Endocrine, Metabolic & Immune Disorders-Drug Targets (Formerly Current Drug Targets - Immune, Endocrine & Metabolic Disorders) - Volume 25, Issue 9, 2025

Toll-like Receptor 4 (TLR4) plays critical roles in innate immunity and several other pathological responses, including a possible role in the susceptibility to Type 2 Diabetes Mellitus (T2DM). Understanding the relationship between TLR4 polymorphism and T2DM is necessary to evaluate the role of innate immunity in diabetes.

This study was conducted to evaluate the potential association between three TLR4 SNPs (SNP ID rs11536858, rs4986790, and rs1927914) and risk susceptibility to T2DM in a cross-section of the Palestinian population.

A total of 96 individuals including 50 T2DM patients participated in this study. The data were analyzed according to the TLR4 allelic variation results. DNAs were extracted from blood samples collected from the T2DM patients and their matched healthy controls and used to evaluate possible associations between the TLR4 SNP variations and T2DM. The genotypes of TLR4 polymorphisms were analyzed by the Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP).

Three allelic variations were detected in the participating individuals. The distribution of alleles between T2DM and healthy controls in the three SNPs did not show significant differences, even though some variations tended to favor certain alleles. To look at potential associations of TLR4 gene polymorphisms with the risk of T2DM development, we analyzed the allelic variation in both T2DM patients and health controls. The rs4986790 TLR4 SNPs showed a significant association with T2DM. There were 20% heterozygous alleles in T2DM patients compared to 4.35% in healthy controls with Odds Ratio (OR) = 5.26 and 95% CI = 1.08, 25.6 (P = 0.0252), indicating the AG allele to be a risk factor. Both rs11536858 and rs1927914 alleles demonstrated a potential association of their allelic variations as either a protective or a high-risk factor.

Our data have indicated that TLR4 rs4986790, rs1927914, and rs11536858 may play a potential role in innate immunity and susceptibility risk to diabetes and can be potential targets for therapeutic drugs.

The significance of circular RNAs (circRNAs) in diabetic complications has been established. However, their role in basal and diabetic states, as well as cognitive dysfunction, requires further investigation.

BV-2 microglial cells were exposed to high glucose (50 mM) and insulin (2 μM) for 48 hours. The levels of interleukin-1beta (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) were assessed through quantitative polymerase chain reaction (qPCR), western blot, and ELISA. CircRNA and messenger RNA (mRNA) sequencing were performed, and the data were analyzed. Differentially expressed circRNAs and mRNAs were identified using qPCR. The circRNA-miRNA interaction was predicted using Miranda and TargetScan software, and their levels were quantified by qPCR.

The results demonstrated a significant increase in mRNA and protein levels of IL-1β, IL-6, and TNF-α in BV2 cells treated with glucose and insulin. Five circRNAs (four upregulated and one downregulated) were identified in both glucose and insulin groups compared to the control. Further qPCR analysis revealed marked increases in the levels of chr17:40159331-40159711+ and chr2:72800499-72801858- (mmu_circ_0010164) in both treatment groups. Competitive endogenous RNA networks showed significant upregulation of mRNA levels of mitochondrial transcription termination factor 1b (Mterf1b) and G protein subunit gamma 4 (Gng4), accompanied by a decrease in mmu-miR-6918-3p and mmu-miR-7043-3p levels in the glucose and insulin groups compared to the control. Knockdown of mmu_circ_0010164 significantly inhibited the inflammatory response induced by glucose and insulin in BV-2 microglial cells.

These findings indicate that both glucose and insulin can elicit inflammatory responses in BV2 cells through the modulation of mmu_circ_0010164 levels. The underlying mechanism may involve potential downstream targets of mmu_circ_0010164, specifically mmu-miR-7043-3p/Gng4 and mmu-miR-6918-3p/Mterf1b. This provides novel insights into the treatment of glucose-induced neuroinflammation.

Senna leaf is a commonly used medication for treating constipation, and long-term use can cause damage to the intestinal mucosa and lead to drug dependence. But the exact mechanism remains unclear.

Using non-targeted metabolomics technology to study the mechanism of senna leaf ethanol extract (EESL) inducing inflammation and oxidative stress in mice and causing side effects.

EESL was administered to mice by gavage to detect inflammation and oxidative stress-related factors in mice, and the EESL components and differential metabolites in mouse plasma were analyzed using non-targeted metabolome techniques.

23 anthraquinone compounds were identified in the EESL, including sennoside and their derivatives. Administration of EESL to mice resulted in a significant increase in pro-inflammatory factors, IL-1β, and IL-6 in the plasma, while the levels of IgA significantly decreased. The levels of oxidative stress significantly increased, and the intestinal mucosal integrity was impaired. 21 endogenous in plasma metabolites were identified as differential metabolites related with taurine and taurine metabolism, glycerophospholipid metabolism, arachidonic acid metabolism, tryptophan metabolism, and sphingolipid metabolism. These metabolic pathways are related to oxidative stress and inflammation.

Senna leaf can inhibit the expression of tight junction proteins in the intestinal mucosa and disrupt intestinal mucosal barrier integrity, exacerbating oxidative stress and inflammation induced by bacterial LPS entering the bloodstream. In addition, the impact of Senna leaf on tryptophan metabolism may be linked to the occurrence of drug dependence.

This study aimed to uncover biomarkers associated with fibroblasts to diagnose ulcerative colitis (UC) and predict sensitivity to TNFα inhibitors.

We identified fibrosis-related genes by analyzing eight bulk RNA and one single-cell RNA sequencing dataset from UC patients. Three machine learning algorithms were employed to identify common significant genes. We utilized five machine learning models, namely Random Forest (RF), Support Vector Machine (SVM), Xgboost, Multilayer Perceptron (MLP), and Logistic Regression, to develop diagnostic models for UC. Following hyperparameter tweaking using grid search, we evaluated Matthew’s Correlation Coefficient (MCC) of each model on the validation set. Finally, we identified five hub genes in UC patients and evaluated their response to infliximab or golimumab.

We identified 23 genes associated with fibroblasts. Further analysis using three ML models revealed BIRC3, IFITM2, ANXA1, ISG20, and MSN as critical fibroblast genes. Following hyperparameter adjustment, the SVM model exhibited the most favorable characteristics in the validation set, achieving an MCC of 0.7. ANXA1 contributed the most to the model that predicts UC. The optimal model was implemented on the website. Among UC patients receiving TNFα inhibitor treatment, the ineffective group showed considerably increased expression of the five critical genes than the responsive group.

BIRC3, IFITM2, ANXA1, ISG20, and MSN may serve as potential diagnostic biomarkers in UC. Through the interaction between characteristic biomarkers and immune infiltrating cells, the immune response mediated by these characteristic biomarkers plays a crucial role in the occurrence and development of UC.

This study aims to investigate the function and potential mechanism of Tanshinone IIA in uric acid-induced HK-2 fibrosis models.

An in vitro model of fibrosis was constructed using uric acid stimulation. RT-qPCR and Western blot were used to evaluate the levels of inflammatory cytokines. The detection of ROS and ELISA assay were used to analyze the changes in oxidative stress.

Tanshinone IIA inhibited the increase in inflammatory cytokines TNF-α, IL-1β, IL-6, and IL-18 and the formation of NLRP3 inflammasome induced by uric acid stimulation. In addition, Tanshinone IIA treatment reduced the production of ROS and MDA, promoting the expression of SOD and CAT, thereby protecting HK-2 cells from oxidative stress damage. Besides, the expression of TGF-β, FN, and Collagen I was significantly reduced by the treatment of Tanshinone IIA. Mechanistically, Tanshinone IIA inhibited the expression of inflammatory cytokines and the formation of the NLRP3 inflammasome by targeting NRF2.

Tanshinone IIA exerts a protective role in uric acid-induced HK-2 fibrosis models by targeting the NRF2-NLRP3 signaling pathway to reduce the occurrence of inflammation and oxidative stress.

To discover new therapeutic targets for Type 2 diabetes (T2D) and develop a new diagnostic model.

T2D is a chronic disease that can be controlled by oral hypoglycemic drugs, however, it cannot be fully cured. The continued increase in the prevalence of T2D and the limitations of existing treatments urgently call for the development of new drugs to be able to effectively control the progression of the disease.

We aimed to discover new therapeutic targets for T2D and to develop a new diagnostic model.

Single-cell transcriptome, web-based systematic pharmacology, and transcriptology were applied to identify T2D diagnostic targets and drug candidates and to analyze the underlying molecular mechanisms.

By single-cell clustering analysis, we identified seven subsets between the normal islet β-cell samples and T2D islet β-cell samples. A total of 27 key genes in the intersection of insulin-related genes and diabetes-related genes were selected by protein-protein interaction (PPI) analysis and MolecularComplexDetection (MCODE) analysis. Notably, ESR1, MME, and CCR5 had the area under curves (AUC) values as high as 67.95%, 66.67%, and 66.03% for the diagnosis of T2D, respectively. Since the expression of MME in T2D samples was significantly higher than in normal samples, we screened 155 drug candidates against MME in T2D. Finally, the molecular docking revealed a strong binding strength between MME and DB05490, which was one of the most effective candidate drugs for treating T2D.

Our study screens for diagnostic signatures and potential therapeutic agents for T2D, which provides valuable insights into the development of T2D biomarkers and their drug discovery.

The purpose of this study was to comprehensively evaluate the association of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins) with neurological adverse events using the US Food and Drug Administration Adverse Event Reporting System (FAERS) database, with the aim of guiding the rational use of statins.

The number and clinical characteristics of adverse events (AEs) to statins in the FAERS database between 2012 and March, 2023, were extracted. Neurological AEs were defined by the system organ classes (SOCs) of “Nervous System Disorders (10029205)” and the corresponding PT. Disproportionality was calculated using the reporting dominance ratio (ROR), proportional reporting ratio (PRR), and information component (IC025).

Between January, 2012 and March, 2023, a total of 90,357 AEs were reported for the three statins (atorvastatin, resuvastatin, and simvastatin). The majority of reports on AEs came from the United States (n = 7284). A total of 8409 reports described neurological AEs following the use of the three statins, with atorvastatin accounting for more than half of the reports (n = 4430). The mean age of patients who developed neurological AEs was 55 years and older. The prevalence was similar in female patients (2230/4480) and male patients (1999/4480). Disproportionate analyses showed that at the SOC level, only the correlation between atorvastatin and neurological AEs suggested a positive signal (ROR: 9.77 (9.56-9.99); IC025: 3.28; PRR (χ²): 9.76 (16.07)) and in total, there were 32 PTs with a positive signal. The median time for neurological AEs was 71 days (IQR: 14-559 days), and the most common AEs were other serious effects (important medical event) (OT) (n = 2283) and hospitalization (HO) (n = 715).

This study suggests that atorvastatin may be associated with an increased risk of neurological AEs. This study provides realistic evidence of the potential risk of statin-related adverse events.