of RDT were very high, suggesting that RDT has high tendency of accurately picking a malaria patient from a given population. The specificity and PPV were higher than that reported elsewhere (Batwala et al., 2010; Hopkins et al., 2008) while Harani et al., (2006) reported a similar specificity of 98.3 % for P. falciparum using an RDT kit; but a lower predictive PPV of 78.0 %. In this study, all the patients who were positive by RDT were confirmed to have malaria by microscopy, in other words, there was no false positive by RDT when compared to microscopy. This indicated that RDT was as effective as microscopy in detecting positive malaria cases. The high specificity/PPV might have been as result of the ability of RDT to react against a specific parasite antigen - Histidine rich protein 2 which is specific for detecting P. falciparum species. The sensitivity of RDT observed in this study was however lower than that reported by other studies with an unacceptably low NPV (Batwala et al., 2010; Harani et al., 2006; Stauffer et al., 2009). This low sensitivity and NPV observed implies that first response has low tendency of correctly predicting a negative patient. This was evidenced by the fact that almost half of the patients tested negative by first response were confirmed to be positive by microscopy while the remaining half were true negatives. By implication, RDT may not be reliable in malaria diagnosis when its result is negative especially in cases where symptoms are present.

4.1.2 Comparison of first RDT with PCR When PCR was used as gold standard, RDT showed a lower sensitivity and specificity than when compared to microscopy, but maintained a high PPV and an unacceptably low NPV. The high PPV and low NPV were similar to that obtained when compared with microscopy. It was also observed that greater percentage of patients who tested positive by RDT were also confirmed to have malaria by PCR as in microscopy, while very few who were positive with first response tested negative by PCR. This implies that RDT is highly reliable when it detects a

121 positive patient, indicating that RDT has a high probability of classifying a sick patient as being sick, leading to prompt and adequate treatment. The few percentages of patients that were false positive suggest that there is little or tiny chances of RDT to classify a healthy patient as sick. These few patients with false positive result by RDT are likely to be patients with persistently circulating antigen due to prior use of anti malarials. On the other hand, two third of the patients that tested negative with first response were confirmed to have malaria by PCR, while one third were confirmed to be truly negative. The high false negative observed with first response signifies that it has high probability of classifying sick patients as healthy, thereby leading to wrong diagnosis by clinicians and denying sick patients of prompt/appropriate treatment. This will lead to progression of infection from uncomplicated to severe malaria and if eventually diagnosed treatment will be cumbersome and involves admission in most cases. Increased cost both directly and indirectly with resultant loss of man power for adult and absence from school for children will be the long term effect. This implication was also observed in a trial carried out in Tanzania where clinicians prescribed antimalarials in patients with a negative test as often with RDTs as with microscopy (Reyburn et al., 2007). The underlying problem appears to be that clinicians are often unsure of what to do when clinical features are compatible with malaria, but the malaria diagnostic test is negative. False negative results could be attributed to the fact that parasite antigen levels were too low to be detected as a result of very low parasitaemia or by semi-immune parasite carriers with low parasitaemia.

The sensitivity, specificity and NPV recorded in this study are lower than what was obtained in another study (Batwala et al., 2010). For confident diagnosis of malaria in a routine outpatient practice, a sensitivity of > 90 % is critical (WHO, 2003) and this was not achieved by first response. First response therefore fell short of the required critical level of sensitivity with the potential consequences of missing infections in individual who might even have had low immunity.

4.1.3 Comparison of microscopy with PCR Microscopy showed a higher sensitivity, PPV and NPV, but had a lower specificity than RDT, indicating that microscopy performance is better than RDT when compared to PCR in the study areas. Similar to RDT, greater percentage of patients that tested positive by microscopy were confirmed to have malaria by PCR. However microscopy had more true positive than RDT,

122 which indicates that microscopy was able to detect more sick patients correctly than RDT. Microscopy detected positive cases in excess of PCR and had a higher false positive than RDT, suggesting that even though microscopy has the ability to detect malaria patients, it has a higher propensity of classifying a healthy patient as sick than RDT. This would lead to treatment of a patient without malaria infection (parasitemia), thereby exposing a healthy patient to treatment. The danger in this situation is that it will lead to development of resistance to the treatment drug. In the case of uncomplicated malaria treatment in Nigeria, artemether-lumefantrine is the drug at risk.

A small percentage of patients enrolled who were negative with microscopy were confirmed positive by PCR. This percentage was smaller than that observed in RDT. This shows that microscopy has a lower tendency of classifying a sick patient to be healthy compared to first response. This false negative observed may be attributed to the ability of PCR to detect P. falciparum DNA from circulating non viable parasite after successful treatment (Karbwang, 1996). The percentage of false negative recorded for microscopy in this study is lower than what was gotten from another study (Tangpukdee, 2009), which reported a high percentage of 67 % of patient who have been classified as negative by microscopy to be actually positive by PCR. Another study also recorded slightly higher false negative of 37 % (Batwala et al., 2010).

4.1.4 Factors contributing to observed performances by the different diagnostic methods Both methods showed low specificity and NPV, while RDT only showed low sensitivity when compared to PCR. Some factors may be responsible for the low performances observed in the use of RDT and microscopy in the diagnosis of malaria. First, the choice of PCR method as the ‘gold standard’ for comparison might influence the outcome of our finding as previous studies used blood film microscopy as their comparator. PCR method is a more sensitive and specific diagnostic method than both microscopy and RDT. The specificity is due to the use of highly purified specific primers which enables it to accurately detect particular specie of interest in Plasmodium and amplify a copy of Plasmodium DNA in a background of one million human DNA. An important use of PCR method is in detecting mixed infections or differentiating between infecting species when microscopic examination is inconclusive. Besides, PCR assays have been developed for the detection of malaria DNA from whole blood as either single, nested,

123 allele specific or multiplex methods. These assays have been used for the initial diagnosis; follow-up to treatment, and as sensitive standards against which other non-molecular methods could be compared.

RDTs are more specific than microscopy, since it is antigen specific and in this study the target antigen HRP 2 is P. falciparum specific, while microscopy depends on the ability of the laboratory scientist to differentiate between the species by virtue of either colour or structure. The lower specificity value observed for microscopy could be caused by subjectivity in reporting of blood films in addition to inter-observer differences in blood film reporting which are known to influence blood film outcomes. Generally, the reliability of microscopy is questionable particularly at low levels of parasitemia and in the interpretation of mixed infection (Hamer, 2007, Murray, 2008). The possible reasons for the false positive result may be due to, poor blood film preparation which generates artifacts commonly mistaken for malaria parasites, including bacteria, fungi, stain precipitation, dirt and cell debris (Ohrt, 2002). It is important to note that inappropriate use of anti-malarials may result to low parasitaemia levels which could affect the performance of microscopy.

Secondly, undue exposure of RDTs to > 70 % humidity and/or > 30 °C temperature especially in the supply chain, may affect the quality of testing. In Nigeria, the National Policy on Malaria Diagnosis and treatment states that RDTs should be deployed in situations where microscopy may not be possible due to lack of adequate laboratory facilities or as a compliment to the use of microscopy in secondary health facilities. As a follow up, RDT kits have been supplied by the different agencies under Roll Back Malaria Program to different health centers in Nigeria. In most cases, due to logistic and other political protocols, kits are not supplied promptly and under required optimal conditions to the final facilities where they are being used. In addition storage of these kits under approved temperature and humidity are also not guaranteed at the different facilities.

Thirdly, false negative results observed in RDT performance may be caused by deletion or mutation of the HRP -2 gene in the Plasmodium (Bell et al., 2003). It has also been suggested that natural anti-HRP-2 antibodies in some individuals leads to reduced HRP 2 expression (Chiodini et al., 2007). Patients under this category never give a positive result with RDTs and

124 will also cause false negative results despite significant parasitemia. Finally, the low sensitivity observed in this study may result from the use of patients > 5 years of age. A study by Batwala et al 2010, revealed that the sensitivity of RDT was significantly higher than that of other techniques and was excellent in children < 5 years of age 97.7 % (95 %, CI: 88-99.9) compared to those ≥ 5 years 83.7 % (95 %, CI: 69.3-93.2).

The use of Nested PCR as the gold standard instead of microscopy agrees with recent studies by Andrade et al., 2010 and Batwala et al., 2010. They indicated that Nested PCR was the gold standard for diagnosis of both symptomatic and asymptomatic malaria in the Brazilian Amazon because it detected major number of cases and presented maximum specificity while microscopy showed a low performance of 65.1 % correct diagnosis. In another study by Coleman et al., 2006, it was observed that although PCR performance appeared poor when compared to microscopy, data indicated that the discrepancy between the two methods resulted from poor performance of microscopy at low parasite densities rather than poor performance of PCR. Hence, the study concluded that PCR appears to be a useful method for detecting Plasmodium parasites during active malaria surveillance in Thailand. Data from this study highlights the problem of using a less-than-perfect diagnostic test as a reference standard.

However, PCR also has its limitations such as false negative results due to failure of the target DNA to amplify because the target sequence recognized by primers is absent or because it is present but inaccessible. This absence of the target sequence may be due to deletion/mutation of sequence homologous to the primers, degradation of DNA during sample preparation or storage. In addition, if the correct target sequence is present, amplification may fail due to inhibition of PCR by sample components. On the other hand, target DNA may not be accessible because of inadequate cellular lysis, or the target sequence copy number may be too low for amplicons to be detected under conditions used. Nonetheless, PCR remains a reference tool both clinically and in research.

4.1.5 Cost and turn-around time of the different diagnostic methods Our study revealed PCR method to be the most expensive and time consuming while RDT is the least in terms of both variables. This implies that although the PCR method is ultra-sensitive, reliable and amenable to high throughput, it requires a bigger capital outlay to establish as well

125 as a balanced skill mix to operate daily on the part of the health giver and more waiting time with significant high cost on the part of the patient. Hence with such high cost and turnaround time, PCR method of malaria diagnosis will not thrive in a poor and holo-endemic area like Nigeria for routine malaria diagnosis. The urgency and importance of obtaining results quickly for patients with suspected malaria limits the usefulness of PCR in routine clinical practice. Furthermore, in malaria endemic areas, limited financial resources, persistent sub-clinical parasitaemia and inadequate laboratory infrastructures in remote settings preclude PCR as a diagnostic method. On the other hand, RDT with a turnaround time of few minutes, shows that it is simple to perform, rapid and easy to interpret, requires less training, very affordable and thus it is applicable for field conditions. Microscopy gave an average turnaround time and cost, which was higher than RDT but lower than PCR.

4.2 Responses following treatment with artemether - lumefantrine In 2005, Nigeria adopted artemether - lumefantrine as the drug of choice for the treatment of uncomplicated malaria in all public health facilities and independent drug marketers (Patent Medicine Vendors). The policy pronouncement was based on clinical trials mainly with children carried out in six Geo-political zones in Nigerian 2002 and 2004, and on the widely acclaimed efficacy of artemether–lumefantrine globally (Federal Republic of Nigeria, 2010). Since children are less likely to develop resistance to drug and when used in efficacy trial may not represent the actual response that may be observed in an average adult patient and very few therapeutic studies has been done with adult, this study made use of patients of all ages since the approved drug is taken across all age groups even though it is known that the use of adult in efficacy trials of antimalarial may give rise to variability in outcomes (World Health Organization, 2003). However children below the age of six were excluded to minimize non- compliance during drug administration and follow up days. It is also imperative to note that the study used out-patients and did not administer drugs with any fatty food. This was done to create a scenario that depicted what is obtainable in real life in this part of the country, as almost all patients take their drug after normal meal without emphasis on the fatty aspect of the food. This would help to evaluate the efficacy of the drug without bias.

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4.2.1 Clinical responses with reference to fever clearance Body temperature of ≥ 37 ºC is a cardinal feature of malaria, and is associated with constitutional symptoms of lassitude, weakness, headache, anorexia and often nausea. Treatment is with antipyretics and tepid sponging. AL is known for high fever clearance rate and it is postulated that the rapid fever clearance is due to the activity of artemether which has a shorter half-life while the sustained action was by lumefantrine.

Patients treated in this study showed good responses clinically as AL was able to clear fever totally in a greater percentage of patients 72 h post treatment. Patients were not monitored on days 1 and 2; hence the fever clearance time was observed on day 3. The high fever clearance was maintained on other follow up days during monitoring. This shows that AL is still active in fever clearance among malarial patients in the study area and can be relatively relied upon in cases of acute malaria attack where immediate symptomatic relieve is needed. However, very few patients had sub-optimal fever clearance 72 h post treatment, with a few percentages showing body temperature between 38 and 39 ºC on day 7. This percentage that had sub-optimal fever clearance and recurrent body temperature on days 3 and 7 resulted in late clinical failure (LCF). This was observed in older patients suggesting that AL clears fever more rapidly in children than in adult in the study population. Almost one third of the patients were afebrile on day 0, following intake of paracetamol prior to hospital visitation.

4.2.2 Response based on parasitemia clearance Resistance to artemisinin-based combination therapy (ACT) has been documented from Southeast Asia and has been observed in patients that show no significant decrease in drug susceptibility in vitro. Evidence is accumulating that the parasite clearance time after ACT therapy is increasing in Asia and Africa and clinical studies have identified delayed parasite clearance time as the most robust marker of artemisinin resistance (Flegg et al., 2011, Beshir et al., 2012). Therefore, there is great interest in surveillance studies of early parasite clearance to provide an early warning system for the emergence/spread of artemisinin resistance in areas where this has not be previously documented. However, accurate characterization of the clinical phenotype of delayed parasite clearance may be complicated by a number of factors acting independent of artemisinin resistance, such as drug concentrations, pharmacodynamic properties

127 of the partner drug, pre-treatment parasite density, and host immunity. The use of sampling multiple times a day at measured time points to estimate the rate of parasite clearance has been proposed as an accurate and reliable method for the early detection of artemisinin resistance (Flegg et al., 2011). However, this approach may be difficult to implement in settings of routine in vivo drug efficacy studies among outpatients. An alternative approach is to measure the detectable proportion of patients with parasitaemia one, two or three days after the initiation of therapy (Stepniewska et al., 2010, Das et al., 2013). Hence in this study, detectable proportion of patients with parasitaemia three days after the initiation of therapy was employed; while response to drug treatment based on parasite clearance was assessed using World Health Organization criteria (WHO, 1973). These criteria were used in this study because they best describe the nature of parasitaemia readings gotten from the qPCR results.

4.2.2.1 Patients with total parasite clearance on day 3 Following initiation of therapy, one third of the patients had total parasitaemia clearance on day 3 without recurrent parasitemia on other follow up days. This proportion of patients was classified as being sensitive to AL therapy. This group of patients was mainly younger patients. This implies that AL is more effective in younger patients than in older patient as was observed in the fever clearance, where older patients contributed to late clinical failure. However, analysis of pre-treatment parasite density showed that the patients classified as being sensitive had moderate to low parasite density compared to other groups with delayed parasite clearance.

4.2.2.2 Patients with delayed parasite clearance Our study showed high prevalence of patients with delayed parasite clearance after initiation of therapy, suggesting that there is development of resistance to AL in the study area. Among these patients with delayed parasite clearance, it was observed that some had decreased parasitaemia on days 3 and 7 and were classified as being moderately resistant to AL treatment. This shows that there is slow parasitaemia clearance as against rapid parasitaemia clearance in these patients which could arise from novel parasite genotypes with reduced drug sensitivity. Such patients will experience delayed recovery from malaria attack following AL treatment. This group of patients is not totally resistant to AL therapy, but is an indicator that reveals dwindling in the efficacy of AL in uncomplicated malaria treatment. Their pre-treatment parasite densities were observed to be higher than those obtained in the group that is sensitive to the drug which could have

128 contributed to the delay in parasite clearance time. Our finding differs greatly from a study carried out with younger patients that revealed that out of 90 children treated with AL 6 (6.6 %) had delayed PCT (Sowunmi et al., 2010).

4.2.2.3 Patients with increased parasitaemia level Another group of patients showed increased parasitaemia level on day 3 showing severe resistance to AL treatment. This implies that plasmodium in this group of patients resisted treatment and is termed parasite resistance, which is the ability of a parasite strain to survive and/or multiply despite the administration and absorption of a drug in doses equal to or higher than those usually recommended but within the limits of tolerance of the subjects. The presence of parasitaemia on day 3 is most likely to be recrudescence than re-infection. However, patients with increased parasitemia level could have been exposed to new mosquito bites and had become re-infected. On the other hand, a different school of thought may argue that the study drug should be able to protect the patient for at least 14 days post treatment against both re-infection and recrudescence. If this is true then, presence of parasitaemia within this time range is considered as a discredit to AL therapy. With this observation, it has to be clearly stated as to what extent AL drug protects a patient after initiation and completion of therapy. Pre-treatment parasite density was not associated to increased parasite density as almost more than half of the patients in this group had lower pre-treatment parasite density compared to other groups. Of great concern is the fact that all patients in this group except for one resulted in late parasitological failure.

4.2.2.4 Patients who did not show any response with respect to parasite clearance on day 3 It is noteworthy to state that while some patients had decreased or increased parasitemia level, a few percentages showed no response as their parasite densities remained the same at day 3 even after a repeat of the qPCR test. This observation reveals another group that is resistant to AL, even though there was no danger sign of severe malaria among them. This observation may have resulted from non compliance, since the patients were not in-patients and AL in-take was not directly observed. Another phenomenon that could lead to this observation is an increased propensity for these parasites to form dormant (or quiescent) rings under artemisinin exposure (Teusher et al., 2010; Witkowski et al., 2010). Under this condition, even when correct dosage is

129 achieved, the parasite will still avert the activities of AL. This could be the possible explanation for the above abnormality.

4.2.2.5 Patients with recurrent parasitemia on day 7 and 14 The study revealed that some of the patients, who had total parasitemia clearance on day 3 and 7 had recurrent parasitemia on day 7 and 14 respectively. This result suggests that patients may have been exposed to new mosquito bite since the study area is in an endemic zone with high malaria transmission, besides; participants were not restricted to those sleeping under insecticide treated nets. Therefore, this seems to be a case of re-infection rather than recrudescence. This result proves that AL therapy is not as effective in adult as it is in children when it comes to parasite clearance. Pre-treatment parasite density was associated with this observation as the entire patient in this group had high pre-treatment parasite densities especially those with recurrent parasitaemia on day 7.

Surprisingly, there were no danger signs of severe malaria in these patients with one form of delayed parasite clearance or the other, except for few that had body temperature of ≥ 37.5 ºC and accompanying headache. Fever and headache was treated with administration of paracetamol tablets according to age. The reason for the above finding may be that areas where infection with P. falciparum constantly occur (holoendemic), it appears that only a small proportion of the infected people fall ill even though they are infected with the Plasmodium. Therefore, it will be useful to differentiate between malaria as an infection and malaria as a disease. This finding indicates that presence of parasitemia on follow up days in these patients is malaria infection rather than disease. Besides, throughout the study, there was no case of P. falciparum infection developing from uncomplicated symptomatic malaria to severe malaria and finally fatal disease or death.

Despite increasing drug treatment failure, there is no clear guideline, at least in Nigeria, about the time to change anti-malarial drug treatment if parasites do not clear quickly from peripheral blood following treatment of uncomplicated acute infections. It is postulated in the present study that, parasite clearance exceeding three days is associated with risk of treatment failure and resistance and could be used as a criterion to change therapy. The present study reports the relationship between delay in parasite clearance and anti-malarial treatment failure in older

130 children and adults with P falciparum malaria in an area of intense transmission in south-eastern Nigeria,

4.2.2.6 Possible factors contributing to high prevalence of patients with presence of parasitaemia post treatment Malaria treatment efforts are hindered by the rapid emergence and spread of drug resistant parasites. Prevalence of resistance-associated mutations within a parasite population has been observed to be associated with delayed parasite clearance. The high prevalence of residual sub- patent parasitaemia after treatment in this study may be due to emergence of novel parasite genotypes with reduced drug sensitivity, inadequate population-level immunity, or the higher sensitivity of qPCR for detection of persisting and non viable parasites.

4.2.2.7 Parasite clearance and treatment response Association of PCT and therapeutic response was clinically and statistically significant (P ≤ 0.0001). Patients that were sensitive to AL treatment had lower PCT value while those under the resistant group had higher PCT value. However, patients that were classified as being moderately resistant (RII) to AL had a lower PCT value than those in the mildly resistant (RI) group. Even though this observation could not be explained, it was supported by the fact that majority of patients with delayed PCT especially those graded as RI and RIII had either late clinical or late parasitological failure. This implies that PCT is a good indicator for measuring treatment outcome and tool for monitoring development of resistance to drugs. Delayed parasite clearance was found to have significantly (P ≤ 0.0001) contributed to treatment failure in our study. This study is in congruence with a study carried out by Sowunmi et al., 2010, which revealed that 17 % of children with delay in parasite clearance subsequently failed therapy and they constituted 72 % of those who had drug failure.

4.2.2.8 Parasite clearance time and patients’ characteristics Patients’ characteristics were tested to show their association with parasite clearance in this study. Age (≥ 30 years), pre-treatment body temperature of above 37.5 ºC, increased pre- treatment parasite density and duration of illness of more than 3 days, were associated with delayed parasite clearance while difference in gender (male or female) and patient’s residence (urban or rural) had no effect on parasite clearance. For pre-treatment parasite density, this finding is expected given that time to parasite clearance is a function of the baseline parasite

131 density (White, 1997). This study showed that patients with greater pre-treatment parasite density had longer PCT than those with lesser parasite densities.

Adult patients are likely to engage in self-medication with artemisinin monotherapy (artesunate) or incomplete treatment with AL. It has been noted that suboptimal levels of drugs, possibly arising from failures to comply with recommended dosing regimens, or from long half-lives of certain hydrophobic drugs that remain in circulation from earlier treatments, probably contribute to a stepwise development of resistance (White, 1992). This could explain why older patients (≥ 30) had the highest PCT value while that of younger patients (≤ 18) had the least.

Patients with duration of illness > 3 days had higher PCT than those that visited the hospital within 3 days of falling ill. Longer duration of malarial attack leads to increase in number of erythrocyte being invaded by P. falciparum merozoites which will lead to erythrocyte structural changes like rigidity and adhesiveness. Owing to the increased adhesiveness, the red cells infected with late stages of P. falciparum (during the second half of the 48 hour life cycle) adhere to the capillary and post-capillary venular endothelium in the deep microvasculature (cytoadherence). The infected red cells also adhere to the uninfected red cells, resulting in the formation of red cell rosettes (rosetting). Subsequently, cytoadherence leads to sequestration of the parasites in various organs like kidney lung and brain. Sequestration of the growing P. falciparum parasites in these deeper tissues provides them the micro-aerophilic venous environment that is better suited for their maturation and the adhesion to endothelium allows them to escape clearance by the spleen and to hide from the immune system. These factors help the P. falciparum parasites to undergo multiplication, thereby increasing the parasite load to very high numbers. This will eventually lead to increased pre-treatment parasitaemia density in patients with longer duration of illness. By this trend, the study showed that increased duration of illness indirectly delay parasite clearance in patients with uncomplicated malaria in the study area.

Although early parasite clearance is predominantly a function of artemisinin activity, different formulations of the artemisinin component and partner drugs used in various ACT may also influence early parasite clearance. This result showed that delay in parasite clearance is multifactorial in origin with the host, pre-treatment parasite density and duration of illness

132 contributing almost equally to delay in clearance and subsequent failure of treatment in those with delay in parasite clearance. 4.2.3 Therapeutic responses to AL treatment 4.2.3.1 Adequate clinical and parasitological response at days 14 and 28 The Criteria for antimalarial treatment policy change states that the main determinant of antimalarial treatment policy is the therapeutic efficacy of the antimalarial medicines in use (WHO, 2002). Therapeutic efficacy monitoring involves the assessment of clinical and parasitological outcomes of treatment over at least 28 days following the start of adequate treatment to monitor for the reappearance of parasites in the blood (WHO, 2002).

Our study has shown reduced ACPR- PCR uncorrected, for both days 14 and 28 post treatment in older patients compared to previous studies done with children in the past years (Yeka et al., 2008, Humphrey et al., 2007). However, our finding is in agreement with a study by Falade et al., (2005), which recorded ACPR of 86.5 % PCR uncorrected and another study by Ukwe et al., (2010), that recorded reduced efficacy in parasitaemia clearance. This finding suggests that AL has a higher efficacy in younger children than in adults, which brings into limelight the fact that there is an emerging resistance to AL in older Nigerian patients. Day 14 had higher ACPR than day 28 indicating that 28 days post monitoring may not have an advantage over 14 days following AL treatment in a malaria endemic area where the risk of re-infection is very high.

4.2.3.2 Early treatment failure Early treatment failure involves the presence of parasitaemia and danger signs of severe malaria on day 3 post treatment. There was no early treatment failure for both days 14 and 28 even though there was high prevalence of delayed parasite clearance at day 3. This is due to the fact that people, who live in area with high rate of malaria transmission, have been exposed to malaria parasites bite several times. After the first exposure, immune system begins to protect such people from being symptomatic following re-infection and this may cause few or no symptoms. This implies that since these older patients are living in area with high malaria transmission, they have been exposed to high parasite densities and hence developed high immunity against certain levels of parasitaemia level which protected them from symptoms of danger signs of severe malaria.

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4.2.3.3 Late clinical failure and late parasitological failure Late clinical failure is associated with presence of parasitaemia and body temperature of ≥ 37.5 ºC on day 7 post treatment, while late parasitological failure is associated with presence of parasitaemia after 14 days. The study showed that a few percentages of the study patients had LCF, while greater percentages had LPF. This implies that majority of patients with presence of parasitemia following AL treatment in the study area, are not symptomatic, perhaps due to acquired immunity following long exposure to Plasmodium falciparum infection.

Recurrence of fever and parasitaemia more than two weeks after treatment could result either from recrudescence or new infection and this distinction can only be made through parasite genotyping by PCR. Since PCR is not routinely used in patient management in the study area, all treatment failures after two weeks of initial treatment, were considered as new infections, especially in areas of high transmission. Hence, cases of LCF are of more clinical importance than LPF since they are more likely to be recrudescence than re-infection.

4.2.3.4 Patients’ characteristics and therapeutic responses The impact of age on therapeutic response showed that a high percentage of patients that are younger (6 – 18 year) had good response compared to older (≥ 30) patients. In the same way younger patients had lower percentage parasitemia failure than in older patients. The possible explanation for this is that adults have different immunity level to malarial parasites and are more at risk of long term exposure to ACTs which might lead to reduced therapeutic efficacy of antimalarials unlike younger ones. A slightly higher percentage of patients leaving in urban area had therapeutic failure compared to those leaving in rural area. This observation could arise from inadequate exposure to AL drug by those leaving in urban areas since they are more likely to engage in self medication than those in rural area.

4.2.3.5 Factors that contributed to low ACPR observed in this study. Factors that may be responsible for the low therapeutic efficacy observed in this study includes: first, participants enrolled in our study were 70 % adult whom are known to show variability in treatment outcome, while children give better therapeutic response than adults. Secondly the study did not genotype the samples with increased or recurrent parasitemia to differentiate re- infection from recrudescence, and since Nigeria is an endemic area, most patients may have been

134 exposed to mosquito bite within the 28 days as the study was not limited to patients sleeping under long lasting insecticide treated nets. Thirdly, AL parasitological failures in this study might result from poor lumefantrine absorption. Oral bioavailability of lumefantrine has been shown to be considerably reduced during the acute phase of malaria and also to vary from one individual to another (Lim et al., 2009). Therefore it could be that the fraction absorbed by the patient who failed treatment did not equate the optimal curative levels, leaving some unaffected residual parasites which are likely to resurface some days later. Finally there might be an emerging resistance developing towards this drug of choice - AL by Plasmodium falciparum, in Enugu State, South Eastern Nigeria. This emerging resistance could be attributed to some genetic variations like mutations, single nucleotide polymorphisms (SNPs) and copy number variation (CNV) in plasmodial genes leading to AL resistance with significant decrease in plasmodial sensitivity.

It has also been observed that during in vitro susceptibility testing of parasites which cleared abnormally slow, there was essentially no shift in IC50 (50 % inhibition concentration) values by AL (Dondrop et al., 2009). This in-vitro observation differs from the known activities of artemisinins in vivo. This apparent discrepancy between the experimental and clinical data may be explained by the reduced susceptibility of Plasmodium parasite at only the ring stage (first third) of its 48 hours intra-erythrocytic developmental cycle (IDC) (Dondrop et al., 2009; Saralamba et al., 2011). The above observations may find their explanation in the fact that artemisinins, mechanism of action still remain unclear as wide range of explanations abide.

4.3 Genetic variations in Pfmdr 1 alleles The protozoan parasite Plasmodium falciparum causes severe malaria resulting in millions of deaths world-wide, a problem exacerbated by the emergence of resistance to almost all known anti-malarial drugs (WHO, 2008). Drug resistance has arisen through acquisition of mutations in drug targets and in drug transporters (Gregson et al., 2005). For example, mutations in the target genes dihydrofolatereductase (dhfr) and dihydropteroate synthase (dhps) led to resistance against the anti-folate drugs pyrimethamine and sulfadoxine, while mutations in transporter gene such as Pfcrt and Pfmdr 1 resulted in resistance to chloroquine and quinine (May et al., 2003). Artemether-lumefantrine presently represents the most important drug for the treatment of

135 uncomplicated malaria in the post-chloroquine and sulfadoxine-pyrimethamine era in Africa. Understanding the molecular basis of progression from susceptibility via tolerance to resistance of P. falciparum against this AL combination is fundamental for the establishment of measures to protect it from premature dismissal and will provide more solid ground for appropriate drug policies. Markers of tolerance, indicating emerging resistance will enable decision makers to change to more effective drugs before resistance has reached deleterious levels.

The involvement of Pfmdr 1 in anti-malarial resistance has been suspected since 1990s (Cowman et al., 1991) but practical use of this information has to wait for methodological improvements and availability of high quality quantitative PCR in endemic areas. In the recent years, the presence of Pfmdr 1 allele at codon 86 (N86Y), 184 (Y184F), 1034 (S1034C), 1042 (N1042D) and 1246 (D1246Y) have been shown to be associated with AL treatment failure or re-infection (Dokomajilar et al., 2006; Humphreys et al., 2007; Sisowath et al., 2005; Zongo et al., 2007). Pfmdr 1 polymorphisms may result from reduction in the therapeutic efficacy of this newly adopted combination treatment for uncomplicated P. falciparum malaria in Saharan countries of Africa. Increasing selection of Pfmdr 1 gene in asexual and sexual parasites following treatment of infections with artemether-lumefantrine (AL) indicates that there is a rising spectre of reduced responses to artemisinin-based combination therapy (ACT) in Africa (Happi et al., 2009).

For the purpose of this study, differentiation between re-infection and recrudescence was not carried out as this study was basically concerned with the occurrence of genetic variations in Pfmdr 1 gene in adult patients treated with AL and their contribution to AL treatment failure. In addition, artemisinins may also decrease malaria transmission since they act on the gametocytes, the parasite stage that is infectious to the mosquito vector hence should be active against re- infection (Pukrittayakamee et al., 2004). It has also been observed that using Pfmdr 1 86 as the marker of lumefantrine resistance, the selective window of lumefantrine has been estimated to last approximately 12 days, based on a model derived from one clinical trial (Hastings et al., 2005). If this statement is true then all recurrent parasitemia within 12 days should be treated as recrudescence. However, distinguishing a new infection from a recrudescent infection is particularly challenging in areas of high transmission where multiple genotype infections are common (Greenhouse et al., 2007). Identification of an identical genotype during follow-up is

136 not absolute proof of recrudescence just as identification of a different genotype could indicate recrudescence of a previously undetected minority genotype.

In order to prolong the efficacy of artemisinins, it is recommended that they should only be used in combination with another effective drug that has a longer half life. In this light, AL was chosen as the recommended treatments for first-line treatments for uncomplicated malaria. ACTs combine the short-acting artemisinins with longer-acting partner drugs, and were initially introduced in Southeast Asia, where transmission intensity is low and exposure to a new infection after therapy is rare. In contrast, in sub-Saharan Africa, where transmission is intense, individuals who have recently been treated for malaria infection are frequently exposed to new infections during the period of time when the partner drug level is waning. If new infections occur during the selection window of the partner drug, drug-resistant parasites will have a survival advantage. AL offers excellent efficacy, but in high transmission areas the relatively short half life of artemether leads to a high incidence of new infections soon after therapy (Kamya et al., 2007, Yeka et al., 2008).There is concern that frequent exposures of parasites to sub-therapeutic drug levels may allow for the rapid emergence of drug resistance. Data from studies in Africa indicate that the use of ACTs leads to the selection of parasites resistant to the long-acting partner drugs (Djimde et al., 2008; Holmgren et al., 2006, Martensson et al., 2005). The long-term effect of this selection is not yet known.

4.3.1 Genotyping of Pfmdr 1 gene among study patients Our study showed that more than half of the patients with P. falciparum infection had one form of Pfmdr 1 mutation or another while the remaining patients had wild type. This result confirms the prevalence of these mutations in the study area. The high prevalence of Pfmdr 1 mutation observed in this study indicates the possibility of nascent clones of P. falciparum with reduced susceptibility to the artemisinin derivatives in the study area. The 121 patients were categorized into two groups; those that failed treatment, and those that responded to treatment. More patients were categorized under treatment failure group. Those under treatment failure group were all patients with either increased parasitemia level on days 3 and 7 or late parasitological failure. Samples with decreased parasitemia levels on days 3 and 7 were also under treatment failure since AL is known for rapid parasitemia clearance by the rapid onset of action by artemether. A

137 delayed or slowed clearance was an indication of emerging resistance to the drug, hence the need for further evaluation of the patients for possible genetic variations. A few percentage of patient selected under treatment failure group failed genotyping while all in good response group were successfully genotyped. Possible reason why these samples failed genotyping might be that the amplified DNA were too small to be viewed by human eye using UV light as a result of low parasite count, since in genotyping, the amount of gDNA should be at least 100 ng.

4.3.2 Genotyping of group with treatment failure Analysis done showed that almost all the patients that had treatment failure, which were genotyped, had one form of Pfmdr 1 mutation or another. The most common allele of Pfmdr 1 gene in the P. falciparum patients were Pfmdr 1 N86Y and Y184F. This is indicative of a gradual gaining of stability of these genotypes in the Enugu Nigeria. This study was consistent with other studies carried out in Nigeria (Happi et al., 2009) and beyond (Dokomajilar et al., 2006; Menard et al., 2006). An important distinction between this study and others is that Happi et al., recorded a higher prevalence (88.0 %) by Pfmdr 1 Y184F while Menard et al., reported a lower prevalence (21.9 %) by Pfmdr 1 N86Y when compared to this study. This result indicates that there is circulation of parasites with reduced sensitivity to artemisinin derivatives. It is therefore not surprising that the majority of the patients with delayed PCT had treatment failure.

The S1034C allele was also observed but at a lower frequency while Pfmdr 1 N1042D allele was not observed in any of the patients. The absence of Pfmdr 1 N1042D allele within the study area supports the findings by Happi et al., (2009) and Dokomajilar et al., (2006), which reported that no sample assayed in their study area contained the Pfmdr 1 N1042D allele. However, it differs from another study carried out in Ghana where the prevalence of wild type of Pfmdr 1 N1042D allele was found to be very high from 2003-2010 (Duah et al., 2013). Presumptive diagnosis based on clinical grounds, improper diagnosis, lack of diagnostic facilities, and empirical treatment are common practices in resource-limited countries such as Nigeria, and these factors likely result in the continued exposure of negative patients to AL and denial of some positive patient of adequate treatment with AL. This will result in development and spread of resistant strains of P. falciparum.

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It is also important to note that artemisinins as a group differ in the routes they take in the human body to convert to the major active metabolite; dihydroartemisinin (DHA). Artemether is rapidly demethylated to the active metabolite dihydroartemisinin by CYP3A4 and CYP3A5. The major antimalarial activity of artemisinin is performed by DHA. People with poorly functioning CYP3A4 and CYP3A5 will have higher concentration of artemether and lower concentration of dihydroartemisinin. This could reduce the drug’s antimalarial activity, kill fewer parasites and increase potential artemether resistance. Such individual is likely to carry resistant strain of P. falciparum which when exposed to mosquito bite, the mosquito picks up this resistant strain (gametocytes) and on feeding on another host transmits this resistant strain onwards.

4.3.3 Genotyping of group that responded to AL treatment On the other hand the group that responded to AL treatment showed very low percentage prevalence of Pfmdr 1 mutations. The mutations observed in this group were Pfmdr 1 N86Y and Y184F at a frequency that was insignificant. None of the samples under this category had either Pfmdr 1 S1034C or N1042D. Possible reason for the occurrence of Pfmdr 1 mutation in patients with good response might be first; patients may have had incomplete AL treatment before enrolment but were not detected. This will subject the Plasmodium to sub therapeutic dose level of AL which will not be able to clear the Plasmodium from the blood. This suggests that mutation or SNP in Pfmdr 1 gene may not be the only mechanism of AL resistance by Plasmodium falciparum. Other mechanism like epigenetic mechanism can lead to development of a resistant strain in an individual. Epigenetic is concerned with how an organisms or parts of organisms look different, despite the fact that they have the same genes and are in the same environment (Holliday, 2006). Epigenetic experts believe that the environmental conditions and life experiences of parents, grandparents, and even great-grandparents can flip "on/off " on the genes in their eggs and sperm, or the genes of developing fetuses in pregnant women, thus changing the genetic code of their offspring and descendants (Holliday, 2006). In this way, new genetic traits can appear in a single generation, and be passed on to children, grandchildren, and beyond. Even though epigenetic mechanism has not been fully explored, it has been implicated as one of the key players in gene regulation, morphological differentiation and antigenic variation. Other

139 mechanisms might include differential gene expression, differential copy number and/or differential transcription of putative drug resistance gene.

Finally, our results also suggest that the presence of a particular mutation may not contribute to drug (AL) resistance. This suggestion is evident in Cambodia, where it was observed that the resistant phenotype detected in western Cambodia does not associate with any polymorphism in the established drug resistant marker (Dondrop et al., 2009).

4.3.4 The association between Pfmdr 1 mutations and AL therapeutic efficacy The presence of individual Pfmdr 1 allele at codon 86, 184 and 1034 in patients that responded to AL treatment were analyzed with respect to patients that failed treatment. It was observed that Pfmdr 1 N86Y allele was not present in the patients who were classified as sensitive using PCT but Pfmdr 1 Y184F and S1034C allele were present in a very few proportion. While most of the mutated Pfmdr 1 allele was found to be present in the RI, RII and RIII groups. The presence of N86Y and Y184F allele were found to be significantly (P < 0.01) higher in the resistant group than the sensitive group, while the difference in the prevalence of S1034C between the two groups was not significant (P = 0.12). This indicated that allelic variations of Pfmdr 1 gene contributed to AL resistance in the study population.

The prevalence of Pfmdr 1 mutation at codon 86, 184 and 1034 was also found to be significantly (P < 0.001) higher in the group that failed treatment than in the group that responded to treatment. The presence of Pfmdr 1 mutated allele was associated with AL treatment failures. These findings are consistent with those of a recent study from Tanzania (Humphreys et al., 2007) but are in contrast to those presented in a previous report from Uganda (Dokomarjilar et al., 2006), in which no association between the Pfmdr1 N-F-D haplotype and treatment failure was found. The cumulative effect of the mutations (Pfmdr 1 N86Y, Y184F and S1034C) contributed significantly (P > 0.01) to AL treatment failure. The prevalence of the individual mutations has no significant contribution to drug resistance. That it was a cumulative effect of the mutations that contributed to AL treatment makes the situation more stringent as fight against AL treatment failure will involve fight against multiple mutations. In order words the hypothesis that allelic variations of Pfmdr 1 gene contributes to AL resistance which this study tested was true. The survival advantage of gametocytes harboring the Pfmdr 1

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N-F-D haplotype after AL treatment suggests that the Pfmdr1 N-F-D haplotype may confer some fitness advantage to Plasmodium falciparum in the presence of AL.

4.3.5 Co-mutation and AL therapeutic response Co-mutation was observed in some isolates, with N86Y+Y184F mutation having higher prevalence than N86Y+S1034C and Y184F+S1034C. The prevalence of Pfmdr 1 co-mutation was higher in the group that failed treatment than in the group that responded, even though a few patients who responded to treatment had co-mutation. This may be due to the fact that in areas of high endemicity of Plasmodium falciparum, human hosts are often super infected with multiple clones of the parasite (Smith et al., 1999). The presence of mutant parasites with Pfmdr 1 co- mutation in the study area is a threat to AL therapy. Pfmdr 1 N86Y+Y184F (P ≤ 0.0001) and Y184F+S1034C (P ≤ 0.02) co-mutation significantly contributed to AL treatment failure as the clinical isolates with these co-mutations came from patients that had delayed parasite clearance. While Pfmdr 1 N86Y+S1034C co-mutation contribution was not significant (P ≥ 0.2).

4.3.6 The effect AL on Plasmodial gene pre and post treatment Positive samples for each SNP were analyzed pre and post treatment. Our study revealed that there was a significant increase from pretreatment to post treatment prevalence of Pfmdr 1 N86Y, Y184F and S1034D allele (P < 0.001). Our data also implied that before exposure to AL therapy, most isolates were wild type while soon after AL initiation; there was significant mutation in the Pfmdr 1 gene among the isolates. This result also indicated that allelic variations of Pfmdr 1 gene are associated with the outcomes of patients treated with AL; suggesting that single nucleotide polymorphism could be a defensive mechanism employed by Plasmodium falciparum in the presence of AL to avert the drug effect. This also implies that the presence of the study drug significantly induced genetic variation in the plasmodial genes. This could be as a result of continual exposure of malaria parasite populations to different drugs, hence selecting not only for resistance to individual drugs but also for genetic traits that favor initiation of resistance to novel unrelated antimalarials. The high frequency of malaria in Nigeria, coupled with a sole reliance on ACT treatment, poses a situation where selection and propagation of drug-resistant lineages is highly possible. The malaria treatment policy changed in 2005 from the use of chloroquine to the use of AL as the first-line drugs for the treatment of uncomplicated

141 malaria in Nigeria, increased the use of artesunate monotherapy, a component in the ACT which may contribute to drug pressure induced resistance.

Previous studies have shown that mutant allele of codon 184 is known to be selected after AL use in recrudescent samples (Gadalla et al., 2011; Zeile et al., 2012). Our report is in agreement with another study done at Uganda which reported that the prevalence of Pfmdr 1 N86Y allele increased significantly from 8 % in pre treatment sample to 43 % in post treatment (P < 0.0001), while that of Pfmdr 1 Y184F also increased significantly from 4 % to 14 % (Dokomajilar et al., 2006). Reports from Zanzibar (Sowunmi et al., 2007) showed a significant accumulation of the Pfmdr 1 N86, F184, and D1246 alleles, among patients who had parasites after AL treatment.

Hence the hypothesis that allelic variations in Pfmdr 1 gene are associated with the outcomes of patients treated with AL has been shown to be true by this study. These findings suggest that polymorphisms in the Pfmdr 1 gene are under AL selection pressure. Pfmdr 1 polymorphisms may result in reduction in the therapeutic efficacy of this newly adopted combination treatment for uncomplicated falciparum malaria in Nigeria

Some factors may have attributed to the increase in the prevalence of Pfmdr1 N-F-D haplotype that we observed after AL treatment compared to the prevalence in the baseline population. First, it is possible that these alleles are selected on a population level but not on an individual level with the recent increase in the use of AL at the study site. There are evidences that exposure of artemether-lumefantrine is the main contributor behind the observed selection of Pfmdr 1 N86, 184F, D1246 SNPs and that it plays a role also for selection of Pfcrt K76 (Sisowath et al., 2007). These evidences include the previously reported specific lumefantrine-driven selection among re-infections during follow up after artemether-lumefantrine treatment (Sisowath et al., 2007; Sisowath et al., 2009), and a recent study conducted in Tanzania, which shows that the selection of N86, 184F and D1246 after artemether-lumefantrine treatment in vivo is significantly associated with the ability to withstand higher lumefantrine concentrations (Malmberg et al., 2013).

Second, it is also possible that in AL-treated patients, lumefantrine may have selected parasites harboring the Pfmdr 1 N86, F184 and S1034D alleles or the Pfmdr1 N-F-D haplotype in new

142 infections emerging from the liver after clearance of artemether, this means that in areas with high rates of malaria parasite transmission in Africa, where re-infection is common and these Pfmdr 1 alleles are circulating, the long-term success of AL may be hampered by the emergence of drug-resistant malaria parasites. A third explanation for this finding is that the post-treatment parasitemia observed in this study were the result of parasites that bore signals of artemisinin selection and that survived the artemether concentrations in AL-treated patients. Finally, the post-treatment parasitemia may be caused by recrudescence of parasite subpopulations that were at very low densities in the pretreatment population.

4.4 Limitations of the study 1. The study did not differentiate recrudescence from re-infection which would have shown whether treatment failure was as a result of re-infection or recrudescence. 2. It did not include sequencing of gene to detect further genetic variations that may have led to AL resistance. 3. The sample size used was not large enough; the use of a larger sample size will result in a better representation of the true population of the study area. 4. The study did not check the bioavailability of AL in each patient considering the fact that some host factors can influence drug bioavailability which in turn affects response.

4.5 Conclusion The findings of this study indicate that microscopy is more sensitive than RDT (first response(R)) using PCR as standard and that the clinical and parasitological therapeutic efficacy of AL in adult Nigerian patients has reduced. It demonstrated that that there is high prevalence of Pfmdr 1 N86Y and F184Y with no incidence of Pfmdr 1 N1042D and that the prevalence of mutated allele of Pfmdr 1 is higher in patients who failed treatment than in those who had good response. It has confirmed that the presence of AL induced genetic variation in the plasmodial genes.

4.6 Further research

The study recommends further research on:

1. Newer modalities for multiple SNPs treatment.

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2. Other mechanisms of AL resistance by P. falciparum such as differential gene expression, copy number variation or presence of novel SNPs. 3. The bioavailability of AL in patients who are treated for uncomplicated malaria 4. Novel genes implicated in Plasmodium falciparum resistance to AL therapy.

4.7 Contribution to knowledge 1. This study has revealed that RDT may not be trusted when result is negative especially when symptom is present. 2. It has shown that AL therapy is more effective in children than in adult patients. 3. This study has confirmed that Pfmdr 1 N86Y, F184Y and S1034C gene occur in Nigerian malaria patients while N1042D does not 4. It has also shown that mutations in Pfmdr 1 genes contribute to AL treatment failure in Enugu, Nigeria. 5. There is now growing evidence for allelic selection after treatment with AL, demonstrating the importance of monitoring this combination closely in high transmission areas.

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APPENDIX 1

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APPENDIX 2

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APPENDIX 3

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APPENDIX 4

171

APPENDIX 5

172

173

174

175

176

APPENDIX 6

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APPENDIX 7

PATIENTS DATA COLLECTION FORM

EVALUATION OF THE RELIABILITY OF DIFFERENT MALARIA DIAGNOSTIC METHODS AND GENETIC DETERMINANTS OF Plasmodium falciparum RESISTANCE TO ARTEMETHER-LUMEFANTRINE THERAPY

PATIENT’S NO:

Dear Sir/Madam,

Please this questionnaire is purely for research on the above topic; hence you are required to supply us with information below before you can be enrolled into the study. We encourage you to be as objective and sincere as possible in answering the questions.

1. Your Name (First name, Surname): 2. Age (in years) : 3. Sex: 4. Your phone number (in case we have to contact you): 5. Phone number of any of your relative: 6. When last did you take any anti-malarial drug? 7. How long has the sickness lasted? 8. Have you had fever in the last one to three days? 9. Do you react to any anti-malarial drug? 10. Are you currently taking any drug? 11. Are you currently taking any herbal treatment for any illness? 12. Are you pregnant? 13. Body temperature reading in degree Celsius:

Name: Pharm. Ayogu Ebere Emilia

Signature:

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Researcher’s Comment:

APPENDIX 8

PATIENT COMPLIANCE FORM

This form is prepared to help you take your drug as prescribed by the doctor. Please be honest and tick ( ) when drug is taken and tick () when drug is not taken.

MORNING NIGHT

DAY 1

DAY 2

DAY 3

Please return this form on the 3rd day after the completion of your drug. This is also the day you will come for your second lab check.

Thanks

Pharm. Ayogu Ebere Emilia.

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APPENDIX 9

SMPL WORK SHEET

Date: Run No: Assay:

Scientist: Sample check before assay:

Record:

S/No Sample No Result S/No Sample No Result

Additional comments:

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Signature and date:

181

APPENDIX 10

SMPL WORK SHEET – 96 WELL PLATE

Date: Run No: Assay:

Scientist: Sample check before assay:

Record:

1 2 3 4 5 6 7 8 9 10 11 12

Additional comments:

Signature and date:

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APPENDIX 11

SMPL WORK SHEET – 48 WELL PLATE

Date: Run No: Assay:

Scientist: Sample check before assay:

Record:

1 2 3 4 5 6 7 8

Additional comments:

Signature and date:

183