Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures

• Type of Material: Article
• Authors: Kathleen A. Sluka, University of Iowa; Tor D. Wager, Dartmouth College; Stephani P. Sutherland, Johns Hopkins University; Patricia A. Labosky, National Institutes of Health; Tessa Balach, University of Chicago; Emine O. Bayman, University of Iowa; Giovanni Berardi, University of Iowa; Chad M. Brummett, University of Michigan; John Burns, Rush Medical College; Asokumar Buvanendran, Rush Medical College; Brian Caffo, Johns Hopkins University; Vince Calhoun, Emory University; Daniel Clauw, University of Michigan; Andrew Chang, University of Michigan; Christopher S. Coffey, University of Iowa; Dana L. Dailey, University of Iowa; Dixie Ecklund, University of Iowa; Oliver Fiehn, University of California Davis; Kathleen M. Fisch, University of California San Diego; Laura A. Frey Law, University of Iowa; Richard E. Harris, University of Michigan; Steven E. Harte, University of Michigan; Timothy D. Howard, Wake Forest University; Joshua Jacobs, Rush Medical College; Jon M. Jacobs, Pacific Northwest National Laboratory; Kristen Jepsen, Institute for Genomic Medicine Genomics Center; Nicolas Johnston, National Institute on Drug Abuse; Carl D. Langefeld, Wake Forest University; Louise C. Laurent, University of California San Diego; Rebecca Lenzi, National Institutes of Health; Martin A. Lindquist, Johns Hopkins University; Anna Lokshin, Hillman Cancer Center; Ari Kahn, University of Texas Austin; Robert J. McCarthy, Rush Medical College; Michael Olivier, Wake Forest University; Linda Porter, National Institute of Neurological Disorders and Stroke; Wei-Jun Qian, Pacific Northwest National Laboratory; Cheryse A. Sankar, National Institute of Neurological Disorders and Stroke; John Satterlee, National Institute on Drug Abuse; Adam C. Swensen, Pacific Northwest National Laboratory; Carol G. T. Vance, University of Iowa; Jennifer Waljee, University of Michigan; Laura D. Wandner, National Institute of Neurological Disorders and Stroke; David A. Williams, University of Michigan; Richard L. Wixson, NorthShore Orthopaedic and Spine Institute; Xiaohong Joe Zhou, University of Illinois
• Language: English
• Date: 2023-09-01
• Publisher: LIPPINCOTT WILLIAMS & WILKINS
• Publication Version: Final Published Version
• Copyright Statement: © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1097/j.pain.0000000000002938
• Title of Journal or Parent Work: PAIN
• Volume: 164
• Issue: 9
• Start Page: 1912
• End Page: 1926
• Grant/Funding Information: The A2CPS Consortium is supported by the National Institutes of Health Common Fund, which is managed by the Office of the Director/Office of Strategic Coordination (OSC). Consortium components include Clinical Coordinating Center (U01NS077179), Data Integration and Resource Center (U01NS077352), Omics Data Generation Centers (U54DA049116, U54DA049115, U54DA09113), Multisite Clinical Center 1 (UM1NS112874), and Multisite Clinical Center 2 (UM1NS118922).
• Keywords: Neurosciences; RISK-ASSESSMENT; TEMPORAL SUMMATION; Science & Technology; LOW-BACK-PAIN; Omics; Biosignatures; PELVIC PAIN; PREOPERATIVE PAIN; Chronic pain; Neurosciences & Neurology; Psychosocial; Anesthesiology; Brain imaging; Pain; Clinical Neurology; ASSOCIATION; TRANSITION; Life Sciences & Biomedicine; TOTAL KNEE; Biomarker; CHRONIC POSTOPERATIVE PAIN; Postsurgical pain; ADVERSE CHILDHOOD EXPERIENCES
• Research Categories: Psychology, Psychobiology; Biology, Neuroscience

Abstract

Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.