Linking protein to phenotype with Mendelian Randomization detects 38 proteins with causal roles in human diseases and traits

Autoři: Andrew D. Bretherick aff001;  Oriol Canela-Xandri aff001;  Peter K. Joshi aff003;  David W. Clark aff003;  Konrad Rawlik aff002;  Thibaud S. Boutin aff001;  Yanni Zeng aff001;  Carmen Amador aff001;  Pau Navarro aff001;  Igor Rudan aff003;  Alan F. Wright aff001;  Harry Campbell aff003;  Veronique Vitart aff001;  Caroline Hayward aff001;  James F. Wilson aff001;  Albert Tenesa aff001;  Chris P. Ponting aff001;  J. Kenneth Baillie aff002;  Chris Haley aff001
Působiště autorů: MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland, United Kingdom aff001;  The Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, Scotland, United Kingdom aff002;  Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, Scotland, United Kingdom aff003;  Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China aff004;  Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China aff005;  Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China aff006
Vyšlo v časopise: Linking protein to phenotype with Mendelian Randomization detects 38 proteins with causal roles in human diseases and traits. PLoS Genet 16(7): e32767. doi:10.1371/journal.pgen.1008785
Kategorie: Research Article


To efficiently transform genetic associations into drug targets requires evidence that a particular gene, and its encoded protein, contribute causally to a disease. To achieve this, we employ a three-step proteome-by-phenome Mendelian Randomization (MR) approach. In step one, 154 protein quantitative trait loci (pQTLs) were identified and independently replicated. From these pQTLs, 64 replicated locally-acting variants were used as instrumental variables for proteome-by-phenome MR across 846 traits (step two). When its assumptions are met, proteome-by-phenome MR, is equivalent to simultaneously running many randomized controlled trials. Step 2 yielded 38 proteins that significantly predicted variation in traits and diseases in 509 instances. Step 3 revealed that amongst the 271 instances from GeneAtlas (UK Biobank), 77 showed little evidence of pleiotropy (HEIDI), and 92 evidence of colocalization (eCAVIAR). Results were wide ranging: including, for example, new evidence for a causal role of tyrosine-protein phosphatase non-receptor type substrate 1 (SHPS1; SIRPA) in schizophrenia, and a new finding that intestinal fatty acid binding protein (FABP2) abundance contributes to the pathogenesis of cardiovascular disease. We also demonstrated confirmatory evidence for the causal role of four further proteins (FGF5, IL6R, LPL, LTA) in cardiovascular disease risk.

Klíčová slova:

Alleles – Asthma – Coronary heart disease – Drug discovery – Genetics of disease – Genome-wide association studies – Instrumental variable analysis – Schizophrenia


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