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Navarro-Ledesma S, Hamed-Hamed D, Pruimboom L. A new perspective of frozen shoulder pathology; the interplay between the brain and the immune system. Front Physiol 2024; 15:1248612. [PMID: 38617059 PMCID: PMC11009429 DOI: 10.3389/fphys.2024.1248612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 03/18/2024] [Indexed: 04/16/2024] Open
Abstract
Frozen shoulder (FS), also known as adhesive capsulitis of the shoulder (FS), is a fibrotic inflammatory process of unknown etiology whose main symptoms are pain, stiffness and the loss of joint mobility. These symptoms may be associated with pathologies such as diabetes, Dupuytren's syndrome and the prevalence of today's sedentary lifestyle. This literature review provides an overview of the epidemiology and pathogenesis of this pathology, as well as the mechanisms of lowgrade chronic inflammation and infection, insulin resistance, and omics-science associated with it. We also propose a new hypothesis related to the possibility that the GABAergic system could play a decisive role in the development of frozen shoulder and that therefore diabetes type 1, endocrinological autoimmune disorders and frozen shoulder are connected by the same pathophysiological mechanisms. If that is true, the combined presence of psycho-emotional stress factors and pathogenic immune challenges could be the main causes of frozen shoulder syndrome. Finally, we propose a series of possible intervention strategies based on a multifactorial etiological and mechanistic concept.
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Affiliation(s)
- Santiago Navarro-Ledesma
- Department of Physical Therapy, Faculty of Health Sciences, Campus of Melilla, University of Granada, Melilla, Spain
- University Chair in Clinical Psychoneuroimmunology, University of Granada and PNI Europe, Melilla, Spain
| | - Dina Hamed-Hamed
- Clinical Medicine and Public Health PhD Program, Faculty of Health Sciences, University of Granada, Granada, Spain
| | - Leo Pruimboom
- University Chair in Clinical Psychoneuroimmunology, University of Granada and PNI Europe, Melilla, Spain
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2
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Mehta O, Vijay A, Gohir SA, Kelly T, Zhang W, Doherty M, Walsh DA, Aithal G, Valdes AM. Serum Metabolome Analysis Identified Amino-Acid Metabolism Associated With Pain in People With Symptomatic Knee Osteoarthritis - A Cross-Sectional Study. THE JOURNAL OF PAIN 2023; 24:1251-1261. [PMID: 36863678 DOI: 10.1016/j.jpain.2023.02.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 03/04/2023]
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.
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Affiliation(s)
- Ojasvi Mehta
- Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham UK; NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham, UK.
| | - Amrita Vijay
- Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham UK; NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham, UK
| | - Sameer A Gohir
- Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham UK; NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham, UK
| | - Tony Kelly
- Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham UK
| | - Weiya Zhang
- Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham UK; Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Michael Doherty
- Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham UK; Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - David A Walsh
- Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham UK; Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Guruprasad Aithal
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham, UK; School of Medicine, University of Nottingham, Nottingham UK
| | - Ana M Valdes
- Injury, Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham UK; NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham, UK
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3
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McKay RT. Metabolomics and NMR. Handb Exp Pharmacol 2023; 277:73-116. [PMID: 36355220 DOI: 10.1007/164_2022_616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The purpose of this manuscript will be to convince the reader to dive deeper into NMR spectroscopy and prevent the technique from being just another "black-box" in the lab. We will try to concisely highlight interesting topics and supply additional references for further exploration at each stage. The advantages of delving into the technique will be shown. The secondary objective, i.e., avoiding common problems before starting, will hopefully then become clear. Lastly, we will emphasize the spectrometer information needed for manuscript reporting to allow reproduction of results and confirm findings.
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Affiliation(s)
- Ryan T McKay
- Department Chemistry, College of Natural and Applied Sciences, University of Alberta, Edmonton, AB, Canada.
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4
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Ghafouri B, Thordeman K, Hadjikani R, Bay Nord A, Gerdle B, Bäckryd E. An investigation of metabolome in blood in patients with chronic peripheral, posttraumatic/postsurgical neuropathic pain. Sci Rep 2022; 12:21714. [PMID: 36522472 PMCID: PMC9755304 DOI: 10.1038/s41598-022-26405-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022] Open
Abstract
Neuropathic pain (NP) is a chronic pain condition resulting from a lesion or disease in the somatosensory nervous system. The aim of this study was to investigate the metabolome in plasma from patients with chronic peripheral, posttraumatic/postsurgical NP compared to healthy controls. Further, we aimed to investigate the correlation between pain intensity and the metabolome in plasma. The metabolic profile in plasma samples from 16 patients with chronic NP and 12 healthy controls was analyzed using a nuclear magnetic resonance spectroscopy method. Information about pain intensity, pain duration, body mass index (BMI), age, sex, and blood pressure were obtained through a questionnaire and clinical examination. Multivariate data analysis was used to identify metabolites significant for group separation and their correlation with pain intensity and duration, BMI, and age. We found 50 out of 326 features in plasma significantly contributing to group discrimination between NP and controls. Several of the metabolites that significantly differed were involved in inflammatory processes, while others were important for central nervous system functioning and neural signaling. There was no correlation between pain intensity and levels of metabolite in NP. These findings indicate that there seems to be peripheral/systemic differences in the metabolic profile between patients with chronic NP and healthy individuals.
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Affiliation(s)
- Bijar Ghafouri
- grid.5640.70000 0001 2162 9922Pain and Rehabilitation Center, and Department of Health, Medicine and Caring Sciences, Linköping University, 581 85 Linköping, Sweden
| | - Katarina Thordeman
- grid.5640.70000 0001 2162 9922Pain and Rehabilitation Center, and Department of Health, Medicine and Caring Sciences, Linköping University, 581 85 Linköping, Sweden
| | - Romina Hadjikani
- grid.5640.70000 0001 2162 9922Pain and Rehabilitation Center, and Department of Health, Medicine and Caring Sciences, Linköping University, 581 85 Linköping, Sweden
| | - Anders Bay Nord
- grid.8761.80000 0000 9919 9582Swedish NMR Centre at the University of Gothenburg, Gothenburg, Sweden
| | - Björn Gerdle
- grid.5640.70000 0001 2162 9922Pain and Rehabilitation Center, and Department of Health, Medicine and Caring Sciences, Linköping University, 581 85 Linköping, Sweden
| | - Emmanuel Bäckryd
- grid.5640.70000 0001 2162 9922Pain and Rehabilitation Center, and Department of Health, Medicine and Caring Sciences, Linköping University, 581 85 Linköping, Sweden
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Miettinen T, Nieminen AI, Mäntyselkä P, Kalso E, Lötsch J. Machine Learning and Pathway Analysis-Based Discovery of Metabolomic Markers Relating to Chronic Pain Phenotypes. Int J Mol Sci 2022; 23:ijms23095085. [PMID: 35563473 PMCID: PMC9099732 DOI: 10.3390/ijms23095085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/28/2022] [Accepted: 04/28/2022] [Indexed: 11/19/2022] Open
Abstract
Recent scientific evidence suggests that chronic pain phenotypes are reflected in metabolomic changes. However, problems associated with chronic pain, such as sleep disorders or obesity, may complicate the metabolome pattern. Such a complex phenotype was investigated to identify common metabolomics markers at the interface of persistent pain, sleep, and obesity in 71 men and 122 women undergoing tertiary pain care. They were examined for patterns in d = 97 metabolomic markers that segregated patients with a relatively benign pain phenotype (low and little bothersome pain) from those with more severe clinical symptoms (high pain intensity, more bothersome pain, and co-occurring problems such as sleep disturbance). Two independent lines of data analysis were pursued. First, a data-driven supervised machine learning-based approach was used to identify the most informative metabolic markers for complex phenotype assignment. This pointed primarily at adenosine monophosphate (AMP), asparagine, deoxycytidine, glucuronic acid, and propionylcarnitine, and secondarily at cysteine and nicotinamide adenine dinucleotide (NAD) as informative for assigning patients to clinical pain phenotypes. After this, a hypothesis-driven analysis of metabolic pathways was performed, including sleep and obesity. In both the first and second line of analysis, three metabolic markers (NAD, AMP, and cysteine) were found to be relevant, including metabolic pathway analysis in obesity, associated with changes in amino acid metabolism, and sleep problems, associated with downregulated methionine metabolism. Taken together, present findings provide evidence that metabolomic changes associated with co-occurring problems may play a role in the development of severe pain. Co-occurring problems may influence each other at the metabolomic level. Because the methionine and glutathione metabolic pathways are physiologically linked, sleep problems appear to be associated with the first metabolic pathway, whereas obesity may be associated with the second.
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Affiliation(s)
- Teemu Miettinen
- Pain Clinic, Department of Perioperative Medicine, Intensive Care and Pain Medicine, Helsinki University Hospital and SleepWell Research Programme, University of Helsinki, 00014 Helsinki, Finland; (T.M.); (E.K.)
| | - Anni I. Nieminen
- Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, 00014 Helsinki, Finland;
| | - Pekka Mäntyselkä
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio Finland, and Primary Health Care Unit, Kuopio University Hospital, 70211 Kuopio, Finland;
| | - Eija Kalso
- Pain Clinic, Department of Perioperative Medicine, Intensive Care and Pain Medicine, Helsinki University Hospital and SleepWell Research Programme, University of Helsinki, 00014 Helsinki, Finland; (T.M.); (E.K.)
| | - Jörn Lötsch
- Institute of Clinical Pharmacology, Goethe—University, Theodor—Stern—Kai 7, 60590 Frankfurt am Main, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
- Correspondence: ; Tel.: +49-69-6301-4589; Fax: +49-69-6301-4354
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Piras C, Pintus BM, Noto A, Evangelista M, Fanos V, Musu M, Mussap M, Atzori L, Sardo S, Finco G. Metabolomics and Microbiomics: New Potential Strategies in Chronic Pain Syndrome. J Pain Res 2022; 15:723-731. [PMID: 35310896 PMCID: PMC8923834 DOI: 10.2147/jpr.s354516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 03/02/2022] [Indexed: 11/23/2022] Open
Affiliation(s)
- Cristina Piras
- Department of Biomedical Sciences, University of Cagliari, Monserrato, 09042, Italy
| | - Bruno Maria Pintus
- Department of Medical Sciences and Public Health, University of Cagliari, Monserrato, 09042, Italy
| | - Antonio Noto
- Department of Biomedical Sciences, University of Cagliari, Monserrato, 09042, Italy
- Correspondence: Antonio Noto, Email
| | - Maurizio Evangelista
- Department of Anesthesiology and Pain Medicine, Cattolica University, Rome, 00168, Italy
| | - Vassilios Fanos
- Department of Surgical Science, University of Cagliari, Monserrato, 09042, Italy
| | - Mario Musu
- Department of Medical Sciences and Public Health, University of Cagliari, Monserrato, 09042, Italy
| | - Michele Mussap
- Department of Surgical Science, University of Cagliari, Monserrato, 09042, Italy
| | - Luigi Atzori
- Department of Biomedical Sciences, University of Cagliari, Monserrato, 09042, Italy
| | - Salvatore Sardo
- Department of Medical Sciences and Public Health, University of Cagliari, Monserrato, 09042, Italy
| | - Gabriele Finco
- Department of Medical Sciences and Public Health, University of Cagliari, Monserrato, 09042, Italy
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Gut microbiota and its role in stress-induced hyperalgesia: gender-specific responses linked to different changes in serum metabolites. Pharmacol Res 2022; 177:106129. [DOI: 10.1016/j.phrs.2022.106129] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 01/31/2022] [Accepted: 02/08/2022] [Indexed: 12/13/2022]
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Shraim MA, Massé-Alarie H, Hodges PW. Methods to discriminate between mechanism-based categories of pain experienced in the musculoskeletal system: a systematic review. Pain 2021; 162:1007-1037. [PMID: 33136983 DOI: 10.1097/j.pain.0000000000002113] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 10/05/2020] [Indexed: 12/18/2022]
Abstract
ABSTRACT Mechanism-based classification of pain has been advocated widely to aid tailoring of interventions for individuals experiencing persistent musculoskeletal pain. Three pain mechanism categories (PMCs) are defined by the International Association for the Study of Pain: nociceptive, neuropathic, and nociplastic pain. Discrimination between them remains challenging. This study aimed to build on a framework developed to converge the diverse literature of PMCs to systematically review methods purported to discriminate between them; synthesise and thematically analyse these methods to identify the convergence and divergence of opinion; and report validation, psychometric properties, and strengths/weaknesses of these methods. The search strategy identified articles discussing methods to discriminate between mechanism-based categories of pain experienced in the musculoskeletal system. Studies that assessed the validity of methods to discriminate between categories were assessed for quality. Extraction and thematic analysis were undertaken on 184 articles. Data synthesis identified 200 methods in 5 themes: clinical examination, quantitative sensory testing, imaging, diagnostic and laboratory testing, and pain-type questionnaires. Few methods have been validated for discrimination between PMCs. There was general convergence but some disagreement regarding findings that discriminate between PMCs. A combination of features and methods, rather than a single method, was generally recommended to discriminate between PMCs. Two major limitations were identified: an overlap of findings of methods between categories due to mixed presentations and many methods considered discrimination between 2 PMCs but not others. The results of this review provide a foundation to refine methods to differentiate mechanisms for musculoskeletal pain.
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Affiliation(s)
- Muath A Shraim
- The University of Queensland, NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury & Health, School of Health & Rehabilitation Sciences, QLD, Australia
| | - Hugo Massé-Alarie
- The University of Queensland, NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury & Health, School of Health & Rehabilitation Sciences, QLD, Australia
- Centre Interdisciplinaire de recherche en réadaptation et Integration sociale (CIRRIS), Université Laval, Québec, QC, Canada
| | - Paul W Hodges
- The University of Queensland, NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury & Health, School of Health & Rehabilitation Sciences, QLD, Australia
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9
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Metabolomics and psychological features in fibromyalgia and electromagnetic sensitivity. Sci Rep 2020; 10:20418. [PMID: 33235303 PMCID: PMC7686375 DOI: 10.1038/s41598-020-76876-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Accepted: 10/30/2020] [Indexed: 12/29/2022] Open
Abstract
Fibromyalgia (FM) as Fibromyalgia and Electromagnetic Sensitivity (IEI-EMF) are a chronic and systemic syndrome. The main symptom is represented by strong and widespread pain in the musculoskeletal system. The exact causes that lead to the development of FM and IEI-EMF are still unknown. Interestingly, the proximity to electrical and electromagnetic devices seems to trigger and/or amplify the symptoms. We investigated the blood plasma metabolome in IEI-EMF and healthy subjects using 1H NMR spectroscopy coupled with multivariate statistical analysis. All the individuals were subjected to tests for the evaluation of psychological and physical features. No significant differences between IEI-EMF and controls relative to personality aspects, Locus of Control, and anxiety were found. Multivariate statistical analysis on the metabolites identified by NMR analysis allowed the identification of a distinct metabolic profile between IEI-EMF and healthy subjects. IEI-EMF were characterized by higher levels of glycine and pyroglutamate, and lower levels of 2-hydroxyisocaproate, choline, glutamine, and isoleucine compared to healthy subjects. These metabolites are involved in several metabolic pathways mainly related to oxidative stress defense, pain mechanisms, and muscle metabolism. The results here obtained highlight possible physiopathological mechanisms in IEI-EMF patients to be better defined.
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10
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Teckchandani S, Nagana Gowda GA, Raftery D, Curatolo M. Metabolomics in chronic pain research. Eur J Pain 2020; 25:313-326. [PMID: 33065770 DOI: 10.1002/ejp.1677] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/22/2020] [Accepted: 10/11/2020] [Indexed: 01/26/2023]
Abstract
BACKGROUND AND OBJECTIVE Metabolomics deals with the identification and quantification of small molecules (metabolites) in biological samples. As metabolite levels can reflect normal or altered metabolic pathways, their measurement provides information to improve the understanding, diagnosis and management of diseases. Despite its immense potential, metabolomics applications to pain research have been sparse. This paper describes current metabolomics techniques, reviews published human metabolomics pain research and compares successful metabolomics research in other areas of medicine with the goal of highlighting opportunities offered by metabolomics to advance pain medicine. DATABASES AND DATA TREATMENT Non-systematic review. RESULTS Our search identified 19 studies that adopted a metabolomics approach in: fibromyalgia (7), chronic widespread pain (4), other musculoskeletal pain conditions (5), neuropathic pain (1), complex regional pain syndrome (1) and pelvic pain (1). The studies used either mass spectrometry or nuclear magnetic resonance. Most are characterized by small sample sizes. Some consistency has been found for alterations in glutamate and testosterone metabolism, and metabolic imbalances caused by the gut microbiome. CONCLUSIONS Metabolomics research in chronic pain is in its infancy. Most studies are at the pilot stage. Metabolomics research has been successful in other areas of medicine. These achievements should motivate investigators to expand metabolomics research to improve the understanding of the basic mechanisms of human pain, as well as provide tools to diagnose, predict and monitor chronic pain conditions. Metabolomics research can lead to the identification of biomarkers to support the development and testing of treatments, thereby facilitating personalized pain medicine.
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Affiliation(s)
- Shweta Teckchandani
- Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA, USA
| | - G A Nagana Gowda
- Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA, USA.,Northwest Metabolomics Research Center, Mitochondria and Metabolism Center, University of Washington, Seattle, WA, USA
| | - Daniel Raftery
- Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA, USA.,Northwest Metabolomics Research Center, Mitochondria and Metabolism Center, University of Washington, Seattle, WA, USA
| | - Michele Curatolo
- Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA, USA.,Harborview Injury Prevention and Research Center, University of Washington, Seattle, WA, USA.,CLEAR Research Center for Musculoskeletal Disorders, University of Washington, Seattle, WA, USA
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11
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Aroke EN, Powell-Roach KL. The Metabolomics of Chronic Pain Conditions: A Systematic Review. Biol Res Nurs 2020; 22:458-471. [PMID: 32666804 DOI: 10.1177/1099800420941105] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Chronic pain is a significant public health problem in the United States, affecting approximately 100 million people. Yet there is a lack of robust biomarkers for clinical use in chronic pain conditions. Downstream effects of environmental, genomic, and proteomic variations in individuals with chronic pain conditions can be identified and quantified using a metabolomic approach. AIM/DESIGN The purpose of this systematic review was to examine the literature for reports of potential metabolomic signatures associated with chronic pain conditions. METHODS We searched relevant electronic databases for published studies that used various metabolomic approaches to investigate chronic pain conditions among subjects of all ages. RESULTS Our search identified a total of 586 articles, 18 of which are included in this review. The reviewed studies used metabolomics to investigate fibromyalgia (n = 5), osteoarthritis (n = 4), migraine (n = 3), musculoskeletal pain (n = 2), and other chronic pain conditions (n = 1/condition). Results show that several known and newly identified metabolites differ in individuals with chronic pain conditions compared to those without these conditions. These include amino acids (e.g., glutamine, serine, and phenylalanine) and intermediate products (e.g., succinate, citrate, acetylcarnitine, and N-acetylornithine) of pathways that metabolize various macromolecules. CONCLUSION Though more high-quality research is needed, this review provides insights into potential biomarkers for future metabolomics studies in people with chronic pain conditions.
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Affiliation(s)
- Edwin N Aroke
- School of Nursing, University of Alabama at Birmingham, AL, USA
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12
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Systematic Review and Synthesis of Mechanism-based Classification Systems for Pain Experienced in the Musculoskeletal System. Clin J Pain 2020; 36:793-812. [DOI: 10.1097/ajp.0000000000000860] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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13
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Neuroimaging-based biomarkers for pain: state of the field and current directions. Pain Rep 2019; 4:e751. [PMID: 31579847 PMCID: PMC6727991 DOI: 10.1097/pr9.0000000000000751] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 03/20/2019] [Accepted: 04/07/2019] [Indexed: 12/15/2022] Open
Abstract
Chronic pain is an endemic problem involving both peripheral and brain pathophysiology. Although biomarkers have revolutionized many areas of medicine, biomarkers for pain have remained controversial and relatively underdeveloped. With the realization that biomarkers can reveal pain-causing mechanisms of disease in brain circuits and in the periphery, this situation is poised to change. In particular, brain pathophysiology may be diagnosable with human brain imaging, particularly when imaging is combined with machine learning techniques designed to identify predictive measures embedded in complex data sets. In this review, we explicate the need for brain-based biomarkers for pain, some of their potential uses, and some of the most popular machine learning approaches that have been brought to bear. Then, we evaluate the current state of pain biomarkers developed with several commonly used methods, including structural magnetic resonance imaging, functional magnetic resonance imaging and electroencephalography. The field is in the early stages of biomarker development, but these complementary methodologies have already produced some encouraging predictive models that must be tested more extensively across laboratories and clinical populations.
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14
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Laíns I, Duarte D, Barros AS, Martins AS, Carneiro TJ, Gil JQ, Miller JB, Marques M, Mesquita TS, Barreto P, Kim IK, da Luz Cachulo M, Vavvas DG, Carreira IM, Murta JN, Silva R, Miller JW, Husain D, Gil AM. Urine Nuclear Magnetic Resonance (NMR) Metabolomics in Age-Related Macular Degeneration. J Proteome Res 2019; 18:1278-1288. [PMID: 30672297 PMCID: PMC7838731 DOI: 10.1021/acs.jproteome.8b00877] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Biofluid biomarkers of age-related macular degeneration (AMD) are still lacking, and their identification is challenging. Metabolomics is well-suited to address this need, and urine is a valuable accessible biofluid. This study aimed to characterize the urinary metabolomic signatures of patients with different stages of AMD and a control group (>50 years). It was a prospective, cross-sectional study, where subjects from two cohorts were included: 305 from Coimbra, Portugal (AMD patients n = 252; controls n = 53) and 194 from Boston, United States (AMD patients n = 147; controls n = 47). For all participants, we obtained color fundus photographs (for AMD staging) and fasting urine samples, which were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy. Our results revealed that in both cohorts, urinary metabolomic profiles differed mostly between controls and late AMD patients, but important differences were also found between controls and subjects with early AMD. Analysis of the metabolites responsible for these separations revealed that, even though distinct features were observed for each cohort, AMD was in general associated with depletion of excreted citrate and selected amino acids at some stage of the disease, suggesting enhanced energy requirements. In conclusion, NMR metabolomics enabled the identification of urinary signals of AMD and its severity stages, which might represent potential metabolomic biomarkers of the disease.
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Affiliation(s)
- Inês Laíns
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts 02115, United States
- Faculty of Medicine, University of Coimbra (FMUC), 3000-354 Coimbra, Portugal
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), 3000-548 Coimbra, Portugal
- Department of Ophthalmology, Centro Hospitalar e Universitário de Coimbra (CHUC), 3075 Coimbra, Portugal
| | - Daniela Duarte
- CICECO- Aveiro Institute of Materials (CICECO/UA), Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
| | - António S. Barros
- CICECO- Aveiro Institute of Materials (CICECO/UA), Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Ana Sofia Martins
- CICECO- Aveiro Institute of Materials (CICECO/UA), Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Tatiana J. Carneiro
- CICECO- Aveiro Institute of Materials (CICECO/UA), Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
| | - João Q. Gil
- Faculty of Medicine, University of Coimbra (FMUC), 3000-354 Coimbra, Portugal
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), 3000-548 Coimbra, Portugal
- Department of Ophthalmology, Centro Hospitalar e Universitário de Coimbra (CHUC), 3075 Coimbra, Portugal
| | - John B. Miller
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Marco Marques
- Faculty of Medicine, University of Coimbra (FMUC), 3000-354 Coimbra, Portugal
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), 3000-548 Coimbra, Portugal
- Department of Ophthalmology, Centro Hospitalar e Universitário de Coimbra (CHUC), 3075 Coimbra, Portugal
| | - Tânia S. Mesquita
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), 3000-548 Coimbra, Portugal
| | - Patrícia Barreto
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), 3000-548 Coimbra, Portugal
| | - Ivana K. Kim
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Maria da Luz Cachulo
- Faculty of Medicine, University of Coimbra (FMUC), 3000-354 Coimbra, Portugal
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), 3000-548 Coimbra, Portugal
- Department of Ophthalmology, Centro Hospitalar e Universitário de Coimbra (CHUC), 3075 Coimbra, Portugal
| | - Demetrios G. Vavvas
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Isabel M. Carreira
- Faculty of Medicine, University of Coimbra (FMUC), 3000-354 Coimbra, Portugal
| | - Joaquim Neto Murta
- Faculty of Medicine, University of Coimbra (FMUC), 3000-354 Coimbra, Portugal
- Department of Ophthalmology, Centro Hospitalar e Universitário de Coimbra (CHUC), 3075 Coimbra, Portugal
| | - Rufino Silva
- Faculty of Medicine, University of Coimbra (FMUC), 3000-354 Coimbra, Portugal
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), 3000-548 Coimbra, Portugal
- Department of Ophthalmology, Centro Hospitalar e Universitário de Coimbra (CHUC), 3075 Coimbra, Portugal
| | - Joan W. Miller
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Deeba Husain
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Ana M. Gil
- CICECO- Aveiro Institute of Materials (CICECO/UA), Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
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15
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Rockel JS, Kapoor M. The Metabolome and Osteoarthritis: Possible Contributions to Symptoms and Pathology. Metabolites 2018; 8:metabo8040092. [PMID: 30551581 PMCID: PMC6315757 DOI: 10.3390/metabo8040092] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 12/07/2018] [Accepted: 12/10/2018] [Indexed: 12/22/2022] Open
Abstract
Osteoarthritis (OA) is a progressive, deteriorative disease of articular joints. Although traditionally viewed as a local pathology, biomarker exploration has shown that systemic changes can be observed. These include changes to cytokines, microRNAs, and more recently, metabolites. The metabolome is the set of metabolites within a biological sample and includes circulating amino acids, lipids, and sugar moieties. Recent studies suggest that metabolites in the synovial fluid and blood could be used as biomarkers for OA incidence, prognosis, and response to therapy. However, based on clinical, demographic, and anthropometric factors, the local synovial joint and circulating metabolomes may be patient specific, with select subsets of metabolites contributing to OA disease. This review explores the contribution of the local and systemic metabolite changes to OA, and their potential impact on OA symptoms and disease pathogenesis.
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Affiliation(s)
- Jason S Rockel
- Arthritis Program, University Health Network, Toronto, ON M5T 2S8, Canada.
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, ON M5T 2S8, Canada.
| | - Mohit Kapoor
- Arthritis Program, University Health Network, Toronto, ON M5T 2S8, Canada.
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, ON M5T 2S8, Canada.
- Department of Surgery, University of Toronto, Toronto, ON M1C 1A4, Canada.
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M1C 1A4, Canada.
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16
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Abstract
Precision medicine is an emerging approach for prevention and treatment of diseases considering individuals’ uniqueness. Omics provide one step forward toward advanced precision medicine and include technologies such as genomics, proteomics and metabolomics generating valuable data through characterization of entire biological systems. With the aid of omics, a major shift has been started to occur in understanding of diseases followed by potential fundamental changes in medical care strategies. This short review aims at providing some examples of current omics that are applied in the field of pain in terms of new biomarkers for diagnosis of different pain types, stratification of patients and new therapeutic targets. Implementation of omics would most likely offer breakthrough in the future of pain management.
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Affiliation(s)
- Parisa Gazerani
- Department of Health Science & Technology, Faculty of Medicine, Aalborg University, Frederik Bajers Vej 7A2-A2-208, 9220 Aalborg East, Denmark
| | - Hye Sook Han Vinterhøj
- Department of Health Science & Technology, Faculty of Medicine, Aalborg University, Frederik Bajers Vej 7A2-A2-208, 9220 Aalborg East, Denmark
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