Advertisement

Molecular Medicine

, Volume 13, Issue 1–2, pp 40–58 | Cite as

Molecular Profile of Peripheral Blood Mononuclear Cells from Patients with Rheumatoid Arthritis

  • Christopher J. Edwards
  • Jeffrey L. Feldman
  • Jonathan Beech
  • Kathleen M. Shields
  • Jennifer A. Stover
  • William L. Trepicchio
  • Glenn Larsen
  • Brian M. J. Foxwell
  • Fionula M. Brennan
  • Marc Feldmann
  • Debra D. Pittman
Research Article

Abstract

Rheumatoid arthritis (RA) is a chronic inflammatory arthritis. Currently, diagnosis of RA may take several weeks, and factors used to predict a poor prognosis are not always reliable. Gene expression in RA may consist of a unique signature. Gene expression analysis has been applied to synovial tissue to define molecularly distinct forms of RA; however, expression analysis of tissue taken from a synovial joint is invasive and clinically impractical. Recent studies have demonstrated that unique gene expression changes can be identified in peripheral blood mononuclear cells (PBMCs) from patients with cancer, multiple sclerosis, and lupus. To identify RA disease-related genes, we performed a global gene expression analysis. RNA from PBMCs of 9 RA patients and 13 normal volunteers was analyzed on an oligonucleotide array. Compared with normal PBMCs, 330 transcripts were differentially expressed in RA. The differentially regulated genes belong to diverse functional classes and include genes involved in calcium binding, chaperones, cytokines, transcription, translation, signal transduction, extracellular matrix, integral to plasma membrane, integral to intracellular membrane, mitochondrial, ribosomal, structural, enzymes, and proteases. A k-nearest neighbor analysis identified 29 transcripts that were preferentially expressed in RA. Ten genes with increased expression in RA PBMCs compared with controls mapped to a RA susceptibility locus, 6p21.3. These results suggest that analysis of RA PBMCs at the molecular level may provide a set of candidate genes that could yield an easily accessible gene signature to aid in early diagnosis and treatment.

Notes

Acknowledgments

The authors thank Dr. James C. Keith, Jr., for reviewing the manuscript.

References

  1. 1.
    Markenson JA. (1991) Worldwide trends in the socioeconomic impact and long-term prognosis of rheumatoid arthritis. Semin. Arthritis Rheum. 21(2 Suppl 1):4–12.CrossRefGoogle Scholar
  2. 2.
    Wong JB, Ramey DR, Singh G. (2001) Long-term morbidity, mortality, and economics of rheumatoid arthritis. Arthritis Rheum. 44(12):2746–9.CrossRefGoogle Scholar
  3. 3.
    No author. (2002) Guidelines for the management of rheumatoid arthritis: update. Arthritis Rheum. 46:328–46.Google Scholar
  4. 4.
    Feldmann M, Maini RN. (2003) Lasker Clinical Medical Research Award. TNF defined as a therapeutic target for rheumatoid arthritis and other autoimmune diseases. Nat. Med. 9:1245–50.CrossRefGoogle Scholar
  5. 5.
    van der Heijde DM, van Leeuwen MA, van Riel PL, van de Putte LB. (1995) Radiographic progression on radiographs of hands and feet during the first 3 years of rheumatoid arthritis measured according to Sharp’s method (van der Heijde modification). J. Rheumatol. 22:1792–6.PubMedGoogle Scholar
  6. 6.
    Bathon JM et al. (2000) A comparison of etanercept and methotrexate in patients with early rheumatoid arthritis. N. Engl. J. Me.d 343:1586–93.CrossRefGoogle Scholar
  7. 7.
    Lipsky PE et al. (2000). Infliximab and methotrexate in the treatment of rheumatoid arthritis: Anti-Tumor Necrosis Factor Trial in Rheumatoid Arthritis with Concomitant Therapy Study Group. N. Engl. J. Med. 343:1594–602.CrossRefGoogle Scholar
  8. 8.
    Quinn MA et al. (2005) Very early treatment with infliximab in addition to methotrexate in early, poor-prognosis rheumatoid arthritis reduces magnetic resonance imaging evidence of synovitis and damage, with sustained benefit after infliximab withdrawal: results from a twelvemonth randomized, double-blind, placebo-controlled trial. Arthritis Rheum. 52:27–35.CrossRefGoogle Scholar
  9. 9.
    Combe B et al. (2001) Prognostic factors for radiographic damage in early rheumatoid arthritis: a multiparameter prospective study. Arthritis Rheum. 44:1736–43.CrossRefGoogle Scholar
  10. 10.
    Dixey J, Solymossy C, Young A. (2004) Is it possible to predict radiological damage in early rheumatoid arthritis (RA)? A report on the occurrence, progression, and prognostic factors of radiological erosions over the first 3 years in 866 patients from the Early RA Study (ERAS). J. Rheumatol. 69 (Suppl):48–54.Google Scholar
  11. 11.
    Lindqvist E, Eberhardt K, Bendtzen K, Heinegard D, Saxne T. (2005) Prognostic laboratory markers of joint damage in rheumatoid arthritis. Ann. Rheum. Dis. 64:196–201.CrossRefGoogle Scholar
  12. 12.
    van Zeben D, Breedveld FC. (1996) Prognostic factors in rheumatoid arthritis. J. Rheumatol. 44(Suppl):31–3.Google Scholar
  13. 13.
    Aune TM, Maas K, Parker J, Moore JH, Olsen NJ. (2004) Profiles of gene expression in human autoimmune disease. Cell Biochem. Biophys. 40:81–96.CrossRefGoogle Scholar
  14. 14.
    Mandel M, Gurevich M, Pauzner R, Kaminski N, Achiron A. (2004) Autoimmunity gene expression portrait: specific signature that intersects or differentiates between multiple sclerosis and systemic lupus erythematosus. Clin. Exp. Immunol. 138:164–70.CrossRefGoogle Scholar
  15. 15.
    Qing X, Putterman C. (2004) Gene expression profiling in the study of the pathogenesis of systemic lupus erythematosus. Autoimmun. Rev. 3:505–9.CrossRefGoogle Scholar
  16. 16.
    Rus V et al. (2004) Gene expression profiling in peripheral blood mononuclear cells from lupus patients with active and inactive disease. Clin. Immunol. 112:231–4.CrossRefGoogle Scholar
  17. 17.
    van’t Veer LJ et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415:530–6.CrossRefGoogle Scholar
  18. 18.
    Arnett FC et al. (1988) The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum. 31:315–24.CrossRefGoogle Scholar
  19. 19.
    Clancy BM et al. (2003) A gene expression profile for endochondral bone formation: oligonucleotide microarrays establish novel connections between known genes and BMP-2-induced bone formation in mouse quadriceps. Bone 33:46–63.CrossRefGoogle Scholar
  20. 20.
    Hill AA, Brown EL, Whitley MZ, Tucker-Kellogg G, Hunter CP, Slonim DK. (2001) Evaluation of normalization procedures for oligonucleotide array data based on spiked cRNA controls. Genome. Biol. 2:RESEARCH0055.Google Scholar
  21. 21.
    Chiang DY, Brown PO, Eisen MB. (2001) Visualizing associations between genome sequences and gene expression data using genome-mean expression profiles. Bioinformatics 17(Suppl 1):S49–55.CrossRefGoogle Scholar
  22. 22.
    Welch BL. (1951) On the comparison of several mean values: an alternative approach. Biometrika 38:330–6.CrossRefGoogle Scholar
  23. 23.
    Benjamini Y, Hochberg Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Royal. Stat. Soc. B 57:289–300.Google Scholar
  24. 24.
    Bonferroni CE. (1935) Il calcolo delle assicurazioni su gruppi di teste. Studi in onore del Professore Salvatore. Rome. p. 11–60.Google Scholar
  25. 25.
    Bonferroni CE. (1936) Teoria statistica delle classi e calcolo delle probabilita. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commerciali di Firenze 8:3–62.Google Scholar
  26. 26.
    Golub TR et al. (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286:531–7.CrossRefGoogle Scholar
  27. 27.
    Jawaheer D et al. (2003) Screening the genome for rheumatoid arthritis susceptibility genes: a replication study and combined analysis of 512 multicase families. Arthritis Rheum. 48:906–16.CrossRefGoogle Scholar
  28. 28.
    Foxwell BM, Bondeson J, Brennan F, Feldmann M. (2000) Adenoviral transgene delivery provides an approach to identifying important molecular processes in inflammation: evidence for heterogeneity in the requirement for NFkappaB in tumor necrosis factor production. Ann. Rheum. Dis. 59 Suppl 1:i54–59.CrossRefGoogle Scholar
  29. 29.
    Keyszer GM et al. (1995) Detection of insulin-like growth factor I and II in synovial tissue specimens of patients with rheumatoid arthritis and osteoarthritis by in situ hybridization. J. Rheumatol. 22:275–81.PubMedGoogle Scholar
  30. 30.
    Ota T, Katsuki I. (1998) Ferritin subunits in sera and synovial fluids from patients with rheumatoid arthritis. J. Rheumatol. 25:2315–8.PubMedGoogle Scholar
  31. 31.
    Akin E, Aversa J, Steere AC. (2001) Expression of adhesion molecules in synovia of patients with treatment-resistant lyme arthritis. Infect. Immun. 69:1774–80.CrossRefGoogle Scholar
  32. 32.
    Makarov SS. (2001) NF-kappaB in rheumatoid arthritis: a pivotal regulator of inflammation, hyperplasia, and tissue destruction. Arthritis Res. 3:200–6.CrossRefGoogle Scholar
  33. 33.
    Sumariwalla PF, Malfait AM, Feldmann M. (2004) P-selectin glycoprotein ligand 1 therapy ameliorates established collagen-induced arthritis in DBA/1 mice partly through the suppression of tumor necrosis factor. Clin. Exp. Immunol. 136:67–75.CrossRefGoogle Scholar
  34. 34.
    Brennan FM, Gibbons DL, Mitchell T, Cope AP, Maini RN, Feldmann M. (1992) Enhanced expression of tumor necrosis factor receptor mRNA and protein in mononuclear cells isolated from rheumatoid arthritis synovial joints. Eur. J. Immunol. 22:1907–12.CrossRefGoogle Scholar
  35. 35.
    Brennan FM, Gibbons DL, Cope AP, Katsikis P, Maini RN, Feldmann M. (1995) TNF inhibitors are produced spontaneously by rheumatoid and osteoarthritic synovial joint cell cultures: evidence of feedback control of TNF action. Scand. J. Immunol. 42:158–65.CrossRefGoogle Scholar
  36. 36.
    Cope AP et al. (1993) Differential regulation of tumor necrosis factor receptors (TNF-R) by IL-4; upregulation of P55 and P75 TNF-R on synovial joint mononuclear cells. Cytokine 5:205–12.CrossRefGoogle Scholar
  37. 37.
    Shealy DJ. et al. (2002) Anti-TNF-alpha antibody allows healing of joint damage in polyarthritic transgenic mice. Arthritis Res. 4:R7.CrossRefGoogle Scholar
  38. 38.
    Williams RO, Feldmann M, Maini RN. (1992) Anti-tumor necrosis factor ameliorates joint disease in murine collagen-induced arthritis. Proc. Natl. Acad. Sci. U. S. A. 89:9784–8.CrossRefGoogle Scholar
  39. 39.
    Boiardi L, Macchioni P, Meliconi R, Pulsatelli L, Facchini A, Salvarani C. (1999) Relationship between serum RANTES levels and radiological progression in rheumatoid arthritis patients treated with methotrexate. Clin. Exp. Rheumatol. 17:419–25.PubMedGoogle Scholar
  40. 40.
    Barnes DA et al. (1998) Polyclonal antibody directed against human RANTES ameliorates disease in the Lewis rat adjuvant-induced arthritis model. J. Clin. Invest. 101:2910–9.CrossRefGoogle Scholar
  41. 41.
    Firestein GS. NF-kappaB: Holy Grail for rheumatoid arthritis? (2004) Arthritis Rheum. 50:2381–6.CrossRefGoogle Scholar
  42. 42.
    Tedder TF, Steeber DA, Chen A, Engel P. (1995) The selectins: vascular adhesion molecules. FASEB. J. 9:866–73.CrossRefGoogle Scholar
  43. 43.
    Hosaka S, Shah MR, Pope RM, Koch AE. (1996) Soluble forms of P-selectin and intercellular adhesion molecule-3 in synovial fluids. Clin. Immunol. Immunopathol. 78:276–82.CrossRefGoogle Scholar
  44. 44.
    Bullard DC et al. (1999) Acceleration and increased severity of collagen-induced arthritis in P-selectin mutant mice. J. Immunol. 163:2844–9.PubMedGoogle Scholar
  45. 45.
    Utku N et al. (1998) Prevention of acute allograft rejection by antibody targeting of TIRC7, a novel T cell membrane protein. Immunity 9:509–18.CrossRefGoogle Scholar
  46. 46.
    Utku N, Boerner A, Tomschegg A, Bennai-Sanfourche F, Bulwin GC, Heinemann T, Loehler J, Blumberg RS, Volk HD. (2004) TIRC7 deficiency causes in vitro and in vivo augmentation of T and B cell activation and cytokine response. J. Immunol. 15:2342–52CrossRefGoogle Scholar
  47. 47.
    Tomlinson MG, Heath VL, Turck CW, Watson SP, Weiss A. (2004) SHIP family inositol phosphatases interact with and negatively regulate the Tec tyrosine kinase. J. Biol. Chem. 279:55089–96.CrossRefGoogle Scholar
  48. 48.
    Aguado B, Campbell RD. (1998) Characterization of a human lysophosphatidic acid acyltransferase that is encoded by a gene located in the class III region of the human major histocompatibility complex. J. Biol. Chem. 273:4096–105.CrossRefGoogle Scholar
  49. 49.
    West J et al. (1997) Cloning and expression of two human lysophosphatidic acid acyltransferase cDNAs that enhance cytokine-induced signaling responses in cells. DNA. Cell. Biol. 16:691–701.CrossRefGoogle Scholar
  50. 50.
    Adachi H, Tsujimoto M. (2002) FEEL-1, a novel scavenger receptor with in vitro bacteria-binding and angiogenesis-modulating activities. J. Biol. Chem. 277:34264–70.CrossRefGoogle Scholar
  51. 51.
    Tamura Y et al. (2003) FEEL-1 and FEEL-2 are endocytic receptors for advanced glycation end products. J. Biol. Chem. 278:12613–7.CrossRefGoogle Scholar
  52. 52.
    Salmi M, Koskinen K, Henttinen T, Elima K, Jalkanen S. (2004) CLEVER-1 mediates lymphocyte transmigration through vascular and lymphatic endothelium. Blood 104:3849–57.CrossRefGoogle Scholar
  53. 53.
    Devauchelle V et al. (2004) DNA microarray allows molecular profiling of rheumatoid arthritis and identification of pathophysiological targets. Genes. Immun. 5:597–608.CrossRefGoogle Scholar
  54. 54.
    Watanabe N et al. (2002) Gene expression profile analysis of rheumatoid synovial fibroblast cultures revealing the overexpression of genes responsible for tumor-like growth of rheumatoid synovium. Biochem. Biophys. Res. Commun. 294:1121–9.CrossRefGoogle Scholar
  55. 55.
    van der Pouw Kraan TC, van Gaalen FA, Huizinga TW, Pieterman E, Breedveld FC, Verweij CL. (2003) Discovery of distinctive gene expression profiles in rheumatoid synovium using cDNA microarray technology: evidence for the existence of multiple pathways of tissue destruction and repair. Genes. Immun. 4:187–96.CrossRefGoogle Scholar
  56. 56.
    Bovin LF et al. (2004) Blood cell gene expression profiling in rheumatoid arthritis: discriminative genes and effect of rheumatoid factor. Immunol. Lett. 93:217–26.CrossRefGoogle Scholar
  57. 57.
    Olsen N et al. (2004) A gene expression signature for recent onset rheumatoid arthritis in peripheral blood mononuclear cells. Ann. Rheum. Dis. 63:1387–92.CrossRefGoogle Scholar
  58. 58.
    Maas K et al. (2002) Cutting edge: molecular portrait of human autoimmune disease. J. Immunol. 169:5–9.CrossRefGoogle Scholar
  59. 59.
    Hirano T. et al. (2000) Comparative study of lymphocyte-suppressive potency between prednisolone and methylprednisolone in rheumatoid arthritis. Immunopharmacology 49:411–7.CrossRefGoogle Scholar
  60. 60.
    Schulze-Koops H, Lipsky PE, Kavanaugh AF, Davis LS. (1996) Persistent reduction in IL-6 mRNA in peripheral blood mononuclear cells of patients with rheumatoid arthritis after treatment with a monoclonal antibody to CD54 (ICAM-1). Clin. Exp. Immunol. 106:190–6.CrossRefGoogle Scholar
  61. 61.
    Schulze-Koops H, Davis LS, Kavanaugh AF, Lipsky PE. (1997) Elevated cytokine messenger RNA levels in the peripheral blood of patients with rheumatoid arthritis suggest different degrees of myeloid cell activation. Arthritis Rheum. 40:639–47.CrossRefGoogle Scholar

Copyright information

© Feinstein Institute for Medical Research 2007

Authors and Affiliations

  • Christopher J. Edwards
    • 1
    • 2
  • Jeffrey L. Feldman
    • 3
  • Jonathan Beech
    • 1
  • Kathleen M. Shields
    • 3
  • Jennifer A. Stover
    • 5
  • William L. Trepicchio
    • 4
  • Glenn Larsen
    • 6
  • Brian M. J. Foxwell
    • 1
  • Fionula M. Brennan
    • 1
  • Marc Feldmann
    • 1
  • Debra D. Pittman
    • 3
  1. 1.The Kennedy Institute of Rheumatology DivisionImperial College School of MedicineLondonUK
  2. 2.Department of RheumatologySouthampton General HospitalSouthamptonUK
  3. 3.Department of Cardiovascular and Metabolic DiseasesWyeth ResearchCambridgeUSA
  4. 4.Millennium PharmaceuticalsCambridgeUSA
  5. 5.AffymetrixSanta ClaraUSA
  6. 6.Hydra BiosciencesCambridgeUSA

Personalised recommendations