Identification of traits and functional connectivity-based neurotraits of chronic pain

• Published in: PLoS biology Vol. 17; no. 8; p. e3000349
• Main Authors: Vachon-Presseau, Etienne, Berger, Sara E, Abdullah, Taha B, Griffith, James W, Schnitzer, Thomas J, Apkarian, A Vania
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 20-08-2019; Public Library of Science (PLoS)
• Subjects: Adult; Back pain; Biology and Life Sciences; Brain; Brain - physiology; Brain mapping; Brain Mapping - methods; Chronic pain; Chronic Pain - physiopathology; Chronic Pain - psychology; Cluster Analysis; Clustering; Computer and Information Sciences; Female; Fibromyalgia; Functional magnetic resonance imaging; Health aspects; Humans; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medicine; Medicine and Health Sciences; Middle Aged; Nerve Net - physiology; Neural networks; Neural Pathways - physiology; Neurobiology; Neuroimaging; Neurophysiology; NMR; Nuclear magnetic resonance; Pain; Personality; Physical Sciences; Physiology; Psychological aspects; Psychology; Questionnaires; Reproducibility of Results; Research and Analysis Methods; Rest; Risk factors; Social Sciences; Socioeconomic Factors; Socioeconomics; Studies; Surveys and Questionnaires; United States; United States > US; Illinois; Chicago Illinois
• ISSN: 1545-7885; 1544-9173; 1545-7885
• DOI: 10.1371/journal.pbio.3000349

Psychological and personality factors, socioeconomic status, and brain properties all contribute to chronic pain but have essentially been studied independently. Here, we administered a broad battery of questionnaires to patients with chronic back pain (CBP) and collected repeated sessions of resting-state functional magnetic resonance imaging (fMRI) brain scans. Clustering and network analyses applied on the questionnaire data revealed four orthogonal dimensions accounting for 56% of the variance and defining chronic pain traits. Two of these traits-Pain-trait and Emote-trait-were associated with back pain characteristics and could be related to distinct distributed functional networks in a cross-validation procedure, identifying neurotraits. These neurotraits showed good reliability across four fMRI sessions acquired over five weeks. Further, traits and neurotraits all related to the income, emphasizing the importance of socioeconomic status within the personality space of chronic pain. Our approach is a first step in providing metrics aimed at unifying the psychology and the neurophysiology of chronic pain applicable across diverse clinical conditions.