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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...

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Autores principales: Adam, Yagoub, Sadeeq, Suraju, Kumuthini, Judit, Ajayi, Olabode, Wells, Gordon, Solomon, Rotimi, Ogunlana, Olubanke, Adetiba, Emmanuel, Iweala, Emeka, Brors, Benedikt, Adebiyi, Ezekiel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2023
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.
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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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