FREQUENCY OF ABNORMAL ELECTROENCEPHALOGRAM IN ASYMPTOMATIC RELATIVES OF PATIENS WITH EPILEPSY: A SYSTEMATIC REVIEW AND META-ANALYSIS
by
Mariam Tashkandi
A thesis submitted in conformity with the requirements for the degree of Masters of Science in Clinical Epidemiology Graduate Department of Institute of Medical Science University of Toronto
© Copyright by Mariam Tashkandi 2016
Frequency of Abnormal Electroencephalogram in Asymptomatic Relatives of Patients with Epilepsy: A Systematic Review and Meta-analysis
Mariam Tashkandi
Master of Science
Institute of Medical Science University of Toronto
2016 Abstract
Objective: To systematically review studies of asymptomatic relatives of patients with
Juvenile Myoclonic (JME), Childhood Absence (CAE) and Benign Rolandic (RE)
Epilepsy who had an abnormal electroencephalogram (EEG) recording and determine the frequency of these waves through meta-analysis in order to better understand the genetics and mode of inheritance of idiopathic epilepsy.
Methods: MEDLINE, EMBASE, CINHAL and Cochrane databases were searched. Two independent reviewers conducted all screening levels, data abstraction, and quality appraisal. A meta-analysis was performed.
Results: After screening 10,233 citations and 211 full-text articles, 15 studies were included. A total 3885 asymptomatic relatives were included. The prevalence of all abnormal waves in asymptomatic relatives was 31%. Prevalence for each epilepsy type was 21% for JME, 42% for CAE and 33% for RE.
Conclusion: Further investigations are needed to test inheritance patterns to identify
“major” genes.
ii ACKNOWLEDGMENTS
First, I would like to express my deepest and sincerest gratitude to my supervisor Dr. Berge Minassian, for his patience, motivation, understanding and encouragement. I could not have imagined having a better advisor and mentor for my Masters study.
I would like to thank the members of my primary advisory committee; Dr. Muhammad Mamdani whose sincerity and encouragement I will never forget. Dr. Mamdani has been my inspiration; he helped me overcome all the obstacles in completion of this degree. Working with him has been a privilege. I am also deeply grateful to Dr. Sharon Straus, for her understanding, encouragement and guidance throughout my training in Canada. Special gratitude goes to Dr. Andrea Tricco for her encouragement, thoughtful advice and personal guidance. Her broad knowledge, logical way of thinking and efficiency inspired me to work harder and accomplish great things.
I would also like to thank my examiners, Dr. Lisa Strug, Dr. Paul Hwang and Dr. Antonio Delgado-Escueta for their time, help and guidance.
My Sincere gratitude goes to Dr. Mohammad Al-Omran for giving me the opportunity to work with him and his team at the KSU-LKSKI research collaboration program and for encouraging me to do my MSc degree at the IMS.
I am grateful to Dr. Duaa Baarmah, Dr. Alaa Baarmah, Dr. Cyrus Boelman, Dr. Jemila Hamid as well as Laure Perrier and David Newton for their knowledge and help. This project could not have been done without their hard work and support.
Finally my greatest appreciation goes to my family, in particular, my husband Dr. Husni Alakkad and to our three wonderful kids Abdullah, Raneem and Randa (who just turned one year old!), for bearing with me and supporting me the past years in every way possible. And, above all, thank you to my parents and brother (Ibrahim) for all their patience, support and help when I needed them the most.
iii CONTRIBUTIONS
This thesis would not have been possible without the guidance and help of several individuals who contributed in one way or another in the completion of this study, among those people I would like to mention the following names:
Dr. Duaa Baarmah, the second reviewer. She contributed in all levels of screening and data abstraction; she also contributed in editing the thesis.
Dr. Jemila Hamid, we consulted Dr. Jemila on statistical methods using the R program for this review.
Dr. Cyrus Boelman, proofread and edited the thesis.
My Supervisor, Dr. Berge Minassian, as well as my Primary Advisory Committee (PAC) Members; Dr. Sharon Straus, Dr. Muhammad Mamdani and Dr. Andrea Tricco
iv
Table of Contents ABSTRACT…………………………………………………………………………………………………………..ii ACKNOWLEDGMENTS ...... iii CONTRIBUTIONS ...... iv List of Abbreviations ...... ix Table of Contents ...... v List of Tables ...... ix List of Figures ...... xi List of Appendices ...... xii Chapter 1: Introduction ...... 1 1.1 Background and Rationale ...... 1 1.2 Description of The Condition ...... 3 1.2.1 Juvenile Myoclonic Epilepsy (JME) ...... 6 1.2.2 Childhood Absence Epilepsy (CAE) ...... 8 1.2.3 Rolandic Epilepsy (RE) ...... 9 1.3 Modes of Inheritance ...... 11 1.3.1 Mendelian Inheritance ...... 11 1.3.2 Multifactorial “Complex” Inheritance ...... 14 1.3.3 Genetic Variations ...... 15 1.4 Description of The Electroencephalogram As a Diagnostic Test ...... 17 1.5 How The Electroencephalogram Might Work ...... 18 1.6 History of Systematic Reviews and Meta-analyses ...... 19 1.7 Promises and Pitfalls of Meta-analyses ...... 22 1.8 Methods of Conducting Systematic Reviews ...... 24 1.8.1 Narrative Synthesis ...... 24 1.8.2 Quantitative Data Synthesis ...... 24 1.8.3 Subgroup Analysis ...... 26 1.8.4 Sensitivity Analysis ...... 26
v 1.9 Graphic Display of the Results of Systematic Quantitative Reviews ...... 28 1.9.1 Forest Plots ...... 28 1.9.2 Funnel Plot ...... 28 1.10 Heterogeneity ...... 28 1.10.1 Identifying and Measuring Heterogeneity ...... 29 1.10.2 Calculating Statistical Models of Heterogenity ...... 30 1.10.3 Investigating Heterogeneity ...... 31 1.12 Risk of Bias and Quality Assessment ...... 31 1.13 The Importance of this Review ...... 32 1.14 Objectives of our review ...... 34 Chapter 2: Methods ...... 35 2.1 Review Question ...... 35 2.2 Protocol ...... 35 2.3 Inclusion Criteria ...... 35 2.4 Exclusion Criteria ...... 35 2.5 Population ...... 36 2.6 Diagnostic Test – Electroencephalogram ...... 36 2.7 Outcome Measures ...... 36 2.7.1 Primary Outcome ...... 36 2.7.2 Secondary Outcome ...... 36 2.8 Search Strategy ...... 37 2.9 Data Collection and Analysis ...... 39 2.9.1 Selection of Studies ...... 39 2.9.2 Verification of Study Eligibility ...... 41 2.9.3 Data Extraction and Management ...... 42 2.9.4 Dealing with Missing Data ...... 42 2.9.5 Quality Appraisal Tool for Included Studies ...... 42 2.9.6 Data Synthesis ...... 43 2.9.7 Subgroup Analysis and Investigation of Heterogeneity ...... 43 2.9.8 Sensitivity Analysis ...... 43 2.10 Statistical Methods ...... 44
vi 2.10.1 Fixed and Random effect models ...... 44 2.10.2 Heterogeneity ...... 45 Chapter 3: Results ...... 47 3.1 Systematic Review Results ...... 47 3.1.1 Literature Search ...... 47 3.1.2 Study Characteristics ...... 58 3.1.3 Electroencephalographs Characteristics ...... 58 3.1.4 Participants Characteristics ...... 63 3.1.5 Outcomes ...... 68 3.2 Statistical Analysis - Meta-analysis Results ...... 78 3.2.1 Studies Included in Meta-analysis ...... 78 3.2.2 Studies Excluded in Meta-analysis ...... 78 3.2.3 Meta-analysis on Abnormal EEG in Asymptomatic Relatives of JME, CAE and RE Patients ...... 80 3.2.4 Subgroup Analysis of Abnormal EEG Waves in Asymptomatic Relatives by Epilepsy Type ...... 81 3.2.5 Subgroup Analysis of Asymptomatic Relatives by EEG Abnormal Wave Type ...... 83 3.2.6 Asymptomatic Sibling’s Analysis ...... 90 3.2.7 Subgroup analysis of Abnormal EEG waves in Asymptomatic Siblings by Epilepsy Type ...... 90 3.2.8 Subgroup Analysis of Asymptomatic Siblings by EEG Abnormal Wave ..... 92 3.3 Sensitivity Analysis Results ...... 96 3.3.1 Sensitivity Analysis of Abnormal EEG waves in JME, CAE and RE Relatives ...... 96 3.3.2 Sensitivity Analysis of Abnormal EEG waves according to Epilepsy type in Relatives ...... 98 3.3.3 Sensitivity Analysis of Abnormal EEG in Siblings ...... 100 3.3.4 Sensitivity Analysis by Epilepsy Type in Siblings ...... 101 3.3.5 Sensitivity Analysis of Abnormal EEG in Parents ...... 103 3.4 Comparison Between Meta-analysis and Sensitivity Analysis Results ...... 104
vii 3.5 Funnel Plot ...... 108 3.6 Methodological Quality ...... 110 Chapter 4: Discussion, Conclusion and Future Directions...... 112 4.1 Discussion ...... 112 4.2 Limitations ...... 119 4.3 Conclusion ...... 121 4.4 Future Direction ...... 122 Appendices ...... 124 Appendix 1 ...... 124 Appendix 2 ...... 126 Quality assessment (Cross-sectional studies)* ...... 130 Appendix 4 ...... 131 Quality assessment (Cohort studies)* ...... 131 References ...... 132 References of Included Studies ...... 140 References of Excluded Studies ...... 142
viii List of Abbreviations
ILAE International League Against Epilepsy AED Antiepileptic Drugs EEG Electroencephalogram PSW Polyspike-wave IGE Idiopathic Generalized Epilepsies JME Juvenile Myoclonic Epilepsy CAE Childhood Absence Epilepsy RE Rolandic Epilepsy GTCS Generalized Tonic Clonic Seizures BECTS Benign Epilepsy with Centro-temporal Spikes CTS Centro-temporal Spikes RCT Randomized Controlled Trials QUOROM Quality Of Reporting Of Meta-analyses PRISMA Preferred Reporting Items for Systematic Reviews and Meta-analyses PRISMA-P Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols SR Systematic Reviews NOS Newcastle-Ottawa Scale PROSPERO International Prospective Register of Systematic Reviews Medline Medical Literature Analysis and Retrieval System Online CINHAL Cumulative Index of Nursing and Allied Health Literature EMBASE Excerpta Medica database PRESS Peer Review of Electronic Search Strategies Checklist CI Confidence Interval PPR Photoparoxysmal Response PCR Photoconvulsive Response
ix List of Tables Table 1: Electronic Databases and Terminology ...... 38 Table 2: Interpretations of Kappa Statistics ...... 40 Table 3: Electronic Database Search Results ...... 50 Table 4: Number of Non-English Papers Potentially Relevant For Inclusion ...... 51 Table 5: Excluded Studies and Reason for Exclusion ...... 52 Table 6: Study Characteristics ...... 60 Table 7: Patients Characteristics ...... 64 Table 8: Asymptomatic Relatives Characteristics ...... 66 Table 9: Abnormal Electroencephalogram Waves in Epileptic Probands ...... 71 Table 10: Abnormal Electroencephalogram Waves in Asyptomatic Relatives ...... 74 Table 11: Abnormal Electroencephalogram Waves in Asymptomatic Siblings ...... 76 Table 12: Abnormal Electroencephalogram Waves in Parents ...... 77 Table 13: Abnormal Electroencephalogram Waves in Offspring ...... 77 Table 14: Excluded Studies in Meta-analysis and Reason for Exclusion ...... 79 Table 15: Comparison Between Meta-analysis and Sensitivity-analysis Results [by Epilepsy Type] ...... 106 Table 16: Comparison Between Meta-analysis and Sensitivity-analysis Results [by abnormal EEG Waves] ...... 107
x List of Figures Figure 1: Verification of Study Eligibility ...... 41 Figure 2: Study Flow Chart ...... 49 Figure 3: Prevalence of Abnormal EEG in Asymptomatic Relatives (Studies n=10) . 80 Figure 4: Prevalence of Abnormal EEG in Asymptomatic Relatives by Epilepsy Type ...... 82 Figure 5: Prevalence of Polyspike Waves in Asymptomatic Relatives ...... 85 Figure 6: Prevalence of 3Hz Spike Waves in Asymptomatic Relatives ...... 86 Figure 7: Prevalence of Centrotemporal Waves in Asymptomatic Relatives ...... 87 Figure 8: Prevalence of Theta Waves in Asymptomatic Relatives ...... 88 Figure 9: Prevalence of PPR/PCR in Asymptomatic Relatives ...... 89 Figure 10: Prevalence of Abnormal EEG in Asymptomatic Siblings by Epilepsy Type ...... 91 Figure 11: Prevalence of Polyspike Waves in Asymptomatic Siblings ...... 93 Figure 12: Prevalence of 3Hz Spikes Waves in Asymptomatic Siblings ...... 94 Figure 13: Prevalence of Centrotemporal Waves in Asymptomatic Siblings ...... 95 Figure 14: Prevalence of Abnormal Waves in Relatives (Studies n=13) ...... 97 Figure 15: Prevalence of Abnormal Waves in Relatives by Epilepsy Type (Studies n=13) ...... 99 Figure 16: Prevalence of Abnormal Waves in Siblings (With Metrakos and Tsuboi) ...... 100 Figure 17: Prevalence of Abnormal Waves in Siblings by Epilepsy Type (With Metrakos and Tsuboi) ...... 102 Figure 18: Prevalcence of Abnormal EEG in Parents (With Metrakos and Tsuboi) 103 Figure 19: Funnel Plot ...... 109
xi List of Appendices
Appendix 1: MEDLINE search ...... 124 Appendix 2: Data abstraction form ...... 126 Appendix 3: Newcastle Ottawa Scale (Cross sectional studies) ...... 130 Appendix 4: Newcastle-Ottawa Scale (Cohort studies)……………………………………….131
xii The Frequency of Electroencephalographic Abnormalities in Asymptomatic Relatives of Patients with Epilepsy: A Systematic Review and Meta-analysis
Chapter 1: Introduction
1.1 Background and Rationale
The advancement in genetics research has led to the identification of genes and their relation to disease causation. There is an important association between genes and the causation of epilepsy; this association could not be more clearly stated than in the most recent International League Against Epilepsy (ILAE) revision of the nomenclature for seizure types and epilepsy syndromes {Berg et al 2010}. Idiopathic epilepsy is defined as a syndrome of epilepsy with no underlying structural brain lesion or other neurological signs or symptoms. This definition is substantially unchanged from that of the 1989 classification. They are believed to have a strong genetic component {Beck- Mannagetta 1991}, the term idiopathic broadly means ‘something that occurs spontaneously’ which could lead us to think of it as a synonym for a genetic type of epilepsy {Thomas et al 2012}.
The idiopathic epilepsies constitute a group of syndromes characterized by generalized or focal epilepsy. There is an overlap in age of onset, type and frequency of seizures, in addition to prognosis and response to treatment {Thomas et al 2012}. There
1 have been conflicting opinions on the importance of genetic factors in epilepsy. A report by Lennox (1951) in which 20,000 relatives of 4,231 epileptic patients were studied, reported an increased familial predisposition, where the prevalence of epilepsy in the near relatives of both groups of patients was significantly increased as compared with the general population {Lennox 1951}.
Patients with idiopathic epilepsy are treated with antiepileptic drugs (AEDs), however AEDs do not “cure” epilepsy and they do not change the brain’s underlying susceptibility to produce seizures. In addition, they do not change the electroencephalogram (EEG); they only treat the symptoms by reducing the frequency of seizures. Although there is a good chance of success, AEDs do not always work {Rogawski and Loscher 2004}.
The idiopathic epilepsies are genetically complex since it is unknown if they are caused by one or multiple combinations of genetic changes; therefore the number of genes involved are unknown, which makes resolving the genetic basis of these epilepsies difficult. On the other hand, these epilepsies are prototypical of all other epilepsies, because they are ‘pure’ epilepsies, where the patient’s brain is completely normal except for causing seizures. In other epilepsies associated with brain damage, such as due to stroke, developmental disorders, infection, and tumors, it is difficult to know which neuronal and neural network abnormalities are related to the epilepsy, whereas in ‘pure’ epilepsies, where the brain is otherwise normal, all abnormalities identified will be part of the epileptogenesis process.
Idiopathic epilepsies are diagnosed clinically and through the electroencephalogram (EEG), which shows an abnormal wave recording for each type of idiopathic epilepsy. The EEG trait is the earliest detectable manifestation of epilepsy. It is hypothesized that genetic mutations cause the EEG disturbance. These EEG hallmarks help in the identification of the type of epilepsy. For example; JME has a classical EEG signature of polyspike-wave (PSW) discharges with 3.5-6 Hz frequencies. This endophenotype PSW is the primary epileptic abnormality. An endophenotype is a trait of
2 any hereditary characteristic that is normally associated with a condition related to a genetic disorder {John and Kenneth 1966, Gottesman and Gould 2003}. This method of employing EEG traits could be used as a marker of genetic susceptibility {Gottesman and Gould 2003}.
Interestingly, previous EEG studies performed on normal asymptomatic adults have shown these abnormal waves in a small proportion of individuals. Jabbari et al. have carefully screened a population of young and middle age adults and found that the incidence of epileptiform activity, photoparoxysmal response or excessive slowing to be less than 1% {Jabbari et al 2000}.
Other studies had shown these abnormal EEG waves amongst asymptomatic (normal) relatives of epileptic patients with a variation ranging from 7% up to 65% {Baier and Doose 1987, Doose et al 1968, Matthes and Weber 1968, Degen and Degen 1990(a), Jayalakshmi et al 2006, Tsuboi and Christian 1973, Metrakos and Metrakos 1961}. Whereas the reported incidence of EEG abnormality in asymptomatic subjects varied greatly in the literature from <0.1 to 10% {Cavazzuti et al 1980, LeTourneau and Merren 1973, O’Connor 1964, Gibbs et al 1943}. Therefore, a systematic review and meta-analysis would help us understand the true frequency of these traits, these endophenotypes, in families, thus clarifying the heritability.
1.2 Description of The Condition
The Idiopathic Generalized Epilepsies (IGE) comprise nearly a third of all cases of epilepsy and are genetically determined; they affect otherwise healthy people of both genders and all ethnicities. IGE manifests through generalized tonic-clonic seizures (GTCSs) or typical absences and myoclonic jerks, alone or in varying combinations and severity. Seizure precipitating factors such as photosensitivity are common. Seizures commonly begin in childhood or adolescence, though some cases start during adulthood.
3 Genetic studies of epilepsy performed in the early 1960s were done on mixed groups of patients. This has changed after the great contribution made to field by Metrakos and Metrakos when they chose to study a very well defined clinical and electroencephalographic entity, known as “centrencephalic” epilepsy as defined by Penfield {Metrakos and Metrakos 1961, Penfield 1950} from the broad heterogeneous group of epilepsies. Their study population had absence attacks and/or grand mal seizures (with no cerebral lesions) and characteristic paroxysmal bilaterally synchronous 3/s spike-wave EEG abnormality. They used the EEG to study the relatives of these patients and concluded that the spike-wave EEG trait, but not the epilepsy, was inherited as an autosomal dominant trait with age-dependent penetrance {Metrakos and Metrakos 1961}.
Similar results were obtained from Doose et al (1973). They studied the parents and siblings of patients with spike-wave absences, although the frequency of spike-wave abnormalities in relatives was lower. In the epilepsy studies undertaken by Metrakos & Metrakos the relatives of probands who had focal EEG abnormalities with or without seizures were found to have a significantly higher prevalence of 3/s spike-wave EEG abnormalities than control relatives but lower than that found in relatives of probands with centrencephalic epilepsy. This method of employing EEG traits as markers of genetic susceptibility would now be termed endophenotyping {Doose et al 1968}.
From the Australian twin studies done by Lennox {Lennox 1951} both authors Berkovic et al and Valdlamudi et al. concluded that the complex or complexes of multiple genes probably underlies the idiopathic generalized epilepsies {Berkovic & Scheffer 1998, Valdamudi et al 2004}. Which suggests that modifying genes or environmental factors are required to determine the specific clinical feature in epilepsy.
In addition to the Metrakos studies, Eva Andermann studied the families of 60 probands who had been operated for focal epilepsy {Andermann & Metrakos 1969}. They obtained detailed family histories and EEG examinations were done on 315 relatives of these patients and the data showed no significant increase in prevalence of seizures in first, second and third degrees relatives, but the prevalence of EEG
4 abnormalities, which included focal and generalized epileptiform abnormalities was significantly increased as compared to control relatives. These findings led the authors to conclude that a complex model of inheritance probably underlines the idiopathic epilepsies.
Seizures vary among family members who carry the same mutations; but they do not represent the same phenotype. Phenotypes vary across families because of both different mutations and differences in modifying genes and environmental factors. Which suggests that modifying genes or environmental factors are required to determine the specific clinical features in epilepsy.
Molecular studies of idiopathic epilepsies suggests a multifactorial or complex inheritance. Many genes described to date for idiopathic epilepsies have been related to either voltage-gated channel genes, or mutations in ligand-gated GABA receptor genes {Cossette et al 2002, Delgado-Escueta 2007}. These intrinsic neuronal membrane defects arising from ion channelopathy leads to a ‘pure’ epilepsy phenotype, where seizures are the only salient medical condition.
In the benign rolandic epilepsy or benign childhood epilepsy with centrotemporal spikes, studies done by Heijbel {Heijbel et al 1975} suggested autosomal dominant inheritance for this disorder and Degen & Degen found increased frequency of EEG abnormalities in siblings {Degen & Degen 1992}. However, recent twin studies by Vadlamudi et al showed no significant concordance in monozygotic or dizygotic twins and suggested that the genetic predisposition was low and that the condition was most probably associated with complex inheritance {Valdamudi et al 2006}.
Therefore, studying these types of epilepsy at their molecular bases is of great importance to confirm the genetic basis of the epilepsy syndromes and to study the genotype-phenotype correlations (to correlate specific mutations with the clinical expression of the gene) as well as to study the mutant protein to better understand the
5 pathophysiology and mechanism(s) of the epilepsies and eventually to develop specific treatments.
Nowadays one can make lists of epilepsy syndromes in which a locus or loci have been mapped and those in which one or more gene mutations or polymorphisms have been identified. These lists are constantly changing as new loci and genes are identified. The aim is to identify these gene mutations and polymorphism and their clinical correlates, to determine the genotype-phenotype correlations {Strachan and Read 2011}.
EEG studies done on asymptomatic relatives of epilepsy patients found that even though those relatives (siblings, parents or offsprings), who do not have seizures and are not epileptic, would still show an abnormal EEG recording {Baier and Doose 1987, Doose et al 1968, Matthes and Weber 1968, Degen and Degen 1990(a), Jayalakshmi et al 2006, Tsuboi and Christian 1973, Metrakos and Metrakos 1961}. Therefore, identifying those relatives and knowing the frequency of the abnormal EEG trait amongst them, would aid in the methods used for studying and identifying genes related to idiopathic epilepsies.
In our review, we focused on the EEG abnormalities found in asymptomatic relatives of three types of idiopathic epilepsies; the Juvenile Myoclonic Epilepsy (JME); the Childhood Absence Epilepsy (CAE) and the Rolandic Epilepsy (RE).
1.2.1 Juvenile Myoclonic Epilepsy (JME)
Juvenile Myoclonic Epilepsy (JME) is characterized by myoclonic jerks on awakening. GTCSs are seen in nearly all patients and typical absences are seen in more than a third of patients. Seizure-precipitating factors include sleep deprivation and fatigue, particularly after excessive alcohol intake. Photosensitivity is confirmed with EEG in more than 30% of patients. This condition begins in childhood or adolescence usually between ages 12 and 18 and lasts into adulthood. Typically, individuals with JME
6 develop the characteristic myoclonic seizures in adolescence, and then develop generalized tonic-clonic seizure few years later. Although seizures can occur anytime, they tend to commonly occur in the morning, shortly after awakening. These seizures can be triggered by a lack of sleep, extreme tiredness, and stress or alcohol consumption. JME affects 1 in 1,000 people and 5 percent of people with epilepsy have juvenile myoclonic epilepsy {Avanzini 2009}.
Genetics: The genetics of JME are complex and not completely understood; the most studied genes are the GABRA1 gene and the EFHC1 gene {Delgado-Escueta 2007}. Mutations in one of several genes can cause or increase susceptibility to this condition. Not all JME individuals have mutations in these genes therefore it is suggested that other unidentified genes are likely involved in this condition {Cossette et al 2002}.
Etiology: The exact cause of JME remains unknown, however it is a genetically determined syndrome. Specific mutations in various genes have been identified suggesting a complex mode of inheritance {Delgado-Escueta 2007}. Although JME can run in families, many cases occur in people with no family history of the disorder.
EEG: It is characterized by 3-6Hz generalized polyspike-and-wave discharges. One third of patients show photoparoxysmal response and a third may also have focal EEG abnormalities of single spikes, spike-wave complexes or slow waves.
Prognosis: JME is a lifelong disease, although JME may vary in severity from mild myoclonic jerks to frequent and severe falls and GTCSs if not diagnosed and treated properly. Seizures are usually well-controlled in more than 90% of patients {Smith 2005}.
Management: Valproic acid has been the first line AED for the last 30 years. All formal current recommendations discourage the use of valproate in women of childbearing age. Both levetiracetam and lamotrigine are presently widely used {Rogawski and Loscher 2004, Panayiotopoulos 2010}.
7
1.2.2 Childhood Absence Epilepsy (CAE)
The hallmark of the absences is abrupt, brief and severe impairment of consciousness with unresponsiveness and interruption of ongoing voluntary activity. Although absence seizures are brief (4-20 seconds) they tend to occur frequently up to one hundred times per day. In older age of onset, the seizures can last several seconds to minutes and may happen a few times a day. Myoclonic and tonic-clonic seizures could also be present especially in older age patients {Panayiotopoulos 2010}.
CAE accounts for 10-15% of childhood epilepsy cases, the absence seizures usually occurs between the ages 4-10 years. During the seizure the child stares and sometimes blinks, the eyes may begin to roll back, usually it interrupts activities such as drinking for a cup or playing, the child loses awareness of surroundings for example when called by name. There are no warning signs for the seizures, they tend to begin and end suddenly. Hyperventilation triggers absence seizures and hence is a good provocative test in the clinic or EEG lab {Berg 2013}.
Genetics: The most studied gene is the mutations in CACNA1H or GABRG2. Mutations in one of several genes can cause or increase susceptibility to this condition {Panayiotopoulos 2010, Avanzini 2009}.
Etiology: The etiology of CAE is genetic with complex multifactorial inheritance. Although CAE is genetically determined, the precise mode of inheritance and the genes involved remain largely unidentified {Rogawski and Loscher 2004, Panayiotopoulos 2010}.
EEG: The EEG is characterized by 3Hz generalized spike and wave discharges {Panayiotopoulos 2010}.
8 Prognosis: The prognosis of CAE is excellent. Remission occurs before the age of 12 years. Less than 10% of the patients may develop infrequent or solitary GTCSs in adolescence or adult life. It is exceptional for patients to continue having absence seizures in their adult life {Smith 2005}.
Management: Monotherapy with either valproate or ethosuximide controls absences in 80% of patients. Another option is lamotrigine monotherapy, although this is less effective with around half of patients becoming seizure free. In case of monotherapy failure, a combination of lamotrigine and valproic acid can be the best choice {Panayiotopoulos 2010, Berg 2010}.
1.2.3 Rolandic Epilepsy (RE)
This syndrome is known by two names; rolandic epilepsy (RE) or benign childhood epilepsy with centro-temporal spikes (BECTS). The cardinal characteristics of rolandic seizures are infrequent, often single, focal seizures consisting of unilateral facial sensorimotor symptoms (30% of patients), speech arrest (40% of patients) and hypersalivation (30% of patients).
Tonic-clonic seizures could also occur typically during sleep. It accounts for 15% of all epilepsies in children. The term “benign” refers to the fact that most children outgrow these seizures during adolescence. The average age when these seizure begin is about 6-8 years old but they maybe seen in children from ages 3-13. its incidence is 10- 20/100,000 of children aged 0-15 years and the peak frequency of onset is 7-10 years {Panayiotopoulos 2010}.
Genetics: Doose in 1970 suggested autosomal dominant inheritance of RE, while Degen & Degen found an increased frequency of EEG abnormalities in siblings {Degen & Degen 1992}. However, recent twin studies by Vadlamudi et al (2006) showed no significant concordance in monozygotic or dizygotic twins and suggested that genetic
9 predisposition was low and the condition was most probably associated with complex inheritance {Vadlamudi et al 2006, Neubauer et al 2000}.
Researchers have not discovered exactly how the gene produces RE. Multiple genes have been implicated in particular families including BDNF, ELP4 genes, GRIN2A. However, most children with RE do not show a link to an identified gene. In some linkage studies done in families with RE probands suggest that band 14 of the long arm chromosome 15 (15q14) is the most likely location for the gene responsible for some, but not all, cases of this syndrome. Neubauer et al, found suggestive linkage to chr15q14 for the EEG abnormalities, but not for the epilepsy {Neubauer et al 2000}. Researchers found that the band 15q14 appears to be involved in regulating the excitability of neurons in the brain that could contribute to seizure susceptibility {Avanzini 2009}.
EEG: The hallmarks of RE, or benign epilepsy with CTS (BECTS), are centro- temporal spikes (CTSs), which are age dependent, appearing at the age of 6-10 years, often continuing despite clinical reduction and usually disappearing by the age of 16 years at the latest. Although called CTSs, these are mainly high-amplitude, sharp and slow-wave complexes localized in the C3-C4 or C5-C6 (midway between central and temporal) electrodes. CTSs may be unilateral, but are more often bilateral independently right or left. They are abundant (4-20/min) and usually occur in clusters and are enhanced by sleep {Berg 2013}.
Prognosis: The prognosis of rolandic seizures is excellent, with a risk of developing infrequent convulsive seizures in adult life of less than 2%{Smith 2005}.
Management: Children with rolandic seizures may not require AEDs, but if the patient had frequent seizures or secondarily GTCS or comorbid conditions, AED may be required. Recent research found levetiractam to be highly effective {Rogawski and Loscher 2004, Panayiotopoulos 2010, Berg 2010}.
10 1.3 Modes of Inheritance
The chromosomes in the cells of a human being have a remarkable ability to pass on genetic material to their daughter cells in pairs of chromosomes. This ability can be realized if the characteristics of individuals and that of their offspring are observed. The visible presentation, phenotype, is controlled during growth and development that occur in different cells and tissues in the expression of alleles. Any difference observed is due to the variation in the expression of the alleles. Modes of genetic inheritance refer to the transfer of traits from parent to offspring resulting from factors or genes. Unifactorial inheritance, also known as Mendelian, refers to transfer of traits from a single gene. It is a simple inheritance pattern that was first investigated by Gregor Mendel in 1865 in his study of peas {Elsevier Health, 2013}. Mendel’s work has been used to understand inheritance as it set the mechanisms and principles for the same. The other modes of genetic inheritance are all referred to Non-mendelian. Multifactorial inheritance, also known as Complex, refers to the transfer of traits made possible by the interaction of multiple genes. As its name suggests, its complexity arises from the great variety of gene material from an individual extended family and other populations.
1.3.1 Mendelian Inheritance
Parents pass on genetic information on to their offspring through genes that are found in chromosomes. This is evidence of the existence of genes based on changes in phenotype that come about from the variation of alleles. As mentioned above, the variation of alleles can be observed depending on the relationship between alleles. The relationship can be either dominant or recessive. A dominant relationship requires only one allele, the dominant of the pair, to reveal a phenotype. In a recessive relationship, the alleles should be similar to manifest a phenotype. Taking “A” as the dominant and “a” as the recessive, AA results to a dominant, aa results to recessive, and Aa heterozygous phenotypes {Elsevier Health 2013}.
11 Sex chromosomes carry the genes that are passed on from parent to offspring. It goes without saying that that the alleles in the chromosomes express either dominant or recessive qualities. The male and female chromosomes are different in term of genes, with male represented as XY and female as XX. This presents an unlikely scenario from that of autosomes.
Mendelian inheritance can be further classified as autosomal dominant, autosomal recessive, X-linked dominant, and X-linked recessive. In autosomal dominant inheritance, an offspring with such a trait should have at least one parent with it. As demonstrated by pedigree, a diagram representing family relationships and information on inherited traits, one parent can have the dominant allele while the other does not {Strachan and Read 2011}. The parent with the dominant allele passes it on to the offspring with a 50% chance of it occurring to any of the offsprings.
The pattern of autosomal dominant inheritance could be summarized as follow: an affected person usually has at least one affected parent; it affects either sex; it is transmitted by either sex; a child with one affected and one unaffected parent has a 50% chance of being affected (this assumes that the affected person is heterozygous which is usually true for rare conditions) {Strachan and Read 2011}.
In autosomal recessive inheritance, an offspring with the trait must have derived it from either heterozygous parents or a recessive phenotype. This can be demonstrated by parents who are heterozygous carriers whose offspring exhibits a recessive trait. It is difficult to predict whether someone is a heterozygous “Aa” carrier of a recessive allele since it does not show negative signs, unlike a dominant recessive. The negative signs of the allele are only exposed if two heterozygous carriers form an offspring. This puts to rest the question of traits that have been absent in a generation suddenly showing in certain offspring. In such cases, only one offspring is affected because there is only 25% chance of them getting both dominant alleles. {Elsevier Health 2013}.
12 The pattern of an autosomal recessive inheritance could be summarized as follow: affected people are usually born to unaffected parents; parents of affected people are usually asymptomatic carriers; there is an increased incidence of parental consanguinity. It affects either sex and after birth of an affected child, each subsequent child has a 25% chance of being affected (assuming that both parents are phenotypically normal carriers) {Strachan and Read 2011}.
X-linked inheritance, also known as sex-linked or X chromosome inheritance does not have any great variations from autosomal inheritance apart from the genes found on the chromosome. It is also remarkable given that males only have one X chromosome while females have XX chromosomes. Therefore, in males the alleles are hemizygous since they do not have another corresponding X chromosome, but a Y chromosome {Strachan and Read 2011, Elsevier Health 2013}. This means an allele in the X chromosome of a male is expressed, whereas an allele in only one X chromosome of a female can be masked.
The pattern of X-linked recessive inheritance, is summarized into the following: it affects mainly males; affected males are usually born to unaffected parents; the mother is normally an asymptomatic carrier and may have affected male relative; females, may be affected if the father is affected and the mother is a carrier, or occasionally as a result of non-random x-inactivation; in addition, there is no male-to-male transmission in the pedigree (but mating of an affected male and carrier female can give the appearance of male-to-male transmission).
On the other hand, X-linked dominant inheritance pattern could be summarized into the following: it affects either sex but more females than males; usually at least one parent is affected, families are often more mildly and more variably affected than males; the child of an affected female, regardless of its sex, has a 50% chance of being affected; for an affected male, all his daughters but none of his sons are affected.
13 In Y-link inheritance, only males are affected. They always have an affected father (unless there is a new mutation) all sons of an affected man are affected.
Mitochondrial inheritance; could affect both sexes; and is usually inherited from an affected mother (but is often caused by de novo mutations with the mother unaffected); a father does not transmit it to his children; and there are highly variable clinical manifestations {Strachan and Read 2011}.
1.3.2 Multifactorial “Complex” Inheritance
A complex interaction of many genes and environment factors can influence their expression to and give rise to certain conditions. Alleles involved in this interaction have their individual patterns that may come from either Mendelian or non-Mendelian inheritance. It is critical to point out that although the alleles have individual patterns; their expression is also dependent on alleles and environmental factors {Elsevier Health 2013}. Such a complexity, therefore, makes it difficult to understand multi-factorial inheritance due to its type of interaction and the disorders that originate from it.
Genes passed on from parent to child influence phenotypes or traits of the offspring such as height and weight. In multi-factorial inheritance, there are a large number of phenotypes whose distribution is known to make a bell-shaped curve in a population. This distribution differentiates the phenotypes that have a continuous variation between their extreme ends. In a phenotype such as height, for instance, extremely tall and short people are not considered to have a clinical condition or disorder {Strachan and Read 2011, Elsevier Health 2013}. However, being in one of the extremes presents a risk that the individuals might suffer from a congenital disorder. This is the threshold level of the distribution, whereby if people on one end of a distribution have a disorder, the people on the extreme opposite end are less likely to have it. An example of such a disorder that affects people on only one end of the distribution is spina bifida.
14 The main features of multifactorial or complex inheritance are known to be as follow: high population frequency where the prevalence is >1/1000; familial prevalence is higher than that in the general population; does not fit classical Mendelian ratios; and environmental factors are important. The risk to relatives depends on the degree of relationship, and drops rapidly from first to third degree relatives unlike autosomal dominant inheritance where the drop is only by a factor of two for each degree of relationship {Avanzini 2009}.
In this type of inheritance, parents, siblings and children may be lumped with respect to risks, similar to autosomal dominant inheritance, but differing from autosomal recessive inheritance. The risk to relatives increases according to the number of affected individuals in the family, and this is unlike Mendelian inheritance, where the risk remains constant {Strachan and Read 2011}.
1.3.3 Genetic Variations
In common diseases, susceptibility genes may represent common gene polymorphisms, each with small phenotypic effects, these are seen in more than one per cent of the general population, for example the single nucleotide polymorphisms or SNPs. As indicated by the name, SNPs are single base changes in the DNA. SNPs variants tend to be common in different human populations, they are used as “markers” in the search for common variants which influence susceptibility to common diseases; a hypothesis known as the common disease-common variant hypothesis or model. This hypothesis predicts that common disease-causing alleles or variants will be found in all human populations, which manifest a given disease {Strachan and Read 2011}.
There is also a possibility of multiple rare polymorphisms, with relatively greater phenotypic effects, each occurring in less than one per cent of the general population, as well as a combination of both. Common gene variants contributing to diseases with complex inheritance can be detected by means of genome-wide association studies, unlike the rare variants {Strachan and Read 2011}.
15
The penetrance of a characteristic, for a given genotype, is the probability that a person who has the genotype will manifest the character. For example, a dominant characteristic is manifested if a person shows 100% penetrance, however, in many human characteristics, even though dominant inheritance is observed overall, they occasionally skip a generation. One example of non-penetrance would be where a parent is affected but his children are carriers of the mutant genes without showing the disease (i.e., phenotypically normal) {Strachan and Read 2011}.
Genetic counselors are able to identify the usual degree of penetrance of each dominant condition from pedigree patterns. These tools are important because they enable the geneticist to estimate the chance that an at-risk but asymptomatic person will subsequently develop the disease. In non-penetrance and in variable expression conditions (where different family members show different features of the syndrome) the causes are either from gene variability, environmental factors or pure chance, all of which influence the development of the symptoms. Therefore, it is important to study the asymptomatic relatives of diseased patients in order to identify inheritance patterns and subsequent abnormal genes {Strachan and Read 2011}.
Endophenotypes are measures of endogenous characteristics of an individual that reflect genetic risk for a specific disorder, or spectrum of disorders, these characters are correlated with the clinical diagnosis but lie closer to biology. One of the criteria of an endophenotype is that it should be present in individuals whose genetic makeup is similar to those with the manifest disorder even if the disorder is absent, such as reaction times or eye movements. The problem here is to know whether the chosen character has any causal relevance or is just a downstream consequence of the clinical problem. Another way is to look for common variants that, in different combinations, predispose to a variety of psychiatric conditions. For example copy-number variants at 1q21 and 15q13 have each been associated with a variety of conditions, including schizophrenia, autism, seizures, and mental retardation. It is noticed that the same variants are also seen in normal individuals (mostly in the parent of an affected child). Making them neither
16 necessary nor sufficient to cause disease but evidently confer significant susceptibility to a range of conditions. Understanding these effects may help understand the biology {Strachan and Read 2011}.
Therefore we are able to study the asymptomatic relatives of epilepsy patients who have the EEG abnormality but are not epileptic individuals and use the EEG as an endophenotype. A potentially important benefit of endophenotypes is that they can convey information about specific neurobiological and pathophysiological processes involved in the particular disorder with which they are associated {Iacono & Malone 2011}.
1.4 Description of The Electroencephalogram As a Diagnostic Test
The electroencephalogram (EEG) is an essential diagnostic tool in epilepsies; it identifies specific pathological findings and characteristics of many idiopathic syndromes. Given the potential relevance of the EEG findings, it is not surprising that it has been used for the look of pathological traits in the relatives of affected individuals, perhaps serving as a neurophysiological genetic marker.
The paroxysmal EEG traits that have been studied most often are generalized bilateral and synchronous spike and wave patterns. Which are divided into the typical trait of 3Hz spike and wave irregular spikes and polyspike and wave patterns, photoparoxysmal responses, and centrotemporal or rolandic spikes. There are others non- specifically abnormal EEG patterns, such as rhythmic parietal theta or posterior delta rhythms that have been less useful.
Hans Berger {Berger 1929, Gloor 1969} has used the EEG since early observations. Many investigators have been impressed by the special characteristics of bilateral synchronous 3 Hz spike-wave discharges associated with absence epilepsy {Gloor 1969}. It was then considered by Penfield & Jasper to be the hallmark of centrencephalic epilepsies {Penfield & Jasper 1954}. These investigations provided a
17 window on the pathophysiology of absence and are now considered one of the main criteria for the definition of childhood absence epilepsy (CAE).
In addition, comparable considerations are applied to related conditions including the benign childhood epilepsy with centrotemporal spikes (BECTS) EEG pattern of ‘Rolandic’ or ‘Centro-temporal spikes’. These characteristics were independently described by Bancaud as well as Nayar in 1958 which were further analyzed by Faure & Loiseau in 1960 {Bancaud et al 1958, Nayer & Beausaurd 1958, Faure & Loiseau 1960}. The identification of these characteristic EEG waves led to the identification of these epileptic changes amongst the population, regardless of whether they were symptomatic or not.
The recognized EEG waves for idiopathic epilepsies are: 1) Generalized 4-6 Hz Spike and Polyspike waves for Juvenile Myoclonic Epilepsy (JME) 2) Generalized 3 Hz spike and slow wave discharges for Childhood Absence Epilepsy (CAE) 3) Centrotemporal spikes for Rolandic Epilepsy {Avanzini 2009, Panayiotopoulos 2010}.
1.5 How The Electroencephalogram Might Work
The electroencephalogram detects the brain electrical field wave abnormality in an individual with epilepsy and hence helps in the diagnosis and identification of their epilepsy type. The EEG’s specificity and sensitivity varies on a routine EEG. It has relatively low sensitivity in epilepsy with a range of 25-56%; however, it has a specificity of 78-98% {Smith 2005}.
A number of large families with idiopathic epilepsy have been identified and described over the years. Although most of these familial traits show an autosomal dominant mode of inheritance with a high (although incomplete) level of penetrance,
18 some autosomal recessive idiopathic generalized epilepsy pedigrees have been reported {Jayalakshmi et al 2006, Tsuboi & Christian 1973, Metrakos & Metrakos 1961}. It is important to note that phenotypes segregating in a family do not differ substantially from the classical phenotypes found in the general population. It has been demonstrated by genetic analyses that mutation segregation in these families are not involved in the more common sporadic forms, which leads to the recognition of the complex and heterogeneous nature of idiopathic epilepsies {Bertram et al 2007}.
The use of EEG in the identification of the traits, and confirming the percentage of these abnormal waves among the asymptomatic relatives of idiopathic epileptic patients would bring insight to the mode of inheritance of these epilepsies and therefore contribute to future studies on whole genome sequencing.
1.6 History of Systematic Reviews and Meta-analyses
According to the Cochrane Handbook of Systematic Reviews of Interventions, “A systematic review attempts to collate all empirical evidence that fits pre-specified eligibility criteria in order to answer a specific research question” {Higgins & Green 2008}. The use of statistical methods to summarize the results of all studies included in the systematic review for the purpose of integrating the findings is called meta-analysis, a term coined by Gene Glass in 1976 {Glass 1976}.
Though systematic review was used as early as 1930s in social sciences, its use in biomedical research became evident only during the 1970s and 1980s {Chalmers et al 2002}. The main objective of systematic review and meta-analysis in health care research arise from a need for evidence-based medicine for the treatment and care of patients. Typically a meta-analysis consists of four components: 1) review of literature identifying studies on subject of interest; 2) specific criteria for selection of studies; 3) abstraction of data from selected studies; 4) meta-analysis and summarization {Glass 1976, Schell and Rathe 1992, Cochrane 2011}.
19
Later, Cochrane pointed at the lack of periodical critical summary, by specialty or subspecialty, of all relevant randomized controlled trials (RCT). Though there were a few critical summaries of RCTs during 1970s, the following decade saw an accelerated momentum in research syntheses {Higgins & Green 2008, Cochrane 2011}.
A 1988 search found more than 110 published meta-analyses in medicine, and in 1990, a MEDLINE search resulted in 203 postings for the term “Meta-Analysis” in medical subject heading. Moreover, researches addressed the difference between traditional literature review and meta-analysis in their publication. These writings played a significant role in securing recognition of the practice of quantitative research synthesis among statisticians {Schell and Rathe 1992, Cochrane 2011}.
With an increasing frequency of RCTs and meta-analyses in the following years, the U.K. Cochrane Center was established in 1992 to maintain systematic reviews of the interventions in health care followed by the Cochrane Collaboration in 1993 consisting of an international network of individuals with a mission to promote evidence-informed health decision-making by producing high-quality, relevant, accessible systematic reviews and other synthesized research evidence {Chalmers et al 2002}.
In 1995, The Cochrane Database of Systematic Reviews came into effect and Cochrane reviews are internationally recognized as the highest standard in evidence- based health care and play an important role in health care policy making.
Quality of systematic reviews was a major concern mainly due to poor study design and reporting of individual research. For example, in a review of study methods followed in 50 reviews published during 1985 and 1986, stated that none of the studies satisfied all of the eight explicit criteria adapted from published guidelines for
20 information syntheses and only one study specified methods of identifying, selecting and validating included information {Higgins & Green 2008}.
The quality of 86 meta-analyses of randomized controlled trials was evaluated and concluded poor reporting with respect to most of the characteristics of the six domains such as study design, combinability, control of bias, statistical analysis, sensitivity analysis and application of results. In this context, other suggestions were laid to encourage higher quality in individual research efforts and reporting literature {Schell and Rathe 1992, Higgins & Green 2008}.
In 1996, an international group consisting of clinical epidemiologists, clinicians, statisticians, editors, and researchers developed the QUOROM (Quality Of Reporting Of Meta-analyses) statement to address standards for improving the quality of reporting of meta-analyses of clinical RCTs and has been widely used as a tool to assess quality of meta-analyses of RCTs ever since {Higgins & Green 2008}.
Several meetings were held in Ottawa, Canada in 2005 to revise the QUOROM statement; Moher et al published the Preferred Reporting Items for Systematic Reviews and Meta-analysis statement (PRISMA) to help authors improve the reporting of systematic reviews and meta-analysis using a checklist {Moher et al 2009}.
In 2014 the PRISMA-P statement was developed to improve the quality of systematic reviews protocols, in addition to its potential to improve the conduct of systematic reviews. These protocols are now considered an imperative step to the development of a systematic review {Moher et al 2015}.
The Centre of Reviews and Dissemination, University of York, established an international register, PROSPERO (International Prospective Register of Ongoing
21 systematic Reviews), which was launched in 2011 {Moher et al 2015}. This improved accessibility of protocols and strengthened transparency, accuracy and completeness’s of the reports.
1.7 Promises and Pitfalls of Meta-analyses
Physicians are in need of evidence for both clinical practice and public health decision-making. Systematic reviews and clinical practice guidelines were developed to provide the best source of evidence to counter the vast medical literature. This method was developed to aid physicians who lack the time to review and critically appraise all the articles obtained to answer their specific question {Reade et al 2008}.
Systematic reviews (SR) are designed to provide a comprehensive summation of the available evidence for decision makers. It is seen as a way to encourage the use of research evidence in clinical decision-making. When conducting a systematic review it is important to use explicit methodology in order to find and synthesize all relevant evidence, these are generally considered higher caliber evidence than individual trials and would make a difference in decision making for clinical practice and health policy {McKenzie et al 2013}.
Meta-analysis is the quantitative analysis for a systematic review. It is the end result of combining the statistical results of multiple studies in order to get a weighted average of the intervention under consideration. The studies that provide more information will contribute more weight i.e. the studies with larger sample size compared to smaller sample size will be weighted more. Usually, the average effect across trials is reported as an overall summary point estimate and an estimate of its precision as reflected in the width of the confidence interval {Moher et al 1998}.
A well-conducted systematic review and meta-analyses can help us keep up-to- date. High-quality systematic review can define the boundaries of what is known and what is not known and helps us not to omit what has already been proven. Medical
22 practitioners are therefore aided in determining solutions for specific clinical hurdles through analysis of inconsistencies among diverse pieces of research evidence. This is done by summarizing existing data, refining hypotheses, estimating sample size and providing a definition for future research agendas. Without them, researchers risk missing promising leads in their search for problem solution or they may incur redundancy through embarking on studies of questions that have been already answered {Murlow & Cook 1998}.
When carefully implemented, the benefits of meta-analysis include increase in power and improvement in precision but it could also lead to serious misconceptions if some trivial aspects such as specific study designs, within-study biases, variation across studies, and reporting biases are not evaluated efficiently {Reade et al 2008, Cochrane 2011}.
The occurrence of bias can be attributed to the publication of studies that show a significant effect of a specific treatment, publication of studies in English and citation of a study by multiple authors. Which gives the studies an advantage over the non-published studies, because they will be identified and included in systematic reviews and therefore producing bias. {Dickersin 1997, Sterne et al 2001, Booth et al 2012}.
The impact of publication bias has been extensively evaluated for clinical trials to avoid exaggeration of the effectiveness of a treatment in the case of studies with statistically positive results and large effect sizes. This necessitates the inclusion of unpublished studies in systematic reviews, which often are difficult to find especially when conducted and funded by private industry {Strene et al 2001}.
Variation across studies (heterogeneity) must also be considered. This can occur if differences in included studies are substantial, which could be due to clinical or methodological heterogeneity, both are important threats to the validity of quantitative synthesis {Hatala et al 2005}.
23 Data combination may be inappropriate for a variety of reasons; this could be due to differences in patient eligibility criterion of the included studies, different interventions and outcomes, methodological differences or missing information {Moher et al 1998}. The various methods used for investigating heterogeneity are discussed later in this chapter.
1.8 Methods of Conducting Systematic Reviews
1.8.1 Narrative Synthesis
The process of gathering information to produce a summary analysis about general characteristics of studies included in a systematic review is known as qualitative synthesis. This information includes study characteristics such as date of publication and country of conduct, patients’ characteristics such as age range and sex of patients, characteristics of the interventions such as the dose range or the methodological quality.
Qualitative data synthesis provides physicians with sufficient information about the quality of the studies, which would aid in the appropriateness of conducting a statistical or quantitative synthesis afterward. It is important to note that Qualitative data identifies the differences between included trials i.e. heterogeneity which could threaten the validity {Hatala 2005, Cochrane 2011}.
1.8.2 Quantitative Data Synthesis
Also known as meta-analysis, it occurs when at least one outcome from two or more studies included in a systematic review is statistically combined to provide an overall summary result. A variety of approaches for harmonization of statistical data in systematic reviews exist. That includes techniques based on Bayesian theory, likelihood method and regression.
24 The results selected for combination and analysis in meta-analyses are determined by the data obtained from the included studies. Meta-analysis of binary data uses within- study variance estimates such as odds ratios, relative risk and the risk difference. Continuous data can be meta-analyzed using the mean differences and standardized mean difference {Kriston 2013, Cochrane 2011}.
There are two models for quantitative synthesis. The first one is called the fixed effect model and the second one is the random effects model. Each model reflects a different quantitative outcome. Fixed effects model assumes that trials included in the review estimate are predetermined and therefore fixed hence the treatment effect and the observed differences across studies are simply due to chance {Kriston 2013}.
In the random effects model, it is assumed that included trials are only a random sample of a theoretical universe of all possible trials and that their results are randomly placed around some central value therefore incorporating a between study variability. The fixed effect approach only includes a within-trial measure of variance, whereas a random effects approach includes a within and a between trials variance.
The statistical properties of both models therefore differ depending on whether the studies analyzed are homogenous or heterogeneous. Research indicates that in most cases however, both approaches provide similar results since the between-study variance which differentiates the two is small or zero {Moher et al 1998, Cochrane 2011}.
The inverse variance method is so named because the weight given to each study is inversely proportional to the variance of the effect estimate. Larger studies with smaller standard errors are therefore given more weight than smaller studies, which have larger standard errors minimizing the imprecision of the pooled effect estimate {Kriston 2013, Cochrane 2011}.
25 1.8.3 Subgroup Analysis
Subgroup analysis is the statistical analysis on a particular subgroup with an important variable of interest e.g. by gender, rates in females and males. It is done in areas in which the systematic reviewer, and reader, might be interested in the results on specific populations or subsets of participants or subsets of studies (such as geographical locations). It is also done as means of investigating heterogeneous results, or to answer specific questions about particular patient groups, types of interventions or types of study. {Moher 1998, Higgins et al 2003, Cochrane 2011}.
1.8.4 Sensitivity Analysis
The process of conducting a systematic review involves a number of decisions to be made. These decisions are mostly objective and non-contentious; some of them will be arbitrary or unclear. For example unclear decisions might be because a study report fails to include the required information: for example the outcomes of individuals who were lost to follow-up, other decisions are made because the included study never obtained the information required. Further decisions are unclear because there was no consensus on what best statistical methods should be used for a particular problem.
In a systematic review it is desirable to prove that the findings do not depend on such unclear decisions. Therefore, a sensitivity analysis is a repeat of the primary analysis or meta-analysis but substituting alternative decisions or ranges of values for the values that were unclear. For example when a meta-analysis is dubious because they did not contain full details, a sensitivity analysis is conducted. Undertaking the meta-analysis twice could perform this: first, by including all studies and second, only including those that are definitely known to be eligible. The study variables remain the same in most cases.
There are many decisions nodes within the systematic review process, which can generate a need for sensitivity analysis, for example, in the area of searching for studies; eligibility criteria; data analysis; or the analysis methods used. These could be pre-
26 specified in the study protocol, but many issues suitable for sensitivity analysis are only identified during the review process where peculiarities of the studies under investigation are identified. However, results must be interpreted with appropriate degree of caution because findings from this analysis may generate proposals for further investigations and future research. {Moher et al 1998, Murlow & Cook 1998, Cochrane 2011}.
Sensitivity analysis differs from subgroup analysis in two ways. First, sensitivity analyses do not attempt to estimate the effect of the intervention in the group of studies removed from the analysis, whereas in subgroup analyses estimates are produced for each subgroup. Second, in sensitivity analyses, informal comparisons are made between different ways of estimating the same thing while in subgroup analyses, formal statistical comparisons are made across the subgroups {Cochrane 2011}.
27 1.9 Graphic Display of the Results of Systematic Quantitative Reviews
1.9.1 Forest Plots
Forest plots are invaluable for displaying the meta-analysis results. An important variation to this graphic method is the graphic representation of cumulative meta-analysis where individual trials are included consecutively, according to some pre-specified order, such as year of publication or quality. Each horizontal line represents the confidence interval from each study, the box in the line for each study represents the point effect estimate, and the area of the box represents the weight given to the study. The diamond below the studies represents the overall effect, and the width of the diamond shows the confidence interval for the overall effect estimate {Cochrane 2011}. The variability between estimates on the plot highlights the heterogeneity of trials {Cochrane 2011, Reade et al 2008, Xu et al 2008}.
1.9.2 Funnel Plot
A funnel plot is a graph designed to check for the presence of publication bias. It is a simple scatter plot of the intervention effect estimates from individual studies against some measures of each study size or precision {Strene et al 2001}. The horizontal scale is for the effect estimate and on the vertical axis is the measure of study size {Cochrane 2011, Reade et al 2008, Xu et al 2008}.
Effect estimates from small studies will scatter more widely at the bottom of the graph and the speared narrows among larger studies. In the absence of bias, the plot should resemble an inverted symmetrical funnel {Cochrane 2011}.
1.10 Heterogeneity
It is inevitable to combine studies in a systematic review that are different. Differences in studies causing variability in a meta-analysis can be broadly categorized
28 into three types of heterogeneity: clinical, methodological and statistical {Thompson 1994, Higgins & Thompson 2003, Xu et al 2008, Cochrane 2011}.
Clinical heterogeneity occurs when variability is present in the participants, interventions and outcomes studied. Methodological heterogeneity is due to variability in study design or conduct. Statistical heterogeneity relates to variation in the intervention effects being evaluated in different studies and reflects the probability that differences observed between studies are consistent with chance variation. Statistical heterogeneity can be a consequence of clinical or methodological heterogeneity or can be due to chance alone {Thompson 1994, Higgins & Thompson 2003, Xu et al 2008, Cochrane 2011}.
1.10.1 Identifying and Measuring Heterogeneity
A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect.
There are several ways to statistically quantify elements of heterogeneity, including using the Q-statistics or Cochran Chi-square; which measures total within- study variance and provides a test of significance for heterogeneity rather than quantifying it. However, it can be quantified by using the index of heterogeneity-I2 statistics (ratio of variability of results among studies to total observed ratio), which quantifies the percentage of total variation between studies that is due to heterogeneity rather than chance. It is important to note that, although heterogeneity can be statistically tested and sometimes managed, it will not be eliminated as an issue {Hatala et al 2005, Reade et al 2008, Cochrane 2011}.
The I2-statistic used to quantify inconsistency in meta-analyses is given by the formula:
I2 = (Q-df/Q) x 100%
29 Where Q is the Chi-squared statistics and df is the degrees of freedom {Higgins and Thompson 2002}.
A rough guide to interpretation of I2 is as follows: • 0% to 40%: might not be important • 30% to 60%: may represent moderate heterogeneity • 50% to 90%: may represents substantial heterogeneity • 75% to 100%: considerable heterogeneity {Higgins and Thompson 2002}.
We did not use the Q-statistic because it is known to be poor at detecting true heterogeneity when a small number of studies are available, therefore yielding a test with low power. The principal advantage of the I2 statistic is that it can be calculated and compared across meta-analyses of different sizes, of different types of studies, and using different types of outcome data. In addition, the I2 can also be used to quantify heterogeneity among subgroups analyses {Higgins and Thompson 2002, Higgins et al 2003}.
Some argue that, since clinical and methodological diversity always occur in a meta- analysis, statistical heterogeneity is inevitable {Higgins et al 2003}. Thus, the test for heterogeneity is irrelevant to the choice of analysis; heterogeneity will always exist whether or not we happen to be able to detect it using a statistical test. About a quarter of meta-analyses have I2 values over 50% {Higgins et al 2003, Cochrane 2011}.
1.10.2 Calculating Statistical Models of Heterogenity
In calculating summary effect estimates, the simplest way of dealing with statistical heterogeneity is to use a random effects model instead of a fixed effect model. It is important to note that quantification of heterogeneity is only one component of a wider investigation of variability across studies, the most important being diversity in clinical and methodological aspects {Xu et al 2008, Cochrane 2011}.
30 1.10.3 Investigating Heterogeneity
There are several ways to investigate heterogeneity, including subgroup analyses, which is done as a means of investigating heterogeneous results, or answer specific questions about particular patient groups, types of intervention or types of study {Higgins et al 2003}.
Another way is by conducting meta-regression, which is an extension to subgroup analyses that allows the effect of continuous as well as categorical characteristics to be investigated across important variables simultaneously {Thompson 1994, Thompson et al 1999, Higgins et al 2003}. However, meta-regression was not done in our investigation of heterogeneity due to the few numbers of studies included.
1.12 Risk of Bias and Quality Assessment
Empirical evidence has shown that validity of studies outcome could be affected and attributed to problems with the design and/or execution of studies. There are numerous tools available to evaluate the validity of studies emphasizing the risk of bias in their results and assessing their methodological quality {Cochrane 2011, Wells et al 2014}.
The Newcastle-Ottawa Scale (NOS) is used for assessing the quality of nonrandomized studies in systematic reviews. In addition some modifications were done on the NOS to use it on cross-sectional studies {Fnais etal 2014}. The NOS consists of eight items pertaining to: selection (representativeness of the exposed cohort, selection of the non-exposed cohort, ascertainment of exposure, demonstration that outcome of interest was not present at start of study), comparability (comparability of cohorts on the basis of the design or analysis) and outcome (assessment of outcome, sufficient duration of follow-up, adequacy of follow up) more details are shown in both Appendix 3 for the modified version of NOS for cross sectional studies, and Appendix 4 for NOS for cohort studies.
31
1.13 The Importance of this Review
The EEG trait is the earliest detectable manifestation of epilepsy. We hypothesize that genetic mutations produce EEG disturbances, which leads to a proportion of affected people becoming patients having clinical seizures; therefore if the EEG abnormality is genetically simple, it will be easy to detect this gene compared to the whole syndrome. Moreover, because the EEG abnormality is primary, resolving its genetics would resolve the earliest phases of seizures.
Genetic conditions that are due to a single gene mutation follow a predictable pattern that can be passed on to subsequent generations in several ways. In dominant conditions (autosomal dominant) each offspring has a 50% chance of inheriting the mutant allele, where half of the children of affected parents will inherit the condition, whereas the other half will not; this is because dominant conditions are expressed in individuals who have just one copy of the mutant allele {Elsevier Health 2013}.
In recessive conditions (Autosomal Recessive), two copies of disease allele are required for an individual to be susceptible to expressing the phenotype, usually the parents of an affected individual are not affected but are rather gene carriers. With each pregnancy of carrier parents; there is a one in four (25%) chance that the offspring will inherit two copies of the disease allele and will therefore have the phenotype. Or there is one in two (50%) chance that the offspring will inherit one copy of the disease allele and will be a carrier. Or there is a one in four (25%) chance that the offspring will inherit no copies of the disease allele and will not express the phenotype or be a carrier, which makes this individual as not being at risk fro passing the disorder to his/her offspring {Elsevier Health 2013}.
In X- Linked dominant inheritance, only one copy of a disease allele on the X- chromosome is required for an individual to be susceptible to an X-linked dominant disease, where both males and females can be affected, although males may be more
32 severely affected because they only carry one copy of genes found on the X chromosome; and in some conditions X-linked dominant disorders are lethal in males. When a female is affected, each pregnancy will have a one in two (50%) chance for the offspring to inherit the disease allele. While when a male is affected, all his daughters will be affected, but none of his sons will be affected {Elsevier Health 2013}.
In the other hand, in X-linked recessive inheritance any male with one copy of an X-linked recessive disease allele is affected, while females are usually carriers because they have one copy of the disease allele and affected males are related through carrier females. For carriers females, with each pregnancy there is a one in two (50%) chance her sons will inherit the disease allele and a one in two (50%) chance her daughters will be carriers. Affected males transmit the disease allele to all of their daughters, who are then carriers, but to none of their sons. While women who are affected when they have two copies of the disease allele, all of their sons will be affected and all of their daughters will be unaffected carriers {Elsevier Health 2013}.
It appears in the literature that genetics of the EEG traits is simple e.g. Mendelian type; therefore we would think of a single gene for each of the traits. However, this needs to be clarified through a meta-analysis to know the real frequency of these traits in families. Whether an individual has both the EEG abnormality in addition to a clinical seizure would involve many genes. Identifying the primary gene responsible for the EEG abnormality is important. The other extra genes responsible for facilitating the spread of epileptic seizures are also important but more secondary to the understanding of epileptogenesis.
We hypothesize that if the frequency is 50% of first-degree relatives then it will be a Mendelian inheritance and simple linkage and related simple genetic methods will resolve this issue.
Attempts are now being made to identify susceptibility genes, employing microarrays, whole genome association studies, and whole genome sequencing.
33 Advances in gene identification have permitted carrier detection and preclinical and prenatal diagnosis in some of these epilepsies, leading to improved genetic counseling. It is important to note that these have resulted in prevention as well as early diagnosis and specific treatment in certain forms of epilepsy {Avanzini 2009}.
For future studies, the next step would be to identify further genes both in monogenic epilepsies and epilepsies with complex inheritance, genotype-phenotype correlations and functional studies of the abnormal proteins. This will have practical applications for diagnosis, genetic counseling and possible treatment, in addition to increasing our knowledge of normal brain function and mechanisms of epileptogenesis.
1.14 Objectives of our review
To determine the frequency of EEG abnormal waves in the healthy/asymptomatic/non-epileptic relatives of epileptic patients with juvenile myoclonic epilepsy (JME), childhood absence epilepsy (CAE) or rolandic epilepsy (RE), through a systematic review and meta-analysis.
34 Chapter 2: Methods
2.1 Review Question
What is the frequency of EEG abnormal waves in the asymptomatic relatives of idiopathic epilepsy patients?
2.2 Protocol
We used the Preferred Reporting Items for Systematic Review and Meta-analysis for Protocols (PRISMA-P) in the reporting of this review {Moher et al 2015}. Our Protocol was registered on Sept. 2013 with the PROSPERO database (CRD42013005615).
2.3 Inclusion Criteria
We included studies with cohort, case-control or cross-sectional methodology examining abnormal electroencephalogram on asymptomatic (non-epileptic) subjects relatives to epileptic patients (parents, siblings or offspring). Both English and non- English language reports, in addition to, published and non-published reports were included.
P: Asymptomatic (non-epileptic) relatives of patients with JME, CAE and RE E: Abnormal EEG Diagnostic tool EEG O: Frequency of abnormal EEG (Polyspike, 3Hz spike, centrotemporal, theta and PPR/PCR) S: Cohort, case control and cross-sectional
2.4 Exclusion Criteria
We excluded case series or case reports, review articles and qualitative studies. In addition, we excluded reports that did not mention the percentage of EEG wave of asymptomatic relatives in their outcome, or if the participants had anomalous features,
35 undergone previous epilepsy surgeries or had a history of seizures, head injury, drug abuse or neurological impairments.
2.5 Population
Asymptomatic (non-epileptic) relatives of epilepsy patients with idiopathic juvenile myoclonic epilepsy (JME), childhood absence epilepsy (CAE) or rolandic epilepsy (RE) were included. Relatives include siblings, parents or offspring of epileptic patients.
2.6 Diagnostic Test – Electroencephalogram
Asymptomatic relatives of epilepsy patients who have undergone an electroencephalogram (EEG) test and had an abnormal EEG wave report.
2.7 Outcome Measures
2.7.1 Primary Outcome
The primary outcome of the review was the frequency of subjects with abnormal EEG brain waves in the asymptomatic relatives of epilepsy patients. In addition, spike and polyspike waves for patients with JME, or spike waves among relatives of CAE, or the centrotemporal spike waves among relatives with RE.
2.7.2 Secondary Outcome
We also sought to determine the percentage of wave activity due to photo- stimulation, or due to closing the eyes during sleep or wakefulness, as well as, the descriptions of other epileptiform changes.
36 2.8 Search Strategy
Medline, EMBASE, CINAHL, and the Cochrane Central Register of Controlled Trials were searched on July 5, 2013. Searches were performed with no year or language restrictions. The following search terms were used: rolandic epilepsy, myoclonic epilepsy, Janz syndrome, electroencephalography and other terminologies as shown in (Table 1).
Appropriate wildcards were used in the searching in order to account for plurals and variations in spelling. This search was conducted by an experienced librarian and was peer-reviewed by another librarian using the Peer Review of Electronic Search Strategies (PRESS) checklist {McGowan et al 2010}. The electronic search was supplemented by scanning the references lists of included studies and relevant reviews. The full search strategy for MEDLINE is in Appendix 1.
37 Table 1: Electronic Databases and Terminology
Type Database Terminology
JME MEDLINE, EMBASE, Juvenile myoclonic epilepsy, Janz syndrome, CINHAL, Cochrane idiopathic epilepsy, genetic epilepsy, electroencephalograph, humans CAE MEDLINE, EMBASE, Childhood absence epilepsy, pyknolepsy, CINHAL, Cochrane idiopathic generalized epilepsy, centrencephalic epilepsy, genetic epilepsy, electroencephalograph, humans RE MEDLINE, EMBASE, Rolandic epilepsy, benign childhood epilepsy CINHAL, Cochrane with centrotemporal spikes, epilepsy syndrome, sylvian seizures, humans
JME: Juvenile Myoclonic Epilepsy, CAE: Childhood Absence Epilepsy, RE: Rolandic Epilepsy, CINHAL: Cumulative Index of Nursing and Allied Health Literature, MEDLINE: Medical Literature Analysis and Retrieval System Online, EMBASE: Excerpta Medica Database.
38 2.9 Data Collection and Analysis
2.9.1 Selection of Studies
We imported the references obtained through our search into a bibliographical database library using RefWorks, where duplicates were manually removed. Then we imported the database into synthesi.sr; online systematic review software {Synthesi.sr 2006}. A training exercise was done prior to conducting the screening process on a random sample of 25 titles and abstract citations. Kappa-Statistics {Higgins 2002} were used to measure the agreement rate between authors (Table 2).
Screening was done at three different levels, during the level-1 screening process we only looked at titles and abstracts. The article was only obtained when a decision could not be easily made from the title or abstract alone, or if the citation satisfied the inclusion criteria. Full-text articles of the selected citations were obtained for further examination during the level-2 screening. They were obtained through the University of Toronto and the Hospital of Sick Children’s libraries. When a paper was not found in the libraries, we ordered them through an inter-library loan. Two independent authors (MT and DB) conducted all levels of screening, when conflicts occurred; the team resolved them through discussion with a third author (BM).
39
Table 2: Interpretations of Kappa Statistics
Kappa Agreement
<0 Poor
0.01-0.20 Slight agreement
0.21-0.40 Fair agreement
0.41-0.60 Moderate agreement
0.61-0.80 Substantial agreement
0.81-0.99 Almost perfect agreement {Higgins 2002}
40
2.9.2 Verification of Study Eligibility
During the first level of screening, verification of study eligibility was conducted by answering five questions. If they were all answered by yes, the study would be transferred to the next screening level; level-2 screening, and then decided upon if it would be included for data abstraction or not (level-3 screening). Full details of verification questions are in Appendix 2.
Figure 1: Verification of Study Eligibility
This figure displays the five questions asked for the verification of study eligibility during level-1 screening, looking at only titles and abstracts the decision is made to either include or exclude the study based on five questions; did the study include asymptomatic relatives? Did the study include juvenile myoclonic epilepsy (JME) or childhood absence epilepsy (CAE) or rolandic epilepsy (RE)? Did the study use the electroencephalogram (EEG)? Did the study report the percentage of abnormal EEG? Is the study a cohort or case control or cross sectional in methodology? If all five questions were answered either with “yes” or “unclear”, the study would be included for level-2 screening. In level-2 screening, all full text articles are obtained and further decisions are made to whether these studies would be included or not for data abstraction (level-3 screening).
41 2.9.3 Data Extraction and Management
Two independent review authors (MT and DB) with methodological and/or content expertise performed data extraction (level-3) on all the selected articles using a standardized data extraction form. Prior to embarking on the data extraction, we conducted a training exercise using a random sample of five included studies. Data extraction included information on publication status, year, country and language of publication. We then extracted information on the description of the study design, participants, interventions and outcome.
To insure data accuracy, two independent review authors (MT and DB) extracted all data in duplicate and conflicts were resolved through discussion amongst the team. We maintained a list of all citations that were excluded after full-text review with justifications for exclusion {Cochrane 2011, Lefebvre 2011}. The data abstraction form can be found in Appendix 2.
2.9.4 Dealing with Missing Data
We contacted the original investigators to request missing data, whenever possible. In addition, we have explained the assumption of any methods used to cope with missing data and addressed the potential impact of missing data on the findings of the review in the discussion section {Higgins et al 2011}.
2.9.5 Quality Appraisal Tool for Included Studies
All observational studies were assessed for risk for bias using the Newcastle-Ottawa Scale (NOS) for cohort studies and the modified version of NOS for cross-sectional studies {Fnais et al 2014, Wells et al 2014} Appendix 3 and 4. Two reviewers (MA and DB) assessed study quality independently, and we resolved discrepancies by discussion or the involvement of a third reviewer (BM).
42 2.9.6 Data Synthesis
We combined the extracted data from the studies and calculated a pooled estimate of the proportion of abnormal EEG in each population along with the corresponding 95% confidence interval (CI). Statistical heterogeneity was considered when the I2 was greater than 50%. All analyses were done using the R statistical program (R Development Core Team 2010) and the meta-analysis was done using the metafor package {Viechtbauer 2010}.
We considered studies for meta-analysis when measures of outcomes were comparable, and when the review team believed that clinical, statistical and methodological homogeneity were present.
2.9.7 Subgroup Analysis and Investigation of Heterogeneity
When clinical or methodological heterogeneity was observed, we conducted subgroup analyses categorizing the frequency of EEG changes in asymptomatic relatives of probands by Epilepsy type and by the abnormal EEG wave type.
2.9.8 Sensitivity Analysis
Sensitivity analysis was conducted when relevant studies were excluded from the meta-analysis because they did not mention the description of “asymptomatic” relatives in the methods of their publication. Sensitivity analysis was done on the prevalence of abnormal EEG in relatives of all idiopathic epilepsy types, as well as the prevalence of abnormal EEG in each Epilepsy type JME, CAE, and RE. By considering these studies in our sensitivity analysis we were able to analyze both siblings and parents.
43 2.10 Statistical Methods
2.10.1 Fixed and Random effect models
th Let Ti be the estimates of the study population effect-size given by �! for the i study, where i=1…k with its estimated variance vi. The overall estimate of the effect size would be given by the following: For the fixed effect model equation :
�! = �! + �!
! where the �! is the sampling error of the study with mean of 0 and variance � : ! �!~� 0, �
In this case the parameter �! is assumed to be the same, � for all the studies, implying that Ti are the various estimates of the same effect size.
On the other hand, the random effect model assumes that each of the study parameter �! estimates the overall population parameter denoted by � . Therefore the above equation becomes:
�! = � + �! + �!
! Where the �! is the random effect part of the studies �!~� 0, �
Under the null hypothesis of no heterogeneity between the studies; the fixed effect model is denoted by H0: �! = �! = �! = ⋯ = �! = � , however the precision of the studies would be different and would be inversely proportional to the variance of the study. In this case the overall estimate of the effect-size is estimated by minimizing the variance using maximum-likelihood method given by
! !!! �!�! �. = ! !!! �!
44 Where ! �! = , followed by the overall sampling variance of the overall estimate given by !! 1 �. = ! !!! �! {Michael et al 2009}.
2.10.2 Heterogeneity
The test of heterogeneity allows to test for at least one of the �!′� that would be different from the remainder of the parameters, which is also interpreted as the comparison of the between-study variability to within-study variability, this measure is given by ! ! � = �!(�! − �.) !!! The between studies variance is computed as follow � − (� − 1) �� � > � − 1 �! = � 0 �� � ≤ � − 1
! !! Where � = �! − !! In order to assess the heterogeneity and summarize them for the meta-analysis it is deemed that H & I2 statistics are fairly interpretable compared to using Q statistics {Higgins et.al 2002}. H represents the proportion of total variation in the study estimates that is due to the heterogeneity and simplified as: � �! = � − 1 The expected value could be represented as the ratio of sampling variance over total variance which corresponds to the sum of the within and between study variability
! ! �(�!) = ! !! , !! Where s is the sample estimate of the within-study variability or sampling error �!. In special circumstances this could be related to the quantification of heterogeneity given by the following equation:
45 �! − 1 �! = �! So, if there is no heterogeneity in the studies, implies that the �! = 0 making H=1, vis-à- vis �! = 0, as described by Higgins in the meta-analysis of Albumin studies {Higgins et. al. 2002}.
46 Chapter 3: Results
3.1 Systematic Review Results
We conducted a pilot-test for both (level 1) and (level 2) screening, as well as for (level 3); data abstraction and quality appraisal. Both reviewers (MA and DB) independently reviewed the fist 25 citations of each level and resulted with high agreement in all levels.
3.1.1 Literature Search
Our literature search yielded 10,223 titles and abstracts (Table 3). We included 211 potential relevant full text articles, 46 of them were non-English papers, 16 were written in German, 6 Russian, 6 French, 5 Italian, 4 Polish, 2 Spanish, 2 Romanian, 1 Chinese, 1 Japanese, 1 Portuguese, 1 Czech and 1 Norwegian (Table 4). Native speakers in the field of Neurology and Epilepsy translated these articles. In addition, Google- translate was used, as required.
A total of 15 studies were passed up to data abstraction. Six studies were on Juvenile Myoclonic Epilepsy (JME), 5 studies on Childhood Absence Epilepsy (CAE), 4 studies on Rolandic Epilepsy (RE) and one study on Idiopathic epilepsy.
According to the pre-specified exclusion criteria, a total of 191 full text articles were excluded for the following reasons; 77 studies did not include relatives of epileptic patients, 35 studies included other types of epilepsy, 26 were review articles, 11 papers did not include outcome of interest, 10 papers were not able to be found despite extensive search, 9 studies only included epileptic patients, 7 papers were abstract only, 5 were case reports, 5 were companion reports, 4 were case series, 2 were letters to the editors, 2 were editors comments, 2 were posters and one study included patients with neurological disorders (Table 5).
47 A total of 15 studies fulfilled the inclusion criteria and were included for data abstraction {Alonso 2005(a), Atakli 1999, Akgun 2009, Jayalakshmi 2006, Tsuboi 1973, Wandschneider 2010, Alonso 2005(b), Degen 1990(a), Doose 1973, Metrakos 1961, Bali 2007, Degen 1990(b), Verrotti 2013, Serra 2001, Kishimoto 1961}. In addition 5 companion reports were included, which were used for supplemental data only (Figure 2).
48
Figure 2: Study Flow Chart
N =10223 Potentially relevant studies identified and screened for retrieval
N=255 excluded (duplicate)
N=9968 Studies retrieved for more detailed evaluation
N=9757 excluded at level 1 screening
N=191 excluded articles: -Abstract of review (1) N=211 Potentially relevant -Case series (4) articles -Case report (5) -Review article (26) -Letter to the editor (2) -Editors comments (2) -Abstract only (6) -Posters (2) -Other epilepsies (35) -No asymptomatic relatives (77) N=15 Studies included for -Patients with neurological data abstraction +5 disorders (1) companion reports -Papers not found (10) -Did not include outcome of interest (11) -Symptomatic relatives only (9)
N= 10 Studies included in Meta-analysis
N= 13 Studies included in Sensitivity Analysis
Study flow. This figure displays the flow of titles/abstracts and full text studies through the systematic review. 49 Table 3: Electronic Database Search Results
Electronic Database Results
Medline 4421
EMBASE 5624
CINHAL 140
Cochrane Clinical Register of Controlled Trials 38
Total with duplicates 10223
50
Table 4: Number of Non-English Papers Potentially Relevant For Inclusion
Language Number of translated papers German 16 Russian 6 French 6 Italian 5 Polish 4 Spanish 2 Romanian 2 Chinese 1 Japanese 1 Portuguese 1 Czech 1 Norwegian 1 Total 46 out of 211 full-text studies
51 Table 5: Excluded Studies and Reason for Exclusion
Author Date Reason Bray 1972 Abstract of review Konishi 1980 Case series Regesta 1987 We were not able to get this paper Baier 1987 Reported different types of epilepsy and did not specify siblings to be asymptomatic or not Bray 1965 Did not specify Epilepsy type Bray 1965 Different type of epilepsy and did not report the percent of abnormal EEG in relatives DeMarco 1986 Case series Doose 2000 Review article Doose 1968 This is a repeated study Doose 1970 Repeated study of ref ID 175515 Doose 1994 Relatives were symptomatic (they had seizures of different types of epilepsy) Doose 1995 Did not specify each type of epilepsy, it only reported different EEG waves Doose 1981 Review article Doose 1973 It’s about photoconvulsive reactions (PCR) and compares epileptic patients with their siblings and healthy controls, but it did not specify which type of epilepsy. Doose 1977 Did not specify each type of epilepsy, it only reported different EEG waves Doose 1970 Included epileptic patients and their siblings, but it includes myoclonic astatic petit mal seizure Doose 1991 Relatives were symptomatic (they had seizures) Doose 1968 Did not specify each type of epilepsy, it only reported different EEG waves (Theta rhythms) and did not specify if children were asymptomatic or not Gerken 1970 Studied photosensitive epilepsies, included epileptic patients and their siblings but did not specify the type of epilepsy. Gerken 1973 Studied spike and waves of different types in epileptic families, including epileptic patients and their siblings but did not specify the type of epilepsy Gerken 1972 Studied occipital waves of different types in epilepsies and other anomalies, included epileptic patients and their siblings but did not specify the type of epilepsy Rodin 1966 Included epileptic patients and psychiatric patients and did not specify the epilepsy type Saito 1991 Included different types of epilepsy and did not specify if offspirngs were asymptomatic or not Iqbal 2009 Analysis was done on neuropsychological profiles of patients and
52 siblings/control, no outcome of interest (no information obtained abut EEG waves in siblings) Koshino 1986 No asymptomatic relative. Only reported on mu rhythm Metrakos 1966 Review article Metrakos 1961 Companion report Tsuboi 1977 All offspring are symptomatic Xie 1988 Family members are epileptic (symptomatic) and no asymptomatic relatives Aktuelle 2005 Not found Adams 1967 Review article Arcos- 1999 Analysis was done on symptomatic (epileptic) relatives of Burgos probands Andermann 1991 Review article Andermann 1972 Surgical epilepsies Anderson 1985 Review article Anderson 1991 Review article Ajmone- 1984 Review article Marsan Afawi 2009 Epidemiological study of other types of epilepsy Alberti 1972 No asymptomatic relatives Andermann 1969 Surgical epilepsies Aicardi 1969 Review article Aparicio 1992 No asymptomatic relatives Barolin 1969 Migraine study not epilepsy Bate 1999 Other epilepsy types Bancaud 1969 Other genetic epilepsy syndrome, no JME Beaumanoir 1974 Epileptic patients only and did not include relatives Beaussart 1969 Different types of epilepsy Bancaud 1969 Case report Bailet 2000 Study on IQ test did not include our outcome of interest Binnie 1992 No relatives Bouquet 1970 Case report Buoni 1998 All relatives have seizures (symptomatic) Blom 1972 No relatives Blume 1978 No relatives Bray 1969 No asymptomatic relatives Bray 1964 No asymptomatic relatives Carignani 1997 No relatives Casaubon 2006 Letter to the editor Clarke 2009 Study about RE epilepsy and migraine Christiani 1979 No asymptomatic relatives
53 Crews 1973 No asymptomatic relatives Capovilla 2001 No asymptomatic relatives Casaubon 2006 Editors comments Cavazzuti 1970 No asymptomatic relatives Da, Silva 2009 No asymptomatic relatives Degen 1991 Febrile seizure Doose 1970 No asymptomatic relatives Doose 1969 Only abstract, no full text Doose 1969 Other epilepsy types Doose 1989 Included other epilepsy syndromes Doose 2000 Review article Doose 1972 Only abstract, no full text Doose 1991 Other epilepsy types Doose 1971 Its myoclonic astatic petit mal not JME Doose 1997 EEG was done in relatives of all 3 types of epilepsy (not only on RE) we are not able to get the data for RE only Delgado- 1991 Review article Escueta Degen 1972 Infantile spasms Delgado- 1989 Review article Escueta Doose 1985 No asymptomatic relatives Doose 1969 Repeated study Dowzenko 1972 No asymptomatic relatives Eeg- 2010 No asymptomatic relatives Olofsson Eeg- 2010 Letter to the editor Olofsson Everett 2007 No asymptomatic relatives Friedlander 1969 No asymptomatic relatives Gastaut 1983 No asymptomatic relatives Gabova 2004 No asymptomatic relatives Geier 1971 No asymptomatic relatives Gerken 1974 Pathogenesis Gerken 1977 Did not report on asymptomatic relatives Gerken 1968 Summary Gianturco 1968 No asymptomatic relatives Gorbunova 1966 Single patient Halliday 1967 No asymptomatic relatives Hall 1971 Abstract no full text Harper 1968 No report on asymptomatic relatives
54 Hajnsek 1969 No relatives Hasaerts 1958 No asymptomatic relatives Hauser 1983 Review of epidemiology Jain 1998 No asymptomatic relatives Jain 2003 No asymptomatic relatives Jain 1997 No asymptomatic relatives Jain 2003 No asymptomatic relatives Jain 1996 No asymptomatic relatives Karlov 1952 No relatives Kato 1977 No relatives Kenedi 1968 No relatives Kellaway 2000 Review of RE and its EEG pattern Kurokawa 1996 No asymptomatic relatives Konishi 1993 No asymptomatic relatives Lee 1994 Review article Loiseau 1992 No asymptomatic relatives Lansdell 1964 No asymptomatic relatives Marini 2003 Symptomatic offspring only Matthews 1973 Review article on EEG uses Mehndiratta 2009 No asymptomatic relatives Millichap 1969 No asymptomatic relatives Nashold 1972 Case series Neubauer 2002 Review on RE and its genetics Neubauer 2000 Review article Negoro 1992 No asymptomatic relatives Needham 1969 Did not report outcome of interest Needham 1971 No asymptomatic relatives Niedermeyer 1973 No asymptomatic relatives Niedermeyer 1968 No asymptomatic relatives Niedermeyer 1969 Abstract in the journal Nishiura 1966 No EEG done on asymptomatic relatives Patra 2012 Review article Pedley 1991 Review article Rowan 1970 Case report Rodin 1969 Abstract only Rodin 1960 Included patient with psychiatric illnesses Sagild 1988 No asymptomatic relatives Serratosa 1999 No asymptomatic relatives Takahashi 1965 No asymptomatic relatives Tsai 2011 EEG was not done on asymptomatic relatives
55 Terzian 1953 No asymptomatic relatives Tsuboi 1980 Review article Usui 2006 Response paper to a study Vadlamudi 2006 No asymptomatic relatives Vogel 1969 Abstract only Wawszczyk 1985 No asymptomatic relatives Wege 1975 No asymptomatic relatives Wolf 2005 No asymptomatic relatives Yamatogi 1993 Symptomatic offspring only Amadian 1976 Russian study. The study was missing and we were not able to retrieve the full study Badalin 1970 Russian study. It was a study on twins only Fridman 1962 Russian study. The study was missing and we were not able to retrieve the full study Mempel 1969 Russian study. Review article Sigidinenko 1989 Russian study. The study was missing and we were not able to retrieve the full study Gorlina 1968 Russian study. The study was missing and we were not able to retrieve the full study Bianchi 1992 Italian study. Included idiopathic epilepsy as generalized and partial with no specifications Bianchi 1991 Italian study. Included idiopathic epilepsy but did not specify epilepsy type Bianchi 1990 Italian study. Did not specify epilepsy type Salvioli 1966 Italian study. Does not include asymptomatic relatives Gloor 1989 French study. Did not include asymptomatic relatives Beaussart 1976 French study. Did not include asymptomatic relatives Bulteau 1995 French study. Did not include asymptomatic relatives Valatx 1975 French study. Did not include asymptomatic relatives Geets 1955 French study. Did not include asymptomatic relatives Bourrous 2010 French study. Did not include asymptomatic relatives Vercelletto 1955 French study. Did not specify outcomes of each epilepsy type and it included case series only Brimani 1976 French study. No asymptomatic relatives. Christian 1975 German study. Did not include relatives Degen 1969 German study. Did not include relatives Degen 1993 German study. Repeated ref ID 175242 Ritter 1977 German study. Did not include relatives Degen 1986 German study. Did not include relatives Doose 1976 German study. Relatives data is unclear Vogel 1962 German study. Did not include relatives
56 Gerken 1969 German study. Studied photosensitive epilepsies and included epileptic patients and their siblings but did not specify the type of epilepsy Lassker 1972 German study. Did not include relatives Matthes 1968 German study. Relatives data is unclear Voelz 1970 German study. Did not include relatives Vogel 1966 German study. Did not include relatives Meyer 1973 German study. Did not include relatives Richter 1956 German study. Did not include relatives Reisner 1962 German study. Did not include relatives Grudzinska 1979 Polish study. Did not report outcome of interest Majchrzak 1987 Polish study. We were not able to find full text paper Niedzielska 1999 Polish study. Did not report outcome of interest Sobczyk 1977 Polish study. Included other types of epilepsy Sakakihara 2002 Japanese study. Review article Trusca 1977 Romanian. Did not include outcome of interest Tudor 1965 Romanian study. Only reports observations in patients not relatives Xie 1986 Chinese study. Included different epilepsy types and did not specify the percent of abnormal waves for each epilepsy type in the asymptomatic relatives Delgado- 2002 Spanish study. Did not report outcome of interest Escueta Gerken 1970 Spanish study. Included different types of epilepsy and did not specify if siblings are asymptomatic or not De Assis 1957 Portuguese study. Case report Fiedlerova 1983 Czech study. Did not include outcome of interest Refsum 1974 Norwegian study. Review article Abdelkefi 2011 Poster presentation Altahan 2010 Poster presentation Dalby 1969 Paper was not found Doose 1967 Paper was not found Buti 1989 Paper was not found
57 3.1.2 Study Characteristics
Studies were published between 1961 and 2013. Three were conducted in the USA {Alonso 2005(a), Alonso 2005(b), Bali 2007}, 5 in Germany {Tsuboi 1973, Wandschneider 2010, Degen 1990(a), Doose 1973, Degen 1990(b)}, 2 in Turkey {Atakli 1999, Akgun 2009}, 2 in Italy {Verritti 2013, Serra 2001}, 1 in India {Jayalakshi 2006}, 1 in Canada {Metrakos 1961}, and one in Japan {Kishimoto 1961}. A total of 13 studies were cross-sectional in methodology, whereas two {Alonso 2005(a),Alonso 2005(b)}, were prospective cohort (Table 6).
3.1.3 Electroencephalographs Characteristics
3.1.3.1 Machine Type
The EEG machine types documented were as follow; 18 Chanel Medelec 118 devices were used by {Atakli 1999, Akgun 2009}. Nihon Kohden Neurofax EEG was used by {Jayalakshmi 2006}. On the other hand, {Doose 1973} used 8 channel Scharzer and {Verroti 2013} used the international 10-20 system of electrode placement.
3.1.3.2 Recording Time
EEG recording time varied across studies. For JME studies {Jayalakshmi 2006, Wandschneider 2010}, the recording time was 40 and 30 minutes, respectively.
For CAE studies {Degen 1990(a), Doose 1973}, the recording times ranged between 20 to 40 minutes during both awake and sleep status.
For RE studies {Bali 2007, Degen 1990(b), Verroti 2013} the recording time ranged between 20 minutes awake and 60 minutes during sleep.
58 3.1.3.3 Technique of Recording:
The techniques used in the JME studies were as follows; {Atakli 1999} reported using an 18-channel 10-20 system, and {Jayalakshmi 2006} used a 21-channel 10-20 system. Whereas, in the CAE studies, {Degen 1990(a)} reported to use a bipolar montage with a time constant 0.3, low-pass filters of 70Hz and a paper speed of 30mm/s, while {Doose 1973} used an 8- channel bipolar/monopolar montages.
Finally, the RE studies reported that {Bali 2007} used an international 10-20- system electrode placement, and {Degen 1990(b)} used a time constant of 0.3 and a high- frequency filter of 70 Hz with a 30mm/s paper speed.
3.1.3.4 Sleep Deprivation
Only three RE studies reported that their patients had undergone sleep deprivation {Bali 2007, Degen 1990(b), Verrotti 2013}. Studies use sleep deprivation as triggering factors for epilepsy.
3.1.3.5 Photic Stimulation and Hyperventilation
All the studies reported that their patients had undergone both photic stimulation and hyperventilation except for three studies {Alonso 2005(a), Serra 2001, Tsuboi 1973}, which did not report them. These are triggering factors for seizures therefore researchers used them to initiate seizures for diagnostic purposes.
59 Table 6: Study Characteristics
Author Year Country Epilepsy Study EEG Machine Recording Montage Sleep Photic Hyper- type Design Time Deprived Stimulation ventilation
Alonso(a) 2005 USA JME Prospective NR NR NR NR NR NR Cohort
Atakli 1999 Turkey JME Cross 18 Channel Medelec NR 18-channel, NR Yes Yes sectional 118 device. Electrodes 10-20 were placed according system to the international 10- 20 system
Akgun 2009 Turkey JME Cross Medelec 118 device NR NR NR Yes Yes sectional
Jayalakshmi 2006 India JME Cross Nihon Kohden 40 min 21-chanel Yes Yes sectional Neurofax EEG 10-20 machine system
Tsuboi 1973 Germany JME Cross NR NR NR NR NR NR [Impulsive sectional petit mal]
Wandschneir 2010 Germany JME Cross NR 30 min NR NR Yes Yes sectional
60 Alonso(b) 2005 USA CAE Prospective NR NR NR NR NR NR evolving Cohort to JME
Degen(a) 1990 Germany CAE Cross NR 20 min Bipolar NR Yes NR sectional awake montage 40 min sleep were used (time constant, 0.3; low- pass filters, 70Hz; paper speed 30mm/s)
Doose 1973 Germany CAE Cross 8 channel Schwarzer The time 8-channel- NR Yes Yes sectional electroencephalograph constant was bipolar/mon according to 0.1 sec and opolar standardized the procedures amplification was 50uV = 5mm
Metrakos 1961 Canada CAE Cross NR NR NR NR Yes Yes Centren- sectional cephalic
Bali 2007 USA RE Cross NR 60 min Internationa Yes Yes Yes sectional l 10-20 (Awake system and electrode sleep) placment
Degen(b) 1990 Germany RE Cross NR 20 min A time Sedated Yes Yes sectional awake and 40 constant of min sleep 0.3 and a high- frequeny filter of (as a rule) 70Hz were used; paper speed was 30mm/s
Verrotti 2013 Italy RE Cross International 10-20 At least 60 NR Yes Yes Yes sectional system of electrode min of digital (Awake placement recording and including sleep) awake and sleep segment was done
61 Serra 2001 Italy RE Cross NR NR NR NR NR NR sectional
Kishimoto 1961 Japan Idiopathic Cross NR NR NR NR NR NR sectional
JME: Juvenile Myoclonic Epilepsy, CAE: Childhood Absence Epilepsy, NR: Not Reported
62 3.1.4 Participants Characteristics
Among the 15 studies, a total of 9248 participants were included, which consisted of epileptic patients, and their first and second-degree relatives. The total number of epileptic patients was 1083. The total number of asymptomatic first-degree relatives was 3885 (siblings, parents and offspring).
All the studies included had siblings as their first-degree relatives. In addition, {Metrakos 1961, Serra 2001} included siblings and parents, while {Tsuboi 1973} included siblings, parents and offspring. In the other hand, Alonso(a) and Alonso(b) included multigenerational first and second-degree relatives.
The number of first degree relatives were as follow; 2332 were relatives of patients with JME, 1289 were relatives of patients with CAE, 178 were relatives of patients with RE and 86 were relatives of Idiopathic epilepsy patients. Further details of the characteristics of probands and relatives are shown in (Table 7) and (Table 8).
The age of the relatives ranged from 2-31 years. Both males and females were included however, not all the studies reported the total number of each gender, therefore limiting our analysis to age and gender predominance.
63 Table 7: Patients Characteristics
Author Year Epilepsy Sample Patients (n) Age Male/Female Type Size
Alonso(a) 2005 JME 2804 186 Classical JME, age Classical JME, Male at recruitment 25.9 (45%) Female (55%) (14-58)
Atakli 1999 JME 141 37 20.33 12 male and 25 female
Akgun 2009 JME 62 21 23.9 11 male and 10 female
Jayalakshmi 2006 JME 163 31 22 years 16 males and 15 females
Tsuboi 1973 JME 529 136 NR 65 males and 71 females
Wandschneir 2010 JME 61 19 25.5 5 males and 15 females
Alonso(b) 2005 CAE 2804 45 Average age was 16 males and 29 females evolving to 6.9 (1 to 11 years) JME
Degen(a) 1990 CAE 118 22 patients Did not specify 59.1% males with only the age of the idiopathic sample size was epilepsy reported
Doose 1973 CAE 1179 252 NR 121 males and 118 female
Metrakos 1961 CAE 938 211 NR 103 males and 108 females
Bali 2007 RE 53 23 NR 17 boys and 6 girls
64 Degen(b) 1990 RE 112 43 Most patients were NR 7-14 years of age
Verrotti 2013 RE 35 9 7.8 5 boys and 4 girls
Serra 2001 RE 114 None NR NR
Kishimoto 1961 Idiopathic 170 48 21 male and 27 NR female
JME: Juvenile Myoclonic Epilepsy, CAE: Childhood Absence Epilepsy, NR: Not Reported
65 Table 8: Asymptomatic Relatives Characteristics
Author Year Epilepsy Sample Asymptomatic Age Male/Female Siblings Parents Offspring type Size relatives (n) (Mean)
Alonso(a) 2005 JME 2804 1756 NR NR NR NR NR
Atakli 1999 JME 141 48 24.17 25 male and Yes No No 23 female
Akgun 2009 JME 62 21 22.8 9 males and Yes No No 12 females
Jayalakshmi 2006 JME 163 116 31.1 74 males and Yes Yes Yes 58 females
Tsuboi 1973 JME 529 370 NR 179 males Yes Yes Yes and 191 females
Wandschneir 2010 JME 61 21 25.1 10 males and Yes No No 11 females
Alonso(b) 2005 CAE 2804 541 NR NR NR NR NR evolve to JME
Degen(a) 1990 CAE 118 50 NR NR Yes No No
Doose 1973 CAE 1179 242 NR 108 males Yes No No and 134 females
Metrakos 1961 CAE 938 418 NR NR Yes Yes No
Bali 2007 RE 53 30 10.3 14 males and Yes NR NR (Median) 16 females
Degen(b) 1990 RE 112 64 NR NR Yes No No
66 Verrotti 2013 RE 35 8 7.7 5 males and 3 Yes No No females
Serra 2001 RE 114 114 2- 16 18 males and Yes Yes No years 23 females
Kishimoto 1961 Idiopathic 170 86 NR 44 male and Yes Yes NR 42 female
JME: Juvenile Myoclonic Epilepsy, CAE: Childhood Absence Epilepsy, NR: Not Reported
67 3.1.5 Outcomes
A total of 15 studies were included. Studies were divided according to their type of epilepsy; 6 JME studies, 4 CAE studies, 4 RE studies and 1 idiopathic epilepsy study as follows:
3.1.5.1 Juvenile Myoclonic Epilepsy (JME)
Proband’s outcome: A total of 6 studies reported on epileptic patients with JME and included their asymptomatic relatives {Tsuboi 1973, Atakli 1999, Jayalakshmi 2006, Alonso 2005(a), Akgun 2009, Wandscheneider 2010}. Among these, only 4 studies {Akgun 2009, Jayalakshmi 2006, Wandschneider 2010} reported their subjects to have polyspike waves. In addition, 3 studies {Alonso 2005(a), Jayalakshmi 2006, Wandschneir 2010} reported both the polyspike waves and 3Hz spike waves to be present in epileptic patients. One study {Atakli 1999} did not specify the type of abnormal discharges in the EEG report; it only reported its epileptic patients to have “abnormal waves”. In addition, {Tsuboi 1973} reported the EEG discharges as specific or unspecific abnormalities (Specific abnormalities included spike and wave complex and or/spike). None of the studies reported their patients to have centero-temporal sharp waves (Table 9).
Relative’s outcome: In regards to their asymptomatic relatives, only 4 out of the 6 studies reported their subjects to have generalized polyspike waves in their outcome {Alonso 2005(a), Atakli 1999, Akgun 2009, Jayalakshmi 2006}. In addition, 3 studies {Alonso 2005(a), Atakli 1999, Wandschneider 2010} reported their subjects to have 3Hz spike waves. One study {Atakli 1999} reported a number of asymptomatic relatives to have centrotemporal waves in their EEG test, while {Tsuboi 1973} reported the abnormal EEG as being specific or unspecific changes (Table 10). The relatives were described as being siblings in 4 JME studies {Atakli 1999, Akgun 2009, Tsuboi 1973, Wandschneir 2010}. Sibling’s data are presented in (Table 11). In addition to including siblings; {Tsuboi
68 1973} also included parents and offsprings, further details are presented in tables (Table 12) and (Table 13) respectively.
3.1.5.2 Childhood Absence Epilepsy (CAE) Outcome
Proband’s outcome: A total of 4 studies reported on patients with CAE and their asymptomatic relatives {Metrakos 1961, Doose 1973, Degen 1990(a), Alonso 2005(b)}. Among them, {Alonso 2005(b)} reported that patients have both 3Hz spike waves and polyspike waves in their EEG report, while {Metrakos 1961} reported both typical type: which were paroxysmal bilaterally synchronous 3 per second wave and spike, and atypical type: which are waves with slight variation from the typical EEG abnormality (Table 9).
Relative’s outcome: In regards to the asymptomatic relatives, all 4 studies reported presence of abnormal brain waves. Among them {Doose 1973, Degen 1990(a),Alonso 2005(a)}, reported the asymptomatic relatives to have shown 3Hz spike waves in their EEG reports. While one study, {Doose 1973} reported that asymptomatic relatives expressed both 3Hz spike waves and centro-temporal waves. In addition, {Metrakos 1961} used the centrencephalic definition for abnormal EEG waves and divided the abnormal waves into typical and atypical waves (Table 10). None of the 4 studies reported to the presence of generalized polyspike waves. Three CAE studies described the relatives to be siblings {Degen 1990(a), Doose 1973, Metrakos 1961} (Table 11), while, {Metrakos 1961} described the relatives to be siblings and parents (Table 12).
3.1.5.3 Rolandic Epilepsy (RE) Outcome
Proband’s outcome: A total of 4 studies reported on patients with RE and their asymptomatic relatives {Degen 1990(b), Serra 2001, Bali 2007, Verroti 2013} most of the studies reported the EEG abnormal waves as being centrotempral discharges (Table 9).
69
Relative’s outcome: In regards to the asymptomatic relatives, all 4 studies reported abnormal brain waves to be present. Among them 2 studies {Bali 2007, Degen 1990(b)} reported that asymptomatic relatives expressed 3Hz spike waves in the EEG. Also, 2 studies {Blai 2007, Verroti 2013} reported their subjects to have centrotemporal waves. Only one study {Serra 2001} did not specify the type of abnormal brain waves in their asymptomatic relatives (Table 10). Four RE studies reported the relatives to be siblings {Bali 2007, Degen 1990(b), Verrotti 2013, Serra 2001} (Table 11). In addition to siblings {Serra 2001} included parents as well (Table 12).
3.1.5.4 Idiopathic Epilepsy Outcome
There was only one study in this category {Kishimoto 1961}, which included both epileptic patients and their asymptomatic relatives with abnormal brain waves. However, the authors did not specify the type of idiopathic epilepsy (Table 10).
70 Table 9: Abnormal Electroencephalogram Waves in Epileptic Probands
Author Year Epilepsy Sample Patients Abnormal Poly 3 Hz Centro- Other EEG findings type Size Sample EEG (n) spike spike temporal size waves waves waves
Alonso(a) 2005 JME 2804 186 186 61% NR NR Focal slow, sharp of spike waves were found in 10%, Generalized bursts of 4-6 Hz slow waves without spike were found in 2%. And 13% of the interictal EEG was normal.
Atakli 1999 JME 141 37 37 NR NR NR None
Akgun 2009 JME 62 21 9 6 NR NR Intermittent generalized slowing (IGS). 3 patients had 6-7 Hz theta activity
Jayalakshmi 2006 JME 163 31 31 27 3 NR 1 proband had 5Hz SW. Photoconvulsive response (PCR) positive in 4 probands (12.9%). Intermittent theta was found in 7 while diffuse theta activity was noted in 2 subjects. Asymmetry in voltage of SW/PSW was found in 4 (12.9%). Focal EEG abnormality was found in 4 subjects (12.9%) Tsuboi 1973 JME 529 136 NR NR NR NR
Wandschneir 2010 JME 61 19 8 19 3 NR 1 (5.3%) subject had IG (intermittent generalized) slowing. 5 (26.3%) subjects had focal slowing
71 Alonso(b) 2005 CAE 2804 45 45 20 45 NR 29 (78%) had 2-5 Hz single spike and evolving slow wave complexes. to JME Both single spike wave and polyspike waves were observed in 34% of all cases. Also diffuse fast low amplitude 15-25 Hz in 22% of cases. Bursts of 3- 5Hz single spike wave and/or 4-6Hz polyspike wave were included during hyperventilation in 29% of probands and during photostimulation in 22%. Background activity was normal in all cases. Degen(a) 1990 CAE 118 22 22 NR NR NR None patients with idiopathi c epilepsy
Doose 1973 CAE 1179 252 252 NR 252 NR Theta wave was found in 61 out of 76. Occipital delta found in 58 out of 102. PS 45 out of 85
Metrakos 1961 CAE 939 211 NR NR NR NR
Bali 2007 RE 53 23 23 NR NR NR None
Degen(b) 1990 RE 112 43 36 NR NR NR None
Verrotti 2013 RE 35 9 9 NR NR NR None
72 Serra 2001 RE 114 None NR NR NR NR None
Kishimoto 1961 Idiopathi 48 45 NR NR NR None c 170
ME: Juvenile Myoclonic Epilepsy, CAE: Childhood Absence Epilepsy, NR: Not Reported
73 Table 10: Abnormal Electroencephalogram Waves in Asyptomatic Relatives
Author Year Epilepsy Sample Relatives Asympto Abnormal Poly 3 Hz spike Centro- Theta PPR/ Comments type Size included matic EEG (n) spike waves (n) temporal Waves PCR relatives waves waves (n) (n) (n) (n) (n)
Alonso(a) 2005 JME 2804 NR 1756 24 15 3 NR NR NE Relatives were not specified
Atakli 1999 JME 141 Siblings 48 13 5 5 3 NR NR
Akgun 2009 JME 62 Siblings 21 7 1 NR NR 6 NR
Jayalakshmi 2006 JME 163 1st degree 116 15 7 NR NR 6 2 (Siblings, relatives parents and offspring)
Tsuboi 1973 JME 529 Siblings 370 267 Unclear Unclear NR NR NR 57 (total Parents specific) Offspring
Wandschneir 2010 JME 61 Siblings 21 4 NR 1 NR NR 1
Alonso(b) 2005 CAE 2804 NR 541 38 3 7 NR NR NR Relatives evolving to were not JME specified
Degen(a) 1990 CAE 118 Siblings 50 36 NR NR NR NR NR
Doose 1973 CAE 1179 Siblings 242 68 NR 12 NR 14 30
Metrakos 1961 CAE 938 Siblings 418 145 Unclear Unclear NR NR NR 97 (typical Parents and atypical centrencphea lic)
Bali 2007 RE 53 Siblings 30 13 NR 2 13 NR NR
74 Degen(b) 1990 RE 112 Siblings 64 24 NR NR NR NR NR 2.5-4Hz were noted in 22 siblings
Verrotti 2013 RE 35 Siblings 8 2 NR NR 2 NR NR
Serra 2001 RE 114 Siblings 114 31 NR NR NR NR NR Parents
Kishimoto 1961 Idiopathic Siblings 86 65 NR NR NR NR NR 170 Parents
JME: Juvenile Myoclonic Epilepsy, CAE: Childhood Absence Epilepsy, NR: Not Reported Specific: Spike and wave complex and/or spikes Centrencphalic: Typical (paroxysmal bilaterally synchronous 3 per second wave and spike), Atypical (slightly variant of the typical) PPR: Photoparoxysmal Response, PCR: Photoconvulsive response.
75
Table 11: Abnormal Electroencephalogram Waves in Asymptomatic Siblings
Author Year Epilepsy Relative Siblings Abnormal Poly 3 Hz Centro- Comments type (n) (n) EEG (n) spike spike temporal waves waves waves (n) (n) (n) Atakli 1999 JME 141 48 13 5 5 3
Akgun 2009 JME 62 21 7 1 NR NR
Tsuboi 1973 JME 529 128 87 Unclear Unclear NR 17 (Specific)
Wandsc 2010 JME 61 21 4 NR 1 NR hneir
Degen 1990 CAE 118 50 36 NR 27.25 NR (a)
Doose 1973 CAE 1179 242 68 NR 12 NR
Metrak 1961 CAE 983 223 119 Unclear Unclear NR 82 os (Centrence phalic)
Bali 2007 RE 53 30 13 NR 2 13
Degen 1990 RE 112 64 26 NR 22 NR (b)
Verrotti 2013 RE 35 8 2 NR NR 2
Serra 2001 RE 114 41 14 NR NR NR
JME: Juvenile Myoclonic Epilepsy, CAE: Childhood Absence Epilepsy, NR: Not Reported Specific: Spike and wave complex and/or spikes Centrencphalic: Typical (paroxysmal bilaterally synchronous 3 per second wave and spike), Atypical (slightly variant of the typical)
76
Table 12: Abnormal Electroencephalogram Waves in Parents
Author Year Epilepsy Relative Parents Abnormal Poly 3 Hz Centro- Comments type (n) (n) EEG (n) spike spike temporal waves waves waves (n) (n) (n) Tsuboi 1973 JME 529 128 73 Unclear Unclear NR 12 (Specific)
Metrakos 1961 CAE - 938 195 26 Unclear Unclear NR 15 Centrenc (centrencep ephalic halic)
Serra 2001 RE 114 73 17 NR NR NR
JME: Juvenile Myoclonic Epilepsy, CAE: Childhood Absence Epilepsy, NR: Not Reported Specific: Spike and wave complex and/or spikes Centrencphalic: Typical (paroxysmal bilaterally synchronous 3 per second wave and spike), Atypical (slightly variant of the typical)
Table 13: Abnormal Electroencephalogram Waves in Offspring
Author Year Epilepsy Relative Offspring Abnormal Poly 3 Hz Centro- Comments type (n) (n) EEG (n) spike spike temporal waves waves waves (n) (n) Tsuboi 1973 JME 529 114 102 Unclear Unclear NR 28 (Specific)
JME: Juvenile Myoclonic Epilepsy. Specific: Spike and wave complex and/or spikes.
77 3.2 Statistical Analysis - Meta-analysis Results
In this review we had conducted both a meta-analysis and a sensitivity analysis. The meta-analysis was done under strict selection criteria where only the studies that mentioned in their methods the description of enrolling “asymptomatic” relatives were included. While in our sensitivity analysis less strict criteria were considered for the selection of studies, and all studies that had done the EEG on relatives even if they did not mention the word “asymptomatic” relatives, were included. The reason behind this sensitivity analysis was because in older studies, conducted in the 1960’s and 1970’s, the quality of reporting was lower than recent years. We assume from our experience in the field of epilepsy that these studies meant to include relatives who were not epileptic, therefore excluding these studies would lead to missing EEG abnormal variables that could be important.
3.2.1 Studies Included in Meta-analysis
Out of 15 studies included in our systematic review, 10 studies were included in our final meta-analysis {Atakli 1999, Akgun 2009, Jayalakshmi 2006, Wandschneider 2010, Degen 1990(a), Doose 1973, Bali 2007, Degen 1990(b), Verrotti 2013 and Serra 2001}.
3.2.2 Studies Excluded in Meta-analysis
A total of 5 studies were excluded from our meta-analysis {Alonso 2005(a), Alonso 2005(b), Tsuboi 1973, Metrakos 1961 and Kishimoto 1961}. Reasons for exclusion were due to methodological diversity and clinical diversity. Methodological heterogeneity was due to variability in the study designs; all included studies were cross- sectional except for {Alonso 2005(a) and Alonso 2005(b)} which were cohort studies. Clinical heterogeneity was due to variability in participants and EEG outcomes; {Kishimoto 1961, Tsuboi 1973 and Metrakos 1961}, further details is shown in (Table 14).
78
Table 14: Excluded Studies in Meta-analysis and Reason for Exclusion
Author Heterogeneity type Reason for exclusion Alonso 2005(a) Methodological Cohort methodology study diversity Alonso 2005(b) Methodological Cohort methodology study diversity Kishimoto 1961 Clinical diversity Did not specify idiopathic epilepsy (participants variability) Metrakos 1961 Clinical diversity Status of asymptomatic relatives included (Participants and was unclear and the outcome of interest outcome variability) was not specified, in addition they divided the abnormal waves into centrencephalic (typical and atypical waves). Tsuboi 1973 Clinical diversity Status of asymptomatic relatives included (Participants and was unclear and the outcome of interest outcome variability) was not specified, they categorized the abnormal waves into specific and unspecific
79 3.2.3 Meta-analysis on Abnormal EEG in Asymptomatic Relatives of JME, CAE and RE Patients
For this meta-analysis a total of 10 studies were included, these studies fulfilled the strict inclusion criteria of including asymptomatic relatives and mentioned them in their methodology sections. This prevalence includes all idiopathic epilepsy patients of our interest; JME; CAE and RE.
The pooled prevalence of abnormal EEG in asymptomatic relatives of idiopathic epilepsy patients from JME, CAE and RE was 31.53% [n= 10 studies, 95% CI: 20.89, 42.18] I2=88% (Figure 3).
Figure 3: Prevalence of Abnormal EEG in Asymptomatic Relatives (Studies n=10)
This figure represents meta-analysis of prevalence of abnormal EEG in asymptomatic relatives. N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves. Degen 1990* is the CAE study {Degen 1990(a)}
80 3.2.4 Subgroup Analysis of Abnormal EEG Waves in Asymptomatic Relatives by Epilepsy Type
In this section a subgroup analysis was done by epilepsy type JME, CAE and RE. In order to know the pooled prevalence of each type of epilepsy individually as well as the pooled prevalence of all of them together as idiopathic epilepsies.
3.2.4.1 Juvenile Myoclonic Epilepsy
Studies on JME patients and their asymptomatic relatives were included in this analysis. A total of four studies were included.
The pooled prevalence of abnormal EEG waves in asymptomatic relatives of JME patients was 21% [n= 4 studies, 95% CI: 11.72-30.49] I2=54% (Figure 4).
3.2.4.2 Rolandic Epilepsy
Studies on RE patients and their asymptomatic relatives were included in this analysis. A total of four studies were included.
The pooled prevalence of abnormal EEG waves in asymptomatic relatives of RE patients was 33% [n=4 studies, 95% CI: 24.79, 41.80] I2=32% (Figure 4).
3.2.4.3 Childhood Absence Epilepsy
Studies on CAE patients and their asymptomatic relatives were included in this analysis. A total of two studies were included
The pooled prevalence of abnormal EEG waves in asymptomatic relatives of CAE patients was 42% [n=2 studies, 95% CI: -3.88-87.51] I2=97% (Figure 4).
81 Figure 4: Prevalence of Abnormal EEG in Asymptomatic Relatives by Epilepsy Type
This figure represents subgroup analysis of the prevalence of abnormal EEG in asymptomatic relatives by epilepsy types; Rolandic Epilepsy studies; Absence Epilepsy studies and Juvenile Myoclonic Epilepsy studies N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves Degen 1990* is the CAE study {Degen 1990(a)}
82 3.2.5 Subgroup Analysis of Asymptomatic Relatives by EEG Abnormal Wave Type
In this section, the subgroup analysis was performed according to the type of EEG waves, which are; the polyspike waves; 3Hz spike waves; centrotemporal waves; theta waves and the PPR/PCR.
These were the abnormal waves recorded in the included studies. The pooled prevalence of these abnormal waves in asymptomatic relatives was calculated.
3.2.5.1 Polyspike Waves in Relatives
The pooled prevalence for polyspike wave in asymptomatic relatives of epileptic patients was 7.14% [n=4 studies, 95% CI: 3.25, 11.02] I2=0% (Figure 5).
Four studies reported the relative to have polyspike waves, which were {Atakli 1999, Akgun 2009 and Jayalakshmi 2006} all of them were JME studies.
3.2.5.2 3Hz Spike Waves in Relatives
The pooled prevalence for 3Hz spike wave in asymptomatic relatives of epileptic patients was 6.38% [n=4 studies, 95% CI: 3.83-9.38] I2=0% (Figure 6).
Four studies reported 3Hz spike waves in relatives. Among them, 2 were JME studies {Atakli 1999 and Wandschneider 2010}, while one was RE study {Bali 2007}, and one CAE study {Doose 1973}.
3.2.5.3 Centrotemporal Spike Waves in Relatives
The pooled prevalence for centrotemporal spike waves in asymptomatic relatives of epileptic patients was 23% [n=3 studies, 95% CI: 3.26, 42.87] I2=75.68% (Figure 7).
83 Three studies reported Centrotempral spike waves. One JME study {Atakli 1999} and two RE studies; {Bali 2007 and Verrotti 2013}.
3.2.5.4 Theta Waves in Relatives
The pooled prevalence of theta waves in asymptomatic relatives of pileptic patints was 9% [n=3 studies, 95% CI: 5.43, 14,47] I2= 0% (Figure 8).
Three studies reported theta waves; two JME studies {Akgun 2009 and Jayalakshmi 2006}, and one CAE study {Doose 1973}.
3.2.5.5 PPR/PCR in Relatives
The pooled prevalence of PPR/PCR waves in asymptomatic relatives of epileptic patients was 7.5% [n=3 studies, 95% CI: 1.50, 13.59] I2=80% (Figure 9).
Three studies reported PPR; two JME studies {Jayalakshmi 2006 and Wandschneider 2010}, and one CAE study {Doose 1973}.
84
Figure 5: Prevalence of Polyspike Waves in Asymptomatic Relatives
This figure represents subgroup analysis of prevalence of abnormal EEG in asymptomatic relatives by EEG abnormal waves; polyspike waves. N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves (polyspike waves).
85 Figure 6: Prevalence of 3Hz Spike Waves in Asymptomatic Relatives
This figure represents subgroup analysis of prevalence of abnormal EEG in asymptomatic relatives by EEG abnormal waves; 3Hz spike waves. N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves (3Hz spike waves).
86 Figure 7: Prevalence of Centrotemporal Waves in Asymptomatic Relatives
This figure represents subgroup analysis of prevalence of abnormal EEG in asymptomatic relatives by EEG abnormal waves; centrotemporal waves. N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves (centrotemporal waves).
87 Figure 8: Prevalence of Theta Waves in Asymptomatic Relatives
This figure represents subgroup analysis of prevalence of abnormal EEG in asymptomatic relatives by EEG abnormal waves; theta waves. N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves (theta waves).
88 Figure 9: Prevalence of PPR/PCR in Asymptomatic Relatives
This figure represents subgroup analysis of prevalence of abnormal EEG in asymptomatic relatives by EEG abnormal waves; PPR/PCR. N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves (PPR/PCR). PPR: Photoparoxysmal Response, PCR:Photoconvulsive response
89 3.2.6 Asymptomatic Sibling’s Analysis
In this section, the analyses were done on studies that included siblings data. Both a meta-analysis and a subgroup analysis were performed in order to know the pooled prevalence of abnormal EEG waves in asymptomatic siblings.
3.2.6.1 Meta-analysis on Abnormal EEG Waves in Asymptomatic Siblings
Meta-analysis was done on 9 studies including siblings as their asymptomatic relatives.
The pooled prevalence of abnormal EEG waves in asymptomatic siblings was 36% [n=9 studies, 95% CI: 25.19, 46.46] I2= 80.42% (Figure 10).
3.2.7 Subgroup analysis of Abnormal EEG waves in Asymptomatic Siblings by Epilepsy Type
Subgroup analysis in siblings was also performed according to epilepsy type; these studies were group as JME; CAE and RE. The pooled prevalence of abnormal EEG in siblings was then calculated for each epilepsy type.
3.2.7.1 Juvenile Myoclonic Epilepsy
The pooled prevalence of abnormal EEG in siblings of JME patients was 26.5% [n=3 studies, 95% CI: 17.35, 35.80] I2=0% (Figure 10).
3.2.7.2 Rolandic Epilepsy
The pooled prevalence of abnormal EEG in siblings of RE patients was 36.40% [n=4 studies, 95% CI: 28.25, 44.56] I2= 0% (Figure 10).
3.2.7.3 Childhood Absence Epilepsy
90 The pooled prevalence of abnormal EEG in siblings of CAE patients was 41.8% [n=2 studies, 95% CI: -3.88, 87.51] I2=97.47% (Figure 10).
Figure 10: Prevalence of Abnormal EEG in Asymptomatic Siblings by Epilepsy Type
This figure represents siblings-subgroup analysis of prevalence of abnormal EEG in asymptomatic relatives by epilepsy types in siblings; rolandic epilepsy; absence epilepsy and juvenile myoclonic epilepsy. N: is the total number of asymptomatic siblings, and Events: are the number of siblings with EEG abnormal waves. Degen 1990* is the CAE study {Degen 1990(a)}
91 3.2.8 Subgroup Analysis of Asymptomatic Siblings by EEG Abnormal Wave
In this section subgroup analysis was performed on studies including siblings data, and groupd by the type of EEG abnormal waves. The waves recorded in siblings were; polyspike waves; 3Hz spike waves and the centrotemporal waves.
3.2.8.1 Polyspike Waves in Siblings
The pooled prevalence of polyspike waves in asymptomatic was 7.47% [n=2 studies, 95% CI: 1.47, 14.01] I2=0% (Figure 11).
Two studies reported polyspike waves in siblings both were JME studies {Atakli 1999 and Akgun 2009}.
3.2.8.2 3Hz Spike Waves in Siblings
The pooled prevalence of 3Hz spike waves in asymptomatic siblings was 6.38% [n=4 studies, 95% CI: 3.38, 9.38] I2= 0% (Figure 12).
Four studies reported 3Hz spike waves; two JME studies {Atakli 199 and Wandschneider 2010}, one CAE study {Doose 1973} and one RE study {Bali 2007}.
3.2.8.3 Centrotemporal Waves in Siblings
The pooled prevalence of centrotemporal waves in asymptomatic siblings was 23.06% [n=3 studies, 95% CI: 3.26, 42.87] I2= 75.68% (Figure 13).
Three studies reported CTS in asymptomatic siblings, one JME study {Atakli 1999}, and two RE studies {Verrotti 2013 and Bali 2007}.
92 Figure 11: Prevalence of Polyspike Waves in Asymptomatic Siblings
This figure represents siblings-subgroup analysis of prevalence of abnormal EEG in siblings by EEG wave type (polyspike waves). N: is the total number of asymptomatic siblings, and Events: are the number of siblings with EEG abnormal waves. (polyspike waves).
93
Figure 12: Prevalence of 3Hz Spikes Waves in Asymptomatic Siblings
This figure represents siblings-subgroup analysis of prevalence of abnormal EEG in siblings by EEG wave type (3Hz spike waves). N: is the total number of asymptomatic siblings, and Events: are the number of siblings with EEG abnormal waves. (3Hz spike waves).
94
Figure 13: Prevalence of Centrotemporal Waves in Asymptomatic Siblings
This figure represents siblings-subgroup analysis of prevalence of abnormal EEG in siblings by EEG wave type (centrotemporal waves). N: is the total number of asymptomatic siblings, and Events: are the number of siblings with EEG abnormal waves. (centrotemporal waves).
95 3.3 Sensitivity Analysis Results
The sensitivity analysis included 13 studies {Verrotti 2013, Wandschneider 2010, Akgun 2009, Bali 2007, Jayalakshmi 2006, Serra 2001, Atakli 1999, Degen 1990(a), Degen 1990(b), Doose 1973, Tsuboi 1973, Kishimoto 1961 and Metrakos 1961}.
Three studies did not specify in their methods the status of included relatives as “asymptomatic”, however from the nature of these studies, it is most likely that the relatives described were asymptomatic {Tsuboi 1973, Kishimoto 1961 and Metrakos 1961}. Therefore, we have done the sensitivity analysis for the prevalence of all abnormal EEG in relatives. By including these studies we were able to analyze the previous prevalence in siblings and parents as well.
In this section the analysis will be done to know the pooled prevalence of abnormal EEG waves in idiopathic epilepsies (JME, CAE, and RE) all together. As well as the pooled prevalence of each type individually.
In addition, the analyses were done on siblings, the pooled prevalence of abnormal EEG was calculated for siblings as well as for each epilepsy type (JME, CAE and RE). Because additional studies were included in the sensitivity analysis, parents data were gathered and the pooled prevalence of abnormal EEG waves was calculated for parents as well.
3.3.1 Sensitivity Analysis of Abnormal EEG waves in JME, CAE and RE Relatives
The pooled prevalence of abnormal EEG in relatives was 41.54% [n=13 studies, 95% CI: 28.94, 54.13] I2=95.75% (Figure 14).
96 Figure 14: Prevalence of Abnormal Waves in Relatives (Studies n=13)
This figure represents sensitivity-analysis of prevalence of abnormal EEG in asymptomatic relatives. N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves. Degen 1990* is the CAE study {Degen 1990(a)}
97
3.3.2 Sensitivity Analysis of Abnormal EEG waves according to Epilepsy type in Relatives
In this section sensitivity analysis was done for each epilepsy type JME; CAE and RE and a pooled estimate was calculated.
3.3.2.1 Juvenile Myoclonic Epilepsy
The pooled prevalence of abnormal EEG in relatives of JME patients was 42.41% [n=5 studies, 95% CI: 17.92, 66.90] I2= 95.54% (Figure 15).
3.3.2.2 Rolandic Epilepsy
The pooled prevalence of abnormal EEG in relatives of RE patients was 33.30% [n=4 studies, 95% CI: 24.79, 41.80] I2= 31.72% (Figure 15).
3.3.2.3 Childhood Absence Epilepsy (CAE)
The pooled prevalence of abnormal EEG in relatives of CAE patients was 38.43% [n=3 studies, 95% CI: 10.55, 66.32] I2=97.91% (Figure 15).
98 Figure 15: Prevalence of Abnormal Waves in Relatives by Epilepsy Type (Studies n=13)
This figure represents sensitivity-analysis of prevalence of abnormal EEG in asymptomatic relatives grouped by epilepsy type; rolandic epilepsy, childhood absence epilepsy and juvenile myoclonic epilepsy. N: is the total number of asymptomatic relatives, and Events: are the number of relatives with EEG abnormal waves. Degen 1990* is the CAE study {Degen 1990(a)}
99
3.3.3 Sensitivity Analysis of Abnormal EEG in Siblings
In this section the analysis was done on siblings, the pooled prevalence of abnormal EEG in siblings was calculated from 11 included studies.
The pooled prevalence of abnormal EEG in siblings was 43% [n=11 studies, 95% CI: 32.05, 53.87] I2= 89% (Figure 16).
Figure 16: Prevalence of Abnormal Waves in Siblings (With Metrakos and Tsuboi)
This figure represents siblings sensitivity-analysis of prevalence of abnormal EEG in asymptomatic siblings. N: is the total number of asymptomatic siblings, and Events: are the number of siblings with EEG abnormal waves. Degen 1990* is the CAE study {Degen 1990(a)}
100
3.3.4 Sensitivity Analysis by Epilepsy Type in Siblings
Siblings data were obtained and grouped according to their epilepsy type into JME; RE and CAE. The pooled prevalence of abnormal EEG in siblings was calculated.
3.3.4.1 Juvenile Myoclonic Epilepsy
The pooled prevalence of abnormal EEG in siblings of JME patients was 43.66% [n=4 studies, 95% CI: 20.20, 67.87] I2= 90.89% (Figure 17).
3.3.4.2 Rolandic Epilepsy
The pooled prevalence of abnormal EEG in siblings of RE patients was 36.4% [n=4 studies, 95% CI: 28.25, 44.56] I2=0% (Figure 17).
3.3.4.3 Childhood Absence Epilepsy
The pooled prevalence of abnormal EEG in siblings of CAE patients was 46.4 [n=3 studies, 95% CI: 20.65, 72.17] I2=96.91% (Figure 17).
101 Figure 17: Prevalence of Abnormal Waves in Siblings by Epilepsy Type (With Metrakos and Tsuboi)
This figure represents sensitivity-analysis of prevalence of abnormal EEG in asymptomatic siblings grouped bye epilepsy type, rolandic epilepsy, childhood absence epilepsy and juvenile myoclonic epilepsy. N: is the total number of asymptomatic siblings, and Events: are the number of siblings with EEG abnormal waves. Degen 1990* is the CAE study {Degen 1990(a)}
102 3.3.5 Sensitivity Analysis of Abnormal EEG in Parents
In this section analysis on parents was possible because of the added studies in sensitivity analysis. Three studies included reported parents data, therefore the pooled prevalence of abnormal EEG waves in parents was calculated.
The pooled prevalence of abnormal EEG waves in parents of idiopathic epilepsy patients was 30.47% [n=3 studies, 95% CI: 8.92, 52.01] I2= 95.81% (Figure 18).
Figure 18: Prevalcence of Abnormal EEG in Parents (With Metrakos and Tsuboi)
This figure represents parents sensitivity-analysis of prevalence of abnormal EEG in parents. N: is the total number of parents, and Events: are the number of parents with EEG abnormal waves .
103 3.4 Comparison Between Meta-analysis and Sensitivity Analysis Results
The following table shows a comparison between our meta-analysis vs. sensitivity analysis results, comparisons of abnormal waves in relatives by epilepsy type (Table 15) and by EEG abnormal waves (Table 16).
The meta-analysis results yielded some heterogeneity. It was present in the prevalence of abnormal EEG in all relatives studies I2=88.35% which represent substantial heterogeneity. In the prevalence of abnormal EEG in the JME studies there were 50% heterogeneity, which may represent moderate heterogeneity. While in the RE studies the I2=31.72% which might not be important {Higgins 2002}. In the other hand, in the CAE studies there were considerable heterogeneity I2=97.47% which makes the results unreliable and one must interpret these results with caution, the reason behind this high heterogeneity is due to the small number of studies reporting asymptomatic relatives of CAE patients (n=2), in addition these two studies differ in the methods used in EEG recording, both clinical and methodological variability contributed to heterogeneity {Doose 1990(a), Degen 1973} (Table 15).
This heterogeneity was reduced when we performed subgroup analysis, by grouping siblings only, the data had less heterogeneity, even though the prevalence of abnormal EEG in siblings combined had an I2=80.42% which represents substantial heterogeneity; when grouping the siblings into JME only and RE only studies (individually) heterogeneity was reduced to 0%. However, for the CAE studies the heterogeneity remained high I2=97.47% for the same reason mentioned above (Table 15).
In addition there were no heterogeneity I2=0% in the meta-analysis of polyspike, 3Hz and Theta waves studies. While a higher heterogeneity was observed in CTS waves studies I2=75.68% which may represent substantial heterogeneity. In addition, PPR/PCR also had high heterogeneity I2=79.9%. Interpreting these results
104 should be considered with caution and further studies are needed to conclude mode of inheritance for these waves (Table 16).
Our sensitivity analysis results yielded higher heterogeneity compared to meta- analysis results (Table 15 and 16). The reasons behind that rely on the wider population included symptomatic vs. asymptomatic relatives and first vs. second degrees relatives. In addition to the different methodological approaches used for EEG recording, and the quality of conducting these studies. Further studies on the frequency of abnormal EEG in asymptomatic relatives are needed to better understand the inheritance pattern.
105
Table 15: Comparison Between Meta-analysis and Sensitivity-analysis Results [by Epilepsy Type]
Meta-analysis Sensitivity-analysis Relatives- 31.53% 41.54% abnormal EEG [n= 10 studies, 95% CI: 20.89, 42.18] [n=13 studies, 95% CI: 28.94, 54.13] I2=88.35% I2=95.75% JME (relatives) 21.10% 42.41% [n= 4 studies, 95% CI: 11.72-30.49] [n=5 studies, 95% CI: 17.92, 66.90] I2=53.75% I2= 95.54% RE (relatives) 33.30% 33.30% [n=4 studies, 95% CI: 24.79, 41.80] [n=4 studies, 95% CI: 24.79, 41.80] I2=31.72% I2= 31.72% CAE (relatives) 41.82% 38.43% [n=2 studies, 95% CI: -3.88-87.51] [n=3 studies, 95% CI: 10.55, 66.32] I2=97.47% I2=97.91% Siblings- 35.82% 42.96% abnormal EEG [n=9 studies, 95% CI: 25.19, 46.46] [n=11 studies, 95% CI: 32.05, 53.87] I2= 80.42% I2= 89.04% JME (siblings) 26.57% 43.66% [n=3 studies, 95% CI: 17.35, 35.80] [n=4 studies, 95% CI: 20.20, 67.87] I2=0% I2= 90.89% RE (siblings) 36.40% 36.40% [n=4 studies, 95% CI: 28.25, 44.56] [n=4 studies, 95% CI: 28.25, 44.56] I2= 0% I2=0% CAE (siblings) 41.82% 46.41% [n=2 studies, 95% CI: -3.88, 87.51] [n=3 studies, 95% CI: 20.65, 72.17] I2=97.47% I2=96.91% Parents- N/A 30.47% abnormal EEG [n=3 studies, 95% CI: 8.92, 52.01] I2= 95.81% JME: Juvenile Myoclonic Epilepsy, RE: Rolandic Epilepsy, CAE: Childhood Absence Epilepsy. N/A: Not Applicable.
106 Table 16: Comparison Between Meta-analysis and Sensitivity-analysis Results [by abnormal EEG Waves]
Meta-analysis Sensitivity-analysis Relatives: Polyspike 7.14% 7.14% [n=4 studies, 95% CI: 3.25, 11.02] [n=4 studies, 95% CI: 3.25, 11.02] I2=0% I2=0% 3Hz 6.38% 6.38% [n=4 studies, 95% CI: 3.83-9.38] [n=4 studies, 95% CI: 3.83-9.38] I2=0% I2=0% CTS 23.06% 23.06% [n=3 studies, 95% CI: 3.26, 42.87] [n=3 studies, 95% CI: 3.26, 42.87] I2=75.68% I2=75.68% Theta 8.95% 8.95% [n=3 studies, 95% CI: 5.43, 14,47] [n=3 studies, 95% CI: 5.43, 14,47] I2= 0% I2= 0% PPR/PCR 7.55% 7.55% [n=3 studies, 95% CI: 1.50, 13.59] [n=3 studies, 95% CI: 1.50, 13.59] I2=79.9% I2=79.9% Siblings: Polyspike 7.74% 7.74% [n=2 studies, 95% CI: 1.47, 14.01] [n=2 studies, 95% CI: 1.47, 14.01] I2=0% I2=0% 3HZ 6.38% 6.38% [n=4 studies, 95% CI: 3.38, 9.38] [n=4 studies, 95% CI: 3.38, 9.38] I2= 0% I2= 0% CTS 23.06% 23.06% [n=3 studies, 95% CI: 3.26, 42.87] [n=3 studies, 95% CI: 3.26, 42.87] I2= 75.68% I2= 75.68% CTS: Centroteporal waves, PPR: Photoparoxysmal Response, PCR: Photocolvulsive Response
107 3.5 Funnel Plot
The funnel plot was done on 10 studies included in our meta-analysis, to look at publication bias. From (Figure 19) the plot is symmetrical, with the studies of lower weight at the bottom of the funnel and studies with higher weights at the top of the funnel. One CAE study (Degen 1990(a)) has the highest prevalence of 72% [95% CI: 59.55, 84.45], this study used a different method in EEG recording, they administered 1mg/kg promazine-hydrocholoride for sleep induction, then waited for one hour for maximum effect and recorded waking EEG while the subject is sitting followed by sleep EEG. This 1-hour sedated recording may contribute for the high rate of EEG activation in this study. In the other hand, one JME study (Jayalakshmi 2006) had a prevalence of 13% [95% CI: 6.82, 19.04] included a wide age group consisting of mixed relatives; parents and siblings (Figure 19).
The pooled prevalence of abnormal EEG in asymptomatic relatives of idiopathic epilepsy patients from JME, CAE and RE was 31.53% [n= 10 studies, 95% CI: 20.89, 42.18] I2=88% (Figure 3).
108 Figure 19: Funnel Plot
This figure displays funnel plot, done on 10 studies included in meta-analysis. Vertical line is the standard error and the horizontal line is the proportion of EEG abnormal waves in asymptomatic relatives of idiopathic epilepsy patients. The plot is symmetrical with no obvious publication bias. Degen 1990* is the CAE study {Degen 1990(a)}
109 3.6 Methodological Quality
Quality assessment was done on all the studies included in our systematic review by using the Newcastle-Ottaw Scale (NOS) {Wells 2014} on the cohort studies (n=2) Appendix 4, and we used the modified Newcastle-Ottawa Scale (NOS) on the cross- sectional studies (n=13) {Fnais et al 2014} Appendix 3.
Out of 13 cross-sectional studies, 9 studies used a sample that was somewhat representative of the average cohort {Atakli 1999, Akgun 2009, Jayalakshmi 2006, Tsuboi 1973, Degen(a) 1990, Metrakos 1961, Bali 2007, Degen(b) 1990, Verrotti 2013}, and 2 studies used a selected group of cohort (e.g. only white individuals who spoke German from the same socioeconomic class of patients and siblings {Wandschneider 2010}, Kindergarten and school children {Doose 1973}). We scored 2 studies as not providing a description of the derivation of the cohort {Serra 2001, Kishimoto 1961}. For the ascertainment of exposure 4 studies used secured records {Atakli 1999, Akgun 2009, Metrakos 1961, Bali 2007}, only 1 study used written self report {Tsuboi 1973} and the remaining 8 studies did not describe the ascertainment of exposure {Jayalakshmi 2006, wandschneider 2010, Degen(a) 1990, Doose 1973, Degen(b) 1990, Verrotti 2013, Serra 2001, Kishimoto 1961}. For the comparability of cohorts on the basis of the design or analysis item 6 studies controlled for the important factors (e.g., age, gender) {Atakli, Akgun, Tsuboi, Wandschneider, Bali 2007, Kishimoto 1961}, and 2 studies controlled for other factors {Doose 1973, Metrakos 1961}, while the remaining 4 studies did not control for anything {Jayalakshmi 2006, Degen(a) 1990, Degen(b) 1990, Serra 2001}. For assessment of outcome criterion, 5 studies used independent blind assessment {Jayalakshmi 2006, Doose 1973, Metrakos 1961, Bali 2007, Verrotti 2013} and only 1 study used a record linkage/questionnaire {Tsuboi 1973} and 7 studies used self report {Atakli 1999, Akgun 2009, Wandschneider 2010, Degen(a) 1990, Degen(b) 1990, Serra 2001, Kishimoto 1961}. Lastly, 11 studies accounted for all eligible individuals who participated in the study {Atakli 1999, Akgun 2009, Jayalakshmi 2006, Tsuboi 1973, Wandschneider 2010, Degen(a) 1990, Doose 1973, Metrakos 1961, Bali 2007, Degen(b) 1990, Kishimoto 1961} only 1 study was rated as subjects lost to follow up were unlikely
110 to introduce bias, and only 1 study provided no statement about eligible individuals or participants for the adequacy of response rate criterion as shown in Appendix 3. For the results of the quality assessment for the 2 cohort studies, see Appendix 4. .
111
Chapter 4: Discussion, Conclusion and Future Directions
4.1 Discussion
This is the first systematic review and meta-analysis providing the prevalence of abnormal EEG in asymptomatic relatives of patients with idiopathic epilepsy mainly JME, CAE and RE. Fifteen studies were identified, including 3885 asymptomatic relatives. These relatives consisted of siblings, parents and offspring with an age ranging from 2-31 years and including both males and females.
In our review we have conducted both a meta-analysis and a sensitivity analysis. In our meta-analysis, only the studies that fulfilled our strict inclusion criteria were included; 10 studies fulfilled this criterion. On the other hand, three studies {Metrakos 1961, Kishimoto 1961, Tsuboi 1973} did not fulfill this criterion. They did not clearly specify in their methods whether the relatives were “asymptomatic” or not. The reasons behind that are because these studies were done in the 1960s and 1970s, both the way of methodology writing and EEG abnormalities definitions differ from recent studies. In addition to, different ways in conducting EEG recording. However from their description of the population as well as the studies discussion and results, it is most likely that those relatives were actually asymptomatic relatives. Studies back then defined some EEG finding as non-specifically abnormal, but are today considered as normal variants in the new definitions of EEG terminology. For example, it was not until the 1990s that theta waves were clearly defined as a normal drowsy pattern in non-epileptic individuals whereas older studies considered it an abnormal variant {Santamaria & Chippa 1987}. This leads us to think that perhaps these waves, defined today as being a normal variant and are overlooked by scientist studying EEG abnormalities, are key features for identifying affected traits in families.
112 For the above reasons, the three studies {Metrakos 1961, Kishimoto 1961, Tsuboi 1973}, were excluded from our meta-analysis but included in our sensitivity analysis. Excluding these studies could lead to missing EEG abnormal variables that could aid basic scientists and researchers studying genetic epilepsy.
The abnormal EEG recorded in all asymptomatic relatives was around 32% and 42%, results from both meta-analysis and sensitivity analysis respectively. These data suggests that the mode of inheritance tends to be more of a Mendelian inheritance, however, next steps should be for investigators to test inheritance patterns to identify “major” genes.
The data presented here may provide guidance for future development of genetic research by taking into consideration the prevalence of EEG abnormalities among siblings and parents, including polyspike, 3Hz spike, centrotemporal, theta waves, photoparoxysmal (PPR) and photoconvuslive (PCR) response. These abnormal waves are hallmark for certain epilepsy syndromes that aid in diagnosing them in the right clinical context. For example polyspike waves are characteristic for JME, 3Hz for CAE and centrotemporal for RE.
These EEG recordings work as an endophenotype, which are measures of endogenous characteristics of an individual that reflect genetic risk for a specific disorder or spectrum of disorders. They are present in individuals whose genetic makeup is similar to those with the manifest disorder even when the disorder is not present. Hence, studying the asymptomatic relatives that do not manifest the epileptic convulsions but have similar abnormal waves in their EEG recording as their epileptic sibling, parent or offspring indicates a similarity in the genetic makeup of those individuals. A potentially important benefit of endophenotypes is that they can express information about specific neurobiological and pathophysiological processes involved in idiopathic epilepsy disorders. Therefore, facilitating genetic research discoveries by identifying abnormal genes causing these excessive electrical discharges and seizures is required.
113 When looking at each epilepsy type individually, the following frequencies were recorded: the estimate of abnormal EEG in JME relatives was 21% and 42% from meta- analysis and sensitivity analysis respectively. There were 6 JME studies included. Two of them {Alonso 2005(a), Alonso 2005(b)}, were the only cohort studies of multi- generations first and second-degree relatives with a wide age group. For that reason, they were excluded from both our meta-analysis and sensitivity analysis.
From the JME studies, {Tsuboi 1973} had the highest prevalence of abnormal EEG to be present in the relatives with a prevalence of 72%. This high percentage is because he used a different classification system for interpreting EEG abnormalities. He classified the abnormal waves as specific (included spike and wave complex and or/spike) or unspecific. Moreover, since he did not clarify if the relatives were symptomatic or not, it might have been that symptomatic relatives could have been included which could have contributed to this high percentage in this study they concluded that the mode of inheritance of impulsive petit mal is most likely polygenic, not autosomal dominant, and the etiology of illness is more genetic, less environmental.
On the other hand, {Atakli 1999, Akgun 2009} reported similar results of abnormal EEG waves 27% and 33% respectively. Both studies included only age- matched asymptomatic siblings only. Whereas, {Jayalakshmi 2006} included parents and offspring and found that around 13% had abnormal EEG waves, his study included mixed relatives with wide age groups. Lastly, {Wandschnieder 2010}, who included siblings as well, only showed that 19% had abnormal EEG waves. The data resulted from our review suggest that these EEG findings are age-sensitive since the studies that included parents or offspring had a lower percentage than studies including siblings only. However, whether excluding the study with the highest variability from the analysis or not {Tsuboi 1973}, the pooled estimate of abnormal EEG waves in JME patients was 21% and 41%. Although this could indicate a Mendelian inheritance, further studies and analysis are needed to conclude type of inheritance.
114 In the CAE studies, the pooled estimate of abnormal EEG in asymptomatic relatives was around 42% and 38% from meta-analysis and sensitivity analysis respectively. Degen 1990(a), had the highest frequency of abnormal EEG in asymptomatic relatives 72%. This could be because of clinical variability in the studies. Degen emphasized the comparability between his study and the study done by, Metrakos 1961, who recorded the epileptic activity in 34% of siblings. Differences between the two studies were in the EEG recording method and the types of epilepsy syndrome included. Metrakos 1961, recorded EEGs of siblings of patients with primary absence, primary tonic clonic seizures, or both. While Degen 1990(a), recruited only subjects with idiopathic absences. Another reason was in the way they conducted the EEG recording. Degen 1990(a), administered 1mg/kg promazine-hydrocholoride for sleep induction, then waited for one hour for maximum effect and recorded waking EEG while the subject is sitting followed by sleep EEG. This 1-hour sedated recording may contribute for the high rate of EEG activation in this study. As previously suggested, these EEG findings are age-sensitive, {Degen 1990(a)} reported the activation rate occurring in siblings was observed between ages of 7 and 14 years, while {Metrakos 196}, observed the peak to be at age 4-16 years. Lastly, {Doose 1973}, included only siblings; the abnormal EEG frequency was around 28%, which is closer to Metrakos than Degen studies. From both our meta-analysis and sensitivity analysis; the pooled estimate of abnormal EEG waves in relatives of CAE patients were 42% and 38% respectively, because of the high heterogeneity yielded from combining these studies due to the different reasons mentioned above, interpretation of these results must be used with caution and further studies done on asymptomatic relatives are needed as well as further analysis are required for identification of inheritance pattern in CAE.
Regarding the studies of RE, the pooled estimate of abnormal EEG waves in asymptomatic relatives was 33%. Four studies included relatives of patients with RE. Relative’s age ranged from 2-16 years. All relatives were sibling except in {Serra 2001}, which included both parents and siblings. This may explain why they got a lower percentage since these specific EEG findings are age sensitive. They have found that 27% of asymptomatic relative had abnormal EEG. Correspondingly, {Verrotti 2013}, found
115 only 25% of siblings with abnormal EEG, they reported only the presence of CTS with no other abnormalities. While {Bali 2007}, found 43% of siblings to have abnormal EEG recording mainly CTS in addition to other waves such as 3Hz. Similarly {Degen 1990(b)}, mentioned that they had recorded spike wave complexes in 32% of siblings. These differences in the results were probably observed because abnormal waves could be easily activated by changes in vigilance.
Bali had concluded that CTS has an autosomal dominant inheritance because of their 50% segregation analysis. This may also have been influenced by well-known confounding factors such as the sleep stage of the EEG and age. Therefore, he excluded subjects with only awake recording. Which explains why the percentage reached up to 50%. In addition, he mentioned that EEG recordings that were done before the age of three or after the age of 16 have low sensitivity for detecting CTS even if subjects truly carry the CTS trait and suggested to exclude subjects out of that age range. Both {Bali 2007} and {Degen 1990(b)}, assumed transmission of the CTS as an autosomal dominant trait with high penetrance and strongly suggested a major genetic influence on the CTS component of RE. However, the genetics of RE versus the EEG hallmark of CTS trait has been intensely debated. It is clear that RE is not genetically identical to CTS. Further studies of linkage analysis for gene identification are recommended to know the mode of inheritance in RE.
In order to study the specific epileptic discharges of each epilepsy type, it is important to note that other EEG abnormalities such as theta waves, mark an existence correlation between the normal relative and the epileptic patient. These waves were observed more frequently in siblings of patients with idiopathic epilepsy. Degen 1990(a), reported that occipital-delta-theta waves were 82.2% in idiopathic compared to 63.6% in symptomatic absences and such difference was expected because occipital slow wave activity is usually combined with generalized 3-4Hz spike wave complexes which are more frequently observed in siblings of patients with idiopathic absences.
116 Despite considering theta waves as an abnormal wave in the earlier studies of epilepsy, the definition changed in the 1990s, by then theta waves were considered as part of the normal brain activity associated with sleep and drowsiness {Santamaria & Chippa 1987}. It is interesting to note that in our studies, theta waves were recorded by {Doose 1973}, {Jayalakshmi 2006} and {Akgun 2009}, and corresponds to 9% of total abnormal EEG waves in asymptomatic relatives.
Similarly, only small subsets of the overall study population 8% were the source of information regarding the photoparoxysmal response (PPR) and photoconvulsive response (PCR) as recorded by {Doose 1973}, {Jayalakshmi 2006} and {Wandschneider 2010}. Because of the small number of studies reporting PPR/PCR waves as well as theta waves in asymptomatic relatives, it is hard to study these waves. Therefore, we emphasize the importance of looking into these waves when studying the EEG recording of asymptomatic relatives.
It is important to note that including only siblings has increased the percentage of abnormal EEG in all epilepsy syndromes. This is because these EEG findings are age sensitive as observed by {Metrakos 1961} and {Degan 1991}. Metrakos found that siblings between the ages 4.5-16.5 year had abnormal EEG. Whereas, {Degan 1991}, found fewer epileptic discharges in younger (25%) than in older patients (28.6%).
Therefore we conducted a meta-analysis for studies of siblings and parents alone. The results of both meta-analysis and sensitivity analysis for siblings 36% and 42% had abnormal EEG recording respectively. Two studies, Serra and Bali reported that a few asymptomatic siblings developed the seizures during the course of study. This may contributed to the higher percentage they found.
From doing this study, one can find out the reasons for variability of the results. The first reason is due to the difference in types or degree of relatives as well as their ages, since the EEG trait is age sensitive. Another reason is because of differences in studies according to EEG recording duration, which ranged from 20-60 minutes, and in
117 the use of sleep deprivation, sleep recording and pharmacological sedation. Which likely contributed to the higher results found in a few studies. Other factors were noticed in most recent studies as they considered the so-called specific EEG finding- as the IGE trait carrier {Jayalakshmi 2006}, whereas older studies considered an abnormality whether it was specific or not as a potential IGE trait {Degan 1981}. Furthermore, over the last decade, the way of EEG reporting and the classification of EEG abnormalities have changed.
The data presented may provide guidance to interesting hypotheses about the inheritance of EEG abnormal waves as endophenotype. Since EEG traits seen in unaffected family members reflect the activity of the same gene that is involved in the expression of IGE, this would aid basic scientists and researchers trying to identify the genetic locus and the possible interacting loci, responsible for the epileptic discharging causing seizures.
Overall, our results support the following tentative conclusions. The EEG endophenotype for each of JME, CAE and RE is likely inherited in autosomal recessive fashion but, importantly, with heterogeneity, likely large heterogeneity, i.e. multiple separate genes leading, independently, to each of the endophenotypes. This is supported by the hovering of the frequencies for affected siblings around 25%, the expected number for recessive inheritance. Alternatively, autosomal dominant inheritance is also possible, because the numbers often approach 50%. That they are not more often than not at 50% could be due to the limitations inherent to a short EEG. Longer EEG’s in most cases may well have brought out the abnormalities in a larger percentage of siblings. Additionally, just as the epilepsy disappears or reduces in these diseases with age, it is possible that the EEG trait also disappears or reduces in parents. Finally, we encountered extensive findings of non-specific abnormalities, as described in the older literature, which today are called benign variants. Variants, however, these are, even if not abnormal. It is very possible that these ‘variants’ are indeed genetically driven and are part of the endophenotypic package. They would be wholly disregarded today, but were mentioned in the past and were in fact increased in siblings of affected patients. Our work strongly
118 suggests a big need to re-perform large EEG studies on siblings in the current genomic era and then correlate all EEG ‘variants’ with genomic ‘variants’, to potentially piece together the genomic underpinnings of brain wave irregularities that might be the building blocks of epilepsy.
4.2 Limitations
There are several limitations that must be considered when interpreting the results of our systematic review. One important limitation of the constituent studies pertains to the methods and tools used for data collection in older versus newer studies which had contributed to both clinical and methodological variability that were carefully investigated and explored.
In addition, meta-analysis cannot always overcome the limitations of individual trials by pooling the effect estimates to generate a single best estimate, the reason behind that is because the original studies could be biased themselves, even if the rigorous meta- analytic methods used were perfect.
Usually Systematic Reviews can increase precision (reduce variability), but precision by itself does not eliminate bias in the original studies. The reasons for these discrepancies could vary, either due to differences in individual studies; for example differences in patient populations, differences were in including first and second degree relatives while other studies included siblings only. Other reasons could be due to difference in outcome definitions i.e {Kishimoto 1961}, {Metrakos 1961} and {Tsuboi 1973}, where older studies that defined abnormal waves differently from newer studies; for example {Metrakos 1961}, defined the abnormal waves as centrencephalic and categorized them into typical and atypical centrencephalic waves, whereas {Tsuboi 1973}, defined them as paroxysmal potentials (compromising specific and unspecific abnormalities). Another variability was in methodology i.e. {Alonso 2005(a)} and {Alonso 2005(b)} were cohort studies compared to the other cross sectional studies. The
119 challenge in identifying which result is correct, or even what standard to use to define correct, is still not clear.
It would not be surprising therefore, to find that the results of these studies were to some degree incompatible with one another, even when rigorous methodological and statistical measures were used. The existence of clinical heterogeneity would be expected to lead to at least some degree of statistical heterogeneity in the results Appendix 3 and Appendix 4. In various meta-analyses, however, statistical evidence for heterogeneity will be lacking and the test of heterogeneity will be non-significant. Yet this cannot be interpreted as evidence of homogeneity i.e. total consistency of the results of all the studies included.
To alleviate shortcomings related to the reliability of outcome data in our review, we have opted to report all idiopathic epilepsy studies with relatives included, only two studies did not mention the status of the relatives whether they were epileptic or not, however, from companion reports and the descriptions of their population, we could assume that they meant to include asymptomatic relatives of epileptic patients. Among them were; {Kishimoto 1961}, {Metrakos 1961} and {Tsuboi 1973}.
Drawing conclusions about the relative importance of any particular prevalence should be done with caution due to the possibility of being misled. Also, we have reported a sufficient level of detail about individual studies such that users are able to selectively draw on the evidence according to individual needs.
The question posed by our review has important implications for cultivating a deeper understanding of prevalence of EEG and the epileptic pattern in relatives. Taken together, our findings may have broad application to epileptologists, electrophysiologists, geneticists and basic scientists in the field of genetics and epilepsy in terms of research development and intervention design.
120 Although the evidence maybe of inadequate quality to draw conclusions about the relative importance of particular prevalence, it is important to bear in mind that if the goal is to guide scientists to find the best evidence and help them design better methods for segregation and linkage analysis or further complex approaches to study families with epilepsy, then such review is unobjectionable to adaptations as new research findings become available.
Therefore, it is vital to work with expert in the fields of Epilepsy and Genetics with clinical expertise dealing with similar populations i.e families with idiopathic epilepsy, in order to get a meaningful result that could benefit both researchers and patients for future genetic counseling, and better understanding of the true value of our final results.
4.3 Conclusion
Prevalence of abnormal EEG waves of asymptomatic relatives of our included idiopathic epilepsies was 31% and 41%. Further studies are needed and further analysis is required to confirm these results in order to know the mode of inheritance in asymptomatic relatives of JME, CAE and RE.
Looking at each epilepsy type individually, prevalence of these abnormal EEG waves in asymptomatic relatives of JME, RE and CAE patients were 21%, 33% and 42% respectively from our meta-analysis and 42%, 33% and 38% from our sensitivity analysis.
We caution that the reliability and utility of our findings is somewhat limited by the quality of individual studies as shown in Appendix 3 and 4. The results of our review suggest that in the non-epileptic relatives of JME, CAE and RE tend to follow a Mendelian type of inheritance. However, it is necessary to conduct further studies and further analysis to confirm our results. The next steps should be for investigators to test inheritance patters or identify major genes.
121
4.4 Future Direction
This review provides clinicians with more reliable estimates of epilepsy risk for relatives, particularly informing a meaningful discussion with parents who understandably are often shaken by a new diagnosis of epilepsy in their previously healthy child. Over the next 6 months, the findings of this review may be widely- discussed with neurologists to update them on the findings.
The certainty of significant proportions of siblings having abnormal EEG findings related to an age-dependent epilepsy raises the possibility of primary prophylaxis, preventing seizures from manifesting – treating the EEG itself though this is not one in current routine clinical practice. One may view these idiopathic epilepsies as relatively benign and so risk of anti-epileptic drugs outweighs any hypothetical benefit. However, over time, perhaps 5-10 years, further risk factors may be discovered that help better predict who amongst the abnormal EEG group will develop seizures, even refractory seizures.
Over the next 2 years, with the explosion of genetics research into idiopathic epilepsy, the relatively prevalence of abnormal EEG finding as endophenotypes of various epilepsy syndromes will help to encourage and refine gene discovery. Simplifying gene discovery to the relative fewer genes of EEG traits may be enough to gain significant headway regarding the enigma of genes underlying idiopathic epilepsy; this could be done by enriching discovery cohorts with relatives with positive abnormal EEGs.
Our work contributes to the findings of a phenotype-endophenotype-genotype correlation by doing a whole genome sequencing for the asymptomatic relatives who carry these EEG traits. Such work is already underway at The Hospital for Sick Children as prospective study. This review informs that research of the importance to obtain sleep recordings in age-matched siblings to maximize the sensitivity of the EEG screening
122 tests. Also, the prevalences in this review will help plan for the number of relatives that will need to be screened to obtain a significant number of positive studies.
The review highlights the ongoing importance of common procedures and nomenclature in EEG studies. Though drowsiness-related theta activity is considered normal and not clinically reported, there was a disproportionate number with theta slowing seen between symptomatic and asymptomatic family members, suggesting that it may be relevant. Theta waves should be looked into while reading EEG and other waves should be sorted when reading EEG, these small discharges could contribute to the discoveries of genetic abnormalities in relative.
A systematic review is a type of scientific research that provides the qualitative and/or quantitative summary of research evidence answering a specific clinical question. Like all types of research, systematic reviews and meta-analysis have both potential strengths and weaknesses. Even though researchers seek to achieve objectivity in developing scientific evidences, considerable subjective judgment is essential in producing systematic reviews. These judgments are relative to the relevance of studies, the quality of eligible studies, the approach to heterogeneity, the method to incorporate heterogeneity in the analysis as well as drawing unbiased conclusions. Meta-analysis that accompanies a systematic review can increase power and precision of estimate. They are considered useful and valuable scientific evidence if they were developed using rigorous and explicit methodology, and if their results and conclusions were unbiased and relevant to current practices. It is important to understand the fundamental principles of systematic reviews and meta-analysis, including the ability to apply critical appraisal not only to the methodologies of review articles, but also to the applicability of the results to particular patients.
123 Appendices
Appendix 1 Database: Ovid MEDLINE(R) <1946 to June Week 2 2013>, Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations
124 30 BCECTS.tw. 31 "temporal-central focal epileps$".mp. 32 (centralopathic adj epileps$).mp. 33 (centrotemporal adj epileps$).mp. 34 or/5-33 35 exp Electroencephalography/ 36 EEG.tw. 37 electroencephalogram?.tw. 38 or/35-37 39 34 and 38 40 exp Animals/ not (exp Animals/ and Humans/) 41 39 not 40
125 Appendix 2 Reviewer name: Title: First Author’s name: Country: Language: Year publication: Study period: Funding Yes No
Abstract Full-length article
Published Unpublished Personal communication
VERIFICATION OF STUDY ELIGIBILITY: PICOD
* Patients - Does the report include non-eplipteic/asymptomatic relatives of epileptic patients? Yes No Unclear * Patients - Does the report include relatives of patients with JME or CAE or Rolandic epilepsy? Yes No Unclear * Interventions -Does this report include the use of electroencephalogram? Yes No Unclear * Outcomes - Does this report assess EEG abnormal changes? Yes No Unclear Is it reporting polyspike wave/ 3Hz spike/ centrotemporal spikes changes? Yes No Unclear
Is it an observational study? Observational epidemiological study (i.e., case control, cohort, cross- sectional).
126 Yes No Unclear
Note: only if all the boxes were checked for “yes” or “unclear”, will studies be included for abstraction. If only one “no” box is checked, then the study will be excluded.
METHODS
RISK Of BIAS ASSESSMENT OF STUDIES For observational studies: NOS. See forms below.
PARTICIPANTS • Total number: • Number eligible: Number enrolled: • Number analyzed: Number followed: • Number completed study: • Setting: • Diagnostic Criteria: • Age: (mean) (range) • Age category Adult vs. Children • Sex: %male %female • Follow up:
Studies including asymptomatic relatives: Probands (N, age, % abnormality) Parent: (N, age, % abnormality) Father (N, age, % abnormality) Mother (N, age, % abnormality) Consanguinity Yes No Unclear Sibling: (N, age, % abnormality) Brother (N, age, % abnormality)
127 Sister (N, age, % abnormality) Offsbirng: (N, age, % abnormality) Son (N, age, % abnormality) Daughter (N, age, % abnormality) First-degree relatives (N, age, % abnormality) Grandmother (N, age, % abnormality) Grandfather (N, age, % abnormality) Aunts (N, age, % abnormality) Uncles (N, age, % abnormality) Second-degree relatives (N, age, % abnormality) Cousins (N, age, % abnormality) Others (N, age, % abnormality)
INCLUSION CRITERIA:
EXCLUSION CRITERIA:
INTERVENTION: EEG characteristics Settings Recording method At rest registration Hyperventilation Intermittent photic stimulation Sleep EEG interpretation
OUTCOMES: • Abnormal EEG in asymptomatic relatives • Polyspike waves in asymptomatic relatives • 3Hz spike waves in asymptomatic relatives
128 • Centrotemporal waves in asymptomatic relatives • Other waves
129 Appendix 3
Quality assessment (Cross-sectional studies)*
Authors Year Representativeness Ascertainment Comparability Assessment of Adequacy of of the exposed of exposure2 of cohorts on outcome4 response rate5 cohort1 the basis of the design or analysis3 Atakli 1999 B A A D A Akgun 2009 B A A D A Jayalakshmi 2006 B D C A A Tsuboi 1973 B C A B A Wandschneider 2010 C D A D A Degen(a) 1990 B D C D A Doose 1973 C D B A A Metrakos 1961 B A B A A Bali 2007 B A A A A Degen(b) 1990 B D C D A Verrotti 2013 B D A A B Serra 2001 D D C D D Kishimoto 1961 D D A D A The Newcastle of Ottawa scale for cross-sectional studies: 1. Representivness: A) truly representative, B) somewhat representative, C) selected group of users, D) no description of the derivation of the cohort 2. Ascertainment: A) secure record, B) structured interview, C) written self report, D) no description 3. Comparability: A) study controls for age or gender, B) study controls for any additional factor, C) no control 4. Assessment of outcome: A) independent blind assessment, B) record linkage, C) self report, D) no description. 5. Adequacy: A) Complete follow up - all subjects accounted for. B) Subjects lost to follow up unlikely to introduce bias - small number lost (<10%) and description of those lost. C) Large number lost (>10%) and no description of those lost. D) No statement.
130 Appendix 4
Quality assessment (Cohort studies)*
Authors Year Representativeness Selection of Ascertainment Demonstration Comparability Assessment Follow up7 Adequacy of the exposed the non- of exposure3 that outcome of cohorts on of outcome6 of response cohort1 exposed of interest was the basis of the rate8 cohort2 not present at design or start of study4 analysis5 Alonso(a) 2005 B A A A C A NR A Alonso(b) 2005 B A A A C A NR A
The Newcastle Ottawa Scale (NOS) for cohort studies. 1. Representivness: A) truly representative, B) somewhat representative, C) selected group of users, D) no description of the derivation of the cohort 2. Selection: A) drawn from the same community as exposed cohort, B) drawn from a different source, C) no description 3. Ascertainment of outcome: A) secure record, B) structured interview, C) written self report, D) no description 4. Demonstration: A) yes, B) no 5. Comparability: A) study controls for age or gender, B) study controls for any additional factor, C) no control 6. Assessment: A) independent blind assessment, B) record linkage, C) self report, D) no description. 7. Follow-up: A) yes, B) no 8. Adequacy: A) Complete follow up - all subjects accounted for. B) Subjects lost to follow up unlikely to introduce bias - small number lost (<10%) and description of those lost. C) Large number lost (>10%) and no description of those lost. D) No statement.
131 References Anderman, E. & Metrakos, J.D. (1969): EEG studies of relatives of probands with focal epilepsy who have been treated surgically. Epilepsia 10 (3), 415.
Avanzini G. Genetics of epilepsy and genetic epilepsies. John Libbey Eurotext; 2009.
Baier WK, Doose H. Interdependence of different genetic EEG patterns in siblings of epileptic patients. Electroencephalogr Clin Neurophysiol 1987, Jun;66(6):483-8.
Bancaud J, Colomb D, Dell MB. Les pointes rolandiques: Un symptôme EEG propre à l’enfant. Rev Neurol 1958;99:206-9.
Beck-Mannagetta G, Janz D. Syndrome-related genetics in generalized epilepsy. Epilepsy Res Suppl 1991;4:105-11.
Berg AT, Berkovic SF, Brodie MJ, Buchhalter J, Cross JH, Van Emde Boas W, et al. Revised terminology and concepts for organization of seizures and epilepsies: Report of the ILAE commission on classification and terminology, 2005--2009. Epilepsia 2010;51(4):676-85.
Berg AT, Millichap JJ. The 2010 revised classification of seizures and epilepsy. CONTINUUM: Lifelong Learning in Neurology 2013;19(3, Epilepsy):571-97.
Berger H. Über das elektrenkephalogramm des menschen. European Archives of Psychiatry and Clinical Neuroscience 1929;87(1):527-70.
Berkovic, S.F. & Scheffer, I.E. (1998): Febrile seizures: genetics and relationship to other epilepsy syndromes. Curr. Opom. Neurol. 11 (2), 129-134.
132 Bertram EH, Onat FY, Ozkara C, Moshé SL, Avanzini G. Workshop on idiopathic generalized epilepsies: Bridging basic science and clinical research (october 3-6, 2007; antalya, turkey). Epilepsia 2008, Nov;49(11):1969-72.
Booth A, Clarke M, Dooley G, Ghersi D, Moher D, Petticrew M, Stewart L. The nuts and bolts of PROSPERO: An international prospective register of systematic reviews. Syst Rev 2012;1:2.
Cavazzuti GB, Cappella L, Nalin A. Longitudinal study of epileptiform EEG patterns in normal children. Epilepsia 1980, Feb;21(1):43-55.
Chalmers I, Hedges LV, Cooper H. A brief history of research synthesis. Eval Health Prof 2002;25(1):12-37.
Cochrane handbook for systematic reviews of interventions 2011:672 Available from: http://rbdigital.oneclickdigital.com.
Cochrane handbook for systematic reviews of interventions 2011:672 Available from: http://rbdigital.oneclickdigital.com.
Cossette Pl, Liu L, Brisebois K, Donh H, Lortie A, Vanasse M, Saint-Hilaire JM, Carmant L, Verner A, Lu WY, Wang YT, Rouleau GA. Mutation of GABRA1 in an autosomal dominant form of juvenile myoclonic epilepsy. Nat Genet. 2002; 31 (2): 184- 9.
Degen R, Degen H-E, Roth CH. Some genetic aspects of idiopathic and symptomatic absence seizures: Waking and sleep eegs in siblings. Epilepsia 1990;31(6):784-94.
Degen Rl, Degen HE. Contribution to the genetics of rolandic epilepsy: waking and sleep EEGs in siblings. Epilepsy Res Suppl. 1992; 6: 49-52.
133 Delgado-Escueta AV. Advances in genetics of juvenile myoclonic epilepsies. Epilepsy Curr. 2007 May-Jun. 7(3): 61-7.
Dickersin K. How important is publication bias? A synthesis of available data. AIDS Educ Prev 1997, Feb;9(1 Suppl):15-21.
Doose H, Gerken H, Völzke E. Genetics of centrencephalic epilepsy in childhood. Epilepsia 1968, Jun;9(2):107-15.
Faure J, Loiseau P. Une corrélation clinique particulière des pointes-ondes rolandiques sans signification focale. Rev Neurol 1960;102:399-406.
Fnais N, Soobiah C, Chen MH, Lillie E, Perrier L, Tashkandi M, Straus SE, Mamdani M, Al-Omran M, Tricco AC. Harassment and discrimination in medical training: a systematic review and meta-analysis. Acad Med. 2014; 89(5):817-21.
Gibbs FA, Gibbs EL, Lennox WG. Electroencephalographic classification of epileptic patients and control subjects. Archives of Neurology and Psychiatry 1943;50(2):111.
Glass GV (1976). "Primary, secondary, and meta-analysis of research". Educational researcher, 5(10),3-8.
Gloor P. Hans Berger and the discovery of the electroencephalogram. Electroencephalogr Clin Neurophysiol. 1969: Suppl 28:1-36.
Gottesman II, Gould TD. The endophenotype concept in psychiatry: Etymology and strategic intentions. Am J Psychiatry 2003, Apr;160(4):636-45.
Hatala R, Keitz S, Wyer P, Guyatt G, Evidence-Based Medicine Teaching Tips Working Group. Tips for learners of evidence-based medicine: 4. Assessing heterogeneity of
134 primary studies in systematic reviews and whether to combine their results. CMAJ 2005, Mar 1;172(5):661-5.
Hedges LV, Vevea JL. Fixed and random effects model in meta-analysis. Psychological methods 1998 (3):486-504.
Heijbel J, Blom S, Rasmuson M. Benign epilepsy of childhood with centrotemporal EEG foci: a genetic study. Epilepsia. 1975; 16 (2): 285-93.
Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Statist. Med. 2002; 21:1539-1558.
Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta- analyses. BMJ 2003, Sep 6;327(7414):557-60.
Higgins JPT, Deeks JJ, Altman DG (editors). Chapter 16: Special topics in statistics. In: Higgins JPT, green S (editors). In: Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 (updated March 2011). The Cochrane Collaboration, 2011. Available from www.cochrane-handbook.org.
Higgins JPT, Green S, Cochrane Collaboration.. Cochrane handbook for systematic reviews of interventions. Chichester, England ; Hoboken, NJ: Wiley-Blackwell; 2008m.
Iacono WG, Malone SM. Developmental endophenotypes: Indexing genetic risk for substance abuse with the P300 brain event-related potential. Child Dev Perspect 2011, Dec 1;5(4):239-47.
Jabbari B, Russo MB, Russo ML. Electroencephalogram of asymptomatic adult subjects. Clin Neurophysiol 2000, Jan;111(1):102-5.
135 Jayalakshmi SS, Mohandas S, Sailaja S, Borgohain R. Clinical and electroencephalographic study of first-degree relatives and probands with juvenile myoclonic epilepsy. Seizure 2006, Apr;15(3):177-83.
John, Bernard; Kenneth R. Lewis. "Chromosome Variability and Geographic Distribution in Insects". Science. 1966; doi:10.1126/science.152.3723.711.
Katrak P, Bialocerkowski AE, Massy-Westropp N, Kumar VSS, Grimmer KA. A systematic review of the content of critical appraisal tools. BMC Medical Research Methodology 2004, Sep;4(1):22.
Lefebvre CMEGJ. Chapter 6: Searching for studies. In: Higgins JPT, green S (editors). In: Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 (updated March 2011).The Cochrane Collaboration, 2011. Available from www.cochrane- handbook.org. . ; 2011r.
Lennox WG. The heredity of epilepsy as told by relatives and twins. J Am Med Assoc 1951;146(6):529-36.
LeTourneau DJ, Merren MD. Experience with electroencephalography in student naval aviation personnel, 1961-1971: A preliminary report. Aerosp Med 1973, Nov;44(11):1302-4.
Matthes A, Weber H. [Clinical and electroencephalographic family studies on pyknolepsy]. Dtsch Med Wochenschr 1968;93(10):429.
McGowan J, Sampson M, Lefebvre C. An evidence based checklist for the peer review of electronic search strategies (PRESS EBC). Evidence Based Library and Information Practice 2010;5(1):149-54.
136 McKenzie JE, Salanti G, Lewis SC, Altman DG. Meta-analysis and the cochrane collaboration: 20 years of the cochrane statistical methods group. Syst Rev 2013;2:80.
Metrakos K, Metrakos JD. Is the centrencephalic EEG inherited as a dominant? Electroencephalogr Clin Neurophysiol 1961, Apr;13:289.
Michael Borenstein, L. V. Hedges, J. P. T. Higgins and H. R. Rothstein (2009).
Introduction to Meta-Analysis. John Wiley & Sons, Ltd. 2009. ISBN: 978-0-470-05724-7
Moher D, Jadad AR, Klassen TP. Guides for reading and interpreting systematic reviews: III. How did the authors synthesize the data and make their conclusions? Arch Pediatr Adolesc Med 1998, Sep;152(9):915-20.
Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Ann Intern Med 2009;151(4):264-9.
Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev 2015;4:1.
Mulrow CD, Cook D. Systematic reviews : Synthesis of best evidence for health care decisions. illustrated ed. Philadelphia, Pa.: ACP Press; 1998r.
Neubauer BA. The genetics of rolandic epilepsy. Epileptic Disord. 2000; 2 Suppl, 1:S67- 8.
Niedermeyer E. EEG and the differential diagnosis of common generalized (centrencephalic) epilepsy. Electroencephalogr Clin Neurophysiol 1969, Jan;26(1):120.
137 O'Connor P. Analysis of 500 routine eegs of RAF aircrew cadets. Electroencephalogr Clin Neurophysiol 1964;17:341.
Panayiotopoulos CP. A clinical guide to epileptic syndromes and their treatment 2010:578.
Penfield W, Jasper H. Epilepsy and the functional anatomy of the human brain. Southern Medical Journal 1954;47(7):704.
Penfield, W. (1950): Epileptic automatism and centrencephalic integrating system. Proc. ARNMD 30, 513-528.
Reade MC, Delaney A, Bailey MJ, Angus DC. Bench-to-bedside review: Avoiding pitfalls in critical care meta-analysis--funnel plots, risk estimates, types of heterogeneity, baseline risk and the ecologic fallacy. Critical Care 2008;12(4):220.
Rogawski MA, Löscher W. The neurobiology of antiepileptic drugs for the treatment of nonepileptic conditions. Nat Med 2004, Jul;10(7):685-92.
Santamaria J, Chippa KH. The EEG of drowsiness in normal adults. Journal of Clinical neurophysiology 1987; 4(4):327-82.
Schell LC, Rathe JR. Meta-analysis: a tool for medical and scientific discoveries. Bull Med Libr Assoc 1992; 80(3):219-222.
Smith SJ. EEG in the diagnosis, classification, and management of patients with epilepsy. J Neurol Neurosurg Psychiatry 2005, Jun;76 Suppl 2:ii2-7.
Sterne JA, Egger M, Smith GD. Systematic reviews in health care: Investigating and dealing with publication and other biases in meta-analysis. BMJ 2001, Jul 14;323(7304):101-5.
138
Strachan T, Read AP, Strachan THMG3. Hum mol genet. New York: Garland Science; 2011f.
Wells GA, Shea B, O’Connell D, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analysis. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 2014.
Thomas RH, Chung S, Hamandi K, Rees MI, Kerr MP. Translation of genetic findings to clinical practice in juvenile myoclonic epilepsy. Epilepsy & Behavior 2012.
Thompson SG, Sharp SJ. Explaining heterogeneity in meta-analysis: A comparison of methods. Stat Med 1999, Oct 30;18(20):2693-708.
Thompson SG. Why sources of heterogeneity in meta-analysis should be investigated. BMJ 1994, Nov 19;309(6965):1351-5.
Tsuboi T, Christian W. On the genetics of the primary generalized epilepsy with sporadic myoclonias of impulsive petit mal type. Humangenetik 1973;19(2):155-82.
Valdamudi L, Kjeldsen MJ, Corey LA, Solass MH, Friis ML, Pellock JM, Nakken KO, Milne RL, Scheffer IE, Harvey AS, Hopper JL, Berkovic SF. Analyzing the etiology of benign rolandic epilepsy: a multicenter twin collaboration. Epilepsia. 2006; 57 (3): 550-5. Viechtbauer W. Conducting meta-analyses in R with the metafor package. Journal of Statistical Software 2010;36(3):1-48.
Winkelstein W. The first use of meta-analysis? Am J Epidemiol 1998;147(8):717.
Xu H, Platt RW, Luo ZC, Wei S, Fraser WD. Exploring heterogeneity in meta-analyses: Needs, resources and challenges. Paediatr Perinat Epidemiol 2008, Jan;22 Suppl 1:18-28.
139 References of Included Studies Akgun, Y., Soysal, A., Atakli, D., Yuksel, B., Dayan, C., & Arpaci, B. (2009). Cortical excitability in juvenile myoclonic epileptic patients and their asymptomatic siblings: A transcranial magnetic stimulation study. Seizure : The Journal of the British Epilepsy Association, 18(6), 387-91. doi:10.1016/j.seizure.2009.02.002
Alonso, M. E., Medina, M. T., Martínez-Juárez, I. E., Durón, R. M., Bailey, J. N., López- Ruiz, M., . . . Delgado-Escueta, A. V. 2005 (a). Familial juvenile myoclonic epilepsy. Advances in Neurology, 95, 227-43.
Alonso, M. E., Medina, M. T., Martínez-Juárez, I. E., Durón, R. M., Bailey, J. N., López- Ruiz, M., . . . Delgado-Escueta, A. V. 2005 (b). Familial juvenile myoclonic epilepsy. Advances in Neurology, 95, 227-43.
Atakli, D., Soysal, A., Atay, T., Altintas, H., Arpaci, B., & Baybas, S. (1999). Somatosensory evoked potentials and EEG findings in siblings of juvenile myoclonic epilepsy patients. Epileptic Disorders : International Epilepsy Journal with Videotape, 1(3), 173-7.
Bali, B., Kull, L. L., Strug, L. J., Clarke, T., Murphy, P. L., Akman, C. I., . . . Pal, D. K. (2007). Autosomal dominant inheritance of centrotemporal sharp waves in rolandic epilepsy families. Epilepsia, 48(12), 2266-72. doi:10.1111/j.1528-1167.2007.01221.x
Degen, R., Degen, H. E., & Roth, C. (1990) (a). Some genetic aspects of idiopathic and symptomatic absence seizures: Waking and sleep eegs in siblings. Epilepsia, 31(6), 784- 94.
Degen, R., & Degen, H. E. (1990) (b). Some genetic aspects of rolandic epilepsy: Waking and sleep eegs in siblings. Epilepsia, 31(6), 795-801.
140 Doose, H., Gerken, H., Horstmann, T., & Völzke, E. (1973). Genetic factors in spike- wave absences. Epilepsia, 14(1), 57-75.
Jayalakshmi, S. S., Mohandas, S., Sailaja, S., & Borgohain, R. (2006). Clinical and electroencephalographic study of first-degree relatives and probands with juvenile myoclonic epilepsy. Seizure : The Journal of the British Epilepsy Association, 15(3), 177-83. doi:10.1016/j.seizure.2005.12.011
Kishimoto, K., Kurita, A., & Amano, S. (1961). A hereditary study on the electroencephalography on some endogenous nervous diseases. Nagoya Med J, 7, 61-5. Needham, W. E., Bray, P. F., Wiser, W. C., & Beck, E. C. (1969). Intelligence and EEG studies in families with idiopathic epilepsy. JAMA : The Journal of the American Medical Association, 207(8), 1497-501.
Metrakos K, Metrakos JD. Genetics of convulsive disorders. II. Genetic and electroencephalographic studies in centrencephalic epilepsy. Neurology 1961, Jun;11:474-83.
Serra, D., Congiu, R., Minafra, L., Murru, F., De, M. N., Cianchetti, C., & Pruna, D. (2001). EEG trait analysis in siblings of patients with benign rolandic epilepsy . Bollettino- Lega Italiana Contro L'Epilessia, 113-114, 267-268.
Tsuboi T, Christian W. On the genetics of the primary generalized epilepsy with sporadic myoclonias of impulsive petit mal type. Humangenetik 1973;19(2):155-82.
Verrotti, A., Matricardi, S., Di Giacomo, D. L., Rapino, D., Chiarelli, F., & Coppola, G. (2013). Neuropsychological impairment in children with rolandic epilepsy and in their siblings. Epilepsy & Behavior : E&B, 28(1), 108-12. doi:10.1016/j.yebeh.2013.04.005
141 Wandschneider, B., Kopp, U. A., Kliegel, M., Stephani, U., Kurlemann, G., Janz, D., & Schmitz, B. (2010). Prospective memory in patients with juvenile myoclonic epilepsy and their healthy siblings. Neurology, 75(24), 2161-7. doi:10.1212/WNL.0b013e318202010a
References of Excluded Studies Abdelkefi I.; Hizem Y.; Gargouri A.; Triki S.; Ben, Djebara M.; Gouider R. (2011). Familial form of juvenile myoclonic epilepsy. European Journal of Neurology. 2011; 18:188., 18, 188.
Adams R. D, S. M. Z. (1967). Epilepsy, physiopathological course in relation to age. Schweizerische Medizinische Wochenschrift, 97(51), 1707-1716.
Afawi, Z., Korczyn, A. D., & Berkovic, S. F. (2009). PO18-WE-04 neuroepidemiology and genetics of epilepsy among jews and arabs in israel. Journal of the Neurological Sciences, 285, S245-S245. doi:10.1016/S0022-510X(09)70933-5
Aicardi, J., Bancaud, J., Beaussart, M., Cohadon, F., Courjon, J., Favel, P., . . . Vercelletto, P. (1969). General conclusions concerning familial factors in epilepsy. Epilepsia, 10(1), 65-8.
Ajmone-Marsan, C. (1984). Electroencephalographic studies in seizure disorders: Additional considerations. Journal of Clinical Neurophysiology : Official Publication of the American Electroencephalographic Society, 1(2), 143-57.
Aktuelle. (n.d.). Specific aspects of epilepsy in childhood. Neurologie, 32(7), 3-5.
Alberti, G., De Toma, M., & Cottini, R. (1972). [Epilepsy in childhood]. Minerva Med, 63(40), 2277-9.
Altahan A.; Alblaihid H. (2010). Two larger saudi families with autosomal recessive juvenile myoclonic epilepsy (JME). European Journal of Neurology, 17, 184.
142
Amadian, M. G., Grabarova, M. I., & Kozhushko, I. F. (1976). [A clinical, électroéncephalographic and biochemical study of epileptic children and adolescents and their relatives]. Zhurnal Nevropatologii I Psikhiatrii Imeni S.S. Korsakova (Moscow, Russia : 1952), 76(3), 420-2.
Andermann, E. (1991). Genetic studies of epilepsy in montreal. Epilepsy Research. Supplement, 4, 129-37.
Andermann, E., & Matrakos, J. D. (1972). Proceedings: A multifactorial analysis of focal and generalized cortico-reticular (centrencephalic) epilepsy. Epilepsia, 13(2), 348-9.
Andermann, E., & Metrakos, J. D. (1969). EEG studies of relatives of probands with focal epilepsy who have been treated surgically. Epilepsia, 10(3), 415.
Anderson, V. E., & Hauser, W. A. (1985). The genetics of epilepsy. Prog Med Genet, 6, 9-52.
Anderson, V. E., Rich, S. S., Hauser, W. A., & Wilcox, K. J. (1991). Family studies of epilepsy. Epilepsy Research. Supplement, 4, 89-103.
Aparicio Meix, J. M. (1992). [Progressive myoclonic epilepsy in childhood and adolescence]. An Esp Pediatr, 37(1), 1-10.
Arcos-Burgos, M., Palacio, L. G., Sánchez, J. L., Jiménez, M. E., Mora, O., Zuluaga, L., . . . Jiménez, I. (1999). [Genetic anticipation in idiopathic epilepsies]. Revista De Neurologia, 29(7), 597-9.
De Assis, J. L., Juliao, A. F., & Russo, G. (1957). [Myoclonic epilepsy, clinical and electroencephalographic study]. Arquivos De Neuro-psiquiatria, 15(3), 215-22.
143
Badalin, L. O., Gorlina, I. S., Leĭbovich, F. A., Oradovskaia, I. V., & Iakovleva, L. F. (1970). [Clinico-genetic and electroencephalographic study of epilepsy in twins]. Zhurnal Nevropatologii I Psikhiatrii Imeni S.S. Korsakova (Moscow, Russia : 1952), 70(3), 329- 36.
Baier, W. K., & Doose, H. (1987). Interdependence of different genetic EEG patterns in siblings of epileptic patients. Electroencephalography and Clinical Neurophysiology, 66(6), 483-8.
Bailet, L. L., & Turk, W. R. (2000). The impact of childhood epilepsy on neurocognitive and behavioral performance: A prospective longitudinal study. Epilepsia, 41(4), 426-31.
Bancaud, J., & Sallou, C. (1969). "Familial" epilepsy and "tumoral" epilepsy. Epilepsia, 10(1), 83-6.
Barolin, G. S. (1969). Migraine families. Electroencephalography and Clinical Neurophysiology, 26(4), 444-5. Bate, L., & Gardiner, M. (1999). Genetics of inherited epilepsies. Epileptic Disorders : International Epilepsy Journal with Videotape, 1(1), 7-19.
Beaumanoir, A., Ballis, T., Varfis, G., & Ansari, K. (1974). Benign epilepsy of childhood with rolandic spikes. A clinical, electroencephalographic, and telencephalographic study. Epilepsia, 15(3), 301-15.
Beaussart, M., & Loiseau, P. (1969). Hereditary factors in a random population of 5200 epileptics. Epilepsia, 10(1), 55-63.
Bianchi A.; Tiezzi A. (1992). The study of the genetics of the EEG in families with epilepsy: Problems and limits. Bollettino - Lega Italiana Contro L'Epilessia, 79-80, 51- 53.
144
Bianchi A.; Tiezzi A.; Fani C. (1990a). EEG genetics in families with a proband with epilepsy. Bollettino - Lega Italiana Contro L'Epilessia, 70-71, 305-306.
Bianchi A.; Tiezzi A.; Fani C. (1990b). EEG genetics in families with a proband with epilepsy. Bollettino - Lega Italiana Contro L'Epilessia, 70-71, 305-306.
Bianchi A.; Tiezzi A.; Fani C. (1991). Some aspects of the EEG genetics in families with partial idiopathic epilepsy. Bollettino - Lega Italiana Contro L'Epilessia, 74, 245-247.
Binnie, C. D., de Silva, M., & Hurst, A. (1992). Rolandic spikes and cognitive function. Epilepsy Research. Supplement, 6, 71-3.
Blom, S., Heijbel, J., & Bergfors, . G. (1972). Benign epilepsy of children with centro- temporal EEG foci. Prevalence and follow-up study of 40 patients*. Epilepsia, 13(5), 609-619. doi:10.1111/j.1528-1157.1972.tb04396.x
Blume, W. T. (1978). Clinical and electroencephalographic correlates of the multiple independent spike foci pattern in children. Annals of Neurology, 4(6), 541-7. doi:10.1002/ana.410040611 Bouquet, F. (1970). [Petit mal epilepsy]. Riv Patol Nerv Ment, 91(2), 107-19.
Bourrous, M., Draiss, G., Amine, M., Assabane, A., & Bouskraoui, M. (2010). [Childhood epilepsy with centrotemporal spikes in marrakech]. Archives De Pédiatrie : Organe Officiel De La Sociéte Française De Pédiatrie, 17(9), 1359-60. doi:10.1016/j.arcped.2010.06.020
Bray, P. F. (1972). A unifying concept of idiopathic epilepsy. Monographs in Human Genetics, 6, 193.
145 Bray, P. F., & Wiser, W. C. (1965). The relation of focal to diffuse epileptiform EEG dischares in genetic epilepsy. Archives of Neurology, 13(3), 223-37. Bray, P. F., & Wiser, W. C. (1969a). A unifying concept of idiopathic epilepsy. Postgraduate Medicine, 46(1), 82-7.
Bray, P. F., & Wiser, W. C. (1969b). A unifying concept of idiopathic epilepsy. Postgraduate Medicine, 46(1), 82-7.
Brimani, D. (1976). [The epileptic heredity in several comitial children]. L'Encéphale, 2(2), 177-86. Bulteau C.; Aubourg P.; Badinand N.; Billard C.; Designolles L.; Fontan D.; Genton P.; Hirsch E.; Livet M. O.; Mancini J.; Moutard M. L.; Parain D.; Pedespan J. M.; Plouin P.; Revol M.; Dulac O. (1995). Genetics of absence epilepsies. Family classification . Epilepsies. 1995; 7(3):257-262., 7(3), 257-262.
Buoni, S., Grosso, S., Di Cosmo, G., Di Bartolo, R. M., Di Marco, V., & Fois, A. (1998). Segregation analysis in typical absence epilepsy. Journal of Child Neurology, 13(2), 89- 93.
Buti, D., Romano, G., Guarnieri, M., Rossi, L., & Lini, M. (1989). Electroclinical study of three families with high incidence of epilepsy. Bollettino - Lega Italiana Contro L'Epilessia, 66-67, 63-65.
Capovilla, G., Rubboli, G., Beccaria, F., Lorenzetti, M. E., Montagnini, A., Resi, C., . . . Tassinari, C. A. (2001). A clinical spectrum of the myoclonic manifestations associated with typical absences in childhood absence epilepsy. A video-polygraphic study. Epileptic Disorders : International Epilepsy Journal with Videotape, 3(2), 57-62.
Carignani, M., & Rosso, D. (1997). Clinical and EEG asymmetries in juvenile myoclonic epilepsy (JME). Epilepsia, 38(2), 258.
146 Casaubon, L., & Wennberg, R. (2006). Video-EEG recordings in idiopathic generalized epilepsy, including juvenile myoclonic epilepsy. Epilepsia, 47(3), 664. doi:10.1111/j.1528-1167.2006.00484_7.x
Cavazzuti, G. B., & Cappella, L. (1970). [Early petit mal epilepsy]. Riv Neurol, 40(4), 242-9.
Christian, W. (1975). [EEG in the diagnosis of epilepsy in adults]. Die Medizinische Welt, 26(11), 508-15.
Christiani, K. (1979). [Clinical and EEG studies in children of epileptics (author's transl)]. Fortschritte Der Neurologie, Psychiatrie, Und Ihrer Grenzgebiete, 47(5), 221-63.
Clarke, T., Baskurt, Z., Strug, L. J., & Pal, D. K. (2009). Evidence of shared genetic risk factors for migraine and rolandic epilepsy. Epilepsia, 50(11), 2428-33. doi:10.1111/j.1528-1167.2009.02240.x
Crews, J., & Sidell, A. D. (1973). The clinical significance of spike and wave abnormalities in the adult. Bulletin of the Los Angeles Neurological Societies, 38(2), 60- 8.
Da, Silva A.; Lacerda P.; Guedes L.; Lopes J.; Leal B.; E, Costa P.; Da, Silva B. (2009). Variation of JME family phenotype anticipated by previous EEG characterization: Clinical and genetic exploration. Epilepsia, 50(118).
Dalby, M. A. (1969). Epilepsy and 3 per second spike and wave rhythms. A clinical, electroencephalographic and prognostic analysis of 346 patients. Acta Neurologica Scandinavica, Suppl 40:3+.
Degen, R. (1969). [Electroencephalography of epileptic diseases in childhood]. Zeitschrift Für Ärztliche Fortbildung, 63(8), 432-8.
147
Degen, R., & Degen, H. E. (1993). [Genetic aspects of symptomatic epilepsy based on waking and sleep EEG recordings in siblings]. Der Nervenarzt, 64(8), 504-10.
Degen, R., Degen, H. E., & Hans, K. (1991). A contribution to the genetics of febrile seizures: Waking and sleep EEG in siblings. Epilepsia, 32(4), 515-22.
Degen, R., Degen, H. E., & Hansmeier, B. (1986). [Sleep EEG without or with sleep deprivation in the provocation of epileptic activity in patients with generalized tonic- clonic seizures]. Der Nervenarzt, 57(11), 662-6.
Degen R.; Arnold H.; Bruhn B. (1972). The genetics of infantile spasms. A clinical and electrocephalographic study of families. Schweizer Archiv Fur Neurologie, Neurochirurgie Und Psychiatrie. 1972; 110:189-203., 110, 189-203.
Delgado-Escueta, A. V., Bai, D., Bailey, J., Medina, M. T., Alonso, M. E., Morita, R., . . . Rubio-Donnadieu, F. (2002). [Juvenile myoclonic epilepsy in chromosome 6p12: Clinical and genetic advances]. Revista De Neurologia, 35(1), 82-6.
Delgado-Escueta, A. V., Greenberg, D. A., Treiman, L., Liu, A., Sparkes, R. S., Barbetti, A., . . . Terasaki, P. I. (1989). Mapping the gene for juvenile myoclonic epilepsy. Epilepsia, 30 Suppl 4, S8-18; discussion S24-7.
Delgado-Escueta, A. V., Greenberg, D. A., Weissbecker, K., Serratosa, J. M., Liu, A., Treiman, L. J., . . . Barbetti, A. (1991). The choice of epilepsy syndromes for genetic analysis. Epilepsy Research. Supplement, 4, 147-59.
DeMarco, P. (1986). Parietal epilepsy with evoked and spontaneous spikes: Report on siblings with possible genetic transmission. Clinical EEG (electroencephalography), 17(4), 159-61.
148 Doose, D. (1971). On the genetics of myoclonic astatic petit mal. Electroencephalography and Clinical Neurophysiology, 31, 1-8.
Doose, H. (1970). [Value of "centrocephalic" convulsibility in the pathogenesis of epilepsy]. Der Nervenarzt, 41(11), 540-5.
Doose, H. (1981). Genetic aspects of the epilepsies. Folia Psychiatrica Et Neurologica Japonica, 35(3), 231-42.
Doose, H. (1989). Symptomatology in children with focal sharp waves of genetic origin. European Journal of Pediatrics, 149(3), 210-5.
Doose, H. (1994). Absence epilepsy of early childhood--genetic aspects. European Journal of Pediatrics, 153(5), 372-7.
Doose, H., & Baier, W. K. (1991). A genetically determined basic mechanism in benign partial epilepsies and related non-convulsive conditions. Epilepsy Research. Supplement, 4, 113-8.
Doose, H., Castiglione, E., & Waltz, S. (1995). Parental generalized EEG alpha activity predisposes to spike wave discharges in offspring. Human Genetics, 96(6), 695-704.
Doose, H., Gerken, H., & Völzke, E. (1968). Genetics of centrencephalic epilepsy in childhood. Epilepsia, 9(2), 107-15.
Doose, H., Gerken, H., Hien-Völpel, K. F., & Völzke, E. (1969). Genetics of photosensitive epilepsy. Neuropädiatrie, 1(1), 56-73. doi:10.1055/s-0028-1091864
Doose, H., Gerken, H., Horstmann, T., & Völzke, E. (1973). Genetic factors in spike- wave absences. Epilepsia, 14(1), 57-75.
149 Doose, H., Gerken, H., Kiefer, R., & Völzke, E. (1977). Genetic factors in childhood epilepsy with focal sharp waves. II. EEG findings in patients and siblings. Neuropädiatrie, 8(1), 10-20. doi:10.1055/s-0028-1091500
Doose, H., Gerken, H., Petersen, C. E., & Völzke, E. (1967a). [Electroencephalographic studies on the genetics of spasmophilia of the centrencephalic type]. Die Medizinische Welt, 8, 417-21.
Doose, H., Gerken, H., Petersen, C. E., & Völzke, E. (1967b). [Electroencephalographic studies on the genetics of spasmophilia of the centrencephalic type]. Die Medizinische Welt, 8, 417-21.
Doose, H., Neubauer, B. A., & Petersen, B. (2000). The concept of hereditary impairment of brain maturation. Epileptic Disorders : International Epilepsy Journal with Videotape, 2 Suppl 1, S45-9.
Doose H.; Brigger-Heuer B.; Neubauer B. (1997). Children with focal sharp waves: Clinical and genetic aspects. Epilepsia. 1997; 38(7):788-796., 38(7), 788-796.
Doose H.; Dieterich E. (1985). Benign partial ('rolandic') epilepsy with centro-temporal sharp waves. Nervenheilkunde, 4(5), 252-255.
Doose H.; Gerken H. (1972). Genetics of primarily generalized epilepsies. Epilepsia, 13, 482-283.
Dowzenko, A., & Huber, Z. (1972). [Petit mal epilepsy]. Neurologia I Neurochirurgia Polska, 6(5), 665-71.
Eeg-Olofsson, O. (2010). Prevalence of epileptiform discharges in healthy children. Epilepsia, 51(11), 2357. doi:10.1111/j.1528-1167.2010.02762.x
150 Everett, K. V., Chioza, B., Aicardi, J., Aschauer, H., Brouwer, O., Callenbach, P., . . . Gardiner, M. (2007). Linkage and association analysis of CACNG3 in childhood absence epilepsy. Eur J Hum Genet, 15(4), 463-72. doi:10.1038/sj.ejhg.5201783
Fiedlerová, D., Grosmanová, A., & Chromová, L. (1983). [Comparison of clinical and electroencephalographic findings in absence in childhood]. Sborník Vědeckých Prací Lékařské Fakulty Karlovy Univerzity V Hradci Králové. Supplementum, 26(3), 175-82.
Fridman, B. O. (1962). [On the problem of some clinco-electroencephalographic indices characteristic of compensation processes in petit mal epilepsy in children]. Vopr Psikhiatr Nevropatol, 8, 50-62.
Friedlander, W. J. (1969). Epilepsy. Prog Neurol Psychiatry, 24, 203-40.
Gabova, A. V., Bosnyakova, D. Y., Bosnyakov, M. S., Shatskova, A. B., & Kuznetsova, G. D. (2004). The time-frequency structure of the spike-wave discharges in genetic absence epilepsy. Dokl Biol Sci, 396, 194-7.
Gastaut, H., Raybaud, C., & Gomez-Almanzar, M. (1983). [Efficacy of "clinical and electroencephalographic sorting" for the etiologic diagnosis of epilepsy]. J Neuroradiol, 10(2), 122-6.
Geets, W. (1955). [Evolutional aspects of petit mal epilepsy with spike-wave complex]. Acta Neurologica Et Psychiatrica Belgica, 55(9), 671-9. Geier, S. (1971). A comparative tele-eeg study of adolescent and adult epileptics. Epilepsia, 12(3), 215-23.
Gerken, H. (1970). [Genetics and clinical studies of photosensitivity]. Rev Chil Pediatr, 41(1), 187-93.
151 Gerken, H., & Doose, H. (1972). On the genetics of EEG anomalies in childhood. II. Occipital 2-4/s rhythms. [Abstract]N. Euro. Padiatrie, 3(4), 437-454.
Gerken, H., & Doose, H. (1973). On the genetics of eeg-anomalies in childhood 3. Spikes and waves. Neuropädiatrie, 4(1), 88-97. doi:10.1055/s-0028-1091730
Gerken, H., Doose, H., Völzke, E., & Schwartz, I. (1974). [Pathogenesis of focal epilepsy]. Monatsschr Kinderheilkd, 122(7), 672-3.
Gerken, H., Doose, H., Völzke, E., & Völz, C. (1969). [Electroencephalographic studies on the genetics of photosensitivity]. Monatsschr Kinderheilkd, 117(4), 191-3.
Gerken, H., Kiefer, R., Doose, H., & Völzke, E. (1977). Genetic factors in childhood epilepsy with focal sharp waves. I. Clinical data and familial morbidity for seizures. Neuropädiatrie, 8(1), 3-9. doi:10.1055/s-0028-1091499
Gerken H.; Doose H.; Volzke E. (1968). Electroencephalographic investigations on the genetics of childhood epilepsies. (Summary). Monatsschrift Fur Kinderheilkunde, 116(6), 381.
Gianturco, D. T., Wilson, W. P., & Harris, B. S. (1968). Interictal focal or lateralized discharges occurring in the electroencephalograms of patients suffering from centrencephalic epilepsy. Confinia Neurologica, 30(5), 368-74.
Gloor, P. (1980). [Basic and clinical electrophysiology of epilepsy]. Union Med Can, 109(7), 986-94.
Gorbunova, E. K. (1966). [Electroencephalographic and clinical study of a patient with myoclonic epilepsy]. Vrach Delo, 4, 125-6.
152 Gorlina, I. S. (1968). [Clinico-genetic study of familial epilepsy]. Voprosy Okhrany Materinstva I Detstva, 13(9), 27-32.
Grudzińska, B., Majchrzak, R., & Kazibutowska, Z. (1979). [EEG in offspring of epileptic mothers]. Neurologia I Neurochirurgia Polska, 13(6), 625-30.
Hajnsek, F., Dogan, S., & Sartorius, N. (1969). Frequency analysis of EEG in centrencephalic epilepsy using petersen's analyser and photic stimulation. Neuropsihijatrija, 17(34), 21-7.
Hall, J. G., & Preziosi, T. J. (1971). Familial myoclonic epilepsy. Birth Defects Orig Artic Ser, 7(1), 227.
Halliday, A. M. (1967). The electrophysiological study of myoclonus in man. Brain : A Journal of Neurology, 90(2), 241-84.
Harper, J. R. (1968). True myoclonic epilepsy in childhood. Archives of Disease in Childhood, 43(227), 28-35.
Hasaerts, R., & Titeca, J. (1958). [Electro-clinical correlates of spike-waves; findings in a case of petit mal & epilepsia minor continua with fuge & confusional episodes]. Acta Neurologica Et Psychiatrica Belgica, 58(2), 142-54.
Hauser, W. A., Annegers, J. F., & Anderson, V. E. (1983). Epidemiology and the genetics of epilepsy. Res Publ Assoc Res Nerv Ment Dis, 61, 267-94.
Iqbal, N., Caswell, H. L., Hare, D. J., Pilkington, O., Mercer, S., & Duncan, S. (2009). Neuropsychological profiles of patients with juvenile myoclonic epilepsy and their siblings: A preliminary controlled experimental video-eeg case series. Epilepsy & Behavior : E&B, 14(3), 516-21. doi:10.1016/j.yebeh.2008.12.025
153 Jain, S., Dixit, S. N., Andrews, P. I., Radtke, R., Maheshwari, M. C., & McNamara, J. O. (1996). Disease expression among probands with juvenile myoclonic epilepsy and their family members in two population groups. Journal of Epilepsy, 9(4), 259-267. doi:10.1016/S0896-6974(96)00040-0
Jain, S., Padma, M. V., & Maheshwari, M. C. (1997). Occurrence of only myoclonic jerks in juvenile myoclonic epilepsy. Acta Neurologica Scandinavica, 95(5), 263-7.
Jain, S., Padma, M. V., Puri, A., & Maheshwari, M. C. (1998). Juvenile myoclonic epilepsy: Disease expression among indian families. Acta Neurologica Scandinavica, 97(1), 1-7.
Jain, S., Tripathi, M., Srivastava, A. K., & Narula, A. (2003). Phenotypic analysis of juvenile myoclonic epilepsy in indian families. Acta Neurologica Scandinavica, 107(5), 356-62.
Karlov, V. A., Sumskiĭ, L. I., Kovalenko, G. A., & Urumova, L. T. (1982). [Clinico- electrophysiologic correlations in epilepsy with primarily generalized peak-wave phenomena on the EEG]. Zhurnal Nevropatologii I Psikhiatrii Imeni S.S. Korsakova (Moscow, Russia : 1952), 82(6), 10-4.
Kellaway, P. (2000). The electroencephalographic features of benign centrotemporal (rolandic) epilepsy of childhood. Epilepsia, 41(8), 1053-6.
Kenedi, I., Walsa, R., & Kenedi, P. (1969). [Electrocardiographic changes in epilepsy]. Acta Med Acad Sci Hung, 26(3), 245-53.
Kriston L. "Dealing with clinical heterogeneity in meta-analysis. Assumptions, methods, interpretation". Int J Methods Psychiatr Res 2013. 22 (1): 1–15.
154 Konishi, N., Kohka, T., Momotani, Y., Yasui, M., & Higashi, Y. (1980). Siblings with rolandic (centrotemporal) discharges in the eegs. Folia Psychiatrica Et Neurologica Japonica, 34(3), 351.
Konishi, T., Naganuma, Y., Hongo, K., Murakami, M., Yamatani, M., Okada, T., & Okuda, T. (1993). Long-Term follow-up of EEG foci in childhood partial epilepsy. Psychiatry and Clinical Neurosciences, 47(2), 325-326. doi:10.1111/j.1440- 1819.1993.tb02091.x
Koshino, Y., & Isaki, K. (1986). Familial occurrence of the mu rhythm. Clinical EEG (electroencephalography), 17(1), 44-50.
Kurokawa, T. (1996). Clinical and EEG findings and prognosis of seizure disorders in children. Epilepsia, 37 Suppl 3, 2-4.
Lansdell, H., & Mirsky, A. F. (1964). Attention in focal and centrencephalic elpilepsy. Exp Neurol, 9, 463-9.
Lassker G. (1972). Clinical significance of focal findings in the EEG in children with epilepsy. Kinderarztliche Praxis. 1972; 40(5):227-233., 40(5), 227-233.
Lee, W. L. (1994). Benign epilepsy of childhood with centrotemporal spikes. Singapore Medical Journal, 35(3), 241-2.
Loiseau, P., & Duché, B. (1992). Benign rolandic epilepsy. Advances in Neurology, 57, 411-7.
Majchrzak, R., Grudzińska, B., & Pierzchała, K. (1987). [Prospective EEG studies of offspring of fathers with epilepsy]. Neurologia I Neurochirurgia Polska, 21(4-5), 329-33.
155 Marini, C., Harvey, A. S., Pelekanos, J. T., & Berkovic, S. F. (2003). Epilepsy in offspring of whom both parents have idiopathic generalized epilepsy: Biparental inheritance. Epilepsia, 44(9), 1250-4.
Matthes, A., & Weber, H. (1968). [Clinical and electroencephalographic family studies on pyknolepsy]. Deutsche Medizinische Wochenschrift (1946), 93(10), 429-35. doi:10.1055/s-0028-1105082
Matthews, W. B. (1973). The clinical value of routine electroencephalography. Journal of the Royal College of Physicians of London, 7(3), 207-12.
Mehndiratta, M. M., Rao, K. B., Singh, S., Ganesh, S., & Khwaja, G. A. (2007). Genetic study of juvenile myoclonic epilepsy (JME) patients and their family members in a university hospital in north india. Neurol Asia, 12(Suppl 1), 105-6. Retrieved from Google Scholar.
Mempel', E. K. (1969). [Views of the french school on the question of so-called centrencephalic epilepsy]. Vopr Neirokhir, 33(2), 57-8.
Metrakos, J. D., & Metrakos, K. (1966). Childhood epilepsy of subcortical ("centrencephalic") origin. Some questions and answers for the pediatrician. Clinical Pediatrics, 5(9), 537-42.
Metrakos, K., & Metrakos, J. D. (1961). Is the centrencephalic EEG inherited as a dominant? Electroencephalography and Clinical Neurophysiology, 13, 289.
Meyer, J. G. (1973). [Inheritance of spike-wave complexes and febrile seizures in three generations]. Deutsche Medizinische Wochenschrift (1946), 98(37), 1717-22. doi:10.1055/s-0028-1107115
156 Millichap, J. G. (1969). Electroencephalography and other diagnostic procedures in epilepsy. Modern Treatment, 6(6), 1190-216.
Nashold, B. S., Stewart, B., & Wilson, W. P. (1972). Depth electrode studies in centrencephalic epilepsy. Confinia Neurologica, 34(1), 252-63.
Needham, W. E., Dustman, R. E., Bray, P. F., & Beck, E. C. (1971). Intelligence, EEG and visual evoked potentials in centrencephalic epilepsy. Electroencephalography and Clinical Neurophysiology, 30(1), 94.
Needham, W. E., Bray, P. F., Wiser, W. C., & Beck, E. C. (1969). Intelligence and EEG studies in families with idiopathic epilepsy. JAMA : The Journal of the American Medical Association, 207(8), 1497-501
Negoro, T., Watanabe, K., Maeda, N., Kito, M., Haga, Y., & Aso, K. (1992). Long-term clinicoelectroencephalographic evolution of childhood absence epilepsy. The Japanese Journal of Psychiatry and Neurology, 46(2), 287-91.
Neubauer, B. A. (2000). The genetics of rolandic epilepsy. Epileptic Disorders : International Epilepsy Journal with Videotape, 2 Suppl 1, S67-8.
Neubauer, B. A., Hahn, A., Stephani, U., & Doose, H. (2002). Clinical spectrum and genetics of rolandic epilepsy. Advances in Neurology, 89, 475-9.
Niedermeyer, E. (1968). [Diagnostic considerations apropos of so-called centrencephalic generalized epilepsy]. Rev Neurol (Paris), 118(6), 514-22.
Niedermeyer, E. (1969). EEG and the differential diagnosis of common generalized (centrencephalic) epilepsy. Electroencephalography and Clinical Neurophysiology, 26(1), 120.
157 Niedermeyer, E. (1973). Common generalized epilepsy. The so-called idiopathic or centrencephalic epilepsy. European Neurology, 9(3), 133-56.
Niedzielska, K., Kuran, W., Romaniak, A., Rzeski, M., Karliński, A., & Lecka, J. (1999). [Electroencephalographic studies of family members of patients with juvenile myoclonic epilepsy]. Neurologia I Neurochirurgia Polska, 33(2), 359-67.
Nishiura, N. (1966). A clinico-genetical and electroencephalographical study of epilepsy. Bulletin of the Osaka Medical School, 12(1), 59-82.
P, W. (n.d.). [Juvenile myoclonic epilepsy]. Zhurnal Nevrologii I Psikhiatrii Imeni S. S. Korsakova, 105(11), 63-64.
Patra K. P.; Lewis D. W. (2012). Focus on diagnosis: Electroencephalography: A primer. Pediatrics in Review, 33(5), 226-231.
Pedley, T. A. (1991). The use and role of EEG in the genetic analysis of epilepsy. Epilepsy Research. Supplement, 4, 31-44.
Refsum, S. (1974). [Genetic aspects of epilepsy]. Tidsskrift for Den Norske Lægeforening : Tidsskrift for Praktisk Medicin, Ny Række, 94(29), 1976-8.
Regesta G.; Tanganelli P. (1987). Sleep EEG recordings in siblings of patients affected with rolandic epilepsy. Rivista Di Neurobiologia, 16(3-4), 391-394.
Reisner, H., & Spunda, C. (1962). [The importance of electroence-phalography for evaluation of the state of health of possible descendants of epileptics]. Wiener Zeitschrift Für Nervenheilkunde Und Deren Grenzgebiete, 19, 35-43.
Richter, K. (1956). [EEG studies of relatives of idiopathic epilepsy patients]. Arch Psychiatr Nervenkr Z Gesamte Neurol Psychiatr, 194(5), 443-55.
158
Ritter, G., & Poser, S. (1977). [Genetic findings in epilepsy]. Der Internist, 18(2), 67-70.
Rodin, E., & Gonzalez, S. (1966). Hereditary components in epileptic patients. Electroencephalogram family studies. JAMA : The Journal of the American Medical Association, 198(3), 221-5.
Rodin, E. A. (1969). The value of EEG investigations among family members in neurological practice. Electroencephalography and Clinical Neurophysiology, 26(4), 444.
Rodin, E. A., & Whelan, J. L. (1960). Familial occurrence of focal temporal electroencephalographic abnormalities. Neurology, 10, 542-5.
Rowan, A. J., Heathfield, K. W., & Scott, D. F. (1970). Is reading epilepsy inherited? Journal of Neurology, Neurosurgery, and Psychiatry, 33(4), 476-8.
Sagild, J. C., & Alving, J. (1988). [Juvenile myoclonic epilepsy. Clinical and electroencephalographic findings and prognosis of seizures in 99 patients]. Ugeskrift for Laeger, 150(34), 2029-32.
Saito, F., Kaneko, S., & Fukushima, Y. (1991). EEG findings in offspring of epileptic mothers. The Japanese Journal of Psychiatry and Neurology, 45(2), 413-5.
Sakakihara, Y. (2002). [Bening epilepsy of childhood with centrotemporal spikes]. Ryoikibetsu Shokogun Shirizu, (37 Pt 6), 15-8.
Salvioli, G. P., & Scanabissi, E. (1966). [Epilepsy of a familial type. Clinical and electroencephalographic study]. La Clinica Pediatrica, 48(11), 493-511.
Serratosa, J. M. (1999). Idiopathic epilepsies with a complex mode of inheritance. Epilepsia, 40 Suppl 3, 12-6.
159
Sigidinenko, L. V., & Korchinskaia, E. I. (1989). [Comparative analysis of various clinico-electrophysiologic manifestations in patients with epilepsy and in their relatives]. Zhurnal Nevropatologii I Psikhiatrii Imeni S.S. Korsakova (Moscow, Russia : 1952), 89(6), 18-22.
Sobczyk, W., & Horyd, W. (1977). [Familial EEG abnormalities in children of epileptics]. Neurologia I Neurochirurgia Polska, 11(1), 109-16.
Takahashi, T., Niedermeyer, E., & Knott, J. R. (1965). (THE EEG IN OLDER AND YOUNGER ADULT GROUPS WITH CONVULSIVE DISORDER.). Epilepsia, 6, 24- 32.
Terzian, H., & Ferri, G. (1953). [Clinical and electroencephalographic comments on petit mal epilepsy; presentation of a litte known EEG picture]. Riv Neurol, 23(4), 457-66.
Truşcă, E. (1977). [Clinical and electroencephalographic study of a case of familial epilepsy]. Revista De Medicină Internă, Neurologie, Psihiatrie, Neurochirurgie, Dermato- venerologie. Neurologie, Psihiatrie, Neurochirurgie, 22(2), 93-7.
Tsuboi, T. (1980). Genetic aspects of epilepsy. Folia Psychiatrica Et Neurologica Japonica, 34(3), 215-25.
Tsuboi, T., & Christian, W. (1973). On the genetics of the primary generalized epilepsy with sporadic myoclonias of impulsive petit mal type. A clinical and electroencephalographic study of 399 probands. Humangenetik, 19(2), 155-82.
Tsuboi, T., & Endo, S. (1977). Incidence of seizures and EEG abnormalities among offspring of epileptic patients. Human Genetics, 36(2), 173-89.
160 Tudor, I., Calcaianu, G., & Serbanescu, T. (1965). [SPECIAL ELECTRO-CLINICAL ASPECTS OF PETIT-MAL EPILEPSY]. Studii Si Cercetări De Neurologie, 10, 125-34.
Usui N.; Kotagel P. (2006). Response: Video-EEG recordings in idiopathic generalized epilepsy, including juvenile myoclonic epilepsy 8]. Epilepsia. 2006; 47(3):664., 47(3), 664.
Vadlamudi, L., Kjeldsen, M. J., Corey, L. A., Solaas, M. H., Friis, M. L., Pellock, J. M., . . . Berkovic, S. F. (2006). Analyzing the etiology of benign rolandic epilepsy: A multicenter twin collaboration. Epilepsia, 47(3), 550-5. doi:10.1111/j.1528- 1167.2006.00466.x
Valatx, J. L. (1975). [Genetics of EEG, of certain forms of epilepsy, sleep and learning]. Revue D'électroencéphalographie Et De Neurophysiologie Clinique, 5(4), 319-29.
Vears, D. F., Tsai, M. H., Sadleir, L. G., Grinton, B. E., Lillywhite, L. M., Carney, P. W., . . . Scheffer, I. E. (2012). Clinical genetic studies in benign childhood epilepsy with centrotemporal spikes. Epilepsia, 53(2), 319-24. doi:10.1111/j.1528-1167.2011.03368.x
Vercelletto, P. (1955). [Electroencephalography of near relatives of epileptics]. Electroencephalography and Clinical Neurophysiology, 7(4), 585-96.
Voelz C.; Doose H.; Gerken H.; Volzke E. (1970). Genetics of myoclonic akinetic petit mal. Monatsschrift Fur Kinderheilkunde, 118, 404.
Vogel, F. (1966). [Of the genetic basis of fronto-precentral beta wave groups in human EEG]. Humangenetik, 2(3), 227-37.
Vogel, F. (1969). The EEG of genetically different types of inherited myoclonic epilepsy. Electroencephalography and Clinical Neurophysiology, 26(4), 444.
161 Vogel, V. (1962). Additional investigations on the genetics of the human low voltage EEG. Deutsche Zeitschrift Fur Nervenheilkunde, 18(2), 105-111.
Wawszczyk, A. (1985). [Clinical and electroencephalographic analysis of the mild form of epilepsy in childhood]. Wiad Lek, 38(11), 774-81.
Wege, H. W. (1975). [Possibilities of echoencephalography in epilepsy]. Wien Med Wochenschr, 125(22-24), 364-7.
Xie, X. K. (1986). [Pedigree EEG study on inheritance factors in epilepsy]. Zhonghua Shen Jing Jing Shen Ke Za Zhi = Chinese Journal of Neurology and Psychiatry, 19(4), 244-6.
Xie, X. K., Yang, J. H., & Shao, Z. W. (1988). An EEG study of 120 epileptic families. Chinese Medical Journal, 101(11), 859-60.
Kato, Y (1977). Clinical electroencephalographic studies on patients with abnormal EEG patterns occurring in the rolandic region. Journal of the Nagoya Medical Associatio, 100(1-2), 31-42.
Yamatogi, Y., Oka, E., Satoh, M., Kobayashi, K., Yoshinaga, H., & Ohtahara, S. (1993). A prospective follow-up of the offspring of epileptic patients. The Japanese Journal of Psychiatry and Neurology, 47(2), 309-11.
162