Angiopoietin-1: an early biomarker of diabetic nephropathy?

Notoginsenoside R1 can inhibit the interaction between FGF1 and VEGFA to retard podocyte apoptosis

BACKGROUND

Diabetic nephropathy (DN) is a chronic condition resulting from microangiopathy in a high-glucose environment. The evaluation of vascular injury in DN has primarily focused on active molecules of VEGF, namely VEGFA and VEGF2(F2R). Notoginsenoside R1 (NGR1), a traditional anti-inflammatory medication, exhibits vascular activity. Therefore, identifying classical drugs with vascular inflammatory protection for the treatment of DN is a valuable pursuit.

METHODS

The "Limma" method was employed to analyze the glomerular transcriptome data, while the Spearman algorithm for Swiss target prediction was utilized to analyze the drug targets of NGR1. The molecular docking technique was employed to investigate the relationship between vascular active drug targets, and the COIP experiment was conducted to verify the interaction between fibroblast growth factor 1 (FGF1) and VEGFA in relation to NGR1 and drug targets.

RESULTS

According to the Swiss target prediction, the LEU32(b) site of the Vascular Endothelial Growth Factor A (VEGFA) protein, as well as the Lys112(a), SER116(a), and HIS102(b) sites of the Fibroblast Growth Factor 1 (FGF1) protein, are potential binding sites for NGR1 through hydrogen bonding. Additionally, the Co-immunoprecipitation (COIP) results suggest that VEGFA and FGF1 proteins can interact with each other, and NGR1 can impede this interaction. Furthermore, NGR1 can suppress the expression of VEGFA and FGF1 in a high-glucose environment, thereby decelerating podocyte apoptosis.

CONCLUSION

The inhibition of the interaction between FGF1 and VEGFA by NGR1 has been observed to decelerate podocyte apoptosis.

APOC1 as a novel diagnostic biomarker for DN based on machine learning algorithms and experiment

INTRODUCTION

Diabetic nephropathy is the leading cause of end-stage renal disease, which imposes a huge economic burden on individuals and society, but effective and reliable diagnostic markers are still not available.

METHODS

Differentially expressed genes (DEGs) were characterized and functional enrichment analysis was performed in DN patients. Meanwhile, a weighted gene co-expression network (WGCNA) was also constructed. For further, algorithms Lasso and SVM-RFE were applied to screening the DN core secreted genes. Lastly, WB, IHC, IF, and Elias experiments were applied to demonstrate the hub gene expression in DN, and the research results were confirmed in mouse models and clinical specimens.

RESULTS

17 hub secretion genes were identified in this research by analyzing the DEGs, the important module genes in WGCNA, and the secretion genes. 6 hub secretory genes (APOC1, CCL21, INHBA, RNASE6, TGFBI, VEGFC) were obtained by Lasso and SVM-RFE algorithms. APOC1 was discovered to exhibit elevated expression in renal tissue of a DN mouse model, and APOC1 is probably a core secretory gene in DN. Clinical data demonstrate that APOC1 expression is associated significantly with proteinuria and GFR in DN patients. APOC1 expression in the serum of DN patients was 1.358±0.1292μg/ml, compared to 0.3683±0.08119μg/ml in the healthy population. APOC1 was significantly elevated in the sera of DN patients and the difference was statistical significant (P > 0.001). The ROC curve of APOC1 in DN gave an AUC = 92.5%, sensitivity = 95%, and specificity = 97% (P < 0.001).

CONCLUSIONS

Our research indicates that APOC1 might be a novel diagnostic biomarker for diabetic nephropathy for the first time and suggest that APOC1 may be available as a candidate intervention target for DN.

Bibliometric Study of Trends in the Diabetic Nephropathy Research Space from 2016 to 2020

Background

Diabetic nephropathy (DN) is one of the most common microvascular complications of diabetes mellitus (DM), but no bibliometric studies pertaining to DN have been published within the last 5 years.

Objectives

Most prior studies have focused on specific problems in the DN field. This study attempts to sort out and visualize the knowledge framework in this research space from a holistic and highly generalized perspective. Readers can quickly understand and master the knowledge regarding DN research conducted from 2016 to 2020, in addition to predicting future research hotspots and possible directions for development in this field in a comprehensive and scientifically valid manner.

Methods

Literature information, discourse matrices, and co-occurrence matrices were generated using BICOMB. gCLUTO was used for biclustering analyses and visualization. Strategic diagrams were generated using GraphPad Prism 5. The social network analysis (SNA) was analyzed and plotted using Ucinet 6.0 and Netdraw.

Results

In total, 55 high-frequency MeSH terms/MeSH subheadings were selected and grouped into 5 clusters in a biclustering analysis. These analyses revealed that extensive studies of the etiology, diagnosis, and treatment of DN have been conducted over the last 5 years, while further research regarding DN-related single nucleotide polymorphisms, miRNAs, and signal transduction are warranted as these research areas remain relatively immature.

Conclusion

Together, these results outline a robust knowledge structure pertaining to the field of DN-related research over the last 5 years, providing a valuable resource for readers by enabling the easy comprehension of relevant information. In addition, this analysis highlights predicted DN-related research directions and hotspots.

Novel biomarkers and therapeutic approaches for diabetic retinopathy and nephropathy: Recent progress and future perspectives

The global burden due to microvascular complications in patients with diabetes mellitus persists and even increases alarmingly, the intervention and management are now encountering many difficulties and challenges. This paper reviews the recent advancement and progress in novel biomarkers, artificial intelligence technology, therapeutic agents and approaches of diabetic retinopathy and nephropathy, providing more insights into the management of microvascular complications.