PhD Recipient: Di Mu, PhD student, Centre for Epidemiology and Biostatistics (CEB), Melbourne School of Population and Global Health, University of Melbourne
Supervisors: A/Prof Shuai Li, Dr James Dowty, Prof Mark Jenkins, Dr Sibel Saya, Dr Jiadong Mao.
Funding: $10,000 in GERA’s PhD Top Up Scholarship Round 2 (2026)
About the project:
This project aims to improve how well breast cancer polygenic risk scores (PRSs) perform across diverse ancestries, addressing the current inequity caused by PRSs being largely developed in European-ancestry populations. Using data from UK Biobank and the Breast Cancer Association Consortium, Di Mu will quantify individual-level genetic distance from the European training population (e.g. via Mahalanobis and other cluster-aware metrics) and incorporate this information into a transfer learning framework. Existing breast cancer PRSs will be adaptively calibrated, penalised or weighted according to each individual’s genetic distance, treating PRS portability as a continuous property rather than a fixed feature of broad ancestry groups. The refined PRS models will be evaluated against standard approaches (such as p-value thresholding, LDpred2 and PRS-CS) using discrimination, calibration and risk-stratification metrics. The work seeks to advance more accurate, interpretable and equitable genomic risk prediction for breast cancer and will provide the candidate with advanced training in statistical genetics, transfer learning and precision prevention.
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