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Transcriptome-wide association studies: opportunities and challenges

By Michael Wainberg, Nasa Sinnott-Armstrong, Nicholas Mancuso, Alvaro N. Barbeira, David A Knowles, David Golan, Raili Ermel, Arno Ruusalepp, Thomas Quertermous, Ke Hao, Johan LM Björkegren, Hae Kyung Im, Bogdan Pasaniuc, Manuel A. Rivas, Anshul B. Kundaje

Posted 20 Oct 2017
bioRxiv DOI: 10.1101/206961 (published DOI: 10.1038/s41588-019-0385-z)

Transcriptome-wide association studies (TWAS) integrate GWAS and expression quantitative trait locus (eQTL) datasets to discover candidate causal gene-trait associations. We integrate multi-tissue expression panels and summary GWAS for LDL cholesterol and Crohn's disease to show that TWAS are highly vulnerable to discovering non-causal genes, because variants at a single GWAS hit locus are often eQTLs for multiple genes. TWAS exhibit acute instability when the tissue of the expression panel is changed: candidate causal genes that are TWAS hits in one tissue are usually no longer hits in another, due to lack of expression or strong eQTLs, while non-causal genes at the same loci remain. While TWAS is statistically valid when used as a weighted burden test to identify trait-associated loci, it is invalid to interpret TWAS associations as causal genes because the false discovery rate for TWAS causal gene discovery is not only high, but unquantifiable. More broadly, our results showcase limitations of using expression variation across individuals to determine causal genes at GWAS loci.

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