Cargando…
Integration of transcriptomics and metabolomics reveals the molecular mechanisms underlying the effect of nafamostat mesylate on rhabdomyolysis-induced acute kidney injury
Objective: To investigate the role and mechanisms of action of nafamostat mesylate (NM) in rhabdomyolysis-induced acute kidney injury (RIAKI). Methods: RIAKI rats were assigned into control group (CN), RIAKI group (RM), and NM intervention group (NM). Inflammatory cytokines and proenkephalin a 119–1...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748812/ https://www.ncbi.nlm.nih.gov/pubmed/36532745 http://dx.doi.org/10.3389/fphar.2022.931670 |
Sumario: | Objective: To investigate the role and mechanisms of action of nafamostat mesylate (NM) in rhabdomyolysis-induced acute kidney injury (RIAKI). Methods: RIAKI rats were assigned into control group (CN), RIAKI group (RM), and NM intervention group (NM). Inflammatory cytokines and proenkephalin a 119–159 (PENKID) were assessed. Cell apoptosis and glutathione peroxidase-4 (GPX4) were detected using TUNEL assay and immunohistochemical staining. Mitochondrial membrane potential (MMP) was detected by JC-1 dye. The expression of genes and metabolites after NM intervention was profiled using transcriptomic and metabolomic analysis. The differentially expressed genes (DEGs) were validated using qPCR. The KEGG and conjoint analysis of transcriptome and metabolome were used to analyze the enriched pathways and differential metabolites. The transcription factors were identified based on the animal TFDB 3.0 database. Results: Serum creatinine, blood urea nitrogen, and PENKID were remarkably higher in the RM group and lower in the NM group compared to the CN group. Pro-inflammatory cytokines increased in the RM group and notably decreased following NM treatment compared to the CN group. Tubular pathological damages were markedly attenuated and renal cell apoptosis was reduced significantly in the NM group compared to the RM group. The expression of GPX4 was lower in the RM group compared to the CN group, and it increased significantly after NM treatment. A total of 294 DEGs were identified in the RM group compared with the NM group, of which 192 signaling pathways were enriched, and glutathione metabolism, IL-17 signaling, and ferroptosis-related pathways were the top-ranking pathways. The transcriptional levels of Anpep, Gclc, Ggt1, Mgst2, Cxcl13, Rgn, and Akr1c1 were significantly different between the NM and RM group. Gclc was the key gene contributing to NM-mediated renal protection in RIAKI. Five hundred and five DEGs were annotated. Compared with the RM group, most of the upregulated DEGs in the NM group belonged to Glutathione metabolism, whereas most of the downregulated DEGs were related to the transcription factor Cytokine-cytokine receptor interaction. Conclusion: NM protects the kidneys against RIAKI, which is mainly associated with NM mediated regulation of glutathione metabolism, inflammatory response, ferroptosis-related pathways, and the related key DEGs. Targeting these DEGs might emerge as a potential molecular therapy for RIAKI. |
---|