Rheumatology International

, Volume 36, Issue 5, pp 703–711 | Cite as

Metabolomics study of fatigue in patients with rheumatoid arthritis naïve to biological treatment

  • Izabella Surowiec
  • Clara Gram Gjesdal
  • Grete Jonsson
  • Katrine Brække Norheim
  • Torbjörn Lundstedt
  • Johan TryggEmail author
  • Roald Omdal
Original Article - Food for Thought


Fatigue occurs in all chronic inflammatory diseases, in cancer, and in some neurological conditions. Patients often regard fatigue as one of their most debilitating problems, but currently there is no established treatment and the mechanisms that lead to and regulate fatigue are incompletely understood. Our objective was to more completely understand the physiology of this phenomenon. Twenty-four patients with rheumatoid arthritis (RA) naïve to treatment with biological drugs were enrolled for the study. Fatigue was measured with a fatigue visual analogue scale (fVAS). Ethylenediaminetetraacetic acid (EDTA) plasma samples were subjected to gas chromatography–time-of-flight mass spectrometry (GC/MS-TOF)-based metabolite profiling. Obtained metabolite data were evaluated by multivariate data analysis with orthogonal projections to latent structures (OPLS) method to pinpoint metabolic changes related to fatigue severity. A significant multivariate OPLS model was obtained between the fVAS scores and the measured metabolic levels. Increasing fatigue scores were associated with a metabolic pattern characterized by down-regulation of metabolites from the urea cycle, fatty acids, tocopherols, aromatic amino acids, and hypoxanthine. Uric acid levels were increased. Apart from fatigue, we found no other disease-related variables that might be responsible for these changes. Our MS-based metabolomic approach demonstrated strong associations between fatigue and several biochemical patterns related to oxidative stress.


Rheumatoid arthritis Fatigue Metabolomics Oxidative stress 



This study was funded by Swedish Research Council Grant No. 2011-6044. KN was funded by the Norwegian Western Health Authorities (Grant No: 911783). RO received an unrestricted grant from Pfizer of 100,000 NOK for research on fatigue in RA and in ankylosing spondylitis.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no other conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

296_2016_3426_MOESM1_ESM.doc (144 kb)
Supplementary material 1 (DOC 144 kb)


  1. 1.
    Kirwan JR, Minnock P, Adebajo A, Bresnhan B, Choy E, De Wit M et al (2007) Patient perspective: fatigue as a recommended patient centered outcome measure in rheumatoid arthritis. J Rheumatol 34:1174–1177PubMedGoogle Scholar
  2. 2.
    Hart BL (1988) Biological basis of the behavior of sick animals. Neurosci Biobehav R 12:123–137CrossRefGoogle Scholar
  3. 3.
    Dantzer R, O’Connor JC, Freund GG, Johnson RW, Kelly KW (2008) From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci 9:46–57CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Norheim KB, Jonsson G, Omdal R (2011) Biological mechanisms of chronic fatigue. Rheumatology 50:1009–1018CrossRefPubMedGoogle Scholar
  5. 5.
    Harboe E, Tjensvoll AB, Vefring HK, Goransson LG, Kvaloy JT, Omdal R (2009) Fatigue in primary Sjogren’s syndrome—A link to sickness behaviour in animals? Brain Behav Immun 23:1104–1108CrossRefPubMedGoogle Scholar
  6. 6.
    Norheim KB, Harboe E, Goransson LG, Omdal R (2012) Interleukin-1 inhibition and fatigue in primary Sjogren’s syndrome—A double blind, randomised clinical trial. PLoS One 7:e30123CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Flannagan RS, Cosio G, Grinstein S (2009) Antimicrobial mechanisms of phagocytes and bacterial evasion strategies. Nat Rev Microbiol 7:355–366CrossRefPubMedGoogle Scholar
  8. 8.
    West AP, Brodsky IE, Rahner C, Woo DK, Erdjument-Bromage H, Tempst P et al (2011) TLR signalling augments macrophage bactericidal activity through mitochondrial ROS. Nature 472:476–480CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Gabrielli A, Avvedimento EV, Krieg T (2009) Mechanisms of disease: scleroderma. New Engl J Med 360:1989–2003CrossRefPubMedGoogle Scholar
  10. 10.
    Brkic S, Tomic S, Maric D, Mikic AN, Turkulov V (2010) Lipid peroxidation is elevated in female patients with chronic fatigue syndrome. Med Sci Monitor 16:628–632Google Scholar
  11. 11.
    Kennedy G, Spence VA, McLaren M, Hill A, Underwood C, Belch JJF (2005) Oxidative stress levels are raised in chronic fatigue syndrome and are associated with clinical symptoms. Free Radic Bio Med 39:584–589CrossRefGoogle Scholar
  12. 12.
    Avalos I, Chung CP, Oeser A, Milne GL, Morrow JD, Gebretsadik T et al (2007) Oxidative stress in systemic lupus erythematosus: relationship to disease activity and symptoms. Lupus 16:195–200CrossRefPubMedGoogle Scholar
  13. 13.
    Chung CP, Titova D, Oeser A, Randels M, Avalos I, Milne GL et al (2009) Oxidative stress in fibromyalgia and its relationship to symptoms. Clin Rheumatol 28:435–438CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Segal BM, Thomas W, Zhu X, Diebes A, McElvain G, Baechler E et al (2012) Oxidative stress and fatigue in systemic lupus erythematosus. Lupus 21:984–992CrossRefPubMedGoogle Scholar
  15. 15.
    Giera M, Ioan-Facsinay A, Toes R, Gao F, Dalli J, Deelder AM et al (2012) Lipid and lipid mediator profiling of human synovial fluid in rheumatoid arthritis patients by means of LC-MS/MS. Biochim Biophys Acta 1821:1415–1424CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Fuchs B, Schiller E, Wagner U, Hantzschel H, Arnold K (2005) The phosphatidylcholine/lysophosphatidylcholine ratio in human plasma is an indicator of the severity of rheumatoid arthritis: investigations by P-31 NMR and MALDI-TOF MS. Clin Biochem 38:925–933CrossRefPubMedGoogle Scholar
  17. 17.
    Kim S, Hwang J, Xuan J, Jung YH, Cha HS, Kim KH (2014) Global metabolite profiling of synovial fluid for the specific diagnosis of rheumatoid arthritis from other inflammatory arthritis. PLoS One 9:e97501CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Young SP, Kapoor SR, Viant MR, Byrne JJ, Filer A, Buckley CD et al (2013) The impact of inflammation on metabolomic profiles in patients with arthritis. Arthritis Rheum 65:2015–2023CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Madsen RK, Lundstedt T, Gabrielsson J, Sennbro CJ, Alenius GM, Moritz T et al (2011) Diagnostic properties of metabolic perturbations in rheumatoid arthritis. Arthritis Res Ther 13:R19CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Wang Z, Chen Z, Yang S, Wang Y, Yu L, Zhang B et al (2012) (1)H NMR-based metabolomic analysis for identifying serum biomarkers to evaluate methotrexate treatment in patients with early rheumatoid arthritis. Exp Ther Med 4:165–171PubMedPubMedCentralGoogle Scholar
  21. 21.
    Kapoor SR, Filer A, Fitzpatrick MA, Fisher AB, Taylor PC, Buckley CD et al (2013) Metabolic profiling predicts response to anti-tumor necrosis factor alpha therapy in patients with rheumatoid arthritis. Arthritis Rheum 65:1448–1456CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Madsen R, Rantapaa-Dahlqvist S, Lundstedt T, Moritz T, Trygg J (2012) Metabolic responses to change in disease activity during tumor necrosis factor inhibition in patients with rheumatoid arthritis. J Proteome Res 11:3796–3804CrossRefPubMedGoogle Scholar
  23. 23.
    Lauridsen MB, Bliddal H, Christensen R, Danneskiold-Samsoe B, Bennett R, Keun H et al (2010) 1H NMR spectroscopy-based interventional metabolic phenotyping: a cohort study of rheumatoid arthritis patients. J Proteome Res 9:4545–4553CrossRefPubMedGoogle Scholar
  24. 24.
    Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO 3rd et al (2010) 2010 rheumatoid arthritis classification criteria: an American college of rheumatology/European league against rheumatism collaborative initiative. Ann Rheum Dis 69:1580–1588CrossRefPubMedGoogle Scholar
  25. 25.
    Wells G, Becker JC, Teng J, Dougados M, Schiff M, Smolen J et al (2009) Validation of the 28-joint Disease Activity Score (DAS28) and European league against rheumatism response criteria based on C-reactive protein against disease progression in patients with rheumatoid arthritis, and comparison with the DAS28 based on erythrocyte sedimentation rate. Ann Rheum Dis 68:954–960CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Balsa A, Carmona L, Gonzalez-Alvaro I, Belmonte MA, Tena X, Sanmarti R et al (2004) Value of Disease Activity Score 28 (DAS28) and DAS28-3 compared to American college of rheumatology-defined remission in rheumatoid arthritis. J Rheumatol 31:40–46PubMedGoogle Scholar
  27. 27.
    Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD (1989) The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 46:1121–1123CrossRefPubMedGoogle Scholar
  28. 28.
    Wolfe F, Hawley DJ, Wilson K (1996) The prevalence and meaning of fatigue in rheumatic disease. J Rheumatol 23:1407–1417PubMedGoogle Scholar
  29. 29.
    Jiye A, Trygg J, Gullberg J, Johannson AI, Johnsson P, Antti H et al (2005) Extraction and GC/MS analysis of the human blood plasma metabolome. Anal Chem 77:8086–8094CrossRefGoogle Scholar
  30. 30.
    Trygg J, Wold S (2002) Orthogonal projections to latent structures (O-PLS). J Chemometr 16:119–128CrossRefGoogle Scholar
  31. 31.
    Wiklund S, Johansson E, Sjostrom L, Mellerowicz EJ, Edlund U, Schockor JP et al (2008) Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal Chem 80:115–122CrossRefPubMedGoogle Scholar
  32. 32.
    Martens H, Naes T (1989) Multivariate calibration. Wiley, ChichesterGoogle Scholar
  33. 33.
    Efron B, Gong G (1983) A leisurely look at the bootstrap, the jack-knife, and cross-validation. Am Stat 37:36–48Google Scholar
  34. 34.
    Xia JG, Mandal R, Sinelnikov IV, Broadhurst D, Wishart DS (2012) MetaboAnalyst 2.0—A comprehensive server for metabolomic data analysis. Nucleic Acids Res 40(W1):W127–W133CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Villamena FA (2013) Molecular basis of oxidative stress: chemistry, mechanisms, and disease pathogenesis. Wiley, HobokenCrossRefGoogle Scholar
  36. 36.
    Winyard PG, Ryan B, Eggleton P, Nissim A, Taylor E, Lo Faro ML et al (2011) Measurement and meaning of markers of reactive species of oxygen, nitrogen and sulfur in healthy human subjects and patients with inflammatory joint disease. Biochem Soc T 39:1226–1232CrossRefGoogle Scholar
  37. 37.
    Jones MG, Cooper E, Amjad S, Goodwin CS, Barron JL, Chalmers RA (2005) Urinary and plasma organic acids and amino acids in chronic fatigue syndrome. Clin Chim Acta 361:150–158CrossRefPubMedGoogle Scholar
  38. 38.
    Kurup RK, Kurup PA (2003) Isoprenoid pathway dysfunction in chronic fatigue syndrome. Acta Neuropsychiatr 15:266–273CrossRefPubMedGoogle Scholar
  39. 39.
    Niki E (2014) Role of vitamin E as a lipid-soluble peroxyl radical scavenger: in vitro and in vivo evidence. Free Radical Bio Med 66:3–12CrossRefGoogle Scholar
  40. 40.
    Vasanthi P, Nalini G, Rajasekhar G (2009) Status of oxidative stress in rheumatoid arthritis. Int J Rheum Dis 12:29–33CrossRefPubMedGoogle Scholar
  41. 41.
    Armstrong CW, McGregor NR, Sheedy JR, Buttfield I, Butt HL, Gooley PR (2012) NMR metabolic profiling of serum identifies amino acid disturbances in chronic fatigue syndrome. Clin Chim Acta 413:1525–1531CrossRefPubMedGoogle Scholar
  42. 42.
    Balboa MA, Balsinde J (2006) Oxidative stress and arachidonic acid mobilization. Biochim Biophys Acta 1761:385–391CrossRefPubMedGoogle Scholar
  43. 43.
    Keyser RE, Rus V, Cade WT, Kalappa N, Flores RH, Handwerger BS (2003) Evidence for aerobic insufficiency in women with systemic lupus erythematosus. Arthritis Rheum 49:16–22CrossRefPubMedGoogle Scholar
  44. 44.
    Grimstad T, Norheim KB, Isaksen K, Leitao K, Hetta AK, Carlsen A et al (2015) Fatigue in newly diagnosed inflammatory bowel disease. J Crohns Colitis 9:725–730CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Izabella Surowiec
    • 1
  • Clara Gram Gjesdal
    • 2
    • 3
  • Grete Jonsson
    • 4
  • Katrine Brække Norheim
    • 5
  • Torbjörn Lundstedt
    • 6
  • Johan Trygg
    • 1
    Email author
  • Roald Omdal
    • 3
    • 5
  1. 1.Computational Life Science Cluster (CLiC), Department of ChemistryUmeå UniversityUmeåSweden
  2. 2.Department of RheumatologyHaukeland University HospitalBergenNorway
  3. 3.Department of Clinical ScienceUniversity of BergenBergenNorway
  4. 4.Department of Medical BiochemistryStavanger University HospitalStavangerNorway
  5. 5.Clinical Immunology Unit, Department of Internal MedicineStavanger University HospitalStavangerNorway
  6. 6.Acureomics ABUmeåSweden

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