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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...

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Autores principales: Dapas, Matthew, Lee, Yu Lin, Wentworth-Sheilds, William, Im, Hae Kyung, Ober, Carole, Schoettler, Nathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
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.
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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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