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

Author:

Sluka Kathleen A.1ORCID,Wager Tor D.2,Sutherland Stephani P.3,Labosky Patricia A.4,Balach Tessa5,Bayman Emine O.6,Berardi Giovanni1,Brummett Chad M.7,Burns John8,Buvanendran Asokumar9,Caffo Brian3,Calhoun Vince D.10,Clauw Daniel7,Chang Andrew11,Coffey Christopher S.6,Dailey Dana L.1,Ecklund Dixie6,Fiehn Oliver12,Fisch Kathleen M.1314,Frey Law Laura A.1,Harris Richard E.7,Harte Steven E.7,Howard Timothy D.1516,Jacobs Joshua17,Jacobs Jon M.18,Jepsen Kristen19,Johnston Nicolas20,Langefeld Carl D.1621,Laurent Louise C.13,Lenzi Rebecca4,Lindquist Martin A.3,Lokshin Anna22,Kahn Ari23,McCarthy Robert J.9,Olivier Michael1624,Porter Linda2526,Qian Wei-Jun18,Sankar Cheryse A.25,Satterlee John20,Swensen Adam C.18,Vance Carol G.T.1,Waljee Jennifer11,Wandner Laura D.25,Williams David A.7,Wixson Richard L.27,Zhou Xiaohong Joe28,

Affiliation:

1. Department of Physical Therapy and Rehabilitation Science, Carver College of Medicine, University of Iowa, Iowa City, IA

2. Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH

3. Department of Biostatistics, Johns Hopkins Bloomberg Schools of Public Health, Baltimore, MD

4. Office of Strategic Coordination, Division of Program Coordination, Planning and Strategic Initiatives, Office of the Director, National Institutes of Health, Bethesda, MD

5. Department of Orthopaedic Surgery and Rehabilitation Medicine, The University of Chicago, Chicago, IL

6. Clinical Trials and Data Management Center, Department of Biostatistics, University of Iowa, Iowa City, IA

7. Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI

8. Division of Behavioral Sciences, Rush Medical College, Chicago, IL

9. Department of Anesthesiology, Rush Medical College, Chicago, IL

10. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA,

11. Department of Surgery, University of Michigan Medical School, Ann Arbor, MI

12. University of California, Davis, Davis, CA, United States

13. Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Diego, San Diego, CA, United States

14. Center for Computational Biology and Bioinformatics, University of California San Diego, San Diego, CA, United States

15. Department of Biochemistry, Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC

16. Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC

17. Department of Orthopedic Surgery, Rush Medical College, CHicago, IL

18. Environmental and Molecular Sciences Laboratory, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA,

19. Institute for Genomic Medicine Genomics Center

20. National Institute on Drug Abuse, Bethesda, MD

21. Department of Biostatistics and Data Science, Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC

22. Hillman Cancer Center

23. Texas Advanced Computing Center, University of Texas, AUstin, TX

24. Department of Internal Medicine, Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC

25. National Institute of Neurological Disorders and Stroke, Bethesda, MD

26. Office of Pain Policy and Planning National Institutes of Health, Bethesda, MD

27. NorthShore Orthopaedic and Spine Institute, CHicago, IL

28. Center for MR Research and Departments of Radiology, Neurosurgery, and Bioengineering, University of Illinois College of Medicine at Chicago, Chicago, IL, United States

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 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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Anesthesiology and Pain Medicine,Neurology (clinical),Neurology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3