Bioinformatics Approach to Investigating the Immuno-Inflammatory Mechanisms of Periodontitis in the Progression of Atherosclerosis.

Unstable atherosclerotic plaques are a major cause of acute cardiovascular events and ischemic stroke. Clinical studies have suggested a link between periodontitis and atherosclerotic plaque progression, but the underlying mechanisms remain unclear. To investigate this, transcriptomic datasets related to periodontitis and atherosclerosis were downloaded from Gene Expression Omnibus. A weighted gene co-expression network analysis was used to identify gene modules associated with periodontitis, and the Limma R package identified differentially expressed genes (DEGs) between unstable and stable plaques. Overlapping genes were defined as periodontitis-related DEGs, followed by functional enrichment analysis and protein-protein interaction network construction. Machine learning methods were used to identify biomarkers for unstable plaques related to periodontitis, which were validated using external datasets. Immune infiltration and single-cell analyses were performed to explore the relationship between biomarkers and immune cells. A total of 161 periodontitis-related DEGs were identified, with the pathway analysis showing associations with immune regulation and collagen matrix degradation.