Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

Plasma proteomic associations with genetics and health in the UK Biobank

Benjamin B. Sun, Joshua Chiou, Matthew Traylor, Christian Benner, Yi‐Hsiang Hsu, Tom G. Richardson, Praveen Surendran, Anubha Mahajan, Chloe Robins, Steven G. Grinnell, Liping Hou, Erika Kvikstad, Oliver S. Burren, Jonathan Davitte, Kyle Ferber, Christopher E. Gillies, Åsa K. Hedman, Sile Hu, Tin-Chi Lin, Rajesh Mikkilineni, Rion Pendergrass, Corran Pickering, Bram P. Prins, Denis Baird, Chia‐Yen Chen, Lucas D. Ward, Aimée M. Deaton, Samantha Welsh, Carissa M. Willis, Nick Lehner, Matthias Arnold, Maria A. Wörheide, Karsten Suhre, Gabi Kastenmüller, Anurag Sethi, Madeleine Cule, Anil Raj, Alnylam Human Genetics, AstraZeneca Genomics Initiative, Biogen Biobank Team, Bristol Myers Squibb, Genentech Human Genetics, GlaxoSmithKline Genomic Sciences, Pfizer Integrative Biology, Population Analytics of Janssen Data Sciences, Hyun Ming Kang, Lucy Burkitt-Gray, Eugene Melamud, Mary Helen Black, Eric B. Fauman, Joanna M. M. Howson, Hyun Min Kang, Mark I. McCarthy, Paul Nioi, Slavé Petrovski, Robert A. Scott, Erin N. Smith, Sándor Szalma, Dawn Waterworth, Lyndon J. Mitnaul, Joseph D. Szustakowski, Bradford W. Gibson, Melissa Miller, Christopher D. Whelan

Nature · 2023

Read source ↗ All evidence

Summary

This large consortium study presents a comprehensive proteomic and genetic characterisation of 54,219 UK Biobank participants, identifying 14,287 genetic associations across 2,923 plasma proteins, of which 81% are previously unreported. The work contextualises the genetic architecture of the plasma proteome through ancestry-specific analyses, trans-acting effects, and epistatic interactions, with particular focus on gastrointestinal, immune, and complement pathways. The resource facilitates mechanistic discovery, biomarker development, and therapeutic target validation across multiple disease domains.

Regional applicability

As a UK Biobank resource, these findings are directly applicable to understanding genetic and proteomic signatures of health and disease in the UK population and support the development of domestically relevant biomarkers and predictive models. The open-access nature of the resource enables UK researchers and healthcare organisations to interrogate proteomic associations with UK-specific health outcomes and policy priorities.

Key measures

Protein quantitative trait loci (pQTLs); genetic associations; ancestry-specific pQTL mapping; trans-pQTL effects; ligand–receptor interactions; pathway perturbations; epistatic effects; protein target effects on disease endpoints; proteomic disease signatures

Outcomes reported

The study characterised plasma proteomic profiles and identified genetic associations across 2,923 proteins in 54,219 UK Biobank participants. It mapped 14,287 protein quantitative trait loci (pQTLs), of which 81% were previously undescribed, and explored trans-acting genetic effects, epistatic interactions, and applications to biomarker and therapeutic development.

Theme
Measurement & metrics
Subject
Measurement methods & nutrient profiling
Study type
Research
Study design
Observational cohort
Source type
Peer-reviewed study
Status
Published
Geography
United Kingdom
System type
Human clinical
DOI
10.1038/s41586-023-06592-6
Catalogue ID
SNmohdw6s2-bwlbld

Topic tags

Pulse AI · ask about this record

Dig deeper with Pulse AI.

Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.