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Integrative transcriptome imputation reveals tissue-specific and shared biological mechanisms mediating susceptibility to complex traits.

Abstract：

:Transcriptome-wide association studies integrate gene expression data with common risk variation to identify gene-trait associations. By incorporating epigenome data to estimate the functional importance of genetic variation on gene expression, we generate a small but significant improvement in the accuracy of transcriptome prediction and increase the power to detect significant expression-trait associations. Joint analysis of 14 large-scale transcriptome datasets and 58 traits identify 13,724 significant expression-trait associations that converge on biological processes and relevant phenotypes in human and mouse phenotype databases. We perform drug repurposing analysis and identify compounds that mimic, or reverse, trait-specific changes. We identify genes that exhibit agonistic pleiotropy for genetically correlated traits that converge on shared biological pathways and elucidate distinct processes in disease etiopathogenesis. Overall, this comprehensive analysis provides insight into the specificity and convergence of gene expression on susceptibility to complex traits.

journal_name

Nat Commun

journal_title

Nature communications

authors

Zhang W,Voloudakis G,Rajagopal VM,Readhead B,Dudley JT,Schadt EE,Björkegren JLM,Kim Y,Fullard JF,Hoffman GE,Roussos P

doi

10.1038/s41467-019-11874-7

subject

Has Abstract

pub_date

2019-08-23 00:00:00

pages

3834

issue

1

issn

2041-1723

pii

10.1038/s41467-019-11874-7

journal_volume

10

pub_type

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