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Genome-wide meta-analysis of common variant differences between men and women.

Hum. Mol. Genet. 21, 4805-4815 (2012)
Verlagsversion Volltext DOI PMC
Free by publisher
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10(-8)) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ∼115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter HUMAN SEX-RATIO; ASSOCIATION; SIMULATION; DISEASE; BIRTH; TIME
ISSN (print) / ISBN 0964-6906
e-ISSN 1460-2083
Quellenangaben Band: 21, Heft: 21, Seiten: 4805-4815 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed