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Revealing polygenic pleiotropy using genetic risk scores for asthma
In this study we examined how genetic risk for asthma associates with different features of the disease and with other medical conditions and traits. Using summary statistics from two multi-ancestry genome-wide association studies of asthma, we modeled polygenic risk scores (PRSs) and validated thei...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474095/ https://www.ncbi.nlm.nih.gov/pubmed/37663543 http://dx.doi.org/10.1016/j.xhgg.2023.100233 |
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author | Dapas, Matthew Lee, Yu Lin Wentworth-Sheilds, William Im, Hae Kyung Ober, Carole Schoettler, Nathan |
author_facet | Dapas, Matthew Lee, Yu Lin Wentworth-Sheilds, William Im, Hae Kyung Ober, Carole Schoettler, Nathan |
author_sort | Dapas, Matthew |
collection | PubMed |
description | In this study we examined how genetic risk for asthma associates with different features of the disease and with other medical conditions and traits. Using summary statistics from two multi-ancestry genome-wide association studies of asthma, we modeled polygenic risk scores (PRSs) and validated their predictive performance in the UK Biobank. We then performed phenome-wide association studies of the asthma PRSs with 371 heritable traits in the UK Biobank. We identified 228 total significant associations across a variety of organ systems, including associations that varied by PRS model, sex, age of asthma onset, ancestry, and human leukocyte antigen region alleles. Our results highlight pervasive pleiotropy between asthma and numerous other traits and conditions and elucidate pathways that contribute to asthma and its comorbidities. |
format | Online Article Text |
id | pubmed-10474095 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104740952023-09-03 Revealing polygenic pleiotropy using genetic risk scores for asthma Dapas, Matthew Lee, Yu Lin Wentworth-Sheilds, William Im, Hae Kyung Ober, Carole Schoettler, Nathan HGG Adv Article In this study we examined how genetic risk for asthma associates with different features of the disease and with other medical conditions and traits. Using summary statistics from two multi-ancestry genome-wide association studies of asthma, we modeled polygenic risk scores (PRSs) and validated their predictive performance in the UK Biobank. We then performed phenome-wide association studies of the asthma PRSs with 371 heritable traits in the UK Biobank. We identified 228 total significant associations across a variety of organ systems, including associations that varied by PRS model, sex, age of asthma onset, ancestry, and human leukocyte antigen region alleles. Our results highlight pervasive pleiotropy between asthma and numerous other traits and conditions and elucidate pathways that contribute to asthma and its comorbidities. Elsevier 2023-08-17 /pmc/articles/PMC10474095/ /pubmed/37663543 http://dx.doi.org/10.1016/j.xhgg.2023.100233 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Dapas, Matthew Lee, Yu Lin Wentworth-Sheilds, William Im, Hae Kyung Ober, Carole Schoettler, Nathan Revealing polygenic pleiotropy using genetic risk scores for asthma |
title | Revealing polygenic pleiotropy using genetic risk scores for asthma |
title_full | Revealing polygenic pleiotropy using genetic risk scores for asthma |
title_fullStr | Revealing polygenic pleiotropy using genetic risk scores for asthma |
title_full_unstemmed | Revealing polygenic pleiotropy using genetic risk scores for asthma |
title_short | Revealing polygenic pleiotropy using genetic risk scores for asthma |
title_sort | revealing polygenic pleiotropy using genetic risk scores for asthma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474095/ https://www.ncbi.nlm.nih.gov/pubmed/37663543 http://dx.doi.org/10.1016/j.xhgg.2023.100233 |
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