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Patients with fibromyalgia display less functional connectivity in the brain's pain inhibitory network.

ABSTRACT: BACKGROUND:There is evidence for augmented processing of pain and impaired endogenous pain inhibition in Fibromyalgia syndrome (FM). In order to fully understand the mechanisms involved in FM pathology, there is a need for closer investigation of endogenous pain modulation. In the present study, we compared the functional connectivity of the descending pain inhibitory network in age-matched FM patients and healthy controls (HC).We performed functional magnetic resonance imaging (fMRI) in 42 subjects; 14 healthy and 28 age-matched FM patients (2 patients per HC), during randomly presented, subjectively calibrated pressure pain stimuli. A seed-based functional connectivity analysis of brain activity was performed. The seed coordinates were based on the findings from our previous study, comparing the fMRI signal during calibrated pressure pain in FM and HC: the rostral anterior cingulate cortex (rACC) and thalamus. RESULTS:FM patients required significantly less pressure (kPa) to reach calibrated pain at 50?mm on a 0-100 visual analogue scale (p?

SUBMITTER: Jensen KB

PROVIDER: S-EPMC3404927 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Patients with fibromyalgia display less functional connectivity in the brain's pain inhibitory network.

Jensen Karin B KB Loitoile Rita R Kosek Eva E Petzke Frank F Carville Serena S Fransson Peter P Marcus Hanke H Williams Steven C R SC Choy Ernest E Mainguy Yves Y Vitton Olivier O Gracely Richard H RH Gollub Randy R Ingvar Martin M Kong Jian J

Molecular pain 20120426

<h4>Background</h4>There is evidence for augmented processing of pain and impaired endogenous pain inhibition in Fibromyalgia syndrome (FM). In order to fully understand the mechanisms involved in FM pathology, there is a need for closer investigation of endogenous pain modulation. In the present study, we compared the functional connectivity of the descending pain inhibitory network in age-matched FM patients and healthy controls (HC).We performed functional magnetic resonance imaging (fMRI) in ...[more]

PMID: 22537768

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Project description:BACKGROUND:The control of food intake in environments with easy access to highly rewarding foods is challenging to most modern societies. The combination of sustained release (SR) naltrexone and SR bupropion (NB32) has been used in weight-loss and obesity management. However, the effects of NB32 on the brain circuits implicated in the regulation of food intake are unknown. Here we used functional connectivity density (FCD) mapping to evaluate the effects of NB32 on resting brain FC. METHODS:Thirty-six healthy women underwent magnetic resonance imaging (MRI) before and after 4-week treatment with NB32 (n?=?16) or with placebo (n?=?20). In each imaging visit, a 5-min resting-state functional MRI scan was conducted after 15?h of fasting. The FC of brain regions showing significant group effects on FCD were subsequently assessed using seed-voxel correlation analyses. We characterized the associations between FCD measures and craving control scores in the Control of Eating Questionnaire. RESULTS:After NB32 treatment, the group showed lower local and global FCD than the placebo group in the right superior parietal cortex and lower local FCD in the left middle frontal gyrus. Seed-voxel correlation analysis for the right superior parietal cortex seed demonstrated higher positive FC with the dorsal anterior cingulate gyrus (ACC), bilateral insula, and left superior parietal gyrus and stronger negative FC with right inferior frontal gyrus and right superior parietal cortices for the NB32 than the placebo group. Further, the NB32 group showed a significant correlation between local FCD change after treatment in left middle frontal gyrus and craving control scores (r?=?0.519, p?=?0.039). CONCLUSIONS:NB32 treatment decreased local and global FCD in superior parietal cortex and increased its connectivity with ACC (involved with saliency attribution), insula (interoception), and decreased local FCD in the medial prefrontal cortex (craving), which might underlie NB32 improved control over eating behaviors. ClinicalTrails.gov: NCT00711.

Project description:Aims/hypothesisThe aim of this work was to investigate whether different clinical pain phenotypes of diabetic polyneuropathy (DPN) are distinguished by functional connectivity at rest.MethodsThis was an observational, cohort study of 43 individuals with painful DPN, divided into irritable (IR, n = 10) and non-irritable (NIR, n = 33) nociceptor phenotypes using the German Research Network of Neuropathic Pain quantitative sensory testing protocol. In-situ brain MRI included 3D T1-weighted anatomical and 6 min resting-state functional MRI scans. Subgroup differences in resting-state functional connectivity in brain regions involved with somatic (thalamus, primary somatosensory cortex, motor cortex) and non-somatic (insular and anterior cingulate cortices) pain processing were examined. Multidimensional reduction of MRI datasets was performed using a machine-learning approach to classify individuals into each clinical pain phenotype.ResultsIndividuals with the IR nociceptor phenotype had significantly greater thalamic-insular cortex (p false discovery rate [FDR] = 0.03) and reduced thalamus-somatosensory cortex functional connectivity (p-FDR = 0.03). We observed a double dissociation such that self-reported neuropathic pain score was more associated with greater thalamus-insular cortex functional connectivity (r = 0.41; p = 0.01) whereas more severe nerve function deficits were more related to lower thalamus-somatosensory cortex functional connectivity (r = -0.35; p = 0.03). Machine-learning group classification performance to identify individuals with the NIR nociceptor phenotype achieved an accuracy of 0.92 (95% CI 0.08) and sensitivity of 90%.Conclusions/interpretationThis study demonstrates differences in functional connectivity in nociceptive processing brain regions between IR and NIR phenotypes in painful DPN. We also establish proof of concept for the utility of multimodal MRI as a biomarker for painful DPN by using a machine-learning approach to classify individuals into sensory phenotypes.

Dataset Information

Patients with fibromyalgia display less functional connectivity in the brain's pain inhibitory network.

Publications

Patients with fibromyalgia display less functional connectivity in the brain's pain inhibitory network.

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