Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

By A. Barbeira, Scott P. Dickinson, Rodrigo Bonazzola, Jiamao Zheng, H. Wheeler, Jason M. Torres, E. Torstenson, Kaanan P. Shah, Tzintzuni I. Garcia, T. Edwards and 242 more. Nature Communications, 2016

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Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes. Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c2adf5906bf3ce0ebae1eb2b2b520d70e9b575c4

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Citations in the corpus

Evaluating the potential role of pleiotropy in Mendelian randomization studies (2018, methodology): “S-PrediXcan (32) adopts a similar strategy of using an”
Annotation-free quantification of RNA splicing using LeafCutter (2017, neutral): “%) of novel splice sites are conserved across vertebrates (ave. phastCons ≥ 0.6, Supplementary Figure 4), indicating that the alternative excision of thousands of introns may be functional (Supplementary Note).”
Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. (2019, background): “In addition toancestral diversity, the current lackof racial andethnicdiversity, which are related but distinct fromancestry (seeBox 1), hinder the development of more complete etiological models (Banda et al., 2015; Medina-Gomez et al., 2015; Race, Ethnicity, and Genetics Working Group, 2005).”
Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses (2019, background): “The studies covered a variety of trait pairs, generally integrating a disease GWAS with molecular quantitative trait loci (QTL) data, [20–39] but also comparing pairs of disease GWAS, [40] eQTL and pQTL [41, 42] or eQTL and other molecular traits.”
webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study (2021, neutral): “Although many studies (13,25,32,34,44,45) have shown that gene expression is highly tissue dependent, an arbitrary reference tissue is often used in many TWAS analyses when the causal tissue type is unknown.”