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

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_278672D79D5D
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Genetic insights into the age-specific biological mechanisms governing human ovarian aging.
Journal
American journal of human genetics
Author(s)
Ojavee S.E., Darrous L., Patxot M., Läll K., Fischer K., Mägi R., Kutalik Z., Robinson M.R.
ISSN
1537-6605 (Electronic)
ISSN-L
0002-9297
Publication state
Published
Issued date
07/09/2023
Peer-reviewed
Oui
Volume
110
Number
9
Pages
1549-1563
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
There is currently little evidence that the genetic basis of human phenotype varies significantly 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 modeling 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 signs 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 modeling of large-scale biobank data.
Keywords
Humans, Female, Aging/genetics, Menopause/genetics, Age of Onset, Ovary, Risk Factors, Age Factors, age at natural menopause, age at onset, age-specific genetic effect, aging, common complex disease, disease etiology, genome-wide association study, interaction, significance testing, time to event
Pubmed
Web of science
Open Access
Yes
Create date
10/08/2023 14:19
Last modification date
23/01/2024 8:22
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