Jiaguan Zhang, Ziyan Liu, Jianqing Deng, Peishan Huang, Huijuan Liu
Periodontitis is a chronic inflammatory condition linked to systemic diseases, yet the neuroendocrine mechanisms underlying its pathogenesis remain unclear. This study aimed to elucidate neuroendocrine-related molecular pathways involved in periodontitis. Transcriptomic data and neuroendocrine-related genes (NRGs) were integrated to identify candidate genes from the overlap between differentially expressed genes (DEGs) and NRGs. Machine learning, ROC analysis and expression validation were used to screen key genes and construct a diagnostic nomogram. Functional enrichment, immune infiltration, drug prediction, molecular docking and single-cell analyses were performed. Key gene expression was further validated using clinical samples. Nine candidate genes were obtained from the intersection of 210 DEGs and 1441 NRGs. Five key genes-FOXN1, XBP1, HCLS1, IRF4 and RORA-were identified and used to develop an effective diagnostic model. These genes showed distinct tissue and cellular distributions and were enriched in pathways such as Ribosome and Protein processing in the ER. Sixteen immune cell types differed between groups, and 24 potential drugs, including melatonin, were predicted. Single-cell analysis highlighted T cells and Endothelial cells as central cell populations. PCR results aligned with bioinformatic findings. Five neuroendocrine-related genes were identified as potential diagnostic biomarkers and therapeutic targets, offering new insights into the neuroendocrine mechanisms of periodontitis.