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Poor metabolic control and host genetic predisposition are critical for diabetic kidney disease (DKD) development. The epigenome integrates information from sequence variations and metabolic alterations. Here, we performed a genome-wide methylome association analysis in 500 subjects with DKD from the Chronic Renal Insufficiency Cohort for DKD phenotypes, including glycemic control, albuminuria, kidney function, and kidney function decline. We show distinct methylation patterns associated with each phenotype. We define methylation variations that are associated with underlying nucleotide variations (methylation quantitative trait loci) and show that underlying genetic variations are important drivers of methylation changes. We implemented Bayesian multitrait colocalization analysis (moloc) and summary data-based Mendelian randomization to systematically annotate genomic regions that show association with kidney function, methylation, and gene expression. We prioritized 40 loci, where methylation and gene-expression changes likely mediate the genotype effect on kidney disease development. Functional annotation suggested the role of inflammation, specifically, apoptotic cell clearance and complement activation in kidney disease development. Our study defines methylation changes associated with DKD phenotypes, the key role of underlying genetic variations driving methylation variations, and prioritizes methylome and gene-expression changes that likely mediate the genotype effect on kidney disease pathogenesis., Competing Interests: The authors declare no competing interest.

In patients with diabetes mellitus, poor metabolic control has a long-lasting impact on kidney disease development. Epigenetic changes, including cytosine methylation, have been proposed as potential mediators of the long-lasting effect of adverse metabolic events. Our understanding of the presence and contribution of methylation changes to disease development is limited because of the lack of comprehensive base-resolution methylome information of human kidney tissue samples and site-specific methylation editing. Base resolution, whole-genome bisulfite sequencing methylome maps of human diabetic kidney disease (DKD) tubule samples, and associated gene expression measured by RNA sequencing highlighted widespread methylation changes in DKD. Pathway analysis highlighted coordinated (methylation and gene expression) changes in immune signaling, including tumor necrosis factor alpha (TNF). Changes in TNF methylation correlated with kidney function decline. dCas9-Tet1-based lowering of the cytosine methylation level of the TNF differentially methylated region resulted in an increase in the TNF transcript level, indicating that methylation of this locus plays an important role in controlling TNF expression. Increasing the TNF level in diabetic mice increased disease severity, such as albuminuria. In summary, our results indicate widespread methylation differences in DKD kidneys and highlights epigenetic changes in the TNF locus and its contribution to the development of nephropathy in patients with diabetes mellitus.

Epigenetic changes might provide the biological explanation for the long-lasting impact of metabolic alterations of diabetic kidney disease development. Here we examined cytosine methylation of human kidney tubules using Illumina Infinium 450 K arrays from 91 subjects with and without diabetes and varying degrees of kidney disease using a cross-sectional design. We identify cytosine methylation changes associated with kidney structural damage and build a model for kidney function decline. We find that the methylation levels of 65 probes are associated with the degree of kidney fibrosis at genome wide significance. In total 471 probes improve the model for kidney function decline. Methylation probes associated with kidney damage and functional decline enrich on kidney regulatory regions and associate with gene expression changes, including epidermal growth factor (EGF). Altogether, our work shows that kidney methylation differences can be detected in patients with diabetic kidney disease and improve kidney function decline models indicating that they are potentially functionally important.

Diabetic nephropathy accounts for most of the excess mortality in individuals with diabetes, but the molecular mechanisms by which nephropathy develops are largely unknown. Here we tested cytosine methylation levels at 397,063 genomic CpG sites for association with decline in the estimated glomerular filtration rate (eGFR) over a six year period in 181 diabetic Pima Indians. Methylation levels at 77 sites showed significant association with eGFR decline after correction for multiple comparisons. A model including methylation level at two probes (cg25799291 and cg22253401) improved prediction of eGFR decline in addition to baseline eGFR and the albumin to creatinine ratio with the percent of variance explained significantly improving from 23.1% to 42.2%. Cg22253401 was also significantly associated with eGFR decline in a case-control study derived from the Chronic Renal Insufficiency Cohort. Probes at which methylation significantly associated with eGFR decline were localized to gene regulatory regions and enriched for genes with metabolic functions and apoptosis. Three of the 77 probes that were associated with eGFR decline in blood samples showed directionally consistent and significant association with fibrosis in microdissected human kidney tissue, after correction for multiple comparisons. Thus, cytosine methylation levels may provide biomarkers of disease progression in diabetic nephropathy and epigenetic variations contribute to the development of diabetic kidney disease., (Published by Elsevier Inc.)

Purpose of Review: Precision medicine approaches, that tailor medications to specific individuals has made paradigm-shifting improvements for patients with certain cancer types., Recent Findings: Such approaches, however, have not been implemented for patients with diabetic kidney disease. Precision medicine could offer new avenues for novel diagnostic, prognostic and targeted therapeutics development. Genetic studies associated with multiscalar omics datasets from tissue and cell types of interest of well-characterized cohorts are needed to change the current paradigm. In this review, we will discuss precision medicine approaches that the nephrology community can take to analyze tissue samples to develop new therapeutics for patients with diabetic kidney disease.

Poor metabolic control and host genetic predisposition are critical for diabetic kidney disease (DKD) development. The epigenome integrates information from sequence variations and metabolic alterations. Here, we performed a genome-wide methylome association analysis in 500 subjects with DKD from the Chronic Renal Insufficiency Cohort for DKD phenotypes, including glycemic control, albuminuria, kidney function, and kidney function decline. We show distinct methylation patterns associated with each phenotype. We define methylation variations that are associated with underlying nucleotide variations (methylation quantitative trait loci) and show that underlying genetic variations are important drivers of methylation changes. We implemented Bayesian multitrait colocalization analysis (moloc) and summary data-based Mendelian randomization to systematically annotate genomic regions that show association with kidney function, methylation, and gene expression. We prioritized 40 loci, where methylation and gene-expression changes likely mediate the genotype effect on kidney disease development. Functional annotation suggested the role of inflammation, specifically, apoptotic cell clearance and complement activation in kidney disease development. Our study defines methylation changes associated with DKD phenotypes, the key role of underlying genetic variations driving methylation variations, and prioritizes methylome and gene-expression changes that likely mediate the genotype effect on kidney disease pathogenesis. [ABSTRACT FROM AUTHOR]