Dataset Information

Application of rare variant transmission disequilibrium tests to epileptic encephalopathy trio sequence data.

ABSTRACT: The classic epileptic encephalopathies, including infantile spasms (IS) and Lennox-Gastaut syndrome (LGS), are severe seizure disorders that usually arise sporadically. De novo variants in genes mainly encoding ion channel and synaptic proteins have been found to account for over 15% of patients with IS or LGS. The contribution of autosomal recessive genetic variation, however, is less well understood. We implemented a rare variant transmission disequilibrium test (TDT) to search for autosomal recessive epileptic encephalopathy genes in a cohort of 320 outbred patient-parent trios that were generally prescreened for rare metabolic disorders. In the current sample, our rare variant transmission disequilibrium test did not identify individual genes with significantly distorted transmission over expectation after correcting for the multiple tests. While the rare variant transmission disequilibrium test did not find evidence of a role for individual autosomal recessive genes, our current sample is insufficiently powered to assess the overall role of autosomal recessive genotypes in an outbred epileptic encephalopathy population.

SUBMITTER: Epi4K Consortium

PROVIDER: S-EPMC5520073 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:MotivationA major focus of current sequencing studies for human genetics is to identify rare variants associated with complex diseases. Aside from reduced power of detecting associated rare variants, controlling for population stratification is particularly challenging for rare variants. Transmission/disequilibrium tests (TDT) based on family designs are robust to population stratification and admixture, and therefore provide an effective approach to rare variant association studies to eliminate spurious associations. To increase power of rare variant association analysis, gene-based collapsing methods become standard approaches for analyzing rare variants. Existing methods that extend this strategy to rare variants in families usually combine TDT statistics at individual variants and therefore lack the flexibility of incorporating other genetic models.ResultsIn this study, we describe a haplotype-based framework for group-wise TDT (gTDT) that is flexible to encompass a variety of genetic models such as additive, dominant and compound heterozygous (CH) (i.e. recessive) models as well as other complex interactions. Unlike existing methods, gTDT constructs haplotypes by transmission when possible and inherently takes into account the linkage disequilibrium among variants. Through extensive simulations we showed that type I error was correctly controlled for rare variants under all models investigated, and this remained true in the presence of population stratification. Under a variety of genetic models, gTDT showed increased power compared with the single marker TDT. Application of gTDT to an autism exome sequencing data of 118 trios identified potentially interesting candidate genes with CH rare variants.Availability and implementationWe implemented gTDT in C++ and the source code and the detailed usage are available on the authors' website (https://medschool.vanderbilt.edu/cgg).Contactbingshan.li@vanderbilt.edu or wei.chen@chp.eduSupplementary informationSupplementary data are available at Bioinformatics online.

Project description:BackgroundDevelopmental and epileptic encephalopathies (DEEs) signify a group of heterogeneous neurodevelopmental disorder associated with early-onset seizures accompanied by developmental delay, hypotonia, mild to severe intellectual disability, and developmental regression. Variants in the DNM1 gene have been associated with autosomal dominant DEE type 31A and autosomal recessive DEE type 31B.MethodsIn the current study, a consanguineous Pakistani family consisting of a proband (IV-2) was clinically evaluated and genetically analyzed manifesting in severe neurodevelopmental phenotypes. WES followed by Sanger sequencing was performed to identify the disease-causing variant. Furthermore, 3D protein modeling and dynamic simulation of wild-type and mutant proteins along with reverse transcriptase (RT)-based mRNA expression were checked using standard methods.ResultsData analysis of WES revealed a novel homozygous non-sense variant (c.1402G>T; p. Glu468*) in exon 11 of the DNM1 gene that was predicted as pathogenic class I. Variants in the DNM1 gene have been associated with DEE types 31A and B. Different bioinformatics prediction tools and American College of Medical Genetics guidelines were used to verify the identified variant. Sanger sequencing was used to validate the disease-causing variant. Our approach validated the pathogenesis of the variant as a cause of heterogeneous neurodevelopmental disorders. In addition, 3D protein modeling showed that the mutant protein would lose most of the amino acids and might not perform the proper function if the surveillance non-sense-mediated decay mechanism was skipped. Molecular dynamics analysis showed varied trajectories of wild-type and mutant DNM1 proteins in terms of root mean square deviation, root mean square fluctuation and radius of gyration. Similarly, RT-qPCR revealed a substantial reduction of the DNM1 gene in the index patient.ConclusionOur finding further confirms the association of homozygous, loss-of-function variants in DNM1 associated with DEE type 31B. The study expands the genotypic and phenotypic spectrum of pathogenic DNM1 variants related to DNM1-associated pathogenesis.

Dataset Information

Application of rare variant transmission disequilibrium tests to epileptic encephalopathy trio sequence data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets