Blood DNA methylation profiling identifies candidate diabetic kidney disease risk signatures in the PROPHECY Aboriginal Diabetes Study

Background: Diabetic kidney disease is a leading cause of kidney failure, yet molecular predictors of risk remain poorly defined, particularly among Indigenous Australians who experience a disproportionate burden. We aimed to identify blood-derived candidate DNA methylation signatures associated with Kidney Disease: Improving Global Outcomes (KDIGO) risk categories in the PROPHECY Aboriginal Diabetes Study. Methods: We applied methyl-CpG binding domain sequencing to blood-derived DNA from 95 participants stratified as non-diabetic (n = 23), low-risk (n = 21), moderate-risk (n = 26), high-risk (n = 14) or very-high-risk (n = 11). Differential MBD-enriched methylated regions were assessed using covariate-adjusted models incorporating clinical, leukocyte-marker and CpG-density covariates. Candidate regions were prioritised using a nominal discovery threshold and explored using annotation, random forest modelling and human podocyte experiments. Results: For the primary diabetic kidney disease risk contrast, 1,317 regions met the nominal discovery threshold of P < 0.001, but no region reached FDR < 0.10. Across 16 predefined analysis terms - 11 pairwise/grouped contrasts and 5 single-group terms - 22,392 nominal DMR entries met P < 0.001, corresponding to 13,024 unique candidate regions. Exploratory random forest models suggested that methylation features may contribute discriminatory information beyond clinical covariates, although estimates require independent validation. Podocyte analyses provided locus-level functional context but not genome-wide cross-tissue replication. Conclusions: This cross-sectional discovery study nominates research-grade candidate methylation biomarkers and pathways for future longitudinal validation in PROPHECY and external cohorts.