Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases

Jie Zheng; Valeriia Haberland; Denis A. Baird; Venexia M. Walker; Philip Haycock; Mark R. Hurle; Alex Gutteridge; Pau Erola; Yi Liu; Shan Luo; Jamie W. Robinson; Tom G. Richardson; James R Staley; Benjamin Elsworth; Stephen Burgess; Benjamin B. Sun; John Danesh; Heiko Runz; Joseph Maranville; Hannah M. Martin; James Yarmolinsky; Charles Laurin; Michael Vaclav Holmes; Jimmy Z. Liu; Karol Estrada; Rita Santos; Linda C. McCarthy; Dawn M. Waterworth; Matthew R. Nelson; George Davey Smith

doi:10.1038/s41588-020-0682-6

GeneticsNature GeneticsSep 7, 2020

Peer-reviewed journal article

Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases

Jie Zheng iD, Valeriia Haberland iD, Denis A. Baird iD, Venexia M. Walker iD, Philip Haycock iD, Mark R. Hurle, Alex Gutteridge iD, Pau Erola iD, Yi Liu iD, Shan Luo iD, Jamie W. Robinson iD, Tom G. Richardson iD, James R Staley iD, Benjamin Elsworth iD, Stephen Burgess iD, Benjamin B. Sun iD, John Danesh iD, Heiko Runz iD, Joseph Maranville iD, Hannah M. Martin iD, James Yarmolinsky iD, Charles Laurin iD, Michael Vaclav Holmes iD, Jimmy Z. Liu iD, Karol Estrada iD, , Tom R. Gaunt iD

Abstract

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here, we estimated the effects of 1002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium (LD) is widespread in naive phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes (www.epigraphdb.org/pqtl/). Evaluation of data from historic drug development programmes showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of our approach in identifying and prioritising potential therapeutic targets.

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