A systems biology network analysis of root resorption biomarkers and their clinical relevance in orthodontics: a pilot study

Abstract Background External apical root resorption is a frequently reported iatrogenic consequence of orthodontic tooth movement. This pilot study used an integrated systems biology approach to identify signaling pathways, key genes, and candidate salivary biomarkers associated with orthodontic root resorption to support future functional research. Methods The present study used a sequential workflow that began with identifying root resorption-associated genes from a systematic literature review and the DisGeNET database. Subsequently, a protein–protein interaction (PPI) network was constructed to identify hub genes, followed by pathway enrichment and Gene Ontology analyses. Next, a Gene Regulatory Network was built to predict upstream transcription factors. Finally, an ELISA assay was performed on saliva samples from 12 patients with orthodontic root resorption and 12 matched controls to validate the computational findings experimentally. The diagnostic utility of the selected markers was assessed using receiver operating characteristic (ROC) curves. Results A set of 160 genes was found to be linked to the process of orthodontic root resorption. Within the PPIN, 13 genes were recognized as central hub genes. Among these, CASP1 and SPP1 were selected for the ELISA assay. Gene Regulatory Network analysis computationally identified IRF4 as the most impactful upstream regulator of CASP1 and SPP1. The ELISA analysis confirmed overexpression of salivary Caspase-1 and Osteopontin proteins in patients with orthodontic root resorption compared with those without signs of the condition. Caspase-1 emerged as a strong candidate for non-invasive diagnosis of root resorption in orthodontic patients, with impressive efficacy (AUC = 0.9861; Youden Index = 0.917). Conclusion This study suggests that elevated salivary levels of CASP1 and SPP1 are associated with radiographically confirmed OIIRR. These proteins represent candidate biomarkers whose potential biological relevance warrants longitudinal evaluation, rather than definitive predictive tools or therapeutic targets. Therefore, given the preliminary nature of these bioinformatics analyses and the limited sample size in the clinical validation, further large-scale prospective studies are required to confirm their diagnostic and therapeutic utility.