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Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation

Complex disorders are caused by a combination of genetic, environmental and lifestyle factors, and their prevalence can vary greatly across different populations. The extent to which genetic risk, as identified by Genome Wide Association Study (GWAS), correlates to disease prevalence in different po...

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Autores principales: Jain, Pritesh R., Burch, Myson, Martinez, Melanie, Mir, Pablo, Fichna, Jakub P., Zekanowski, Cezary, Rizzo, Renata, Tümer, Zeynep, Barta, Csaba, Yannaki, Evangelia, Stamatoyannopoulos, John, Drineas, Petros, Paschou, Peristera
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662565/
https://www.ncbi.nlm.nih.gov/pubmed/37986041
http://dx.doi.org/10.1186/s12863-023-01168-9
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author Jain, Pritesh R.
Burch, Myson
Martinez, Melanie
Mir, Pablo
Fichna, Jakub P.
Zekanowski, Cezary
Rizzo, Renata
Tümer, Zeynep
Barta, Csaba
Yannaki, Evangelia
Stamatoyannopoulos, John
Drineas, Petros
Paschou, Peristera
author_facet Jain, Pritesh R.
Burch, Myson
Martinez, Melanie
Mir, Pablo
Fichna, Jakub P.
Zekanowski, Cezary
Rizzo, Renata
Tümer, Zeynep
Barta, Csaba
Yannaki, Evangelia
Stamatoyannopoulos, John
Drineas, Petros
Paschou, Peristera
author_sort Jain, Pritesh R.
collection PubMed
description Complex disorders are caused by a combination of genetic, environmental and lifestyle factors, and their prevalence can vary greatly across different populations. The extent to which genetic risk, as identified by Genome Wide Association Study (GWAS), correlates to disease prevalence in different populations has not been investigated systematically. Here, we studied 14 different complex disorders and explored whether polygenic risk scores (PRS) based on current GWAS correlate to disease prevalence within Europe and around the world. A clear variation in GWAS-based genetic risk was observed based on ancestry and we identified populations that have a higher genetic liability for developing certain disorders. We found that for four out of the 14 studied disorders, PRS significantly correlates to disease prevalence within Europe. We also found significant correlations between worldwide disease prevalence and PRS for eight of the studied disorders with Multiple Sclerosis genetic risk having the highest correlation to disease prevalence. Based on current GWAS results, the across population differences in genetic risk for certain disorders can potentially be used to understand differences in disease prevalence and identify populations with the highest genetic liability. The study highlights both the limitations of PRS based on current GWAS but also the fact that in some cases, PRS may already have high predictive power. This could be due to the genetic architecture of specific disorders or increased GWAS power in some cases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12863-023-01168-9.
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spelling pubmed-106625652023-11-20 Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation Jain, Pritesh R. Burch, Myson Martinez, Melanie Mir, Pablo Fichna, Jakub P. Zekanowski, Cezary Rizzo, Renata Tümer, Zeynep Barta, Csaba Yannaki, Evangelia Stamatoyannopoulos, John Drineas, Petros Paschou, Peristera BMC Genom Data Research Complex disorders are caused by a combination of genetic, environmental and lifestyle factors, and their prevalence can vary greatly across different populations. The extent to which genetic risk, as identified by Genome Wide Association Study (GWAS), correlates to disease prevalence in different populations has not been investigated systematically. Here, we studied 14 different complex disorders and explored whether polygenic risk scores (PRS) based on current GWAS correlate to disease prevalence within Europe and around the world. A clear variation in GWAS-based genetic risk was observed based on ancestry and we identified populations that have a higher genetic liability for developing certain disorders. We found that for four out of the 14 studied disorders, PRS significantly correlates to disease prevalence within Europe. We also found significant correlations between worldwide disease prevalence and PRS for eight of the studied disorders with Multiple Sclerosis genetic risk having the highest correlation to disease prevalence. Based on current GWAS results, the across population differences in genetic risk for certain disorders can potentially be used to understand differences in disease prevalence and identify populations with the highest genetic liability. The study highlights both the limitations of PRS based on current GWAS but also the fact that in some cases, PRS may already have high predictive power. This could be due to the genetic architecture of specific disorders or increased GWAS power in some cases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12863-023-01168-9. BioMed Central 2023-11-20 /pmc/articles/PMC10662565/ /pubmed/37986041 http://dx.doi.org/10.1186/s12863-023-01168-9 Text en © The Author(s) 2023 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Jain, Pritesh R.
Burch, Myson
Martinez, Melanie
Mir, Pablo
Fichna, Jakub P.
Zekanowski, Cezary
Rizzo, Renata
Tümer, Zeynep
Barta, Csaba
Yannaki, Evangelia
Stamatoyannopoulos, John
Drineas, Petros
Paschou, Peristera
Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation
title Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation
title_full Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation
title_fullStr Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation
title_full_unstemmed Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation
title_short Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation
title_sort can polygenic risk scores help explain disease prevalence differences around the world? a worldwide investigation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662565/
https://www.ncbi.nlm.nih.gov/pubmed/37986041
http://dx.doi.org/10.1186/s12863-023-01168-9
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