Osteoarthritis (OA) manifests with chronic pain, motor impairment, and proprioceptive changes. However, the role of the brain in the disease is largely unknown. Here, we studied brain networks using the mathematical properties of graphs in a large sample of knee and hip OA (KOA, n = 91; HOA, n = 23) patients. We used a robust validation strategy by subdividing the KOA data into discovery and testing groups and tested the generalizability of our findings in HOA. Despite brain global topological properties being conserved in OA, we show there is a network wide pattern of reorganization that can be captured at the subject‐level by a single measure, the hub disruption index. We localized reorganization patterns and uncovered a shift in the hierarchy of network hubs in OA: primary sensory and motor regions and parahippocampal gyrus behave as hubs and insular cortex loses its central placement. At an intermediate level of network structure, frontoparietal and cingulo‐opercular modules showed preferential reorganization. We examined the association between network properties and clinical correlates: global disruption indices and isolated degree properties did not reflect clinical parameters; however, by modeling whole brain nodal degree properties, we identified a distributed set of regions that reliably predicted pain intensity in KOA and generalized to hip OA. Together, our findings reveal that while conserving global topological properties, brain network architecture reorganizes in OA, at both global and local scale. Network connectivity related to OA pain intensity is dissociated from the major hub disruptions, challenging the extent of dependence of OA pain on nociceptive signaling.

BackgroundExercise alleviates pain and it is a central component of treatment strategy for chronic pain in clinical setting. However, little is known about mechanism of this exercise-induced hypoalgesia. The mesolimbic dopaminergic network plays a role in positive emotions to rewards including motivation and pleasure. Pain negatively modulates these emotions, but appropriate exercise is considered to activate the dopaminergic network. We investigated possible involvement of this network as a mechanism of exercise-induced hypoalgesia.MethodsIn the present study, we developed a protocol of treadmill exercise, which was able to recover pain threshold under partial sciatic nerve ligation in mice, and investigated involvement of the dopaminergic reward network in exercise-induced hypoalgesia. To temporally suppress a neural activation during exercise, a genetically modified inhibitory G-protein-coupled receptor, hM4Di, was specifically expressed on dopaminergic pathway from the ventral tegmental area to the nucleus accumbens.ResultsThe chemogenetic-specific neural suppression by Gi-DREADD system dramatically offset the effect of exercise-induced hypoalgesia in transgenic mice with hM4Di expressed on the ventral tegmental area dopamine neurons. Additionally, anti-exercise-induced hypoalgesia effect was significantly observed under the suppression of neurons projecting out of the ventral tegmental area to the nucleus accumbens as well.ConclusionOur findings suggest that the dopaminergic pathway from the ventral tegmental area to the nucleus accumbens is involved in the anti-nociception under low-intensity exercise under a neuropathic pain-like state.

Brain functional network properties are globally disrupted in multiple musculoskeletal chronic pain conditions. Back pain with lumbar disk herniation (LDH) is highly prevalent and a major route for progression to chronic back pain. However, brain functional network properties remain unknown in such patients. Here, we examined resting-state functional magnetic resonance imaging-based functional connectivity networks in chronic back pain patients with clear evidence for LDH (LDH-chronic pain n = 146), in comparison to healthy controls (HCs, n = 165). The study was conducted in China, thus providing the opportunity to also examine the influence of culture on brain functional reorganization with chronic pain. The data were equally subdivided into discovery and validation subgroups (n = 68 LDH-chronic pain and n = 68 HC, for each subgroup), and contrasted to an off-site data set (n = 272, NITRC 1000). Graph disruption indices derived from 3 network topological measurements, degree, clustering coefficient, and efficiency, which respectively represent network hubness, segregation, and integration, were significantly decreased compared with HC, across all predefined link densities, in both discovery and validation groups. However, global mean clustering coefficient and betweenness centrality were decreased in the discovery group and showed trend in the validation group. The relationship between pain and graph disruption indices was limited to males with high education. These results deviate somewhat from recent similar analysis for other musculoskeletal chronic pain conditions, yet we cannot determine whether the differences are due to types of pain or also to cultural differences between patients studied in China and the United States.