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.

Keywords: diabetic nephropathy; longitudinal phenotype; morphogenomics; pathway networks; transcriptomic profiling.

Figure 1

Schematic representation of the study design to identify VvInt associated co-expressed modules and long-term clinical outcome. In Step 1, modules or groups of genes with similar expression profiles are constructed from the transcriptome profile using a Weighted Gene Coexpression Analysis strategy. In Step 2, module eigengene (ME) is derived from each module and associated to clinical and structural parameters. The heatmap table illustrates the correlation coefficients of the module eigengene to the tested parameters. The significant modules (represented with asterisks) are then further investigated for functional enrichments.

Figure 2

Association of module eigengene (ME) to VvInt and ACR/iGFR at the time of biopsy. 11 co-expressed modules were identified from tubulointerstitial gene expression profiles (n=49) in kidney tissue from Pima Indians. VvInt associated modules with a q-value ≤0.05 are considered significant (MEbrown, MEblack, MEblue and MEgreen). Green color indicates a negative correlation and red color indicates a positive correlation. The number inside each box is the correlation coefficient (Pearson correlation). Significance is denoted as *. The grey module collects the genes that do not share similar expression pattern.

Figure 3

Transcriptional networks generated from the top 100 highly connected VvInt correlated transcripts. The connections or edges between the transcripts are established by a function word (inhibition, activation, regulation) derived from the known literature via Natural Language Processing. A) Positively-correlated VvInt network and B) Negatively-correlated VvInt network.

Figure 4

Ingenuity Pathway network showing significant pathways (P-value ≤0.05) enriched by VvInt correlated transcripts. Pathways are connected by 1 or more shared genes. The network displays two principal domains driven by negatively correlated (left) and positively correlated (right) transcripts. The nodes (pathways) are connected by (edges) genes shared between them

Figure 5

Association of four VvInt correlated modules and long-term clinical outcomes (ACR/iGFR). r ≥0.3 and P-value ≤0.05 are considered significant. Green color indicates a negative and red color indicates a positive correlation of modules to outcomes. The number inside each box is the correlation coefficient (Pearson correlation). Significance is denoted as *

Figure 6

Transcriptional network generated from differentially expressed transcripts comparing ERCB DKD with healthy controls. The network represents the top 100 highly connected transcripts. The main nodes seen in the morphogenomic study in early DKD in Pima Indians are maintained and directionality of expression changes is conserved in 98.85% of nodes. The node color represents the direction of expression in DKD. Green = Decreased, Red = Increased levels compared to controls.