{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T07:02:49Z","timestamp":1782975769441,"version":"3.54.5"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T00:00:00Z","timestamp":1782950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Periodontitis is a chronic inflammatory disease characterized by progressive destruction of periodontal supporting tissues, yet the molecular mechanisms underlying its pathogenesis remain incompletely defined. This study aimed to identify key genes associated with periodontitis through an integrative bioinformatics strategy combined with experimental validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Two independent transcriptomic datasets (GSE16134 and GSE10334) were analyzed to identify differentially expressed genes. Weighted gene co-expression network analysis, protein\u2013protein interaction network construction, and machine-learning approaches, including random forest and support vector machine algorithms, were employed to screen for candidate hub genes. Gene set enrichment analysis was performed to investigate potential biological functions. A ligature-induced rat periodontitis model and human periodontal tissue samples were used for validation through micro-computed tomography, histological analysis, immunohistochemistry, and quantitative real-time PCR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>CD48 and CXCR4 were identified as key genes consistently selected across datasets and analytical methods. Both genes were significantly upregulated in periodontitis samples and demonstrated robust diagnostic performance. Functional enrichment analysis indicated that these genes were closely associated with immune-inflammatory pathways. Experimental validation further confirmed increased expression of CD48 and CXCR4 at both mRNA and protein levels in rat and human periodontal tissues.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>CD48 and CXCR4 are potential biomarkers associated with periodontitis and may be involved in the regulation of immune-inflammatory processes, particularly those related to inflammatory cell recruitment and periodontal tissue destruction, thereby providing additional insight into disease pathogenesis and offering promising molecular candidates for future translational investigation.<\/jats:p>\n                  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