Sally Mortlock

Understanding Endometriosis Heterogeneity Across the Life Course

Endometriosis is a heterogeneous condition characterised by wide variation in symptoms, comorbidities, lesion types, and treatment response, contributing to delayed diagnosis and poor outcomes. This PhD project will investigate the genetic and life course drivers of this heterogeneity, examining how symptom profiles and comorbidities cluster and vary across women.

Using large-scale datasets including the Australian Longitudinal Study on Women’s Health (ALSWH) and international genomic resources, the project will characterise disease subtypes, assess causal links between endometriosis, symptoms and comorbidities, and explore how genetic risk interacts with life course exposures to shape symptom trajectories. Advanced methods including longitudinal and trajectory modelling and causal inference will be applied.

The project will generate new insights into endometriosis subtypes, underlying mechanisms, and gene–environment interactions, with the goal of improving early diagnosis and informing more personalised, targeted care pathways.

Understanding Shared Mechanisms Across Reproductive and Menstrual Health

This project will apply genetic epidemiology and life course approaches to investigate the causes, overlap, and shared biological mechanisms underlying reproductive and menstrual disorders across women’s lives. Focusing on conditions including endometriosis, endometritis, infertility, polyendocrine metabolic ovarian syndrome (PMOS), fibroids, heavy menstrual bleeding, and related reproductive traits and milestones (e.g., age at menarche and menopause), the project will examine how co-occurring conditions interact and contribute to women’s health across the life course. Moving beyond a disease-centred approach, the research will adopt a person-centred framework to identify shared pathways and causal links between reproductive disorders, fertility outcomes, gynaecological cancers, and broader chronic disease risk. Using methods including Mendelian randomisation, polygenic risk modelling, and interaction analyses, the project will investigate how genetic susceptibility and life course exposures (e.g., BMI, contraceptive use, reproductive stage) influence disease risk, infertility, and condition overlap. Findings will support earlier identification of risk, targeted interventions, and improved women’s health outcomes.