A case-control collapsing analysis identifies epilepsy genes implicated in trio sequencing studies focused on de novo mutations

Zhu, Xiaolin; Padmanabhan, Raghavendra; Copeland, Brett; Bridgers, Joshua; Ren, Zhong; Kamalakaran, Sitharthan; O’Driscoll-Collins, Ailbhe; Berkovic, Samuel F.; Scheffer, Ingrid E.; Poduri, Annapurna; Mei, Davide; Guerrini, Renzo; Lowenstein, Daniel H.; Allen, Andrew S.; Heinzen, Erin L.; Goldstein, David B.

doi:10.1371/journal.pgen.1007104

Cited by 26 publications

(26 citation statements)

References 34 publications

(35 reference statements)

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“…This study provided the initial evidence of the deleterious effect of variants p.Ser347Arg, p.Thr374Ile, and p.Gly379Arg on KCNB1 function. Following the initial identification of KCNB1 variants (Torkamani et al, ), 29 new KCNB1 variants have been reported in 37 patients detected through next‐generation high‐throughput sequencing in cohorts of individuals with developmental delay and/or DEE (Allen et al, ; Fitzgerald et al, ; Saitsu et al, ; Soden et al, ; Srivastava et al, ; Thiffault et al, ; Torkamani et al, ; Calhoun, Vanoye, Kok, George, & Kearney, ; de Kovel et al, ; Latypova et al, ; Marini et al, ; Miao, Peng, Chen, Gai, & Yin, , 2018; Parrini et al, ; Samanta, ; Zhu et al, ). The majority of these patients had epilepsy, intellectual disability, and behavioral problems (MIM# 616056; epileptic encephalopathy, early infantile, 26).…”

Section: Introductionmentioning

confidence: 99%

Expanding the genetic and phenotypic relevance of KCNB1 variants in developmental and epileptic encephalopathies: 27 new patients and overview of the literature

Bar

Barcia

Jennesson³

et al. 2019

Human Mutation

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Developmental and epileptic encephalopathies (DEE) refer to a heterogeneous group of devastating neurodevelopmental disorders. Variants in KCNB1 have been recently reported in patients with early‐onset DEE. KCNB1 encodes the α subunit of the delayed rectifier voltage‐dependent potassium channel Kv2.1. We review the 37 previously reported patients carrying 29 distinct KCNB1 variants and significantly expand the mutational spectrum describing 18 novel variants from 27 unreported patients. Most variants occur de novo and mainly consist of missense variants located on the voltage sensor and the pore domain of Kv2.1. We also report the first inherited variant (p.Arg583*). KCNB1‐related encephalopathies encompass a wide spectrum of neurodevelopmental disorders with predominant language difficulties and behavioral impairment. Eighty‐five percent of patients developed epilepsies with variable syndromes and prognosis. Truncating variants in the C‐terminal domain are associated with a less‐severe epileptic phenotype. Overall, this report provides an up‐to‐date review of the mutational and clinical spectrum of KCNB1, strengthening its place as a causal gene in DEEs and emphasizing the need for further functional studies to unravel the underlying mechanisms.

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Section: Introductionmentioning

confidence: 99%

Expanding the genetic and phenotypic relevance of KCNB1 variants in developmental and epileptic encephalopathies: 27 new patients and overview of the literature

Bar

Barcia

Jennesson³

et al. 2019

Human Mutation

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“…We focus on EPI because this disorder had DN and CC data, including recent rare CC variant studies 12,13 . In addition, multiple EPI genes were prioritized by gTADA.…”

Section: Resultsmentioning

confidence: 99%

“…Recently, additional risk genes have been reported by meta-analyzing DNMs and rare case-control (CC) variants, an approach that has been particularly successful for autism spectrum disorders (ASD) 9,10 . For epilepsy (EPI), multiple associated genes have been identified through DN based studies 4,5,11 , and in recent years, a number of EPI significant genes have also been identified through CC studies 12,13 . We hypothesized that, as for ASD, additional significant EPI genes could be discovered through the integration of DN and CC data.…”

Section: Introductionmentioning

confidence: 99%

Integrative analysis of rare variants and pathway information shows convergent results between immune pathways, drug targets and epilepsy genes

Dobbyn

et al. 2018

Preprint

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Trio family and case-control studies of next-generation sequencing data have proven integral to understanding the contribution of rare inherited and de novo single-nucleotide variants to the genetic architecture of complex disease. Ideally, such studies should identify individual risk genes of moderate to large effect size to generate novel treatment hypotheses for further follow-up. However, due to insufficient power, gene set enrichment analyses have come to be relied upon for detecting differences between cases and controls, implicating sets of hundreds of genes rather than specific targets for further investigation. Here, we present a Bayesian statistical framework, termed gTADA, that integrates gene-set membership information with gene-level de novo and rare inherited case-control counts, to prioritize risk genes with excess rare variant burden within enriched gene sets. Applying gTADA to available whole-exome sequencing datasets for several neuropsychiatric conditions, we replicated previously reported gene set enrichments and identified novel risk genes. For epilepsy, gTADA prioritized 40 risk genes (posterior probabilities > 0.95), 6 of which replicate in an independent whole-genome sequencing study. In addition, 30/40 genes are novel genes. We found that epilepsy genes had high protein-protein interaction (PPI) network connectivity, and show specific expression during human brain development. Some of the top prioritized EPI genes were connected to a PPI subnetwork of immune genes and show specific expression in prenatal microglia. We also identified multiple enriched drug-target gene sets for EPI which included immunostimulants as well as known antiepileptics. Immune biology was supported specifically by case-control variants from familial epilepsies rather than do novo mutations in generalized encephalitic epilepsy. meta-analyzing DNMs and rare case-control (CC) variants, an approach that has been particularly successful for autism spectrum disorders (ASD) 9,10 . For epilepsy (EPI), multiple associated genes have been identified through DN based studies 4,5,11 , and in recent years, a number of EPI significant genes have also been identified through CC studies 12,13 . We hypothesized that, as for ASD, additional significant EPI genes could be discovered through the integration of DN and CC data. EPI is a serious brain disorder which includes multiple subtypes. Studies of cases/controls and twins have shown that genetic components have played important roles in EPI [14][15][16] . Some of EPI's subtypes can be explained by single genes, but multiple subtypes might be caused by multiple genes 15 . It is still challenging to develop specific drugs for this disorder. There have been multiple antiepileptic drugs used for EPI treatments; however, 20-30% of EPI patients have not been successful in controlling their seizures by using current medications 17 . Identifying additional genes or gene sets might help better understand its etiology as well as better design drug targets for the disorder.Due to the high p...

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“…Here we investigate using LIMBR in this role. Using a cohort of 488 epileptic encephalopathy-affected case subjects and 12,151 unrelated control subjects from a previous rare variant collapsing analysis, 27 we performed a group-wise association test on the five epilepsy-associated genes mentioned above (Equation 4). 17 In the first set of tests, we assign equal weights to all variants; in the second, we weight the variants by the inverse percentile of their exon-level intolerance scores (details in Material and Methods).…”

Section: Using Sub-region Level Intolerance In Analyses Of Whether Thmentioning

confidence: 99%

Improved Pathogenic Variant Localization via a Hierarchical Model of Sub-regional Intolerance

Hayeck

Stong

Wolock

et al. 2019

The American Journal of Human Genetics

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Different parts of a gene can be of differential importance to development and health. This regional heterogeneity is also apparent in the distribution of disease-associated mutations, which often cluster in particular regions of disease-associated genes. The ability to precisely estimate functionally important sub-regions of genes will be key in correctly deciphering relationships between genetic variation and disease. Previous methods have had some success using standing human variation to characterize this variability in importance by measuring sub-regional intolerance, i.e., the depletion in functional variation from expectation within a given region of a gene. However, the ability to precisely estimate local intolerance was restricted by the fact that only information within a given sub-region is used, leading to instability in local estimates, especially for small regions. We show that borrowing information across regions using a Bayesian hierarchical model stabilizes estimates, leading to lower variability and improved predictive utility. Specifically, our approach more effectively identifies regions enriched for ClinVar pathogenic variants. We also identify significant correlations between sub-region intolerance and the distribution of pathogenic variation in disease-associated genes, with AUCs for classifying de novo missense variants in Online Mendelian Inheritance in Man (OMIM) genes of up to 0.86 using exonic sub-regions and 0.91 using sub-regions defined by protein domains. This result immediately suggests that considering the intolerance of regions in which variants are found may improve diagnostic interpretation. We also illustrate the utility of integrating regional intolerance into gene-level disease association tests with a study of known disease-associated genes for epileptic encephalopathy.

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A case-control collapsing analysis identifies epilepsy genes implicated in trio sequencing studies focused on de novo mutations

Cited by 26 publications

References 34 publications

Expanding the genetic and phenotypic relevance of KCNB1 variants in developmental and epileptic encephalopathies: 27 new patients and overview of the literature

Expanding the genetic and phenotypic relevance of KCNB1 variants in developmental and epileptic encephalopathies: 27 new patients and overview of the literature

Integrative analysis of rare variants and pathway information shows convergent results between immune pathways, drug targets and epilepsy genes

Improved Pathogenic Variant Localization via a Hierarchical Model of Sub-regional Intolerance

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