Comparison of Kidney Transcriptomic Profiles of Early and Advanced Diabetic Nephropathy Reveals Potential New Mechanisms for Disease Progression

Abstract

To identify the factors mediating the progression of diabetic nephropathy (DN), we performed RNA sequencing of kidney biopsy samples from patients with early DN, advanced DN, and normal kidney tissue from nephrectomy samples. A set of genes that were upregulated at early but downregulated in late DN were shown to be largely renoprotective, which included genes in the retinoic acid pathway and glucagon-like peptide 1 receptor. Another group of genes that were downregulated at early but highly upregulated in advanced DN consisted mostly of genes associated with kidney disease pathogenesis, such as those related to immune response and fibrosis. Correlation with estimated glomerular filtration rate (eGFR) identified genes in the pathways of iron transport and cell differentiation to be positively associated with eGFR, while those in the immune response and fibrosis pathways were negatively associated. Correlation with various histopathological features also identified the association with the distinct gene ontological pathways. Deconvolution analysis of the RNA sequencing data set indicated a significant increase in monocytes, fibroblasts, and myofibroblasts in advanced DN kidneys. Our study thus provides potential molecular mechanisms for DN progression and association of differential gene expression with the functional and structural changes observed in patients with early and advanced DN.

Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney

“…We used snRNA-seq and snATAC-seq to identify a subpopulation of proximal tubule (PT_VCAM1) that expressed VCAM1, HAVCR1 (KIM-1), vimentin (VIM), PROM1 (CD133), and CD24. The PT_VCAM1 population was also identified in bulk RNA-seq datasets from non-tumor TCGA kidney and human diabetic nephropathy 65 . The proportion of PT_VCAM1 increased in response to acute and chronic kidney injury in both mouse and human 69 .…”

“…For the mouse ischemia reperfusion dataset from Liu et al 69 , a normalized count matrix was downloaded from GSE98622 and converted to human annotations using biomaRt and ensembl prior to deconvolution with BisqueRNA with default parameters. For the diabetic nephropathy dataset 65 , fastq files were downloaded from GSE128736, transcript abundance was quantified with Salmon using GRCh38, count matrices were imported to DESeq2 with tximport, and data was normalized prior to deconvolution with BisqueRNA.…”

Time-series proteomic study of the response of HK-2 cells to hyperglycemic, hypoxic diabetic-like milieu

“…A similar discordance between the transcriptome and the metabolome in sciatic nerve from db/db type 2 diabetic mice led the authors to suggest that post-transcriptional or post-translational modifications are important in the development of diabetic nephropathy [30]. Moreover, different transcriptomic studies of kidney biopsy samples from patients with DKD or DN have not identified significant changes in the mRNA levels of glycolytic enzymes [33,34].…”

Collecting duct cells show differential retinoic acid responses to acute versus chronic kidney injury stimuli

“…In diabetic mouse kidneys, atRA biosynthesis and atRA-dependent gene expression are compromised 73 , at least in part, due to o-GlcNAcylation of proteins crucial for retinoid binding, metabolism and signalling 74 . Furthermore, a biphasic regulation of renal RA/RAR signalling has been suggested by transcriptomic analysis of renal biopsy tissues of early-and late-stage diabetic nephropathy, respectively 75 .…”