A molecular morphometric approach to diabetic kidney disease can link structure to function and outcome

Abstract

Diabetic kidney disease is the leading cause of kidney failure. However, studies of molecular mechanisms of early kidney damage are lacking. Here we examined for possible linkage between transcriptional regulation and quantitative structural damage in early diabetic kidney disease in Pima Indians with type 2 diabetes. Tissue obtained from protocol kidney biopsies underwent genome-wide compartment-specific gene expression profiling and quantitative morphometric analysis. The ultrastructural lesion most strongly associated with transcriptional regulation was cortical interstitial fractional volume (VvInt), an index of tubule-interstitial damage. Transcriptional co-expression network analysis identified 1843 transcripts that correlated significantly with VvInt. These transcripts were enriched for pathways associated with mitochondrial dysfunction, inflammation, migratory mechanisms, and tubular metabolic functions. Pathway network analysis identified IL-1β as a key upstream regulator of the inflammatory response and five transcription factors cooperating with p53 to regulate metabolic functions. VvInt-associated transcripts showed significant correlation with the urine albumin to creatinine ratio and measured glomerular filtration rate 10 years after biopsy, establishing a link between the early molecular events and long-term disease progression. Thus, molecular mechanisms active early in diabetic kidney disease were revealed by correlating intrarenal transcripts with quantitative morphometry and long-term outcomes. This provides a starting point for identification of urgently needed therapeutic targets and non-invasive biomarkers of early diabetic kidney disease.

An integrative systems biology approach for precision medicine in diabetic kidney disease

“…Recent work published by our group tackled this challenge by providing transcriptomic data of protocol kidney biopsies derived from Pima Indian participants with type 2 diabetes. 24 Together, these studies illustrate the success of systems biology approaches at identifying novel markers of DKD progression and providing mechanistic insights involved in progressive CKD and early DKD. response, such that a subgroup of patients benefitted whereas other subgroups did not or were even harmed.…”

“…However, the lack of kidney biopsy samples from patients with early stage DKD is a big barrier to the discovery of novel biomarkers. Recent work published by our group tackled this challenge by providing transcriptomic data of protocol kidney biopsies derived from Pima Indian participants with type 2 diabetes . These individuals did not have overt clinical evidence of DKD at the time of biopsy but the ultrastructure lesion was observed morphologically.…”

“…Integrative analysis of the transcriptomic data derived from tubular tissue with the quantitative morphometric analysis of the ultrastructural lesion indicated that the genes significantly correlated with tubule‐interstitial damage are enriched for pathways involving in mitochondrial dysfunction, inflammation, migratory mechanisms and tubular metabolic functions suggesting ongoing disease processes. Importantly, the expression of these genes at time of biopsy showed significant association with the urine albumin‐to‐creatinine ratio (uACR) and measured eGFR 10 years after biopsy, indicating a link between the early molecular events and long‐term disease progression . These transcriptomic data, along with rich longitudinal clinical follow‐up information and the plasma and urine samples collected following standard procedures, provides a valuable resource which will continuously contribute to future identification and validation of novel therapeutic targets and non‐invasive biomarkers of early DKD.…”

“…High‐throughput multi‐omics approaches (transcriptomics, proteomics, metabolomics and lipidomics) have been used to profile patients' biospecimen (kidney biopsy, plasma and urine samples). These multi‐omics data sets contributed to the discovery of biomarker candidates that are associated with disease progression . Table includes molecular biomarkers that were discovered using systems biology approaches with demonstrated association with kidney outcomes in patient‐related studies.…”

“…These multiomics data sets contributed to the discovery of biomarker candidates that are associated with disease progression. 17,[22][23][24][25][26][27][28][29] Table 2 includes molecular biomarkers that were discovered using systems biology approaches with demonstrated association with kidney outcomes in patient-related studies.…”