Significance Diabetic kidney disease (DKD) is the most common cause of chronic and end-stage renal failure in the world. In a genetically susceptible host, poor metabolic control contributes to DKD development. The epigenome integrates signals from sequence variations and environmental alterations. We performed genome-wide DNA methylation association analysis in one of the best-characterized kidney disease cohorts: The Chronic Renal Insufficiency Cohort study. Complex computational integration analysis indicated the key role of genetic variations in DNA methylation. Our analysis highlighted loci, where methylation and gene-expression changes likely mediate the genotype effect on kidney disease development. Functional annotation of high-confidence genes suggested the causal role of inflammation, specifically, complement activation and apoptotic cell clearance in kidney disease development.