Characterizing the Transcriptional Features That Underlie Established Injury and Disease Progression in Diabetic Kidney Disease
Paraish S. Misra, Shukai Huang, Lauren Caldwell, Xiaolin He, Tianzhou Zhang, Adriana Krizova, Kevin D. Burns, Richard E. Gilbert, Jeffrey L. Wrana, Darren A. YuenKey Points
Diabetic kidney disease is characterized by a specific transcriptional pattern associated with inflammation and fibrosis, as well as downregulation of metabolic activity. Genes associated with rapid kidney function loss are mostly unique and not associated with other clinical and histopathologic features. Rapid kidney function loss in diabetic kidney disease is associated with lower expression of transcripts related to intercalated cell function and identity.
Background
Diabetes is the leading cause of kidney failure in the developed world. Despite its importance, the molecular events driving the pathogenesis of diabetic kidney disease (DKD) remain incompletely understood. We thus sought to use transcriptional profiling of kidney biopsy tissue to uncover relationships between transcriptional features and clinical parameters related to established kidney injury and disease progression.
Methods
Using bulk RNA sequencing, we comprehensively explored the human diabetic kidney transcriptome in the largest cohort of patients with DKD to be transcriptionally profiled to date. These data were combined with clinical indices of established injury (eGFR, urinary albumin‑creatinine ratio, interstitial fibrosis, and glomerulosclerosis) and disease progression (rate of eGFR decline and progression to ESKD) and integrated with previously published mouse and human datasets to better delineate the transcriptional features that characterize this disease.
Results
We profiled 50 diabetic kidney and 13 healthy control biopsies, identifying a global transcriptional signature of human DKD, which included nearly universal upregulation of
Conclusions
In addition to shedding light on the molecular events underpinning its pathogenesis, our data will serve as a valuable resource to help accelerate the discovery of improved diagnostics and therapeutics for DKD.