Cross Talk between Inflammation and Metabolic Disorders

Temporal relationship between inflammation and metabolic disorders and their impact on cancer risk

Background

Inflammation and metabolic disorders are closely associated with cancer. Whether inflammation leads to metabolic disorders or vice versa during cancer initiation remains unclear. In this study, we explored this temporal relationship and the co-exposure effect on cancer risk.

Methods

This prospective study had two phases. Initially, we examined the temporal relationship between inflammation (high-sensitivity C-reactive protein (CRP)) and metabolic disorders (metabolic syndrome severity Z-score (MetS-Z)) using a 3.98-year survey and cross-lagged analysis. Subsequently, we assessed the connection of co-exposure to inflammation and metabolic disorders, and the risks of overall cancer, as well as specific obesity-related, non-obesity-related, digestive system, lung, and other cancers using an 11.04-year survey and Cox proportional hazard models.

Results

The cross-lagged analysis revealed that the path coefficient from baseline CRP to follow-up MetS-Z (β2 = 0.032; 95% confidence interval (CI) = 0.026, 0.046) was more significant than the path coefficient from baseline MetS-Z to follow-up CRP (β1 = 0.009; 95% CI = -0.001, 0.019). During the follow-up, 2304 cases of cancer occurred. Compared with the risk of cancer of patients with low average cumulative CRP and MetS-Z, patients with high value had a significantly increased risk (hazard ratio = 1.54, 95% CI = 1.30, 1.83). The mediation analysis showed that MetS-Z mediated the association between CRP levels and overall cancer (12.67%), digestive system cancer (10.16%), and obesity-related cancer risk (13.87%).

Conclusions

Inflammation had a greater impact on metabolic disorders than vice versa. Co-exposure to inflammation and metabolic disorders significantly increased the risk of cancer, particularly digestive system and obesity-related cancers.

Registration

Chinese Clinical Trial Registry: ChiCTR-TNRC-11001489.

New insights into the role of mitochondrial metabolic dysregulation and immune infiltration in septic cardiomyopathy by integrated bioinformatics analysis and experimental validation

BACKGROUND

Septic cardiomyopathy (SCM), a common cardiovascular comorbidity of sepsis, has emerged among the leading causes of death in patients with sepsis. SCM's pathogenesis is strongly affected by mitochondrial metabolic dysregulation and immune infiltration disorder. However, the specific mechanisms and their intricate interactions in SCM remain unclear. This study employed bioinformatics analysis and drug discovery approaches to identify the regulatory molecules, distinct functions, and underlying interactions of mitochondrial metabolism and immune microenvironment, along with potential interventional strategies in SCM.

METHODS

GSE79962, GSE171546, and GSE167363 datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and module genes were identified using Limma and Weighted Correlation Network Analysis (WGCNA), followed by functional enrichment analysis. Machine learning algorithms, including support vector machine-recursive feature elimination (SVM-RFE), least absolute shrinkage and selection operator (LASSO) regression, and random forest, were used to screen mitochondria-related hub genes for early diagnosis of SCM. Subsequently, a nomogram was developed based on six hub genes. The immunological landscape was evaluated by single-sample gene set enrichment analysis (ssGSEA). We also explored the expression pattern of hub genes and distribution of mitochondria/inflammation-related pathways in UMAP plots of single-cell dataset. Potential drugs were explored using the Drug Signatures Database (DSigDB). In vivo and in vitro experiments were performed to validate the pathogenetic mechanism of SCM and the therapeutic efficacy of candidate drugs.

RESULTS

Six hub mitochondria-related DEGs [MitoDEGs; translocase of inner mitochondrial membrane domain-containing 1 (TIMMDC1), mitochondrial ribosomal protein S31 (MRPS31), F-box only protein 7 (FBXO7), phosphatidylglycerophosphate synthase 1 (PGS1), LYR motif containing 7 (LYRM7), and mitochondrial chaperone BCS1 (BCS1L)] were identified. The diagnostic nomogram model based on the six hub genes demonstrated high reliability and validity in both the training and validation sets. The immunological microenvironment differed between SCM and control groups. The Spearman correlation analysis revealed that hub MitoDEGs were significantly associated with the infiltration of immune cells. Upregulated hub genes showed remarkably high expression in the naive/memory B cell, CD14+ monocyte, and plasma cell subgroup, evidenced by the feature plot. The distribution of mitochondria/inflammation-related pathways varied across subgroups among control and SCM individuals. Metformin was predicted to be the most promising drug with the highest combined score. Its efficacy in restoring mitochondrial function and suppressing inflammatory responses has also been validated.

CONCLUSIONS

This study presents a comprehensive mitochondrial metabolism and immune infiltration landscape in SCM, providing a potential novel direction for the pathogenesis and medical intervention of SCM.

A novel berberine derivative targeting adipocyte differentiation to alleviate TNF-α-induced inflammatory effects and insulin resistance in OP9 cells

Inflammation and insulin resistance play important roles in the development and progression of type 2 diabetes mellitus. The enhancement of adipocyte differentiation can improve insulin sensitivity by increasing glucose uptake, improving insulin signaling, and reducing inflammation. However, only a few adipogenic agents have shown clinical success in patients with type 2 diabetes mellitus. The therapeutic potential of berberine in type 2 diabetes mellitus was confirmed in terms of the target gene-disease relationship using a network pharmacology database prior to synthesizing the derivatives. Novel berberine derivatives were synthesized, and compound 3b promoted adipocyte differentiation and improvement of insulin resistance in OP9 cells. Compound 3b significantly increased the expression of key adipogenic markers including peroxisome proliferator-activated receptor γ (PPARγ) and CCAAT/enhancer binding protein β (C/EBPβ) and promoted lipid accumulation without cytotoxicity. Furthermore, tumor necrosis factor α (TNF-α)-induced inhibition of adipocyte differentiation and the elevation of inflammatory responses were reversed by compound 3b. Subsequently glucose uptake level through insulin sensitivity improvement was enhanced by compound 3b. Mechanistically, TNF-α activated mitogen-activated protein kinases (MAPKs): ERK, JNK, and p38, whereas compound 3b attenuated phosphorylation of three MAPKs. Finally, in silico molecular docking suggested the possible binding sites of compound 3b on PPARγ. Collectively, the adipogenic and glucose uptake effects of compound 3b were associated with its anti-inflammatory effects and reduced phosphorylation of MAPKs. These findings suggest that the berberine derivative compound 3b may be a potent antidiabetic agent.