Uncovering the Genetic Architecture and Evolutionary Roots of Androgenetic Alopecia in African Men

January 2024 in “ bioRxiv (Cold Spring Harbor Laboratory) ”

Rohini Janivara, Ujani Hazra, Aaron Pfennig, Maxine Harlemon, Michelle S. Kim, Muthukrishnan Eaaswarkhanth, Wenlong Carl Chen, Adebola Ogunbiyi, Paidamoyo Kachambwa, Lindsay N. Petersen, Mohamed Jalloh, James E. Mensah, Andrew A. Adjei, Ben Adusei, Maureen Joffe, Serigne Guèye, Oseremen I. Aisuodionoe-Shadrach, P. Fernandez, Thomas E. Rohan, Caroline Andrews, Timothy R. Rebbeck, Akindele Olupelumi Adebiyi, Ilir Agalliu, Joseph Lachance

androgenetic alopecia male pattern baldness genetic predictions GWAS autosomal X chromosome SNPs EDA2R gene AR gene allele frequency genome-wide association study single nucleotide polymorphisms

Studysummary This study found that genetic predictions of male pattern baldness derived from European data do not accurately predict baldness in African populations, highlighting significant continental differences in genetic architecture and evolutionary history.

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The study "Uncovering the genetic architecture and evolutionary roots of androgenetic alopecia in African men" examined the genetics of male pattern baldness in 2,136 men from Ghana, Nigeria, Senegal, and South Africa. The researchers found that genetic predictions of baldness based on European data performed worse in African populations, with AUC statistics ranging from 0.513 to 0.546. The first African GWAS of androgenetic alopecia identified 266 moderately significant associations, 51 of which were independent. Most baldness associations were autosomal, and the X chromosome did not have a large impact on baldness in African men. The study found no evidence that European-ascertained baldness hits were enriched for signatures of ancient introgression. However, multiple baldness-associated SNPs near the EDA2R and AR genes showed large allele frequency differences between continents. The findings suggest that evolutionary history contributes to the limited portability of genetic predictions across ancestries.

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