# Gene Expression as a Guide for the Development of Novel Therapies in Hypertensive and Diabetic Kidney Disease

## TL;DR

This paper explores gene expression patterns in diabetic and hypertensive kidney disease to identify new therapies based on molecular mechanisms.

## Contribution

The study identifies disease-specific gene signatures and potential therapeutic compounds for diabetic and hypertensive kidney disease.

## Key findings

- Disease-specific gene signatures were identified in human glomeruli from diabetic and hypertensive kidney disease patients.
- Computational analysis revealed biological pathways and potential drugs to reverse kidney disease phenotypes.
- The findings suggest new therapeutic targets for personalized treatment of kidney diseases.

## Abstract

Background/Objectives: Diabetes mellitus and hypertension are the first and second most common causes of chronic kidney disease, respectively. Despite improvements in elucidating the pathophysiology behind these diseases and the expansion of the therapeutic armamentarium, the knowledge about the implicated genes, epigenetics, and biological pathways is limited. Methods: We sought to define diabetic nephropathy-specific and hypertensive nephropathy-specific gene signatures in human glomeruli through computational systems biology approaches. Results: Gene expression data of human glomeruli from patients with diabetic kidney disease (DKD) and hypertensive nephropathy (HTN) were collected and compared to gene expression patterns from healthy kidneys. Pathways were identified with functional enrichment analysis of DEGs. Transcription factor enrichment analysis, protein–protein interaction network expansion, and kinase enrichment analysis were also performed. Finally, novel drugs and small-molecule compounds that may reverse the kidney-specific phenotype of these disorders have been identified. Conclusions: These data suggest putative expansion of the therapeutic armamentarium in DKD and HTN, underscoring that understanding the molecular mechanisms occurring within tissue in kidney diseases may guide personalized therapy.