Altered Catecholamine Metabolism in Atypical Facial Pain: Quantitative and Predictive Insights from Salivary COMT Expression
DOI:
https://doi.org/10.15517/w2q1r170Keywords:
Pain; Biomarker; Mental health; COMT; Saliva.Abstract
Atypical Facial Pain (AFP) is a chronic orofacial pain disorder marked by persistent, idiopathic facial pain significantly affecting the mental health and quality of life. Identifying objective biomarkers remains challenging. Catechol-O-methyltransferase (COMT), a key enzyme in catecholamine metabolism, modulates pain and stress responses; its reduced activity has been linked to chronic pain. This study assessed salivary COMT levels in AFP patients and explored its diagnostic utility through statistical and machine-learning approaches. A comparative cross-sectional study was conducted with 20 AFP patients and 20 age- and sex-matched healthy controls. Unstimulated saliva samples (8:00-10:00 AM) were analyzed using a Human COMT ELISA kit (KRISHGEN Biosystems). Group differences were tested with an independent samples t-test, and effect size, confidence intervals, and power were calculated. Diagnostic performance was evaluated using ROC and logistic regression, with leave-one-out cross-validation (LOOCV) for model validation. AFP patients showed significantly lower salivary COMT (14.20±3.15 ng/mL) than controls (20.08±2.39 ng/mL; t(18)=3.03, p=0.0073). The mean difference (7.03 ng/mL; 95% CI: 2.07-11.49) yielded a large effect size (Cohen’s d=1.35) and power of 0.82. ROC analysis produced an AUC=0.86 with 90% sensitivity and specificity at 17.7 ng/mL. Logistic regression confirmed COMT as a significant AFP predictor (β= –1.19, p<0.05). LOOCV achieved 75% accuracy, 0.86 precision, 0.60 recall, and AUC=0.82. Salivary COMT levels are markedly reduced in AFP, reflecting altered catecholamine metabolism and pain modulation. Both statistical and machine-learning analyses confirmed excellent discriminative accuracy, supporting COMT as a promising non-invasive, accessible biomarker for AFP screening and diagnosis.
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