Faculty of Graduate Studies and Scientific Research Molecular

Republic of Sudan

Ministry of Higher Education and Scientific Research Shendi University Faculty of Graduate Studies and Scientific Research

Molecular Identification of Genetic Markers of Susceptibility to Essential Hypertension Using Whole Exome Sequencing among Sudanese Patients from Afro- Asiatic and Nilo-Saharan ethnic groups

A Thesis Submitted in Fulfillment for the Requirements of PhD Degree in Biochemistry

By:

Wesal Ahmed ELHanbli Babiker MBBS- MSc Medical Biochemistry

Supervisor:

Dr: Dina Ahmed Hassan Associate professor of Biochemistry (2020)

سورة الفاتحة

Bibliographic Entry

Author: Wesal Ahmed ELHanbli Babiker Thesis: Molecular Identification of Genetic Markers of Susceptibility to Essential Hypertension Using Whole Exome Sequencing among Sudanese Patients from Afro-asiatic and Nilo-Saharan ethnic groups

Degree program: PhD Faculty: Faculty of Medicine Field of study: Biochemistry Supervisor: Dr: Dina Ahmed Hassan Duration: (from 2015 to 2020) Key words: Essential hypertension, whole exome sequencing, bioinformatics tools, GPCR, MTHFR, ADM, Real-time PCR.

PhD Examination Committee Members

Thesis Title:

Molecular Identification of Genetic Markers of Susceptibility to Essential Hypertension Using Whole Exome Sequencing among Sudanese Patients from Afro-asiatic and Nilo-Saharan ethnic groups Supervisor: Dr: Dina Ahmed Hassan Signature …………………………… date …………………………….

Internal Examiner: Prof. Rashid Eltayeb Abdalla

Signature …………………………….. date ……………………………

External Examiner: Prof. Mamoun Makki EL Manna

Signature …………………………….. date …………………………….

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Statement

I Wesal Ahmed ELHanbli Babiker, declare that the study of Molecular Identification of Genetic Markers of Susceptibility to Essential Hypertension Using Whole Exome Sequencing among Sudanese Patients from Afro-asiatic and Nilo- Saharan ethnic groups, is my own original work and submitted in fulfillment for the requirements of PhD degree in biochemistry. I have followed all ethical and technical principles in the preparation, data collection, data analysis and compilation of this study. I declare that it has not been presented to any other university for a similar or any degree award, and any sources used are indicated as references.

Signature ......

Date ………………………………………………………………

DEDEICATION

To soul of my dear father, To my kind dear mother, To my supportive lovely little family, To my sisters and brother, To my friends, To all whom I love ,,,,,

Acknowledgments

I would like to express my profound appreciation and gratitude to my supervisor Dr. Dina Ahmed Hassan Ibrahim Associate Professor of Biochemistry, director of Central Laboratory, Ministry of Higher Education and Scientific Research for her supervision and continuous encouragement and support throughout the course of this study.

I would like to appreciate the contribution of both: Dr. Mutaz Amin and Dr. Mahmoud Koko for their informative knowledge and help in Bioinformatics tools.

I specifically thank the two family members for their generous participation in this study. Further thanks to the patients, the healthy volunteers and all the study participants for contributing to this effort.

I am grateful to all members in Central Lab with special thanks to Dr. Khalid Enan, Dalia Mursi and Raya Osman for their counseling and Kind support.

My appreciation is also extended to my dear friends and colleagues in Shendi University for their continuous support.

Abstract

Background: Essential hypertension (EH) is one of most important risk factors for CVDs, stroke and end stage renal disease and a major cause of premature deaths worldwide. It is a multigene complex disorder with no known single gene playing a major role, but rather many genes each with mild effects reacting to different environmental stimuli contribute to BP. This study we hypothesized that a block of specific single nucleotide polymorphisms (SNPs) and insertion /deletion mutations (InDels) in genes controlling pathways of BP regulation is associated with susceptibility to EH among Sudanese taking the Afro-asiatic ethnic group as a model.

Aim of study: To identify the genetic markers of EH among Sudanese patients.

Study design: Prospective laboratory case control study

Duration: (from 2015 to 2020)

Site of work: Central laboratory, Ministry of Higher Education and Scientific Research.

Methods and Results: Whole exome sequencing (WES) was used to analyze genomic DNA of (15) members (13 hypertensive cases and 2 normotensive controls) of two families of strong family history of EH. The 2 families belong to the Afro-asiatic ethnic group. In silico analysis and data filtration with bioinformatics tools identified set of genes which function in different metabolic pathways; mainly lipid and lipoproteins metabolism as well as signal transduction, informational and immune system pathways.

Screening for MTHFR rs1801133 and ADM rs5005 was performed using real time PCR for a total of (221) samples (107 hypertensive cases and 114

VII normotensive controls). Results showed high frequency of the 2 variants among Sudanese especially among Nilo-Saharan ethnic group. Unlike ADM, MTHFR variant is associated with EH (P value 0.04) and this association is significant among females.

Conclusions: WES is a molecular method used to identify novel variants associated with polygenetic complex diseases. In silico analysis applied highlighted the importance of G-protein coupled receptors (GPCRs) as an important pathway in regulating blood pressure via its role in activation of calcium release. Screening of population for the identified variants is required to determine alleles associated with susceptibility to EH and BP regulation.

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المستخلص

ارتفاع ضغط الدم األساسي (EH) هو واحد من أهم عوامل الخطر ألمراض القلب واألوعية الدموية ، والسكتة الدماغية والمرض الكلوي في المرحلة النهائية وسبب رئيسي للوفاة المبكرة في جميع أنحاء العالم . إنه اضطراب معقد متعدد الجينات مع عدم وجود جين واحد معروف يلعب دو ًرا رئيسيًا ، ولكن العديد من الجينات ذات اآلثار الخفيفة التي تتفاعل مع المنبهات البيئية المختلفة تساهم في ضغط الدم .في هذه الدراسة افترضنا أن كتلة من تعدد أشكال النوكليوتيدات الفردية (SNPs) وطفرات الحذف اإلدراج (InDels) في الجينات التي تتحكم في مسارات تنظيم ضغط الدم ترتبط بارتفاع ضغط الدم األساسي بين السودانيين وتم اخذ مجموعة عرقية أفرواسيوية كنموزج.

تم استخدام تسلسل اإلكسوم الكامل (WES) لتحليل الحمض النووي الجينومي لـ 15 عض ًوا - 13 حالة ارتفاع ضغط الدم و 2 ضوابط معيارية - لضغط الدم لعائلتين من تاريخ عائلي قوي الرتفاع ضغط الدم األساسي. تنتمي العائلتان إلى المجموعة اإلثنية األفرو آسيوية .حددت تصفية البيانات باستخدام أدوات المعلوماتية الحيوية مجموعة من الجينات التي تعمل في مسارات التمثيل الغذائي المختلفة ؛ بشكل رئيسي استقالب الدهون والبروتينات الدهنية وكذلك تحويل اإلشارة ، ومسارات المعلومات ونظام المناعة .

تم إجراء الفحص لـ MTHFR rs1801133 و ADM rs5005 باستخدام PCR في الوقت الفعلي لمجموعه 221 عينة - 107 حاالت ارتفاع ضغط الدم و 114 ضوابط معيارية . أظهرت النتائج توات ًرا عاليًا للمتغيرين بين السودانيين خاصة بين مجموعة النيلو الصحراوية العرقية .على عكس ADM ، يرتبط متغير MTHFRبارتفاع ضغط الدم األساسي- P 0.04 - وه اذ االرتباط مهم خاصة عند االناث.

تسلسل اإلكسوم الكامل هي طريقة جذابة لتحديد المتغيرات الجديدة المرتبطة باألمراض الوراثية المعقدة . يسلط تحليلنا في السليكو الضوء على أهمية المستقبالت المقترنة بالبروتين GPCRs) G) كمسار مهم في تنظيم ضغط الدم من خالل دوره في تنشيط إطالق الكالسيوم .مطلوب فحص السكان للمتغيرات المحددة لتحد د ياألليالت المرتبطة بقابلية التأثر بالصحة وتنظيم ضغط الدم.

Table of Contents

I االيه

Bibliographic Entry II PhD Examination Committee Members III Statement IV Dedication V Acknowledgements VI English Abstract VII Arabic Abstract IX Table of Contents X List of Tables XIV List of Figures XVI List of Abbreviations XVII Glossary XXV CHAPTER ONE: INTRODUCTION 1.1 Definition 1 1.2 Classification 2 1.3 Pathogenesis of essential hypertension 3 1.4 Genetic role in EH 6 1.5 Methods of mapping human disease genes 6 1.6 Molecular study of hypertension in Sudan 7 1.7 Justification 9 1.8 Objectives 11

CHAPTER TWO: LITERATURE REVIEW 2.1 Prevalence of essential hypertension 12 2.2 Genetics of hypertension 13 2.3 Clinical application of genomic sequencing to the detection of germ-line mutations 14 2.3.1 Sanger sequencing 14 2.3.2 Next generation sequencing 14 2.3.3 Whole genome sequencing 15 2.3.4 Whole exome sequencing 15 2.4 Development of genetic hypotheses in essential hypertension 16 2.4.1 Renin-angiotensin aldosterone system 17 2.4.2 G protein B3 subunit 20 2.4.3 α-adducin 21 2.4.4 Other genetic polymorphisms 22

CHAPTER THREE: MATERIALS AND METHODS

3.1 Study design 32 3.2 Study area and population 32 3.3 Inclusion criteria 32 3.4 Exclusion criteria 32 3.5 Sample size 32 3.6 Data tools 32 3.7 Study description and protocol 33 3.7.1 Phase 1: Whole exome sequencing 33 3.7.1.1 Preparation of WES sample 33 3.7.1.2 In-silico bioinformatics analysis 36 3.7.2 Phase II: Screening of the population 36

3.7.2.1 DNA extraction. 36 3.7.2.2 Primer Design 37 3.7.2.3 Real-time PCR assay 37 3.8 Statistical analysis 39 3.9 Ethical consideration 39 CHAPTER FOUR: RESULTS

Phase 1: Whole Exome Sequencing

4.1 Demographic characterization of the (2 ) families members 40

4.2 Whole exome sequencing results 41 4.2.1 In silico analysis 41 4.2.2 Identification of variants related to hypertension 42

4.2.3 Individual family analysis 43

4.2.4 Pathways and interactions of the selected genes 58

Phase II: Screening of the population

4.3 Case-control study results 61

4.3.1 MTHFR gene variant rs1801133 (G/A) 61 4.3.2 ADM gene variant rs5005 (C/G) 63 4.3.3 Demographic characterization of study population 64 4.3.4 Genetic screening of MTHR and ADM SNPs 66

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CHAPTER FIVE: DISCUSSION, CONCLUSION AND RECOMMENDATIONS

Discussion 69

Phase I : Whole Exome Sequencing 69

Phase II: Screening of the population 78

Conclusion 81

Recommendations 82

Reference 83

Appendices 95

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list of Tables

Table 1 .1: Comparison of the latest hypertension guidelines 2

Table 4.1: Demographic characteristics of hypertensive cases and normotensive controls in the (2) families 40

Table 4.2: Characteristic of the SNP shared between hypertensive patients and not by the controls 41

Table 4.3: Characteristic of the InDel shared between hypertensive patients and not by the controls 42

Table 4.4: Common SNPS in genes known to cause hypertension found in both families 42

Table 4.5: Common InDels in genes known to cause hypertension found in both families 43

Table 4.6: SNPSs found in all hypertensive and not in control sample in family 1 44

Table 4.7: InDels found in all hypertensive patients and not in control sample in family 1 47

Table 4.8: SNPSs found in all hypertensive and not in control sample in family 2 50

Table 4.9:InDels found in all hypertensive and not in control sample in family 2 54

Table 4.10: Grouping of mutated genes into different pathways 58

Table 4.11: Some genes co-express and/or interact with other genes 60

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Table 4.12: Demographic characteristics of study population 64

Table 4.13: Frequency of the MTHFR and ADM SNPs among study groups 67

Table 4.14: Cross-tabulation between study groups and SNPs concerning gender 67

Table 4.15: Cross-tabulation between ethnic groups and SNPs frequency 68

List of Figures

Figure 1.1: Pathogenesis of essential hypertension 5

Figure 2.1: MTHFR pathway interaction 25

Figure 2.2: Methionine – Homocysteine cycle 27

Figure 2.3: ADM pathway interaction 29

Figure 3.1: Family (1) pedigree 34

Figure 3.2: Family (2) pedigree 35

Figure 4.1: MTHFR rs1801133 61

Figure 4.2: Exome reads of the exons of MTHFR gene 62

Figure 4.3: MTHFR rs1801133 alignment of the exome reads against reference genome 62

Figure 4.4: The exome reads of the exons of ADM gene 63 Figure 4.5: ADM rs5005 alignment of the exome reads against reference genome 63

Figure 4.6: Antihypertensive drugs used among study group 65

Figure 4.7: Family history of hypertension among study population 66

Figure 4.8: Real time PCR amplification curve 66

Figure 5.1: GPCR signaling pathway that modulate vascular tone 72

Figure 5.2: Network of hypertension genes 74

Figure 5.3: JPH3 pathway interaction 76

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List of Abbreviations

The abbreviation Terminology ADM Adrenomodullin gene AGT Angiotensinogen AM Adrenomedullin Ang II Angiotensin II ANP Atrial natriuretic peptide Arg Arginine AT1 Angiotensin II receptor type 1 AT2 Angiotensin II receptor type 2 BMI Body mass index BP Blood pressure bp Base pair Ca.M Calmodulin cGMP Cyclic 3’,5’-guanosine monophosphate CGRP Calcitonin gene related peptide CNVs Copy number variations CO Cardiac output Ct Threshold cycle CVA Cardiovascular accident DAG Diacylglycerol DBP Diastolic blood pressure ECs Endothelial cells EGF Epidermal growth factor EH Essential hypertension

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F Forward Gln Glutamine GPCR G-protein coupled receptor GRKs G-protein coupled receptor kinases GWAS genome-wide association studies GWS Genome-wide scan Hsp 90 Heat shock protein HTN Hypertension IDT Integrated DNA technology IL-1 Interlukin-1 InDel Insertion/deletion IP3 Inositol 1,4,5- triphosphate ITPR Inositol 1,4,5- triphosphate receptors JMCs Junctional membrane complexes JPH3 Junctophilin 3 gene MA Mutation Assessor MAP kinase Mitogen activated protein kinase MLCK Myosin light chain kinase MTHFR Methylene tetrahydrofolate reductase NGS Next generation sequencing NO Nitric oxide NOS3 Nitric oxide synthase 3 P- value Probability value PAMP Proadrenomedullin N-terminal 20 peptide PG Prostaglandins PKC Protein kinase C

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PLC Phospholipase C Polyphen-2 Polymorphism Phenotyping v2 R Reverse RAAS Rennin – Angiotensin – Aldosterone System REN Renin gene RFLP Restriction fragment length polymorphism RFT Renal function test RGS Regulator of G-Protein Signaling ROS Reactive oxygen species rs Reference SNP SBP Systolic blood pressure SIFT Sorting Intolerant From Tolerant SLC Sodium- Lithium Counter-transport SNP Single nucleotide polymorphisms SSA Sub-Saharan Africa SVs Structural variants TNF Tumor necrosis factor TPR Total peripheral resistance TX Thromboxane UPR Unfolded protein response VEGF Vascular endothelial growth factor VSM Vascular smooth muscle WES Whole exome sequencing WGS Whole genome sequencing WHO World Health Organization WH-ratio Waist- hip ratio

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OR Odd ratio SD Standard deviation ELAM Endothelial leucocytes adhesion molecule SRA1 Steroid Receptor RNA Activator 1gene SIRPA Signal Regulatory Protein Alpha gene PRSS3 Serine Protease 3 gene SOWAHA Sosondowah Ankyrin Repeat Domain Family Member A gene Guanine nucleotide-binding proteins Subunit GNB3 Beta 3 gene ADD2 Beta-Adducin gene ADD1 Adducin 1 (Alpha) gene Olfactory Receptor Family 8 Subfamily U OR8U1 Member 1 gene WNK1 Lysine Deficient Protein Kinase 1 gene CLSPN Claspin gene LCE2A Late Cornified Envelope 2A gene CAPN8 Calpain 8 gene SP140L Nuclear Body Protein Like gene PRDM5 PR Domain Zinc Finger Protein 5 gene Family With Sequence Similarity 173 FAM173B Member B gene RANBP3L RAN Binding Protein 3 Like gene CCDC125 Coiled-Coil Domain Containing 125 gene B Double Prime 1, Subunit Of RNA BDP1 Polymerase III Transcription Initiation Factor IIIB gene

INMT Indolethylamine N-Methyltransferase Chromosome 7 Open Reading Frame 57 C7orf57 gene FCN2 Ficolin 2 gene Family With Sequence Similarity 35, FAM35A Member A gene NRAP Nebulin Related Anchoring Protein gene Polypeptide N- GALNT4 Acetylgalactosaminyltransferase 4 gene PABPC3 Poly(A) Binding Protein Cytoplasmic 3 gene SSX5 SSX Family Member 5 gene Acidic Nuclear Phosphoprotein 32 Family ANP32E Member E gene SULT1C3 Sulfotransferase Family 1C Member 3 gene B Double Prime 1, Subunit Of RNA BDP1 Polymerase III Transcription Initiation Factor IIIB gene WWC1 WW And C2 Domain Containing 1 gene FOXC1 Forkhead Box C1 gene PRICKLE4 Prickle Planar Cell Polarity Protein 4 gene COBL Cordon-Bleu WH2 Repeat Protein gene Olfactory Receptor Family 2 Subfamily A OR2A14 Member 14 gene Olfactory Receptor Family 1 Subfamily B OR1B1 Member 1 gene SCUBE2 Signal Peptide, CUB Domain And EGF Like

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Domain Containing 2 gene PTGES3 Prostaglandin E Synthase 3 gene BRI3BP BRI3 Binding Protein gene Essential Meiotic Structure-Specific EME1 Endonuclease 1 gene ZNF772 Zinc Finger Protein 772 gene BMP15 Bone Morphogenetic Protein 15 gene HNMT Histamine N-Methyltransferase gene COL6A6 Collagen Type VI Alpha 6 Chain gene NIMA- (Never In Mitosis Gene A)- Related NEK11 Kinase 11 gene Sphingomyelin Phosphodiesterase Acid Like SMPDL3A 3A gene POLR2J3 RNA Polymerase II Subunit J3 gene Olfactory Receptor Family 13 Subfamily C OR13C5 Member 5 gene Olfactory Receptor Family 13 Subfamily C OR13C2 Member 2 gene SYNPO2L Synaptopodin 2 Like gene Mucin 6, Oligomeric Mucus/Gel-Forming MUC6 gene MS4A15 Membrane Spanning 4-Domains A15 gene SLC22A25 Solute Carrier Family 22 Member 25 gene KRT75 Keratin 75 gene KRT3 Keratin 3 gene OTOGL Otogelin Like gene

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CORO7 (coronin 7) and PAM16 gene (presequence translocase-associated motor CORO7-PAM16 16) gene KRT40 Keratin 40 gene KRT32 Keratin 32 gene PRR29 Proline-Rich Protein 29 gene DHX34 DExH-Box Helicase 34 gene Leukocyte Immunoglobulin Like Receptor LILRB3 B3 gene Killer Cell Immunoglobulin Like Receptor, Three Ig Domains And Long Cytoplasmic KIR3DL2 Tail 2 gene SEC14L4 SEC14 Like Lipid Binding 4 gene AIM1L Absent In Melanoma 1-Like Protein gene EFCAB2 EF-Hand Calcium Binding Domain 2 gene SCRN3 Secernin 3 gene COL6A5 Collagen Type VI Alpha 5 Chain gene MUC4 Mucin 4, Cell Surface Associated gene SLC9B1 Solute Carrier Family 9 Member B1 gene Sosondowah Ankyrin Repeat Domain SOWAHA Family Member A gene Chromosome 6 Open Reading Frame 223 C6orf223 gene ZAN Zonadhesin gene TMEM229A Transmembrane Protein 229A gene OR13C2 Olfactory Receptor Family 13 Subfamily C

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Member 2 gene MEGF9 Multiple EGF Like Domains 9 gene PSMD5 Antisense RNA 1 (Head To Head) PSMD5-AS1 gene MUC19 Mucin 19, Oligomeric gene Family With Sequence Similarity 186 FAM186A Member A gene GP1BA Glycoprotein Ib Platelet Subunit Alpha gene CDC27 Cell Division Cycle 27 gene SIGLEC12 Sialic Acid Binding Ig Like Lectin 12 gene

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GLOSSARY

Gene is a sequence of nucleotides in DNA or RNA that encodes the synthesis of a gene product, either RNA or protein. Homozygotes A cell is said to be homozygous for a particular gene when identical alleles of the gene are present on both homologous chromosomes. Heterozygotes A diploid organism is heterozygous at a gene locus when its cells contain two different alleles (one wild-type allele and one mutant allele) of a gene. Gene Locus A fixed position on a chromosome that is occupied by a given gene or one of its alleles. Gene family A gene family is a set of several similar genes, formed by duplication of a single original gene, that generally have similar biochemical functions Exon A nucleic acid sequence that is represented in the mature form of an RNA molecule either after portions of a precursor RNA (introns) have been removed by cis-splicing or when two or more precursor RNA molecules have been ligated by trans-splicing. The mature RNA molecule can be a messenger RNA or a functional form of a non-coding RNA such as rRNA or tRNA. Depending on the context, exon can refer to the sequence in the DNA or its RNA transcript.

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Intron A segment (nucleotide sequence) of a DNA or RNA molecule that does not code for proteins. It is removed to generate the final mature RNA product of a gene. Allele In the field of genetic variation, the term allele refers to different versions of the same variant. Variant the term variant is used to refer to a specific region of the genome which differs between two genomes. Polymorphism When two or more clearly different phenotypes exist in the same population of a species. Single Nucleotide Variants / Polymorphisms Single nucleotide variants (SNVs) or single nucleotide polymorphisms (SNPs) refer to single base differences between individuals of the same population. NCBI The National Center for Biotechnology Information advances science and health by providing access to biomedical and genomic information. ClinVar is a freely accessible, public archive of aggregates information about genomic variation and its relationship to human health hosted by the National Center for Biotechnology Information (NCBI) and funded by intramural National Institutes of Health (NIH) funding.

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REACTOME database which is an open source, open access manually curated and peer reviewed pathway database aimed for interpretation, visualization and analysis of related pathways. A genome-wide association study (GWAS) is an approach used in genetics research to associate specific genetic variations with particular diseases. The method involves scanning the genomes from many different people and looking for genetic markers that can be used to predict the presence of a disease. Illumina is a biotech company specializing in genomics, microarrays and sequencing technologies (www.illumina.com). Next generation sequencing(NGS) is defined as technology allowing one to determine in a single experiment the sequence of a DNA molecule(s) with total size significantly larger than 1million base pairs (1millionbp or 1Mb). Whole genome sequencing (WGS) (also known as, full genome sequencing, complete genome sequencing, or entire genome sequencing) is ostensibly the process of determining the complete DNA sequence of an organism's genome at a single time. Whole exome sequencing (WES) is a genomic technique for sequencing all of the protein-coding regions of genes in a genome (known as the exome). Variant calling Variant calling involves comparing a sample sequence, which may be a single gene sequence, a whole exome or a whole genome, and comparing it to a reference sequence. Differences between the sample and the reference

XXVII are identified, which may be single base changes, such as SNPs and indels, or may be larger scale structural variants. Real-time PCR A real-time polymerase chain reaction is a laboratory technique of molecular biology based on the polymerase chain reaction (PCR). It monitors the amplification of a targeted DNA molecule during the PCR, i.e. in real-time, and not at its end, as in conventional PCR. A DNA probe can be either single stranded nucleotides, ranging from 25 to 7 or more bases in length, or double stranded DNA products, generally generated from PCR amplification of genomic DNA or of cDNA library clones. Quencher A molecule that absorbs the fluorescence emitted by the reporter molecule in Real-time PCR. P-value The probability of an event or outcome in a statistical experiment. The p- value measures the probability that a difference between two experimental conditions happened by chance. The lower the p-value, the more likely it is that the difference between the two conditions is a true reflection of the biological process being studied either than a random phenomenon. Cycle threshold (Ct) Is the intersection point between the amplification curve and the threshold line which indicates the cycle in which the fluorescence reaches the threshold value. The higher the initial DNA amount the lesser the number of cycles are needed (low Ct value) to reach the threshold.

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Restriction fragment length polymorphism: Variation in DNA sequence that can be detected through its effect of allowing or preventing cleavage of a chromosomal DNA segment by a restriction enzyme. Mutation is a heritable alteration in DNA nucleotide sequence. Missense mutation Is a Point mutation altering single nucleotide sequence in a codon that codes for a different amino acid. Frame shift mutation If one or two nucleotides are either deleted from or added to the coding region of a mRNA and the reading frame is altered, this can result in a different amino acid sequence, or a truncated product due to the creation of a termination codon. Epigenetic In biology, epigenetics is the study of heritable phenotype changes that do not involve alterations in the DNA sequence. Hereditary factor is the passing on of traits from parents to their offspring; either through asexual reproduction or sexual reproduction, the offspring cells or organisms acquire the genetic information of their parents.

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1. Introduction

1.1 Definition:

EH is high blood pressure that doesn’t have a known secondary cause. It’s also called primary hypertension. According to World Health Organization (WHO) criteria, Hypertension (HTN) (elevated blood pressure levels exceeding 140/90 mmHg) is a common complex disorder. It is classified as primary-essential- hypertension (EH) without a known pathology which constitutes about (90-95%) of all hypertension cases. The other type is secondary hypertension about (5%) of cases. HTN is the one of most important risk factors for cardiovascular diseases, stroke and end stage renal disease (Lacruz et al., 2015). It is also associated with many other complications that affect vital body functions such as the heart, blood vessels and the brain (Tanira & Al Balushi, 2005).

According to WHO statistics an estimated (1.13 billion) people worldwide have HTN, most of them (two-thirds) are living in low-and middle-income countries. In 2015, (1 in 4 men) and (1 in 5 women) had HTN. HTN is a major cause of premature death worldwide, accounting for almost (10 million) deaths. One of the global targets for noncommunicable diseases is to reduce the prevalence of HTN by (25%) in 2025 (baseline 2010). The overall prevalence of HTN in adults is around (30– 45%). Hypertension becomes progressively more common with advancing age, with a prevalence of more than (60%) in people aged more than (60 years). It is estimated that the number of people with HTN will increase by (15–20%) by 2025, reaching close to (1.5 billion) (Williams et al., 2018).

1.2 Classification

The criteria of the Seventh Report of the Joint International Committee on Prevention, Detection, and Treatment of HBP were used to classify BP levels as follows: (Bushara, Noor, Ibraheem, Elmadhoun, & Ahmed, 2016)

Normal BP is defined as (BP <120/80 mmHg).

Prehypertension is defined as systolic BP (120–139/80–89 mmHg)

Stage 1 hypertension: (140–159/90–99 mmHg)

Stage 2 hypertension: (160–179/ 100–109 mmHg)

Stage 3 hypertension: (≥180/≥110 mmHg) .

The latest European guidelines define HTN to (BP >140/90 mm Hg )whereas the American guidelines lowered the threshold to define HTN to (<130/80 mm Hg ) (Chopra & Ram, 2019). Table1.1

Table 1.1 : Comparison of the latest hypertension guidelines

Parameter American guidelines European guidelines Definition of HTN, >130/80. >140/90 mm Hg Grading of normal Normal, <120/80 Optimal <120/80 pressure, mm Hg Elevated, 120–129/<80 Normal, 120–129/80–84 Grade 1,130–139/80–89 High normal 130–139/85–89 Grade 2, ≥140/90 Grade 1, 140–159/90–99 Grade 2, 160–179/100–109 Grade 3, ≥180/110

Target blood pressure ≤65 yrs, <130/80 <65 yrs, <130/80 in various subsets ≥65 yrs, <130/80 ≥65 yrs, <140/80

1.3 Pathogenesis of essential hypertension

In spite of intensive investigations, etiology of EH remains poorly understood. Heredity is a predisposing factor of developing HTN, but environmental factors (e.g., dietary Na+, obesity, sedentary lifestyle, stress, alcohol intake) known to increase the risk (Lackland & Egan, 2007).

Two mechanisms are involved in determination of BP, cardiac output (CO) and total peripheral vascular resistance (TPVR), therefore pathogenic mechanisms must involve increased CO, increased TPVR, or both. The most important theory have been proposed to explain these mechanisms; is the microcirculation theory. In which the primary defect involves small resistance vessels, leading to increased TPVR and sustained elevated BP. Endothelial cells (EC) release several biologically active substances, which maintain the hemostasis between circulating blood and arterial wall via autocrine and paracrine mechanisms. Vasoconstricting factors are including endothelin-1, thromboxane A2, angiotensin II on one side and vaso-relaxing factors including prostacyclin, nitric oxide (NO) on the other side all are secreted by EC ((Seo, Oemar, Siebenmann, von Segesser, & Lüscher, 1994) (Vane, Änggård, & Botting, 1990). Basal generation of NO keeps arterial circulation in an actively dilated state. The intracellular mechanism by which NO causes dilation in vascular smooth muscle cells involves formation of cyclic 3’,5’-guanosine monophosphate (cGMP) (Hansson et al., 1994).

The key role of endothelial function in the pathogenesis of EH is very important. The functional and morphological changes in small resistance vessels are thought to be the cause of HTN due to abnormal EC function and decreased production of NO leading to unbalanced production of other vasoactive substances (angiotensin II, endothelin-1, prostacyclin, and aldosterone) and reactive oxygen species (ROS) (Williams et al., 2018) . ROS play an important role in the development of CVDs such as HTN. The primary source of ROS in the vascular smooth muscle (VSM) cell is NADPH oxidase which is triggered by angiotensin 11, endothelin, norepinephrine through G protein (Miroslava Majzunova1, 2013). Also The autonomic nervous system plays an important role in the control of BP as both increased release of, and enhanced peripheral sensitivity to, norepinephrine can be found. In addition, there is increased responsiveness to stressful stimuli (panel LeWanga, 2018).

There is currently no effective treatment known for HTN. It is important to treat HTN in the early stages, when preventive measures and antihypertensive therapy are most effective figure (1.1).

Figure 1.1: Pathogenesis of essential hypertension

(CVS pathology -4 Hypertension (HTN) .slideshare.net)

1.4 Gene-environment interaction mode of stress induced EH:

The development of EH may be due to repeated exposure to stress in combination with an environmentally and/or genetically mediated susceptibility. The genes underlying the physiological systems mediating the stress response of heart, vasculature, and kidney are increasing vulnerability to stress and confer susceptibility to development of EH. These systems are: the sympathetic nervous system, rennin – angiotensin – aldosterone system (RAAS) and sodium reabsorption and the endothelial system. Also the genes underlying (3) additional systems that may mediate the influence of stress on the development of EH : the parasympathetic nervous system, the serotonergic system, and the hypothalamus–pituitary–adrenal axis The knowledge of gene-environment interaction model of stress-induced EH will improve the understanding of the role of stress in development of EH . This knowledge may lead to more effective prevention particularly for individuals at increased genetic risk of EH. (Imumorin et al., 2005).

1.5 Methods of mapping human disease genes:

Because HTN is a multigene complex disorder, the genetic analysis of hypertension produces complex, inconsistent and non-reproducible results, which makes it difficult to draw conclusions about the association between specific genes and hypertension. So, there are current research strategies in search for HTN-predisposing genetic loci - HTN susceptibility genes- (Tanira & Al Balushi, 2005). These include:

1.5.1 Genome-wide scan (GWS);

In this approach, (100s) of polymorphic markers are genotyped in a selected sample of individuals and has the advantage of testing all genomic regions. 6

GWS studies identified linkage to different chromosomal regions although some GWS studies failed to find a linkage with EH and this suggests that large numbers of individuals in a study might not be sufficient in the presence of ethnic and phenotypic heterogeneity (Tanira & Al Balushi, 2005).

1.5.2 Candidate gene approach:

It is the most used strategy to study candidate genes. It is useful for rare monogenic forms of HTN but not for EH because at least (51 genes/loci) affect different physiological and biochemical systems (Tanira & Al Balushi, 2005).

1.5.3 Use of intermediate phenotypes:

It represent an early stage towards the development of HTN and may aid in the search for HTN susceptibility genes.

1.5.4 Comparative genomics;

This approach uses data from animal studies to target potential BP loci in humans.

1.5.5 Combination of the above methods.

1.6 Molecular study of hypertension in Sudan:

Concerning the RAAS, an insertion/deletion (InDels) polymorphism of the angiotensin-converting enzyme (ACE) gene in its (intron 16) has been widely investigated in different populations including Sudanese, Somalis, and Arab nationals of the United Arab Emirates (UAE) and Oman and the results were the predominance of the deletion allele among the Arab and African population studied (Bayoumi et al., 2006). Another study (including (9) Sudanese patients) was done to investigate the possibility that familial hypertension was due to

7 mineralocorticoid (MC) hypersecretion, by using spironolactone, which selectively blocked the MC receptors (64 hypertensive patients with at least one or more affected parent or sibling), the result was that, inherited forms of mineralocorticoid HTN were common, as (84%) of the patients under study responded to spironolactone, and recommended that all patients with familial HTN should undergo therapeutic trial with MC receptor blocking agents, before undertaking expensive endocrine investigations (Woodhouse, Elshafie, Johnston, & Al-Kaabi, 2003). Another case control study was done to investigate the association of nitric oxide synthase gene-3 (NOS3) polymorphisms with EH in Sudanese patients and the results of this study indicated that the rs2070744 polymorphism in NOS3 may be a genetic susceptibility factor for EH in the Sudanese population (Gamil, Erdmann, Abdalrahman, & Mohamed, 2017)

From a genetic perspective, several (SNPs) and epigenetic factors are associated with EH. This suggested that people with these hereditary factors might have a genetic predisposition to HTN (J. E. Hall et al., 2012).

Genome-wide association(GWAS) and exome sequencing studies over the past few years have resulted in an unparalleled burst of discovery in the genetics of BP regulation. More importantly, exome-wide association studies (EWAS) expand the list of common genetic variants associated with HTN. Moreover, GWAS have implicated a number of susceptibility loci for systolic and diastolic BP but a large portion of the heritability cannot be explained by the top GWAS loci and a comprehensive understanding of the underlying molecular mechanisms is still lacking (Zhao1 et al., 2019).

1.7 Justification

HTN is a common and complex human disease that causes significant morbidity and mortality worldwide. According to the 2012 World Health Statistics report released by the (WHO), HTN affects approximately (24.8%) of the global population with the range from (19.7 to 35.5%) in different regions. In Sudan, the prevalence was (24.6%) in 2015. Unfortunately, despite recent advances in understanding and treating hypertension, its prevalence continues to rise. EH accounts for (90%) of hypertensive cases and genetics is a major predisposing factor. This study, hypothesized that a block of specific SNPs in genes controlling pathways of BP regulation is associated with susceptibility to EH among Sudanese. Identification of such block will facilitate early detection (or even prediction) of the disease and thus shift the management of EH towards prevention rather than treatment and identifying gene variants that contribute to EH provide better understanding of the pathophysiology of the disease and also help understanding the interaction between genes and environmental factors. Discovering EH susceptibility genes would help recognizing those at risk for developing the disease before the manifestation of clinical symptoms. Also treatment of HTN is imperfect. Medication prescription tends to be nonspecific and is associated with side effects and non-compliance. The National Heart, Lung, and Blood Institute (NHBLI) stated that most patients with hypertension will require more than one drug to control their HTN.

Moreover, identification of such SNPs will contribute to the proper use of antihypertensive drugs by targeting defected pathways and make a breakthrough in introducing the concept of personalized medicine into our hypertension clinics.

This current study is bridging the informational gap as there is no recent knowledge or information handled the topic before in Sudan .

1.8 Objectives:

1.8.1 General:

To identify the genetic markers of EH among Sudanese patients.

1.8.2 Specific:

1. To study the correlation between the demographic data (Gender, Age, ethnic group, BMI, WH-ratio, average systolic and diastolic blood pressure) and susceptibility to EH. 2. To identify SNPs related to susceptibility to EH using WES of samples obtained from patients with strong family history of the disease. 3. To assess the pathogenicity of detected variants using in-silico bioinformatics tools. 4. To identify novel polymorphisms in genes related to susceptibility to EH that could be used as potential markers for those at risk for developing the disease. 5. To introduce the new concept of personalized treatment and management of EH based on the molecular profile of the patients.

2. Literature review

2.1 Prevalence of essential hypertension:

EH is a rise in BP due to unknown reason and accounts for (90%) of hypertensive cases (Bolívar, 2013). EH has become a huge public health problem in both developed and developing countries causing serious morbidity and mortality rates. Its complications include increased risk of stroke, congestive heart failure, coronary heart disease, cerebrovascular disorders and end-stage renal disease (Arora & Newton-Cheh, 2010).

HTN, the leading single cause of morbidity and mortality worldwide, is a growing public health problem in sub-Saharan Africa (SSA). Few studies have estimated and compared the burden of HTN across different SSA populations, a cross-sectional analysis of BP data collected through a cohort study in (4) SSA countries, to estimate the prevalence of hypertension found the age-standardized prevalence of HTN among the (1216 )participants was (25.9 %) (Guwatudde et al., 2015).

Globally CVDs accounts for approximately (17 million) deaths / year, nearly one third of the total deaths , of these, complications of HTN account for (9.4 million) deaths worldwide every year (World Health Statistics; 2013). Moreover, HTN is found to affect (25-35%) of adults and (60-70%) of elderly population above the age of (70 years) in developed and developing countries (Staessen, Wang, Bianchi, & Birkenhäger, 2003).

Variation in the prevalence of EH depends on the ethnicity of the population. It was reported to be higher in American Blacks (32.4%) as compared to Whites (23.3%) and Mexican Americans (22.6%) (Carretero & Oparil, 2000). Not only the blacks are more likely to develop HTN, but compared with other ethnic 12 groups, the disorder in black patients is often more severe, more resistant to treatment, and more likely to be fatal at an earlier age (Brewster, Van Montfrans, & Kleijnen, 2004). Prevalence is significantly higher in urban than in rural populations (Twagirumukiza et al., 2011).

In Sudan, a study that involved (954) Sudanese adults the prevalence of HTN was (35.7%), and the newly diagnosed cases were (22.4%). Of interest, (41.8%) of the subjects were diagnosed with prehypertension (Bushara et al., 2016). Another study in Khartoum region including (323) respondents the prevalence of HTN is (27.6%) (Awadalla et al., 2018) . Importantly, the prevalence of HTN in Nubian ethnic population in South of Sudan was around (50%) (Noor, Elsugud, Bushara, Elmadhoun, & Ahmed, 2016).

Sudan is a diverse country. It consists of (3) linguistic groups. Mantel tests revealed a strong correlation between genetic and linguistic structures (r = 0.31, P = 0.007). Accordingly, Sudan was divided into three ethnic groups namely Nilo-saharan speaking group including Nilotics, Fur, Borgu, and Masalit, Afro- Asiatic speaking group including Arabs, Beja, Copts, and Hausa then the Niger- Congo speakers including the Fulani (Hassan, Underhill, Cavalli‐Sforza, & Ibrahim, 2008).

2.2 Genetics of hypertension:

EH is believed to involve multiple genes with variant alleles. Manifestation of EH in any single individual depends on a variety of genetic and environmental factors making identification of EH susceptibility genes in the general population an area of interest. Identifying gene variants which contribute to EH may provide better understanding of the pathophysiology of the disease and may elucidate the biochemical and physiological pathways which link different risk

13 factors and help to understand the interplay between genetic and environmental factors. It has been estimated that approximately (30%) of the inter-individual variability in BP is genetically determined (Rodriguez et al., 2013).

However, the hypertensive patients often respond to different classes of antihypertensive drugs which indicates that the etiology of hypertension varies considerably among patients. (Y. Wang et al., 2009) recommend that, studies must be done to elucidate the interactions between heterogeneous genetic backgrounds, different environmental factors, and differential etiologies in the pathogenesis of this disorder.

2.3 Clinical application of genomic sequencing to the detection of germ-Line mutations:

Sequencing technology development is enabling clinical applications to improve medical diagnosis and treatment. These technologies include:

2.3.1 Sanger sequencing:

Also called first generation sequencing, which is used to sequence the ﬁrst human genome. It’s the most available technology today, and it is well deﬁned chemistry makes it is the most accurate method for sequencing. But it is expensive and involved sequencing of one DNA strand at a time. This method is still used routinely for sequencing small amounts of DNA fragments (Rizzo & Buck, 2012).

2.3.2 Next generation sequencing (NGS):

It enables rapid generation of data by sequencing large numbers of different DNA sequences in a single reaction (i.e., in parallel), inexpensive, and accurate. NGS technologies introduced in 2007 and its common NGS applications include 14

DNA sequencing that can be applied to the whole genome sequencing (WGS), Whole exome sequencing (WES), or a specific targeted region of the genome. (Rizzo & Buck, 2012).

In general, the goal of DNA sequencing is to discover genomic variations in the form of SNPs, small insertions and deletions (InDels), copy number variations (CNVs), or other structural variants (SVs), with the ultimate goal of associating those variations to human disease (Bao et al., 2014).

2.3.2.1 Whole genome sequencing (WGS):

This term implies the determination of the sequence of most of the DNA content (the entire genome) of an individual. The rapid drop in sequencing cost and the ability of WGS to produce large volumes of data rapidly make it a powerful tool for genomic research .it equally useful for sequencing any species such as plants and bacteria (www.illumina.com/technology/next-generation-sequencing.html).

2.3.2.2 Whole exome sequencing (WES):

The exome represents less than (2%) of the human genome, but contains most of the known disease-causing variants (80%). Efficient strategies for selectively sequencing this exome have the potential to contribute to the understanding of rare and common human diseases (Choi et al., 2009). WES has proven success in identifying new causal mutations for diseases of previously unknown etiology (Seaby, Pengelly, & Ennis, 2015). WES involves determination of the DNA sequence of most of these protein-encoding exons. With WES, the protein- coding portion of the genome is selectively captured and sequenced and so it can efficiently identify variants (www.illumina.com/technology/next-generation- sequencing.html).

A typical workflow of WES analysis consists of many steps including ; raw data quality control (QC), preprocessing, mapping (alignment to reference human genome), post-alignment processing, variant calling (SNPs, InDels,..), annotation (genomic features), and prioritization ( filtration) (Bao et al., 2014).

In some cases, exome testing or analysis may be targeted to particular genes of clinical interest and so called targeted NGS reactions, in which sequencing reads are intentionally distributed to speciﬁc genomic locations, which allows for higher sequencing coverage and therefore ensures accurate detection of sequence variants at these loci (Rizzo & Buck, 2012).

Recently (GWAS) and exome sequencing studies have revealed important information related to genetics of BP regulation. Moreover, WES gives an impacts of the role of genes involved in the signaling pathway regulating ion hemostasis that help in understanding mechanisms controlling BP.

2.4 Development of genetic hypotheses in essential hypertension To understand the genetic background of EH variants a testable hypotheses was developed regarding the variants of the renin-angiotensin system, of signaling pathways such as GPCRs and α - adducin. Moreover, genetic association studies often fail to replicate findings from previous studies due to the polygenetic nature of the disease and the diversity of the investigated populations. (Naber & Siffert, 2004) recommend that, there is the need for different approaches to understand the complex, polygenetic disorders implementing gene-gene, and gene-environment interactions under standardized environmental conditions.

2.4.1 The renin-angiotensin system:

This system plays a central role in salt and water hemostasis and the maintenance of vascular tone. Each component of it represents a potential candidate in the etiology of HTN (J. Hall, Guyton, & Mizelle, 1990). Plasma angiotensinogen (AGT) is primarily synthesized in the liver under the positive control of estrogens, glucocorticoids, thyroid hormones and angiotensin 11.Cleavage of the amino-terminal segment of AGT by renin releases a decapeptide prohormone, angiotensin 1, which is further processed to the active octapeptide angiotensin 11 by the dipeptidyle carboxypeptidase angiotensin converting enzyme (ACE). Cleavage of AGT by renin is the rate limiting step in the activation of the RAAS. polymorphisms in RAAS genes for examples; (AGT M235T), angiotensin- converting enzyme (ACE I/D), angiotensin II type 1 receptor (AT1 A/C1166), and aldosterone synthase (CYP11B2-344T/C) have been major targets for genetic investigation in association with EH, the influence of these genetic factors is still to be determined (Miyama et al., 2007).

A study aimed to investigate the association between (3) polymorphisms of the RAAS and the EH in the population of Burkina Faso in West Africa. The AGT 235M/T and AT1R 1166A/C polymorphisms were not associated with the hypertension while the genotype frequencies of the ACE I/D polymorphism between patients and controls were significantly different and the DD (deletion ) genotype of the ACE gene is involved in susceptibility to HTN (Tchelougou et al., 2015).

In that population these genes ACE, AGT, AGTR1, and (CYP11β2), were studied and the result showed no evidence of association between RAAS-related genes and HTN (Charoen et al., 2019).

The AGT gene has been linked with human EH in Caucasians but the relationship in Asian populations has been less consistent. A study was done to examine genetic associations between HTN and the M235T, T174M, and G- 217A polymorphisms of the AGT in Chinese siblings, and the results were these variants M235T and T174M, especially the T235 allele, contribute to an increased risk of HTN in these Chinese subjects (Fang et al., 2010).

Angiotensin11 receptors, which mediate the vasoconstrictive and salt-conserving actions of the RAAS, also represent interesting candidate genes for EH. In humans, the AT1 receptor is present predominantly in vascular smooth muscle (VSM) cells, and the AT2 receptor is present in the uterus, brain, and adrenal medulla. Both subtypes are also expressed in the adrenal cortex and kidney. The AT1 receptor, through which the most of the actions of angiotensin 11 are exerted, is a GPCR spanning (7) transmembrane domain.

In Calabar and Uyo cities, Nigerian study was designed to determine the frequency of the A1166C polymorphism of the AT1R gene and its association with HTN, (99%) of the study population had the wild type AA genotype, and (1%) was AC heterozygous carriers of the A1166C polymorphism and so the A1166C polymorphism was not a predictor of HTN in the sample population of Calabar and Uyo.

A significant correlation of body sodium (Na+) and potassium (K+) with BP may suggest a role for aldosterone in EH. Aldosterone is an important cardiovascular hormone; (15%) of hypertensive subjects have alteration in aldosterone

18 regulation, defined by a raised ratio of aldosterone to rennin. Studies of the (CYP11β2) gene have focused on a SNP in the 5- promoter region (-344 C/T). Study was done in association with the 11β -hydroxylase which leads to increased ACTH to maintain cortisol production in subjects with EH, and the result was hypertensives homozygous for the (-344 T) allele of CYP11β2 demonstrate altered 11β-hydroxylase efficiency (CYP11β1); this is consistent with the hypothesis of a genetically determined increase in adrenal ACTH drive in these subjects. The correlation between excretion of aldosterone and cortisol metabolites suggested that, in TT subjects, ACTH exerts an important common regulatory influence on adrenal corticosteroid production in subjects with HTN (Freel et al., 2007).

Also the rennin gene (REN) is a good candidate implicated in the molecular etiology of EH. A (REN Mbo1) restriction fragment length polymorphism (RFLP) has been shown to be significantly associated with a family history of HTN in Japanese population. Investigation was done to Mbo1 genotype distributions in subjects from UAE and a statistically significant association was found between alleles on which the Mbo1 site is present and clinical diagnosis of EH indicating that the presence of Mbo1 site is a marker for susceptibility to HTN in the UAE; and variations of the REN (or of a nearby) gene that may be in linkage disequilibrium with this marker play a role in the development of EH in the UAE (Frossard, Lestringant, Elshahat, John, & Obineche, 1998). Another study in Korea investigated the associations between the REN gene and the risk of EH and BP levels in Koreans, they found that the A allele of rs6682082 in promoter region is a positive genetic marker for predisposition to EH and high BP in Korean women (Park, Song, Jang, & Kim Yoon, 2015).

The SNPs within RAAS have been reported to be significantly associated with HTN. In order to confirm this, a systemic research for the (GWAS) catalogue was done and after processing of data they found that the only SNP associated with a BP trait, SBP was rs17367504 which is located in the intronic region of MTHFR gene. Therefore, the effect of RAAS polymorphisms may have been overestimated during the 'candidate gene era' (Ji et al., 2017).

2.4.2 The G-protein B3 subunit

Several studies have demonstrated an association between G-protein polymorphisms and EH in some populations, although contradictive results also exist. G -proteins are heterotrimeric, consisting of α-, β-, and γ-subunits, of which there are at least (17, 5, and 6) known isoforms, respectively but a recent study has found a significant association of a polymorphism in pertussis toxin– sensitive G-protein b3 gene (GNB3; chromosome 12p13) with EH. The T allele of a C825T variant in (exon 10) of the G -protein b3 subunit gene (GNB3) induces formation of splice variant GNB3 with enhanced activity. This T allele of GNB3 was shown to be associated with HTN in German patients and also is confirmed by study in Australian white hypertensives (Benjafield, Jeyasingam, Nyholt, Griffiths, & Morris, 1998).

Genes encoding elements of the G-protein system are candidate genes in HTN and obesity. A study was done to determine the association between GNB3 polymorphism C825T and diabetes type 2 (T2DM) in polish population but they found that was not associated with type T2DM itself, nor with overweight and obesity, but was associated with diabetic hypertension and so this variant may be useful as a genetic marker of susceptibility to HTN and vascular complications in T2DM (Dzida et al., 2002). Another study, investigated the role of the C825T, C1429T, and G5177A polymorphisms of the β3 subunit of G-proteins in 20

EH in a group of Turkish subjects and the result showed that T allele frequency in overall population had significant association with HTN for C825T (Cabadak et al., 2011).

Another study was done to analyze the association of the C825T polymorphism of the GNB3 gene with the occurrence of HTN in a Portuguese population, and they found that this mutation is significantly associated with HTN (Sousa et al., 2018).

On the other hand a meta-analysis to evaluate the association between the GNB3 C825T polymorphism and hypertension or stroke was done and there was no evidence indicating that the 825T allele or TT genotype was associated with HTN or stroke in Asians or HTN in Caucasians. However, (Guo et al., 2013). Recommend that, further studies regarding Africans and other ethnicities are needed to identify further correlations.

2.4.3 α-adducin:

Adducin is one of the important candidate genes for EH. It is a heterodimeric or heterotetrameric protein that consists of α, β, and γ subunits; the (3) subunits are encoded by genes (ADD1, ADD2, and ADD3) located in (3) different chromosomes. Changes in SNPs at any of the adducin family gene increases the (Na+-K+- ATPase )activity of the renal tubular cell and increase the reabsorption of Na+ by renal tubular epithelial cells, which may cause HTN (J. R. Zhang, Hu, & Li, 2019).

A study to investigate the relationship between the α-adducin (ADD1) gene G460W and the (GNB3) gene C825T polymorphisms and EH conducted in a Northern Chinese Han population, the results revealed that α -adducin gene may be a susceptible gene to EH in Northern Chinese Han population, however, the 21

GNB3 gene C825T polymorphism may not play a significant role in EH in the same population (Huang et al., 2007).

Another study was carried out to examine a possible association between α-adducin gene G614T and EH patients with high LDL level in Chinese population showed significant association between ADD1 gene G614T polymorphism and EH in Chinese patients (L. Wang et al., 2014).

2.4.4 Other genetic polymorphisms

2.4.4.1Serine/Threonine Kinase gene (STK39)

GWAS of systolic and diastolic BP in Amish subjects was conducted and found strong association signals with common variants in a Serine/Threonine Kinase gene, STK39. This gene interacts with WNK kinases and cation-chloride co- transporters, mutations in which cause monogenic forms of BP dysregulation. Thus, variants in STK39 may lead to alteration in renal Na+-excretion (Y. Wang et al., 2009). This suggests that people with these hereditary factors might have a genetic predisposition to having high BP.

2.4.4.2 Sodium- Lithium Counter-transport (SLC)

The Sodium- Lithium Counter-transport (SLC) is a transport system that exchange Na+ (or Li+) for Li+ (or Na+) in the presence of ouabain, amiloride and Furosemide. This transporter SLC is an intermediate phenotype of EH, the discovery of its genes may have clinical importance. Association and linkage analyses of the SLC in lymphoblasts showed that a number of genomic regions harboring genes involved in glutathione metabolism might explain variations in SLC activity as glutathione reduce the oxidative stress that increased with HTN (Schork et al., 2002).

2.4.4.3E-selectin E- selectin, a cell-surface single chain glycoprotein, was firstly identified in 1985. It is a member of adhesion molecule, also known as endothelial leukocyte adhesion molecule-1(ELAM-1). EH is characterized by chronic inflammation which plays an important role in the pathogenesis and the maintenance of HTN. HBP may activate and damage the endothelial cells (ECs), and increase E- selectin. Subsequently, the adhesion and aggregation between leukocytes and EC occurs that lead to changes in microcirculation which increase the BP. In addition, E-selectin also has a pro-angiogenesis effect. E- selectin gene polymorphisms (A561C and C1839T) may be associated with EH, but the results are conflicting in different ethnic populations. Meta-analysis to investigate a more authentic association between E-selectin gene polymorphisms and the risk of EH was done, and concluded that the C allele of E-selectin A561C gene polymorphism might increase the EH risk in Asian population, whereas the T allele of E-selectin C1839T gene polymorphism might decrease the EH risk (Cai et al., 2014).

2.4.4.4 Methylene tetrahydrofolate reductase (MTHFR)

Active folate plays a vital role in amino acid conversion specifically in the homocysteine to methionine cycle. Methionine is an essential amino acid required for producing glutathione, the body’s primary antioxidant product. (MTHFR) is enzyme catalyzes the formation of 5-methylene-tetrahydrofolate, a co-substrate for the conversion of homocysteine to methionine. The most extensively studied genetic variation contributing to hyperhomocysteinemia is C to T SNP at nucleotide position 677 of MTHFR gene which causes an alanine (A) to valine (V) substitution at codon 222 within the catalytic region of the MTHFR protein. The MTHFR 677T variant is associated with the reduced

23 enzyme activity by about (70%) and (40%) in homozygotes and heterozygotes, respectively resulting in elevation of plasma homocysteine. A study to investigate the role of the MTHFR C677T SNP with predisposition to EH was done and a significant association of MTHFR 677CT-genotype as well as 677T- allele in predisposition of EH was found in both Caucasian and Asian populations (Qian, Lu, Tan, Liu, & Lu, 2007). Another study was done in Morocco and the homozygous mutant for 677TT of MTHFR gene is associated with the risk of HTN (Nassereddine, Kassogue, Korchi, Habbal, & Nadifi, 2015).

Figure 2.1: MTHFR pathway interaction (www.uniprot.org)

A defect in the MTHFR gene lead to an abnormally high level of homocysteine in tissues which is associated with CVDs, HBP, glaucoma, ischemic stroke, and atherosclerosis. The homozygous T allele of this gene has been associated with the formation of a thermolabile enzyme isoform with reduced activity that lead to hyperhomocysteinemia. Although, homocysteine pathway has not a direct control over BP, but any genetic alteration in this pathway can lead to hyperhomocysteinemia which may predispose to atherosclerosis by injuring the vascular endothelium and vasoconstriction subsequently result in HTN. MTHFR mutation is a problem associated with poor methylation and enzyme production. MTHFR mutations affect every person differently, sometimes with no symptoms at all, while other times leading to serious, long-term health problems (Lin Wan1, 2018). Other variants of this gene may be part of the observed HTN process in Mexican-Mestizo populations, reduced the promoter activity of the MTHFR regulatory region (Juan Carlos Pérez-Razo & Gilberto Vargas Alarcón, 2015)

Figure 2.2: Methionine – Homocysteine cycle (Chambers et al., Circ,Res.2001)

2.4.4.5 Adrenomodulin gene (ADM)

ADM initially isolated from the adrenal gland, has diverse physiological and pathophysiological functions in the cardiovascular system. It is produced in many organs and tissues including the vasculature. ADM is encoded by a gene in human chromosome 11 and consisting of (4) exons and (3) introns. It has numerous actions, including vasodilation, natriuresis, antiapoptosis and stimulation of NO production (Wong, Cheung, & Cheung, 2012). The protein encoded by this gene is a preprohormone which is cleaved to form (2) biologically active peptides, adrenomedullin (AM) and proadrenomedullin N- terminal 20 peptide (PAMP). AM and PAMP are potent hypotensive and vasodilatator agents. Numerous actions have been reported most related to the physiologic control of fluid and electrolyte hemostasis. In the kidney, AM is diuretic and natriuretic, and both AM and PAMP inhibit aldosterone secretion by direct adrenal actions. In pituitary gland, both peptides at physiologically relevant doses inhibit basal ACTH secretion. It function through signaling by GPCR, and G alpha (s) signalling events (www.genecards.org).

Systemic administration of ADM decreases the peripheral vascular resistance and lowers BP. Plasma ADM concentration is increased in patients with primary arterial hypertension and is higher in individuals with complications of HTN , such as left ventricular hypertrophy and nephrosclerosis (Be³towski & Jamroz, 2004). ADM and calcitonin gene-related peptide (CGRP) both peptides strongly depressed aldosterone production through angiotensin-II (Mazzocchi, Rebuffat, Gottardo, & Nussdorfer, 1996). GWAS of systolic and diastolic BP, which used a multi-stage design in (200,000) individuals of European descent, identified (16) novel loci: (6) of these loci contain genes previously known or suspected to regulate BP and ADM was one of them (Ehret et al., 2011).

Figure 2.3 : ADM pathway interaction (www.uniprot.org)

2.4.4.6 Vascular endothelial growth factor (VEGF) VEGF is a major mediator of angiogenesis; it binds to its receptor VEGFR2 (a receptor tyrosine kinase) on the surface of ECs and triggers dimerization and transphosphorylation to activate signaling cascades. These VEGF responses can be further promoted by a small number of VEGFR2 co-receptors. SCUBE2 (Signal peptide-complement protein C1r/C1s, Uegf, and Bmp1 [CUB]- epidermal growth factor [EGF] domain-containing protein 2) is the second member of a small, evolutionarily conserved gene family composed of (3) different genes (SCUBE1, 2, and 3) originally identified from human ECs. Endothelial SCUBE2 may be a novel co-receptor for VEGFR2 and potentiate VEGF-induced signaling in adult angiogenesis (Lin et al., 2016).

2.4.4.7 FSHR

Recently it has been found that the follicle-stimulating hormone receptor (FSHR) knockout mouse exhibits HTN. The effects of follicle-stimulating hormone (FSH) are mediated by its interaction with specific receptors and the activation of the stimulatory guanine nucleotide binding protein Gs, which stimulates the enzyme adenylyl cyclase. The FSH receptor (FSHR) belongs to the superfamily of GPCRs . So a study was done to investigate the association between polymorphisms in the human FSHR gene and EH by using SNPs and performed (2) genetic case–control studies in different populations. The result was that the SNP in the 5-untranslated region of the FSHR gene affects levels of transcriptional activity and is a susceptibility mutation of EH in women (Nakayama et al., 2006).

Despite maternal transmission of HTN in some pedigrees, pathophysiology of maternally inherited HTN remains poorly understood. A study to establish a relation between mitochondrial dysfunction and EH was done. Mutational 30 analysis of their mitochondrial genomes identified a novel mutation located at the processing site for the tRNA. These findings may help in understanding of the pathophysiology of maternally transmitted HTN (S. Wang et al., 2011).

2.4.4.8 kynureninase ( KYNU)

Genetic studies in mouse and human suggest that KYNU activity may influence BP and renal function. The gene coding KYNU is located on chromosome band (2q14-q23), where a linkage peak for EH was previously detected in the Chinese Han population. A study was done aimed to assess the role of (1) rare variant of KYNU, Arg188Gln, and kynureninase activity in relation to HTN. The results show that this rare KYNU variant Arg188Gln affects kynureninase activity and can predispose to EH(Y. Zhang et al., 2011).

3. Materials and Methods

3.1 Study design: It is a prospective, laboratory case control study. EH patients and healthy control subjects were included in this study. 3.2 Study area and population: The subjects were selected from residents of community in Shendi Locality .River Nile and Khartoum States, Sudan 2015-2019. 3.3 Inclusion criteria: Adult Sudanese subjects, either on treatment with antihypertensive medications and/or SBP (>140 mm Hg) and/or DBP (>90 mm Hg). 3.4 Exclusion criteria: -Current pregnancy -Metabolic diseases developed before the onset of HTN. -Thyroid, liver, kidney and CVDs developed before the onset of hypertension. -Normotensive subjects with SBP (<120 mm Hg) and (DBP <80 mm Hg); and no current use of antihypertensive medication and free from any history of the above mentioned diseases. 3.5 Sample size: The number of people will be consisted of middle-aged to elderly, (107) hypertensive cases and (114) control. 3.6 Data tools: All participants answered a questionnaire used for collecting socioeconomic data, as well as age, sex, ethnic group , family history of HTN , antihypertensive drugs used, other diseases and clinical examination including Wt, Ht, waist and hip measurement and Bp twice , also any relevant investigation (if present).

3.7 Study description and protocol: This study includes two phases: 3.7.1 Phase 1: Whole exome sequencing (WES):

3.7.1.1 Preparation of WES sample

i.A pedigree was constructed for (2) families having (3) generations with (13) members of them diagnosed as essential hypertension. Fig (3. 1, 2). ii.Thirteen hypertensive patients and (2) normotensive controls were recruited from (2) selected families for whole exome sequencing after signing a consent form. iii.All family members underwent investigations include renal function test (RFT) and abdominal ultrasound (all were normal). iv.Blood samples were obtained from each of the selected member .Genomic DNA was extracted from whole blood cells by standard methods using commercial kits ( kia gene) following the manufacturer`s instructions). v.DNA samples were sent for exome sequencing and analysis (PGI Inc. (China). vi.Whole exome sequencing was performed for (13) known hypertensive cases and (2) controls. The genomic DNA samples were enriched using TrueSeq library preparation kit v3 targeting a total length of (45Mb) of the human coding exons. The samples were paired-end sequenced on an illumine HiSeq 2000 platform. The sequencing service and alignment was provided by PGI Inc. (China).

Figure 3. 1: Family (1) pedigree

*EH1->HH10 are hypertensive patients

*EC2 is a healthy control

Figure 3.2: Family (2) pedigree

*MH1, MH2, MH3, MH4 are hypertensive patients

* DNA of MH2 sample was not sequenced

*MC2 is a healthy control

3.7.1.2 In-silico bioinformatics analysis: i. Variants which were detected by whole exome sequencing, evaluated and filtered on the basis of allele frequency in controls and predicted pathogenicity using bioinformatics tools. Prioritization was done to the variants that have a loss of function effect (stop-effect, frameshifts, splice- sites) or a damaging effect: (both Polymorphism Phenotyping v2 (PolyPhen-2) damaging (D) or probably damaging (P) prediction, Sorting Intolerant From Tolerant (SIFT) deleterious prediction (D) and Mutation Assessor high (H) or medium prediction (M)). ii. Candidate variants in genes known to cause EH were prioritized according to predicted pathogenicity and segregation. iii. Analysis of pathways and gene interaction of mutated genes shared by cases has been done using REACTOME database which is an open source, open access manually curated and peer reviewed pathway database aimed for interpretation, visualization and analysis of related pathways. 3.7.2 Phase II: Screening of the population: 3.7.2.1 DNA extraction: Peripheral blood sample was collected from each participant into EDTA tubes. DNA was isolated from whole blood samples manually using this method : i. Collect (5 ml) blood in EDTA tube wash (2-3 times) by RCLB (6000 rpm) for (10 mins) to collect the pellet . ii. Add (2 ml) lysis buffer, (10 µl) proteinase K, and (1 ml) guanidine chloride and (300 µl) NH4 acetate, incubate at (37°C) over night or (65°C) for (2 hrs). iii. Cool to room temperature, and then add (2 ml) pre chilled chloroform. 36

iv. Vortex and then centrifuge for (5 mins at 3000 rpm). v. Collect the upper layer to a new tube and add (10 ml) cold absolute ethanol, shake and keep at (-20°C ) for at least ( 2hrs) or overnight. vi. Centrifuge at (3000 rpm) for (15-20 mins), carefully drain the supernatant, invert the tube on a tissue paper for (5 mins). vii. Wash the pellet with (4 ml of 70% EtOH). viii. Centrifuge at (3000 rpm for 15 mins). ix. Pour off the supernatant and allow the pellet to dry for (10 min) (avoid over dry). x. Re-suspend the pellet in (200 µl) dH2O or TE (Tris EDTA), briefly vortex and put in (4 °C )overnight( in case of incomplete re-suspension put in (37 °C ) ovens for maximum (1hr) ). xi. Aliquot the DNA into stock solution (store at -20 °C) and working solution (store at 4 °C). 3.7.2.2 Primer Design: IDT (Integrated DNA Technology) was used to design the primers with probe that flanking the selected SNPs in coding region of the selected genes to be studied in population (MTHFR and ADM).Genes sequence was obtained from NCBI (https://www.ncbi.nlm.nih.gov) and the sequences around target SNPs were selected and entered to IDT website. Specific primers (forward and reverse with probe) were selected. No alignments were found between the final sequence of primers and other genome sequence using NCBI. The primers were obtained from Metabion International AG -Germany.

3.7.2.3The real-time PCR assay The real-time PCR assay primer sets; i. For the detection of MTHFR rs1801133

F- primer 5′ TCACAAAGCGGAAGAATG 3′ with (Tm 52 °C) , R- primer 5′ GAAGCACTTGAAGGAGAAG 3′ with (Tm 55°C) and the probe 6-Fam- ATGATGAAATCGACTCCCGCAGACAC-Tamra with (Tm 68 °C) were used to amplify fragments of approximately (89 bp).

ii. For the detection of ADM rs5005

F- primer 5′ TGGAATAAGTGGGCTCTG 3′ with (Tm 54 °C) , R- primer 5′ GCCGAATAAGGGTCTGG 3′ with (Tm 55°C) and the probe 6-Fam- CTGGACATCCGCAGTTCCCTCTTC-BHQ -1 with (Tm 69 °C) were used to amplify fragments of approximately (109 bp). iii. The real-time PCR protocol:

The real-time PCR was performed using Rotor Gene Q – Germany, with a total reaction volume of (20 μl). Each reaction mix contained (4μl) of 5x Hot FIREP probe Universal qPCR Mix, (1μl) each of the oligonucleotide primers, (0.5μl) of 6-Fam probe, (5 μl) of template DNA and (8.5μl) distilled water. A negative DNA control (using distilled water instead of template DNA) were included in each run. The thermal cycling conditions were as follows: Initial denaturation at (95 °C) for (10 mins), followed by (45 cycles) of (30s) denaturation at (95 °C), annealing at (60 °C) for (1min). The fluorescence intensity of the dye was measured during annealing step. At the end of each run, amplification curve was performed and samples crossed the threshold line at Ct- (Threshold Cycle) are positive and those did not cross it were negative.

3.8 Statistical analysis: Demographic data (age, sex, BMI, WH-ratio average systolic and diastolic blood pressure) and screening of MTHFR and ADM SNPs between cases and controls were done using Pearson Chi square test. Differences were considered significant with (P ≤o.o5). Statistical analysis was performed with the SPSS statistical package version 20.0. 3.9 Ethical consideration: Ethical clearance was obtained from the Ministry of Health, Khartoum State.

4. Results:

Phase I: Whole Exome Sequencing

4.1 Demographic characterization of the two families members:

Table 4.1: Demographic characteristics of hypertensive cases (13) and normotensive controls (2) in the two families

Parameters Patients with Control EH n=13 n=2 Gender (M/F) 6/7 1/1 Age, years 59.8 ±13.7 67±28. SBP (mmHg) 143.07 ±12.5 112.5±10.6 DBP (mmHg) 87.7±7.3 72.5±10.6 BMI 28.9±4.17 26.12 WH-ratio 0.93±0.13 0.9 Antihypertensive drugs calcium channel blockers 46.2 % angiotensin receptor inhibitor 38.5 % - Combination 7.7 % None 7.7 % Results were expressed as (Mean ± Standard Deviation (SD), hypertensive patients showed higher systolic-diastolic blood pressure, increased BMI and WH-ratio than control. Antihypertensive drug used was the calcium channel blockers fallowed by angiotensin receptor blockers.

4.2 Whole Exome Sequencing results:

4.2.1 In- silico analysis:

Whole exome sequencing of genomic DNA was done to (15) samples from two afro-asiatic families (family 1 and family 2) and revealed the presence of (296042) polymorphisms of which (9859) were novel. Prioritization according to mutations in genes shared between all hypertensive patients (13) but not by the normotensive participants (2) resulted in one SNP (rs141382822 in PRSS3 gene) and one InDel (rs566990199 in SOWAHA gene).

Table 4.2: Characteristic of the SNP shared between hypertensive patients and not by the controls (n =13/2).

DbSNP PolyPhen Mutation Function Gene Impact SIFT Chr Ref Obs 2 Assessor 0.88, rs1413 0.032 missense PRSS3 0.933 2.93(M) chr9 MODERATE 82822 (D) G C _variant (P,D)

This SNP is missense variant with moderate impact damaging in chromosome 9.

Table 4.3: Characteristic of the InDel shared between hypertensive patients and not by the controls (n =13/2).

DbSNP Function Gene Biotype Impact Chr Ref Obs disruptive protein_ GGCCG _inframe SOWAHA MODERATE rs566990199 chr5 G coding CCGCC insertion This is disruptive insertion mutation with moderate impact in chromosome 5.

4.2.2 Identification of variants related to hypertension:

According to Clinvar database, variants directly related to hypertension were identified and listed in table (4: 4, 5).

Table 4.4: Common SNPS in genes known to cause hypertension found in both families (n=15)

Function Gene Impact dbSNP Chr Ref Obs Frequency missense_ 12/15 MTHFR MODERATE rs1801133 chr1 G A variant missense_ Chr 11/15 ADM MODERATE rs5005 C G variant 11 missense_ Chr 4/15 GNB3 MODERATE rs5442 G A variant 12 missense_ 315 ADD2 MODERATE rs61030669 chr2 T A variant missense_ 7/15 ADD1 MODERATE rs4961 chr4 G T variant

All SNPs were missense with moderate impact in different chromosomes .

Table 4.5: Common InDels in genes known to cause hypertension found in both families (n=15).

DbSNP Function Gene Biotype Impact Chr Ref Obs Frequency frameshift protein_ Chr 15/15 OR8U1 HIGH rs778684909 AGT A _variant coding 11 frameshift protein_ Chr 10/15 WNK1 HIGH rs141823469 T TC _variant coding 12 frameshift protein_ Chr 10/15 WNK1 HIGH rs11441897 T TC _variant coding 12 frameshift protein_ Chr 13/15 SIRPA HIGH rs148409797 A AGT _variant coding 20 frameshift protein_ Chr 9/15 SRA1 HIGH rs3085220 A AGT _variant coding 5

All were frame shift mutations with high impact in different chromosomes

4.2.3 Individual family analysis:

Analyzing each family separately, (19) missense damaging SNPs, (17) InDels and (25) missense damaging SNPs, (22) indels were shared between all cases and not by their controls in family 1 and 2 respectively. Table (4: 6, 7, 8, 9)

Table 4.6: SNPSs found in all hypertensive and not in control sample in family 1(n=11)

DbSNP PolyPhen Mutation Function Gene Impact SIFT Chr Ref Obs 2 Assessor rs1801 0.002 2.965 Missense_ variant MTHFR MODERATE 0.941 (D) chr1 G A 133 (D) (M) rs7537 0.015 Missense_ variant CLSPN MODERATE 0.994(D) 2.71(M) chr1 T C 203 (D) rs5873 0.0 Missense_ variant LCE2A MODERATE 0.996(D) 2.93(M) chr1 G A 3562 (D) rs6182 0.011 Missense_ variant CAPN8 MODERATE 0.828(P) 3.05(M) chr1 G A 3553 (D) 0.635,0.0 rs4973 0.006 2.855 Missense_ variant SP140L MODERATE 26 chr2 T C 318 (D) (M) (P,B) rs1462 0.006 0.109,0.5 Missense_ variant PRDM5 MODERATE 2.14(M) chr4 T A 68537 (D) 58 (B,P)

0.851,0.0 rs2438 0.063 Missense_ variant FAM173B MODERATE 09 2.56(M) chr5 G A 652 (T) (P,B) RANBP3 rs1690 0.001 3.225 Missense_ variant MODERATE 0.999(D) chr5 G A L 2872 (D) (M) rs1114 0.039 Missense_ variant CCDC125 MODERATE 0.971 (D) 2.48(M) chr5 G C 17600 (D)

Missense_ variant+ rs3699 0.001 2.215 BDP1 MODERATE 0.912 (D) chr5 A T splice_ region_ variant 64684 (D) (M)

rs4720 0.061 Missense_ variant INMT MODERATE 0.995(D) 2.93(M) chr7 T G 015 (T) rs1095 0.047 Missense_ variant C7orf57 MODERATE 0.962(D) 2.71(M) chr7 G T 1942 (D) 0.032 0.88,0.93 PRSS3 rs1413 2.93(M) chr9 Missense_ variant MODERATE (D) 3 (P,D) G C 82822

rs7851 0.022 Missense_ variant FCN2 MODERATE 0.865 (P) 2.21(M) chr9 G T 696 (D) rs1120 0.017 Chr Missense_ variant FAM35A MODERATE 0.785(P) 2.3(M) A T 2365 (D) 10 rs1119 0.032 0.211,0.4 Chr Missense_ variant NRAP MODERATE 2.32(M) C T 6400 (D) 77 (B,P) 10 rs2230 0.007 Chr Missense_ variant GALNT4 MODERATE 0.753 (P) 2.24(M) C T 283 (D) 12 rs7882 0.001 Chr Missense_ variant PABPC3 MODERATE 0.953(D) 2.36(M) A G 6513 (D) 13 rs4824 0.035 chr Missense_ variant SSX5 MODERATE 0.721 (P) 2.36(M) C G 675 (D) X

Al l SNPs are missense variants, with moderate impact, damaging and in different chromosomes mainly chromosome 1, 5, 7 and 10.

Table 4.7: InDels found in all hypertensive patients and not in control sample in family 1(n=11)

dbSNP Function Gene Biotype Impact Chr Ref Obs

disruptive_inframe_ protein_ ANP32E MODERATE rs68136184 chr1 CTCCTCT C deletion coding AAAACTTGG protein_ frameshift_variant SULT1C3 HIGH rs540686743 chr2 TCAGGTGAT A coding GTTAT splice_ acceptor_ protein_ variant+ intron_ BDP1 HIGH rs201462177 chr5 C CT coding variant disruptive_inframe_ protein_ GGCCGCCG SOWAHA MODERATE rs566990199 chr5 G insertion coding CC disruptive_inframe_ protein_ WWC1 MODERATE rs111457550 chr5 TGGA T deletion coding disruptive_inframe_ protein_ FOXC1 MODERATE rs572346201 chr6 A ACGG insertion coding disruptive_inframe_ protein_ PRICKLE4 MODERATE rs140326303 chr6 C CCTT insertion coding

47 disruptive_inframe_ protein_ COBL MODERATE rs142060269 chr7 GTCT G deletion coding disruptive_inframe_ protein_ OR2A14 MODERATE rs66549240 chr7 ACTT A deletion coding protein_ frameshift_variant OR1B1 HIGH rs11421222 chr9 C CA coding disruptive_inframe_ protein_ Chr SCUBE2 MODERATE rs142900716 GGCA G deletion coding 11 frameshift_variant+ protein_ Chr PTGES3 HIGH rs10579382 CAT C start_lost coding 12 disruptive_inframe_ protein_ Chr BRI3BP MODERATE rs546819378 C CCTG insertion coding 12 CCTGCTG,C CTGCTGCT disruptive_inframe_ protein_ Chr JPH3 MODERATE ------C GCTGCTGC insertion coding 16 TGCTGCTG CTGCTG disruptive_inframe_ protein_ Chr EME1 MODERATE rs558756129 A AAGC insertion coding 17

disruptive_inframe_ protein_ Chr ZNF772 MODERATE rs528587884 A AGCC insertion coding 19 disruptive_inframe_ protein_ BMP15 MODERATE rs531409392 chrX C CTCT insertion coding

All InDels are disruptive inframe (deletion or insertion) or frame shift variants, all are protein coding with moderate impact except three of them which have high impact, distributed in different chromosomes mainly chromosome (5, 6, 7 and 12).

Table 4.8: SNPSs found in all hypertensive and not in control sample in family2 (n=4)

DbSNP PolyPhen Mutation Function Gene Impact SIFT Chr Ref Obs 2 Assessor rs11558 0.004 missense_variant HNMT MODERATE 538 (D) 0.602(P) 2.65(M) chr2 C T rs98302 0.046 missense_variant COL6A6 MODERATE 53 (D) 0.886(P) 2.72(M) chr3 G A 0.056 missense_variant rs37380 0.037 2.045 NEK11 MODERATE 00 (T,D) 0.998 (D) (M) chr3 A T 0.0,0. missense_variant SMPDL3A MODERATE rs28385 003 2.545 609 (D) 1.0(D) (M) chr6 C T rs13904 0.018 missense_variant POLR2J3 MODERATE 9967 (D) 0.647(P) 2.8(M) chr7 G C rs14138 0.032 0.88,0.93 missense_variant PRSS3 MODERATE 2822 (D) 3 (P,D) 2.93(M) chr9 G C

rs41179 0.007 3.435 missense_variant OR13C5 MODERATE 66 (D) 1.0(D) (M) chr9 C T rs10991 0.0 missense_variant OR13C2 MODERATE 326 (D) 0.91(D) 2.34(M) chr9 A T rs34163 0.02 2.085 chr1 missense_variant SYNPO2L MODERATE 229 (D) 0.459 (P) (M) 0 G T

rs60632 0.02 2.045 chr1 missense_variant SYNPO2L MODERATE 610 (D) 0.879(P) (M) 0 C T rs34844 0.001 chr1 missense_variant MUC6 MODERATE 844 (D) 0.994(D) 2.11(M) 1 G T 0.003 rs12363 0.054 0.842,0.9 chr1 missense_variant MS4A15 MODERATE 342 (D,T) 52 (P,D) 2.19(M) 1 A G rs11231 0.024 0.925,0.9 3.255 chr1 missense_variant SLC22A25 MODERATE 397 (D) 44 (D) (M) 1 C G rs22323 0.0 chr1 missense_variant KRT75 MODERATE 87 (D) 0.999(D) 4.315(H) 2 C T

rs38879 0.001 chr1 missense_variant KRT3 MODERATE 54 (D) 0.944(D) 3.975(H) 2 G C missense_variant+ 0.05, splice_region_vari rs15511 0.052 chr1 ant OTOGL MODERATE 22 (D,T) 0.91(D) 2.4(M) 2 A G CORO7- rs37475 0.039 0.11,0.98 3.335 chr1 missense_variant PAM16 MODERATE 79 (D) 8(B,D) (M) 6 C T rs72195 0.02 2.215 chr1 missense_variant KRT40 MODERATE 8 (D) 0.819(P) (M) 7 C G rs99083 0.004 2.235 chr1 missense_variant KRT40 MODERATE 04 (D) 0.984(D) (M) 7 G A rs20715 0.0 chr1 missense_variant KRT32 MODERATE 61 (D) 0.977(D) 4.51(H) 7 G T 0.021 rs62070 0.167 0.841,0.7 2.045 chr1 missense_variant PRR29 MODERATE 903 (D,T) 32(P) (M) 7 C G rs61751 0.001 chr1 missense_variant DHX34 MODERATE 860 (D) 0.973(D) 2.8(M) 9 C T

rs71263 0.038 0.906,0.9 chr1 missense_variant LILRB3 MODERATE 238 (D) 96(P,D) 3.13(M) 9 C T rs37459 0.034 0.88,0.03 3.425 chr1 missense_variant KIR3DL2 MODERATE 02 (D) (P,B) (M) 9 C T rs61744 0.004 0.942,0.8 chr2 missense_variant SEC14L4 MODERATE 139 (D) (D,P) 2.85(M) 2 C G

All SNPs are missense variants, with moderate impact, damaging and in different chromosomes mainly chromosome (9, 11, 12, 17 and 19).

Table 4.9: InDels found in all hypertensive and not in control sample in family2 (n=4)

dbSNP Function Gene Biotype Impact Chr Ref Obs

GAAATG frameshift_ protein_ rs75914 AIM1L HIGH chr1 AGGCAT G variant coding 0804 CA frameshift_ protein_ rs75562 AIM1L HIGH chr1 AGCAC A variant coding 3773 GGGGCC CTTCAC frameshift_ protein_ GACCTC AIM1L HIGH chr1 G variant coding TTTCCA GGTGGG GAACA splice_accept protein_ rs14583 or_variant+in EFCAB2 HIGH chr1 T TCCTCC coding 5471 tron_variant TTCAAA frameshift_ protein_ rs14569 SCRN3 HIGH chr2 TTTATC T variant coding 9077 AG frameshift_ protein_ rs11355 COL6A5 HIGH chr3 AT A variant coding 796 disruptive_ GTGGTG protein_ rs77087 inframe_ MUC4 MODERATE chr3 TCACCT G coding 8205 deletion GTGGAT

GCTGAG GAAGGG CTAGTG ACAGGA AGAGGC A frameshift_ protein_ rs75324 SLC9B1 HIGH chr4 AAC A variant coding 2024 disruptive_ protein_ rs56699 GGCCG inframe_ SOWAHA MODERATE chr5 G coding 0199 CCGCC insertion CGCGG disruptive_ CGCGGC protein_ CGGCG inframe_ C6orf223 MODERATE chr6 GGCGGC coding GCGGC insertion GGCG GGCG,C splice_accept or_variant+ splice_region protein_ rs14880 ZAN HIGH chr7 T TG _variant+ coding 0656 intron_ variant disruptive_ TMEM229 protein_ rs56632 CGCTGC inframe_ MODERATE chr7 C A coding 7350 T deletion frameshift_ protein_ rs14319 OR13C2 HIGH chr9 TGTTA T variant coding 8170

disruptive_ protein_ rs36998 ACGGCG inframe_ MEGF9 MODERATE chr9 A coding 9873 G deletion splice_dono variant+ splice_region CGAAGG _variant+intr PSMD5- rs72298 HIGH chr9 CGTGAG C on_variant+n AS1 225 TAATA on_coding_ transcript_ex on_ variant GGTGA CAGAG disruptive_ ACAAT protein_ Chr inframe_ MUC19 MODERATE G TGGAC coding 12 insertion TATCA GCTGG A CGCCT GCTGA GGGGT disruptive_ protein_ Chr GAGAG inframe_ FAM186A MODERATE C coding 12 AGATC insertion CCCAG AGCCT GGGCC

TGCTG AGGGG TGAGA GGGAT ACCCA GGGCC TGG frameshift_ protein_ rs77302 Chr FAM186A HIGH T TGA variant coding 6868 12 splice_dono_ protein_ rs14065 Chr variant+intro KRT3 HIGH T TA coding 3778 12 n_variant GGAGCC CACCTC disruptive_ AGAGCC protein_ rs77099 Chr inframe_ GP1BA MODERATE CGCCCC G coding 1996 17 deletion CAGCCC GACCAC CCCA frameshift_ protein_ rs11284 Chr CDC27 HIGH CA C variant coding 8754 17 frameshift_ protein_ rs66949 Chr SIGLEC12 HIGH G GC variant coding 844 19 All InDels are disruptive inframe (deletion or insertion) or frame shift variants, all are protein coding mostly with high to moderate impact, distributed in different chromosomes mainly chromosome (1, 9 and 12).

4.2.4 Pathways and interactions of the selected genes:

Variants identified within each family were grouped according to their functional pathways and interactions using REACTOME database (reactome.org). Table (4.10, 11).

Table 4.10: Grouping of mutated genes into different pathways

Identified pathway Genes involved Signal transduction pathway: GNB3, OR8U1, ADM, SIRPA1, (GPCR, receptor tyrosine kinase, SRA1, PTGES3, SCUBE2, WWC1, Glucagon signaling in metabolic OR1B1, OR2A14, ANP32E, BDP1, regulation, G alpha signaling, SYNPO2L,SCRN3, CDC27, COL6A6, events, Olfactory Signaling COL6A5, OR13C2, OR13C5, GP1BA Pathway) Immune system pathway, WNK1, SIRPA1, PRSS3, FCN2, complement system, lectin BDP1, SP140L, WWC1, FAM173B, pathway, cytokines, interleukins, NRAP, BRI3BP, SIGLEC12, SCRN3, interferon gamma signaling MUC19, CDC27, KIR3DL2, LILRB3, pathways. PRSS3, MUC4, MUC6. Information pathway (DNA repair, WNK1, PTGES3, EME1, CLSPN, gene expression, transcription BDP1, ZNF772, GALNTA4, NRAP, pathway, chromosomal and SP140L, BRI3BP, BMP15, CDC27, telomeres maintenance, chromatin GP1BA, MUC19, MUC4, MUC6, organization, methylation, histone, post translation modification, RNA polymerases, epigenetic regulation)

Metabolism (folate, fatty acid, MTHFR, GNB3, WNK1, ADD1, arachidonic acid, lipid, protein and PTGES3, SULTIC3, GALNT4, NRAP, water soluble vitamin and BRI3BP, INMT, MUC19, MUC4, cofactors metabolism, MUC6, HNMT, PRSS3, ADM Glucagon signaling in metabolic regulation, Inositol phosphate pathway). Ion channel transport GNB3, WNK1, FAM173B, PRDM5, (K channel pathway, Ca2+ SLC9B1, CDC27 pathway Cell cycle, apoptosis, programmed ADD1, PTGES3, CLSPN. cell death. Cell surface interactions and cell SIRPA1, CDC27 communication at the vascular wall. Chaperones activation and protein ADD1,GNB3,PGTES3, BRI3BP folding. Hemostasis GNB3, SIRPA1, SCRN3, GP1BA Mitochondrial translation WNK1

Table 4.11: Some genes co-express and/or interact with other genes

Gene Co-expression Genetic interaction MTHFR JPH3, PABPC3, TPK1 PTGES3, FOXC1, GNB3 JPH3 MTHFR PTGES3, BMP15 PTGES3 FAM35A MTHFR, JPH3, FCN2, PRICKLE4 ADM GNB3 WNK1 ADD1, SIRPA, ADD3, ADD1 ADD2 SLC9A3 KRT40

FAM186A KRT3,SLC9A3,MUC4, PRSS3

KIR3DL2 KRT40,SIG LEC12

Phase II: Screening of the population:

4.3 Case-control results:

Two variants were selected for population screening; MTHFR and ADM

4.3.1 MTHFR gene variant rs1801133 (G/A)

SIFT: 0.002 (D)

PolyPhen: 0.94 (D)

Mutation Assessor: 2.9 (M)

AF: 0.24

Figure 4 .1: MTHFR rs1801133.

This SNP is missense found in (12 out of 13) of the hypertensive patients in both families.

Figure 4.2 : Exome reads of the exons of MTHFR gene .

Figure 4.3: MTHFR rs1801133 alignment of the exome reads against reference genome

4.3.2 ADM gene variant rs5005 (C/G) :

SIFT: 0.133, 0.005 (T,D)

PolyPhen: 0.827 (P)

Mutation Assessor: 2.34 (M)

Figure 4.4 : Exome reads of the exons of ADM gene

Figure 4.5: ADM rs5005 alignment of the exome reads against reference genome 63

4.3.3 Characterization of study population:

A total of (107) hypertensive patients (M: F 0.43:1) and (114) controls (M: F 0.5:1) were enrolled in this study according to the above mentioned inclusion criteria. Analysis of anthropometric data revealed that there were significant differences in BMI and WH-ratio as well as in average SBP and DBP between cases and controls. BMI, WH-ratio were significantly correlated to both SBP (r=0.000, 0.03) and DBP (r=0.001, 0.01) respectively in controls. However, such correlation was not observed among hypertensive patients.

Table 4.12: Demographic characteristics of study population

Parameters Hypertensive Controls P value (n=107) (n=114) Gender (M/F) 32/75 (0.43:1) 38/76 (0.5:1) Age <30 1.9 % 21.9 % 30-45 16.0 % 22.8 % 46-60 50.0 % 45.6 % >60 32.1 % 9.6 % Ethnic groups Nilo-saharan 18.9 % 3.5 % Afro-asiatic 81.1 % 95.6 % Niger-congo 0 0.9 % Antihypertensive drug Yes 77.6 % - No 22.4 % SBP (mmHg) 143.6±17.9 119.5±12.2 0.000

DBP (mmHg) 89.0±8.9 78.2±7.6 0.000 BMI 28.6±5.3 26.6±5.8 .010 WH-ratio 0.94±0.1 0.86±0.1 .001 Results are expressed as (Mean ± Standard Deviation (SD).

Among hypertensive patients, (79.0%) were on drug control and the majority (47.7%) were on calcium channel blockers. (Fig 4.6). A significant difference was found between hypertensive and controls regarding family history of the HTN (P value 0.001), while no significant difference was found regarding CVD (P value 0.09).

47.7 50 45 40 35 30 25 20.6 15.8 20 15.0 15 10 5 0.9 0 beta-blockers calcium Angiotensin Combination None channel receptor blockers inhibitor

Figure 4.6: Antihypertensive drugs used among study group .

The commonest drug class used is calcium channel blockers.

100 87.5

80 65.8 60 Yes 40 34.2 12.5 No 20

0 HYP CON

Figure 4.7: Family history of hypertension among study population

HYP= hypertensive, CON= control.

High frequency of family history of HTN among both hypertensive and controls.

4.3.4 Genetic screening of MTHR and ADM SNPs

Figure 4.8: Real time PCR Amplification curve

In this curve samples crossed the threshold line are positive and those did not cross it were negative. This report was generated by Rotor-Gene Q Series Software 2.3.1.

Table 4.13: Frequency of the MTHFR and ADM SNPs among study groups

SNPs Hypertensive Control P value n=107 n=114 MTHFR Yes 78.5 % 65.3 % No 21.5 % 34.7 % 0.04 ADM Yes 69.2 % 56.8 % No 30.8 % 43.2 % 0.08 Significant difference in MTHFR SNP frequency was observed between hypertensive and controls (Odds ratio1.9, 95% CI 1.01- 3.7) while no significant difference in ADM SNP between hypertensive and control (Odds ratio 1.7, 95% CI 0.9- 3.1).

Table 4.14: Cross-tabulation between study groups and SNPs concerning gender

Male P value Female P value SNPs Hypertensive Control Hypertensive Control MTHFR 0.7 0.02 Yes 48% 52 % 57.6 % 42.3 % No 42.9 % 57.1 % 35.9 % 64.1 % ADM 0.5 0.08 Yes 48.8 % 51.2 % 56.8 % 43.2 % No 40.0 % 60 % 40.8 % 59.2 %

No significant difference in males between cases and control in both MTHFR and ADM (Odd ratio 1.2, 95% CI 0.3-4.0 and Odd ratio1.4, 95% CI 0.49-4.2 respectively). But there was significant difference in females between cases and control in MTHFR (Odds Ratio 2.4, 95% CI 1.1-5.3). While no significant difference in females between cases and control in ADM, Odds Ratio1.9 and 95% CI 0.9-3.9)

Table 4.15: Cross-tabulation between ethnic groups and SNPs frequency

Ethnic group MTHR P value ADM P value Yes No Yes No Nilo-saharan 94.7 % 5.3 % 91.3 % 8.7 % Afro-asiatic 68.9 % 31.1 % 0.01 58.4 % 41.6 % 0.002 Significant difference in frequency of both MTHFR and ADM SNPs between different ethnic group was observed (Odds Ratio8.1, 95% CI 1.0- 62 and Odds Ratio 7.5, 95% CI 1.7-33 respectively).

5. Discussion

Phase I: Whole Exome Sequencing

Genome-wide association and whole exome sequencing (WES) studies recently have become the method of choice to identify genes related to susceptibility to complex polygenic diseases in a population as in case of EH. Despite the huge data obtained, exome sequencing has a major role in discovering novel pathways of BP regulation and identifying susceptibility genes relate to HTN. This will augur a new era of novel drug development and stratification in the management of hypertension. However, variants in genes identified by WES should be tested at population level before confirming its effect on the disease.

In the first phase of this present study, (15) members of (2) families belonging to the Afro-asiatic ethnic group (Shwayga) and with strong family history of EH were selected for WES. Prioritization according to mutations in genes shared between all hypertensive patients in the (2) families combined and not by their controls resulted in one SNP in Serine Protease 3 gene (PRSS3) and one InDel in Sosondowah Ankyrin Repeat Domain Family Member A gene (SOWAHA). Both genes are not reported in Clinvar and are not directly related to HTN. SOWAHA gene is a protein coding gene and is likely to be disease-causing. However, no data is available for its pathways (www.genecards.org). On the other hand, PRSS3 is involved in the innate immune system and peptide ligand- binding receptors pathways. It is also related to calcium ion binding and serine- type peptidase activity (www.genecards.org).

Analyzing each family separately a total of (19, 25) SNPs and (17, 22) InDels were found in hypertensive cases and not shared by controls in family 1 and 2 respectively. Using REACTOME database analysis, identified variants were

69 grouped according to their pathways and gene interaction. Accordingly, genes were grouped into (10) pathways (signal transduction pathway, immune system pathways, informational pathways, metabolism pathways, ion channels transport pathways, cell cycle and apoptosis, Chaperones activation and protein folding, Hemostasis and mitochondrial translation), Table 4.10.

The results of the present study, showed that (19) of the total variants in both families are related to the immune system in a variety of ways including innate immune system complement system, lectin pathway, cytokines, interleukins, interferon gamma signaling pathways. It has been reported that the immune system in general interacts with hormonal and environmental factors to control BP and plays an important role in the pathogenesis of arterial HTN and hypertension end-organ damage (Sievers & Eckardt, 2019).

Interestingly, the results also revealed the presence of (20) variants related to G- protein coupled receptors (GPCRs). GPCRs are known to be involved in the pathophysiology of HTN.

Activation of these receptors through interaction of G-protein coupled receptor kinases (GRKs) and Regulator of G-Protein Signaling (RGS) proteins affect the phosphorylation state of the receptor leading to different biological responses. Defects in GPCR regulation via these modulators have severe consequences affecting pathological situations such as hypertension (Henriette L. Brinks, 2010). Increased expression of GRKs may play a role in HTN by reducing NO production and thereby deactivating one of the main vasodilatation responses in endothelial cells. GRKs are degraded upon β-adrenergic receptor stimulation and oxidative stress, which is often increased during disease states. On the other hand, heat-shock protein Hsp90 has an important role in maturation of GRKs and stabilization of its correct folding form. 70

These current results identified (4) variants (ADD1 rs4961, GNB3rs5442, PGTES3 rs10579382 and BRI3BP rs546819378) which are related to chaperones activation and protein folding. Hence, it will be hypothesized that these variants up-regulate the expression of GRKs and consequently increases the activation of GPCR.

Most patients with EH have a normal cardiac output but a raised peripheral vascular resistance which is determined by small arterioles. Contraction of the vascular smooth muscle (VSM) cells is related to a rise in intracellular Ca2+ concentration. Regarding the molecular pathways involved in hypertension, the information carried by Ca2+ signal is conveyed through GPCRs by various intracellular calcium binding motifs including Ca2+ channel proteins (Inositol triphosphate receptor (IP3R), ryanodine receptor (RYR) in the endoplasmic/sarcoplasmic reticulum) and proteins mediating calcium-controlled cell function. These proteins associated with effecter proteins (calmodulin (CaM) or troponin C) (Rafaela Bagur1 and Gyo¨ rgy Hajno´ czky1, 2017 ). Ca2+ activates the Ca2+/calmodulin dependent myosin light chain kinase (MLCK) to phosphorylate the regulatory light chain of myosin, allowing for the interaction of myosin with actin, thus affecting constriction of smooth muscle. Ca2+ influx and therefore the intracellular Ca2+ concentration is influenced by GPCR signaling pathway.

RAAS system is known to play important role in BP regulation, Angiotensin II, an important component of the RAAS system, mediates vasoconstriction through GPCR pathway. It increases intracellular Ca2+ by activation of IP3- sensitive Ca2+ stores. The role of phospholipase C (PLC) in HTN is a mediator of vasoconstriction, through increased PKC and hence increase Ca2+ levels. In hypertensive rats, protein levels of both PLC and PKC isoforms are upregulated,

71 suggesting augmented signaling via this pathway through GPCRs (Henriette L. Brinks, 2010).

A diagram was constructed for GPCRs signaling pathway that modulate vascular tone in VSM cell. Figure 51.

Figure 5.1: GPCR signaling pathway that modulate vascular tone in VSM cell.

* (GPCR) G-protein couple receptor, (PLC) phospholipase C, (IP3) Inositol triphosphate, (DAG) diacyleglycerol, (PKC) protein kinase C, (I.C.Ca) intracellular calcium, (Ca.M) calcium calmodulin, (MLCK) myosin light chain kinase, (LCM) light chain myosin, (VSM) vascular smooth muscle, (cAMP) cyclic adenosine monophosphate .

These results identified about (20) variants related to GPCRs regulation, these include; ADM, GNB3, OR8U1, SIRPA1, SRA1, PTGES3, SCUBE2, WWC1, OR1B1, OR2A14, ANP32E, BDP1, SYNPO2L, SCRN3, CDC27, COL6A6, COL6A5, OR13C2, OR13C5, GP1BA. Some of these genes were reported to have an association with EH according to Clinvar database, Figure 5.2.

Figure 5.2: Network of hypertension genes (genemania.org).

The above mentioned genes, were regulated the expression of GPCRs in different ways. Guanine nucleotide-binding proteins -G proteins- Subunit Beta 3 (GNB3rs5442) integrates signals between receptors and effector proteins in various transmembrane signaling systems and has been reported to be associated with EH, in Portuguese population there was a significant association with HTN and the C825T polymorphism of the GNB3 gene (Sousa et al., 2018). 74

Adrenomedullin (ADM) gene is up-regulated by oxidative stress, proinflammatory cytokines such as TNF-and IL-1, angiotensin II, endothelin-1, hyperglycemia, atrial natriuretic peptide (ANP) and aldosterone. ADM activates at least two types of G-protein-coupled receptors (Be³towski & Jamroz, 2004).

Olfactory Receptor Family 8 Subfamily U Member 1(OR8U1 rs778684909) acts through GPCRs and olfactory transduction pathways. Of interest, This variant was detected in all sequenced exomes of this study.

Steroid Receptor RNA Activator 1 (SRA1 rs3085220) also functions through GPCR Pathway and is related to transcription and nuclear receptor transcription coactivator activity.

Signal Regulatory Protein Alpha (SIRPA rs148409797) is related to innate immune system and cell surface interactions at the vascular wall. Involved in the negative regulation of receptor-tyrosine kinase coupled cellular responses.

A novel InDel in Junctophilin 3 gene (JPH3) located in chromosome 16 was detected in (9) out of the (15) sequenced exomes. However, it was not detected in the control samples. JPH3 gene belongs to the junctophilin gene family and contributes to the formation of junctional membrane complexes (JMCs) which link the plasma membrane with the endoplasmic or sarcoplasmic reticulum in excitable cells. Hence, it provides a structural foundation for functional cross- talk between the cell surface and intracellular Ca2+ release channels. Interestingly this gene has genetic interaction with short Transient Receptor Potential Channel 3 gene (TRPC3) to form a receptor-activated non-selective Ca2+ permeate cation channel. The proposed mechanism of action is via a phosphatidylinositol second messenger system activated by receptor tyrosine kinases or GPCRs and activated by diacylglycerol (DAG), independently of

PKC, and by Inositol triphosphate receptors (ITPR) which bound IP3. This mutation should be considered as it may have a role in calcium signaling cascade.

Figure 5.3 : JPH3 pathway interaction (www.uniprot.org).

The results highlight the importance of these variants among Sudanese of the Afro-asiatic ethnic group and their role in modifying GPCRs signaling pathway which leads to an increased intracellular Ca+2 release leading to vascular contraction and eventually increases blood pressure.

Mutations in genes associated with certain metabolic pathways were also observed in the recent results. These (16) variants were reported to play a role in the metabolism of lipid, protein, water soluble vitamins, including folate, and glucagon signaling. These results also revealed that some of the detected variants are related to lipid and lipoproteins metabolism (PTGES3 rs10579382, BRI3BP rs546819378). PTGES3 is involved arachidonic acid metabolism. Arachidonic acid is the precursor of all prostanoids including prostaglandins (PG), thromboxanes (TX) and protacyclins. It has been reported that PGE₂ have a vasodilator effect thus lowering systemic arterial pressure and it also inhibits the release of noradrenaline from sympathetic nerve terminals. However, Txs are known to cause vasoconstriction and thus up regulate BP (Das, 2018) . BRI3BP, on the other hand, is involved in IP3 signaling pathway which is related to GPCRs.

A variant in methylene tetrahydrofolate reductase gene (MTHFR, rs1801133) is also detected in (12) out of the (15) sequenced exomes and interestingly it was not detected in any of the two control samples. MTHFR catalyzes the conversion of 5, 10 - methylene tetrahydrofolate to 5 -Methyltetrahydrofolate, a co-substrate for homocysteine remethylation to methionine. Genetic variation in this gene influences susceptibility to occlusive vascular disease and is reported to be associated with EH. MTHFR deficiency results in increased level of homocysteine leading to hyperhomocysteinemia which induces arteriolar constriction, renal dysfunction, increased sodium reabsorption, increase arterial stiffness and oxidative stress, all associated with development of HTN.

Phase II: Screening of the population

SNPs identified by exome sequencing must be tested at population level in order to confirm their association with the disease. In the current study, (2) selected SNPs in (2) genes to evaluate their relation to EH. The first, (MTHFR, rs1801133), is related to the metabolic pathway and the second, (ADM, rs5005) is associated with the GPCRs pathway.

Analysis of anthropometric data revealed that there was significant differences in BMI and WH-ratio as well as in average SBP and DBP between cases and controls. BMI, WH-ratio were significantly correlated to both SBP (r=0.000, 0.03) and DBP (r=0.001, 0.01) respectively in controls. However, such correlation was not observed among hypertensive patients. This finding was consistence with the study done in china and revealed that the association between BMI and BP was substantially weaker in patients taking antihypertensive treatment compared with those who were untreated (George C. Linderman, 2018). However, the average SBP and DBP were reported to be increased signiﬁcantly across BMI, which suggests the effect of BMI on BP and to be consider as independent risk factors for HTN (Francesco Landi 2018). Another study revealed that SBP was positively correlated with Waist by Hip ratio and DBP was positively correlated with Waist Circumference and were statistically highly significant. This is stronger correlation than BMI even in normal subjects (Sonam Chaudhary & Munna Alam, 2018).

The fact that (91%) of the selected hypertensive cases have a positive family history of hypertension compared to (65%) of the control samples (P value = 0.001) reflects the role of genetics in development of EH. Among hypertensive patients, (79.0%) were on drug control of which (47.7%) were on Ca2+channel blockers. This may explain the role of increased intracellular Ca2+in molecular 78 signaling which leads to the VSM contraction of these hypertensive cases. Hence, it is likely that calcium channel blockers are the drug of choice among the cases as they decrease intracellular Ca2+ level leading to vasodilatation and subsequently reduce the BP.

Genetic screening of study population for MTHFR (rs1801133 (G/A)) revealed significant difference between hypertensive and control subjects (P = 0.04). Similar results were reported among different population. A study among Turkish population concluded that this variant is an independent risk factor for EH (Nevin Ilhan, 2008). Yang et al in a meta-analysis study reported the association of this SNP with EH among East Asians and Caucasians and it was recommended that this variant should be studied among African population (Yang et al., 2014). In Cameron, a study revealed an association between this variant and hypertension in Cameroonian patients from the South West Region (Ghogomu, Ngolle, Mouliom, & Asa, 2016).

Noteworthy, the significant difference in this polymorphism between hypertensive cases and normal controls was only observed among female participants suggesting that this SNP is gender specific and may increase the susceptibility to EH only among females. However, a larger population size is required in order to confirm the results of this study..

Vitamins have important role as coenzyme in regulation of different metabolic pathway. Riboflavin supplementation in patients with MTHFFR 677TT was proved to lower the BP more effectively than treatment with current antihypertensive drugs only (Wilson et al., 2013). On the other hand, increased level of homocysteine may be associated with young-onset EH and supplementation with folic acid, vitamins B6 and B12 decreases or even normalizes plasma homocysteine concentrations in most cases (VAM Garfunkel, 79

2003). A recent study in Sudan investigated the levels of homocysteine and folic acid in cardiovascular accident (CVA) patients in River Nile state and found a significantly high homocysteine level among CVA patients and a significant low level of folic acid (unpublished data 2019 ).

It was also investigated the prevalence of a specific SNP (rs5005) in ADM gene. According to the results, no significant difference in prevalence was observed between hypertensive and control subjects (P value 0.08). This is consistent with a study among Chinese population which concluded that genetic variations in the ADM gene were not associated with the risk of HTN. Other studies suggested the existence of sex-specific ADM variants affecting male susceptibility to EH in association with other genes variants (NLRP6/AVR ) (Glorioso1 et al., 2013).

Although there was significantly high frequency of both mutations MTHFR and ADM (P = 0.01, 0.002 respectively) in the (2) ethnic groups, it was observed that Nilo-saharan had the high frequency (94.7%) for MTHFR, (91.3 %) for ADM in Nilo-saharan and (68.9 %, 58.4 %) in Afro-asiatic respectively. Variation in prevalence and severity of EH depends on ethnicity. It was reported to be higher and more severe in American Blacks as compared to Whites and Mexican Americans. Moreover, Blacks are more likely to develop resistant phenotype of the disease which might be fatal at an early age (Brewster et al., 2004).

Conclusions

This is the first study in Sudan applying whole exome sequencing as a method to detect important and novel variants associated with susceptibility to EH. This study identified a total of (47) variants in genes that might play a role in blood pressure regulation in (10) different pathways. Analyzing pathways and gene interaction of mutated genes showed that most of these genes were related to metabolic pathways specially lipid and lipoproteins metabolism while others function in the immune system and signal transduction pathways. An important finding of this in silico analysis is the fact that most of these genes act through GPCRs which lead to increased intracellular calcium release. The down-stream signaling of calcium lead to vascular smooth muscle contraction and increased vascular resistance resulting in high blood pressure. A novel variant in JPH3 gene is identified and might play a role in blood pressure regulation as it acts through GPCRs pathway and interact with other genes related to calcium metabolism. These results highlighted the importance of a variant of MTHFR (rs1801133) as a possible genetic marker for EH among Sudanese specially those of Nilo- saharan and afro-asiatic ethnic groups.

Recommendations

 To evaluate allele frequencies of all detected SNPs and Indel among Sudanese population including the three ethnic groups in order to identify block/blocks of variants associated with susceptibility to hypertension.  GPCRs regulation offers a broad and potent base for further study and development of therapeutic options to overcome the complex disorders such as HTN.  Genotyping for MTHFR rs1801133 is recommended in large sample size.  Estimation of serum Homocysteine and associated vitamins (B12and Folic acid) in hypertensive patients.  To screen the genes involving in different pathways (signal transduction , immune system and complement , informational pathway and gene expression , metabolism, hemostasis , apoptosis ) and the novel mutation in JPH3 gene in general population.  To select other ethnic groups to determine the specific block of genes which might be involved in development of HTN in Sudan.  More detailed knowledge about the molecular pathways involved in pathophysiology of HTN and BP regulation are needed to improve the current understanding of the molecular mechanisms responsible for the development of the disease and proper selection of antihypertensive drug to control blood pressure and prevent its complication.  More studies must be done to elucidate the interactions between heterogeneous genetic backgrounds, different environmental factors, and differential etiologies in the pathogenesis of this disorder.

 There is the need for different approaches to understand the complex, polygenetic disorders implementing gene-gene, and gene-environment interactions under standardized environmental conditions.  Further studies regarding Africans and other ethnicities are needed to identify further correlations.

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Genetics of Essential Hypertension

Case Code:

A. Personal History: 1. Name: …………………………. Mobile No: 2. Sex: M F 3. Age:

4. Tribe: Ethnic Group:

5. Marital Status: Single Married Divorced Widowed

6. Consignuity: Yes No

B. Medical History: are you suffering from any of these diseases?

7. Hypertension: Yes No

8. Diabetes: Yes No

9. CVD Yes No

10. Renal Disease: Yes No

11. Others…………………………………………….

C. Drug History:

13. Drugs used for treatment of hypertension: 1. ……………………….. 2………………………..

3. ……………………………………. 4. ……………………………………….. 5. ……………………………………..

D. Family History:

14. Hypertension: yes No

If yes specify: parents siblings child uncle/aunt

Others

15. CVD: Yes No

16. O/E:  Weight: Height BMI

Waist Hip

 Blood pressure measurement:

 1st Systolic 1st Diastolic

 2ndsystolic 2nd Diastolic

17. Laboratory investigations: 1. Blood Glucose ……………………………….

2. TG………………………………………………..

3. LDL…………………………………………………..

4. HDL………………………………………………..

5. Uric acid………………………………………………..

6. Urea………………………………………………..

7. Creatinine……………………………………………….

8. Others………………………………………………..

The real time PCR machine