Gut Microbiome and Individual Differences in Lumbosacral Radicular Pain
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The profile of pain severity, impact, and persistence after (surgical) treatment is heterogeneous. For example, some patients with lumbosacral radicular pain, who do not respond to conservative therapies, eventually undergo spine surgeries. While many improve after surgery, some continue to suffer from back or leg pain, or develop new or worsened symptoms, leading to unfavorable outcomes. While the mechanisms underlying individual differences in pain including lumbosacral radicular pain are unknown, a large body of evidence suggests that genetic factors appear to explain only a small fraction of the individual variability in pain outcomes, suggesting significant contribution from other factors. The gut microbiome is a critical player in hosts’ physiology. Recently, important links between the gut microbiome and chronic pain have been elucidated, raising the question of whether the gut microbiome contributes mechanistically to the individual differences in lumbosacral radicular pain. In previous studies, we have established critical roles of the gut microbiome in neuropathic pain. More recently, we conducted a metabolomics study in patients undergoing hip, knee and spine surgeries and found that blood levels of 3-aminoisobutyric acid were negatively correlated with pain control. Notably, 3- aminoisobutyric acid has been linked to PGC-1α, a key molecule modulating pain processing. Besides extensive experiences with -omics in pain, this investigator team has built a cutting-edge tool for functional assessment of pain aided by artificial intelligence. Leveraging machine learning algorithms, we have established a robust and reliable pipeline that can accurately identify and quantify a diverse set of real-life activities. This tool will be implemented to capture the global impact of pain and the progress of pain relief in free-living conditions. Built on existing data and our own research, we hypothesize that the gut microbiome is a mediator of inter-individual differences of lumbosacral radicular pain with or without back pain (LSRP), including its responsiveness to spinal surgery. We plan to recruit 250 LSRP patients (150 for Aim1&2; 100 for Aim 3) who undergo spine surgery and carry out three Aims: Aim 1: To deeply phenotype LSRP using shot-gun metagenomics, metabolomics, real-life activity based functional assessment, sleep and psychosocial questionnaires. Aim 2: To interrogate if the gut microbiome mediates the individual differences in LSRP. For this, we will follow up patients up to 12 months post spine surgery and determine their pain outcomes. Aim 3: To establish a model that integrates the microbiome, metabolome, and psychosocial features for LSRP inter-personal differences including its responsiveness to spine surgery. Additionally, we will enroll another cohort (100 patients) with LSRP who are scheduled for spine surgery with 12 months follow up postoperatively. This additional cohort will validate and refine the model to characterize inter-personal differences in pain. A successful execution of proposed studies will provide novel mechanistic understanding of individual differences in LSRP, facilitate patient stratification for spine surgery, and inform the development of evidence-based treatment towards precision and personalized pain medicine.
The profile of pain severity, impact, and persistence after (surgical) treatment is heterogeneous. For example, some patients with lumbosacral radicular pain, who do not respond to conservative therapies, eventually undergo spine surgeries. While many improve after surgery, some continue to suffer from back or leg pain, or develop new or worsened symptoms, leading to unfavorable outcomes. While the mechanisms underlying individual differences in pain including lumbosacral radicular pain are unknown, a large body of evidence suggests that genetic factors appear to explain only a small fraction of the individual variability in pain outcomes, suggesting significant contribution from other factors. The gut microbiome is a critical player in hosts’ physiology. Recently, important links between the gut microbiome and chronic pain have been elucidated, raising the question of whether the gut microbiome contributes mechanistically to the individual differences in lumbosacral radicular pain. In previous studies, we have established critical roles of the gut microbiome in neuropathic pain. More recently, we conducted a metabolomics study in patients undergoing hip, knee and spine surgeries and found that blood levels of 3-aminoisobutyric acid were negatively correlated with pain control. Notably, 3- aminoisobutyric acid has been linked to PGC-1, a key molecule modulating pain processing. Besides extensive experiences with -omics in pain, this investigator team has built a cutting-edge tool for functional assessment of pain aided by artificial intelligence. Leveraging machine learning algorithms, we have established a robust and reliable pipeline that can accurately identify and quantify a diverse set of real-life activities. This tool will be implemented to capture the global impact of pain and the progress of pain relief in free-living conditions. Built on existing data and our own research, we hypothesize that the gut microbiome is a mediator of inter-individual differences of lumbosacral radicular pain with or without back pain (LSRP), including its responsiveness to spinal surgery. We plan to recruit 250 LSRP patients (150 for Aim1&2; 100 for Aim 3) who undergo spine surgery and carry out three Aims: Aim 1: To deeply phenotype LSRP using shot-gun metagenomics, metabolomics, real-life activity based functional assessment, sleep and psychosocial questionnaires. Aim 2: To interrogate if the gut microbiome mediates the individual differences in LSRP. For this, we will follow up patients up to 12 months post spine surgery and determine their pain outcomes. Aim 3: To establish a model that integrates the microbiome, metabolome, and psychosocial features for LSRP inter-personal differences including its responsiveness to spine surgery. Additionally, we will enroll another cohort (100 patients) with LSRP who are scheduled for spine surgery with 12 months follow up postoperatively. This additional cohort will validate and refine the model to characterize inter-personal differences in pain. A successful execution of proposed studies will provide novel mechanistic understanding of individual differences in LSRP, facilitate patient stratification for spine surgery, and inform the development of evidence-based treatment towards precision and personalized pain medicine.
