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Magnetic resonance imaging of neuroinflammation in chronic pain: a role for astrogliosis?

ABSTRACT: Noninvasive measures of neuroinflammatory processes in humans could substantially aid diagnosis and therapeutic development for many disorders, including chronic pain. Several proton magnetic resonance spectroscopy (H-MRS) metabolites have been linked with glial activity (ie, choline and myo-inositol) and found to be altered in chronic pain patients, but their role in the neuroinflammatory cascade is not well known. Our multimodal study evaluated resting functional magnetic resonance imaging connectivity and H-MRS metabolite concentration in insula cortex in 43 patients suffering from fibromyalgia, a chronic centralized pain disorder previously demonstrated to include a neuroinflammatory component, and 16 healthy controls. Patients demonstrated elevated choline (but not myo-inositol) in anterior insula (aIns) (P = 0.03), with greater choline levels linked with worse pain interference (r = 0.41, P = 0.01). In addition, reduced resting functional connectivity between aIns and putamen was associated with both pain interference (whole brain analysis, pcorrected < 0.01) and elevated aIns choline (r = -0.37, P = 0.03). In fact, aIns/putamen connectivity statistically mediated the link between aIns choline and pain interference (P < 0.01), highlighting the pathway by which neuroinflammation can impact clinical pain dysfunction. To further elucidate the molecular substrates of the effects observed, we investigated how putative neuroinflammatory H-MRS metabolites are linked with ex vivo tissue inflammatory markers in a nonhuman primate model of neuroinflammation. Results demonstrated that cortical choline levels were correlated with glial fibrillary acidic protein, a known marker for astrogliosis (Spearman r = 0.49, P = 0.03). Choline, a putative neuroinflammatory H-MRS-assessed metabolite elevated in fibromyalgia and associated with pain interference, may be linked with astrogliosis in these patients.

SUBMITTER: Jung C

PROVIDER: S-EPMC7305954 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The International Classification of Headache Disorders provides criteria for the diagnosis and subclassification of migraine. Since there is no objective gold standard by which to test these diagnostic criteria, the criteria are based on the consensus opinion of content experts. Accurate migraine classifiers consisting of brain structural measures could serve as an objective gold standard by which to test and revise diagnostic criteria. The objectives of this study were to utilize magnetic resonance imaging measures of brain structure for constructing classifiers: (1) that accurately identify individuals as having chronic vs episodic migraine vs being a healthy control; and (2) that test the currently used threshold of 15 headache days/month for differentiating chronic migraine from episodic migraine.Study participants underwent magnetic resonance imaging for determination of regional cortical thickness, cortical surface area, and volume. Principal components analysis combined structural measurements into principal components accounting for 85% of variability in brain structure. Models consisting of these principal components were developed to achieve the classification objectives. Tenfold cross validation assessed classification accuracy within each of the 10 runs, with data from 90% of participants randomly selected for classifier development and data from the remaining 10% of participants used to test classification performance. Headache frequency thresholds ranging from 5-15 headache days/month were evaluated to determine the threshold allowing for the most accurate subclassification of individuals into lower and higher frequency subgroups.Participants were 66 migraineurs and 54 healthy controls, 75.8% female, with an average age of 36?+/-?11 years. Average classifier accuracies were: (1) 68% for migraine (episodic?+?chronic) vs. healthy controls; (2) 67.2% for episodic migraine vs healthy controls; (3) 86.3% for chronic migraine vs. healthy controls; and (4) 84.2% for chronic migraine vs episodic migraine. The classifiers contained principal components consisting of several structural measures, commonly including the temporal pole, anterior cingulate cortex, superior temporal lobe, entorhinal cortex, medial orbital frontal gyrus, and pars triangularis. A threshold of 15 headache days/month allowed for the most accurate subclassification of migraineurs into lower frequency and higher frequency subgroups.Classifiers consisting of cortical surface area, cortical thickness, and regional volumes were highly accurate for determining if individuals have chronic migraine. Furthermore, results provide objective support for the current use of 15 headache days/month as a threshold for dividing migraineurs into lower frequency (i.e., episodic migraine) and higher frequency (i.e., chronic migraine) subgroups.

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Magnetic resonance imaging of neuroinflammation in chronic pain: a role for astrogliosis?

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