Structural genomic variation in childhood epilepsies with complex phenotypes

Copy Number Variation and Epilepsy: State of the Art in the Era of High-Throughput Sequencing-A Multicenter Cohort Study

BACKGROUND

Genetic epilepsy diagnosis is increasing due to technological advancements. Although the use of molecular diagnosis is increasing, chromosomal microarray analysis (CMA) remains an important diagnostic tool for many patients. We aim to explore the role and indications of CMA in epilepsy, given the current genomic advances.

METHODS

We obtained data from 378 epileptic described patients, who underwent CMA between 2015 and 2021. Different types of syndromic or nonsyndromic epilepsy were represented.

RESULTS

After excluding patients who were undertreated or had missing data, we included 250 patients with treated epilepsy and relevant clinical information. These patients mostly had focal epilepsy or developmental and epileptic encephalopathy, with a median start age of 2 years. Ninety percent of the patients had intellectual disability, more than two thirds had normal head size, and 60% had an abnormal magnetic resonance imaging. We also included 10 patients with epilepsy without comorbidities. In our cohort, we identified 35 pathogenic copy number variations (CNVs) explaining epilepsy with nine recurrent CNVs enriched in patients with epilepsy, 12 CNVs related to neurodevelopmental disorder phenotype with possible epilepsy, five CNVs including a gene already known in epilepsy, and nine CNVs based on size combined with de novo occurrence. The diagnosis rate in our study reached 14% (35 of 250) with first-line CMA, as previously reported. Although targeted gene panel sequencing could potentially diagnose some of the reported epilepsy CNVs (34% [12 of 35]).

CONCLUSIONS

CMA remains a viable option as the first-line genetic test in cases where other genetic tests are not available and as a second-line diagnostic technique if gene panel or exome sequencing yields negative results.

The importance of routine genetic testing in pediatric epilepsy surgery

Genetic variants in relevant genes coexisting with MRI lesions in children with drug-resistant epilepsy (DRE) can negatively influence epilepsy surgery outcomes. Still, presurgical evaluation does not include genetic diagnostics routinely. Here, we report our presurgical evaluation algorithm that includes routine genetic testing. We analyzed retrospectively the data of 68 children with DRE operated at a mean age of 7.8 years (IQR: 8.1 years) at our center. In 49 children, genetic test results were available. We identified 21 gene variants (ACMG III: n = 7, ACMG IV: n = 2, ACMG V: n = 12) in 19 patients (45.2%) in the genes TSC1, TSC2, MECP2, DEPDC5, HUWE1, GRIN1, ASH1I, TRIO, KIF5C, CDON, ANKD11, TGFBR2, ATN1, COL4A1, JAK2, KCNQ2, ATP1A2, and GLI3 by whole-exome sequencing as well as deletions and duplications by array CGH in six patients. While the results did not change the surgery indication, they supported counseling with respect to postoperative chance of seizure freedom and weaning of antiseizure medication (ASM). The presence of genetic findings leads to the postoperative retention of at least one ASM. In our cohort, the International League against Epilepsy (ILAE) seizure outcome did not differ between patients with and without abnormal genetic findings. However, in the 7/68 patients with an unsatisfactory ILAE seizure outcome IV or V 12 months postsurgery, 2 had an abnormal or suspicious genetic finding as a putative explanation for persisting seizures postsurgery, and 3 had received palliative surgery including one TSC patient. This study highlights the importance of genetic testing in children with DRE to address putative underlying germline variants as genetic epilepsy causes or predisposing factors that guide patient and/or parent counseling on a case-by-case with respect to their individual chance of postoperative seizure freedom and ASM weaning. PLAIN LANGUAGE SUMMARY: Genetic variants in children with drug-resistant epilepsy (DRE) can negatively influence epilepsy surgery outcomes. However, presurgical evaluation does not include genetic diagnostics routinely. This retrospective study analyzed the genetic testing results of the 68 pediatric patients who received epilepsy surgery in our center. We identified 21 gene variants by whole-exome sequencing as well as deletions and duplications by array CGH in 6 patients. These results highlight the importance of genetic testing in children with DRE to guide patient and/or parent counseling on a case-by-case with respect to their individual chance of postoperative seizure freedom and ASM weaning.

Diagnostic Yield of Epilepsy-Genes Sequencing and Chromosomal Microarray in Pediatric Epilepsy

BACKGROUND

Around 40% of individuals with epilepsy have an underlying identifiable genetic etiology. Common methods for epilepsy genetic testing are chromosomal microarray (CMA) and epilepsy-genes sequencing (EGS). Historically, CMA was the first-line test for patients with epilepsy, but recent studies have shown that EGS has a superior diagnostic yield. To further optimize testing algorithms for epilepsy, we compared these tests' diagnostic yields and explored how they are influenced by age of onset and phenotype complexity.

METHODS

Genetic test results from a cohort of patients with epilepsy were used to determine the diagnostic yield of CMA (n = 366) versus EGS (n = 370) for genetic epilepsy etiologies. Further analysis examined the probability of diagnostic results based on age of seizure onset and patients' phenotype complexity.

RESULTS

For patients who underwent CMA, causative variants were found in 28 of 366 cases (7.7%), and 60 of 366 patients (16.4%) had at least one variant of uncertain significance (VUS). For EGS, 65 of 370 (17.6%) cases had causative variants, whereas 155 of 370 (41.9%) had at least one VUS. EGS had a significantly higher diagnostic yield than CMA (odds ratio [OR] = 2.63, P < 0.001). This difference in diagnostic yield was further pronounced among patients with infantile seizure onset (OR = 4.69, P < 0.001) and patients with additional neurological findings (OR = 2.99, P < 0.001).

CONCLUSION

To minimize the time and resources required to reach a diagnosis, clinicians and insurers alike should consider using EGS as an initial diagnostic tool.

Rates of rare copy number variants in different circumstances among patients with genetic developmental and epileptic encephalopathy

BACKGROUND

Most patients with developmental and epileptic encephalopathy (DEE) have genetic etiology, which has been uncovered with different methods. Although chromosomal microarray analysis (CMA) has been broadly used in patients with DEE, data is still limited.

METHODS

Among 560 children (<18 years) who underwent CMA in our hospital between January 2013 and June 2021, 146 patients with developmental delay and recurrent seizures were screened. Patients with major brain abnormalities, metabolic abnormalities, and specific syndromes were excluded. The rate of rare copy number variants (CNVs) was estimated in total and according to seizure-onset age, relation to first seizure with the diagnosis of developmental delay, epilepsy syndromes, and organ anomalies.

RESULTS

Among the 110 patients enrolled, the rate of rare CNVs was 16.4%, varying by seizure-onset age: 33.3% in three neonates, 21.2% in 33 infants, 13.3% in 45 early childhood patients, 5.3% in 19 late childhood patients, and 30.0% in 10 adolescents. In relation to the first seizure with the diagnosis of developmental delay, the rates were 3.7%, 22.2%, and 12.5% in "before", "after", and "concurrent" subclasses, respectively. The rates of rare CNVs were 16.7% in "other predominantly focal or multifocal epilepsy", 28.6% in "other predominantly generalized epilepsy (PGE)", and 15.4% in West syndrome. The rates were 27.8% in minor brain anomalies, 37.5% in facial dysmorphism, and 22.2%, 20.0%, and 57.1% in endocrine, genitourinary and cardiovascular anomalies, respectively.

CONCLUSION

The rate of rare CNVs in patients with genetic DEE was 16.4% in total, which was higher in seizures occurring below the infantile period or after the diagnosis of developmental delay, in PGE, and in the presence of facial dysmorphism or cardiovascular anomalies.

Diagnostic Considerations in the Epilepsies-Testing Strategies, Test Type Advantages, and Limitations

The role of genetics in epilepsy has been recognized for a long time. Over the past decade, genome-wide technologies have identified numerous genes and variants associated with epilepsy. In the clinical setting, a myriad of genetic testing options are available, and a subset of specific genetic diagnoses have management implications. Furthermore, genetic testing can be a dynamic process. As a result, fundamental knowledge about genetics and genomics has become essential for all specialists. Here, we review current knowledge of the genetic contribution to various types of epilepsy, provide an overview of types of genetic variants, and discuss genetic testing options and their diagnostic yield. We also consider advantages and limitations of testing approaches.

The high frequency of chromosomal copy number variations and candidate genes in epilepsy patients

OBJECTIVE

Epilepsy is a chronic brain disease and is estimated to affect more than 50 million people worldwide.Epilepsy is a polygenic and multifactorial disease.Genetic causes play a major role in 40-60 % of all epilepsies.Copy number variations(CNVs) have been reported in approximately 5-12 % of patients with different types of epilepsy.Here we aimed to determine the diagnostic yield of the aCGH in epilepsy and to reveal new candidate genes and CNVs by analyzing aCGH data retrospectively.

METHODS

The clinical data of 80 patients with the diagnosis of epilepsy were examined retrospectively and the raw data of aCGH of these patients were reanalyzed in the light of current literature.

RESULTS

Pathogenic/likely pathogenic CNVs were detected in 14 of 80 patients and 12 of these CNVs (15 %) were associated with epilepsy phenotype. In addition, 18 CNVs in 16 different chromosomal loci that were evaluated as the variant of unknown clinical significance(VOUS). In four cases (5%), CNVs associated with epilepsy were less than 100 kb and these accounted for 13.3 % of all epilepsy associated CNVs.

CONCLUSION

The diagnostic yield of aCGH in epilepsy patients was found to be higher than most studies in the literature. MACROD2,ADGRB3(BAI3),SOX8,HIP1,PARK2 and TAFA2 genes were evaluated as potential epilepsy-related genes and NEDD9,RASAL2 and TNR genes thought to be the candidate genes for epilepsy. Our study showed that the diagnostic efficiency of aCGH in epilepsy is high and with more comprehensive studies, it will contribute to the elucidation of genes involved in genetic etiology in epilepsy patients.

Genetic diagnoses in pediatric patients with epilepsy and comorbid intellectual disability

PURPOSE

The aim of this retrospective study is to investigate the genetic etiology and propose a diagnostic strategy for pediatric patients with epilepsy and comorbid intellectual disability (ID).

METHODS

From September 2014 to May 2020, a total of 102 pediatric patients diagnosed with epilepsy with co-morbid ID with unknown causes were included in this study. All patients underwent tests of single nucleotide polymorphism (SNP) array for chromosomal abnormalities. Whole exome sequencing (WES) was consecutively performed in patients without diagnostic copy number variants (CNVs) (n = 85) for single nucleotide variants (SNVs). Subgroup analyses based on the age of seizure onset and ID severity were done.

RESULTS

The overall diagnostic yield of genetic aberrations was 33.3 % (34/102), which comprised 50.0 % with diagnostic CNVs and 50.0 % with diagnostic SNVs. The yield nominally increased with ID severity and decreased with age of seizure onset, though this result was not statistically significant. The diagnostic yield of SNVs in patients with seizure onset in the first year of life (25.0 % (11/44)) was significantly higher than those with childhood-onset epilepsy (10.3 % (6/58)) (p = 0.049), however, the diagnostic yield of CNVs in patients with childhood-onset epilepsy (17.2 % (10/58) was higher than the diagnostic yield of SNVs (10.3 % (6/58)). The most frequently syndromic epilepsy detected by SNP array was Angelman syndrome (n=4), including one confirmed with paternal uniparental disomy. Meanwhile, the most frequent SNVs were mutations of MECP2 (n=2) and IQSEC2 (n = 2) in sporadic cases.

CONCLUSION

Both CMA and WES are advantageous as unbiased approaches for a genetically heterogeneous condition. We proposed an effective diagnostic strategy for pediatric patients with epilepsy. For patients with seizure onset in the first year of life, WES is recommended as the first-tier test. However, for patients with childhood-onset epilepsy, SNP array should be considered for the first-tier test.

Complement: Bridging the innate and adaptive immune systems in sterile inflammation

The complement system is a collection of soluble and membrane-bound proteins that together act as a powerful amplifier of the innate and adaptive immune systems. Although its role in infection is well established, complement is becoming increasingly recognized as a key contributor to sterile inflammation, a chronic inflammatory process often associated with noncommunicable diseases. In this context, damaged tissues release danger signals and trigger complement, which acts on a range of leukocytes to augment and bridge the innate and adaptive immune systems. Given the detrimental effect of chronic inflammation, the complement system is therefore well placed as an anti-inflammatory drug target. In this review, we provide a general outline of the sterile activators, effectors, and targets of the complement system and a series of examples (i.e., hypertension, cancer, allograft transplant rejection, and neuroinflammation) that highlight complement's ability to bridge the 2 arms of the immune system.

Genetics and Extracellular Vesicles of Pediatrics Sleep Disordered Breathing and Epilepsy

Sleep remains one of the least understood phenomena in biology, and sleep disturbances are one of the most common behavioral problems in childhood. The etiology of sleep disorders is complex and involves both genetic and environmental factors. Epilepsy is the most popular childhood neurological condition and is characterized by an enduring predisposition to generate epileptic seizures, and the neurobiological, cognitive, psychological, and social consequences of this condition. Sleep and epilepsy are interrelated, and the importance of sleep in epilepsy is less known. The state of sleep also influences whether a seizure will occur at a given time, and this differs considerably for various epilepsy syndromes. The development of epilepsy has been associated with single or multiple gene variants. The genetics of epilepsy is complex and disorders exhibit significant genetic heterogeneity and variability in the expressivity of seizures. Phenobarbital (PhB) is the most widely used antiepileptic drug. With its principal mechanism of action to prolong the opening time of the γ-aminobutyric acid (GABA)-A receptor-associated chloride channel, it enhances chloride anion influx into neurons, with subsequent hyperpolarization, thereby reducing excitability. Enzymes that metabolize pharmaceuticals including PhB are well known for having genetic polymorphisms that contribute to adverse drug–drug interactions. PhB metabolism is highly dependent upon the cytochrome P450 (CYP450) and genetic polymorphisms can lead to variability in active drug levels. The highly polymorphic CYP2C19 isozymes are responsible for metabolizing a large portion of routinely prescribed drugs and variants contribute significantly to adverse drug reactions and therapeutic failures. A limited number of CYP2C19 single nucleotide polymorphisms (SNPs) are involved in drug metabolism. Extracellular vesicles (EVs) are circular membrane fragments released from the endosomal compartment as exosomes are shed from the surfaces of the membranes of most cell types. Increasing evidence indicated that EVs play a pivotal role in cell-to-cell communication. Theses EVs may play an important role between sleep, epilepsy, and treatments. The discovery of exosomes provides potential strategies for the diagnosis and treatment of many diseases including neurocognitive deficit. The aim of this study is to better understand and provide further knowledge about the metabolism and interactions between phenobarbital and CYP2C19 polymorphisms in children with epilepsy, interplay between sleep, and EVs. Understanding this interplay between epilepsy and sleep is helpful in the optimal treatment of all patients with epileptic seizures. The use of genetics and extracellular vesicles as precision medicine for the diagnosis and treatment of children with sleep disorder will improve the prognosis and the quality of life in patients with epilepsy.

Diagnostic implications of genetic copy number variation in epilepsy plus

OBJECTIVE

Copy number variations (CNVs) represent a significant genetic risk for several neurodevelopmental disorders including epilepsy. As knowledge increases, reanalysis of existing data is essential. Reliable estimates of the contribution of CNVs to epilepsies from sizeable populations are not available.

METHODS

We assembled a cohort of 1255 patients with preexisting array comparative genomic hybridization or single nucleotide polymorphism array based CNV data. All patients had "epilepsy plus," defined as epilepsy with comorbid features, including intellectual disability, psychiatric symptoms, and other neurological and nonneurological features. CNV classification was conducted using a systematic filtering workflow adapted to epilepsy.

RESULTS

Of 1097 patients remaining after genetic data quality control, 120 individuals (10.9%) carried at least one autosomal CNV classified as pathogenic; 19 individuals (1.7%) carried at least one autosomal CNV classified as possibly pathogenic. Eleven patients (1%) carried more than one (possibly) pathogenic CNV. We identified CNVs covering recently reported (HNRNPU) or emerging (RORB) epilepsy genes, and further delineated the phenotype associated with mutations of these genes. Additional novel epilepsy candidate genes emerge from our study. Comparing phenotypic features of pathogenic CNV carriers to those of noncarriers of pathogenic CNVs, we show that patients with nonneurological comorbidities, especially dysmorphism, were more likely to carry pathogenic CNVs (odds ratio = 4.09, confidence interval = 2.51-6.68; P = 2.34 × 10-9 ). Meta-analysis including data from published control groups showed that the presence or absence of epilepsy did not affect the detected frequency of CNVs.

SIGNIFICANCE

The use of a specifically adapted workflow enabled identification of pathogenic autosomal CNVs in 10.9% of patients with epilepsy plus, which rose to 12.7% when we also considered possibly pathogenic CNVs. Our data indicate that epilepsy with comorbid features should be considered an indication for patients to be selected for a diagnostic algorithm including CNV detection. Collaborative large-scale CNV reanalysis leads to novel declaration of pathogenicity in unexplained cases and can promote discovery of promising candidate epilepsy genes.

Diagnostic yield of genetic tests in epilepsy: A meta-analysis and cost-effectiveness study

OBJECTIVE

To compare the cost-effectiveness of genetic testing strategies in patients with epilepsy of unknown etiology.

METHODS

This meta-analysis and cost-effectiveness study compared strategies involving 3 genetic tests: chromosomal microarray (CMA), epilepsy panel (EP) with deletion/duplication testing, and whole-exome sequencing (WES) in a cost-effectiveness model, using "no genetic testing" as a point of comparison.

RESULTS

Twenty studies provided information on the diagnostic yield of CMA (8 studies), EP (9 studies), and WES (6 studies). The diagnostic yield was highest for WES: 0.45 (95% confidence interval [CI]: 0.33-0.57) (0.32 [95% CI: 0.22-0.44] adjusting for potential publication bias), followed by EP: 0.23 (95% CI: 0.18-0.29), and CMA: 0.08 (95% CI: 0.06-0.12). The most cost-effective test was WES with an incremental cost-effectiveness ratio (ICER) of $15,000/diagnosis. However, after adjusting for potential publication bias, the most cost-effective test was EP (ICER: $15,848/diagnosis) followed by WES (ICER: $34,500/diagnosis). Among combination strategies, the most cost-effective strategy was WES, then if nondiagnostic, EP, then if nondiagnostic, CMA (ICER: $15,336/diagnosis), although adjusting for potential publication bias, the most cost-effective strategy was EP ± CMA ± WES (ICER: $18,385/diagnosis). While the cost-effectiveness of individual tests and testing strategies overlapped, CMA was consistently less cost-effective than WES and EP.

CONCLUSION

WES and EP are the most cost-effective genetic tests for epilepsy. Our analyses support, for a broad population of patients with unexplained epilepsy, starting with these tests. Although less expensive, CMA has lower yield, and its use as the first-tier test is thus not supported from a cost-effectiveness perspective.

Copy number variants implicate cardiac function and development pathways in earthquake-induced stress cardiomyopathy

The pathophysiology of stress cardiomyopathy (SCM), also known as takotsubo syndrome, is poorly understood. SCM usually occurs sporadically, often in association with a stressful event, but clusters of cases are reported after major natural disasters. There is some evidence that this is a familial condition. We have examined three possible models for an underlying genetic predisposition to SCM. Our primary study cohort consists of 28 women who suffered SCM as a result of two devastating earthquakes that struck the city of Christchurch, New Zealand, in 2010 and 2011. To seek possible underlying genetic factors we carried out exome analysis, genotyping array analysis, and array comparative genomic hybridization on these subjects. The most striking finding was the observation of a markedly elevated rate of rare, heterogeneous copy number variants (CNV) of uncertain clinical significance (in 12/28 subjects). Several of these CNVs impacted on genes of cardiac relevance including RBFOX1, GPC5, KCNRG, CHODL, and GPBP1L1. There is no physical overlap between the CNVs, and the genes they impact do not appear to be functionally related. The recognition that SCM predisposition may be associated with a high rate of rare CNVs offers a novel perspective on this enigmatic condition.

Global characterization of copy number variants in epilepsy patients from whole genome sequencing

Epilepsy will affect nearly 3% of people at some point during their lifetime. Previous copy number variants (CNVs) studies of epilepsy have used array-based technology and were restricted to the detection of large or exonic events. In contrast, whole-genome sequencing (WGS) has the potential to more comprehensively profile CNVs but existing analytic methods suffer from limited accuracy. We show that this is in part due to the non-uniformity of read coverage, even after intra-sample normalization. To improve on this, we developed PopSV, an algorithm that uses multiple samples to control for technical variation and enables the robust detection of CNVs. Using WGS and PopSV, we performed a comprehensive characterization of CNVs in 198 individuals affected with epilepsy and 301 controls. For both large and small variants, we found an enrichment of rare exonic events in epilepsy patients, especially in genes with predicted loss-of-function intolerance. Notably, this genome-wide survey also revealed an enrichment of rare non-coding CNVs near previously known epilepsy genes. This enrichment was strongest for non-coding CNVs located within 100 Kbp of an epilepsy gene and in regions associated with changes in the gene expression, such as expression QTLs or DNase I hypersensitive sites. Finally, we report on 21 potentially damaging events that could be associated with known or new candidate epilepsy genes. Our results suggest that comprehensive sequence-based profiling of CNVs could help explain a larger fraction of epilepsy cases.

Epileptic Encephalopathies-Clinical Syndromes and Pathophysiological Concepts

Epileptic encephalopathies account for a large proportion of the intractable early-onset epilepsies and are characterized by frequent seizures and poor developmental outcome. The epileptic encephalopathies can be loosely divided into two related groups of named syndromes. The first comprises epilepsies where continuous EEG changes directly result in cognitive and developmental dysfunction. The second includes patients where cognitive impairment is present at seizure onset and is due to the underlying etiology but the epileptic activity may then worsen the cognitive abilities over time. Recent, large-scale exome studies have begun to establish the genetic architecture of the epileptic encephalopathies, resulting in a re-consideration of the boundaries of these named syndromes. The emergence of this genetic architecture has lead to three main pathophysiological concepts to provide a mechanistic framework for these disorders. In this article, we will review the classic syndromes, the most significant genetic findings, and relate both to the pathophysiological understanding of epileptic encephalopathies.

Progress from genome-wide association studies and copy number variant studies in epilepsy

PURPOSE OF REVIEW

The pace of gene discovery in epilepsy remains frenetic. Although most recent discoveries have come from next-generation sequencing studies, there has also been important progress using more established methodologies, such as genome-wide association studies (GWASs) and copy number variants (CNVs) identified through array-based techniques. Progress in these areas over the last year is reviewed.

RECENT FINDINGS

The first meta-analysis of GWASs was a landmark development for the epilepsy community, though more sizeable studies are sorely needed. Other GWASs point to potentially interesting discoveries, and are in need of replication and follow-up. Copy number variation is emerging as an important genetic contribution to causation across a wide range of epilepsies, with a number of discoveries in epilepsies from the common, such as genetic generalized epilepsies, to the individually comparatively rare, such as particular epileptic encephalopathies. The first studies of CNV analysis from next-generation sequencing data, and of the combination of sequencing and array-based data, have also emerged, allowing more comprehensive genetic evaluation of specific phenotypes.

SUMMARY

GWASs based on single nucleotide polymorphisms, and CNV analyses based on a variety of data sources, retain a place in the discovery of causation and susceptibility in the epilepsies, and will probably become more powerful in the near future through the use of large-scale next-generation sequencing studies. There are still discoveries to come through these routes.

Genetic screening and diagnosis in epilepsy?

PURPOSE OF REVIEW

Genetic discovery has been extremely rapid over the last year, with many new discoveries illuminating novel mechanisms and pathways. In particular, the application of whole exome and whole genome sequencing has identified many new genetic causes of the epilepsies. As such methods become increasingly available, it will be critical for practicing neurologists to be acquainted with them. This review surveys some important developments over the last year.

RECENT FINDINGS

The range of tests available to the clinician is wide, and likely soon to be dominated by whole exome and whole genome sequencing. Both whole exome and whole genome sequencing have usually proven to be more powerful than most existing tests. Many new genes have been implicated in the epilepsies, with emerging evidence of the involvement of particular multigene pathways.

SUMMARY

For the practicing clinician, it will be important to appreciate progress in the field, and to prepare for the application of novel genetic testing in clinical practice, as genetic data are likely to contribute importantly for many people with epilepsy.

A roadmap for precision medicine in the epilepsies

Technological advances have paved the way for accelerated genomic discovery and are bringing precision medicine clearly into view. Epilepsy research in particular is well suited to serve as a model for the development and deployment of targeted therapeutics in precision medicine because of the rapidly expanding genetic knowledge base in epilepsy, the availability of good in-vitro and in-vivo model systems to efficiently study the biological consequences of genetic mutations, the ability to turn these models into effective drug-screening platforms, and the establishment of collaborative research groups. Moving forward, it is crucial that these collaborations are strengthened, particularly through integrated research platforms, to provide robust analyses both for accurate personal genome analysis and gene and drug discovery. Similarly, the implementation of clinical trial networks will allow the expansion of patient sample populations with genetically defined epilepsy so that drug discovery can be translated into clinical practice.

Burden analysis of rare microdeletions suggests a strong impact of neurodevelopmental genes in genetic generalised epilepsies

Genetic generalised epilepsy (GGE) is the most common form of genetic epilepsy, accounting for 20% of all epilepsies. Genomic copy number variations (CNVs) constitute important genetic risk factors of common GGE syndromes. In our present genome-wide burden analysis, large (≥ 400 kb) and rare (< 1%) autosomal microdeletions with high calling confidence (≥ 200 markers) were assessed by the Affymetrix SNP 6.0 array in European case-control cohorts of 1,366 GGE patients and 5,234 ancestry-matched controls. We aimed to: 1) assess the microdeletion burden in common GGE syndromes, 2) estimate the relative contribution of recurrent microdeletions at genomic rearrangement hotspots and non-recurrent microdeletions, and 3) identify potential candidate genes for GGE. We found a significant excess of microdeletions in 7.3% of GGE patients compared to 4.0% in controls (P = 1.8 x 10-7; OR = 1.9). Recurrent microdeletions at seven known genomic hotspots accounted for 36.9% of all microdeletions identified in the GGE cohort and showed a 7.5-fold increased burden (P = 2.6 x 10-17) relative to controls. Microdeletions affecting either a gene previously implicated in neurodevelopmental disorders (P = 8.0 x 10-18, OR = 4.6) or an evolutionarily conserved brain-expressed gene related to autism spectrum disorder (P = 1.3 x 10-12, OR = 4.1) were significantly enriched in the GGE patients. Microdeletions found only in GGE patients harboured a high proportion of genes previously associated with epilepsy and neuropsychiatric disorders (NRXN1, RBFOX1, PCDH7, KCNA2, EPM2A, RORB, PLCB1). Our results demonstrate that the significantly increased burden of large and rare microdeletions in GGE patients is largely confined to recurrent hotspot microdeletions and microdeletions affecting neurodevelopmental genes, suggesting a strong impact of fundamental neurodevelopmental processes in the pathogenesis of common GGE syndromes.

Identification of structural variation in mouse genomes

Structural variation is variation in structure of DNA regions affecting DNA sequence length and/or orientation. It generally includes deletions, insertions, copy-number gains, inversions, and transposable elements. Traditionally, the identification of structural variation in genomes has been challenging. However, with the recent advances in high-throughput DNA sequencing and paired-end mapping (PEM) methods, the ability to identify structural variation and their respective association to human diseases has improved considerably. In this review, we describe our current knowledge of structural variation in the mouse, one of the prime model systems for studying human diseases and mammalian biology. We further present the evolutionary implications of structural variation on transposable elements. We conclude with future directions on the study of structural variation in mouse genomes that will increase our understanding of molecular architecture and functional consequences of structural variation.