Common genetic variation and susceptibility to partial epilepsies: a genome-wide association study

Genome wide association study identifies variants in NBEA associated with migraine in bipolar disorder

BACKGROUND

Migraine is a common comorbidity among individuals with bipolar disorder, but the underlying mechanisms for this co-occurrence are poorly understood. The aim of this study was to investigate the genetic background of bipolar patients with and without migraine.

METHODS

We performed a genome-wide association analysis contrasting 460 bipolar migraneurs with 914 bipolar patients without migraine from the Bipolar Genome Study (BiGS).

RESULTS

We identified one genome-wide significant association between migraine in bipolar disorder patients and rs1160720, an intronic single nucleotide polymorphism (SNP) in the NBEA gene (P=2.97 × 10(-8), OR: 1.82, 95% CI: 1.47-2.25), although this was not replicated in a smaller sample of 289 migraine cases.

LIMITATIONS

Our study is based on self-reported migraine.

CONCLUSIONS

NBEA encodes neurobeachin, a scaffolding protein primarily expressed in the brain and involved in trafficking of vesicles containing neurotransmitter receptors. This locus has not previously been implicated in migraine per se. We found no evidence of association in data from the GWAS migraine meta-analysis consortium (n=118,710 participants) suggesting that the association might be specific to migraine co-morbid with bipolar disorder.

Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus

Gene-regulatory network analysis is a powerful approach to elucidate the molecular processes and pathways underlying complex disease. Here we employ systems genetics approaches to characterize the genetic regulation of pathophysiological pathways in human temporal lobe epilepsy (TLE). Using surgically acquired hippocampi from 129 TLE patients, we identify a gene-regulatory network genetically associated with epilepsy that contains a specialized, highly expressed transcriptional module encoding proconvulsive cytokines and Toll-like receptor signalling genes. RNA sequencing analysis in a mouse model of TLE using 100 epileptic and 100 control hippocampi shows the proconvulsive module is preserved across-species, specific to the epileptic hippocampus and upregulated in chronic epilepsy. In the TLE patients, we map the trans-acting genetic control of this proconvulsive module to Sestrin 3 (SESN3), and demonstrate that SESN3 positively regulates the module in macrophages, microglia and neurons. Morpholino-mediated Sesn3 knockdown in zebrafish confirms the regulation of the transcriptional module, and attenuates chemically induced behavioural seizures in vivo.

Pharmacogenetics of second-generation antipsychotics

This review considers pharmacogenetics of the so called 'second-generation' antipsychotics. Findings for polymorphisms replicating in more than one study are emphasized and compared and contrasted with larger-scale candidate gene studies and genome-wide association study analyses. Variants in three types of genes are discussed: pharmacokinetic genes associated with drug metabolism and disposition, pharmacodynamic genes encoding drug targets, and pharmacotypic genes impacting disease presentation and subtype. Among pharmacokinetic markers, CYP2D6 metabolizer phenotype has clear clinical significance, as it impacts dosing considerations for aripiprazole, iloperidone and risperidone, and variants of the ABCB1 gene hold promise as biomarkers for dosing for olanzapine and clozapine. Among pharmacodynamic variants, the TaqIA1 allele of the DRD2 gene, the DRD3 (Ser9Gly) polymorphism, and the HTR2C -759C/T polymorphism have emerged as potential biomarkers for response and/or side effects. However, large-scale candidate gene studies and genome-wide association studies indicate that pharmacotypic genes may ultimately prove to be the richest source of biomarkers for response and side effect profiles for second-generation antipsychotics.

Genome-wide association studies in neurology

Genome-wide association studies (GWAS) are a powerful tool for understanding the genetic underpinnings of human disease. In this article, we briefly review the role and findings of GWAS in common neurological diseases, including Stroke, Alzheimer's disease, Parkinson's disease, epilepsy, multiple sclerosis, migraine, amyotrophic lateral sclerosis, frontotemporal lobar degeneration, restless legs syndrome, intracranial aneurysm, human prion diseases and moyamoya disease. We then discuss the present and future implications of these findings with regards to disease prediction, uncovering basic biology, and the development of potential therapeutic agents.

The effect of genetic polymorphisms of cytochrome P450 CYP2C9, CYP2C19, and CYP2D6 on drug-resistant epilepsy in Turkish children

BACKGROUND AND OBJECTIVE

Despite the availability of several antiepileptic drugs, drug resistance remains one of the major challenges in epilepsy therapy. Genetic factors are known to play a significant role in the prognosis and treatment of epilepsy. The aim of this study was to determine the frequencies of alleles for CYP2C9, CYP2C19, and CYP2D6 genes in Turkish children with epilepsy, and to investigate the relationship between the genetic polymorphism of these genes with multiple drug resistance in epilepsy patients.

METHODS

We genotyped 132 epileptic patients (60 drug resistant and 72 drug responsive) and 55 healthy controls for six single nucleotide polymorphisms (SNPs) in CYP2C9, CYP2C19, and CYP2D6. Genotype, allele, and haplotype frequencies were compared between groups.

RESULTS

The frequencies of CYP2C9*3/*3 genotype and CYP2C9*3 allele, and the haplotype CCGG (CYP2C9*2 C>T, CYP2C9*3 A>C, and CYP2C19*2 G>A, CYP2C19* G>A) were significantly higher in drug-resistant versus -responsive patients.

CONCLUSION

Our results demonstrated the important role of the CYP2C9*3 allelic variant in preventing epilepsy patients from developing drug resistance. These data suggest that CYP2C9, CYP2C19, and CYP2D6 SNPs and haplotypes may affect the response to antiepileptic drugs.

Genetic determinants of common epilepsies: a meta-analysis of genome-wide association studies

Background

The epilepsies are a clinically heterogeneous group of neurological disorders. Despite strong evidence for heritability, genome-wide association studies have had little success in identification of risk loci associated with epilepsy, probably because of relatively small sample sizes and insufficient power. We aimed to identify risk loci through meta-analyses of genome-wide association studies for all epilepsy and the two largest clinical subtypes (genetic generalised epilepsy and focal epilepsy).

Methods

We combined genome-wide association data from 12 cohorts of individuals with epilepsy and controls from population-based datasets. Controls were ethnically matched with cases. We phenotyped individuals with epilepsy into categories of genetic generalised epilepsy, focal epilepsy, or unclassified epilepsy. After standardised filtering for quality control and imputation to account for different genotyping platforms across sites, investigators at each site conducted a linear mixed-model association analysis for each dataset. Combining summary statistics, we conducted fixed-effects meta-analyses of all epilepsy, focal epilepsy, and genetic generalised epilepsy. We set the genome-wide significance threshold at p<1·66 × 10⁻⁸.

Findings

We included 8696 cases and 26 157 controls in our analysis. Meta-analysis of the all-epilepsy cohort identified loci at 2q24.3 (p=8·71 × 10⁻¹⁰), implicating SCN1A, and at 4p15.1 (p=5·44 × 10⁻⁹), harbouring PCDH7, which encodes a protocadherin molecule not previously implicated in epilepsy. For the cohort of genetic generalised epilepsy, we noted a single signal at 2p16.1 (p=9·99 × 10⁻⁹), implicating VRK2 or FANCL. No single nucleotide polymorphism achieved genome-wide significance for focal epilepsy.

Interpretation

This meta-analysis describes a new locus not previously implicated in epilepsy and provides further evidence about the genetic architecture of these disorders, with the ultimate aim of assisting in disease classification and prognosis. The data suggest that specific loci can act pleiotropically raising risk for epilepsy broadly, or can have effects limited to a specific epilepsy subtype. Future genetic analyses might benefit from both lumping (ie, grouping of epilepsy types together) or splitting (ie, analysis of specific clinical subtypes).

Funding

International League Against Epilepsy and multiple governmental and philanthropic agencies.

Describing the genetic architecture of epilepsy through heritability analysis

Epilepsy is highly heritable, but its genetic architecture is poorly understood. Speed et al. estimate the number of susceptibility loci, show that common variants account for the majority of heritability, and demonstrate that epilepsy consists of genetically distinct subtypes. They conclude that gene-based prediction models may have clinical utility in first-seizure settings.

Epilepsy is a disease with substantial missing heritability; despite its high genetic component, genetic association studies have had limited success detecting common variants which influence susceptibility. In this paper, we reassess the role of common variants on epilepsy using extensions of heritability analysis. Our data set consists of 1258 UK patients with epilepsy, of which 958 have focal epilepsy, and 5129 population control subjects, with genotypes recorded for over 4 million common single nucleotide polymorphisms. Firstly, we show that on the liability scale, common variants collectively explain at least 26% (standard deviation 5%) of phenotypic variation for all epilepsy and 27% (standard deviation 5%) for focal epilepsy. Secondly we provide a new method for estimating the number of causal variants for complex traits; when applied to epilepsy, our most optimistic estimate suggests that at least 400 variants influence disease susceptibility, with potentially many thousands. Thirdly, we use bivariate analysis to assess how similar the genetic architecture of focal epilepsy is to that of non-focal epilepsy; we demonstrate both significant differences (P = 0.004) and significant similarities (P = 0.01) between the two subtypes, indicating that although the clinical definition of focal epilepsy does identify a genetically distinct epilepsy subtype, there is also scope to improve the classification of epilepsy by incorporating genotypic information. Lastly, we investigate the potential value in using genetic data to diagnose epilepsy following a single epileptic seizure; we find that a prediction model explaining 10% of phenotypic variation could have clinical utility for deciding which single-seizure individuals are likely to benefit from immediate anti-epileptic drug therapy.

Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia

The brain's default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging-genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases.

Gene-wide tagging study of the association between KCNT1 polymorphisms and the susceptibility and efficacy of genetic generalized epilepsy in Chinese population

AIMS

The causes of genetic generalized epilepsies (GGEs) are still uncertain now. Some studies found that the human potassium channel, subfamily T, member 1 (KCNT1) is the candidate gene causing malignant migrating partial seizures of infancy and autosomal dominant nocturnal frontal lobe epilepsy which are all rare genetic generalized epilepsies. The aims of this study were going to evaluate the association between KCNT1 common variations and the susceptibility and drug resistance of genetic generalized epilepsies in Chinese population.

METHODS

The allele-specific MALDI-TOF mass spectrometry method was used to assess 17 tagSNPs (tagged single-nucleotide polymorphisms) of KCNT1 in 284 healthy Chinese controls and 483 Chinese GGEs patients including 279 anti-epileptic drug-responsive patients and 204 drug-resistant patients.

RESULTS

Genotype distributions of all the selected tagSNPs were consistent with Hardy-Weinberg equilibrium in GGEs and healthy controls. None of the all 17 tagSNPs alleles were found to be related with the susceptibility and drug resistance of genetic generalized epilepsies. The frequencies of haplotype 5 and haplotype 1 were significantly lower in GGEs than that in healthy controls (2% vs. 4%, OR = 0.47 [0.27-0.94], P = 0.03) and obviously higher in drug-resistant patients than that in drug-response patients (6% vs. 3%, OR = 2.56 [1.23-5.35], P = 0.01). However, after the correction of multiple comparisons with Bonferroni's method, we found that the above two haplotypes were not associated with the susceptibility and drug resistance in GGEs and healthy controls.

CONCLUSION

This gene-wide tagging study revealed no association between KCNT1 17 common variations and susceptibility of GGEs or AEDs (anti-epileptic drugs) efficacy of genetic generalized epilepsies in Chinese population.

The potential role of CAMSAP1L1 in symptomatic epilepsy

In a recent genome-wide association study (GWAS) of symptomatic epilepsy in the Chinese population, the most significant single nucleotide polymorphism (SNP) allele was rs2292096 [G] (P=1.0×10(-8), odds ratio [OR]=0.63), in the CAMSAP1L1 gene (also known as CAMSAP2). Here, we report that rs2292096 genotypes tended to associate with expression of CAMSAP1L1 RNA in the temporal lobe (p=0.054) and hippocampus (p=0.20) of epilepsy surgery patients, with expression tending to increase with the G allele. CAMSAP1L1 and β-tubulin double immunofluorescence exhibited partial overlap. CAMSAP1L1 siRNA transfection of human SH-SY5Y neuroblastoma cells treated with or without retinoic acid reduced the CAMSAP1L1 protein level nearly 60% and stimulated neurite outgrowth, as measured by total length, number of processes and number of branches. Therefore, the rs2292096 G allele of CAMSAP1L1, which was associated with reduced risk of symptomatic epilepsy, tended to associate with increased expression of CAMSAP1L1, which represses neurite outgrowth. Greater neurite growth in response to brain insults might increase formation of ectopic neural circuits and thus the risk of epileptogenesis.

Epilepsy, hippocampal sclerosis and febrile seizures linked by common genetic variation around SCN1A

Epilepsy comprises several syndromes, amongst the most common being mesial temporal lobe epilepsy with hippocampal sclerosis. Seizures in mesial temporal lobe epilepsy with hippocampal sclerosis are typically drug-resistant, and mesial temporal lobe epilepsy with hippocampal sclerosis is frequently associated with important co-morbidities, mandating the search for better understanding and treatment. The cause of mesial temporal lobe epilepsy with hippocampal sclerosis is unknown, but there is an association with childhood febrile seizures. Several rarer epilepsies featuring febrile seizures are caused by mutations in SCN1A, which encodes a brain-expressed sodium channel subunit targeted by many anti-epileptic drugs. We undertook a genome-wide association study in 1018 people with mesial temporal lobe epilepsy with hippocampal sclerosis and 7552 control subjects, with validation in an independent sample set comprising 959 people with mesial temporal lobe epilepsy with hippocampal sclerosis and 3591 control subjects. To dissect out variants related to a history of febrile seizures, we tested cases with mesial temporal lobe epilepsy with hippocampal sclerosis with (overall n = 757) and without (overall n = 803) a history of febrile seizures. Meta-analysis revealed a genome-wide significant association for mesial temporal lobe epilepsy with hippocampal sclerosis with febrile seizures at the sodium channel gene cluster on chromosome 2q24.3 [rs7587026, within an intron of the SCN1A gene, P = 3.36 × 10(-9), odds ratio (A) = 1.42, 95% confidence interval: 1.26-1.59]. In a cohort of 172 individuals with febrile seizures, who did not develop epilepsy during prospective follow-up to age 13 years, and 6456 controls, no association was found for rs7587026 and febrile seizures. These findings suggest SCN1A involvement in a common epilepsy syndrome, give new direction to biological understanding of mesial temporal lobe epilepsy with hippocampal sclerosis with febrile seizures, and open avenues for investigation of prognostic factors and possible prevention of epilepsy in some children with febrile seizures.

Seizure predisposition after perinatal hypoxia: effects of subsequent age and of an epilepsy predisposing gene mutation

PURPOSE

There is a gap in our knowledge of the factors that modulate the predisposition to seizures following perinatal hypoxia. Herein, we investigate in a mouse model the effects of two distinct factors: developmental stage after the occurrence of the perinatal insult, and the presence of a seizure predisposing mutation.

METHODS

Effects of age: P6 (postnatal day 6) mouse pups were subjected to acute hypoxia down to 4% O2 over the course of 45 min. Seizure susceptibilities to flurothyl-induced seizures (single exposures) and to flurothyl kindling were determined at specific subsequent ages. Effects of mutation: Heterozygote mice, with deletion of one copy of the Kcn1a gene, subjected to P6 hypoxia were compared as adults to wild-type mice with respect to susceptibility to a single exposure to flurothyl and to the occurrence of spontaneous seizures as detected by hippocampal electroencephalography (EEG) and video recordings.

KEY FINDINGS

Effects of age: As compared to controls, wild-type mice exposed to P6 hypoxia had a shortened seizure latency in response to a single flurothyl exposure at P50, but not at P7 or P28 (p < 0.04). In addition, perinatal hypoxia at P6 enhanced the rate of development of flurothyl kindling performed at P28-38 (p < 0.03), but not at P7-17. Effects of mutation: Kcn1a heterozygous mice subjected to P6 hypoxia exhibited increased susceptibility to flurothyl-induced seizures at P50 as compared to Normoxia heterozygote littermates, and to wild-type Hypoxia and Normoxia mice. In addition, heterozygotes exposed to P6 hypoxia were the only group in which spontaneous seizures were detected during the period of long-term monitoring (p < 0.027 in all comparisons).

SIGNIFICANCE

Our data establish a mouse model of mild perinatal hypoxia in which we document the following: (1) the emergence, after a latent period, of increased susceptibility to flurothyl-induced seizures, and to flurothyl induced kindling; and (2) an additive effect of a gene mutation to the seizure predisposing consequences of perinatal hypoxia, thereby demonstrating that a modifier (or susceptibility) gene can exacerbate the long-term consequences of hypoxic injury.

Genetics of the epilepsies: where are we and where are we going?

PURPOSE OF REVIEW

We aim to review the most recent advances in the field of epilepsy genetics with particular focus on the progress in gene discovery in monogenic epilepsies, identification of risk genes in complex genetic epilepsies and recent findings in the field of epilepsy pharmacogenomics.

RECENT FINDINGS

During the last 12 months, the use of massive parallel sequencing technologies has allowed for the discovery of several genes for monogenic epilepsies. Most importantly, PRRT2 was identified as the long-sought gene for benign familial infantile seizures. Mutations in KCNT1 were found in two seemingly unrelated monogenic epilepsies including malignant migrating partial seizures of infancy and severe autosomal dominant nocturnal frontal lobe epilepsy. A genome-wide association study in idiopathic generalized epilepsy revealed the first common risk variants for human seizure disorders including variants in VRK2, PNPO and SCN1A. Furthermore, a landmark study provided evidence that screening for the HLA-B1502 variant may prevent carbamazepine CBZ-induced side effects in the Taiwanese population. Also, HLA-A3101 variants were identified as a risk factor for carbamazepine side effects in Europeans.

SUMMARY

Novel technologies and an unprecedented level of international collaboration have resulted in identification of novel genes for monogenic and complex genetic epilepsies as well as risk factors for side effects of antiepileptic drugs. This review provides an overview of the most relevant studies in the last year and highlights the future direction of the field.

De novo mutations in epileptic encephalopathies

Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown. Here we report a screen for de novo mutations in patients with two classical epileptic encephalopathies: infantile spasms (n = 149) and Lennox-Gastaut syndrome (n = 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the ∼4,000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 × 10(-3)). Among these are GABRB3, with de novo mutations in four patients, and ALG13, with the same de novo mutation in two patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P = 4.1 × 10(-10) and P = 7.8 × 10(-12), respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P < 10(-8)), as has been reported previously for autism spectrum disorders.

CYP3A5*3 and C3435T MDR1 polymorphisms in prognostication of drug-resistant epilepsy in children and adolescents

Drug-resistant epilepsies still remain one of the most profound problems of contemporary epileptology. Several mechanisms of drug resistance are possible; among them, genetic factors have a prominent place. Much importance is attached to genes, which encode enzymes that metabolize antiepileptic drugs CYP 3A, which belong to the family of cytochromes P450 and the genome of multidrug resistance, such as multidrug resistance 1 (MDR1) that expresses P-glycoprotein (P-gp), a drug transporter protein. The aim of the study was to assess the relation between polymorphism of gene CYP3A5 and polymorphism C3435T of MDR1 gene with the occurrence of focal, drug-resistant epilepsy in children and youths up to 18 years of age. The study comprised 85 patients, and their age range was from 33 months to 18 years of age, suffering from epilepsy, partly responding well to treatment, partly drug resistant. The polymorphism of both genes has been analysed using the PCR-RFLP method. The study failed to corroborate association between polymorphism CYP3A5∗3 and C3435T polymorphism in MDR1 gene and pharmacoresistant epilepsy. The results of our research do not confirm the prognostic value of the polymorphisms examined in the prognostication of drug resistance in epilepsies.

Genome wide association studies (GWAS) and common forms of human epilepsy

Several GWAS focused on common forms of epilepsy are underway. Currently, only one locus has been published that reached genome wide statistical significance. Two other loci that also reach genome wide statistical significance have been reported as preliminary data and are awaiting publication. Several additional loci identified in these studies fall just short of statistical significance, and it is hoped that future large scale meta-analyses will confirm these early findings and identify new loci that influence common forms of human epilepsy. Next generation DNA sequencing (NGS) studies are also underway and in the future will identify rare DNA variations of large effect that also contribute to the final epilepsy phenotypes under study. Finally, these studies have the potential to identify biomarkers of antiepileptic drug (AED) response as epilepsy patient GWAS and NGS data are stratified based on AED efficacy and tolerability.

The unexpected role of copy number variations in juvenile myoclonic epilepsy

Structural genomic variants or copy number variants (CNVs) comprise submicroscopic deletions and duplications of chromosomal material, including both rearrangements at genomic hotspots as well as duplications and deletions with unique breakpoints. Copy number variants have increasingly been recognized in the Idiopathic/Genetic Generalized Epilepsies (IGE/GGE) including juvenile myoclonic epilepsy (JME). Microdeletions at 15q13.3, 15q11.2, and 16p13.11 are genetic risk factors that can be identified in 3% of patients with IGE including JME. These microdeletions, however, also represent genetic risk factors to a broad range of other neurodevelopmental disorders. Additionally, 6% of patients with GGE carry other, potentially pathogenic structural genomic variants. While family studies largely support the channelopathy concept of the idiopathic epilepsies, the results of studies investigating copy number variations suggest that JME genetically overlaps with a broad range of other neurodevelopmental disorders. In addition, the particular genetic properties of structural genomic variations as rare genetic variants highlight the complexity of the genetic architecture of human disease.

The epilepsy phenome/genome project

BACKGROUND

Epilepsy is a common neurological disorder that affects approximately 50 million people worldwide. Both risk of epilepsy and response to treatment partly depend on genetic factors, and gene identification is a promising approach to target new prediction, treatment, and prevention strategies. However, despite significant progress in the identification of genes causing epilepsy in families with a Mendelian inheritance pattern, there is relatively little known about the genetic factors responsible for common forms of epilepsy and so-called epileptic encephalopathies. Study design The Epilepsy Phenome/Genome Project (EPGP) is a multi-institutional, retrospective phenotype-genotype study designed to gather and analyze detailed phenotypic information and DNA samples on 5250 participants, including probands with specific forms of epilepsy and, in a subset, parents of probands who do not have epilepsy.

RESULTS

EPGP is being executed in four phases: study initiation, pilot, study expansion/establishment, and close-out. This article discusses a number of key challenges and solutions encountered during the first three phases of the project, including those related to (1) study initiation and management, (2) recruitment and phenotyping, and (3) data validation. The study has now enrolled 4223 participants.

CONCLUSIONS

EPGP has demonstrated the value of organizing a large network into cores with specific roles, managed by a strong Administrative Core that utilizes frequent communication and a collaborative model with tools such as study timelines and performance-payment models. The study also highlights the critical importance of an effective informatics system, highly structured recruitment methods, and expert data review.

The genetics of dystonia: new twists in an old tale

Dystonia is a common movement disorder seen by neurologists in clinic. Genetic forms of the disease are important to recognize clinically and also provide valuable information about possible pathogenic mechanisms within the wider disorder. In the past few years, with the advent of new sequencing technologies, there has been a step change in the pace of discovery in the field of dystonia genetics. In just over a year, four new genes have been shown to cause primary dystonia (CIZ1, ANO3, TUBB4A and GNAL), PRRT2 has been identified as the cause of paroxysmal kinesigenic dystonia and other genes, such as SLC30A10 and ATP1A3, have been linked to more complicated forms of dystonia or new phenotypes. In this review, we provide an overview of the current state of knowledge regarding genetic forms of dystonia—related to both new and well-known genes alike—and incorporating genetic, clinical and molecular information. We discuss the mechanistic insights provided by the study of the genetic causes of dystonia and provide a helpful clinical algorithm to aid clinicians in correctly predicting the genetic basis of various forms of dystonia.

Identifying SNP targeted pathways in partial epilepsies with genome-wide association study data

PURPOSE

In a recent genome-wide association study for partial epilepsies in the European population, a common genetic variation has been reported to affect partial epilepsy only modestly. However, in complex diseases such as partial epilepsy, multiple factors (e.g. single nucleotide polymorphisms, microRNAs, metabolic and epigenetic factors) may target different sets of genes in the same pathway, affecting its function and thus causing the disease development. In this regard, we hypothesize that the pathways are critical for elucidating the mechanisms underlying partial epilepsy.

METHODS

Previously we had developed a novel methodology with the aim of identifying the disease-related pathways. We had combined evidence of genetic association with current knowledge of (i) biochemical pathways, (ii) protein-protein interaction networks, and (iii) the functional information of selected single nucleotide polymorphisms. In our present study, we apply this methodology to a data set on partial epilepsy, including 3445 cases and 6935 controls of European ancestry.

RESULTS

We have identified 30 overrepresented pathways with corrected p-values smaller than 10(-12). These pathways include complement and coagulation cascades, cell cycle, focal adhesion, extra cellular matrix-receptor interaction, JAK-STAT signaling pathway, MAPK signaling pathway, proteasome, ribosome, calcium signaling and regulation of actin cytoskeleton pathways. Most of these pathways have growing scientific support in the literature as being associated with partial epilepsy. We also demonstrate that different factors affect distinct parts of the pathways, as shown here on complement and coagulation cascades pathway with a comparison of gene expression vs. genome-wide association study.

CONCLUSIONS

Traditional studies on genome-wide association have not revealed strong associations in epilepsies, since these single nucleotide polymorphisms are not shared by most of the patients. Our results suggest that it is more effective to incorporate the functional effect of a single nucleotide polymorphism on the gene product, protein-protein interaction networks and functional enrichment tools into genome-wide association studies. These can then be used to determine leading molecular pathways, which cannot be detected through traditional analyses. We hope that this type of analysis brings the research community one step closer to unraveling the complex genetic structure of epilepsies.

Unraveling the genetics of common epilepsies: approaches, platforms, and caveats

With no known intervention to prevent or cure epilepsy, treatment is primarily symptomatic and requires long-term administration of medications to suppress seizure occurrence. Current antiepileptic drugs (AEDs) are ineffective in one-third of patients (Kwan and Brodie, 2000). Such therapeutic inadequacy is largely due to our insufficient understanding of the basic molecular pathophysiological processes that underlie epileptogenesis. Breakthroughs are needed in the identification of new molecular targets that will translate to novel intervention approaches. Discovering genetic variants that increase the susceptibility to disease is a promising avenue to identifying such targets. However, early candidate gene-based studies in epilepsy proved ineffective in identifying genetic risk factors for the non-Mendelian, complex epilepsies, which represent >95% of clinically encountered epilepsy. Furthermore, genome-wide association studies (GWAS) of epilepsy patients have been largely negative, with the exception of several putative susceptibility loci discovered in Han Chinese focal epilepsy and European Caucasian GGE patients (Kasperaviciute et al., 2010; Guo et al., 2012; Consortium et al., 2012). Results of these GWAS suggest that, similar to other common diseases, associations with common single nucleotide variants (SNV) appear likely to account for a small fraction of the heritability of epilepsy, thus fuelling the effort to also search for alternative genetic contributors, with a recent increased emphasis on rare variants with larger effects (Manolio et al., 2009). It is possible that both common and rare variants contribute to an increased susceptibility to common epilepsy syndromes (Mulley et al., 2005). We review the approaches that have been taken to identify genetic risk markers of the common epilepsy syndromes, the experimental platforms, and their caveats. We discuss current technologies and analytical frameworks that might expedite the discovery of these variants by leveraging advances in microarray-based, high-throughput, genotyping technology, and complementary interdisciplinary expertise of study teams including the need for meta-analyses under global collaborative frameworks. We briefly discuss the analytical options made available through rapid advances in sequencing and other genomic technologies.

Next generation sequencing for neurological diseases: new hope or new hype?

Over the past year huge advances have been made in our ability to determine the genetic aetiology of many neurological diseases through the utilisation of next generation sequencing platforms. This technology is, on a daily basis, providing new breakthroughs in neurological disease. The aim of this article is to clearly describe the technological platforms, methods of data analysis, established breakthroughs, and potential future clinical and research applications of this innovative and exciting technique which has relevance to all those working within clinical neuroscience.

Genome-wide association analysis of genetic generalized epilepsies implicates susceptibility loci at 1q43, 2p16.1, 2q22.3 and 17q21.32

Genetic generalized epilepsies (GGEs) have a lifetime prevalence of 0.3% and account for 20-30% of all epilepsies. Despite their high heritability of 80%, the genetic factors predisposing to GGEs remain elusive. To identify susceptibility variants shared across common GGE syndromes, we carried out a two-stage genome-wide association study (GWAS) including 3020 patients with GGEs and 3954 controls of European ancestry. To dissect out syndrome-related variants, we also explored two distinct GGE subgroups comprising 1434 patients with genetic absence epilepsies (GAEs) and 1134 patients with juvenile myoclonic epilepsy (JME). Joint Stage-1 and 2 analyses revealed genome-wide significant associations for GGEs at 2p16.1 (rs13026414, P(meta) = 2.5 × 10(-9), OR[T] = 0.81) and 17q21.32 (rs72823592, P(meta) = 9.3 × 10(-9), OR[A] = 0.77). The search for syndrome-related susceptibility alleles identified significant associations for GAEs at 2q22.3 (rs10496964, P(meta) = 9.1 × 10(-9), OR[T] = 0.68) and at 1q43 for JME (rs12059546, P(meta) = 4.1 × 10(-8), OR[G] = 1.42). Suggestive evidence for an association with GGEs was found in the region 2q24.3 (rs11890028, P(meta) = 4.0 × 10(-6)) nearby the SCN1A gene, which is currently the gene with the largest number of known epilepsy-related mutations. The associated regions harbor high-ranking candidate genes: CHRM3 at 1q43, VRK2 at 2p16.1, ZEB2 at 2q22.3, SCN1A at 2q24.3 and PNPO at 17q21.32. Further replication efforts are necessary to elucidate whether these positional candidate genes contribute to the heritability of the common GGE syndromes.

Advances in epilepsy genetics and genomics

Current and emerging technologies for mutation identification are changing the landscape of genetics and accelerating the pace of discovery. Application of high throughput genomic analysis to epilepsy will advance our understanding of the genetic contribution to common forms of epilepsy and suggest novel therapeutic strategies for improved treatment.

MRI-based brain structure volumes in temporal lobe epilepsy patients and their unaffected siblings: a preliminary study

INTRODUCTION

Investigating the heritability of brain structure may be useful in simplifying complicated genetic studies in temporal lobe epilepsy (TLE). A preliminary study is presented to determine if volume deficits of candidate brain structures present at a higher rate in unaffected siblings than controls subjects.

METHODS

T1-weighted MR images was acquired for 28 TLE patients, a same-sex unaffected sibling of 12 of these and 28 normal controls. Selected brain structure volumes were measured using an automated whole brain segmentation technique. Candidate brain structure endophenotypes were determined and group differences were investigated between (1) controls and patients and (2) controls and siblings. ICC's were used to measure the quantitative volumetric association within each sibling pair.

RESULTS

TLE patients demonstrated a significantly lower cerebral white matter, bilateral hippocampus, thalamus, and left entorhinal cortex volumes when compared with controls. A significant deficit in cerebral white matter (CWM) was common to patient and nonaffected siblings when compared with controls. Furthermore, a significant correlation was revealed between patients and siblings in CWM and bilateral thalamus.

CONCLUSION

The findings suggest an overlap in the neurodevelopmental genes responsible for both brain structure and the expression of the disease. Further work is ongoing to confirm these findings.

Epi4K: gene discovery in 4,000 genomes

A major challenge in epilepsy research is to unravel the complex genetic mechanisms underlying both common and rare forms of epilepsy, as well as the genetic determinants of response to treatment. To accelerate progress in this area, the National Institute of Neurological Disorders and Stroke (NINDS) recently offered funding for the creation of a “Center without Walls” to focus on the genetics of human epilepsy. This article describes Epi4K, the collaborative study supported through this grant mechanism and having the aim of analyzing the genomes of a minimum 4,000 subjects with highly selected and well-characterized epilepsy.

An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people

Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find rare variants are abundant (1 every 17 bases) and geographically localized, so that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. We conclude that because of rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk.

Identification of common variants associated with human hippocampal and intracranial volumes

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10(-7)).

The genetic variability and commonality of neurodevelopmental disease

Despite detailed clinical definition and refinement of neurodevelopmental disorders and neuropsychiatric conditions, the underlying genetic etiology has proved elusive. Recent genetic studies have revealed some common themes: considerable locus heterogeneity, variable expressivity for the same mutation, and a role for multiple disruptive events in the same individual affecting genes in common pathways. Recurrent copy number variation (CNV), in particular, has emphasized the importance of either de novo or essentially private mutations creating imbalances for multiple genes. CNVs have foreshadowed a model where the distinction between milder neuropsychiatric conditions from those of severe developmental impairment may be a consequence of increased mutational burden affecting more genes.

Deep sequencing of the LRRK2 gene in 14,002 individuals reveals evidence of purifying selection and independent origin of the p.Arg1628Pro mutation in Europe

Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single-nucleotide variants, 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Among Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.

Genetics of temporal lobe epilepsy: a review

Temporal lobe epilepsy (TLE) is usually regarded as a polygenic and complex disorder. To understand its genetic component, numerous linkage analyses of familial forms and association studies of cases versus controls have been conducted since the middle of the nineties. The present paper lists genetic findings for TLE from the initial segregation analysis to the most recent results published in May 2011. To date, no genes have been clearly related to TLE despite many efforts to do so. However, it is vital to continue replication studies and collaborative attempts to find significant results and thus determine which gene variant combination plays a definitive role in the aetiology of TLE.

Implications of central immune signaling caused by drugs of abuse: mechanisms, mediators and new therapeutic approaches for prediction and treatment of drug dependence

In the past two decades a trickle of manuscripts examining the non-neuronal central nervous system immune consequences of the drugs of abuse has now swollen to a significant body of work. Initially, these studies reported associative evidence of central nervous system proinflammation resulting from exposure to the drugs of abuse demonstrating key implications for neurotoxicity and disease progression associated with, for example, HIV infection. However, more recently this drug-induced activation of central immune signaling is now understood to contribute substantially to the pharmacodynamic actions of the drugs of abuse, by enhancing the engagement of classical mesolimbic dopamine reward pathways and withdrawal centers. This review will highlight the key in vivo animal, human, biological and molecular evidence of these central immune signaling actions of opioids, alcohol, cocaine, methamphetamine, and 3,4-methylenedioxymethamphetamine (MDMA). Excitingly, this new appreciation of central immune signaling activity of drugs of abuse provides novel therapeutic interventions and opportunities to identify 'at risk' individuals through the use of immunogenetics. Discussion will also cover the evidence of modulation of this signaling by existing clinical and pre-clinical drug candidates, and novel pharmacological targets. Finally, following examination of the breadth of central immune signaling actions of the drugs of abuse highlighted here, the current known common immune signaling components will be outlined and their impact on established addiction neurocircuitry discussed, thereby synthesizing a common neuroimmune hypothesis of addiction.

What is complex about complex disorders?

Rather than being polygenic, complex disorders probably represent umbrella terms for collections of conditions caused by rare, recent mutations in any of a large number of different genes.

Opportunities and challenges for genome sequencing in the clinic

Human genome sequencing technology is developing rapidly. These developments are providing exciting opportunities for genetic mapping of human traits, ranging from accelerated discovery of mutations underlying relatively simple Mendelian disorders to more genetically complex human diseases. This chapter outlines the development of whole-genome sequencing in a historical context of genetic mapping and explores the impact that sequencing is having on gene discovery study design. Using the example of epilepsy, the authors outline the opportunities and barriers for the translation of genetic predictors from discovery to the clinic. Finally, the authors discuss the practical challenges of actual implementation of whole-genome sequencing to the clinic.

A cross-sectional MRI study of brain regional atrophy and clinical characteristics of temporal lobe epilepsy with hippocampal sclerosis

PURPOSE

Applying a cross-sectional design, we set out to further characterize the significance of extrahippocampal brain atrophy in a large sample of 'sporadic' mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE+HS). By evaluating the influence of epilepsy chronicity on structural atrophy, this work represents an important step towards the characterization of MRI-based volumetric measurements as genetic endophenotypes for this condition.

METHODS

Using an automated brain segmentation technique, MRI-based volume measurements of several brain regions were compared between 75 patients with 'sporadic' MTLE+HS and 50 healthy controls. Applying linear regression models, we examined the relationship between structural atrophy and important clinical features of MTLE+HS, including disease duration, lifetime number of partial and generalized seizures, and history of initial precipitating insults (IPIs).

RESULTS

Significant volume loss was detected in ipsilateral hippocampus, amygdala, thalamus, and cerebral white matter (WM). In addition, contralateral hippocampal and bilateral cerebellar grey matter (GM) volume loss was observed in left MTLE+HS patients. Hippocampal, amygdalar, and cerebral WM volume loss correlated with duration of epilepsy. This correlation was stronger in patients with prior IPIs history. Further, cerebral WM, cerebellar GM, and contralateral hippocampal volume loss correlated with lifetime number of generalized seizures.

CONCLUSION

Our findings confirm that multiple brain regions beyond the hippocampus are involved in the pathogenesis of MTLE+HS. IPIs are an important factor influencing the rate of regional atrophy but our results also support a role for processes related to epilepsy chronicity. The consequence of epilepsy chronicity on candidate brain regions has important implications on their application as genetic endophenotypes.

Systems biology impact on antiepileptic drug discovery

Systems biology (SB), a recent trend in bioscience research to consider the complex interactions in biological systems from a holistic perspective, sees the disease as a disturbed network of interactions, rather than alteration of single molecular component(s). SB-relying network pharmacology replaces the prevailing focus on specific drug-receptor interaction and the corollary of rational drug design of "magic bullets", by the search for multi-target drugs that would act on biological networks as "magic shotguns". Epilepsy being a multi-factorial, polygenic and dynamic pathology, SB approach appears particularly fit and promising for antiepileptic drug (AED) discovery. In fact, long before the advent of SB, AED discovery already involved some SB-like elements. A reported SB project aimed to find out new drug targets in epilepsy relies on a relational database that integrates clinical information, recordings from deep electrodes and 3D-brain imagery with histology and molecular biology data on modified expression of specific genes in the brain regions displaying spontaneous epileptic activity. Since hitting a single target does not treat complex diseases, a proper pharmacological promiscuity might impart on an AED the merit of being multi-potent. However, multi-target drug discovery entails the complicated task of optimizing multiple activities of compounds, while having to balance drug-like properties and to control unwanted effects. Specific design tools for this new approach in drug discovery barely emerge, but computational methods making reliable in silico predictions of poly-pharmacology did appear, and their progress might be quite rapid. The current move away from reductionism into network pharmacology allows expecting that a proper integration of the intrinsic complexity of epileptic pathology in AED discovery might result in literally anti-epileptic drugs.

Heredity in epilepsy: neurodevelopment, comorbidity, and the neurological trait

The genetic bases of common, nonmendelian epilepsy have been difficult to elucidate. In this article, we argue for a new approach to genetic inquiry in epilepsy. In the latter part of the 19th century, epilepsy was universally acknowledged to be part of a wider "neurological trait" that included other neuropsychiatric conditions. In recent years, studies of comorbidity have shown clear links between epilepsy and various neuropsychiatric disorders including psychosis and depression, and genetic studies of copy number variants (CNVs) have shown that in some cases, the same CNV underpins neuropsychiatric illness and epilepsy. Functional annotation analysis of the sets of genes impacted by epilepsy CNVs shows enrichment for genes involved with neural development, with gene ontological (GO) categories including "neurological system process" (P=0.006), "synaptic transmission" (P=0.009), and "learning or memory" (P=0.01). These data support the view that epilepsy and some neuropsychiatric conditions share pathogenic neurodevelopmental pathways, and that epilepsy should be included in the spectrum of neurodevelopmental disorders. Yet, most current genetic research in epilepsy has restricted samples to specific types of epilepsy categorized according to the clinical classification schemes on the basis of seizure type, anatomical location, or epilepsy syndrome. These schemes are, to an extent, arbitrary and do not necessarily align with biological reality. We propose an alternative approach that makes no phenotypic assumptions beyond including epilepsy in the neurodevelopmental spectrum. A "'value-free" strategy of reverse phenotyping may be worth exploring, starting with genetic association and looking backward at the phenotype. Finally, it should be noted that there are societal implications to associating epilepsy with other neuropsychiatric disorders, and it is vital to ensure research in this area does not result in increased stigma for patients with epilepsy.

A genetic epidemiological survey of idiopathic epilepsy in the Chinese Han population

BACKGROUND

Idiopathic epilepsy (IE) is a syndrome that comprises epilepsy only, with no underlying structural brain lesion or other neurological signs or symptoms. Numerous studies have shown that genetic factors play an important role in IE. IE is a common disease in the Chinese Han population. However, the genetic epidemiological characteristics of IE in the Chinese population, such as its heritability and genetic models remain unclear.

PURPOSE

To study the clinical and epidemiological profile of IE, to estimate the heritability and determine the possible genetic models for IE in the Chinese Han population.

METHODS

A case-control family-based study was carried out in a rural Chinese county. We collected data from eligible IE patients, controls, and their relatives by a uniform structured questionnaire, and then established an epidemiologic database of epilepsy using Access2010. General statistical and genetic epidemiological analyses (Falconer's-method-based heritability, simple segregation ratio and complex segregation analysis) were performed using SAS9.1 and the SAGE-SEGREG program.

RESULTS

(1) The prevalence of IE among the relatives of probands with IE (2.75‰) was higher than that among the relatives of the control group (0.61‰). The prevalence of IE among the first-, second-, and third-degree relatives of the probands with IE was 11.45‰, 2.64‰ and 0.98‰, respectively, which were all higher than the corresponding prevalences in the relatives of controls. Trend-chi-squared tests indicated that the prevalence of epilepsy increased among the relatives of probands with decreasing kinship distance (χ(2)=97.16, P=0.00). (2) The heritability of IE among first-, second-, and third-degree relatives was 55.06%, 50.72% and 16.98%, respectively. The weighted mean heritability was 46.07%. (3) The simple segregation ratio of IE was 0.03, significantly lower than the Mendelian recessive segregation ratio of 0.25. Complex segregation analysis showed that the population we studied accepted a Mendelian genetic model (dominant, recessive, additive, and a major gene model) and excluded the general model, non-transmitted model, and environment-only model. A Mendelian additive inheritance model was ultimately the best-fit because it had the lowest Akaike Information Criteria score.

CONCLUSION

In the Chinese Han population, IE follows a pattern of polygenic Mendelian additive inheritance rather than single-gene inheritance. Nearly half of the total variance can be explained by genetic factors.

Pharmacogenomics and epilepsy: the road ahead

Epilepsy is one of the most common, serious neurological disorders, affecting an estimated 50 million people worldwide. The condition is typically treated using antiepileptic drugs of which there are 16 in widespread use. However, there are many different syndrome and seizure types within epilepsy and information guiding clinicians on the most effective drug and dose for individual patients is lacking. Further, all of the antiepileptic drugs have associated adverse reactions, some of which are severe and life-threatening. Here, we review the pharmacogenomic work to date in the context of these issues and comment on key aspects of study design that are required to speed up the identification of clinically relevant genetic factors.

Performance of genotype imputation for rare variants identified in exons and flanking regions of genes

Genotype imputation has the potential to assess human genetic variation at a lower cost than assaying the variants using laboratory techniques. The performance of imputation for rare variants has not been comprehensively studied. We utilized 8865 human samples with high depth resequencing data for the exons and flanking regions of 202 genes and Genome-Wide Association Study (GWAS) data to characterize the performance of genotype imputation for rare variants. We evaluated reference sets ranging from 100 to 3713 subjects for imputing into samples typed for the Affymetrix (500K and 6.0) and Illumina 550K GWAS panels. The proportion of variants that could be well imputed (true r(2)>0.7) with a reference panel of 3713 individuals was: 31% (Illumina 550K) or 25% (Affymetrix 500K) with MAF (Minor Allele Frequency) less than or equal 0.001, 48% or 35% with 0.0010.05. The performance for common SNPs (MAF>0.05) within exons and flanking regions is comparable to imputation of more uniformly distributed SNPs. The performance for rare SNPs (0.01 Collapse

Key Words Collapse

MESH Headings

• Exons/genetics
• Gene Frequency
• Genes/genetics
• Genetic Variation
• Genome-Wide Association Study
• Genotype
• Humans
• Polymorphism, Single Nucleotide/genetics

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Grants

• R01 HG004960 NHGRI NIH HHS
• R01 HG005701 NHGRI NIH HHS
• R01HG005701 NHGRI NIH HHS
• R01HG004960 NHGRI NIH HHS

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Affiliation(s)

Li Li Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Yun Li Department of Genetics, Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
Sharon R. Browning Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
Brian L. Browning Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington, United States of America
Andrew J. Slater Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Xiangyang Kong Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Jennifer L. Aponte Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Vincent E. Mooser Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Stephanie L. Chissoe Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
John C. Whittaker Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Matthew R. Nelson Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Margaret Gelder Ehm Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom

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Newly diagnosed epilepsy and pharmacogenomics research: a step in the right direction?

Pharmacogenomics holds the promise of selecting the right drug at the right dose for the right person. Its research and application in epilepsy are in their infancy. Although advances have been made in identifying genetic markers of adverse effects in terms of severe cutaneous reactions, there has been little progress in predicting efficacy. Most studies have been retrospective and case-control in design, despite the associated problems of recall bias and a usually undefined relationship between genotype and outcome. We describe the epidemiological framework necessary to detect genetic influences on antiepileptic drug response, and propose an ambitious prospective outcome study of newly diagnosed epilepsy across all age ranges, countries, and continents, which would provide the template for a global pharmacogenomic project. Other epidemiological considerations and statistical constraints and issues related to study design, databases, and ethics that are critical for advancement in the field are also discussed.