An international team of researchers has discovered specific brain activity patterns that can predict how sensitive a person is to pain, potentially paving the way for better pain management strategies.
The study, conducted by scientists from Western University, the University of Maryland School of Dentistry (UMSOD), and Neuroscience Research Australia (NeuRA), was published in JAMA Neurology.
Chronic pain affects millions of people worldwide and often disrupts daily life, work, and relationships. The Global Burden of Disease study estimates that about 1.7 billion people suffer from musculoskeletal conditions, which include persistent pain in muscles, bones, and joints.
Despite its widespread impact, there is a significant gap in understanding why some people transition from acute pain to chronic pain, and effective treatments remain limited.
This groundbreaking research focuses on two specific brain biomarkers: corticomotor excitability (CME) and peak alpha frequency (PAF).
CME measures activity in the part of the brain responsible for movement, while PAF is linked to cognitive performance and is measured using electroencephalography (EEG), which records electrical signals in the brain. CME is assessed through transcranial magnetic stimulation, a technique that uses magnetic fields to activate brain cells.
The researchers found that these biomarkers can distinguish between individuals who are highly sensitive to pain and those who are less sensitive, with an impressive 88% accuracy. This discovery could lead to tailored treatments for people experiencing prolonged or chronic pain, improving their quality of life.
For the study, the team focused on jaw pain, a common symptom of temporomandibular disorders, which affect the joint and muscles of the jaw. They analyzed data from 150 participants in Australia, aged 18 to 44.
By measuring PAF and CME during and after pain episodes, they identified patterns that predict an individual’s sensitivity to prolonged pain.
The findings showed that people with slower PAF before experiencing prolonged pain and reduced CME shortly after the onset of pain were more likely to have higher pain levels days or weeks later.
Similar results from complementary studies revealed that individuals with low CME during the early stages of low back pain were more likely to develop chronic pain after six months. These results suggest that monitoring these biomarkers could help predict a person’s likelihood of transitioning from acute to chronic pain.
The potential applications of this research are wide-ranging. For example, PAF and CME measurements could be used before surgery or after an injury to determine whether a patient is more likely to experience chronic pain. This could allow healthcare providers to intervene early with targeted treatments, reducing the risk of long-term pain.
“This study represents a major leap forward in pain science,” said Siobhan Schabrun, a professor at Western University’s School of Physical Therapy. “A biomarker that predicts pain sensitivity with such high accuracy could transform how we treat and prevent pain in the future.”
Building on these findings, the researchers are working to validate the biomarkers in clinical settings. If successful, this could help predict the transition from acute to chronic pain and guide personalized pain management strategies.
Senior author David Seminowicz emphasized the importance of this discovery, stating, “The burden of chronic pain is massive. Having objective biomarkers would greatly assist in diagnosing, preventing, and treating chronic pain.”
In conclusion, the study demonstrates the potential of brain biomarkers like CME and PAF to revolutionize pain management. By providing a reliable way to predict pain sensitivity, this research opens new doors for personalized treatment plans, early interventions, and improved patient outcomes.
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The research findings can be found in JAMA Neurology.
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