Large‐Scale Plasma Proteomics to Profile Pathways and Prognosis of Chronic Pain

While increasing peripheral mechanisms related to chronic pain, the plasma proteomics profile associated with it and its prognosis remains elusive. This study utilizes 2923 plasma proteins and chronic pain of 51 644 participants from UK Biobank and finds 474 proteins linked to chronic pain in six sites: head, neck or shoulder, back, stomach or abdominal, hip, and knee, with 11 proteins sharing across pain sites. The identified proteins are largely enriched in immune and metabolic pathways and highly expressed in tissues like lungs and small intestines. Phenome-wide analysis highlights the significance of pain-related proteome on diverse facets of human health, and in-depth Mendelian randomization validates 10 proteins (CD302, RARRES2, TNFRSF1B, BTN2A1, TNFRSF9, COL18A1, TNF, CD74, TNFRSF4, and BTN2A1) as markers of chronic pain. Furthermore, protein sets capable of classifying pain patients and healthy participants, particularly performing best in hip pain (area under curve, AUC = 0.725), are identified. Interestingly, the prediction of pain spreading over ten years achieves an AUC of 0.715, with leptin identified as a crucial predictor. This study delineates proteins associated with various pain conditions and identifies proteins capable of classifying pain and predicting pain spreading, offering benefits for both research and clinical practice.

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Publication Details

Journal
Advanced Science
Published
2025-03-06
DOI
https://doi.org/10.1002/advs.202410160
Citations
1
Primary Topic
Fibromyalgia and Chronic Fatigue Syndrome Research
Type
article
Field-Weighted Citation Impact
1.47

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article

Large‐Scale Plasma Proteomics to Profile Pathways and Prognosis of Chronic Pain

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1 citations
Advanced Science
Fibromyalgia and Chronic Fatigue Syndrome Research
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article

Large‐Scale Plasma Proteomics to Profile Pathways and Prognosis of Chronic Pain

Qinggang Hao, Jianfeng Feng, Jujiao Kang, Wei Cheng, Yue‐Ting Deng, Qing Ma, Jia You, Zeyu Li, Linbo Wang, Yiheng Tu, Xinrui Wu, Bang‐Sheng Wu, Xiao Xiao, Yuzhu Li, Rong Yin, Chun Shen, Jin‐Tai Yu, Jie Zhang
article en
1 citations

Abstract

While increasing peripheral mechanisms related to chronic pain, the plasma proteomics profile associated with it and its prognosis remains elusive. This study utilizes 2923 plasma proteins and chronic pain of 51 644 participants from UK Biobank and finds 474 proteins linked to chronic pain in six sites: head, neck or shoulder, back, stomach or abdominal, hip, and knee, with 11 proteins sharing across pain sites. The identified proteins are largely enriched in immune and metabolic pathways and highly expressed in tissues like lungs and small intestines. Phenome-wide analysis highlights the significance of pain-related proteome on diverse facets of human health, and in-depth Mendelian randomization validates 10 proteins (CD302, RARRES2, TNFRSF1B, BTN2A1, TNFRSF9, COL18A1, TNF, CD74, TNFRSF4, and BTN2A1) as markers of chronic pain. Furthermore, protein sets capable of classifying pain patients and healthy participants, particularly performing best in hip pain (area under curve, AUC = 0.725), are identified. Interestingly, the prediction of pain spreading over ten years achieves an AUC of 0.715, with leptin identified as a crucial predictor. This study delineates proteins associated with various pain conditions and identifies proteins capable of classifying pain and predicting pain spreading, offering benefits for both research and clinical practice.

Advanced ScienceVol. 12(16)
Zhejiang Normal University (CN), Fudan University (CN), University of Warwick (GB), Institute of Psychology, Chinese Academy of Sciences (CN), Huashan Hospital (CN), Shanghai Center for Brain Science and Brain-Inspired Technology (CN), East China Normal University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Program of Shanghai Academic Research Leader
Good health and well-being
Openalex Percentile: Top 22%
Fibromyalgia and Chronic Fatigue Syndrome Research
1.47
DOIOpen Access PDFOpenAlex
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