Preview

Научно-практическая ревматология

Расширенный поиск

Современные подходы к лабораторной диагностике ревматических заболеваний: роль молекулярных и клеточных биомаркеров

https://doi.org/10.14412/1995-4484-2016-324-338

Полный текст:

Аннотация

Достижения лабораторной медицины начала XXI в., обусловленные разработкой и быстрым внедрением в практику инновационных молекулярно-клеточных технологий, способствовали увеличению диагностической чувствительности и специфичности лабораторных тестов и существенному расширению спектра исследуемых биомаркеров в ревматологии. В последнее десятилетие для определения биомаркеров ревматических заболеваний (РЗ) в крови, синовиальной жидкости, моче, биоптатах синовиальной оболочки, почек и других пораженных тканей применяют высокотехнологичные автоматизированные аналитические системы с использованием как «классических» униплексных методов иммунохимического анализа (непрямая реакция иммунофлюоресценции, иммуноферментный анализ, иммуноблот, иммунодот, иммунонефелометрия, хемилюминесцентный иммунный анализ, радиоиммуноанализ), так и мультиплексных диагностических платформ на основе ДНК-, РНК-, белковых и клеточных микрочипов, полимеразной цепной реакции, проточной цитометрии, масс-спектрометрии.

Современная генерация молекулярных и клеточных биомаркеров (аутоантитела, острофазовые белки воспаления, цитокины, хемокины, маркеры активации сосудистого эндотелия, иммуноглобулины, компоненты системы комплемента, субпопуляции лимфоцитов, продукты метаболизма костной и хрящевой ткани, внутриклеточные сигнальные молекулы, протеазы, генетические, эпигенетические, транскриптомные маркеры) является важным инструментом для профилактики, ранней диагностики, оценки активности, скорости прогрессирования, клинико-лабораторных субтипов РЗ, прогнозирования эффективности терапии и риска развития нежелательных реакций на фоне лечения.

Расшифровка ключевых патогенетических механизмов РЗ позволила идентифицировать молекулярные и клеточные биомаркеры, которые могут быть использованы в качестве терапевтических «мишеней». В настоящее время для лечения РЗ успешно применяются генно-инженерные биологические препараты (моноклональные антитела и гибридные белковые молекулы), селективно ингибирующие провоспалительные цитокины и мембранные молекулы, опосредующие патологическую активацию иммунокомпетентных клеток. К альтернативным методам терапии РЗ относится использование низкомолекулярных химически синтезированных препаратов, подавляющих активность тирозинкиназ. Важным направлением терапии РЗ является восстановление иммунологической толерантности и коррекция аутоиммунных нарушений с помощью аутологичных гемопоэтических стволовых клеток, мезенхимальных стромальных клеток, аутологичных толерогенных дендритных клеток, Т- и В-регуляторных клеток, генной терапии, пептидных антигенов. Перспективы лабораторной диагностики РЗ связаны с необходимостью гармонизации и стандартизации современных методов определения аутоантител, поиском и клинической валидацией новых протеомных, транскриптомных и геномных биомаркеров.

Об авторах

Е. Н. Александрова
ФГБНУ Научно-исследовательский институт ревматологии им. В.А. Насоновой
Россия
115522 Москва, Каширское шоссе, 34А


А. А. Новиков
ФГБНУ Научно-исследовательский институт ревматологии им. В.А. Насоновой
Россия
115522 Москва, Каширское шоссе, 34А


Е. Л. Насонов
ФГБНУ Научно-исследовательский институт ревматологии им. В.А. Насоновой; ГБОУ ВПО «Первый Московский государственный медицинский университет им. И.М. Сеченова» Минздрава России
Россия

115522 Москва, Каширское шоссе, 34А;

кафедра ревматологии Института профессионального образования,

119991 Москва, ул. Трубецкая, 8, стр. 2



Список литературы

1. Насонов ЕЛ, Александрова ЕН, Новиков АА. Аутоиммунные ревматические заболевания – проблемы иммунопатологии и персонифицированной терапии. Вестник РАМН. 2015;70(2):169-82 [Nasonov EL, Aleksandrova EN, Novikov AA. Autoimmune rheumatic diseases – problems of immunopathology and personalized therapy. Vestnik RAMN. 2015;70(2):169-82 (In Russ.)]. doi: 10.15690/vramn,v70i2.1310

2. Щербо СН. Тенденции развития и технологии современной лабораторной медицины. Лабораторная медицина. 2013;(12):39-44 [Shcherbo SN. Development trends and technologies of modern laboratory medicine. Laboratornaya Meditsina. 2013;(12):39-44 (In Russ.)].

3. Щербо СН, Щербо ДС. Биомаркеры персонализированной медицины. 1. Системная биология и биомаркеры. Медицинский алфавит. Современная лаборатория. 2013;(4):7-9 [Shcherbo SN, Shcherbo DS. Biomarkers for personalized medicine. 1. Systems biology and biomarkers. Meditsinskii Alfavit. Sovremennaya Laboratoriya. 2013;(4):7-9 (In Russ.)].

4. Clinical medicine. Hot research front. Biological sciences. In Research fronts 2014: 100 top ranked specialties in the sciences and social sciences. The National Science Library, Chinese Academy of Sciences. Thomson Reuters IP&Science. The Joint research Center of Emerging Technology Analysis. December 2014:20-8.

5. Tozzoli R, Bonaguri C, Melegari A, et al. Current state of diagnostic technologies in the autoimmunology laboratory. Clin Chem Lab Med. 2013; 51:129-38. doi: 10.1515/cclm-2012-0191

6. Miossec P, Verweij CL, Klareskog L, et al. Biomarkers and personalised medicine in rheumatoid arthritis: a proposal for interactions between academia, industry and regulatory bodies. Ann Rheum Dis. 2011;70:1713-8. doi: 10.1136/ard.2011.154252

7. McInnes IB, Schett G. The pathogenesis of rheumatoid arthritis. N Engl J Med. 2011;365:2205-19. doi: 10.1056/NEJMra1004965

8. Dorner T. Deciphering the role of NETs and networks in SLE. Nat Rev Rheumatol. 2012;8:68-70. doi: 10.1038/nrrheum.2011.200

9. Wahren-Herlenius M, Dö rner T. Immunopathogenic mechanisms of systemic autoimmune disease. Lancet. 2013;382(9894):819-31. doi: 10.1016/S0140-6736(13)60954-X

10. Liu CC, Kao AH, Manzi S, Ahearn JM. Biomarkers in systemic lupus erythematosus: challenges and prospects for the future. Ther Adv Musculosceletal Dis. 2013;5:210-33. doi: 10.1177/1759720X13485503

11. Squatrito D, Emmi G, Silvestri E, et al. Pathogenesis and potential therapeutic targets in systemic lupus erythematosus: from bench to bedside. Auto Immun Highlights. 2014;5:33-45. doi: 10.1007/s13317-014-0058-y

12. Daien CI, Morel J. Predictive factors of response to biological disease modifying antirheumatic drugs: towards personalized medicine. Mediators Inflamm. 2014;2014:386148. doi: 10.1155/2014/386148

13. Damoiseaux J, Andrade LE, Fritzler MJ, Shoenfeld Y. Autoantibodies 2015: From diagnostic biomarkers toward prediction, prognosis and prevention. Autoimmun Rev. 2015;14:555-63. doi: 10.1016/j.autrev.2015.01.017

14. Wang L, Wang FS, Gershwin ME. Human autoimmune diseases: a comprehensive update. J Intern Med. 2015;278:369-95. doi: 10.1111/joim.12395

15. Wener MH. Multiplex, megaplex, index, and complex: the present and future of laboratory diagnostics in rheumatology. Arthritis Res Ther. 2011;13(6):134. doi: 10.1186/ar3498

16. Mease PJ. The potential roles for novel biomarkers in rheumatoid arthritis assessment. Clin Exp Rheumatol. 2011;29(3):567-74. doi: 10.3899/jrheum.100759

17. Новиков АА, Александрова ЕН, Насонов ЕЛ. Протеомные исследования в ревматологии. Научно-практическая ревматология. 2012;50(6):19-24 [Novikov AA, Aleksandrova EN, Nasonov EL. Proteomic studies in rheumatology. Nauchno-Prakticheskaya Revmatologiya = Rheumatology Science and Practice. 2012;50(6):56-62. (In Russ.)]. doi: 10.14412/1995-4484-2012-1295

18. Takakubo Y, Konttinen YT. Immune-regulatory mechanisms in systemic autoimmune and rheumatic diseases. Clin Dev Immunol. 2012;2012:941346. doi: 10.1155/2012/941346

19. Насонов ЕЛ, редактор. Анти-В-клеточная терапия в ревматологии: фокус на ритуксимаб. Москва: ИМА-ПРЕСС; 2012. 344 с. [Nasonov EL, editor. Anti-B-kletochnaya terapiya v revmatologii: fokus na rituksimab [Anti-B-cell therapy in rheumatology: Focus on rituximab]. Moscow: IMA-PRESS; 2012. 344 p.].

20. Насонов ЕЛ, редактор. Генно-инженерные биологические препараты в лечении ревматоидного артрита. Москва: ИМА-ПРЕСС; 2013. 552 с. [Nasonov EL, editor. Genno-inzhenernye biologicheskie preparaty v lechenii revmatoidnogo artrita [Genetically engineered biological agents in the treatment of rheumatoid arthritis]. Moscow: IMA-PRESS; 2013. 552 p.].

21. Насонов ЕЛ, Денисов ЛН, Станислав МЛ. Новые аспекты фармакотерапии ревматоидного артрита: ингибиторы малых молекул. Научно-практическая ревматология. 2012;50(2):66-75 [Nasonov EL, Denisov LN, Stanislav MI. New aspects of pharmacotherapy for rheumatoid arthritis: small molecule inhibitors. Nauchno-Prakticheskaya Revmatologiya = Rheumatology Science and Practice. 2012;50(2):66-75 (In Russ.)]. doi: 10.14412/1995-4484-2012-1276

22. Насонов ЕЛ, Денисов ЛН, Станислав МЛ, Ильина АЕ. Перспективы фармакотерапии ревматоидного артрита: моноклональные антитела. Научно-практическая ревматология. 2012;50(3):75-82 [Nasonov EL, Denisov LN, Stanislav ML, Ilyina AE. Prospects of pharmacotherapy for rheumatoid arthritis: Monoclonal antibodies. Nauchno-Prakticheskaya Revmatologiya = Rheumatology Science and Practice. 2012;50(3):75-82. (In Russ.)]. doi: 10.14412/1995-4484-2012-713

23. Насонов ЕЛ, Соловьев СК. Перспективы фармакотерапии системной красной волчанки. Научно-практическая ревматология. 2014;52(3):311-21 [Nasonov EL, Solovyev SK. Prospects for pharmacotherapy of systemic lupus erythematosus. Nauchno-Prakticheskaya Revmatologiya = Rheumatology Science and Practice. 2014;52(3):311-21 (In Russ.)]. doi: 10.14412/1995-4484-2014-311-321

24. Ананьева ЛП, Алекперов РТ, Насонов ЕЛ. Мезенхимальные клетки костного мозга – перспективы использования при ревматических болезнях. Научно-практическая ревматология. 2013;51(1):59-67 [Ananyeva LP, Alekperov RT, Nasonov EL. Bone marrow mesenchymal cells: Promises for use in rheumatic diseases. Nauchno-Prakticheskaya Revmatologiya = Rheumatology Science and Practice. 2013;51(1):59-67 (In Russ.)]. doi: 10.14412/1995-4484-2013-1203

25. Aletaha D, Neogi T, Silman AS, et al. 2010 rheumatoid arthritis classification criteria. Arthritis Rheum. 2010;62:2569-81. doi: 10.1002/art.27584

26. Petri M, Orbai AM, Alarcon GS, et al. Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus. Arthritis Rheum. 2012;64:2677-86. doi: 10.1002/art.34473

27. Jordan S, Maurer B, Michel B, Distler O. Performance of the new EULAR/ACR classification criteria for systemic sclerosis in clinical practice. Ann Rheum Dis. 2013;72 Suppl 3:60. doi: 10.1093/rheumatology/keu5

28. Shiboski SC, Shiboski CH, Criswell L, et al. American College of Rheumatology classification criteria for Sjögren's syndrome: a data-driven, expert consensus approach in the Sjögren's International Collaborative Clinical Alliance cohort. Arthritis Care Res (Hoboken). 2012;64:475-87. doi: 10.1002/acr.21591

29. Miller FW, Rider LG, Plotz PH, et al. Diagnostic criteria for polymyositis and dermatomyositis. Lancet. 2003;362(9397):1762-3. doi: 10.1016/S0140-6736(03)14862-3

30. Amigues JM, Cantagrel A, Abbal M, Mazieres B. Comparative study of 4 diagnosis criteria sets for mixed connective tissue disease in patients with anti-RNP antibodies. Autoimmunity Group of the Hospitals of Toulouse. J Rheumatol. 1996;23(12):2055-62.

31. Mosca M, Neri R, Bombardieri S. Undifferentiated connective tissue diseases (UCTD): a review of the literature and a proposal for preliminary classification criteria. Clin Exp Rheumatol. 1999;17:615-20.

32. Miyakis S, Lockshin MD, Atsumi T, et al. International consensus statement on an update of the classification criteria for definite antiphospholipid syndrome (APS). J Thromb Haemost. 2006;4:295-306. doi: 10.1111/j.1538-7836.2006.01753.x

33. Watts R, Lane S, Hanslik T, et al. Development and validation of a consensus methodology for the classification of the ANCAassociated vasculitides and polyarteritis nodosa for epidemiological studies. Ann Rheum Dis. 2007;66:222-7. doi: 10.1136/ard.2006.054593

34. Lanham JG, Elkon KB, Pusey CD, Hughes GR. Systemic vasculitis with asthma and eosinophilia: a clinical approach to the Churg-Strauss syndrome. Medicine (Baltimore). 1984;63:65-81. doi: 10.1097/00005792-198403000-00001

35. Lightfoot RW Jr, Michel BA, Bloch DA, et al. The American College of Rheumatology 1990 criteria for the classification of polyarteritis nodosa. Arthritis Rheum. 1990;33:1088-93. doi: 10.1002/art.1780330805

36. Henegar C, Pagnoux C, Puechal X, et al. French Vasculitis Study Group. A paradigm of diagnostic criteria for polyarteritis nodosa: analysis of a series of 949 patients with vasculitides. Arthritis Rheum. 2008;58:1528-38. doi: 10.1002/art.23470

37. Hunder GG, Bloch DA, Michel BA, et al. The American College of Rheumatology 1990 criteria for the classification of giant cell arteritis. Arthritis Rheum. 1990;33:1122-8. doi: 10.1002/art.1780330810

38. De Vita S, Soldano F, Isola M, et al. Preliminary classification criteria for the cryoglobulinaemic vasculitis. Ann Rheum Dis. 2011;70:1183-90. doi: 10.1136/ard.2011.150755

39. Fox RI, Fox CM. IgG4 levels and plasmablasts as a marker for IgG4-related disease (IgG4-RD). Ann Rheum Dis. 2015;74:1-3. doi: 10.1136/annrheumdis-2014-205476

40. Shi J, van Veelen PA, Machler M, et al. Carbamylation and antibodies against carbamylated proteins in autoimmunity and other pathologies. Autoimmune Rev. 2014;13: 225-30. doi: 10.1016/j.autrev.2013.10.008

41. Maksymowych WP, van der Heijde D, Allaart CF. 14-3-3η is a novel mediator associated with the pathogenesis of rheumatoid arthritis and joint damage. Arthr Res Ther. 2014;16:R99. doi: 10.1186/ar4547

42. Cornillet M, Sebbag M, Verrouil E, et al. The fibrin-derived citrullinated peptide β60-74Cit60,72,74 bears the major ACPA epitope recognised by the rheumatoid arthritis-specific anticitrullinated fibrinogen autoantibodies and anti-CCP2 antibodies. Ann Rheum Dis. 2014;73:1246-52. doi: 10.1136/annrheumdis-2012-202868

43. Willemze A, Toes RE, Huizinga TW, Trouw LA. New biomarkers in rheumatoid arthritis. Neth J Med. 2012;70:392-9.

44. Meroni PL, Biggioggero M, Pierangeli SS, et al. Standardization of autoantibody testing: a paradigm for serology in rheumatic diseases. Nat Rev Rheumatol. 2013 Nov 26. doi: 10.1038/nrrheum.2013.180

45. Meroni PL, Schur PH. ANA screening: an old test with new recommendations. Ann Rheum Dis. 2010;69:1420-2. doi: 10.1136/ard.2009.127100

46. Agmon-Levin N, Damoiseaux J, Kallenberg C, et al. International recommendations for the assessment of autoantibodies to cellular antigens referred to as anti-nuclear antibodies. Ann Rheum Dis. 2014;73:17-23. doi: 10.1136/annrheumdis-2013-203863

47. Chan EK, Damoiseaux J, Carballo OG, et al. Report of the First International Consensus on Standardized Nomenclature of Antinuclear Antibody HEp-2 Cell Patterns 2014-2015. Front Immunol. 2015;6:412. doi: 10.3389/fimmu.2015.00412

48. Willitzki A, Hiemann R, Peters V, et al. New platform technology for comprehensive serological diagnostics of autoimmune diseases. Clin Dev Immunol. 2012;2012:284740. doi: 10.1155/2012/284740

49. Satoh M, Tanaka S, Chan EK. The uses and misuses of multiplex autoantibody assays in systemic autoimmune rheumatic diseases. Front Immunol. 2015;6:181. doi: 10.3389/fimmu.2015.00181

50. Arbuckle MR, McClain MT, Rubertone MV, et al. Development of autoantibodies before the clinical onset of systemic lupus erythematosus. New Eng J Med. 2003;349:1526-33. doi: 10.1056/NEJMoa021933

51. Nielen MM, van Schaardenburg D, Reesink HW, et al. Specific autoantibodies precede the symptoms of rheumatoid arthritis: a study of serial measurements in blood donors. Arthritis Rheum. 2004;50:380-6. doi: 10.1002/art.20018

52. Bizzaro N, Tozzoli R, Shoenfeld Y. Are we at a stage to predict autoimmune rheumatic diseases? Arthritis Rheum. 2007;56:1736-44. doi: 10.1002/art.22708

53. Gerlag DM, Raza K, van Baarsen LG, et al. EULAR recommendations for terminology and research in individuals at risk of rheumatoid arthritis: report from the Study Group for Risk Factors for Rheumatoid Arthritis. Ann Rheum Dis. 2012;71:638-41. doi: 10.1136/annrheumdis-2011-200990

54. Jonsson R, Theander E, Sjö ström B, et al. Autoantibodies present before symptom onset in primary Sjögren syndrome. JAMA. 2013;310:1854-5. doi: 10.1001/jama.2013.278448

55. Deane KD, El-Gabalawy H. Pathogenesis and prevention of rheumatic disease: focus on preclinical RA and SLE. Nat Rev Rheumatol. 2014;10:212-28. doi: 10.1038/nrrheum.2014.6

56. Kokkonen H, Soderstrom I, Rocklov J, et al. Up-regulation of cytokines and chemokines predates the onset of rheumatoid arthritis. Arthritis Rheum. 2010;62:383-91. doi: 10.1002/art.27186

57. Jorgensen KT, Wiik A, Pedersen M, et al. Cytokines, autoantibodies and viral antibodies in premorbid and postdiagnostic sera from patients with rheumatoid arthritis: case-control study nested in a cohort of Norwegian blood donors. Ann Rheum Dis. 2008;67:860-6. doi: 10.1136/ard.2007.073825

58. Deane K, O'Donnell C, Hueber W, et al. The number of elevated cytokines and chemokines in preclinical seropositive rheumatoid arthritis predicts time to diagnosis in an agedependent manner. Arthritis Rheum. 2010;62:3161-72. doi: 10.1002/art.27638

59. Nagy G, van Vollenhoven RF. Sustained biologic-free and drugfree remission in rheumatoid arthritis, where are we now? Arthritis Res Ther. 2015;17:181. doi: 10.1186/s13075-015-0707-1

60. Новиков АА, Александрова ЕН, Герасимов АН и др. Многопараметрический анализ биомаркеров в лабораторной диагностике раннего ревматоидного артрита. Научно-практическая ревматология. 2013;51(2):111-6 [Novikov AA, Aleksandrova EN, Gerasimov AN, et al. Multiparameter analysis of biomarkers in the laboratory diagnosis of early rheumatoid arthritis. NauchnoPrakticheskaya Revmatologiya = Rheumatology Science and Practice. 2013;51(2):111-6 (In Russ.)]. doi: 10.14412/1995-4484-2013-636

61. Chandra PE, Sokolove J, Hipp BG, et al. Novel multiplex technology for diagnostic characterization of rheumatoid arthritis. Arthritis Res. Ther. 2011;24;13(3):R102. doi: 10.1186/ar3383

62. Kalunian KC, Chatham WW, Massarotti EM, et al. Measurement of cell-bound complement activation products enhances diagnostic performance in systemic lupus erythematosus. Arthritis Rheum. 2012;64:4040-7. doi: 10.1002/art.34669

63. Bertsias G, Ioannidis JP, Boletis J, et al. EULAR recommendations for the management of systemic lupus erythematosus. Report of a Task Force of the EULAR Standing Committee for International Clinical Studies Including Therapeutics. Ann Rheum Dis. 2008;67:195-205. doi: 10.1136/ard.2007.070367

64. Kallenberg CG. Anti-C1q autoantibodies. Autoimmun Rev. 2008;7(8):612-5. doi: 10.1016/j.autrev.2008.06.006

65. Kemna MJ, Damoiseaux J, Austen J. ANCA as a predictor of relapse: useful in patients with renal involvement but not in patients with non renal disease. J Am Soc Nephrol. 2015;26:537-42. doi: 10.1681/ASN.2013111233

66. Shah AA, Casciola-Rosen L, Rosen A. Review: cancer-induced autoimmunity in the rheumatic diseases. Arthritis Rheum. 2015;67(2):317-26. doi: 10.1002/art.38928

67. Nihtyanova SI, Denton CP. Autoantibodies as predictive tools in systemic sclerosis. Nat Rev Rheumatol. 2010;6:112-6. doi: 10.1038/nrrheum.2009.238

68. Hirschfield GM. Diagnosis of primary biliary cirrhosis. Best Pract Res Clin Gastroenterol. 2011;25:701-12. doi: 10.1016/j.bpg.2011.10.005

69. Kavanaugh AF, Solomon DH. American College of Rheumatology Ad Hoc Committee on Immunologic Testing Guidelines. Guidelines for immunologic laboratory testing in the rheumatic diseases: anti-DNA antibody tests. Arthritis Rheum. 2002;47:546-55. doi: 10.1002/art.10558

70. Oke V, Wahren-Herlenius M. The immunobiology of Ro52 (TRIM21) in autoimmunity: a critical review. J Autoimmun. 2012;39:77-82. doi: 10.1016/j.jaut.2012.01.014

71. Hengstman GJD, van Engelen BGM, Venrooij WJ. Myositis specific autoantibodies: changing insights in pathophysiology and clinical associations. Curr Opin Rheumatol. 2004;16:692-9.

72. Hanly JG, Urowitz MB, Siannis F, et al. Autoantibodies and neuropsychiatric events at the time of systemic lupus erythematosus diagnosis: results from an international inception cohort study. Arthritis Rheum. 2008;58:843-53. doi: 10.1002/art.23218

73. Katz U, Zandman-Goddard G. Drug-induced lupus: an update. Autoimmun Rev. 2010;10:46-50. doi: 10.1016/j.autrev.2010.07.005

74. Gomez-Puerta JA, Burlingame RW, Cervera R. Anti-chromatin (anti-nucleosome) antibodies: diagnostic and clinical value. Autoimmun Rev. 2008;7:606-11. doi: 10.1016/j.autrev.2008.06.005

75. Pickering MC, Botto M. Are anti-C1q antibodies different from other SLE autoantibodies? Nat Rev Rheumatol. 2010;6:490-3. doi: 10.1038/nrrheum.2010.56

76. Mukhtyar C, Flossmann O, Hellmich B, et al. Outcomes from studies of antineutrophil cytoplasm antibody associated vasculitis: a systematic review by the European League Against Rheumatism systemic vasculitis task force. Ann Rheum Dis. 2008;67:1004-10. doi: 10.1136/ard.2007.071936

77. Taylor P, Gartemann J, Hsieh J, Creeden J. A systematic review of serum biomarkers anti-cyclic citrullinated peptide and rheumatoid factor as tests for rheumatoid arthritis. Autoimmune Dis. 2011;2011:815038. doi: 10.4061/2011/815038

78. Dayer E, Dayer JM, Roux-Lombard P. Primer: the practical use of biological markers of rheumatic and systemic inflammatory diseases. Nat Clin Pract Rheumatol. 2007;3:512-20. doi: 10.1038/ncprheum0572

79. Costenbader KH, Chibnik LB, Schur PH. Discordance between erythrocyte sedimentation rate and C-reactive protein measurements: clinical significance. Clin Exp Rheumatol. 2007;25:746-9.

80. Crowson CS, Rahman MU, Matteson EL. Which measure of inflammation to use? A comparison of erythrocyte sedimentation rate and C-reactive protein measurements from randomized clinical trials of golimumab in rheumatoid arthritis. J Rheumatol. 2009;36:1606-10. doi: 10.3899/jrheum.081188

81. Inoue E, Yamanaka H, Hara M, et al. Comparison of Disease Activity Score (DAS)28- erythrocyte sedimentation rate and DAS28- C-reactive protein threshold values. Ann Rheum Dis. 2007;66:407-9. doi: 10.1136/ard.2006.054205

82. Wells G, Becker J, Teng J, et al. Validation of the Disease Activity Score 28 (DAS28) disease progression in patients with rheumatoid arthritis and EULAR response criteria based on CRP against arthritis, and comparison with the DAS28 based on ESR. Ann Rheum Dis. 2009;68:954-60. doi: 10.1136/ard.2007.084459

83. Kay J, Morgacheva O, Messing SP, et al. Clinical disease activity and acute phase reactant levels are discordant among patients with active rheumatoid arthritis: acute phase reactant levels contribute separately to predicting outcome at one year. Arthritis Res Ther. 2014;16(1):R40. doi: 10.1186/ar4469

84. Combe B, Dougados M, Goupille P, et al. Prognostic factors for radiographic damage in early rheumatoid arthritis: a multiparameter prospective study. Arthritis Rheum. 2001;44:1736-43. doi: 10.1002/1529-0131(200108)44:8<1736::AID-ART308>3.0.CO;2-I

85. Pepys MB, Hirschfield GM. C-reactive protein: a critical update. J Clin Invest. 2003;111:1805-12. doi: 10.1172/JCI200318921

86. Cunnane G, Grehan S, Geoghegan S, et al. Serum amyloid A in the assessment of early inflammatory arthritis. J Rheumatol. 2000;27:58-63.

87. Gillmore JD, Lovat LB, Persey MR, et al. Amyloid load and clinical outcome in AA amyloidosis in relation to circulating concentration of serum amyloid A protein. Lancet. 2001;358:24-9. doi: 10.1016/S0140-6736(00)05252-1

88. Abildtrup M, Kingsley GH, Scott DL. Calprotectin as a biomarker for rheumatoid arthritis: a systematic review. J Rheumatol. 2015;42:5. doi: 10.3899/jrheum.140628

89. Scire CA, Cavagna L, Perotti C, et al. Diagnostic value of procalcitonin measurement in febrile patients with systemic autoimmune diseases. Clin Exp Rheum. 2006;24:123-8.

90. Rosario C, Zandman-Goddard G, Meyron-Holtz EG, et al. The hyperferritinemic syndrome: macrophage activation syndrome, Still's disease, septic shock and catastrophic antiphospholipid syndrome. BMC Med. 2013;11:185. doi: 10.1186/1741-7015-11-185

91. Illei GG, Tackey E, Lapteva L, Lipsky PE. Biomarkers in systemic lupus erythematosus: II. Markers of disease activity. Arthritis Rheum. 2004;50:2048-65. doi: 10.1002/art.20345

92. Hueber W, Tomooka BH, Zhao X, et al. Proteomic analysis of secreted proteins in early rheumatoid arthritis: anti-citrulline autoreactivity is associated with up regulation of proinflammatory cytokines. Ann Rheum Dis. 2007;66:712-9. doi: 10.1136/ard.2006.054924

93. Burska A, Boissinot M, Ponchel F. Cytokines as biomarkers in rheumatoid arthritis. Mediators Inflamm. 2014;2014:545493. doi: 10.1155/2014/545493

94. Rioja I, Hughes FJ, Sharp CH, et al. Potential novel biomarkers of disease activity in rheumatoid arthritis patients: CXCL13, CCL23, transforming growth factor alpha, tumor necrosis factor receptor superfamily member 9, and macrophage colony-stimulating factor. Arthritis Rheum. 2008;58:2257-67. doi: 10.1002/art.23667

95. Centola M, Cavet G, Shen Y, et al. Development of a multi-biomarker disease activity test for rheumatoid arthritis. PLoS One. 2013;8(4):e60635. doi: 10.1371/journal.pone.0060635

96. Bakker MF, Cavet G, Jacobs JW, et al. Performance of a multibiomarker score measuring rheumatoid arthritis disease activity in the CAMERA tight control study. Ann Rheum Dis. 2012;71:1692-7. doi: 10.1136/annrheumdis-2011-200963

97. Hirata S, Dirven L, Shen Y, et al. A multi-biomarker score measures rheumatoid arthritis disease activity in the BeSt study. Rheumatology (Oxford). 2013;52:1202-7. doi: 10.1093/rheumatology/kes362

98. Hambardzumyan K, Bolce R, Saevarsdottir S, et al. Pretreatment multi-biomarker disease activity score and radiographic progression in early RA: results from the SWEFOT trial. Ann Rheum Dis. 2015;74:1102-9. doi: 10.1136/annrheumdis-2013-204986

99. Новиков АА, Александрова ЕН, Герасимов АН и др. Применение многопараметрического анализа лабораторных биомаркеров для оценки активности ревматоидного артрита. Научно-практическая ревматология. 2015;53(6):591-5 [Novikov AA, Aleksandrova EN, Gerasimov AN, et al. Use of multiparameter analysis of laboratory biomarkers to assess rheumatoid arthritis activity. Nauchno-Prakticheskaya Revmatologiya=Rheumatology Science and Practice. 2015;53(6):591-5 (In Russ.)]. doi: 10.14412/1995-4484-2015-591-595

100. Bauer JW, Petri M, Batliwalla FM, et al. Interferon-regulated chemokines as biomarkers of systemic lupus erythematosus disease activity: a validation study. Arthritis Rheum. 2009;60:3098-107. doi: 10.1002/art.24803

101. Petri M, Stohl W, Chatham W, et al. Association of plasma B lymphocyte stimulator levels and disease activity in systemic lupus erythematosus. Arthritis Rheum. 2008;58:2453-9. doi: 10.1002/art.23678

102. Chun HY, Chung JW, Kim HA, et al. Cytokine IL-6 and IL-10 as biomarkers in systemic lupus erythematosus. J Clin Immunol. 2007;27:461-6.

103. Korte EA, Gaffney PM, Powell DW. Contributions of mass spectrometry-based proteomics to defining cellular mechanisms and diagnostic markers for systemic lupus erythematosus. Arthritis Res Ther. 2012;14(1):204. doi: 10.1186/ar3701

104. Emery P, Dö rner T. Optimising treatment in rheumatoid arthritis: a review of potential biological markers of response. Ann Rheum Dis. 2011;70:2063-70. doi: 10.1136/ard.2010.148015

105. Isaacs JD, Cohen SB, Emery P, et al. Effect of baseline rheumatoid factor and anticitrullinated peptide antibody serotype on rituximab clinical response: a meta-analysis. Ann Rheum Dis. 2013;72:329-36. doi: 10.1136/annrheumdis-2011-201117

106. Maneiro RJ, Salgado E, Carmona L, Gomez-Reino JJ. Rheumatoid factor as predictor of response to abatacept, rituximab and tocilizumab in rheumatoid arthritis: Systematic review and meta-analysis. Semin Arthritis Rheum. 2013;43:9-17. doi: 10.1016/j.semarthrit.2012.11.007

107. Gottenberg JE, Ravaud P, Cantagrel A, et al. Positivity for anticyclic citrullinated peptide is associated with a better response to abatacept: data from the Orencia and Rheumatoid Arthritis' registry. Ann Rheum Dis. 2012;71:1815-9. doi: 10.1136/annrheumdis-2011-201109

108. Van Dongen H, van Aken J, Lard LR, et al. Efficacy of methotrexate treatment in patients with probable rheumatoid arthritis: a double-blind, randomized, placebo-controlled trial. Arthritis Rheum. 2007;56:1424-32.

109. Visser K, Verpoort KN, van Dongen H, et al. Pretreatment serum levels of anti-cyclic citrullinated peptide antibodies are associated with the response to methotrexate in recent-onset arthritis. Ann Rheum Dis. 2008;67:1194-5. doi: 10.1136/ard.2008.088070

110. Visser K, Goekoop-Ruiterman YP, de Vries-Bouwstra JK, et al. A matrix risk model for the prediction of rapid radiographic progression in patients with rheumatoid arthritis receiving different dynamic treatment strategies: post hoc analyses from the BeSt study. Ann Rheum Dis. 2010;69:1333-7. doi: 10.1136/ard.2009.121160

111. Van der Woude D, Young A, Jayakumar K, et al. Prevalence of and predictive factors for sustained disease-modifying antirheumatic drug-free remission in rheumatoid arthritis: results from two large early arthritis cohorts. Arthritis Rheum. 2009;60:2262-71. doi: 10.1002/art.24661

112. Ng KP, Cambridge G, Leandro MJ, et al. B cell depletion therapy in systemic lupus erythematosus: long-term follow-up and predictors of response. Ann Rheum Dis. 2007;66:1259-62.

113. Van Vollenhoven RF, Petri MA, Cervera R, et al. Belimumab in the treatment of systemic lupus erythematosus: high disease activity predictors of response. Ann Rheum Dis. 2012;71:1343-9. doi: 10.1136/annrheumdis-2011-200937

114. Choi IY, Gerlag DM, Herenius MJ, et al. MRP8/14 serum levels as a strong predictor of response to biological treatments in patients with rheumatoid arthritis. Ann Rheum Dis. 2015;74:499-505. doi: 10.1136/annrheumdis-2013-203923

115. Wijbrandts CA, Dijkgraaf MG, Kraan MC, et al. The clinical response to infliximab in rheumatoid arthritis is in part dependent on pretreatment tumour necrosis factor alpha expression in the synovium. Ann Rheum Dis. 2008;67:1139-44. doi: 10.1136/ard.2007.080440

116. Takeuchi T, Miyasaka N, Tatsuki Y, et al. Baseline tumour necrosis factor alpha levels predict the necessity for dose escalation of infliximab therapy in patients with rheumatoid arthritis. Ann Rheum Dis. 2011;70:1208-15. doi: 10.1136/ard.2011.153023

117. Chen DY, Chen YM, Chen HH, et al. Increasing levels of circulating Th17 cells and interleukin-17 in rheumatoid arthritis patients with an inadequate response to anti-TNF-α therapy. Arthritis Res Ther. 2011;13(4):R126. doi: 10.1186/ar3431

118. Fabre S, Dupuy AM, Dossat N, et al. Protein biochip array technology for cytokine profiling predicts etanercept responsiveness in rheumatoid arthritis. Clin Exp Immunol. 2008;153:188-95. doi: 10.1111/j.1365-2249.2008.03691

119. Ferraccioli G, Tolusso B, Bobbio-Pallavicini F, et al. Biomarkers predictors of good EULAR response to B cell depletion therapy in all seropositive rheumatoid arthritis patients: clues for the pathogenesis. PLoS One. 2012;7(7):e40362. doi: 10.1371/journal.pone.0040362 120. Morozzi G, Fabbroni M, Bellisai F, et al. Low serum level of COMP, a cartilage turnover marker, predicts rapid and high ACR70 response to adalimumab therapy in rheumatoid arthritis. Clin Rheumatol. 2007;26:1335-8. doi: 10.1007/s10067-006-0520-y

120. Gonzalez-Alvaro I, Ortiz AM, Tomero EG, et al. Baseline serum RANKL levels may serve to predict remission in rheumatoid arthritis patients treated with TNF antagonists. Ann Rheum Dis. 2007;66:1675-8. doi: 10.1136/ard.2007.071910

121. Hueber W, Tomooka BH, Batliwalla F, et al. Blood autoantibody and cytokine profiles predict response to anti-tumor necrosis factor therapy in rheumatoid arthritis. Arthritis Res Ther. 2009;11:R76. doi: 10.1186/ar2706

122. Visvanathan S, Rahman MU, Keystone E, et al. Association of serum markers with improvement in clinical response measures after treatment with golimumab in patients with active rheumatoid arthritis despite receiving methotrexate: results from the GO-FORWARD study. Arthritis Res Ther. 2010;12:R211. doi: 10.1186/ar3188

123. Wagner C, Visvanathan S, Braun J, et al. Serum markers associated with clinical improvement in patients with ankylosing spondylitis treated with golimumab. Ann Rheum Dis. 2012;71:674-80. doi: 10.1136/ard.2010.148890

124. Novikov AA, Alexandrova EN, Gerasimov AN, et al. Multi-biomarker scores as predictors of response to biologic therapies in rheumatoid arthritis. Ann Rheum Dis. 2013;72 Suppl 3:203. doi: 10.1136/annrheumdis-2013-eular.650

125. Dass S, Rawstron AC, Vital EM, et al. High sensitivity B cell analysis predicts response to rituximab therapy in rheumatoid arthritis. Arthritis Rheum. 2008;58:2993-9. doi: 10.1002/art.23902

126. Anolik JH, Barnard J, Owen T, et al. Delayed memory B cell recovery in peripheral blood and lymphoid tissue in systemic lupus erythematosus after B cell depletion therapy. Arthritis Rheum. 2007;56:3044-56. doi: 10.1002/art.22810

127. Roll P, Dorner T, Tony HP. Anti-CD20 therapy in patients with rheumatoid arthritis: predictors of response and B cell subset regeneration after repeated treatment. Arthritis Rheum. 2008;58:1566-75. doi: 10.1002/art.23473

128. Sellam J, Abbedd K, Rouanet S, et al. Pre-therapeutic decrease frequency of memory B cell is predictive of response to a first course of rituximab in rheumatoid arthritis patients with inadequate respose or intolerance to anti-TNF: data from the SMART trial. Ann Rheum Dis. 2010;69 Suppl 3:490.

129. Scarsi M, Ziglioli T, Airo P. Baseline numbers of circulating CD28-negative T cells may predict clinical response to abatacept in patients with rheumatoid arthritis. J Rheum. 2011;38:2105-11. doi: 10.3899/jrheum.110386

130. Bansard C, Lequerre T, Daveau M, et al. Can rheumatoid arthritis responsiveness to methotrexate and biologics be predicted? Rheumatology (Oxford). 2009;48:1021-8. doi: 10.1093/rheumatology/kep112

131. Quartuccio L, Lombardi S, Fabris M, et al. Long-term effects of rituximab in rheumatoid arthritis: clinical, biological and pharmacogenetic aspects. Ann N Y Acad Sci. 2009;1173:692-700. doi: 10.1111/j.1749-6632.2009.04668.x

132. Badot V, Galant C, Nzeusseu Toukap A, et al. Gene expression profiling in the synovium identifies a predictive signature of absence of response to adalimumab therapy in rheumatoid arthritis. Arthritis Res Ther. 2009;11:R57. doi: 10.1186/ar2678

133. Thurlings RM, Boumans M, Tekstra J, et al. Relationship between the type I interferon signature and the response to rituximab in rheumatoid arthritis patients. Arthritis Rheum. 2010;62:3607-14. doi: 10.1002/art.27702

134. Sanayama Y, Ikeda K, Saito Y, et al. Prediction of therapeutic responses to tocilizumab in patients with rheumatoid arthritis: biomarkers identified by analysis of gene expression in peripheral blood mononuclear cells using genome-wide DNA microarray. Arthritis Rheumatol. 2014;66:1421-31. doi: 10.1002/art.38400

135. Krintel SB, Dehlendorff C, Hetland ML, et al. Prediction of treatment response to adalimumab: a double-blind placebo-controlled study of circulating microRNA in patients with early rheumatoid arthritis. Pharmacogenomics J. 2016;16:141-6. doi: 10.1038/tpj.2015.30. 2015

136. Krieckaert C, Rispens T, Wolbink G. Immunogenicity of biological therapeutics: from assay to patient. Curr Opin Rheumatol. 2012;24:306-11. doi: 10.1097/BOR.0b013e3283521c4e

137. Vincent FB, Morand EF, Murphy K, et al. Antidrug antibodies (ADAb) to tumour necrosis factor (TNF)-specific neutralising agents in chronic inflammatory diseases: a real issue, a clinical perspective. Ann Rheum Dis. 2013;72:165-78. doi: 10.1136/annrheumdis-2012-202545

138. Jamnitski A, Bartelds GM, Nurmohamed MT, et al. The presence or absence of antibodies to infliximab or adalimumab determines the outcome of switching to etanercept. Ann Rheum Dis. 2011;70:284-8. doi: 10.1136/ard.2010.135111

139. Garces S, Antunes M, Benito-Garcia E, et al. A preliminary algorithm introducing immunogenicity assessment in the management of patients with RA receiving tumour necrosis factor inhibitor therapies. Ann Rheum Dis. 2014;73:1138-43. doi: 10.1136/annrheumdis-2013-203296

140. Chen DY, Chen YM, Tsai WC, et al. Significant associations of antidrug antibody levels with serum drug trough levels and therapeutic response of adalimumab and etanercept treatment in rheumatoid arthritis. Ann Rheum Dis. 2015;74:e16. doi: 10.1136/annrheumdis-2013-203893

141. Van Leeuwen M, Damoiseaux J, Duijvestijn A, Tervaert JW. The therapeutic potential of targeting B cells and anti-oxLDL antibodies in atherosclerosis. Autoimmun Rev. 2009;9:53-7. doi: 10.1016/j.autrev.2009.03.001

142. Witte T. IgM antibodies against dsDNA in SLE. Clin Rev Allergy Immunol. 2008;34:345-7. doi: 10.1007/s12016-007-8046-x

143. Grönwall C, Akhter E, Oh C, et al. IgM autoantibodies to distinct apoptosis-associated antigens correlate with protection from cardiovascular events and renal disease in patients with SLE. Clin Immunol. 2012;142:390-8. doi: 10.1016/j.clim.2012.01.002


Для цитирования:


Александрова Е.Н., Новиков А.А., Насонов Е.Л. Современные подходы к лабораторной диагностике ревматических заболеваний: роль молекулярных и клеточных биомаркеров. Научно-практическая ревматология. 2016;54(3):324-338. https://doi.org/10.14412/1995-4484-2016-324-338

For citation:


Aleksandrova E.N., Novikov A.A., Nasonov E.L. CURRENT APPROACHES TO THE LABORATORY DIAGNOSIS OF RHEUMATIC DISEASES: ROLE OF MOLECULAR AND CELLULAR BIOMARKERS. Rheumatology Science and Practice. 2016;54(3):324-338. (In Russ.) https://doi.org/10.14412/1995-4484-2016-324-338

Просмотров: 483


Creative Commons License
Контент доступен под лицензией Creative Commons Attribution 4.0 License.


ISSN 1995-4484 (Print)
ISSN 1995-4492 (Online)