Transcriptome Analysis of Human Diabetic Kidney Disease

Abstract

OBJECTIVE Diabetic kidney disease (DKD) is the single leading cause of kidney failure in the U.S., for which a cure has not yet been found. The aim of our study was to provide an unbiased catalog of gene-expression changes in human diabetic kidney biopsy samples. RESEARCH DESIGN AND METHODS Affymetrix expression arrays were used to identify differentially regulated transcripts in 44 microdissected human kidney samples. DKD samples were significant for their racial diversity and decreased glomerular filtration rate (~25–35 mL/min). Stringent statistical analysis, using the Benjamini-Hochberg corrected two-tailed t test, was used to identify differentially expressed transcripts in control and diseased glomeruli and tubuli. Two different web-based algorithms were used to define differentially regulated pathways. RESULTS We identified 1,700 differentially expressed probesets in DKD glomeruli and 1,831 in diabetic tubuli, and 330 probesets were commonly differentially expressed in both compartments. Pathway analysis highlighted the regulation of Ras homolog gene family member A, Cdc42, integrin, integrin-linked kinase, and vascular endothelial growth factor signaling in DKD glomeruli. The tubulointerstitial compartment showed strong enrichment for inflammation-related pathways. The canonical complement signaling pathway was determined to be statistically differentially regulated in both DKD glomeruli and tubuli and was associated with increased glomerulosclerosis even in a different set of DKD samples. CONCLUSIONS Our studies have cataloged gene-expression regulation and identified multiple novel genes and pathways that may play a role in the pathogenesis of DKD or could serve as biomarkers.