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Genetics of 35 blood and urine biomarkers in the UK Biobank
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 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations, an...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867639/ https://www.ncbi.nlm.nih.gov/pubmed/33462484 http://dx.doi.org/10.1038/s41588-020-00757-z |
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author | Armstrong, Nasa Sinnott- Tanigawa, Yosuke Amar, David Mars, Nina Benner, Christian Aguirre, Matthew Venkataraman, Guhan Ram Wainberg, Michael Ollila, Hanna M. Kiiskinen, Tuomo Havulinna, Aki S. Pirruccello, James P. Qian, Junyang Shcherbina, Anna consortium, FinnGen Rodriguez, Fatima Assimes, Themistocles L. Agarwala, Vineeta Tibshirani, Robert Hastie, Trevor Ripatti, Samuli Pritchard, Jonathan K. Daly, Mark J. Rivas, Manuel A. |
author_facet | Armstrong, Nasa Sinnott- Tanigawa, Yosuke Amar, David Mars, Nina Benner, Christian Aguirre, Matthew Venkataraman, Guhan Ram Wainberg, Michael Ollila, Hanna M. Kiiskinen, Tuomo Havulinna, Aki S. Pirruccello, James P. Qian, Junyang Shcherbina, Anna consortium, FinnGen Rodriguez, Fatima Assimes, Themistocles L. Agarwala, Vineeta Tibshirani, Robert Hastie, Trevor Ripatti, Samuli Pritchard, Jonathan K. Daly, Mark J. Rivas, Manuel A. |
author_sort | Armstrong, Nasa Sinnott- |
collection | PubMed |
description | 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 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations, and additional sets of large-effect (> 0.1 sd) protein-altering, HLA, and copy-number variant associations. Through Mendelian Randomization 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 for each biomarker and built ‘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, their causal influences on diseases, and improve genetic risk stratification for common diseases. |
format | Online Article Text |
id | pubmed-7867639 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
record_format | MEDLINE/PubMed |
spelling | pubmed-78676392021-07-18 Genetics of 35 blood and urine biomarkers in the UK Biobank Armstrong, Nasa Sinnott- Tanigawa, Yosuke Amar, David Mars, Nina Benner, Christian Aguirre, Matthew Venkataraman, Guhan Ram Wainberg, Michael Ollila, Hanna M. Kiiskinen, Tuomo Havulinna, Aki S. Pirruccello, James P. Qian, Junyang Shcherbina, Anna consortium, FinnGen Rodriguez, Fatima Assimes, Themistocles L. Agarwala, Vineeta Tibshirani, Robert Hastie, Trevor Ripatti, Samuli Pritchard, Jonathan K. Daly, Mark J. Rivas, Manuel A. Nat Genet Article 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 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations, and additional sets of large-effect (> 0.1 sd) protein-altering, HLA, and copy-number variant associations. Through Mendelian Randomization 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 for each biomarker and built ‘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, their causal influences on diseases, and improve genetic risk stratification for common diseases. 2021-01-18 2021-02 /pmc/articles/PMC7867639/ /pubmed/33462484 http://dx.doi.org/10.1038/s41588-020-00757-z Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Armstrong, Nasa Sinnott- Tanigawa, Yosuke Amar, David Mars, Nina Benner, Christian Aguirre, Matthew Venkataraman, Guhan Ram Wainberg, Michael Ollila, Hanna M. Kiiskinen, Tuomo Havulinna, Aki S. Pirruccello, James P. Qian, Junyang Shcherbina, Anna consortium, FinnGen Rodriguez, Fatima Assimes, Themistocles L. Agarwala, Vineeta Tibshirani, Robert Hastie, Trevor Ripatti, Samuli Pritchard, Jonathan K. Daly, Mark J. Rivas, Manuel A. Genetics of 35 blood and urine biomarkers in the UK Biobank |
title | Genetics of 35 blood and urine biomarkers in the UK Biobank |
title_full | Genetics of 35 blood and urine biomarkers in the UK Biobank |
title_fullStr | Genetics of 35 blood and urine biomarkers in the UK Biobank |
title_full_unstemmed | Genetics of 35 blood and urine biomarkers in the UK Biobank |
title_short | Genetics of 35 blood and urine biomarkers in the UK Biobank |
title_sort | genetics of 35 blood and urine biomarkers in the uk biobank |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867639/ https://www.ncbi.nlm.nih.gov/pubmed/33462484 http://dx.doi.org/10.1038/s41588-020-00757-z |
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