Genome-wide analyses identify 25 infertility loci and relationships with reproductive traits across the allele frequency spectrum
Venkatesh, Samvida S; Wittemans, Laura B L; Palmer, Duncan S; Baya, Nikolas A; Ferreira, Teresa; Hill, Barney; Lassen, Frederik Heymann; Parker, Melody J; Reibe, Saskia; Elhakeem, Ahmed; Banasik, Karina; Bruun, Mie T; Erikstrup, Christian; Aagard Jensen, Bitten; Juul, Anders; Mikkelsen, Christina; Nielsen, Henriette S; Ostrowski, Sisse R; Pedersen, Ole B; Rohde, Palle Duun; Sørensen, Erik; Ullum, Henrik; Westergaard, David; Haraldsson, Asgeir; Holm, Hilma; Jonsdottir, Ingileif; Olafsson, Isleifur; Steingrimsdottir, Thora; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Figueredo, Jessica; Karjalainen, Minna K; Pasanen, Anu; Jacobs, Benjamin M; Kalantzis, Georgios; Hubers, Nikki; 7, Genes & Health Research Team; Estonian Biobank Research Team; Estonian Health Informatics Research Team; DBDS Genomic Consortium; FinnGen; Lippincott, Margaret; Fraser, Abigail; Lawlor, Deborah A; Timpson, Nicholas J; Nyegaard, Mette; Stefansson, Kari; Magi, Reedik; Laivuori, Hannele; van Heel, David A; Boomsma, Dorret I; Balasubramanian, Ravikumar; Seminara, Stephanie B; Chan, Yee-Ming; Laisk, Triin; Lindgren, Cecilia M (2025-04-14)
Springer
14.04.2025
Venkatesh, S.S., Wittemans, L.B.L., Palmer, D.S. et al. Genome-wide analyses identify 25 infertility loci and relationships with reproductive traits across the allele frequency spectrum. Nat Genet (2025). https://doi.org/10.1038/s41588-025-02156-8
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Copyright © 2025, The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
Copyright © 2025, The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202504162714
https://urn.fi/URN:NBN:fi:oulu-202504162714
Tiivistelmä
Abstract
Genome-wide association studies (GWASs) may help inform the etiology of infertility. Here, we perform GWAS meta-analyses across seven cohorts in up to 42,629 cases and 740,619 controls and identify 25 genetic risk loci for male and female infertility. We additionally identify up to 269 genetic loci associated with follicle-stimulating hormone, luteinizing hormone, estradiol and testosterone through sex-specific GWAS meta-analyses (n = 6,095–246,862). Exome sequencing analyses reveal that women carrying testosterone-lowering rare variants in some genes are at risk of infertility. However, we find no local or genome-wide genetic correlation between female infertility and reproductive hormones. While infertility is genetically correlated with endometriosis and polycystic ovary syndrome, we find limited genetic overlap between infertility and obesity. Finally, we show that the evolutionary persistence of infertility-risk alleles may be explained by directional selection. Taken together, we provide a comprehensive view of the genetic determinants of infertility across multiple diagnostic criteria.
Genome-wide association studies (GWASs) may help inform the etiology of infertility. Here, we perform GWAS meta-analyses across seven cohorts in up to 42,629 cases and 740,619 controls and identify 25 genetic risk loci for male and female infertility. We additionally identify up to 269 genetic loci associated with follicle-stimulating hormone, luteinizing hormone, estradiol and testosterone through sex-specific GWAS meta-analyses (n = 6,095–246,862). Exome sequencing analyses reveal that women carrying testosterone-lowering rare variants in some genes are at risk of infertility. However, we find no local or genome-wide genetic correlation between female infertility and reproductive hormones. While infertility is genetically correlated with endometriosis and polycystic ovary syndrome, we find limited genetic overlap between infertility and obesity. Finally, we show that the evolutionary persistence of infertility-risk alleles may be explained by directional selection. Taken together, we provide a comprehensive view of the genetic determinants of infertility across multiple diagnostic criteria.
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