%0 Journal Article %J Nat Genet %D 2020 %T A unified framework for joint-tissue transcriptome-wide association and Mendelian randomization analysis. %A Zhou, Dan %A Jiang, Yi %A Zhong, Xue %A Cox, Nancy J %A Liu, Chunyu %A Gamazon, Eric R %K Animals %K Gene Expression Profiling %K Genetic Association Studies %K Humans %K Lipoproteins, LDL %K Mendelian Randomization Analysis %K Mice %K Models, Genetic %K Multifactorial Inheritance %K Predictive Value of Tests %X

Here, we present a joint-tissue imputation (JTI) approach and a Mendelian randomization framework for causal inference, MR-JTI. JTI borrows information across transcriptomes of different tissues, leveraging shared genetic regulation, to improve prediction performance in a tissue-dependent manner. Notably, JTI includes the single-tissue imputation method PrediXcan as a special case and outperforms other single-tissue approaches (the Bayesian sparse linear mixed model and Dirichlet process regression). MR-JTI models variant-level heterogeneity (primarily due to horizontal pleiotropy, addressing a major challenge of transcriptome-wide association study interpretation) and performs causal inference with type I error control. We make explicit the connection between the genetic architecture of gene expression and of complex traits and the suitability of Mendelian randomization as a causal inference strategy for transcriptome-wide association studies. We provide a resource of imputation models generated from GTEx and PsychENCODE panels. Analysis of biobanks and meta-analysis data, and extensive simulations show substantially improved statistical power, replication and causal mapping rate for JTI relative to existing approaches.

%B Nat Genet %V 52 %P 1239-1246 %8 2020 11 %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/33020666?dopt=Abstract %R 10.1038/s41588-020-0706-2 %0 Journal Article %J Am J Hum Genet %D 2019 %T Ultra-Rare Genetic Variation in the Epilepsies: A Whole-Exome Sequencing Study of 17,606 Individuals. %X

Sequencing-based studies have identified novel risk genes associated with severe epilepsies and revealed an excess of rare deleterious variation in less-severe forms of epilepsy. To identify the shared and distinct ultra-rare genetic risk factors for different types of epilepsies, we performed a whole-exome sequencing (WES) analysis of 9,170 epilepsy-affected individuals and 8,436 controls of European ancestry. We focused on three phenotypic groups: severe developmental and epileptic encephalopathies (DEEs), genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We observed that compared to controls, individuals with any type of epilepsy carried an excess of ultra-rare, deleterious variants in constrained genes and in genes previously associated with epilepsy; we saw the strongest enrichment in individuals with DEEs and the least strong in individuals with NAFE. Moreover, we found that inhibitory GABA receptor genes were enriched for missense variants across all three classes of epilepsy, whereas no enrichment was seen in excitatory receptor genes. The larger gene groups for the GABAergic pathway or cation channels also showed a significant mutational burden in DEEs and GGE. Although no single gene surpassed exome-wide significance among individuals with GGE or NAFE, highly constrained genes and genes encoding ion channels were among the lead associations; such genes included CACNA1G, EEF1A2, and GABRG2 for GGE and LGI1, TRIM3, and GABRG2 for NAFE. Our study, the largest epilepsy WES study to date, confirms a convergence in the genetics of severe and less-severe epilepsies associated with ultra-rare coding variation, and it highlights a ubiquitous role for GABAergic inhibition in epilepsy etiology.

%B Am J Hum Genet %V 105 %P 267-282 %8 2019 Aug 01 %G eng %N 2 %1 https://www.ncbi.nlm.nih.gov/pubmed/31327507?dopt=Abstract %R 10.1016/j.ajhg.2019.05.020