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Polygenic Risk Score in African populations: progress and challenges
Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects single nucleo...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233318/ https://www.ncbi.nlm.nih.gov/pubmed/37273966 http://dx.doi.org/10.12688/f1000research.76218.2 |
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author | Adam, Yagoub Sadeeq, Suraju Kumuthini, Judit Ajayi, Olabode Wells, Gordon Solomon, Rotimi Ogunlana, Olubanke Adetiba, Emmanuel Iweala, Emeka Brors, Benedikt Adebiyi, Ezekiel |
author_facet | Adam, Yagoub Sadeeq, Suraju Kumuthini, Judit Ajayi, Olabode Wells, Gordon Solomon, Rotimi Ogunlana, Olubanke Adetiba, Emmanuel Iweala, Emeka Brors, Benedikt Adebiyi, Ezekiel |
author_sort | Adam, Yagoub |
collection | PubMed |
description | Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects single nucleotide polymorphisms (SNPs) that contribute to the disease with low effect size making it more precise at individual level risk prediction. PRS analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with low effect size but play an indispensable role to the observed phenotypic/trait variance. PRS analysis has applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies show that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that lack of sufficient GWAS data and tools is the limiting factor of applying PRS analysis to sub-Saharan populations. We recommend developing Africa-specific PRS methods and tools for estimating and analyzing African population data for clinical evaluation of PRSs of interest and predicting rare diseases. |
format | Online Article Text |
id | pubmed-10233318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-102333182023-06-02 Polygenic Risk Score in African populations: progress and challenges Adam, Yagoub Sadeeq, Suraju Kumuthini, Judit Ajayi, Olabode Wells, Gordon Solomon, Rotimi Ogunlana, Olubanke Adetiba, Emmanuel Iweala, Emeka Brors, Benedikt Adebiyi, Ezekiel F1000Res Review Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects single nucleotide polymorphisms (SNPs) that contribute to the disease with low effect size making it more precise at individual level risk prediction. PRS analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with low effect size but play an indispensable role to the observed phenotypic/trait variance. PRS analysis has applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies show that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that lack of sufficient GWAS data and tools is the limiting factor of applying PRS analysis to sub-Saharan populations. We recommend developing Africa-specific PRS methods and tools for estimating and analyzing African population data for clinical evaluation of PRSs of interest and predicting rare diseases. F1000 Research Limited 2023-04-11 /pmc/articles/PMC10233318/ /pubmed/37273966 http://dx.doi.org/10.12688/f1000research.76218.2 Text en Copyright: © 2023 Adam Y et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Adam, Yagoub Sadeeq, Suraju Kumuthini, Judit Ajayi, Olabode Wells, Gordon Solomon, Rotimi Ogunlana, Olubanke Adetiba, Emmanuel Iweala, Emeka Brors, Benedikt Adebiyi, Ezekiel Polygenic Risk Score in African populations: progress and challenges |
title | Polygenic Risk Score in African populations: progress and challenges |
title_full | Polygenic Risk Score in African populations: progress and challenges |
title_fullStr | Polygenic Risk Score in African populations: progress and challenges |
title_full_unstemmed | Polygenic Risk Score in African populations: progress and challenges |
title_short | Polygenic Risk Score in African populations: progress and challenges |
title_sort | polygenic risk score in african populations: progress and challenges |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233318/ https://www.ncbi.nlm.nih.gov/pubmed/37273966 http://dx.doi.org/10.12688/f1000research.76218.2 |
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