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Assessment of multi-population polygenic risk scores for lipid traits in African Americans
Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198155/ https://www.ncbi.nlm.nih.gov/pubmed/37214096 http://dx.doi.org/10.7717/peerj.14910 |
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author | Drouet, Domenica E. Liu, Shiying Crawford, Dana C. |
author_facet | Drouet, Domenica E. Liu, Shiying Crawford, Dana C. |
author_sort | Drouet, Domenica E. |
collection | PubMed |
description | Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting an emphasis to generate these needed data for trans-population and population-specific PRS construction. Given diverse genome-wide discoveries are just now being completed, there has been little opportunity for PRS to be evaluated in diverse populations independent from the discovery efforts. To fill this gap, we leverage here summary data from a recent genome-wide discovery study of lipid traits (HDL-C, LDL-C, triglycerides, and total cholesterol) conducted in diverse populations represented by African Americans, Hispanics, Asians, Native Hawaiians, Native Americans, and others by the Population Architecture using Genomics and Epidemiology (PAGE) Study. We constructed lipid trait PRS using PAGE Study published genetic variants and weights in an independent African American adult patient population linked to de-identified electronic health records and genotypes from the Illumina Metabochip (n = 3,254). Using multi-population lipid trait PRS, we assessed levels of association for their respective lipid traits, clinical outcomes (cardiovascular disease and type 2 diabetes), and common clinical labs. While none of the multi-population PRS were strongly associated with the tested trait or outcome, PRS(LDL-C)was nominally associated with cardiovascular disease. These data demonstrate the complexity in applying PRS to real-world clinical data even when data from multiple populations are available. |
format | Online Article Text |
id | pubmed-10198155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101981552023-05-20 Assessment of multi-population polygenic risk scores for lipid traits in African Americans Drouet, Domenica E. Liu, Shiying Crawford, Dana C. PeerJ Genetics Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting an emphasis to generate these needed data for trans-population and population-specific PRS construction. Given diverse genome-wide discoveries are just now being completed, there has been little opportunity for PRS to be evaluated in diverse populations independent from the discovery efforts. To fill this gap, we leverage here summary data from a recent genome-wide discovery study of lipid traits (HDL-C, LDL-C, triglycerides, and total cholesterol) conducted in diverse populations represented by African Americans, Hispanics, Asians, Native Hawaiians, Native Americans, and others by the Population Architecture using Genomics and Epidemiology (PAGE) Study. We constructed lipid trait PRS using PAGE Study published genetic variants and weights in an independent African American adult patient population linked to de-identified electronic health records and genotypes from the Illumina Metabochip (n = 3,254). Using multi-population lipid trait PRS, we assessed levels of association for their respective lipid traits, clinical outcomes (cardiovascular disease and type 2 diabetes), and common clinical labs. While none of the multi-population PRS were strongly associated with the tested trait or outcome, PRS(LDL-C)was nominally associated with cardiovascular disease. These data demonstrate the complexity in applying PRS to real-world clinical data even when data from multiple populations are available. PeerJ Inc. 2023-05-16 /pmc/articles/PMC10198155/ /pubmed/37214096 http://dx.doi.org/10.7717/peerj.14910 Text en ©2023 Drouet et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Genetics Drouet, Domenica E. Liu, Shiying Crawford, Dana C. Assessment of multi-population polygenic risk scores for lipid traits in African Americans |
title | Assessment of multi-population polygenic risk scores for lipid traits in African Americans |
title_full | Assessment of multi-population polygenic risk scores for lipid traits in African Americans |
title_fullStr | Assessment of multi-population polygenic risk scores for lipid traits in African Americans |
title_full_unstemmed | Assessment of multi-population polygenic risk scores for lipid traits in African Americans |
title_short | Assessment of multi-population polygenic risk scores for lipid traits in African Americans |
title_sort | assessment of multi-population polygenic risk scores for lipid traits in african americans |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198155/ https://www.ncbi.nlm.nih.gov/pubmed/37214096 http://dx.doi.org/10.7717/peerj.14910 |
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