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Genetic links between ovarian ageing, cancer risk and de novo mutation rates

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posted on 2025-08-02, 12:58 authored by S Stankovic, S Shekari, QQ Huang, EJ Gardner, EV Ivarsdottir, NDL Owens, N Mavaddat, A Azad, G Hawkes, KA Kentistou, RN Beaumont, FR Day, Y Zhao, H Jonsson, T Rafnar, V Tragante, G Sveinbjornsson, A Oddsson, U Styrkarsdottir, J Gudmundsson, SN Stacey, DF Gudbjartsson, K Kennedy, AR Wood, MN Weedon, KK Ong, CF Wright, ER Hoffmann, P Sulem, ME Hurles, KS Ruth, HC Martin, K Stefansson, JRB Perry, A Murray
Human genetic studies of common variants have provided substantial insight into the biological mechanisms that govern ovarian ageing1. Here we report analyses of rare protein-coding variants in 106,973 women from the UK Biobank study, implicating genes with effects around five times larger than previously found for common variants (ETAA1, ZNF518A, PNPLA8, PALB2 and SAMHD1). The SAMHD1 association reinforces the link between ovarian ageing and cancer susceptibility1, with damaging germline variants being associated with extended reproductive lifespan and increased all-cause cancer risk in both men and women. Protein-truncating variants in ZNF518A are associated with shorter reproductive lifespan—that is, earlier age at menopause (by 5.61 years) and later age at menarche (by 0.56 years). Finally, using 8,089 sequenced trios from the 100,000 Genomes Project (100kGP), we observe that common genetic variants associated with earlier ovarian ageing associate with an increased rate of maternally derived de novo mutations. Although we were unable to replicate the finding in independent samples from the deCODE study, it is consistent with the expected role of DNA damage response genes in maintaining the genetic integrity of germ cells. This study provides evidence of genetic links between age of menopause and cancer risk.

Funding

MC_UU_00006/1

MC_UU_00006/2

MC_UU_12015/1

MC_UU_12015/2

Medical Research Council (MRC)

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© 2024 The Author(s). Open Access 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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Notes

This is the final version. Available from Nature Research via the DOI in this record. Data availability: All data used in discovery analyses are available upon application from the UK Biobank study and Genomics England. Research on the de-identified patient data used in this publication can be carried out in the Genomics England Research Environment subject to a collaborative agreement that adheres to patient led governance. All interested readers will be able to access the data in the same manner that the authors accessed the data. For more information about accessing the data, interested readers may contact research-network@genomicsengland.co.uk or access the relevant information on the Genomics England website: https://www.genomicsengland.co.uk/research. The deCODE dataset was used for replication purposes and only summary level results for the specific findings are provided.

Journal

Nature

Pagination

608-614

Publisher

Springer Nature

Place published

England

Version

  • Version of Record

Language

en

FCD date

2024-11-01T14:17:56Z

FOA date

2025-03-07T01:03:14Z

Citation

Vol. 633, No. 8030, pp. 608-614

Department

  • Clinical and Biomedical Sciences

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