Genetics of 35 blood and urine biomarkers in the UK Biobank
Published in Nature Genetics, 2021
Clinical lab tests are often used in clinical practice to guide diagnoses and treatment plans. Thanks to UK Biobank, we have a fortunate to analyze the genetic basis of those biomarkers and investigate their influence on diseases.
Through UK Biobank-wide GWAS meta-analysis, we report > 10,000 GWAS associations (p < 5e-9) across 35 biomarkers and >5,700 loci. This includes > 450 large-effect (>0.1 s.d.) associations on protein-altering variants, which we highlight in a Fuji plot (gene symbols).
With FINEMAP, we identified >27,000 distinct signals in >5,000 regions across the 35 traits, of which >2,500 signals were fine-mapped to a single variant. We also trained sparse polygenic risk score (PRS) models with Lasso L1- penalized regression using the snpnet package.
To investigate the influence of the identified genetic basis on diseases, we performed single-variant PheWAS, PRS-PheWAS, and causal inference. Motivated by those results, we developed multi-PRS by combining a single-trait PRS model of disease with that of 35 biomarkers.
When we compare the predictive performance, multi-PRS showed improvements over single-trait snpnet PRS across many diseases, which we also replicated in FinnGen, suggesting both large case numbers and multi-trait modeling might complementary contribute to improving the power.
This work was led by Nasa Sinnott-Armstrong, myself, and Dr. Manuel A. Rivas, with many contributions from colleagues. We thank UK Biobank, FinnGen, their participants, amazing collaborators, and colleagues, as well as funding.
- Supplementary Data (500GB+) is available at NIH’s archive instance of figshare
- Analysis and visualization scripts used in this manuscript is available at GitHub repo
- Full text
- Research highlights in Nature Reviews Nephrology
- Allison, S.J. Biomarker genetics. Nat Rev Nephrol (2021). https://doi.org/10.1038/s41581-021-00400-y
- Genome web news article
Reference: N. Sinnott-Armstrong*, Y. Tanigawa*, D. Amar, N. J. Mars, C. Benner, M. Aguirre, G. R. Venkataraman, M. Wainberg, H. M. Ollila, T. Kiiskinen, A. S. Havulinna, J. P. Pirruccello, J. Qian, A. Shcherbina, FinnGen, F. Rodriguez, T. L. Assimes, V. Agarwala, R. Tibshirani, T. Hastie, S. Ripatti, J. K. Pritchard, M. J. Daly, M. A. Rivas, Genetics of 35 blood and urine biomarkers in the UK Biobank. Nat Gen. 53(2), 185-194 (2021). https://doi.org/10.1038/s41588-020-00757-z (full text)