Crosstalk between ubiquitin ligases and ncRNAs drives cardiovascular disease progression

Plasmodium Infection Modulates Host Inflammatory Response through circRNAs during the Intracellular Stage in Red Blood Cells

The integration of RNA- and DNA-based assays enables the investigation of disease dynamics, specifically assessing the role of asymptomatic or subclinical infections in malaria transmission. Circular RNAs (circRNAs), a distinct category of noncoding RNAs, are implicated in numerous pathogenic mechanisms. As of now, research has yet to explore circRNAs' function in malaria infection. The findings revealed that Plasmodium infection upregulated 60 circRNAs and downregulated 71 in BALB/c mice. We selected 11 differentially expressed (DE) circRNAs according to function prediction of target miRNA-mRNA and coding protein, and these were further confirmed by validation experiments. IRESfinder, GO, and KEGG evaluations indicated that 7 DE circRNAs possess protein-coding potential and are enriched in the MAPK signaling cascade. In P.y17XL-infected BALB/c mouse models, the findings substantiated that the dynamic characteristics of DE circRNAs correlated with inflammation, and the MAPK and NF-κB signaling cascades were activated, also contributing to the inflammatory reaction during malaria infection. This study establishes Plasmodium-induced circRNA expression as a novel mechanism by which the parasite modulates host immune signaling, advancing the understanding of Plasmodium-host cell interactions. In addition, 42 circRNAs were found in normal BALB/c mice, and 25 circRNAs were discovered in P.y17XL-infected BALB/c mice, excluding 1238 circRNAs shared by normal and P.y17XL-infected BALB/c mice. Plasmodium infection changes the expression profile of circRNAs in the host, and these altered circRNAs are involved in the inflammatory response during malaria infection. In addition, Plasmodium possibly regulates the reverse splicing of pre-mRNA or m6A modification of RNA, inducing the production of novel circRNAs in the host.

Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning

Background

Recent studies have suggested a potential association between gastric cancer (GC) and myocardial infarction (MI), with shared pathogenic factors. This study aimed to identify these common factors and potential pharmacologic targets.

Methods

Data from the IEU Open GWAS project were used. Two-sample Mendelian randomization (MR) analysis was used to explore the causal link between MI and GC. Transcriptome analysis identified common differentially expressed genes, followed by enrichment analysis. Drug target MR analysis and eQTLs validated these associations with GC, and the Steiger direction test confirmed their direction. The random forest and Lasso algorithms were used to identify genes with diagnostic value, leading to nomogram construction. The performance of the model was evaluated via ROC, calibration, and decision curves. Correlations between diagnostic genes and immune cell infiltration were analyzed.

Results

MI was linked to increased GC risk (OR=1.112, P=0.04). Seventy-four genes, which are related mainly to ubiquitin-dependent proteasome pathways, were commonly differentially expressed between MI and GC. Nine genes were consistently associated with GC, and eight had diagnostic value. The nomogram built on these eight genes had strong predictive performance (AUC=0.950, validation set AUC=0.957). Immune cell infiltration analysis revealed significant correlations between several genes and immune cells, such as T cells, macrophages, neutrophils, B cells, and dendritic cells.

Conclusion

MI is associated with an increased risk of developing GC, and both share common pathogenic factors. The nomogram constructed based on 8 genes with diagnostic value had good predictive performance.

LncRNA NR_045147 modulates osteogenic differentiation and migration in PDLSCs via ITGB3BP degradation and mitochondrial dysfunction

Periodontitis is an inflammation of the alveolar bone and soft tissue surrounding the teeth. Although mesenchymal stem cells (MSCs) have been implicated in periodontal regeneration, the mechanisms by which they promote osteogenesis remain unclear. We examined whether epigenetic modifications mediated by the long-noncoding RNA (lncRNA) NR_045147, which plays a crucial role in cancer, influence the osteogenic differentiation of periodontal ligament stem cells (PDLSCs). Alkaline phosphatase staining, alizarin red staining, and western blotting were used to detect the effects of NR_045147 on PDLSC osteogenic differentiation. Scratch migration and transwell chemotaxis assays were used to evaluate the effects of NR_045147 on PDLSC migration. Mitochondrial function was evaluated via Seahorse XF analysis to measure changes in cellular respiration upon manipulation of NR_045147 expression. Ubiquitination assays were performed to examine the protein stability and degradation pathways affected by the NR_045147-MDM2 interaction. An in vivo nude rat calvarial defect model was established and gene-edited PDLSCs were re-implanted to examine the osteogenic effects of NR_045147. NR_045147 significantly reduced PDLSC osteogenic differentiation and migration ability both in vitro and in vivo. Under inflammatory conditions, the loss of NR_045147 rescued osteogenesis. NR_045147 significantly blocked the expression of integrin beta3-binding protein (ITGB3BP). Mechanistically, NR_045147 promoted the ITGB3BP-MDM2 interaction, thus increasing ITGB3BP ubiquitination and degradation. NR_045147 regulated PDLSC mitochondrial respiration and ITGB3BP upregulation efficiently promoted their osteogenic differentiation and migration ability. Concluding, NR_045147 downregulation enhances PDLSC osteogenic differentiation and migration, connects changes in cellular metabolism to functional outcomes via mitochondrial respiration, and promotes ITGB3BP degradation by mediating its interaction with MDM2.

LncRNA NR_045147 modulates osteogenic differentiation and migration in PDLSCs via ITGB3BP degradation and mitochondrial dysfunction

Periodontitis is an inflammation of the alveolar bone and soft tissue surrounding the teeth. Although mesenchymal stem cells (MSCs) have been implicated in periodontal regeneration, the mechanisms by which they promote osteogenesis remain unclear. We examined whether epigenetic modifications mediated by the long-noncoding RNA (lncRNA) NR_045147, which plays a crucial role in cancer, influence the osteogenic differentiation of periodontal ligament stem cells (PDLSCs). Alkaline phosphatase staining, alizarin red staining, and western blotting were used to detect the effects of NR_045147 on PDLSC osteogenic differentiation. Scratch migration and transwell chemotaxis assays were used to evaluate the effects of NR_045147 on PDLSC migration. Mitochondrial function was evaluated via Seahorse XF analysis to measure changes in cellular respiration upon manipulation of NR_045147 expression. Ubiquitination assays were performed to examine the protein stability and degradation pathways affected by the NR_045147–MDM2 interaction. An in vivo nude rat calvarial defect model was established and gene-edited PDLSCs were re-implanted to examine the osteogenic effects of NR_045147. NR_045147 significantly reduced PDLSC osteogenic differentiation and migration ability both in vitro and in vivo. Under inflammatory conditions, the loss of NR_045147 rescued osteogenesis. NR_045147 significantly blocked the expression of integrin beta3-binding protein (ITGB3BP). Mechanistically, NR_045147 promoted the ITGB3BP-MDM2 interaction, thus increasing ITGB3BP ubiquitination and degradation. NR_045147 regulated PDLSC mitochondrial respiration and ITGB3BP upregulation efficiently promoted their osteogenic differentiation and migration ability. Concluding, NR_045147 downregulation enhances PDLSC osteogenic differentiation and migration, connects changes in cellular metabolism to functional outcomes via mitochondrial respiration, and promotes ITGB3BP degradation by mediating its interaction with MDM2.