Genome-wide mapping of markers for epilepsy predisposition and treatment.

There is an increasing amount of evidence to suggest genetics plays a large role in governing an individual's risk for developing epilepsy and their response to anti-epileptic drug treatment. Responses can range from seizure control with first drug, complete resistance and serious idiopathic and doserelated adverse events occurring upon exposure to specific drugs. This thesis consists of five studies with a common aim of identifying novel genetic influences on epilepsy predisposition and treatment. A candidate gene study was conducted to assess the association of variants within the MHC locus, coding for different HLA gene subtypes, with carbamazepine-induced subcutaneous adverse reactions in an ancestrally-European epilepsy case cohort. Together with international colleagues, we identified HLA-A*3101 as a strong predictor of the clinical spectrum of mild to severe subcutaneous adverse reactions caused by carbamazepine. In a follow-up study, we attempted to replicate our finding in a similar case cohort caused by exposure to lamotrigine and phenytoin. This study could not detect a genetic association with any common variant tested, implying the HLA-A*3101 gene is a specific predictor of carbamazepine-induced adverse events. A genome-wide association study of response to anti-epileptic drugs sought to identify common variants of large effect that may influence the refractory phenotype witnessed in up to 30% of epilepsy patients. This study did not detect a genetic association with any common variants tested suggesting that common variants with smaller effect size, or multiple rare variants may have a role to play. Finally, we turned our attention to genetic variation that may exist in a number of Irish families with varied inherited forms of the disease. Using a combination of genome-wide association and whole exome sequencing, we identified a number of interesting susceptibility genes shared by affected individuals including an intellectual disability locus, two ion channels and a glucose transporter.</p

Quantitative analysis of phenotypic elements augments traditional electroclinical classification of common familial epilepsies

Objective: Classification of epilepsy into types and subtypes is important for both clinical care and research into underlying disease mechanisms. A quantitative, data-driven approach may augment traditional electroclinical classification and shed new light on existing classification frameworks.Methods: We used latent class analysis, a statistical method that assigns subjects into groups called latent classes based on phenotypic elements, to classify individuals with common familial epilepsies from the Epi4K Multiplex Families study. Phenotypic elements included seizure types, seizure symptoms, and other elements of the medical history. We compared class assignments to traditional electroclinical classifications and assessed familial aggregation of latent classes.Results: A total of 1120 subjects with epilepsy were assigned to five latent classes. Classes 1 and 2 contained subjects with generalized epilepsy, largely reflecting the distinction between absence epilepsies and younger onset (class 1) versus myoclonic epilepsies and older onset (class 2). Classes 3 and 4 contained subjects with focal epilepsies, and in contrast to classes 1 and 2, these did not adhere as closely to clinically defined focal epilepsy subtypes. Class 5 contained nearly all subjects with febrile seizures plus or unknown epilepsy type, as well as a few subjects with generalized epilepsy and a few with focal epilepsy. Family concordance of latent classes was similar to or greater than concordance of clinically defined epilepsy types.Significance: Quantitative classification of epilepsy has the potential to augment traditional electroclinical classification by (1) combining some syndromes into a single class, (2) splitting some syndromes into different classes, (3) helping to classify subjects who could not be classified clinically, and (4) defining the boundaries of clinically defined classifications. This approach can guide future research, including molecular genetic studies, by identifying homogeneous sets of individuals that may share underlying disease mechanisms.</p

Correction: Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia

Prior to and following the publication of this article the authors noted that the complete list of authors was not included in the main article and was only present in Supplementary Table 1. The author list in the original article has now been updated to include all authors, and Supplementary Table 1 has been removed. All other supplementary files have now been updated accordingly. Furthermore, in Table 1 of this Article, the replication cohort for the row Close relative in data set, n (%) was incorrect. All values have now been corrected to 0(0%). The publishers would like to apologise for this error and the inconvenience it may have caused.<br

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes

Testing for pharmacogenomic predictors of ppRNFL thinning in individuals exposed to vigabatrin

Background: The anti-seizure medication vigabatrin (VGB) is effective for controlling seizures, especially infantile spasms. However, use is limited by VGB-associated visual field loss (VAVFL). The mechanisms by which VGB causes VAVFL remains unknown. Average peripapillary retinal nerve fibre layer (ppRNFL) thickness correlates with the degree of visual field loss (measured by mean radial degrees). Duration of VGB exposure, maximum daily VGB dose, and male sex are associated with ppRNFL thinning. Here we test the hypothesis that common genetic variation is a predictor of ppRNFL thinning in VGB exposed individuals. Identifying pharmacogenomic predictors of ppRNFL thinning in VGB exposed individuals could potentially enable safe prescribing of VGB and broader use of a highly effective drug. Methods: Optical coherence topography (OCT) and GWAS data were processed from VGB-exposed individuals (n = 71) recruited through the EpiPGX Consortium. We conducted quantitative GWAS analyses for the following OCT measurements: (1) average ppRNFL, (2) inferior quadrant, (3) nasal quadrant, (4) superior quadrant, (5) temporal quadrant, (6) inferior nasal sector, (7) nasal inferior sector, (8) superior nasal sector, and (9) nasal superior sector. Using the summary statistics from the GWAS analyses we conducted gene-based testing using VEGAS2. We conducted nine different PRS analyses using the OCT measurements. To determine if VGB-exposed individuals were predisposed to having a thinner RNFL, we calculated their polygenic burden for retinal thickness. PRS alleles for retinal thickness were calculated using published summary statistics from a large-scale GWAS of inner retinal morphology using the OCT images of UK Biobank participants. Results: The GWAS analyses did not identify a significant association after correction for multiple testing. Similarly, the gene-based and PRS analyses did not reveal a significant association that survived multiple testing. Conclusion: We set out to identify common genetic predictors for VGB induced ppRNFL thinning. Results suggest that large-effect common genetic predictors are unlikely to exist for ppRNFL thinning (as a marker of VAVFL). Sample size was a limitation of this study. However, further recruitment is a challenge as VGB is rarely used today because of this adverse reaction. Rare variants may be predictors of this adverse drug reaction and were not studied here.</p

A pharmacogenomic assessment of psychiatric adverse drug reactions to levetiracetam

Objective: Levetiracetam (LEV) is an effective antiseizure medicine, but 10%-20% of people treated with LEV report psychiatric side-effects, and up to 1% may have psychotic episodes. Pharmacogenomic predictors of these adverse drug reactions (ADRs) have yet to be identified. We sought to determine the contribution of both common and rare genetic variation to psychiatric and behavioral ADRs associated with LEV. Methods: This case-control study compared cases of LEV-associated behavioral disorder (n = 149) or psychotic reaction (n = 37) to LEV-exposed people with no history of psychiatric ADRs (n = 920). All samples were of European ancestry. We performed genome-wide association study (GWAS) analysis comparing those with LEV ADRs to controls. We estimated the polygenic risk scores (PRS) for schizophrenia and compared cases with LEV-associated psychotic reaction to controls. Rare variant burden analysis was performed using exome sequence data of cases with psychotic reactions (n = 18) and controls (n = 122). Results: Univariate GWAS found no significant associations with either LEV-associated behavioural disorder or LEV-psychotic reaction. PRS analysis showed that cases of LEV-associated psychotic reaction had an increased PRS for schizophrenia relative to contr ols (p = .0097, estimate = .4886). The rare-variant analysis found no evidence of an increased burden of rare genetic variants in people who had experienced LEV-associated psychotic reaction relative to controls. Significance: The polygenic burden for schizophrenia is a risk factor for LEV-associated psychotic reaction. To assess the clinical utility of PRS as a predictor, it should be tested in an independent and ideally prospective cohort. Larger sample sizes are required for the identification of significant univariate common genetic signals or rare genetic signals associated with psychiatric LEV ADRs.</p

Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies.

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology

De-novo mutations in patients with chronic ultra-refractory epilepsy with onset after age five years

We set out to investigate whether a de-novo paradigm could explain genetic causes of chronic ultra-refractory epilepsy, with onset later than the typical age for the epileptic encephalopathies. We performed exome sequencing on nine adult patients with MRI-negative epilepsy and no preceding intellectual disability. All had an onset of seizures after five years old and had chronic ultra-refractory epilepsy defined here as having failed more than six anti-epileptic drugs and currently experiencing ≥4 disabling seizures per month. Parents were sequenced to identify de-novo mutations and these were assessed for likelihood of pathogenicity based on the American College of Medical Genetics and Genomics (ACMG) criteria. We confirmed the presence of functional and predicted-damaging de-novo mutations in 3/9 patients. One of these pathogenic de-novo mutations, in DNM1L, was previously reported in a patient with severe epilepsy and chronic pharmacoresistance adding to the evidence for DNM1L as an epilepsy gene. Exome sequencing is a successful strategy for identifying de-novo mutations in paediatric epileptic encephalopathies and rare neurological disorders. Our study demonstrates the potential benefit of considering ultra-refractory epilepsy patients with later onset for genetic testing. Identifying genetic mutations underpinning severe epilepsy of unknown aetiology may provide new insight into the underlying biology and offers the potential for therapeutic intervention in the form of precision medicine in older patients

Development of a genomics module within an epilepsy-specific electronic health record: Toward genomic medicine in epilepsy care

Objectives: Both clinical genomics and e-Health technology are changing the way medicine is being practiced. Although the basic clinical methodology of good medical care will remain unchanged, the combined power of genomics and electronic health records has the capability of enhancing, and in some cases transforming, the practice of medicine. This is particularly true in the care of patients with complex long-term medical conditions such as chronic refractory epilepsy, especially in those with related complex comorbidities including intellectual disability and psychiatric disease.Methods: Herein we outline the development and integration of an epilepsy genomics module into a preexisting epilepsy electronic patient record (EPR) system.Results: We describe how this EPR infrastructure is used to facilitate discussion at multidisciplinary clinical meetings around molecular diagnosis and resulting changes in management.Significance: This work illustrates the role of eHealth technology in embedding genomics into the clinical pathway.</div

Analysis of shared common genetic risk between amyotrophic lateral sclerosis and epilepsy

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins