| Title: | Genetics of 35 blood and urine biomarkers in the UK Biobank |
| Journal: | Nature Genetics |
| Published: | 18 Jan 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33462484/ |
| DOI: | https://doi.org/10.1038/s41588-020-00757-z |
| URL: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867639 |
| Citations: | 458 (240 in last 2 years) as of 8 Aug 2024 |
Publication 9543
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Abstract
Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n = 363,228 individuals). We identify 5,794 independent loci associated with at least one trait (p < 5 × 10−9), containing 3,374 fine-mapped associations and additional sets of large-effect (>0.1 s.d.) protein-altering, human leukocyte antigen (HLA) and copy number variant (CNV) associations. Through Mendelian randomization (MR) analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores (PRSs) for each biomarker and build 'multi-PRS' models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n = 135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases.</p>
23 Authors
- Nasa Sinnott-Armstrong
- Yosuke Tanigawa
- David Amar
- Nina Mars
- Christian Benner
- Matthew Aguirre
- Guhan Ram Venkataraman
- Michael Wainberg
- Hanna M. Ollila
- Tuomo Kiiskinen
- Aki S. Havulinna
- James P. Pirruccello
- Junyang Qian
- Anna Shcherbina
- Fatima Rodriguez
- Themistocles L. Assimes
- Vineeta Agarwala
- Robert Tibshirani
- Trevor Hastie
- Samuli Ripatti
- Jonathan K. Pritchard
- Mark J. Daly
- Manuel A. Rivas
1 Application
| Application ID | Title |
|---|---|
| 24983 | Generating effective therapeutic hypotheses from genomic and hospital linkage data |
Enabling scientific discoveries that improve human health