MicroRNA networks potentially relevant to mandibular condylar cartilage adaptation during functional appliance therapy: an exploratory bioinformatic analysis

Background Mandibular condylar cartilage(MCC) adaptation during functional appliance therapy(FAT) involves interconnected molecular processes, not characterized using individual biomarkers. MicroRNAs(miRNAs) can regulate multiple genes and signaling pathways. Thus, maybe useful candidates for network-level study of MCC biology. Aims To characterize predicted target genes, signaling pathways, shared regulatory relationships, and network-central genes associated with miR-145, miR-200a, and miR-675, and to interpret these findings using the previously proposed BioSig-MCC framework. Methods This exploratory bioinformatic study used three prespecified miRNAs(miR-200a-3p, miR-145-5p, miR-675-5p), previously investigated in a prospective cohort of 10 growing patients(skeletal Class II malocclusion, 9 months of FAT). Predicted miRNA targets were identified using miRDB, followed by functional pathway enrichment using DAVID. Shared target genes were identified. An integrated protein-protein interaction(PPI) network was analyzed using STRING and Cytoscape. Network connectivity was assessed using degree and betweenness centrality. Highly connected genes were identified using more than 10 neighboring nodes. The resulting molecular findings were interpreted within the previously proposed six-layer BioSig-MCC framework. Patient-level ?Ct values were not used as quantitative inputs for target prediction, pathway enrichment, or network analysis. Results The analysis identified 1,088 predicted targets for miR-200a-3p, 909 for miR-145-5p, and 38 for miR-675-5p. Fourteen enriched pathways for miR-200a-3p and 17 for miR-145-5p were identified, including MAPK, PI3K-Akt, ErbB, Ras, and focal adhesion signaling. A total of 122 predicted genes were shared between miR-200a-3p and miR-145-5p. Two genes were shared between miR-200a-3p and miR-675-5p, and three between miR-145-5p and miR-675-5p, with no target shared by all three miRNAs. The integrated PPI network comprised of 101 highly connected genes. No pathway-level interpretation was done for miR-675-5p as no pathway remained significantly enriched after FDR correctio. The identified pathways and network-central genes were conceptually organized across multiple functional layers of MCC using the BioSig-MCC framework. Conclusion This miRNA-centered bioinformatic analysis identified molecular networks potentially relevant to MCC adaptation during FAT, interpreted within the proposed six-layer BioSig-MCC model. The identified candidate miRNA-target and pathway associations do not, however, establish pathway activation, causality, or MCC activity. Future animal studies are warranted to validate the spatial and temporal relevance of layer-specific molecular biomarkers during mandibular advancement.