Contrast‐induced nephropathy (CIN) is a condition that causes kidney damage in patients receiving angiography with iodine‐based contrast agents. This study investigated the potential protective effects of berberine (BBR) against CIN and its underlying mechanisms. The researchers conducted both in vivo and in vitro experiments to explore BBR's renal protective effects. In the in vivo experiments, SD rats were used to create a CIN model, and different groups were established. The results showed that CIN model group exhibited impaired renal function, severe damage to renal tubular cells and increased apoptosis and ferroptosis. However, BBR treatment group demonstrated improved renal function, decreased apoptosis and ferroptosis. Similar results were observed in the in vitro experiments using HK‐2 cells. BBR reduced ioversol‐induced apoptosis and ferroptosis, and exerted its protective effects through Akt/Foxo3a/Nrf2 signalling pathway. BBR administration increased the expression of Foxo3a and Nrf2 while decreasing the levels of p‐Akt and p‐Foxo3a. In conclusion, this study revealed that BBR effectively inhibited ioversol‐induced apoptosis and ferroptosis in vivo and in vitro. The protective effects of BBR were mediated through the modulation of Akt/Foxo3a/Nrf2 signalling pathway, leading to the alleviation of CIN. These findings suggest that BBR may have therapeutic potential for protecting against CIN in patients undergoing angiography with iodine‐based contrast agents.

Background: Tubulointerstitial injury (TIL) is common in chronic kidney disease (CKD), which in turn, leads to loss of renal function. The aims of present study were to screen critical genes with tubulointerstitial lesion in CKD by weighted gene correlation network analysis (WGCNA). Methods: GSE104954 gene expression data downloaded from GEO database were used for analysis for differential expression genes(DEGs); Meanwhile, 90 expression data of tubulointerstitial samples in GSE47185 combined with clinic information were applied to WGCNA. According to the enrichment analysis and relationship with estimated glomerular filtration rate (eGFR), the eGFR-associated modules were defined, and the hub gene is selected according to the average intramodular connectivity (Kwithin); Clinical data from Nephroseq were obtained to further validate the relationship between CKD and hub genes. Results: Totally 294 DEGs were screened. Using the WGCNA, we identified 15 co-expressed modules, the blue, brown and yellow modules exhibited strongly association with eGFR, and were significantly enriched in several signaling pathways that have been reported involved in pathogenesis of CKD. Furthermore, it was found that the 4 genes (PLG, ITGB2, CTSS and CCL5) was one of the DEGs which also be identified as hub genes according to Kwithin. Finally, the Nephroseq online tool showed that the tubulointerstitial expression levels of PLG significantly positively correlated with the eGFR, while ITGB2, CTSS and CCL5 connected negatively to the eGFR. Conclusion: WGCNA is an efficient approach to system biology. By this procedure, the present study improved the understanding of the transcriptome status of renal tubulointerstitial injury in CKD.

Background: Tubulointerstitial injury (TIL) is common in chronic kidney disease (CKD), which in turn, leads to loss of renal function. The aims of present study were to screen critical genes with tubulointerstitial lesion in CKD by weighted gene correlation network analysis (WGCNA). Methods: GSE104954 gene expression data downloaded from GEO database were used for analysis for differential expression genes(DEGs); Meanwhile, 90 expression data of tubulointerstitial samples in GSE47185 combined with clinic information were applied to WGCNA. According to the enrichment analysis and relationship with estimated glomerular filtration rate (eGFR), the eGFR-associated modules were defined, and the hub gene is selected according to the average intramodular connectivity (Kwithin); Clinical data from Nephroseq were obtained to further validate the relationship between CKD and hub genes. Results: Totally 294 DEGs were screened. Using the WGCNA, we identified 15 co-expressed modules, the blue, brown and yellow modules exhibited strongly association with eGFR, and were significantly enriched in several signaling pathways that have been reported involved in pathogenesis of CKD. Furthermore, it was found that the 4 genes (PLG, ITGB2, CTSS and CCL5) was one of the DEGs which also be identified as hub genes according to Kwithin. Finally, the Nephroseq online tool showed that the tubulointerstitial expression levels of PLG significantly positively correlated with the eGFR, while ITGB2, CTSS and CCL5 connected negatively to the eGFR. Conclusion: WGCNA is an efficient approach to system biology. By this procedure, the present study improved the understanding of the transcriptome status of renal tubulointerstitial injury in CKD.