Genetic insights into the age-specific biological mechanisms governing human ovarian ageing

Abstract

There is currently little evidence that the genetic basis of human phenotype varies signifi- cantly across the lifespan. However, time-to-event phenotypes are understudied and can be thought of as reflecting an underlying hazard, which is unlikely to be constant through life when values take a broad range. Here, we find that 74% of 245 genome-wide significant genetic associations with age at natural menopause (ANM) in the UK Biobank show a form of age-specific effect. Nineteen of these replicated discoveries are identified only by our modelling framework, which determines the time-dependency of DNA variant-age-at-onset associations, without a significant multiple-testing burden. Across the range of early to late menopause, we find evidence for significantly different underlying biological pathways, changes in the sign of genetic correlations of ANM to health indicators and outcomes, and differences in inferred causal relationships. We find that DNA damage response processes only act to shape ovarian reserve and depletion for women of early ANM. Genetically mediated delays in ANM were associated with increased relative risk of breast cancer and leiomyoma at all ages, and with high cholesterol and heart failure for late-ANM women. These findings suggest that a better understanding of the age-dependency of genetic risk factor relationships among health indicators and outcomes is achievable through appropriate statistical modelling of large-scale biobank data.

Competing Interest Statement

MRR receives research funding from Boehringer Ingelheim for a research project unrelated to that presented here. SEO is an employee of MSD at the time of the submission, contribution to the research occurred during the affiliation at the University 568 of Lausanne.

Funding Statement

This project was funded by an SNSF Eccellenza Grant to MRR (PCEGP3-181181), and by core funding from the Institute of Science and Technology Austria.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This project uses UK Biobank data under project 35520. UK Biobank genotypic and phenotypic data is available through a formal request at (http://www.ukbiobank.ac.uk). The UK Biobank has ethics approval from the North West Multi-centre Research Ethics Committee (MREC). For access to be granted to the Estonian Biobank genotypic and corresponding phenotypic data, a preliminary application must be presented to the oversight committee, who must first approve the project, ethics permission must then be obtained from the Estonian Committee on Bioethics and Human Research, and finally a full project must be submitted and approved by the Estonian Biobank. This project was granted ethics approval by the Estonian Committee on Bioethics and Human Research (https://genomics.ut.ee/en/biobank.ee/data-access).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data Availability

The BayesW model was executed with the software Hydra, with full open source code available at https://github.com/medical-genomics-group/hydra [28]. The scripts used to execute CAMP model are available at https://github.com/svenojavee/CAMP. Age-specific summary statistic estimates are released publicly on Dryad: https://doi.org/10.5061/dryad.nvx0k6dx5.

https://doi.org/10.5061/dryad.nvx0k6dx5

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