Alterations in Protein Translation and Carboxylic Acid Catabolic Processes in Diabetic Kidney Disease

Tanshinone IIA is superior to paricalcitol in ameliorating tubulointerstitial fibrosis through regulation of VDR/Wnt/β-catenin pathway in rats with diabetic nephropathy

Glomerulosclerosis and tubulointerstitial fibrosis (TIF) are closely involved in the development of diabetic nephropathy (DN). Moreover, the development of TIF is closely related to epithelial-to-mesenchymal transition (EMT). Tanshinone IIA (Tan) has various pharmacological effects, especially the anti-fibrotic effect. And it is mainly used in the clinical treatment of cardiovascular diseases. Currently, the protective effect of Tan on DN and its possible mechanism have not been clearly elucidated. Our previous studies illustrated that Tan could improve the EMT of HK-2 cells induced by high glucose by regulating the vitamin D receptor (VDR)/Wnt/β-catenin pathway. Here, we collected demographic information and laboratory results from the National Health and Nutrition Examination Survey (NHANES) database in order to investigate the relationship between VD and DN. Then, we established a DN model and treated DN rats with Tan and paricalcitol (Par) for 6 weeks. We subsequently compared the changes in general condition, renal function, pathological changes, and TIF-related protein expression levels of control rats, DN rats induced by STZ, DN rats with Tan at 5.4 mg/kg, DN rats with Tan at 10.8 mg/kg, and DN rats with Par at 0.054 µg/kg, to explore the effect and mechanism of Tan and Par on DN rats. The results showed that VD had a protective effect against DN in diabetic patients. And we found that Tan had a protective effect on renal fibrosis in DN rats, which was superior to Par in improving the symptoms of "three more and one less," reducing fasting blood glucose level, improving renal index, BUN/SCr, and UACR, reducing histopathological damage of kidney, and improving the expression of fibrosis-related proteins in kidney tissue by regulating VDR/Wnt/β-catenin pathway. Tan was superior to Par in ameliorating tubulointerstitial fibrosis by regulating VDR/Wnt/β-catenin pathway in rats with diabetic nephropathy.

New insights into the role of immunity and inflammation in diabetic kidney disease in the omics era

Diabetic kidney disease (DKD) is becoming the leading cause of chronic kidney disease, especially in the industrialized world. Despite mounting evidence has demonstrated that immunity and inflammation are highly involved in the pathogenesis and progression of DKD, the underlying mechanisms remain incompletely understood. Substantial molecules, signaling pathways, and cell types participate in DKD inflammation, by integrating into a complex regulatory network. Most of the studies have focused on individual components, without presenting their importance in the global or system-based processes, which largely hinders clinical translation. Besides, conventional technologies failed to monitor the different behaviors of resident renal cells and immune cells, making it difficult to understand their contributions to inflammation in DKD. Recently, the advancement of omics technologies including genomics, epigenomics, transcriptomics, proteomics, and metabolomics has revolutionized biomedical research, which allows an unbiased global analysis of changes in DNA, RNA, proteins, and metabolites in disease settings, even at single-cell and spatial resolutions. They help us to identify critical regulators of inflammation processes and provide an overview of cell heterogeneity in DKD. This review aims to summarize the application of multiple omics in the field of DKD and emphasize the latest evidence on the interplay of inflammation and DKD revealed by these technologies, which will provide new insights into the role of inflammation in the pathogenesis of DKD and lead to the development of novel therapeutic approaches and diagnostic biomarkers.

Identification of AGXT2, SHMT1, and ACO2 as important biomarkers of acute kidney injury by WGCNA

Acute kidney injury (AKI) is a serious and frequently observed disease associated with high morbidity and mortality. Weighted gene co-expression network analysis (WGCNA) is a research method that converts the relationship between tens of thousands of genes and phenotypes into the association between several gene sets and phenotypes. We screened potential target genes related to AKI through WGCNA to provide a reference for the diagnosis and treatment of AKI. Key biomolecules of AKI were investigated based on transcriptome analysis. RNA sequencing data from 39 kidney biopsy specimens of AKI patients and 9 normal subjects were downloaded from the GEO database. By WGCNA, the top 20% of mRNAs with the largest variance in the data matrix were used to construct a gene co-expression network with a p-value < 0.01 as a screening condition, showing that the blue module was most closely associated with AKI. Thirty-two candidate biomarker genes were screened according to the threshold values of |MM|≥0.86 and |GS|≥0.4, and PPI and enrichment analyses were performed. The top three genes with the most connected nodes, alanine-glyoxylate aminotransferase 2(AGXT2), serine hydroxymethyltransferase 1(SHMT1) and aconitase 2(ACO2), were selected as the central genes based on the PPI network. A rat AKI model was constructed, and the mRNA and protein expression levels of the central genes in the model and control groups were verified by PCR and immunohistochemistry experiments. The results showed that the relative mRNA expression and protein levels of AGXT2, SHMT1 and ACO2 showed a decrease in the model group. In conclusion, we inferred that there is a close association between AGXT2, SHMT1 and ACO2 genes and the development of AKI, and the down-regulation of their expression levels may induce AKI.

Single-cell transcriptomics: A new tool for studying diabetic kidney disease

The kidney is a complex organ comprising various functional partitions and special cell types that play important roles in maintaining homeostasis in the body. Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease and is an independent risk factor for cardiovascular diseases. Owing to the complexity and heterogeneity of kidney structure and function, the mechanism of DKD development has not been fully elucidated. Single-cell sequencing, including transcriptomics, epigenetics, metabolomics, and proteomics etc., is a powerful technology that enables the analysis of specific cell types and states, specifically expressed genes or pathways, cell differentiation trajectories, intercellular communication, and regulation or co-expression of genes in various diseases. Compared with other omics, RNA sequencing is a more developed technique with higher utilization of tissues or samples. This article reviewed the application of single-cell transcriptomics in the field of DKD and highlighted the key signaling pathways in specific tissues or cell types involved in the occurrence and development of DKD. The comprehensive understanding of single-cell transcriptomics through single-cell RNA-seq and single-nucleus RNA-seq will provide us new insights into the pathogenesis and treatment strategy of various diseases including DKD.

Association of amino acids related to urea cycle with risk of diabetic nephropathy in two independent cross-sectional studies of Chinese adults

OBJECTIVE

To investigate the association between amino acids related to the urea cycle and diabetic nephropathy (DN) in two independent cross-sectional studies.

METHODS

We obtained the medical records of 145 individuals with DN and 596 individuals without DN who attended an annual health examination at Liaoning Medical University First Affiliated Hospital (LMUFAH), China, from May 2015 to August 2016. From April 2018 to April 2019, we collected medical records of another 741 individuals: 338 individuals with DN and 403 individuals without DN from the Second Affiliated Hospital of Dalian Medical University (DALIAN), China. Binary logistic regression was used to obtain the odds ratio (OR) and 95% confidence interval (CI).

RESULTS

In two independent cross-sectional studies, we observed that citrulline was consistently associated with DN risk [OR (95% CI) of per standard deviation (SD) increase for citrulline in the LMUFAH population: 1.200 (1.006, 1.432); OR (95% CI) of per SD increase for citrulline in the DALIAN population: 1.189 (1.012, 1.396); pooled effect size for citrulline: 1.194 (1.060, 1.345)]. However, ornithine, arginine, and the ratio of arginine to ornithine were consistently unrelated to DN risk, and the ratios of other amino acids in the urea cycle were inconsistently associated with DN risk.

CONCLUSIONS

Citrulline was consistently associated with DN risk in two independent cross-sectional studies in Chinese adults.