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

Genetics of 35 blood and urine biomarkers in the UK Biobank

Nasa Sinnott-Armstrong, Yosuke Tanigawa, David Amar, Nina Mars, Christian Benner, Matthew Aguirre, Guhan Venkataraman, Michael Wainberg, Hanna M. Ollila, Tuomo Kiiskinen, Aki S. Havulinna, James P. Pirruccello, Junyang Qian, Anna Shcherbina, FinnGen, Fátima Rodríguez, Themistocles L. Assimes, Vineeta Agarwala, Robert Tibshirani, Trevor Hastie, Samuli Ripatti, Jonathan K. Pritchard, Mark J. Daly, Manuel A. Rivas

Nature Genetics · 2021

Read source ↗ All evidence

Summary

This large-scale genomic study published in Nature Genetics examined the genetic architecture underlying 35 commonly measured blood and urine biomarkers in over 400,000 UK Biobank participants. The authors conducted comprehensive GWAS analyses to identify genetic variants associated with these clinical measures, characterising heritability and genetic correlations across biomarkers. The work provides a foundational reference for understanding the heritable component of metabolic and clinical traits relevant to human health outcomes.

UK applicability

As the study was conducted entirely within the UK Biobank population, findings are directly applicable to understanding genetic variation in biomarker levels amongst UK populations. Results may inform UK clinical genetics research and the interpretation of biomarker variation in precision medicine contexts.

Key measures

Genome-wide association statistics for 35 blood and urine biomarkers; heritability estimates; genetic correlation matrices; variant effect sizes and frequencies

Outcomes reported

The study identified genetic variants associated with 35 blood and urine biomarkers using genome-wide association study (GWAS) methodology in the UK Biobank cohort. The research characterised the heritability and genetic architecture of these clinical and metabolic biomarkers.

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/s41588-020-00757-z
Catalogue ID
SNmohdwfqg-tnz57k

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.