Journal article
Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures
Pain (Amsterdam), Vol.164(9), pp.1912-1926
09/2023
DOI: 10.1097/j.pain.0000000000002938
PMCID: PMC10436361
PMID: 37326643
Abstract
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 generated by 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.
Details
- Title: Subtitle
- Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures
- Creators
- Kathleen A Sluka - University of IowaTor D Wager - Dartmouth CollegeStephani P Sutherland - Johns Hopkins UniversityPatricia A Labosky - Division of Program Coordination Planning and Strategic InitiativesTessa Balach - University of ChicagoEmine O Bayman - University of IowaGiovanni Berardi - University of IowaChad M Brummett - University of MichiganJohn Burns - Rush University Medical CenterAsokumar Buvanendran - Rush University Medical CenterBrian Caffo - Johns Hopkins UniversityVince D Calhoun - Center for Translational Research in Neuroimaging and Data ScienceDaniel Clauw - University of MichiganAndrew Chang - University of MichiganChristopher S Coffey - University of IowaDana L Dailey - University of IowaDixie Ecklund - University of IowaOliver Fiehn - University of California, DavisKathleen M Fisch - University of California San DiegoLaura A Frey LawRichard E Harris - University of MichiganSteven E Harte - University of MichiganTimothy D Howard - Wake Forest UniversityJoshua Jacobs - Department of Orthopedic Surgery, Rush Medical College, CHicago, ILJon M Jacobs - Pacific Northwest National LaboratoryKristen Jepsen - Center for Genomic ScienceNicolas Johnston - National Institute on Drug AbuseCarl D Langefeld - Wake Forest UniversityLouise C Laurent - University of California San DiegoRebecca Lenzi - Division of Program Coordination Planning and Strategic InitiativesMartin A Lindquist - Johns Hopkins UniversityAnna Lokshin - UPMC Hillman Cancer CenterAri Kahn - Computing CenterRobert J McCarthy - Rush University Medical CenterMichael Olivier - Wake Forest UniversityLinda Porter - National Institute of Neurological Disorders and StrokeWei-Jun Qian - Pacific Northwest National LaboratoryCheryse A Sankar - National Institute of Neurological Disorders and StrokeJohn Satterlee - National Institute on Drug AbuseAdam C Swensen - Pacific Northwest National LaboratoryCarol G T Vance - University of IowaJennifer Waljee - University of MichiganLaura D Wandner - National Institute of Neurological Disorders and StrokeDavid A Williams - University of MichiganRichard L Wixson - The Spine InstituteXiaohong Joe Zhou - University of Illinois Chicago
- Resource Type
- Journal article
- Publication Details
- Pain (Amsterdam), Vol.164(9), pp.1912-1926
- DOI
- 10.1097/j.pain.0000000000002938
- PMID
- 37326643
- PMCID
- PMC10436361
- NLM abbreviation
- Pain
- ISSN
- 0304-3959
- eISSN
- 1872-6623
- Language
- English
- Electronic publication date
- 06/15/2023
- Date published
- 09/2023
- Academic Unit
- Iowa Neuroscience Institute; Biostatistics; Nursing; Anesthesia; Physical Therapy and Rehabilitation Science; Neuroscience and Pharmacology
- Record Identifier
- 9984436459702771
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