Abstract: TH-PO874
Comparison of Kidney Transcriptomic Profiles Between Patients with Early and Advanced Diabetic Nephropathy Reveals Potential New Mechanisms for Disease Progression
Session Information
- Diabetic Kidney Disease: Basic - I
November 07, 2019 | Location: Exhibit Hall, Walter E. Washington Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 601 Diabetic Kidney Disease: Basic
Authors
- Fan, Ying, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
- Yi, Zhengzi, Icahn School of Medicine at Mount Sinai, Elmhurst, New York, United States
- Wang, Niansong, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
- He, John Cijiang, Icahn School of Medicine at Mount Sinai, Elmhurst, New York, United States
Background
Genome-wide gene expression profiling can be useful in providing a global picture of the disease pathogenesis and to identify potential new biomarkers and drug targets for DN.
Methods
We performed RNA sequencing of the whole kidney biopsy samples from 28 patients with early DN (n=6), advanced DN (n=22) and normal kidney tissues (n=9) from nephrectomy samples. Correlation of differentially expressed genes (DEGs) with renal function (eGFR) and histological parameters in the DN patients was analyzed. We took advantage of the recently published scRNA-seq data to perform a computational deconvolution analysis of the gene expression data from whole kidney to estimate the number of cells in the normal and diseased kidneys. Finally, we validated some of these findings by immunostaining of the kidney tissues from these patients.
Results
We found that a group of genes were upregulated at early DN but down-regulated in late DN, many of which were shown to be renoprotective, including those in the retinoic acid and glucagon-like peptide-1 receptor (GLP1R) pathways. Another group of genes that were downregulated at early DN, but highly upregulated in advanced DN, consisted mostly of genes known to be involved in progression of DN, such as those related to immune response and fibrosis. We found that the DEGs in the pathways of iron transport and cell differentiation were positively associated with eGFR, while those in the immune response and fibrosis pathways were negatively associated. We also found that individual renal pathology features were associated with the DEGs belonging to the unique GO terms and pathways. We performed deconvolution analysis of the RNA sequencing data to deduce the number of different cell types in DN by using recently published single-cell transcriptome datasets, which showed a significant increase in monocytes/macrophage, fibroblasts, and myofibroblasts in the kidneys from patients with advanced DN. Finally, we validated the expression of RBP4 and GLP1R and the markers of immune cells in the kidney tissues of these patients by immunostaining.
Conclusion
Our study provides potential molecular mechanisms for DN progression as well as the associations of DEGs with the functional and structural changes observed in patients with both early and advanced DN.
Funding
- Government Support - Non-U.S.