By training machine learning algorithms on data from gut bacteria, scientists from McGill University and their collaborators developed a computational tool to detect patterns in the microbiome that are connected to complex regional pain syndrome (CRPS), a relatively rare condition that affects hundreds of thousands of people worldwide. When they applied the tool to patient samples, it identified a common microbiome signature connected to CRPS n that could lead to advances in how the condition is treated. Details are provided in a new Anesthesiology paper titled, “Altered gut microbiome composition and function in individuals with complex regional pain syndrome.”
CRPS typically develops in a limb after injury or surgery and can lead to long-term disability. It causes severe, persistent pain that is often far worse than the initial injury, along with swelling and changes in skin color and temperature. The condition is challenging to treat, “with patients often experiencing prolonged suffering before receiving appropriate care,” said Amir Minerbi, MD, PhD, senior author on the paper, director of the Institute for Pain Medicine in Haifa, Israel, and senior lecturer at the Technion–Israel Institute of Technology.
The results of this study could help change that. As the researchers noted in the paper, even though the condition has been linked to “dysregulation in several physiologic systems … including aberrant inflammatory and immune responses, vasomotor dysfunction, and nervous system changes,” the exact cause remains unclear, making it harder to treat. Their research could “pave the way for future studies elucidating the pathophysiology of CRPS and exploring new diagnostic aids and treatment modalities.”
Digging into the details, the scientists explain that they used advanced machine learning to analyze gut microbiome samples from two cohorts from Israel and Canada—the samples from Israel were used for training. In total, the scientists analyzed data from 120 microbiome samples as well as over 100 plasma samples from 53 CRPS patients and 52 unrelated controls.
The scientists reported that their algorithm identified significant differences between the gut bacteria of CRPS patients and pain-free individuals. In fact, they successfully predicted CRPS in Canadian patients with over 90% accuracy, according to Emmanuel Gonzalez, PhD, lead author on the paper and a member of the McGill Centre for Microbiome Research. “This is extraordinary because factors like geography, climate, diet, and natural variation between people typically create large microbiome differences. Yet, our AI approach seems to have identified a common ‘microbiome signature’ of CRPS, suggesting microbiome-based diagnostics could work across populations in different countries.”
Furthermore, even patients whose symptoms cleared after limb amputation still had the same gut bacteria pattern linked to CRPS. That suggests that the gut microbiome “might make some people more prone to developing CRPS, with an injury or other event triggering the condition,” said Yoram Shir, MD, a professor in the department of anesthesia at McGill’s Faculty of Medicine and Health Sciences.
The post AI Uncovers Gut Signature Tied to Complex Regional Pain Syndrome appeared first on GEN - Genetic Engineering and Biotechnology News.
CRPS typically develops in a limb after injury or surgery and can lead to long-term disability. It causes severe, persistent pain that is often far worse than the initial injury, along with swelling and changes in skin color and temperature. The condition is challenging to treat, “with patients often experiencing prolonged suffering before receiving appropriate care,” said Amir Minerbi, MD, PhD, senior author on the paper, director of the Institute for Pain Medicine in Haifa, Israel, and senior lecturer at the Technion–Israel Institute of Technology.
The results of this study could help change that. As the researchers noted in the paper, even though the condition has been linked to “dysregulation in several physiologic systems … including aberrant inflammatory and immune responses, vasomotor dysfunction, and nervous system changes,” the exact cause remains unclear, making it harder to treat. Their research could “pave the way for future studies elucidating the pathophysiology of CRPS and exploring new diagnostic aids and treatment modalities.”
Digging into the details, the scientists explain that they used advanced machine learning to analyze gut microbiome samples from two cohorts from Israel and Canada—the samples from Israel were used for training. In total, the scientists analyzed data from 120 microbiome samples as well as over 100 plasma samples from 53 CRPS patients and 52 unrelated controls.
The scientists reported that their algorithm identified significant differences between the gut bacteria of CRPS patients and pain-free individuals. In fact, they successfully predicted CRPS in Canadian patients with over 90% accuracy, according to Emmanuel Gonzalez, PhD, lead author on the paper and a member of the McGill Centre for Microbiome Research. “This is extraordinary because factors like geography, climate, diet, and natural variation between people typically create large microbiome differences. Yet, our AI approach seems to have identified a common ‘microbiome signature’ of CRPS, suggesting microbiome-based diagnostics could work across populations in different countries.”
Furthermore, even patients whose symptoms cleared after limb amputation still had the same gut bacteria pattern linked to CRPS. That suggests that the gut microbiome “might make some people more prone to developing CRPS, with an injury or other event triggering the condition,” said Yoram Shir, MD, a professor in the department of anesthesia at McGill’s Faculty of Medicine and Health Sciences.
The post AI Uncovers Gut Signature Tied to Complex Regional Pain Syndrome appeared first on GEN - Genetic Engineering and Biotechnology News.