Variability of polygenic prediction for body mass index in Africa

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dc.contributor.authorNorris, Shane A.
dc.contributor.authorChikowore, Tinashe
dc.contributor.authorLäll, Kristi
dc.contributor.authorMicklesfield, Lisa K.
dc.contributor.authorLombard, Zane
dc.contributor.authorGoedecke, Julia H.
dc.contributor.authorFatumo, Segun
dc.contributor.authorMagi, Reedik
dc.contributor.authorRamsay, Michele
dc.contributor.authorFranks, Paul W.
dc.contributor.authorPare, Guillaume
dc.contributor.authorMorris, Andrew P.
dc.date.accessioned2024-08-04T17:08:43Z
dc.date.available2024-08-04T17:08:43Z
dc.date.issued2024
dc.description.abstractBackground: 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: 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: 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: 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.
dc.description.sponsorshipNational Human Genome Research Institute (NHGRI)
dc.description.submitterPM2024
dc.facultyFaculty of Health Sciences
dc.identifier0000-0001-7124-3788
dc.identifier.citationChikowore, T., Läll, K., Micklesfield, L.K. et al. Variability of polygenic prediction for body mass index in Africa. Genome Med 16, 74 (2024). https://doi.org/10.1186/s13073-024-01348-x
dc.identifier.issn1756-994X (online)
dc.identifier.other10.1186/s13073-024-01348-x
dc.identifier.urihttps://hdl.handle.net/10539/39965
dc.journal.titleGenome Medicine
dc.language.isoen
dc.publisherBioMed Central (BMC)
dc.rights© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.
dc.schoolSchool of Clinical Medicine
dc.subjectBMI
dc.subjectVariability
dc.subjectPolygenic prediction
dc.subjectPolygenic risk score
dc.subject.otherSDG-3: Good health and well-being
dc.titleVariability of polygenic prediction for body mass index in Africa
dc.typeArticle
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