A RECENT cohort study has identified a novel cortical biomarker signature that accurately predicts individual pain sensitivity, offering promising implications for the diagnosis, prevention, and treatment of chronic pain. The study focused on two specific measures of cortical activity: sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME).
Conducted at Neuroscience Research Australia between November 2020 and October 2022, the study recruited 150 healthy adults aged 18 to 44 years with no history of chronic pain or neurological or psychiatric conditions. Participants underwent a model of prolonged temporomandibular pain induced by nerve growth factor injections into the right masseter muscle on days 0 and 2, resulting in pain lasting up to four weeks. Electroencephalography (EEG) was used to assess PAF, while transcranial magnetic stimulation (TMS) evaluated CME on days 0, 2, and 5. Pain levels were self-reported twice daily from days 1 through 30.
The researchers employed a nested control-test scheme to determine the predictive accuracy of the PAF/CME biomarker signature. A logistic regression model was trained on a subset of 100 participants, using PAF and CME as predictors and pain sensitivity as the outcome. This model demonstrated outstanding performance, with an area under the curve (AUC) of 1.00. When tested on the remaining 50 participants, the model maintained excellent performance (AUC = 0.88; 95% CI, 0.78-0.99). Notably, including variables such as sex and pain catastrophizing did not enhance the model’s performance, indicating the robustness of the biomarker-based model. Additionally, PAF and CME measures exhibited good to excellent test-retest reliability.
The findings suggest that the combination of slower PAF and CME depression is predictive of higher pain sensitivity. This cortical biomarker signature not only distinguishes between individuals with high and low pain sensitivity but also holds potential for predicting the transition from acute to chronic pain. The study’s authors emphasize the need for further research to explore the clinical applications of this biomarker signature in patient populations, which could lead to more personalized and effective pain management strategies.
In summary, this study provides compelling evidence for a sensorimotor cortical biomarker signature that accurately predicts individual pain sensitivity. The combination of PAF and CME measures offers a reliable and reproducible tool with significant potential for clinical translation in the field of pain management.
Reference: Chowdury NS et al. Predicting Individual Pain Sensitivity Using a Novel Cortical Biomarker Signature. JAMA Neurol. 2025. doi:10.1001/jamaneurol.2024.4857.
