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Transferability of genetic risk scores in African populations
The poor transferability of genetic risk scores (GRSs) derived from European ancestry data in diverse populations is a cause of concern. We set out to evaluate whether GRSs derived from data of African American individuals and multiancestry data perform better in sub-Saharan Africa (SSA) compared to...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205766/ https://www.ncbi.nlm.nih.gov/pubmed/35654908 http://dx.doi.org/10.1038/s41591-022-01835-x |
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author | Kamiza, Abram B. Toure, Sounkou M. Vujkovic, Marijana Machipisa, Tafadzwa Soremekun, Opeyemi S. Kintu, Christopher Corpas, Manuel Pirie, Fraser Young, Elizabeth Gill, Dipender Sandhu, Manjinder S. Kaleebu, Pontiano Nyirenda, Moffat Motala, Ayesha A. Chikowore, Tinashe Fatumo, Segun |
author_facet | Kamiza, Abram B. Toure, Sounkou M. Vujkovic, Marijana Machipisa, Tafadzwa Soremekun, Opeyemi S. Kintu, Christopher Corpas, Manuel Pirie, Fraser Young, Elizabeth Gill, Dipender Sandhu, Manjinder S. Kaleebu, Pontiano Nyirenda, Moffat Motala, Ayesha A. Chikowore, Tinashe Fatumo, Segun |
author_sort | Kamiza, Abram B. |
collection | PubMed |
description | The poor transferability of genetic risk scores (GRSs) derived from European ancestry data in diverse populations is a cause of concern. We set out to evaluate whether GRSs derived from data of African American individuals and multiancestry data perform better in sub-Saharan Africa (SSA) compared to European ancestry-derived scores. Using summary statistics from the Million Veteran Program (MVP), we showed that GRSs derived from data of African American individuals enhance polygenic prediction of lipid traits in SSA compared to European and multiancestry scores. However, our GRS prediction varied greatly within SSA between the South African Zulu (low-density lipoprotein cholesterol (LDL-C), R(2) = 8.14%) and Ugandan cohorts (LDL-C, R(2) = 0.026%). We postulate that differences in the genetic and environmental factors between these population groups might lead to the poor transferability of GRSs within SSA. More effort is required to optimize polygenic prediction in Africa. |
format | Online Article Text |
id | pubmed-9205766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-92057662022-06-19 Transferability of genetic risk scores in African populations Kamiza, Abram B. Toure, Sounkou M. Vujkovic, Marijana Machipisa, Tafadzwa Soremekun, Opeyemi S. Kintu, Christopher Corpas, Manuel Pirie, Fraser Young, Elizabeth Gill, Dipender Sandhu, Manjinder S. Kaleebu, Pontiano Nyirenda, Moffat Motala, Ayesha A. Chikowore, Tinashe Fatumo, Segun Nat Med Brief Communication The poor transferability of genetic risk scores (GRSs) derived from European ancestry data in diverse populations is a cause of concern. We set out to evaluate whether GRSs derived from data of African American individuals and multiancestry data perform better in sub-Saharan Africa (SSA) compared to European ancestry-derived scores. Using summary statistics from the Million Veteran Program (MVP), we showed that GRSs derived from data of African American individuals enhance polygenic prediction of lipid traits in SSA compared to European and multiancestry scores. However, our GRS prediction varied greatly within SSA between the South African Zulu (low-density lipoprotein cholesterol (LDL-C), R(2) = 8.14%) and Ugandan cohorts (LDL-C, R(2) = 0.026%). We postulate that differences in the genetic and environmental factors between these population groups might lead to the poor transferability of GRSs within SSA. More effort is required to optimize polygenic prediction in Africa. Nature Publishing Group US 2022-06-02 2022 /pmc/articles/PMC9205766/ /pubmed/35654908 http://dx.doi.org/10.1038/s41591-022-01835-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Brief Communication Kamiza, Abram B. Toure, Sounkou M. Vujkovic, Marijana Machipisa, Tafadzwa Soremekun, Opeyemi S. Kintu, Christopher Corpas, Manuel Pirie, Fraser Young, Elizabeth Gill, Dipender Sandhu, Manjinder S. Kaleebu, Pontiano Nyirenda, Moffat Motala, Ayesha A. Chikowore, Tinashe Fatumo, Segun Transferability of genetic risk scores in African populations |
title | Transferability of genetic risk scores in African populations |
title_full | Transferability of genetic risk scores in African populations |
title_fullStr | Transferability of genetic risk scores in African populations |
title_full_unstemmed | Transferability of genetic risk scores in African populations |
title_short | Transferability of genetic risk scores in African populations |
title_sort | transferability of genetic risk scores in african populations |
topic | Brief Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205766/ https://www.ncbi.nlm.nih.gov/pubmed/35654908 http://dx.doi.org/10.1038/s41591-022-01835-x |
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