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Associations between age of menarche and genetic variation in women of African descent: genome-wide association study and polygenic score analysis

Abstract

Introduction Many diseases of adulthood are associated with a woman’s age at menarche. Genetic variation affects age at menarche, but it remains unclear whether in women of African ancestry the timing of menarche is regulated by genetic variants that were identified in predominantly European and East Asian populations.

Methods We explored the genetic architecture of age at menarche in 3145 women of African ancestry who live in the USA, Barbados and Nigeria. We undertook a genome-wide association study, and evaluated the performance of previously identified variants.

Results One variant was associated with age at menarche, a deletion at chromosome 2 (chr2:207216165) (p=1.14×10−8). 349 genotyped variants overlapped with these identified in populations of non-African ancestry; these replicated weakly, with 51.9% having concordant directions of effect. However, collectively, a polygenic score constructed of those previous variants was suggestively associated with age at menarche (beta=0.288 years; p=0.041). Further, this association was strong in women enrolled in the USA and Barbados (beta=0.445 years, p=0.008), but not in Nigerian women (beta=0.052 years; p=0.83).

Discussion This study suggests that in women of African ancestry the genetic drivers of age at menarche may differ from those identified in populations of non-African ancestry, and that these differences are more pronounced in women living in Nigeria, although some associated trait loci may be shared across populations. This highlights the need for well-powered ancestry-specific genetic studies to fully characterise the genetic influences of age at menarche.

  • epidemiology
  • reproductive health
  • genetic epidem

Data availability statement

Data are available in a public, open access repository. The genotype data of the Root genome-wide association study are posted in dbGaP (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000383.v1.p1).

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