A NOVEL cortical biomarker signature combining sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME) can accurately distinguish between high and low pain-sensitive individuals, with strong potential for clinical application.
Chronic pain affects millions worldwide, yet objective tools to predict individual pain sensitivity remain limited. Identifying reliable biomarkers could revolutionise pain management by enabling early interventions and personalised treatment strategies. This study aimed to validate a sensorimotor cortical biomarker signature for pain sensitivity using electroencephalography (EEG) and transcranial magnetic stimulation (TMS) in a cohort of healthy adults. By assessing the predictive power of PAF and CME, researchers sought to establish a robust and reproducible method for classifying individuals based on pain sensitivity.
A total of 150 healthy participants (mean age 25.1 years, 66 female, 84 male) were recruited for this cohort study. Each participant received nerve growth factor (NGF) injections to induce prolonged temporomandibular pain. PAF and CME were measured at multiple time points using EEG and TMS, respectively. Pain sensitivity was assessed over 30 days. A logistic regression model trained on 100 participants demonstrated outstanding predictive performance (AUC = 1.00). When validated on a test set of 50 participants, the model retained excellent accuracy (AUC = 0.88, 95% CI 0.78-0.99). Importantly, results remained consistent across methodological variations, and the inclusion of sex and pain catastrophizing did not enhance model performance, indicating the robustness of the biomarker signature.
The findings provide compelling evidence that a cortical biomarker signature can effectively predict pain sensitivity. The combination of high accuracy, reproducibility, and reliability suggests strong potential for clinical translation. Future research should explore its application in predicting the transition from acute to chronic pain, which could transform patient care by identifying at-risk individuals and tailoring early interventions. Integrating this biomarker into clinical practice could enhance precision medicine approaches for pain management, ultimately improving patient outcomes.
Katrina Thornber, EMJ
Reference
Chowdhury NS et al. Predicting individual pain sensitivity using a novel cortical biomarker signature. JAMA Neurol. 2025;DOI:10.1001/jamaneurol.2024.4857.
