Our partners at Indiana University leveraged Next-Generation Metabolomics to profile metabolic and lipidomic changes in gingival crevicular fluid from healthy individuals and patients with periodontitis. Using dual LC-MS platforms and deep-learning–assisted data curation, the study identified 256 differentially expressed metabolites, revealing elevated purine degradation products, increased ceramides, reduced oxy-fatty acids, and enrichment of known periodontitis biomarkers. Distinct microbial metabolite signatures further highlighted disease-related biochemical disruptions, supporting the potential of GCF metabolomics for advancing precision approaches in periodontal research.
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