Pain is a subjective, multifaceted experience that varies substantially between and within chronic pain patients and is characterized by somatosensory, affective, and cognitive components. However, whether high day-to-day fluctuation amplitude (“hope for change”) or low amplitude/consistent pain experience (“know what to expect”) contributes to better or worse therapeutic outcomes is an ongoing debate. In this longitudinal MRI study involving an 8-week cognitive behavioral therapy (CBT) intervention in Fibromyalgia patients (N=61, all female, age (SD) = 41.27 (12.54) years), the impact of baseline daily reported pain fluctuations, i.e., standard deviation, on brain responses to nociceptive stimuli and clinical outcomes were investigated. Patients either received CBT or a duration-matched education-control (EDU). Preceding the intervention, patients underwent an evoked pressure pain paradigm during whole-brain fMRI (Siemens 3T-MRI, TR/TE=1250/33ms, voxel size 2mm3 isotropic, SMS MB acc. factor 5). Thetask included six leg cuff stimulations of either non- or moderately painful pressures (calibrated to individual’s threshold). Clinical outcomes were assessed using the Pain Catastrophizing Scale (PCS), a specific target of CBT. Greater baseline day-to-day clinical pain fluctuations were associated with greater post-therapy improvement in pain catastrophizing in the CBT but not the EDU group. Furthermore, greater day-to-day clinical pain fluctuations were negatively correlated with BOLD-fMRI responses during pain anticipation in nociceptive processing areas (i.e., primary-somatosensory-cortex, insula, and superior-parietal-lobule). The results suggest that greater clinical pain fluctuations may boost clinical treatment effects by influencing anticipation of pain. Importantly, this study highlights the predictive importance of clinical pain variability in longitudinal interventional research involving chronic pain populations. Funding: R01-AT-007550, R33-AT-009306, P01-AT-009965, R01-AR-064367, R01-AR-079110, P41-RR-14075, S10-RR-021110, S10-RR-023043, R01-AT-012144.

Abstract Pain catastrophizing is prominent in chronic pain conditions such as fibromyalgia and has been proposed to contribute to the development of pain widespreadness. However, the brain mechanisms responsible for this association are unknown. We hypothesized that increased resting salience network (SLN) connectivity to nodes of the default mode network (DMN), representing previously reported pain-linked cross-network enmeshment, would be associated with increased pain catastrophizing and widespreadness across body sites. We applied functional magnetic resonance imaging (fMRI) and digital pain drawings (free-hand drawing over a body outline, analyzed using conventional software for multivoxel fMRI analysis) to investigate precisely quantified measures of pain widespreadness and the associations between pain catastrophizing (Pain Catastrophizing Scale), resting brain network connectivity (Dual-regression Independent Component Analysis, 6-minute multiband accelerated fMRI), and pain widespreadness in fibromyalgia patients (N = 79). Fibromyalgia patients reported pain in multiple body areas (most frequently the spinal region, from the lower back to the neck), with moderately high pain widespreadness (mean ± SD: 26.1 ± 24.1% of total body area), and high pain catastrophizing scale scores (27.0 ± 21.9, scale range: 0-52), which were positively correlated (r = 0.26, P = 0.02). A whole-brain regression analysis focused on SLN connectivity indicated that pain widespreadness was also positively associated with SLN connectivity to the posterior cingulate cortex, a key node of the DMN. Moreover, we found that SLN-posterior cingulate cortex connectivity statistically mediated the association between pain catastrophizing and pain widespreadness (P = 0.01). In conclusion, we identified a putative brain mechanism underpinning the association between greater pain catastrophizing and a larger spatial extent of body pain in fibromyalgia, implicating a role for brain SLN-DMN cross-network enmeshment in mediating this association.

BACKGROUND:Fibromyalgia is a centralized multidimensional chronic pain syndrome, but its pathophysiology is not fully understood.METHODS:We applied 3D magnetic resonance spectroscopic imaging (MRSI), covering multiple cortical and subcortical brain regions, to investigate the association between neuro-metabolite (e.g. combined glutamate and glutamine, Glx; myo-inositol, mIno; and combined (total) N-acetylaspartate and N-acetylaspartylglutamate, tNAA) levels and multidimensional clinical/behavioural variables (e.g. pain catastrophizing, clinical pain severity and evoked pain sensitivity) in women with fibromyalgia (N = 87).RESULTS:Pain catastrophizing scores were positively correlated with Glx and tNAA levels in insular cortex, and negatively correlated with mIno levels in posterior cingulate cortex (PCC). Clinical pain severity was positively correlated with Glx levels in insula and PCC, and with tNAA levels in anterior midcingulate cortex (aMCC), but negatively correlated with mIno levels in aMCC and thalamus. Evoked pain sensitivity was negatively correlated with levels of tNAA in insular cortex, MCC, PCC and thalamus.CONCLUSIONS:These findings support single voxel placement targeting nociceptive processing areas in prior 1 H-MRS studies, but also highlight other areas not as commonly targeted, such as PCC, as important for chronic pain pathophysiology. Identifying target brain regions linked to multidimensional symptoms of fibromyalgia (e.g. negative cognitive/affective response to pain, clinical pain, evoked pain sensitivity) may aid the development of neuromodulatory and individualized therapies. Furthermore, efficient multi-region sampling with 3D MRSI could reduce the burden of lengthy scan time for clinical research applications of molecular brain-based mechanisms supporting multidimensional aspects of fibromyalgia.SIGNIFICANCE:This large N study linked brain metabolites and pain features in fibromyalgia patients, with a better spatial resolution and brain coverage, to understand a molecular mechanism underlying pain catastrophizing and other aspects of pain transmission. Metabolite levels in self-referential cognitive processing area as well as pain-processing regions were associated with pain outcomes. These results could help the understanding of its pathophysiology and treatment strategies for clinicians.

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. 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.