Variability of polygenic prediction for body mass index in Africa.
BMI
Polygenic prediction
Polygenic risk score
Variability
Journal
Genome medicine
ISSN: 1756-994X
Titre abrégé: Genome Med
Pays: England
ID NLM: 101475844
Informations de publication
Date de publication:
30 May 2024
30 May 2024
Historique:
received:
30
04
2023
accepted:
21
05
2024
medline:
31
5
2024
pubmed:
31
5
2024
entrez:
30
5
2024
Statut:
epublish
Résumé
Polygenic prediction studies in continental Africans are scarce. Africa's genetic and environmental diversity pose a challenge that limits the generalizability of polygenic risk scores (PRS) for body mass index (BMI) within the continent. Studies to understand the factors that affect PRS variability within Africa are required. Using the first multi-ancestry genome-wide association study (GWAS) meta-analysis for BMI involving continental Africans, we derived a multi-ancestry PRS and compared its performance to a European ancestry-specific PRS in continental Africans (AWI-Gen study) and a European cohort (Estonian Biobank). We then evaluated the factors affecting the performance of the PRS in Africans which included fine-mapping resolution, allele frequencies, linkage disequilibrium patterns, and PRS-environment interactions. Polygenic prediction of BMI in continental Africans is poor compared to that in European ancestry individuals. However, we show that the multi-ancestry PRS is more predictive than the European ancestry-specific PRS due to its improved fine-mapping resolution. We noted regional variation in polygenic prediction across Africa's East, South, and West regions, which was driven by a complex interplay of the PRS with environmental factors, such as physical activity, smoking, alcohol intake, and socioeconomic status. Our findings highlight the role of gene-environment interactions in PRS prediction variability in Africa. PRS methods that correct for these interactions, coupled with the increased representation of Africans in GWAS, may improve PRS prediction in Africa.
Sections du résumé
BACKGROUND
BACKGROUND
Polygenic prediction studies in continental Africans are scarce. Africa's genetic and environmental diversity pose a challenge that limits the generalizability of polygenic risk scores (PRS) for body mass index (BMI) within the continent. Studies to understand the factors that affect PRS variability within Africa are required.
METHODS
METHODS
Using the first multi-ancestry genome-wide association study (GWAS) meta-analysis for BMI involving continental Africans, we derived a multi-ancestry PRS and compared its performance to a European ancestry-specific PRS in continental Africans (AWI-Gen study) and a European cohort (Estonian Biobank). We then evaluated the factors affecting the performance of the PRS in Africans which included fine-mapping resolution, allele frequencies, linkage disequilibrium patterns, and PRS-environment interactions.
RESULTS
RESULTS
Polygenic prediction of BMI in continental Africans is poor compared to that in European ancestry individuals. However, we show that the multi-ancestry PRS is more predictive than the European ancestry-specific PRS due to its improved fine-mapping resolution. We noted regional variation in polygenic prediction across Africa's East, South, and West regions, which was driven by a complex interplay of the PRS with environmental factors, such as physical activity, smoking, alcohol intake, and socioeconomic status.
CONCLUSIONS
CONCLUSIONS
Our findings highlight the role of gene-environment interactions in PRS prediction variability in Africa. PRS methods that correct for these interactions, coupled with the increased representation of Africans in GWAS, may improve PRS prediction in Africa.
Identifiants
pubmed: 38816834
doi: 10.1186/s13073-024-01348-x
pii: 10.1186/s13073-024-01348-x
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
74Subventions
Organisme : Wellcome Trust
ID : 214205/Z/18/Z
Pays : United Kingdom
Organisme : National Institute for Health Care Management Foundation
ID : U54HG006938
Organisme : H2020 European Institute of Innovation and Technology
ID : 101016775
Organisme : Programma Operativo Nazionale Ricerca e Competitività
ID : 2014-2020.4.01.15-0012
Informations de copyright
© 2024. The Author(s).
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