Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

: Eleonora Porcu, Sina Rüeger, Kaido Lepik; eQTLGen Consortium; BIOS Consortium; Federico A. Santoni, Alexandre Reymond, Zoltán Kutalik

Publisher: NATURE PUBLISHING GROUP

: 2019

Nature Communications

NATURE COMMUNICATIONS

: NAT COMMUN

: ARTN 3300

: 10

: 12

: 2041-1723

DOI: https://doi.org/10.1038/s41467-019-10936-0

: https://research.utu.fi/converis/portal/detail/Publication/42212312

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.

s41467-019-10936-0.pdf