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Abstract
As the genetic etiologies of an expanding number of epilepsy syndromes are revealed, the complexity of the phenotype genotype correlation increases. As our review will show, multiple gene mutations cause different epilepsy syndromes, making identification of the specific mutation increasingly more important for prognostication and often more directed treatment. Examples of that include the need to avoid specific drugs in Dravet syndrome and the ongoing investigations of the potential use of new directed therapies such as retigabine in KCNQ2-related epilepsies, quinidine in KCNT1-related epilepsies, and memantine in GRIN2A-related epilepsies.
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Affiliation(s)
- Abeer J Hani
- Division of Pediatric Neurology, Department of Pediatrics, Duke Children's Hospital and Health Center, Suite T0913J, 2301 Erwin Road, Durham, NC 27710, USA
| | - Husam M Mikati
- Center of Human Genome Variation, LSRC, Duke University School of Medicine, 201 Trent Drive, Durham, NC 27710, USA
| | - Mohamad A Mikati
- Division of Pediatric Neurology, Department of Pediatrics, Duke Children's Hospital and Health Center, Suite T0913J, 2301 Erwin Road, Durham, NC 27710, USA.
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52
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A statistical approach for rare-variant association testing in affected sibships. Am J Hum Genet 2015; 96:543-54. [PMID: 25799106 DOI: 10.1016/j.ajhg.2015.01.020] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 01/30/2015] [Indexed: 11/21/2022] Open
Abstract
Sequencing and exome-chip technologies have motivated development of novel statistical tests to identify rare genetic variation that influences complex diseases. Although many rare-variant association tests exist for case-control or cross-sectional studies, far fewer methods exist for testing association in families. This is unfortunate, because cosegregation of rare variation and disease status in families can amplify association signals for rare variants. Many researchers have begun sequencing (or genotyping via exome chips) familial samples that were either recently collected or previously collected for linkage studies. Because many linkage studies of complex diseases sampled affected sibships, we propose a strategy for association testing of rare variants for use in this study design. The logic behind our approach is that rare susceptibility variants should be found more often on regions shared identical by descent by affected sibling pairs than on regions not shared identical by descent. We propose both burden and variance-component tests of rare variation that are applicable to affected sibships of arbitrary size and that do not require genotype information from unaffected siblings or independent controls. Our approaches are robust to population stratification and produce analytic p values, thereby enabling our approach to scale easily to genome-wide studies of rare variation. We illustrate our methods by using simulated data and exome chip data from sibships ascertained for hypertension collected as part of the Genetic Epidemiology Network of Arteriopathy (GENOA) study.
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53
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Rackham OJL, Shihab HA, Johnson MR, Petretto E. EvoTol: a protein-sequence based evolutionary intolerance framework for disease-gene prioritization. Nucleic Acids Res 2014; 43:e33. [PMID: 25550428 PMCID: PMC4357693 DOI: 10.1093/nar/gku1322] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Methods to interpret personal genome sequences are increasingly required. Here, we report a novel framework (EvoTol) to identify disease-causing genes using patient sequence data from within protein coding-regions. EvoTol quantifies a gene's intolerance to mutation using evolutionary conservation of protein sequences and can incorporate tissue-specific gene expression data. We apply this framework to the analysis of whole-exome sequence data in epilepsy and congenital heart disease, and demonstrate EvoTol's ability to identify known disease-causing genes is unmatched by competing methods. Application of EvoTol to the human interactome revealed networks enriched for genes intolerant to protein sequence variation, informing novel polygenic contributions to human disease.
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Affiliation(s)
- Owen J L Rackham
- Medical Research Council (MRC) Clinical Sciences Centre, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK
| | - Hashem A Shihab
- The Medical Research Council Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Michael R Johnson
- Division of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, London W12 0NN, UK
| | - Enrico Petretto
- Medical Research Council (MRC) Clinical Sciences Centre, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK Duke-NUS Graduate Medical School, 8 College Road, Singapore 169857, Singapore
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54
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Katsonis P, Koire A, Wilson SJ, Hsu TK, Lua RC, Wilkins AD, Lichtarge O. Single nucleotide variations: biological impact and theoretical interpretation. Protein Sci 2014; 23:1650-66. [PMID: 25234433 PMCID: PMC4253807 DOI: 10.1002/pro.2552] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Revised: 09/12/2014] [Accepted: 09/15/2014] [Indexed: 12/27/2022]
Abstract
Genome-wide association studies (GWAS) and whole-exome sequencing (WES) generate massive amounts of genomic variant information, and a major challenge is to identify which variations drive disease or contribute to phenotypic traits. Because the majority of known disease-causing mutations are exonic non-synonymous single nucleotide variations (nsSNVs), most studies focus on whether these nsSNVs affect protein function. Computational studies show that the impact of nsSNVs on protein function reflects sequence homology and structural information and predict the impact through statistical methods, machine learning techniques, or models of protein evolution. Here, we review impact prediction methods and discuss their underlying principles, their advantages and limitations, and how they compare to and complement one another. Finally, we present current applications and future directions for these methods in biological research and medical genetics.
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Affiliation(s)
- Panagiotis Katsonis
- Department of Molecular and Human Genetics, Baylor College of MedicineHouston, Texas
| | - Amanda Koire
- Department of Structural and Computational Biology and Molecular BiophysicsHouston, Texas
| | - Stephen Joseph Wilson
- Department of Biochemistry and Molecular Biology, Baylor College of MedicineHouston, Texas
| | - Teng-Kuei Hsu
- Department of Biochemistry and Molecular Biology, Baylor College of MedicineHouston, Texas
| | - Rhonald C Lua
- Department of Molecular and Human Genetics, Baylor College of MedicineHouston, Texas
| | - Angela Dawn Wilkins
- Department of Molecular and Human Genetics, Baylor College of MedicineHouston, Texas
- Computational and Integrative Biomedical Research Center, Baylor College of MedicineHouston, Texas
| | - Olivier Lichtarge
- Department of Molecular and Human Genetics, Baylor College of MedicineHouston, Texas
- Department of Structural and Computational Biology and Molecular BiophysicsHouston, Texas
- Department of Biochemistry and Molecular Biology, Baylor College of MedicineHouston, Texas
- Computational and Integrative Biomedical Research Center, Baylor College of MedicineHouston, Texas
- Department of Pharmacology, Baylor College of MedicineHouston, Texas
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55
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Busch RM. Comments on Motamedi G, Meador K. Epilepsy and cognition. Epilepsy & behavior 2003;4:S25-S28. Epilepsy Behav 2014; 40:26-8. [PMID: 25307191 PMCID: PMC4391193 DOI: 10.1016/j.yebeh.2014.08.021] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Accepted: 08/10/2014] [Indexed: 01/08/2023]
Affiliation(s)
- Robyn M Busch
- Cleveland Clinic Epilepsy Center, 9500 Euclid Avenue, P57, Cleveland, OH 44195, USA.
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56
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Olson HE, Poduri A, Pearl PL. Genetic forms of epilepsies and other paroxysmal disorders. Semin Neurol 2014; 34:266-79. [PMID: 25192505 DOI: 10.1055/s-0034-1386765] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Genetic mechanisms explain the pathophysiology of many forms of epilepsy and other paroxysmal disorders, such as alternating hemiplegia of childhood, familial hemiplegic migraine, and paroxysmal dyskinesias. Epilepsy is a key feature of well-defined genetic syndromes including tuberous sclerosis complex, Rett syndrome, Angelman syndrome, and others. There is an increasing number of single-gene causes or susceptibility factors associated with several epilepsy syndromes, including the early-onset epileptic encephalopathies, benign neonatal/infantile seizures, progressive myoclonus epilepsies, genetic generalized and benign focal epilepsies, epileptic aphasias, and familial focal epilepsies. Molecular mechanisms are diverse, and a single gene can be associated with a broad range of phenotypes. Additional features, such as dysmorphisms, head size, movement disorders, and family history may provide clues to a genetic diagnosis. Genetic testing can impact medical care and counseling. We discuss genetic mechanisms of epilepsy and other paroxysmal disorders, tools and indications for genetic testing, known genotype-phenotype associations, the importance of genetic counseling, and a look toward the future of epilepsy genetics.
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Affiliation(s)
- Heather E Olson
- Division of Epilepsy, Department of Neurology, Boston Children's Hospital, Boston, Massachusetts
| | - Annapurna Poduri
- Division of Epilepsy, Department of Neurology, Boston Children's Hospital, Boston, Massachusetts
| | - Phillip L Pearl
- Division of Epilepsy, Department of Neurology, Boston Children's Hospital, Boston, Massachusetts
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Epi4K Phase I: Gene Discovery in Epileptic Encephalopathies by Exome Sequencing. Epilepsy Curr 2014; 14:208-10. [PMID: 25170321 DOI: 10.5698/1535-7597-14.4.208] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
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58
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Abstract
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.
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Du X, An Y, Yu L, Liu R, Qin Y, Guo X, Sun D, Zhou S, Wu B, Jiang YH, Wang Y. A genomic copy number variant analysis implicates the MBD5 and HNRNPU genes in Chinese children with infantile spasms and expands the clinical spectrum of 2q23.1 deletion. BMC MEDICAL GENETICS 2014; 15:62. [PMID: 24885232 PMCID: PMC4061518 DOI: 10.1186/1471-2350-15-62] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2014] [Accepted: 05/13/2014] [Indexed: 02/06/2023]
Abstract
Background Infantile spasms (IS) is a specific type of epileptic encephalopathy associated with severe developmental disabilities. Genetic factors are strongly implicated in IS, however, the exact genetic defects remain unknown in the majority of cases. Rare mutations in a single gene or in copy number variants (CNVs) have been implicated in IS of children in Western countries. The objective of this study was to dissect the role of copy number variations in Chinese children with infantile spasms. Methods We used the Agilent Human Genome CGH microarray 180 K for genome-wide detection of CNVs. Real-time qPCR was used to validate the CNVs. We performed genomic and medical annotations for individual CNVs to determine the pathogenicity of CNVs related to IS. Results We report herein the first genome-wide CNV analysis in children with IS, detecting a total of 14 CNVs in a cohort of 47 Chinese children with IS. Four CNVs (4/47 = 8.5%) (1q21.1 gain; 1q44, 2q31.1, and 17p13 loss) are considered to be pathogenic. The CNV loss at 17p13.3 contains PAFAH1B1 (LIS1), a causative gene for lissencephaly. Although the CNVs at 1q21.1, 1q44, and 2q23.1 have been previously implicated in a wide spectrum of clinical features including autism spectrum disorders (ASD) and generalized seizure, our study is the first report identifying them in individuals with a primary diagnosis of IS. The CNV loss in the 1q44 region contains HNRNPU, a strong candidate gene recently suggested in IS by the whole exome sequencing of children with IS. The CNV loss at 2q23.1 includes MBD5, a methyl-DNA binding protein that is a causative gene of ASD and a candidate gene for epileptic encephalopathy. We also report a distinct clinical presentation of IS, microcephaly, intellectual disability, and absent hallux in a case with the 2q23.1 deletion. Conclusion Our findings strongly support the role of CNVs in infantile spasms and expand the clinical spectrum associate with 2q23.1 deletion. In particular, our study implicates the HNRNPU and MBD5 genes in Chinese children with IS. Our study also supports that the molecular mechanisms of infantile spasms appear conserved among different ethnic backgrounds.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Yong-Hui Jiang
- Division of Neurology, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai 201102, China.
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Poduri A. DEPDC5 does it all: shared genetics for diverse epilepsy syndromes. Ann Neurol 2014; 75:631-3. [PMID: 24753000 DOI: 10.1002/ana.24160] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2014] [Revised: 04/13/2014] [Accepted: 04/17/2014] [Indexed: 01/14/2023]
Affiliation(s)
- Annapurna Poduri
- Epilepsy Genetics Program, Division of Epilepsy and Clinical Neurophysiology Department of Neurology, Boston Children's Hospital, Boston, MA
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61
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Peljto AL, Barker-Cummings C, Vasoli VM, Leibson CL, Hauser WA, Buchhalter JR, Ottman R. Familial risk of epilepsy: a population-based study. ACTA ACUST UNITED AC 2014; 137:795-805. [PMID: 24468822 DOI: 10.1093/brain/awt368] [Citation(s) in RCA: 105] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Almost all previous studies of familial risk of epilepsy have had potentially serious methodological limitations. Our goal was to address these limitations and provide more rigorous estimates of familial risk in a population-based study. We used the unique resources of the Rochester Epidemiology Project to identify all 660 Rochester, Minnesota residents born in 1920 or later with incidence of epilepsy from 1935-94 (probands) and their 2439 first-degree relatives who resided in Olmsted County. We assessed incidence of epilepsy in relatives by comprehensive review of the relatives' medical records, and estimated age-specific cumulative incidence and standardized incidence ratios for epilepsy in relatives compared with the general population, according to proband and relative characteristics. Among relatives of all probands, cumulative incidence of epilepsy to age 40 was 4.7%, and risk was increased 3.3-fold (95% confidence interval 2.75-5.99) compared with population incidence. Risk was increased to the greatest extent in relatives of probands with idiopathic generalized epilepsies (standardized incidence ratio 6.0) and epilepsies associated with intellectual or motor disability presumed present from birth, which we denoted 'prenatal/developmental cause' (standardized incidence ratio 4.3). Among relatives of probands with epilepsy without identified cause (including epilepsies classified as 'idiopathic' or 'unknown cause'), risk was significantly increased for epilepsy of prenatal/developmental cause (standardized incidence ratio 4.1). Similarly, among relatives of probands with prenatal/developmental cause, risk was significantly increased for epilepsies without identified cause (standardized incidence ratio 3.8). In relatives of probands with generalized epilepsy, standardized incidence ratios were 8.3 (95% confidence interval 2.93-15.31) for generalized epilepsy and 2.5 (95% confidence interval 0.92-4.00) for focal epilepsy. In relatives of probands with focal epilepsy, standardized incidence ratios were 1.0 (95% confidence interval 0.00-2.19) for generalized epilepsy and 2.6 (95% confidence interval 1.19-4.26) for focal epilepsy. Epilepsy incidence was greater in offspring of female probands than in offspring of male probands, and this maternal effect was restricted to offspring of probands with focal epilepsy. The results suggest that risks for epilepsies of unknown and prenatal/developmental cause may be influenced by shared genetic mechanisms. They also suggest that some of the genetic influences on generalized and focal epilepsies are distinct. However, the similar increase in risk for focal epilepsy among relatives of probands with either generalized (2.5-fold) or focal epilepsy (2.6-fold) may reflect some coexisting shared genetic influences.
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Affiliation(s)
- Anna L Peljto
- 1 Department of Epidemiology, School of Public Health, University of Colorado Denver, Aurora, Colorado 80045, USA
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62
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Abstract
Genomic tools have evolved with remarkable rapidity, but their clinical relevance and application have lagged behind. Now, consistent clinical applications have finally arrived and bring with them the promise of identifying the underlying causes of complex neurological disorders in a patient-specific manner.
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Affiliation(s)
- Norman Delanty
- Department of Neurology, Beaumont Hospital, Royal College of Surgeons, Dublin 9, Ireland.
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63
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Chukwu J, Delanty N, Webb D, Cavalleri GL. Weight change, genetics and antiepileptic drugs. Expert Rev Clin Pharmacol 2013; 7:43-51. [PMID: 24308788 DOI: 10.1586/17512433.2014.857599] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Weight gain caused by antiepileptic drugs (AEDs) constitutes a serious problem in the management of people with epilepsy. AEDs associated with weight gain include sodium valproate, pregabalin and vigabatrin. Excessive weight gain can lead to non-compliance with treatment and to an exacerbation of obesity-related conditions. The mechanisms by which AEDs cause weight gain are not fully understood. It is likely that weight change induced by some AEDs has a genetic underpinning, and recent developments in DNA sequencing technology should speed the understanding, prediction and thus prevention of serious weight change associated with AEDs. This review focuses on the biology of obesity in the context of AEDs. Future directions in the investigations of the mechanism of weight change associated with these drugs and the use of such knowledge in tailoring the treatment of specific patient groups are explored.
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Affiliation(s)
- Joseph Chukwu
- Department of Paediatric Neurology, Our Lady's Hospital for Sick Children, Crumlin, Ireland
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Widdess-Walsh P, Dlugos D, Fahlstrom R, Joshi S, Shellhaas R, Boro A, Sullivan J, Geller E. Lennox-Gastaut syndrome of unknown cause: Phenotypic characteristics of patients in the Epilepsy Phenome/Genome Project. Epilepsia 2013; 54:1898-904. [DOI: 10.1111/epi.12395] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/26/2013] [Indexed: 11/29/2022]
Affiliation(s)
- Peter Widdess-Walsh
- Institute of Neurology and Neurosurgery at St. Barnabas; Livingston New Jersey U.S.A
| | - Dennis Dlugos
- Departments of Neurology and Pediatrics; The Children's Hospital of Philadelphia; Philadelphia Pennsylvania U.S.A
| | - Robyn Fahlstrom
- Department of Neurology; University of California; San Francisco California U.S.A
| | - Sucheta Joshi
- Department of Pediatrics & Communicable Diseases; University of Michigan; Ann Arbor Michigan U.S.A
| | - Renée Shellhaas
- Department of Pediatrics & Communicable Diseases; University of Michigan; Ann Arbor Michigan U.S.A
| | - Alex Boro
- Department of Neurology; Montefiore Medical Center; New York New York U.S.A
| | - Joseph Sullivan
- Department of Neurology; University of California; San Francisco California U.S.A
| | - Eric Geller
- Institute of Neurology and Neurosurgery at St. Barnabas; Livingston New Jersey U.S.A
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65
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Abstract
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.
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66
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Veeramah KR, Johnstone L, Karafet TM, Wolf D, Sprissler R, Salogiannis J, Barth-Maron A, Greenberg ME, Stuhlmann T, Weinert S, Jentsch T, Pazzi M, Restifo LL, Talwar D, Erickson RP, Hammer MF. Exome sequencing reveals new causal mutations in children with epileptic encephalopathies. Epilepsia 2013; 54:1270-81. [PMID: 23647072 PMCID: PMC3700577 DOI: 10.1111/epi.12201] [Citation(s) in RCA: 226] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/19/2013] [Indexed: 02/06/2023]
Abstract
PURPOSE The management of epilepsy in children is particularly challenging when seizures are resistant to antiepileptic medications, or undergo many changes in seizure type over time, or have comorbid cognitive, behavioral, or motor deficits. Despite efforts to classify such epilepsies based on clinical and electroencephalographic criteria, many children never receive a definitive etiologic diagnosis. Whole exome sequencing (WES) is proving to be a highly effective method for identifying de novo variants that cause neurologic disorders, especially those associated with abnormal brain development. Herein we explore the utility of WES for identifying candidate causal de novo variants in a cohort of children with heterogeneous sporadic epilepsies without etiologic diagnoses. METHODS We performed WES (mean coverage approximately 40×) on 10 trios comprised of unaffected parents and a child with sporadic epilepsy characterized by difficult-to-control seizures and some combination of developmental delay, epileptic encephalopathy, autistic features, cognitive impairment, or motor deficits. Sequence processing and variant calling were performed using standard bioinformatics tools. A custom filtering system was used to prioritize de novo variants of possible functional significance for validation by Sanger sequencing. KEY FINDINGS In 9 of 10 probands, we identified one or more de novo variants predicted to alter protein function, for a total of 15. Four probands had de novo mutations in genes previously shown to harbor heterozygous mutations in patients with severe, early onset epilepsies (two in SCN1A, and one each in CDKL5 and EEF1A2). In three children, the de novo variants were in genes with functional roles that are plausibly relevant to epilepsy (KCNH5, CLCN4, and ARHGEF15). The variant in KCNH5 alters one of the highly conserved arginine residues of the voltage sensor of the encoded voltage-gated potassium channel. In vitro analyses using cell-based assays revealed that the CLCN4 mutation greatly impaired ion transport by the ClC-4 2Cl(-) /H(+) -exchanger and that the mutation in ARHGEF15 reduced GEF exchange activity of the gene product, Ephexin5, by about 50%. Of interest, these seven probands all presented with seizures within the first 6 months of life, and six of these have intractable seizures. SIGNIFICANCE The finding that 7 of 10 children carried de novo mutations in genes of known or plausible clinical significance to neuronal excitability suggests that WES will be of use for the molecular genetic diagnosis of sporadic epilepsies in children, especially when seizures are of early onset and difficult to control.
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Affiliation(s)
- Krishna R Veeramah
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, 85721, USA
| | - Laurel Johnstone
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, 85721, USA
| | - Tatiana M Karafet
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, 85721, USA
| | - Daniel Wolf
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, 85721, USA
| | - Ryan Sprissler
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, 85721, USA
| | - John Salogiannis
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Asa Barth-Maron
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | | | - Till Stuhlmann
- Leibniz-Institut für Molekulare Pharmakologie (FMP) and Max-Delbrück-Centrum für Molekulare Medizin (MDC), 13125 Berlin, Germany
| | - Stefanie Weinert
- Leibniz-Institut für Molekulare Pharmakologie (FMP) and Max-Delbrück-Centrum für Molekulare Medizin (MDC), 13125 Berlin, Germany
| | - Thomas Jentsch
- Leibniz-Institut für Molekulare Pharmakologie (FMP) and Max-Delbrück-Centrum für Molekulare Medizin (MDC), 13125 Berlin, Germany
| | | | - Linda L Restifo
- Department of Neurology, Arizona Health Science Center, Tucson AZ 85724, USA
- Department of Neuroscience, University of Arizona, Tucson, AZ 85821, USA
- Department of Cellular & Molecular Medicine, Arizona Health Science Center, Tucson, AZ 85724, USA
| | - Dinesh Talwar
- Center for Neurosciences, Tucson, AZ 85718, USA
- Department of Neurology, Arizona Health Science Center, Tucson AZ 85724, USA
- Department of Pediatrics, Arizona Health Science Center, Tucson AZ 85724, USA
| | - Robert P Erickson
- Department of Pediatrics, Arizona Health Science Center, Tucson AZ 85724, USA
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA
| | - Michael F Hammer
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ, 85721, USA
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67
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Affiliation(s)
- M J Keogh
- James Cook University Hospital, , Middlesbrough, UK
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68
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Unraveling the genetics of common epilepsies: approaches, platforms, and caveats. Epilepsy Behav 2013; 26:229-33. [PMID: 23103323 DOI: 10.1016/j.yebeh.2012.09.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2012] [Accepted: 09/13/2012] [Indexed: 11/21/2022]
Abstract
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.
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Jones NC, O'Brien TJ. Stress, epilepsy, and psychiatric comorbidity: how can animal models inform the clinic? Epilepsy Behav 2013; 26:363-9. [PMID: 23099287 DOI: 10.1016/j.yebeh.2012.09.002] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2012] [Accepted: 09/06/2012] [Indexed: 12/15/2022]
Abstract
Psychiatric complaints afflict many patients with epilepsy, and these contribute significantly to the impaired quality of life experienced by sufferers of this common group of neurological conditions. Psychiatric disorders in epilepsy patients are under-diagnosed and under-treated. Moreover, evidence suggests that the psychiatric disorders may act as risk factors for some types of epilepsy and exacerbate disease progression in established cases, promoting the case for a bidirectional relationship between epilepsy and psychopathology. While cause and effect relationships can be difficult to establish in human studies, appropriate animal models provide valuable tools with which to study the interactions between epilepsy and stress-related disorders. Indeed, many epilepsy models exhibit behavioral phenotypes which are reflective of psychiatric disorders, and, conversely, stressful environments appear to promote a vulnerability to developing epilepsy. This review summarizes this research area, exploring the behavioral phenotypes in animal models of epilepsy and then examining the influence of stressful environments on susceptibility to seizures and epilepsy. The ultimate goal of this line of research is to be able to translate these findings to humans. Understanding the relationships between epilepsy and associated psychiatric disorders will facilitate effective treatment of mood disorders in epilepsy, inform about the pathophysiology of each individually, and potentially open up novel therapeutic disease-modifying strategies for patients with epilepsy.
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Affiliation(s)
- Nigel C Jones
- Department of Medicine (Royal Melbourne Hospital), Melbourne Brain Centre, University of Melbourne, Parkville, VIC, Australia.
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Heinzen E, Depondt C, Cavalleri G, Ruzzo E, Walley N, Need A, Ge D, He M, Cirulli E, Zhao Q, Cronin K, Gumbs C, Campbell C, Hong L, Maia J, Shianna K, McCormack M, Radtke R, O'Conner G, Mikati M, Gallentine W, Husain A, Sinha S, Chinthapalli K, Puranam R, McNamara J, Ottman R, Sisodiya S, Delanty N, Goldstein D. Exome sequencing followed by large-scale genotyping fails to identify single rare variants of large effect in idiopathic generalized epilepsy. Am J Hum Genet 2012; 91:293-302. [PMID: 22863189 DOI: 10.1016/j.ajhg.2012.06.016] [Citation(s) in RCA: 74] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2012] [Revised: 03/30/2012] [Accepted: 06/26/2012] [Indexed: 10/28/2022] Open
Abstract
Idiopathic generalized epilepsy (IGE) is a complex disease with high heritability, but little is known about its genetic architecture. Rare copy-number variants have been found to explain nearly 3% of individuals with IGE; however, it remains unclear whether variants with moderate effect size and frequencies below what are reliably detected with genome-wide association studies contribute significantly to disease risk. In this study, we compare the exome sequences of 118 individuals with IGE and 242 controls of European ancestry by using next-generation sequencing. The exome-sequenced epilepsy cases include study subjects with two forms of IGE, including juvenile myoclonic epilepsy (n = 93) and absence epilepsy (n = 25). However, our discovery strategy did not assume common genetic control between the subtypes of IGE considered. In the sequence data, as expected, no variants were significantly associated with the IGE phenotype or more specific IGE diagnoses. We then selected 3,897 candidate epilepsy-susceptibility variants from the sequence data and genotyped them in a larger set of 878 individuals with IGE and 1,830 controls. Again, no variant achieved statistical significance. However, 1,935 variants were observed exclusively in cases either as heterozygous or homozygous genotypes. It is likely that this set of variants includes real risk factors. The lack of significant association evidence of single variants with disease in this two-stage approach emphasizes the high genetic heterogeneity of epilepsy disorders, suggests that the impact of any individual single-nucleotide variant in this disease is small, and indicates that gene-based approaches might be more successful for future sequencing studies of epilepsy predisposition.
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Cavalleri GL, Delanty N. Opportunities and challenges for genome sequencing in the clinic. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2012; 89:65-83. [PMID: 23046882 DOI: 10.1016/b978-0-12-394287-6.00003-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
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.
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Affiliation(s)
- Gianpiero L Cavalleri
- Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland.
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