Your browser doesn't support javascript.
loading
Genetic insights into the age-specific biological mechanisms governing human ovarian aging.
Ojavee, Sven E; Darrous, Liza; Patxot, Marion; Läll, Kristi; Fischer, Krista; Mägi, Reedik; Kutalik, Zoltan; Robinson, Matthew R.
Affiliation
  • Ojavee SE; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland. Electronic address: sven.ojavee@gmail.com.
  • Darrous L; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, Lausanne, Switzerland.
  • Patxot M; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
  • Läll K; Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
  • Fischer K; Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia; Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia.
  • Mägi R; Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
  • Kutalik Z; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, Lausanne, Switzerland.
  • Robinson MR; Institute of Science and Technology Austria, Klosterneuburg, Austria. Electronic address: matthew.robinson@ist.ac.at.
Am J Hum Genet ; 110(9): 1549-1563, 2023 09 07.
Article in En | MEDLINE | ID: mdl-37543033
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.
Subject(s)
Key words

Full text: 1 Database: MEDLINE Main subject: Aging / Menopause Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Am J Hum Genet Year: 2023 Type: Article

Full text: 1 Database: MEDLINE Main subject: Aging / Menopause Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Am J Hum Genet Year: 2023 Type: Article