Biomarker und Bildgebung zur Diagnose und Stratifizierung der rheumatoiden Arthritis und Spondylarthritis im BMBF-Verbund ArthroMark

Biomarkers and imaging for diagnosis and stratification of rheumatoid arthritis and spondylarthritis in the BMBF consortium ArthroMark

Zusammenfassung

Rheumatische Erkrankungen gehören zu den häufigsten chronisch entzündlichen Krankheiten. Neben ausgeprägter Schmerzhaftigkeit und progredienter Gelenkzerstörung reduzieren die rheumatoide Arthritis (RA), die Spondyloarthritiden (SpA) und die Psoriasisarthritis (PsA) die Arbeitsfähigkeit, die Lebensqualität und bei unzureichender Behandlung auch die Lebenserwartung. Seit der Einführung der Biologika zur Therapie dieser Erkrankungen hat die Suche nach geeigneten Biomarkern zur Frühdiagnostik und Vorhersage des Therapieerfolgs zunehmend an Bedeutung gewonnen. Das Hauptziel des Verbundes ArthroMark ist, neue Biomarker zu identifizieren und moderne Bildgebungsverfahren einzusetzen mit dem Ziel, die Diagnose, die Verlaufskontrolle und die Stratifizierung von Patienten mit RA, SpA und PsA zu verbessern. Mit der Entwicklung geeigneter Biomarker für diese Erkrankungen trägt dieses Vorhaben zur Gesundheitsforschung im Bereich chronischer Erkrankungen des Bewegungsapparates bei. Durch die Zusammenarbeit verschiedener nationaler Zentren sollen standortspezifische Ressourcen wie Probenbanken und klinische Studien gemeinsam nutzbar gemacht werden und individuelle Schwerpunkte in der Biomarkeranalyse mit einem entsprechenden Mehrwert vernetzt werden. Gemeinsames Datenmanagement und Vereinheitlichung der Datenerhebung sowie bestmögliche Charakterisierung der Patienten durch neue Bildgebungsmethoden sollen die Qualität der Markerprüfung optimieren.

Abstract

Rheumatic diseases are among the most common chronic inflammatory disorders. Besides severe pain and progressive destruction of the joints, rheumatoid arthritis (RA), spondyloarthritides (SpA) and psoriatic arthritis (PsA) impair working ability, reduce quality of life and if treated insufficiently may enhance mortality. With the introduction of biologics to treat these diseases, the demand for biomarkers of early diagnosis and therapeutic stratification has been growing continuously. The main goal of the consortium ArthroMark is to identify new biomarkers and to apply modern imaging technologies for diagnosis, follow-up assessment and stratification of patients with RA, SpA and PsA. With the development of new biomarkers for these diseases, the ArthroMark project contributes to research in chronic diseases of the musculoskeletal system. The cooperation between different national centers will utilize site-specific resources, such as biobanks and clinical studies for sharing and gainful networking of individual core areas in biomarker analysis. Joint data management and harmonization of data assessment as well as best practice characterization of patients with new imaging technologies will optimize quality of marker validation.

This is a preview of subscription content, access via your institution.

Abb. 1
Abb. 2

Literatur

  1. 1.

    Hoppe B, Dörner T (2012) Coagulation and fibrin network formation: beyond hemostasis and into inflammation. Nat Rev Rheumatol 8:738–746

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Schwedler C, Häupl Th, Kalus U, Blanchard V, Burmester G‑R, Poddubnyy D, Hoppe B (2018) Hypogalactosylation of immunoglobulin G in rheumatoid arthritis: relation to HLADRB1 shared epitope, anti-citrullinated protein antibodies, rheumatoid factor and correlation with inflammatory activity. Arthritis. https://doi.org/10.1186/s13075-018-1540-0

    Google Scholar 

  3. 3.

    Smiljanovic B, Radzikowska A, Kuca-Warnawin E et al (2018) Monocyte alterations in rheumatoid arthritis are dominated by preterm release from bone marrow and prominent triggering in the joint. Ann Rheum Dis 77:300–308

    Article  PubMed  Google Scholar 

  4. 4.

    Smiljanovic B, Stuhlmüller B, Sörensen T et al (2016) Tissue- and cell-specific transcriptomes indicate systemic nature of ra and revealed combinations of protein biomarkers relevant for disease characterisation in serum. Ann Rheum Dis 75:A49–A50

    Article  Google Scholar 

  5. 5.

    Sörensen T, Baumgart S, Durek P et al (2015) immunoClust—an automated analysis pipeline for the identification of immunophenotypic signatures in high-dimensional cytometric datasets. Cytometry A 87:603–615

    Article  PubMed  Google Scholar 

  6. 6.

    Duroux-Richard I, Roubert C, Ammari M, Présumey J, Grün JR, Häupl T, Grützkau A, Lecellier CH, Boitez V, Codogno P, Escoubet J, Pers YM, Jorgensen C, Apparailly F (2016) miR-125b controls monocyte adaptation to inflammation through mitochondrial metabolism and dynamics. Blood 128(26):3125–3136

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Adler J, Baumann M, Voigt B, Scheidt HA, Bhowmik D, Häupl T, Abel B, Madhu PK, Balbach J, Maiti S, Huster D (2016) A detailed analysis of the morphology of fibrils of selectively mutated amyloid β (1–40). Chemphyschem 17(17):2744–2753

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Ge C, Tong D, Liang B, Lönnblom E, Schneider N, Hagert C, Viljanen J, Ayoglu B, Stawikowska R, Nilsson P, Fields GB, Skogh T, Kastbom A, Kihlberg J, Burkhardt H, Dobritzsch D, Holmdahl R (2017) Anti-citrullinated protein antibodies cause arthritis by cross-reactivity to joint cartilage. JCI Insight 2(13):93688

    Article  PubMed  Google Scholar 

  9. 9.

    Budu-Aggrey A, Bowes J, Loehr S, Uebe S, Zervou MI, Helliwell P, Ryan AW, Kane D, Korendowych E, Giardina E, Packham J, McManus R, FitzGerald O, McHugh N, Behrens F, Burkhardt H, Hüffmeier U, Ho P, Martin J, Castañeda S, Goulielmos G, Reis A, Barton A (2016) Replication of a distinct psoriatic arthritis risk variant at the IL23R locus. Ann Rheum Dis 75:1417–1418

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Bowes J, Loehr S, Budu-Aggrey A, Uebe S, Bruce IN, Feletar M, Marzo-Ortega H, Helliwell P, Ryan AW, Kane D, Korendowych E, Alenius GM, Giardina E, Packham J, McManus R, FitzGerald O, Brown MA, Behrens F, Burkhardt H, McHugh N, Hüffmeier U, Ho P, Reis A, Barton A (2015) PTPN22 is associated with susceptibility to psoriatic arthritis but not psoriasis: evidence for a further PsA-specific risk locus. Ann Rheum Dis 74:1882–1885

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Bowes J, Budu-Aggrey A, Hüffmeier U, Uebe S, Steel K, Hebert HL, Wallace C, Massey J, Bruce IN, Bluett J, Feletar M, Morgan AW, Marzo-Ortega H, Donohoe G, Morris DW, Helliwell P, Ryan AW, Kane D, Warren RB, Korendowych E, Alenius GM, Giardina E, Packham J, McManus R, FitzGerald O, McHugh N, Brown MA, Ho P, Behrens F, Burkhardt H, Reis A, Barton A (2015) Dense genotyping of immune-related susceptibility loci reveals new insights into the genetics of psoriatic arthritis. Nat Commun 6:6046

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Poddubnyy D, Haibel H, Listing J, Marker-Hermann E, Zeidler H, Braun J et al (2012) Baseline radiographic damage, elevated acute-phase reactant levels, and cigarette smoking status predict spinal radiographic progression in early axial spondylarthritis. Arthritis Rheum 64(5):1388–1398

    Article  PubMed  Google Scholar 

  13. 13.

    Poddubnyy D, Haibel H, Listing J, Marker-Hermann E, Zeidler H, Braun J et al (2013) Cigarette smoking has a dose-dependent impact on progression of structural damage in the spine in patients with axial spondyloarthritis: results from the GErman SPondyloarthritis Inception Cohort (GESPIC). Ann Rheum Dis 72(8):1430–1432

    Article  PubMed  Google Scholar 

  14. 14.

    Poddubnyy D, Rudwaleit M, Haibel H, Listing J, Marker-Hermann E, Zeidler H et al (2012) Effect of non-steroidal anti-inflammatory drugs on radiographic spinal progression in patients with axial spondyloarthritis: results from the German Spondyloarthritis Inception Cohort. Ann Rheum Dis 71(10):1616–1622

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Poddubnyy D, Conrad K, Haibel H, Syrbe U, Appel H, Braun J et al (2014) Elevated serum level of the vascular endothelial growth factor predicts radiographic spinal progression in patients with axial spondyloarthritis. Ann Rheum Dis 73(12):2137–2143

    CAS  Article  PubMed  Google Scholar 

  16. 16.

    Turina MC, Sieper J, Yeremenko N, Conrad K, Haibel H, Rudwaleit M et al (2014) Calprotectin serum level is an independent marker for radiographic spinal progression in axial spondyloarthritis. Ann Rheum Dis 73(9):1746–1748

    Article  PubMed  Google Scholar 

  17. 17.

    Heiland GR, Appel H, Poddubnyy D, Zwerina J, Hueber A, Haibel H et al (2012) High level of functional dickkopf-1 predicts protection from syndesmophyte formation in patients with ankylosing spondylitis. Ann Rheum Dis 71(4):572–574

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Appel H, Ruiz-Heiland G, Listing J, Zwerina J, Herrmann M, Mueller R et al (2009) Altered skeletal expression of sclerostin and its link to radiographic progression in ankylosing spondylitis. Arthritis Rheum 60(11):3257–3262

    Article  PubMed  Google Scholar 

  19. 19.

    Sewerin P, Vordenbaeumen S, Brinks R, Ostendorf B (2017) Prospective MRI score to predict negative EULAR response in patients with rheumatoid arthritis (RA) before therapy-escalation to a biological therapy. Ann Rheum Dis. https://doi.org/10.1136/annrheumdis-2017-211257

    Google Scholar 

  20. 20.

    Sewerin P et al (2018) Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) predicts DAS-28 therapy response in Rheumatoid Arthritis patients: Results of the German ArthroMark cohort. J Rheumatol. https://doi.org/10.3899/jrheum.170797

    PubMed  Google Scholar 

  21. 21.

    Sewerin P et al (2017) Silent progression in patients with rheumatoid arthritis: is DAS28 remission an insufficient goal in RA? Results from the German Remission-plus cohort. BMC Musculoskelet Disord 18:163

    Article  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Schleich C et al (2015) Evaluation of a simplified version of the Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) comprising 5 joints (RAMRIS5). Clin Exp Rheumatol 33(2):209–215

    PubMed  Google Scholar 

  23. 23.

    Müller-Lutz A et al (2014) Comparison of quantitative and semiquantitative dynamic contrast-enhanced MRI with respect to their correlation to delayed gadolinium-enhanced MRI of the cartilage in patients with early rheumatoid arthritis. J Comput Assist Tomogr. https://doi.org/10.1097/RCT.0000000000000164

    Google Scholar 

  24. 24.

    Sewerin P et al (2018) Dynamic MRI in rheumatoid arthritis for the assessment of synovitis promoting cartilage loss. Skeletal Radiol. (under review)

  25. 25.

    Backhaus M, Ohrndorf S, Kellner H et al (2009) Evaluation of a novel 7‑joint ultrasound score in daily rheumatologic practice: a pilot project. Arthritis Rheum 61:1194–1201

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Werner SG, Langer HE, Ohrndorf S et al (2012) Inflammation assessment in patients with arthritis using a novel in vivo fluorescence optical imaging technology. Ann Rheum Dis 71(4):504–510

    Article  PubMed  Google Scholar 

  27. 27.

    Glimm AM, Werner SG, Burmester GR et al (2016) Analysis of distribution and severity of inflammation in patients with osteoarthritis compared to rheumatoid arthritis by ICG-enhanced fluorescence optical imaging and musculoskeletal ultrasound: a pilot study. Ann Rheum Dis 75:566–570

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Bonin-Andresen M, Smiljanovic B, Stuhlmüller B, Sörensen T, Grützkau A, Häupl T (2018) Die Bedeutung von Big Data für die molekulare Diagnostik. Z Rheumatol 77(3):195–202. https://doi.org/10.1007/s00393-018-0436-3

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Stuhlmüller B, Mans K, Tandon N, Bonin MO, Smiljanovic B, Sörensen TA, Schendel P, Martus P, Listing J, Detert J, Backhaus M, Neumann T, Winchester RJ, Burmester GR, Häupl T (2016) Genomic stratification by expression of HLA-DRB4 alleles identifies differential innate and adaptive immune transcriptional patterns—a strategy to detect predictors of methotrexate response in early rheumatoid arthritis. Clin Immunol 171:50–61

    Article  PubMed  Google Scholar 

  30. 30.

    Mansmann U (2018) Big data from clinical routine. Z Rheumatol. https://doi.org/10.1007/s00393-018-0424-7

    Google Scholar 

  31. 31.

    Haupt S, Söntgerath VS, Leipe J, Schulze-Koops H, Skapenko A (2016) Methylation of an intragenic alternative promoter regulates transcription of GARP. Biochim Biophys Acta 1859:223–234

    CAS  Article  PubMed  Google Scholar 

  32. 32.

    Prots I, Skapenko A, Wendler J, Mattyasovszky S, Yoné CL, Spriewald B, Burkhardt H, Rau R, Kalden JR, Lipsky PE, Schulze-Koops H (2006) Association of the IL4R single-nucleotide polymorphism I50V with rapidly erosive rheumatoid arthritis. Arthritis Rheum 54:1491–1500

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Leipe J, Schramm M, Baeuerle M, Dechant C, Grunke M, Witt M, Nigg A, Reindl C, Schulze-Koops H, Skapenko A (2011) Interleukin-22 serum levels are associated with clinical outcome in rheumatoid arthritis. Ann Rheum Dis 70:1453–1457

    CAS  Article  PubMed  Google Scholar 

  34. 34.

    Witt M, Mueller F, Nigg A, Reindl C, Leipe J, Proft F, Stein N, Hammitzsch A, Mayer S, Dechant C, Schulze-Koops H, Grunke M (2013) Relevance of grade 1 gray-scale ultrasound findings in wrists and small joints to the assessment of subclinical synovitis in rheumatoid arthritis. Arthritis Rheum 65:1694–1701

    Article  PubMed  Google Scholar 

  35. 35.

    Witt M, Mueller F, Weinert P, Nigg AP, Reindl CS, Proft F, Schulze-Koops H, Grunke M (2014) Ultrasound of synovitis in rheumatoid arthritis: advantages of the dorsal over the palmar approach to finger joints. J Rheumatol 41:422–428

    Article  PubMed  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to PD Dr. T. Häupl.

Ethics declarations

Interessenkonflikt

T. Häupl, A. Skapenko, B. Hoppe, K. Skriner, H. Burkhardt, D. Poddubnyy, S. Ohrndorf, P. Sewerin, U. Mansmann, B. Stuhlmüller, H. Schulze-Koops und G.-R. Burmester geben an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Häupl, T., Skapenko, A., Hoppe, B. et al. Biomarker und Bildgebung zur Diagnose und Stratifizierung der rheumatoiden Arthritis und Spondylarthritis im BMBF-Verbund ArthroMark. Z Rheumatol 77, 16–23 (2018). https://doi.org/10.1007/s00393-018-0458-x

Download citation

Schlüsselwörter

  • Rheumatoide Arthritis
  • Spondyloarthritiden
  • Psoriasisarthritis
  • Arbeitsfähigkeit
  • Lebensqualität

Keywords

  • Rheumatoid arthritis
  • Spondyloarthritides
  • Psoriatic arthritis
  • Ability to work
  • Quality of life