Epigenetic data, especially DNA methylation, contain the footprints of environmental exposures accumulated over the lifetime. In previous work, we have identified over 4,000 methylation sites along the genome to be associated with smoking, over 1,500 with alcohol consumption, and over 500 with BMI. These findings were obtained using data from the Melbourne Collaborative Cohort Study in approximately 7,000 participants; DNA methylation was measured in blood using the Illumina HM450K assay (~480,000 methylation sites). We hypothesise that methylation changes are more abundant and marked in individuals who are more affected by lifestyle exposures, or have been more heavily exposed than the level measured using questionnaires. We will seek to maximise the use of the available data by i) building methylation scores (similar to polygenic risk scores) for lifestyle factors to quantify their damage on the methylome, and ii) using these scores as well as methylation measures at individual genetic loci to improve the prediction of cancer risk (several types e.g. bladder, breast, colorectal, prostate, etc.). The ideal student would have a background in epidemiology, statistics or bioinformatics, a desire to develop their data analysis skills and to make a contribution to cancer research. Depending on the specific sub-project undertaken using these data, methods will include: various types of regression models including linear, logistic, mixed-effects, regularised regression, survival analysis, pathway analyses, scientific writing.
Cancer risk, Epigenetics, DNA methylation, Epidemiology, Biostatistics, Genomics, Bioinformatics, Risk prediction
School of Clinical Sciences at Monash Health / Hudson Institute of Medical Research
Masters by research
Top-up scholarship funding available
Monash Medical Centre Clayton