Postdoc Recipient: Dr. Zhoufeng Ye, Centre for Epidemiology and Biostatistics (CEB), University of Melbourne
Supervisors: Associate Professor Shuai Li, CEB
Awarded: $40,000 in GERA’s Grant Round 1 (2025)
About the project: Menopause marks a critical biological milestone in women and is associated with numerous long-term health outcomes, including cardiovascular disease, osteoporosis, cognitive decline, hormone-related cancers, and mortality. While age at menopause has known genetic and environmental influences, the epigenetic mechanisms underlying menopausal timing and status
remain underexplored. DNA methylation (DNAm), an epigenetic marker responsive to environmental exposures and aging, holds promise for identifying biological pathways involved in reproductive aging. Importantly, emerging studies have linked DNAm-based aging clocks (e.g.,GrimAge, DunedinPACE) to menopause-related traits. However, a key research gap remains: few studies have systematically investigated CpG-level and region-level DNAm changes associated with menopause traits, incorporating robust discovery and replication designs and exploring causal and functional relevance. This project will address this gap using well-powered multicohort datasets and state-of-the-art analytical approaches.
Research aims:
- Identify CpG-level and region-level DNAm signatures associated with age at menopause
and menopausal status. - Investigate functional relevance by integrating regulatory annotations and examining
associations with epigenetic aging clocks. - Evaluate potential causal relationships between DNAm and menopause traits using
Mendelian randomisation (MR).
Methods:
I will use two blood-based DNAm datasets as discovery cohorts, including the Australian Mammographic Density Twins and Sisters Study (AMDTSS) and the Melbourne Collaborative Cohort Study (MCCS). These include high-quality Illumina 450K array DNAm profiles and detailed phenotypic information on age at natural menopause and menopausal status. Epigenome-wide association studies (EWAS) will be conducted within each dataset, adjusting for key covariates such as age, batch effects, and cell composition.
Differentially methylated regions (DMRs) will be identified using both DMRcate and comb-p with stringent significance thresholds. To complement standard EWAS approaches, I will apply function-on-region regression models (e.g., functional linear transformation) to assess region based effects, as previously implemented in my epigenetic project of age at menarche.
To assess replication, I will use the publicly available Parkinson’s Environment & Genes (PEG) study, which includes blood-based Illumina 450K DNAm and relevant menopause phenotype data. Top CpGs and DMRs from discovery will be tested in PEG for consistency in association direction and significance.
To explore causality, I will perform MR using publicly available mQTL data and GWAS summary statistics for age at menopause and menopausal status from the ReproGen consortium and UK Biobank. Directionality will be evaluated using Steiger filtering and bidirectional MR. Top loci will be annotated using resources such as MethMotif and ENCODE SCREEN to assess enhancer
activity, transcription factor binding, and chromatin interactions.
Lastly, I will evaluate whether menopause traits are correlated with epigenetic clocks in all three datasets and the National Health and Nutrition Examination Survey (NHNES), providing insight into links between reproductive aging and systemic biological aging.
Impact: Ultimately, this work hopes to inform preventive strategies and personalised health interventions targeting women at risk of early or late menopause and associated diseases. Identifying epigenetic marks associated with reproductive timing may also uncover broader aging mechanisms, contributing to public health and health span policy.
Go back to: