Brain aging among individuals with trigeminal neuralgia

Trigeminal neuralgia (TN) is a complex orofacial neuropathic pain condition with limited understanding of underlying mechanisms and therapeutic options. Emerging evidence suggests the involvement of the brain in persons with TN including widespread brain changes when employing a widely used brain aging biomarker that estimates a predicted brain age difference or brain age gap. The aim of the present cross-sectional study was to assess the predicted brain age difference (brain-PAD) or brain age gap across two TN subtypes (classical TN, and secondary/idiopathic TN) in comparison with age-and sex-matched pain-free controls and its association with several clinical and psychological characteristics. Thirty-four individuals diagnosed with Classical TN, 17 diagnosed with secondary/idiopathic TN were age- and sex-matched to pain-free controls (n = 54). All participants underwent a T1 brain MRI and completed clinical and psychological measures. There were significant differences in brain-PAD among TN subtypes (ANCOVA p = 0.0078, effect size f² = 0.28²), with individuals diagnosed with Classical TN having a brain-PAD significantly greater than the controls by 3.87 years (p = 0.01, Bonferroni-corrected). There were no significant brain-PAD differences between secondary/idiopathic TN and pain-free controls. Brain-PAD had a significant positive association with both pain catastrophizing (p < 0.05) and pain-related anxiety (p < 0.05), but no significant association with disease duration (p < 0.05) or usual pain intensity (p < 0.05) in persons with classical TN. The results were similar using a second brain aging biomarker. We report here accelerated brain aging processes in individuals with classical TN, but not in persons diagnosed with secondary/idiopathic TN. Our study replicates previous findings and adds to the literature that accelerated brain aging may not occur across all TN subtypes. Given the increased use of MRI for TN diagnostics, combined with our own recent work deriving brain aging biomarkers from clinical-grade scans, future studies within clinical settings are feasible and may help understand this debilitating condition.