Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids

Adriaan Graaf, Annique Claringbould, Antoine Rimbert, Harm-Jan Westra, Yang Li, Cisca Wijmenga and Serena Sanna ()
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Adriaan Graaf: University of Groningen, University Medical Centre Groningen, Department of Genetics
Annique Claringbould: University of Groningen, University Medical Centre Groningen, Department of Genetics
Antoine Rimbert: University of Groningen, University Medical Centre Groningen, Department of Pediatrics, Section Molecular Genetics
Harm-Jan Westra: University of Groningen, University Medical Centre Groningen, Department of Genetics
Yang Li: University of Groningen, University Medical Centre Groningen, Department of Genetics
Cisca Wijmenga: University of Groningen, University Medical Centre Groningen, Department of Genetics
Serena Sanna: University of Groningen, University Medical Centre Groningen, Department of Genetics

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract Inference of causality between gene expression and complex traits using Mendelian randomization (MR) is confounded by pleiotropy and linkage disequilibrium (LD) of gene-expression quantitative trait loci (eQTL). Here, we propose an MR method, MR-link, that accounts for unobserved pleiotropy and LD by leveraging information from individual-level data, even when only one eQTL variant is present. In simulations, MR-link shows false-positive rates close to expectation (median 0.05) and high power (up to 0.89), outperforming all other tested MR methods and coloc. Application of MR-link to low-density lipoprotein cholesterol (LDL-C) measurements in 12,449 individuals with expression and protein QTL summary statistics from blood and liver identifies 25 genes causally linked to LDL-C. These include the known SORT1 and ApoE genes as well as PVRL2, located in the APOE locus, for which a causal role in liver was not known. Our results showcase the strength of MR-link for transcriptome-wide causal inferences.

Date: 2020
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DOI: 10.1038/s41467-020-18716-x

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