Silencing of IGF2BP1 restrains ox-LDL-induced lipid accumulation and inflammation by reducing RUNX1 expression and promoting autophagy in macrophages

Overexpression of insulin-like growth factor-2 mRNA-binding protein 1 is associated with periodontal disease

Objective

To investigate the potential role of a novel m6A RNA regulator, Insulin-like Growth Factor-2 mRNA-binding protein 1 (IGF2BP1), in periodontal disease pathogenesis.

Materials and methods

Gingival tissue samples from 60 periodontitis patients and 60 healthy individuals were analyzed for IGF2BP1 mRNA and protein expression via real-time quantitative PCR (RT-qPCR) and Western blotting. Additionally, Porphyromonas gingivalis Lipopolysaccharide (Pg-LPS) -induced human gingival fibroblasts (HGFs) were evaluated for IGF2BP1 and proinflammatory cytokine expression. In silico functional analysis further explored potential molecular mechanisms.

Results

IGF2BP1 mRNA and protein levels were significantly higher in the periodontitis group compared to the healthy group. Functional analysis implicated IGF2BP1 in regulating the IL-17 signaling pathway, a key player in inflammation. Pg-LPS treatment upregulated IGF2BP1 and proinflammatory cytokines in HGFs, supporting this finding.

Conclusion

Our study suggests that IGF2BP1 overexpression contributes to periodontitis pathogenesis, potentially through IL-17 signaling. Further research is needed to elucidate the precise molecular mechanisms and explore IGF2BP1 as a potential therapeutic target or biomarker for this common oral disease.

Identification of pivotal genes and regulatory networks associated with atherosclerotic carotid artery stenosis based on comprehensive bioinformatics analysis and machine learning

Objective

Bioinformatics methods were applied to investigate the pivotal genes and regulatory networks associated with atherosclerotic carotid artery stenosis (ACAS) and provide new insights for the treatment of this disease.

Methods

The study utilized five ACAS datasets (GSE100927, GSE11782, GESE28829, GSE41571, and GSE43292) downloaded from the NCBI GEO database. The first four datasets were combined as the training set (n = 99), while GSE43292 (n = 64) was used as the validation set. Difference analysis and functional enrichment analysis were then performed on the training set. The pathogenic targets of ACAS were screened by protein-protein interaction networks and MCODE analyses, combined with three machine learning algorithms. The results were next verified by analysis of inter-group differences and ROC curve analysis. Next, immune-related function and immune cell correlation analyses were performed, and plaques of human ACAS were applied to verify the results via immunohistochemistry (IH) and immunofluorescence (IF). Finally, the competing endogenous RNAs (ceRNA) and transcription factors (TFs) regulatory networks of the characterized genes were constructed.

Results

A total of 177 differentially expressed genes were identified, including 67 genes downregulated and 110 genes upregulated. Gene set enrichment analysis revealed that five pathways were active in the experimental group, including xenograft rejection, autoimmune thyroid disease, graft-versus-host disease, leishmaniasis infection, and lysosomes. Four key genes were identified, with C3AR1 being upregulated and FBLN5, PPP1R12A, and TPM1 being downregulated. The analysis of inter-group differences demonstrated that the four characterized genes were differentially expressed in both the control and experimental groups. The ROC analysis showed that they had high AUC values in both the training and validation sets. Therefore, a predictive ACAS patient nomogram model based on the screened genes was established. Correlation analysis revealed a positive correlation between C3AR1 expression and neutrophils, which was further validated in IH and IF. One or multiple lncRNAs may compete with the characterized genes for binding miRNAs. Additionally, each characterized gene interacts with multiple TFs.

Conclusion

Four pivotal genes were screened, and relevant ceRNA and TFs were predicted. These molecules may exert a crucial role in ACAS and serve as potential biomarkers and therapeutic targets.

Low circulating levels of miR-17 and miR-126-3p are associated with increased mortality risk in geriatric hospitalized patients affected by cardiovascular multimorbidity

MultiMorbidity (MM), defined as the co-occurrence of two or more chronic conditions, is associated with poorer health outcomes, such as recurrent hospital readmission and mortality. As a group of conditions, cardiovascular disease (CVD) exemplifies several challenges of MM, and the identification of prognostic minimally invasive biomarkers to stratify mortality risk in patients affected by cardiovascular MM is a huge challenge. Circulating miRNAs associated to inflammaging and endothelial dysfunction, such as miR-17, miR-21-5p, and miR-126-3p, are expected to have prognostic relevance. We analyzed a composite profile of circulating biomarkers, including miR-17, miR-21-5p, and miR-126-3p, and routine laboratory biomarkers in a sample of 246 hospitalized geriatric patients selected for cardiovascular MM from the Report-AGE INRCA database and BioGER INRCA biobank, to evaluate the association with all-cause mortality during 31 days and 12 and 24 months follow-up. Circulating levels of miR-17, miR-126-3p, and some blood parameters, including neutrophil to lymphocyte ratio (NLR) and eGFR, were significantly associated with mortality in these patients. Overall, our results suggest that in a cohort of geriatric hospitalized patients affected by cardiovascular MM, lower circulating miR-17 and miR-126-3p levels could contribute to identify patients at higher risk of short- and medium-term mortality.

Identification of hub genes and transcription factors in patients with primary gout complicated with atherosclerosis

Evidence shows that primary gout is prone to develop to atherosclerosis, but the mechanism of its occurrence is still not fully clarified. The aim of this study was to explore the molecular mechanism of the occurrence of this complication in gout. The gene expression profiles of primary gout and atherosclerosis were downloaded from the gene expression omnibus database. Overlapping differentially expressed genes (DEGs) between gout and atherosclerosis were identified. The biological roles of common DEGs were explored through enrichment analyses. Hub genes were identified using protein-protein interaction networks. The immune infiltrations of 28 types of immune cells in gout and control samples from GSE160170 were evaluated by the ssGSEA method. Transcription factors (TFs) were predicted using Transcriptional Regulatory Relationships Unraveled by Sentence Based Text Mining (TRRUST) database. A total of 168 overlapping DEGs were identified. Functional enrichment analyses indicated that DEGs were mostly enriched in chemokine signaling pathway, regulation of actin cytoskeleton, and TNF signaling pathway. CytoScape demonstrated 11 hub genes and two gene cluster modules. The immune infiltration analysis showed that the expression of DEGs in gout was significantly upregulated in activated CD4 T cells, gamma delta T cells, T follicular helper cell, CD56dim natural killer cells, and eosinophil. TRRUST predicted one TF, RUNX family transcription factor 1. Our study explored the pathogenesis of gout with atherosclerosis and discovered the immune infiltration of gout. These results may guide future experimental research and clinical transformation.

Circular RNA CircSLC8A1 contributes to osteogenic differentiation in hBMSCs via CircSLC8A1/miR-144-3p/RUNX1 in periprosthetic osteolysis

Circular RNAs (circRNAs) are often found in eukaryocyte and have a role in the pathogenesis of a variety of human disorders. Our related research has shown the differential expression of circRNAs in periprosthetic osteolysis (PPOL). However, the involvement of circRNAs in the exact process is yet unknown. CircSLC8A1 expression was evaluated in clinical samples and human bone marrow mesenchymal stem cells (hBMSCs) in this investigation using quantitative real-time PCR. In vitro and in vivo studies were conducted to explicate its functional role and pathway. We demonstrated CircSLC8A1 is involved in PPOL using gain- and loss-of-function methods. The association of CircSLC8A1 and miR-144-3p, along with miR-144-3p and RUNX1, was predicted using bioinformatics. RNA pull-down and luciferase assays confirmed it. The impact of CircSLC8A1 in the PPOL-mouse model was also investigated using adeno-associated virus. CircSLC8A1 was found to be downregulated in PPOL patients' periprosthetic tissues. Overexpression of CircSLC8A1 promoted osteogenic differentiation (OD) and inhibited apoptosis of hBMSCs in vitro. The osteogenic markers of RUNX1, osteopontin (OPN) and osteocalcin (OCN) were significantly upregulated in hBMSCs after miR-144-3p inhibitor was transferred. Mechanistic analysis demonstrated that CircSLC8A1 directly bound to miR-144-3p and participated in PPOL through the miR-144-3p/RUNX1 pathway in hBMSCs. Micro-CT and quantitative analysis showed that CircSLC8A1 markedly inhibited PPOL, and osteogenic markers (RUNX1, OPN and OCN) were significantly increased (P<0.05) in the mice model. Our findings prove that CircSLC8A1 exerted a regulatory role in promoting osteogenic differentiation in hBMSCs, and CircSLC8A1/miR-144-3p/RUNX1 pathway may provide a potential target for prevention of PPOL.

Novel insight into m6A regulator-mediated methylation modification patterns and immune characteristics in intracranial aneurysm

Background

Growing evidence demonstrated that m6A modification in cardiovascular diseases. However, how it is involved in the intracranial aneurysm (IA) is still unclear. This study aimed to identify the role of m6A modification in IA.

Methods

Three datasets downloaded from the Gene Expression Omnibus (GEO) database were used, including GSE122897, GSE15629, and GSE3679. The landscapes of 24 m6A regulators were depicted using the STRING database, Pearson’s correlation analysis, and Wilcoxon test. The targets of differentially expressed m6A (DEm6A) were predicted in the m6A2Target database and the modification m6A sites of hub targets were identified in SRAMP online tool. A diagnostic model based on DEm6A was constructed and verified in training and test databases. A consensus clustering algorithm was performed to classify IA patients into distinct m6A-related clusters. Functional analyses including gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set variation analysis, and gene set enrichment analysis analyses were conducted to elucidate the underlying mechanisms. ssGSEA algorithm was performed to uncover the immune characteristics. A PCA method was adopted to quantify the m6A score.

Results

Nine DEm6A (IGF2BP1, IGF2BP3, YTHDF2, ZNF217, RBM15, YTHDF3, YTHDC1, FTO, and LRPPRC) significantly differed between IA and controls. Biological annotations showed that immune-related pathways (such as complement activation, inflammatory response, and interleukin signaling) and apoptosis were more enriched in IAs than in controls. Immune analyses indicate that the abundance of immune cells, immune responses, and HLA gene expression were elevated in IA samples than in controls. PCA results showed that IA has a lower m6A score than controls. An immune/apoptosis-related network modified by DEm6A was constructed. The m6A sites of six hub targets (CDK1, ASPM, AURKB, BUB1B, MKI67, and TPX2) were predicted with very high confidence. A diagnostic model with four genes (LRPPRC, YTHDF3, IGF2BP1, and ZNF217) was constructed and verified. Two m6A modification subtypes were identified with unsupervised cluster analysis. Immune infiltration analysis revealed that cluster 1 had higher immune activation than cluster 2. Further study showed that cluster 1 had a larger proportion of ruptured IAs.

Conclusion

The m6A modification may shape the IAs microenvironment and participates in the formation and rupture of IAs by regulating immune infiltration.

Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Fatty acid metabolism takes part in malignancy progression. However, the roles fatty acid metabolism plays in LUAD are still unclear.

Methods: The transcriptomic and clinical data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were extracted. ssGSEA, WGCNA, univariable Cox regression, and LASSO Cox regression analyses were performed to identify the fatty acid metabolism-related genes which influenced the overall survival (OS) and build a fatty acid-related risk score (FARS) model. A nomogram was established based on the FARS and other clinicopathological features, and ROC and calibration plots were used to validate the prediction accuracy. The tumor microenvironment (TME) of patients with high and low FARS was compared.

Results: A total of 38 genes were identified to be independently related to the survival outcome and put into a FARS model. High FARS patients exhibited significantly worse OS. The nomogram included the FARS and pathological stage, and the AUC of the nomogram predicting 1-, 2-, 3-, 4-, and 5-year OS was 0.789, 0.807, 0.798, 0.809, and 0.753, respectively. Calibration plots also indicated good accuracy. Moreover, the samples of the high FARS had higher expression of PDL1.

Conclusion: We constructed a FARS model which could accurately predict the survival outcome of the LUAD patients. The genes of the FARS are related to the tumor microenvironment and patients with high FARS can potentially benefit more from anti-PD1/PDL1 immunotherapy. In addition, the mechanisms of the genes in the FARS affecting prognosis are worthy of further research to develop new gene-targeted drugs.