Skip to main content

Research Repository

Advanced Search

Serum Metabolome Analysis Identified Amino-Acid Metabolism Associated With Pain in People With Symptomatic Knee Osteoarthritis – A Cross-Sectional Study

Mehta, Ojasvi; Vijay, Amrita; Gohir, Sameer Akram; Kelly, Tony; Zhang, Weiya; Doherty, Michael; Walsh, David A.; Aithal, Guruprasad; Valdes, Ana. M.

Serum Metabolome Analysis Identified Amino-Acid Metabolism Associated With Pain in People With Symptomatic Knee Osteoarthritis – A Cross-Sectional Study Thumbnail


Authors

Ojasvi Mehta

Sameer Akram Gohir

TONY KELLY Tony.Kelly@nottingham.ac.uk
Research Fellow

Michael Doherty

DAVID WALSH david.walsh@nottingham.ac.uk
Professor of Rheumatology



Abstract

Osteoarthritis (OA) is the most common arthritis affecting synovial joints such as knees and hips of millions of people globally. Usage-related joint pain and reduced function are the most common symptoms experienced by people with OA. To improve pain management, there is a need to identify validated biomarkers predicting therapeutic responses in targeted clinical trials. Our study aimed to identify the metabolic biomarkers for pain and pressure pain detection thresholds (PPTs) in participants with knee pain and symptomatic OA using metabolic phenotyping. Metabolite and cytokine measurements were done on serum samples using LC-MS/MS (liquid gas chromatography integrated magnetic resonance mass spectrometry) and Human Proinflammatory panel 1 kit respectively. Regression analysis was done in a test (n = 75) and replication study (n = 79) to investigate the metabolites associated with current knee pain scores and pressure pain detection thresholds (PPTs). Meta-analysis and correlation were done estimating precision of associated metabolites and identifying relationship between significant metabolites and cytokines respectively. Acyl ornithine, carnosine, cortisol, cortisone, cystine, DOPA, glycolithocholic acid sulphate (GLCAS), phenylethylamine (PEA) and succinic acid were found to be significantly (FDR <.1) associated with pain scores in meta-analysis of both studies. IL-10, IL-13, IL-1β, IL2, IL8 and TNF-α were also found to be associated with the significant metabolites. Significant associations of these metabolites and inflammatory markers with knee pain suggests that targeting relevant pathways of amino acid and cholesterol metabolism may modulate cytokines and these could be targeted as novel therapeutics development to improve knee pain and OA management. Perspective: Foreseeing the global burden of knee pain in Osteoarthritis (OA) and adverse effects of current pharmacological therapies, this study is envisaged to investigate serum metabolites and molecular pathways involved in knee pain. The replicated metabolites in this study suggests targeting amino-acid pathways for better management of OA knee pain.

Citation

Mehta, O., Vijay, A., Gohir, S. A., Kelly, T., Zhang, W., Doherty, M., …Valdes, A. M. (2023). Serum Metabolome Analysis Identified Amino-Acid Metabolism Associated With Pain in People With Symptomatic Knee Osteoarthritis – A Cross-Sectional Study. Journal of Pain, https://doi.org/10.1016/j.jpain.2023.02.023

Journal Article Type Article
Acceptance Date Feb 22, 2023
Online Publication Date Feb 28, 2023
Publication Date Feb 28, 2023
Deposit Date May 9, 2023
Publicly Available Date May 9, 2023
Journal The Journal of Pain
Print ISSN 1526-5900
Electronic ISSN 1526-5900
Publisher Elsevier
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1016/j.jpain.2023.02.023
Keywords Osteoarthritis, molecular pathways, serum metabolic profiling, knee pain, meta-analysis
Public URL https://nottingham-repository.worktribe.com/output/18805292
Publisher URL https://www.sciencedirect.com/science/article/pii/S1526590023000561?via%3Dihub
Additional Information This article is maintained by: Elsevier; Article Title: Serum Metabolome Analysis Identified Amino-Acid Metabolism Associated With Pain in People With Symptomatic Knee Osteoarthritis – A Cross-Sectional Study; Journal Title: The Journal of Pain; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jpain.2023.02.023; Content Type: article; Copyright: © 2023 The Author(s). Published by Elsevier Inc. on behalf of United States Association for the Study of Pain, Inc.