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Brain metabolite concentration in pain processing regions is linked with multidimensional morbidity in fibromyalgia - a voxel-wise 3D MR Spectroscopic Imaging study

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      Fibromyalgia is a multidimensional chronic pain syndrome. It is thought to result mainly from central nervous system dysfunction, but its working mechanism is not fully understood. In this study, we applied multi-slice magnetic resonance spectroscopy imaging (MRSI) to investigate the relationship between brain metabolite (e.g., combined glutamate and glutamine, Glx; myo-inositol, mIno; and combined N-acetylaspartate and N-acetylaspartylglutamate; tNAA) levels and the severity of multidimensional clinical/behavioral metrics (e.g., pain catastrophizing, clinical pain severity, and evoked pain sensitivity) in fibromyalgia patients (N=87). Fibromyalgia patients showed greater pain catastrophizing and hyperalgesia compared with age-matched healthy controls (N=40). In fibromyalgia patients, pain catastrophizing scale scores were positively correlated with Glx and tNAA levels in the insular cortex, and were negatively correlated with mIno levels in the posterior cingulate cortex (PCC). Clinical pain severity showed positive correlations with Glx levels in the insular and PCC, and with tNAA levels in the anterior middle cingulate cortex (aMCC), but negatively with mIno levels in the aMCC and thalamus. The level of tNAA in the insular cortex, MCC, PCC, and thalamus, were negatively correlated with evoked pain sensitivity. These results highlight the utility of MRSI in the understanding of molecular mechanisms underlying multidimensional aspects of fibromyalgia. This work was supported by the NIH (National Institute of Arthritis and Musculoskeletal and Skin Diseases grant R01-AR064367, National Center for Complementary and Integrative Health grants R01-AT007550, R61-AT009306, and P01-AT AT009965, and National Center for Research Resources grants P41-RR14075, S10-RR021110, and S10-RR023043). Development of MRSI pulse sequence and processing was funded by NIH/NCI grants K22CA178269 and R01CA211080.
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