Summary: New research demonstrates that artificial intelligence can detect complex regional pain syndrome (CRPS) by analyzing gut microbiome patterns, achieving over 90% accuracy. Despite differences in geography and diet, researchers found a consistent “microbiome signature” in patients from Israel and Canada.
Remarkably, people who no longer showed CRPS symptoms after limb amputation still retained this gut microbiome pattern, suggesting it may indicate an underlying susceptibility. These results open the possibility of microbiome-based diagnostics and earlier, more reliable detection of CRPS and potentially other chronic pain disorders.
Key Facts:
- High diagnostic accuracy: Machine learning models distinguished CRPS patients from controls using gut microbiome data with over 90% accuracy across countries.
- Persistent microbiome signature: The distinctive gut bacterial pattern associated with CRPS persisted in some patients even after symptoms resolved following amputation.
- Potential susceptibility marker: The findings suggest the gut microbiome could predispose certain individuals to develop CRPS after an injury or trigger.
Source: McGill University
Researchers at McGill University, together with collaborators in Israel and Ireland, used advanced AI to identify gut bacterial patterns linked to complex regional pain syndrome (CRPS). Their approach may significantly change diagnosis and management of this debilitating condition.
CRPS is a chronic pain disorder that most often affects a limb following injury or surgery and can cause intense, long-lasting pain far exceeding the original injury. Symptoms frequently include swelling and changes in skin colour and temperature, and the condition can lead to serious disability. Estimates suggest CRPS affects hundreds of thousands to millions of people worldwide.
“CRPS remains difficult to treat, and many patients endure long periods of suffering before receiving appropriate care,” said Dr. Amir Minerbi, Director of the Institute for Pain Medicine at Rambam Health Campus in Haifa, Israel, and senior lecturer at the Technion – Israel Institute of Technology.
A ‘microbiome signature’ of CRPS
Published in the journal Anesthesiology, the study applied machine learning to gut microbiome data collected from cohorts in Israel and Canada. Algorithms trained on Israeli patient data successfully identified CRPS in the independent Canadian cohort with more than 90% accuracy.
“Achieving high predictive accuracy across populations is especially noteworthy because factors like geography, diet and individual variation usually produce substantial differences in microbiome composition,” said Emmanuel Gonzalez, lead author and member of the McGill Centre for Microbiome Research and the Canadian Centre for Computational Genomics. “Our results suggest a shared microbiome signature for CRPS that might be robust across diverse populations.”
The analysis highlighted significant compositional differences in gut bacteria between CRPS patients and pain-free controls, including changes in taxa involved in short-chain fatty acid metabolism.
Findings suggest some people may be predisposed to CRPS
An unexpected observation was that some individuals who no longer experienced CRPS symptoms after limb amputation continued to exhibit the same gut microbiome pattern associated with the disorder. This persistence implies the microbiome could represent a predisposing factor, with an injury or other trigger initiating symptomatic disease in susceptible people.
“A lasting microbiome signature in symptom-free individuals points to the gut ecosystem playing a role in vulnerability to CRPS,” said Dr. Yoram Shir, Professor in the Department of Anesthesia at McGill’s Faculty of Medicine and Health Sciences, who led the clinical effort in Montreal.
The study included sequencing and metabolite analyses from a substantial sample set—120 microbiome samples and more than 100 plasma samples—making it among the largest investigations to date linking gut microbiome composition and chronic pain.
Funding: The research received support from Rambam Health Care Campus, the Weston Family Foundation, the Alan Edwards Pain Management Unit, McGill University Health Centre and the Rambam Institute for Pain Medicine.
About this AI, microbiome and pain research
Author: Keila DePape
Source: McGill University
Contact: Keila DePape – McGill University
Image credit: Neuroscience News
Original research: Closed access. “Altered Gut Microbiome Composition and Function in Individuals with Complex Regional Pain Syndrome” by Amir Minerbi et al., Anesthesiology. DOI: 10.1097/ALN.0000000000005435
Abstract
Altered Gut Microbiome Composition and Function in Individuals with Complex Regional Pain Syndrome
Background:
Complex regional pain syndrome is a chronic condition often affecting a limb, characterized by severe spontaneous and evoked pain together with vasomotor, autonomic and motor disturbances. Although alterations in inflammatory and immune responses, vasomotor control and nervous system function have been proposed, the precise mechanisms of CRPS remain unclear. Limited effective treatments and mounting evidence that the gut microbiome influences chronic pain prompted investigation of microbial composition and function in CRPS.
Methods:
Researchers compared gut microbiomes from individuals with CRPS to age-, sex- and ethnicity-matched pain-free controls using 16S rRNA gene sequencing. To reduce environmental confounders, participants were recruited from two geographically distinct regions. Targeted metabolomic analyses of stool and plasma explored microbially derived metabolites, and machine learning models were trained to identify a microbiome profile specific to CRPS and validated on an independent cohort.
Results:
Differential abundance analysis of 53 CRPS patients and 52 unrelated controls revealed significant differences in several bacterial taxa, including shifts in species that metabolize short-chain fatty acids. Targeted metabolite profiling confirmed altered fecal and plasma short-chain fatty acid levels between patients and controls. Importantly, microbiome composition alone accurately classified patients and controls in a geographically independent test cohort.
Conclusions:
The study identifies distinct compositional and functional changes in the gut microbiome of individuals with CRPS, supporting a growing body of evidence that the microbiome contributes to chronic pain syndromes. These findings encourage further research into CRPS pathophysiology and the development of microbiome-informed diagnostic tools and therapeutic strategies.