Elevated senescence in the bone marrow mesenchymal stem cells of acquired aplastic anemia patients: A possible implication of DNA damage responses and telomere attrition.

BACKGROUND: Bone marrow mesenchymal stem cells (BM-MSC) are an integral part of the BM niche that is essential to maintain hematopoietic homeostasis. In aplastic anemia (AA), a few studies have reported phenotypic defects in the BM-MSC, such as reduced proliferation, imbalanced differentiation, and apoptosis; however, the alterations at the molecular level need to be better characterized. Therefore, the current study aims to identify the causative factors underlying the compromised functions of AA BM-MSC that might eventually be contributing to the AA pathobiology. METHODS: We performed RNA sequencing (RNA-Seq) using the Illumina platform to comprehend the distinction between the transcriptional landscape of AA and control BM-MSC. Further, we validated the alterations observed in senescence by Senescence- associated beta-galactosidase (SA -ß-gal) assay, DNA damage by γH2AX staining, and telomere attrition by relative telomere length assessment and telomerase activity assay. We used qRT-PCR to analyze changes in some of the genes associated with these molecular mechanisms. RESULTS: The transcriptome profiling revealed enrichment of senescence-associated genes and pathways in AA BM-MSC. The senescent phenotype of AA BM-MSC was accompanied by enhanced SA -ß-gal activity and elevated expression of senescence associated genes TP53, PARP1, and CDKN1A. Further, we observed increased γH2AX foci indicating DNA damage, reduced telomere length, and diminished telomerase activity in the AA BM-MSC. CONCLUSION: Our results highlight that AA BM-MSC have a senescent phenotype accompanied by other cellular defects like DNA damage and telomere attrition, which are most likely driving the senescent phenotype of AA BM-MSC thus hampering their hematopoiesis supporting properties as observed in AA.

TRAIL and EGFR Pathways Targeting microRNAs are Predominantly Regulated in Human Diabetic Nephropathy.

BACKGROUND: Unbiased microRNA profiling of renal tissue and urinary extracellular vesicles (uEVs) from diabetic nephropathy (DN) subjects may unravel novel targets with diagnostic and therapeutic potential. Here we used the miRNA profile of uEVs and renal biopsies from DN subjects available on the GEO database. METHODS: The miR expression profiles of kidney tissue (GSE51674) and urinary exosomes (GSE48318) from DN and control subjects were obtained by GEO2R tools from Gene Expression Omnibus (GEO) databases. Differentially expressed miRNAs in DN samples, relative to controls, were identified using a bioinformatic pipeline. Targets of miRs commonly regulated in both sample types were predicted by miRWalk, followed by functional gene enrichment analysis. Gene targets were identified by MiRTarBase, TargetScan and MiRDB. RESULTS: Eight miRs, including let-7c, miR-10a, miR-10b and miR-181c, were significantly regulated in kidney tissue and uEVs in DN subjects versus controls. The top 10 significant pathways targeted by these miRs included TRAIL, EGFR, Proteoglycan syndecan, VEGF and Integrin Pathway. Gene target analysis by miRwalk upon validation using ShinyGO 70 targets with significant miRNA-mRNA interaction. CONCLUSION: In silico analysis showed that miRs targeting TRAIL and EGFR signaling are predominately regulated in uEVs and renal tissue of DN subjects. After wet-lab validation, the identified miRstarget pairs may be explored for their diagnostic and/or therapeutic potential in diabetic nephropathy.

The Functional Role of microRNAs and mRNAs in Diabetic Kidney Disease: A Review.

Diabetes is a group of diseases marked by poor control of blood glucose levels. Diabetes mellitus (DM) occurs when pancreatic cells fail to make insulin, which is required to keep blood glucose levels stable, disorders, and so on. High glucose levels in the blood induce diabetic effects, which can cause catastrophic damage to bodily organs such as the eyes and lower extremities. Diabetes is classified into many forms, one of which is controlled by hyperglycemia or Diabetic Kidney Disease (DKD), and another that is not controlled by hyperglycemia (nondiabetic kidney disease or NDKD) and is caused by other factors such as hypertension, hereditary. DKD is associated with diabetic nephropathy (DN), a leading cause of chronic kidney disease (CKD) and end-stage renal failure. The disease is characterized by glomerular basement membrane thickening, glomerular sclerosis, and mesangial expansion, resulting in a progressive decrease in glomerular filtration rate, glomerular hypertension, and renal failure or nephrotic syndrome. It is also represented by some microvascular complications such as nerve ischemia produced by intracellular metabolic changes, microvascular illness, and the direct impact of excessive blood glucose on neuronal activity. Therefore, DKD-induced nephrotic failure is worse than NDKD. MicroRNAs (miRNAs) are important in the development and progression of several diseases, including diabetic kidney disease (DKD). These dysregulated miRNAs can impact various cellular processes, including inflammation, fibrosis, oxidative stress, and apoptosis, all of which are implicated during DKD. MiRNAs can alter the course of DKD by targeting several essential mechanisms. Understanding the miRNAs implicated in DKD and their involvement in disease development might lead to identifying possible therapeutic targets for DKD prevention and therapy. Therefore, this review focuses specifically on DKD-associated DN, as well as how in-silico approaches may aid in improving the management of the disease.

An In-Silico Approach to Identify Therapeutic Target and Markers Associated with Diabetic Nephropathy.

BACKGROUND: Renal disease in T2DM could arise independent of hyperglycemia, aka non diabetic kidney disease. Their prevalence ranges from 33%to72.5% among T2DM patients. Specific molecular signatures that distinguish Diabetic Nephropathy from NDKD (FSGS) in T2DM might provide new targets for CKD management. METHODS: Five original GEO microarray DN and FSGS datasets were evaluated (GSE111154, GSE96804, GSE125779, GSE129973 and GSE121233). Each of the three groups (DN, FSGS, and Controls) had equal renal transcriptome data (n=32) included in the analysis to eliminate bias. The DEGs were identified using TAC4.0. Pathway analysis was performed on the discovered genes that aligned to official gene symbols using Reactome, followed by functional gene enrichment analysis using Funrich,Enrichr. STRING and Network analyst investigated PPI, followed by Webgestalt's pathway enrichment. Finally, using the Targetscan7.0 and DIANA tools, filtered differential microRNAs downregulated in DN were evaluated for target identification. RESULT: Between the three groups, DN, FSGS, and Control, a total of 194 DEGs. with foldchange >2&<-2 and P-value0.01 were found in the renal transcriptome. In comparison to control, 45 genes were elevated particularly in DN, whereas 43 were upregulated specifically in FSGS. DN datasets were compared to FSGS in a separate analysis. FABP4, EBF1, ADIRF, and ART4 were shown to be among the substantially up-regulated genes unique to DN in both analyses. The transcriptional regulation of white adipocytes was discovered by a pathway analysis. CONCLUSION: The molecular markers revealed might be employed as specific targets in the aetiology of DN, as well as in T2DM patients' therapeutic care.