Tracking Pain in Resting State Networks in Patients with Hereditary and Diabetic Neuropathy.

Abstract

Introduction\nChronic pain is associated with maladaptive plastic changes in the brain. It is usually more prominent in acquired pathologies of nerve fibers as in diabetic neuropathy despite less severe degeneration than hereditary neuropathies. Based on clinical differences concerning pain perception, we hypothesized that functional connectivity analysis would reveal distinct patterns in resting-state networks in these groups.\n\n\nMethods\nTen diabetic patients with painful neuropathy (5F/5M; mean age=50.10±6.05 years), 10 patients with hereditary neuropathy (5F/5M; mean age=37.80±14.01 years), 18 age-and gender-matched healthy controls (eight for painful diabetic neuropathy and 10 for hereditary neuropathy) and seven diabetic controls without painful neuropathy were enrolled in the study. All subjects (n=45) underwent a 5-min resting-state scan in a 3T magnetic resonance scanner. The images were analyzed with seed-based functional connectivity method. The group-level maps of the default mode network and insula-cingulate network were identified for each group.\n\n\nResults\nPatients with hereditary neuropathy displayed increased connectivity between left insula and left anterior cingulate cortex and inversely correlated activity between left insula and left inferior parietal lobule compared to their controls. In patients with painful diabetic neuropathy, the major findings were the increased connectivity between left anterior cingulate cortex and posterior cingulate cortex/precuneus, and the increased connectivity between medial prefrontal cortex and left medial temporal region compared to their controls.\n\n\nConclusion\nThis study revealed that hereditary and diabetic painful neuropathy patients exhibit different patterns of functional connectivity. The clinical differences in these groups regarding the presence of neuropathic pain may relate to this difference in cortical organization.