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Abstract: FR-PO404

Integrated Epigenetic Analysis for Kidney Function and Functional Decline Defines Novel Biological Pathways for Patients with Diabetic Kidney Disease

Session Information

Category: Diabetic Kidney Disease

  • 601 Diabetic Kidney Disease: Basic

Authors

  • Sheng, Xin, university of pennsylvania, Philadelpiha, Pennsylvania, United States
  • Qiu, Chengxiang, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Gluck, Caroline A., Nemours/AI DuPont Hospital for Children, Wilmington, Delaware, United States
  • Townsend, Raymond R., University of Pennsylvania School of Medicine, Villanova, Pennsylvania, United States
  • Susztak, Katalin, University of Pennsylvania, Philadelphia, Pennsylvania, United States
Background

Poor metabolic control induces epigenetic changes, which play an important role in development and progression of diabetic kidney disease (DKD). Prior studies failed to integrate epigenetic information with genotype and transcriptomic data. Here we performed an integrated epigenetic, genetic and transcriptomic analysis in CRIC (Chronic Renal Insufficiency Cohort).

Methods

We analyzed genome wide cytosine methylation changes in blood samples of 473 patients with DKD from the CRIC. Subjects were matched for baseline features but showed differences in their kidney function decline. We adopted linear regression model adjusted for age, sex, batch, genetic background, hypertension, cell type heterogeneity and glucose control for eGFR and eGFR slope. To distinguish between genetically or environmentally driven methylation differences, we catalogued genotype-driven methylation changes by performing mQTL (methylation quantitative trait) analysis. To define genetically driven gene expression changes, we performed expression of quantitative trait analysis (eQTL). Bayesian co-localization analysis was adopted to identify causal genes by integrating GWAS, mQTL and eQTL datasets.

Results

We identified that methylation level of 2 probes significantly associated with baseline kidney function (eGFR). Methylation level of 9 probes significantly association with kidney function decline. We were able to replicate the association for 3 of the 11 probes in the ARIC (Atherosclerosis Risk in Communities Study) and FHS (Framingham Heart Study) cohorts. We found that methylation of 6 of the 11 loci were driven by genetic variation (mQTL SNP). To understand functional consequences of methylation changes, we integrated the results with RNA-seq data using expression of quantitative trait (eQTL) analysis. We found that the expression of (Lyzosome) LYZ significantly associated with the genetic variation and methylation differences. Transcript level of LYZ in the kidney also strongly correlated with kidney function.

Conclusion

We identified and replicated significant methylation changes associated with kidney function and functional decline. Integrated genetic, epigenetic and transcriptomic analysis defines genetically and potentially environmentally driven changes and novel biological mechanisms for DKD.