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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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Detalles Bibliográficos
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
Descripción
Sumario: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.