TNFSF14-Derived Molecules as a Novel Treatment for Obesity and Type 2 Diabetes

IL-20RA is Associated with the Risk of Diabetic Microangiopathy: A Bidirectional Mendelian Randomization Analysis and Clinical Validation

Objective

Studies have demonstrated a link between chronic inflammatory responses and diabetic microangiopathy, which include diabetic nephropathy, diabetic retinopathy, and diabetic neuropathy. However, it remains unclear whether there is a causal association between circulating inflammatory cytokines and the development of diabetic microvascular complications. This study aimed to investigate whether altered genetically predicted concentrations of circulating inflammatory cytokines were associated with the development of diabetic microvascular complications using two-sample Mendelian randomization (MR) analysis and clinical validation.

Methods

Pooled data on diabetic nephropathy, diabetic retinopathy, diabetic neuropathy, and 91 circulating inflammatory cytokines were obtained from publicly available databases. The analysis was conducted mainly using the inverse variance weighting (IVW) method and the results were assessed based on the odds ratio (OR) and 95% confidence interval (CI). In addition, the stability and reliability of the results were verified using the leave-one-out method, heterogeneity tests, and horizontal pleiotropy. Finally, ELISA and RT-qPCR were utilized to assess the expression of relevant inflammatory cytokines associated with diabetic microvascular complications.

Results

Mendelian randomization analysis identified a total of 9 circulating inflammatory cytokines that exhibit causal associations with the diabetic microangiopathy, with IL-20RA being a common risk factor for all three conditions. Clinical studies have found elevated plasma IL-20RA concentrations in patients with diabetic peripheral neuropathy, and RT-qPCR testing of peripheral blood mononuclear cells revealed significantly higher IL-20RA mRNA expression in patients with diabetic peripheral neuropathy as compared to normal individuals.

Conclusion

This study highlights the potential role of specific inflammatory cytokines in the development of diabetic microangiopathy (diabetic nephropathy, diabetic retinopathy and diabetic neuropathy). Additionally, IL-20RA emerges as a potential common risk factor for three diabetic microvascular complications. These findings may provide novel insights into early prevention and new therapeutic strategies for diabetic microvascular complications.

Multi-Omics Analysis Revealed the rSNPs Potentially Involved in T2DM Pathogenic Mechanism and Metformin Response

The goal of our study was to identify and assess the functionally significant SNPs with potentially important roles in the development of type 2 diabetes mellitus (T2DM) and/or their effect on individual response to antihyperglycemic medication with metformin. We applied a bioinformatics approach to identify the regulatory SNPs (rSNPs) associated with allele-asymmetric binding and expression events in our paired ChIP-seq and RNA-seq data for peripheral blood mononuclear cells (PBMCs) of nine healthy individuals. The rSNP outcomes were analyzed using public data from the GWAS (Genome-Wide Association Studies) and Genotype-Tissue Expression (GTEx). The differentially expressed genes (DEGs) between healthy and T2DM individuals (GSE221521), including metformin responders and non-responders (GSE153315), were searched for in GEO RNA-seq data. The DEGs harboring rSNPs were analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We identified 14,796 rSNPs in the promoters of 5132 genes of human PBMCs. We found 4280 rSNPs to associate with both phenotypic traits (GWAS) and expression quantitative trait loci (eQTLs) from GTEx. Between T2DM patients and controls, 3810 rSNPs were detected in the promoters of 1284 DEGs. Based on the protein-protein interaction (PPI) network, we identified 31 upregulated hub genes, including the genes involved in inflammation, obesity, and insulin resistance. The top-ranked 10 enriched KEGG pathways for these hubs included insulin, AMPK, and FoxO signaling pathways. Between metformin responders and non-responders, 367 rSNPs were found in the promoters of 131 DEGs. Genes encoding transcription factors and transcription regulators were the most widely represented group and many were shown to be involved in the T2DM pathogenesis. We have formed a list of human rSNPs that add functional interpretation to the T2DM-association signals identified in GWAS. The results suggest candidate causal regulatory variants for T2DM, with strong enrichment in the pathways related to glucose metabolism, inflammation, and the effects of metformin.

Impact of Lipids on Insulin Resistance: Insights from Human and Animal Studies

Insulin resistance (IR) is a complex pathological condition central to metabolic diseases such as type 2 diabetes mellitus (T2DM), cardiovascular disease, non-alcoholic fatty liver disease, and polycystic ovary syndrome (PCOS). This review evaluates the impact of lipids on insulin resistance (IR) by analyzing findings from human and animal studies. The articles were searched on the PubMed database using two keywords: (1) "Role of Lipids AND Insulin Resistance AND Humans" and (2) "Role of Lipids AND Insulin Resistance AND Animal Models". Studies in humans revealed that elevated levels of free fatty acids (FFAs) and triglycerides (TGs) are closely associated with reduced insulin sensitivity, and interventions like metformin and omega-3 fatty acids show potential benefits. In animal models, high-fat diets disrupt insulin signaling and increase inflammation, with lipid mediators such as diacylglycerol (DAG) and ceramides playing significant roles. DAG activates protein kinase C, which eventually impairs insulin signaling, while ceramides inhibit Akt/PKB, further contributing to IR. Understanding these mechanisms is crucial for developing effective prevention and treatment strategies for IR-related diseases.

Construction of an immune-related prognostic model by exploring the tumor microenvironment of clear cell renal cell carcinoma

OBJECTIVE

In this study, bioinformatics methods were performed to screen the candidate prognosis-related genes of clear cell renal cell carcinoma (ccRCC) by analyzing the tumor microenvironment (TME).

METHODS

Gene expression and clinical data of ccRCC patients were accessed from TCGA, and R package ESTIMATE was applied to calculate immune, stromal, and ESTIMATE scores of the patients. Survival analysis was conducted per median of these three scores. Based on the scoring results, differentially expressed genes (DEGs) were screened. Regression algorithms were utilized to screen prognostic genes and establish a risk model. Finally, pathway activity differences were analyzed through GSEA.

RESULTS

Patients with the unfavorable prognosis had high immune scores. 619 DEGs (499 up-regulated and 120 down-regulated) were screened based on the differences in gene expression of the patients with high and low immune scores. These genes mainly participated in immune-related signaling pathways. A prognostic risk model for ccRCC patients was constructed and 7 immune-related signature genes (RORB, TNFSF14, UCN2, USP2, TOX3, KLRC2, SLAMF9) were obtained through regression analysis. The constructed prognostic risk model could be used for determining prognoses of patients with ccRCC.

CONCLUSION

We unraveled the association between TME and prognosis of ccRCC patients and established a prognostic risk model based on the differentially expressed genes. These results contributed to understanding of TME that affected patients' prognosis and progression of ccRCC and conduced to finding potential biomarkers of ccRCC.