Pulse Brain · Growing Health Evidence Index
Tier 1 — Meta-analysis / systematic reviewPeer-reviewed

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

Jie Zheng, Valeriia Haberland, Denis Baird, Venexia Walker, Philip Haycock, Mark R. Hurle, Alex Gutteridge, Pau Erola, Yi Liu, Shan Luo, Jamie 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 V. Holmes, Jimmy Z. Liu, Karol Estrada, Rita Santos, Linda McCarthy, Dawn Waterworth, Matthew R. Nelson, George Davey Smith, Adam S. Butterworth, Gibran Hemani, Robert A. Scott, Tom R. Gaunt

Nature Genetics · 2020

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Summary

This phenome-wide Mendelian randomization study examined how circulating protein levels causally influence susceptibility to complex diseases, integrating data from large-scale genome-wide association studies and protein quantitative trait loci. The approach used genetic variants as instrumental variables to infer causal relationships whilst accounting for confounding and reverse causation, providing evidence-grounded candidates for therapeutic intervention. The findings suggest that plasma proteomics may identify modifiable intermediate pathways linking genetic risk to disease manifestation.

UK applicability

The study's international cohort design and genetic instrumental variable approach are broadly generalisable to UK populations of European ancestry. Findings may inform future clinical biomarker development and personalised disease prevention strategies in UK healthcare settings, though population-specific validation would strengthen translation.

Key measures

Causal effect estimates (odds ratios, log odds) of plasma proteins on disease outcomes; statistical significance thresholds and multiple testing correction; bidirectional analyses to detect reverse causation

Outcomes reported

The study used Mendelian randomization to map causal associations between plasma protein levels and risk of complex diseases across multiple phenotypes. This approach leveraged genetic variants as instrumental variables to infer protein–disease relationships.

Theme
Nutrition & health
Subject
Dietary patterns & chronic disease
Study type
Meta-analysis
Study design
Meta-analysis
Source type
Peer-reviewed study
Status
Published
Geography
International
System type
Human clinical
DOI
10.1038/s41588-020-0682-6
Catalogue ID
BFmovi24gk-97fs10

Topic tags

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