Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Advances in biomarkers for paediatric rheumatic diseases

Key Points

  • The search for biomarkers in paediatric rheumatic diseases is attracting increased interest

  • Several biomarkers have potential to predict the clinical phenotype, disease activity, response to treatment and course of disease in juvenile idiopathic arthritis

  • Biomarkers that reflect the degree of activation and expansion of T cells and macrophages could help to identify subclinical macrophage activation syndrome

  • Novel urine biomarkers for childhood lupus nephritis hold promise for facilitating early diagnosis, improving disease monitoring and assessment of response to therapy

  • Myositis-specific autoantibodies define distinct serological subgroups of juvenile idiopathic inflammatory myositis, albeit with similar clinical characteristics

  • The diagnostic power of biomarkers might help to avoid invasive procedures, such as renal biopsy in systemic lupus erythematosus, and muscle biopsy in juvenile dermatomyositis

Abstract

The search for biomarkers in paediatric rheumatic diseases, particularly juvenile idiopathic arthritis (JIA), childhood lupus nephritis (LN), and juvenile idiopathic inflammatory myopathies (JIIMs) is attracting increased interest. In JIA, a number of biomarkers have shown potential for predicting clinical phenotype, disease activity and severity, clinical remission and relapse, response to treatment, and disease course over time. In systemic JIA, measurement of biomarkers that reflect the degree of activation and expansion of T cells and macrophages might be helpful for detecting subclinical macrophage activation syndrome. Urine biomarkers for childhood LN hold promise for facilitating early diagnosis and improving disease monitoring and assessment of response to therapy. Myositis-specific autoantibodies define distinct serological subgroups of JIIMs, albeit with similar clinical features, responses to therapy, and prognoses. Use of biomarkers may potentially help to avoid invasive procedures, such as renal biopsy in systemic lupus erythematosus and muscle biopsy in juvenile dermatomyositis. Incorporation of effective and reliable biomarkers into routine practice might facilitate adoption of a stratified approach to investigation and management, foster the implementation of research into the design of personalized and targeted therapies, and ultimately lead to more rational and effective clinical care.

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

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Biomarkers for use in paediatric rheumatic diseases.
Figure 2: Biomarkers for JIA are associated with inflammatory pathways linked to its pathophysiology.
Figure 3: An overview of noninvasive biomarkers for paediatric lupus nephritis (LN).

Similar content being viewed by others

References

  1. De Gruttola, V. G. et al. Considerations in the evaluation of surrogate endpoints in clinical trials. Summary of a National Institutes of Health workshop. Control Clin. Trials 22, 485–502 (2001).

    Article  CAS  PubMed  Google Scholar 

  2. Ahearn, J. M., Liu, C. C., Kao, A. H. & Manzi, S. Biomarkers for systemic lupus erythematosus. Transl. Res. 159, 326–342 (2012).

    Article  CAS  PubMed  Google Scholar 

  3. Bennett, M. & Brunner, H. I. Biomarkers and updates on pediatric lupus nephritis. Rheum. Dis. Clin. North Am. 39, 833–853 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Klassen, T. P., Hartling, L., Craig, J. C. & Offringa, M. Children are not just small adults: the urgent need for high-quality trial evidence in children. PLoS Med. 5, e172 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Goldman, J., Becker, M. L., Jones, B., Clements, M. & Leeder, J. S. Development of biomarkers to optimize pediatric patient management: what makes children different? Biomark. Med. 5, 781–794 (2011).

    Article  CAS  PubMed  Google Scholar 

  6. Duurland, C. L. & Wedderburn, L. R. Current developments in the use of biomarkers for juvenile idiopathic arthritis. Curr. Rheumatol. Rep. 16, 406 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Petty, R. E. et al. International League of Associations for Rheumatology classification of juvenile idiopathic arthritis: second revision, Edmonton, 2001. J. Rheumatol. 31, 390–392 (2004).

    PubMed  Google Scholar 

  8. Ravelli, A. & Martini, A. Juvenile idiopathic arthritis. Lancet 369, 767–778 (2007).

    Article  CAS  PubMed  Google Scholar 

  9. Prakken, B., Albani, S. & Martini, A. Juvenile idiopathic arthritis. Lancet 377, 2138–2149 (2011).

    Article  PubMed  Google Scholar 

  10. Southwood, T. R. & Ryder, C. A. Ophthalmological screening in juvenile arthritis: should the frequency of screening be based on the risk of developing chronic iridocyclitis? Br. J. Rheumatol. 31, 633–634 (1992).

    Article  CAS  PubMed  Google Scholar 

  11. American Academy of Pediatrics Section on Rheumatology and Section on Ophthalmology: Guidelines for ophthalmologic examinations in children with juvenile rheumatoid arthritis. Pediatrics 92, 295–296 (1993).

  12. Cassidy, J., Kivlin, J., Lindsley, C. & Nocton, J. Ophthalmologic examinations in children with juvenile rheumatoid arthritis. Pediatrics 117, 1843–1845 (2006).

    Article  PubMed  Google Scholar 

  13. Heiligenhaus, A., Niewerth, M., Ganser, G., Heinz, C. & Minden, K. Prevalence and complications of uveitis in juvenile idiopathic arthritis in a population-based nation-wide study in Germany: suggested modification of the current screening guidelines. Rheumatology (Oxford) 46, 1015–1019 (2007).

    Article  CAS  Google Scholar 

  14. Calandra, S. et al. Female sex and oligoarthritis category are not risk factors for uveitis in Italian children with juvenile idiopathic arthritis. J. Rheumatol. 41, 1416–1425 (2014).

    Article  PubMed  Google Scholar 

  15. Hunter, P. J. et al. Biologic predictors of extension of oligoarticular juvenile idiopathic arthritis as determined from synovial fluid cellular composition and gene expression. Arthritis Rheum. 62, 896–907 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Gibson, D. S. et al. Stratification and monitoring of juvenile idiopathic arthritis patients by synovial proteome analysis. J. Proteome Res. 8, 5601–5609 (2009).

    Article  CAS  PubMed  Google Scholar 

  17. Myles, A. & Aggarwal, A. Expression of Toll-like receptors 2 and 4 is increased in peripheral blood and synovial fluid monocytes of patients with enthesitis-related arthritis subtype of juvenile idiopathic arthritis. Rheumatology (Oxford) 50, 481–488 (2011).

    Article  CAS  Google Scholar 

  18. Viswanath, V., Myles, A., Dayal, R. & Aggarwal, A. Levels of serum matrix metalloproteinase-3 correlate with disease activity in the enthesitis-related arthritis category of juvenile idiopathic arthritis. J. Rheumatol. 38, 2482–2487 (2011).

    Article  CAS  PubMed  Google Scholar 

  19. Aoki, C. et al. Discrepancy between clinical and radiological responses to tocilizumab treatment in patients with systemic-onset juvenile idiopathic arthritis. J. Rheumatol. 41, 1171–1177 (2014).

    Article  CAS  PubMed  Google Scholar 

  20. Foell, D. & Roth, J. Proinflammatory S100 proteins in arthritis and autoimmune disease. Arthritis Rheum. 50, 3762–3771 (2004).

    Article  CAS  PubMed  Google Scholar 

  21. Holzinger, D. et al. The Toll-like receptor 4 agonist MRP8/14 protein complex is a sensitive indicator for disease activity and predicts relapses in systemic-onset juvenile idiopathic arthritis. Ann. Rheum. Dis. 71, 974–980 (2012).

    Article  CAS  PubMed  Google Scholar 

  22. Vastert, S. & Prakken, B. Update on research and clinical translation on specific clinical areas: from bench to bedside: how insight in immune pathogenesis can lead to precision medicine of severe juvenile idiopathic arthritis. Best. Pract. Res. Clin. Rheumatol. 28, 229–246 (2014).

    Article  PubMed  Google Scholar 

  23. de Jager, W. et al. Blood and synovial fluid cytokine signatures in patients with juvenile idiopathic arthritis: a cross-sectional study. Ann. Rheum. Dis. 66, 589–598 (2007).

    Article  CAS  PubMed  Google Scholar 

  24. Lotito, A. P., Campa, A., Silva, C. A., Kiss, M. H. & Mello, S. B. Interleukin 18 as a marker of disease activity and severity in patients with juvenile idiopathic arthritis. J. Rheumatol. 34, 823–830 (2007).

    CAS  PubMed  Google Scholar 

  25. Ling, X. B. et al. Urine peptidomic and targeted plasma protein analyses in the diagnosis and monitoring of systemic juvenile idiopathic arthritis. Clin. Proteomics 6, 175–193 (2010).

    Article  CAS  PubMed  Google Scholar 

  26. Scott, C. et al. A reappraisal of intra-articular corticosteroid therapy in juvenile idiopathic arthritis. Clin. Exp. Rheumatol. 28, 774–781 (2010).

    CAS  PubMed  Google Scholar 

  27. Lanni, S. et al. Outcome and predicting factors of single and multiple intra-articular corticosteroid injections in children with juvenile idiopathic arthritis. Rheumatology (Oxford) 50, 1627–1634 (2011).

    Article  CAS  Google Scholar 

  28. Vilca, I. et al. Predictors of poor response to methotrexate in polyarticular-course juvenile idiopathic arthritis: analysis of the PRINTO methotrexate trial. Ann. Rheum. Dis. 69, 1479–1483 (2010).

    Article  CAS  PubMed  Google Scholar 

  29. Papsdorf, V. & Horneff, G. Complete control of disease activity and remission induced by treatment with etanercept in juvenile idiopathic arthritis. Rheumatology (Oxford) 50, 214–221 (2011).

    Article  CAS  Google Scholar 

  30. Otten, M. H. et al. Factors associated with treatment response to etanercept in juvenile idiopathic arthritis. JAMA 306, 2340–2347 (2011).

    Article  CAS  PubMed  Google Scholar 

  31. Solari, N. et al. Factors associated with achievement of inactive disease in children with juvenile idiopathic arthritis treated with etanercept. J. Rheumatol. 40, 192–200 (2013).

    Article  CAS  PubMed  Google Scholar 

  32. Gattorno, M. et al. The pattern of response to anti-interleukin-1 treatment distinguishes two subsets of patients with systemic-onset juvenile idiopathic arthritis. Arthritis Rheum. 58, 1505–1515 (2008).

    Article  CAS  PubMed  Google Scholar 

  33. Moncrieffe, H. et al. A subgroup of juvenile idiopathic arthritis patients who respond well to methotrexate are identified by the serum biomarker MRP8/14 protein. Rheumatology (Oxford) 52, 1467–1476 (2013).

    Article  CAS  Google Scholar 

  34. Vastert, S. J. et al. Effectiveness of first-line treatment with recombinant interleukin-1 receptor antagonist in steroid-naive patients with new-onset systemic juvenile idiopathic arthritis: results of a prospective cohort study. Arthritis Rheumatol. 66, 1034–1043 (2014).

    Article  CAS  PubMed  Google Scholar 

  35. Foell, D. et al. Methotrexate withdrawal at 6 vs 12 months in juvenile idiopathic arthritis in remission: a randomized clinical trial. JAMA 303, 1266–1273 (2010).

    Article  CAS  PubMed  Google Scholar 

  36. Gerss, J. et al. Phagocyte-specific S100 proteins and high-sensitivity C reactive protein as biomarkers for a risk-adapted treatment to maintain remission in juvenile idiopathic arthritis: a comparative study. Ann. Rheum. Dis. 71, 1991–1997 (2012).

    Article  CAS  PubMed  Google Scholar 

  37. Rothmund, F. et al. Validation of relapse risk biomarkers for routine use in patients with juvenile idiopathic arthritis. Arthritis Care Res. (Hoboken) 66, 949–955 (2013).

    Article  CAS  Google Scholar 

  38. Ravelli, A., Grom, A. A., Behrens, E. M. & Cron, R. Q. Macrophage activation syndrome as part of systemic juvenile idiopathic arthritis: diagnosis, genetics, pathophysiology and treatment. Genes Immun. 13, 289–298 (2012).

    Article  CAS  PubMed  Google Scholar 

  39. Behrens, E. M., Beukelman, T., Paessler, M. & Cron, R. Q. Occult macrophage activation syndrome in patients with systemic juvenile idiopathic arthritis. J. Rheumatol. 34, 1133–1138 (2007).

    PubMed  Google Scholar 

  40. Bleesing, J. et al. The diagnostic significance of soluble CD163 and soluble interleukin-2 receptor α-chain in macrophage activation syndrome and untreated new-onset systemic juvenile idiopathic arthritis. Arthritis Rheum. 56, 965–971 (2007).

    Article  CAS  PubMed  Google Scholar 

  41. Ho, C. et al. Marrow assessment for haemophagocytic lymphohistiocytosis demonstrates poor correlation with disease probability. Am. J. Clin. Pathol. 141, 62–71 (2014).

    Article  PubMed  Google Scholar 

  42. Ravelli, A. et al. Preliminary diagnostic guidelines for macrophage activation syndrome complicating systemic juvenile idiopathic arthritis. J. Pediatr. 146, 598–604 (2005).

    Article  PubMed  Google Scholar 

  43. Minoia, F. et al. Development of new classification criteria for macrophage activation syndrome complicating systemic juvenile idiopathic arthritis [abstract]. Pediatr. Rheumatol. 12 (Suppl. 1) O1 (2014).

    Article  Google Scholar 

  44. Reddy, V. V., Myles, A., Cheekatla, S. S., Singh, S. & Aggarwal, A. Soluble CD25 in serum: a potential marker for subclinical macrophage activation syndrome in patients with active systemic onset juvenile idiopathic arthritis. Int. J. Rheum. Dis. 17, 261–267 (2014).

    Article  CAS  PubMed  Google Scholar 

  45. Gorelik, M. et al. Follistatin-like protein 1 and the ferritin/erythrocyte sedimentation rate ratio are potential biomarkers for dysregulated gene expression and macrophage activation syndrome in systemic juvenile idiopathic arthritis. J. Rheumatol. 40, 1191–1199 (2013).

    Article  CAS  PubMed  Google Scholar 

  46. Shimizu, M., Nakagishi, Y. & Yachie, A. Distinct subsets of patients with systemic juvenile idiopathic arthritis based on their cytokine profiles. Cytokine 61, 345–348 (2013).

    Article  CAS  PubMed  Google Scholar 

  47. Gracie, J. A., Robertson, S. E. & McInnes, I. B. Interleukin-18. J. Leukoc. Biol. 73, 213–224 (2003).

    Article  CAS  PubMed  Google Scholar 

  48. McInnes, I. B., Gracie, J. A., Leung, B. P., Wei, X. Q. & Liew, F. Y. Interleukin 18: a pleiotropic participant in chronic inflammation. Immunol. Today 21, 312–315 (2000).

    Article  CAS  PubMed  Google Scholar 

  49. de Jager, W. et al. Defective phosphorylation of interleukin-18 receptor β causes impaired natural killer cell function in systemic-onset juvenile idiopathic arthritis. Arthritis Rheum. 60, 2782–2793 (2009).

    Article  CAS  PubMed  Google Scholar 

  50. Lattanzi, B. & Ravelli, A. in Textbook of Clinical Pediatrics (eds Elzouki, A. Y. et al.), 1629–1641 (Springer, 2012).

    Book  Google Scholar 

  51. Weening, J. J. et al. The classification of glomerulonephritis in systemic lupus erythematosus revisited. J. Am. Soc. Nephrol. 15, 241–250 (2004).

    Article  PubMed  Google Scholar 

  52. Rovin, B. H., Birmingham, D. J., Nagaraja, H. N., Yu, C. Y. & Hebert, L. A. Biomarker discovery in human SLE nephritis. Bull. NYU Hosp. Jt. Dis. 65, 187–193 (2007).

    PubMed  Google Scholar 

  53. Batal, I. et al. Prospective assessment of C4d deposits on circulating cells and renal tissues in lupus nephritis: a pilot study. Lupus 21, 13–26 (2012).

    Article  CAS  PubMed  Google Scholar 

  54. Dhir, V. Is cellular C4d a good biomarker for SLE nephritis? Lupus 21, 1036 (2012).

    Article  CAS  PubMed  Google Scholar 

  55. Edelbauer, M. et al. Markers of childhood lupus nephritis indicating disease activity. Pediatr. Nephrol. 26, 401–410 (2011).

    Article  PubMed  Google Scholar 

  56. Hewitt, S. M., Dear, J. & Star, R. A. Discovery of protein biomarkers for renal diseases. J. Am. Soc. Nephrol. 15, 1677–1689 (2004).

    Article  PubMed  Google Scholar 

  57. Rovin, B. H. The chemokine network in systemic lupus erythematous nephritis. Front. Biosci. 13, 904–922 (2008).

    Article  CAS  PubMed  Google Scholar 

  58. Rovin, B. H. et al. Urine chemokines as biomarkers of human systemic lupus erythematosus activity. J. Am. Soc. Nephrol. 16, 467–473 (2005).

    Article  CAS  PubMed  Google Scholar 

  59. Kiani, A. N. et al. Urine osteoprotegerin and monocyte chemoattractant protein-1 in lupus nephritis. J. Rheumatol. 36, 2224–2230 (2009).

    Article  CAS  PubMed  Google Scholar 

  60. Tucci, M. et al. Strong association of a functional polymorphism in the monocyte chemoattractant protein 1 promoter gene with lupus nephritis. Arthritis Rheum. 50, 1842–1849 (2004).

    Article  CAS  PubMed  Google Scholar 

  61. Watson, L. et al. Urinary monocyte chemoattractant protein 1 and α 1 acid glycoprotein as biomarkers of renal disease activity in juvenile-onset systemic lupus erythematosus. Lupus 21, 496–501 (2012).

    Article  CAS  PubMed  Google Scholar 

  62. Wu, T. et al. Elevated urinary VCAM-1, P-selectin, soluble TNF receptor-1, and CXC chemokine ligand 16 in multiple murine lupus strains and human lupus nephritis. J. Immunol. 179, 7166–7175 (2007).

    Article  CAS  PubMed  Google Scholar 

  63. Graves, D. T., Alsulaimani, F., Ding, Y. & Marks, S. C. Jr. Developmentally regulated monocyte recruitment and bone resorption are modulated by functional deletion of the monocytic chemoattractant protein-1 gene. Bone 31, 282–287 (2002).

    Article  CAS  PubMed  Google Scholar 

  64. Zhang, X. et al. Biomarkers of lupus nephritis determined by serial urine proteomics. Kidney Int. 74, 799–807 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Tian, S. et al. Urinary levels of RANTES and M-CSF are predictors of lupus nephritis flare. Inflamm. Res. 56, 304–310 (2007).

    Article  CAS  PubMed  Google Scholar 

  66. Chan, R. W. et al. The effect of immunosuppressive therapy on the messenger RNA expression of target genes in the urinary sediment of patients with active lupus nephritis. Nephrol. Dial. Transplant. 21, 1534–1540 (2006).

    Article  CAS  PubMed  Google Scholar 

  67. Gwira, J. A. et al. Expression of neutrophil gelatinase-associated lipocalin regulates epithelial morphogenesis in vitro. J. Biol. Chem. 280, 7875–7882 (2005).

    Article  CAS  PubMed  Google Scholar 

  68. Brunner, H. I. et al. Urinary neutrophil gelatinase-associated lipocalin as a biomarker of nephritis in childhood-onset systemic lupus erythematosus. Arthritis Rheum. 54, 2577–2584 (2006).

    Article  CAS  PubMed  Google Scholar 

  69. Watson, L. et al. Urine biomarkers for monitoring juvenile lupus nephritis: a prospective longitudinal study. Pediatr. Nephrol. 29, 397–405 (2014).

    Article  PubMed  Google Scholar 

  70. Hinze, C. H. et al. Neutrophil gelatinase-associated lipocalin is a predictor of the course of global and renal childhood-onset systemic lupus erythematosus disease activity. Arthritis Rheum. 60, 2772–2781 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Suzuki, M. et al. Neutrophil gelatinase-associated lipocalin as a biomarker of disease activity in pediatric lupus nephritis. Pediatr. Nephrol. 23, 403–412 (2008).

    Article  PubMed  Google Scholar 

  72. Campbell, S., Michaelson, J., Burkly, L. & Putterman, C. The role of TWEAK/Fn14 in the pathogenesis of inflammation and systemic autoimmunity. Front. Biosci. 9, 2273–2284 (2004).

    Article  CAS  PubMed  Google Scholar 

  73. Campbell, S. et al. Proinflammatory effects of TWEAK/Fn14 interactions in glomerular mesangial cells. J. Immunol. 176, 1889–1898 (2006).

    Article  CAS  PubMed  Google Scholar 

  74. Schwartz, N. et al. Urinary TWEAK and the activity of lupus nephritis. J. Autoimmun. 27, 242–250 (2006).

    Article  CAS  PubMed  Google Scholar 

  75. Schwartz, N. et al. Urinary TWEAK as a biomarker of lupus nephritis: a multicentre cohort study. Arthritis Res. Ther. 11, R143 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Abulaban, K. et al. A78: urine biomarkers role in predicting the future development of renal functional loss with lupus nephritis in children and adults. Arthritis Rheumatol. 66 (Suppl. 11), S111 (2014).

    Article  Google Scholar 

  77. Avihingsanon, Y. et al. Measurement of urinary chemokine and growth factor messenger RNAs: a noninvasive monitoring in lupus nephritis. Kidney Int. 69, 747–753 (2006).

    Article  CAS  PubMed  Google Scholar 

  78. Wu, T. et al. Elevated urinary VCAM-1, P-selectin, soluble TNF receptor-1, and CXC chemokine ligand 16 in multiple murine lupus strains and human lupus nephritis. J. Immunol. 179, 7166–7175 (2007).

    Article  CAS  PubMed  Google Scholar 

  79. Wang, G. et al. Urinary FOXP3 mRNA in patients with lupus nephritis—relation with disease activity and treatment response. Rheumatology (Oxford) 48, 755–760 (2009).

    Article  CAS  Google Scholar 

  80. Hammad, A. M., Youssef, H. M. & El-Arman, M. M. Transforming growth factor β 1 in children with systemic lupus erythematosus: a possible relation with clinical presentation of lupus nephritis. Lupus 15, 608–612 (2006).

    Article  CAS  PubMed  Google Scholar 

  81. Suzuki, M. et al. Identification of a urinary proteomic signature for lupus nephritis in children. Pediatr. Nephrol. 22, 2047–2057 (2007).

    Article  PubMed  Google Scholar 

  82. Suzuki, M. et al. Initial validation of a novel protein biomarker panel for active pediatric lupus nephritis. Pediatr. Res 65, 530–536 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Brunner, H. I. et al. Association of noninvasively measured renal protein biomarkers with histologic features of lupus nephritis. Arthritis Rheum. 64, 2687–2697 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Wedderburn, L. R. & Rider, L. G. Juvenile dermatomyositis: new developments in pathogenesis, assessment and treatment. Best. Pract. Res. Clin. Rheumatol. 23, 665–678 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  85. Rider, L. G. & Miller, F. W. Deciphering the clinical presentations, pathogenesis, and treatment of the idiopathic inflammatory myopathies. JAMA 305, 183–190 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Bohan, A. & Peter, J. B. Polymyositis and dermatomyositis (first of two parts). N. Engl. J. Med. 292, 344–347 (1975).

    Article  CAS  PubMed  Google Scholar 

  87. Bohan, A. & Peter, J. B. Polymyositis and dermatomyositis (second of two parts). N. Engl. J. Med. 292, 403–407 (1975).

    Article  CAS  PubMed  Google Scholar 

  88. Brown, V. E., Pilkington, C. A., Feldman, B. M. & Davidson, J. E. An international consensus survey of the diagnostic criteria for juvenile dermatomyositis (JDM). Rheumatology (Oxford) 45, 990–993 (2006).

    Article  CAS  Google Scholar 

  89. Davis, W. R. et al. Assessment of active inflammation in juvenile dermatomyositis: a novel magnetic resonance imaging-based scoring system. Rheumatology (Oxford) 50, 2237–2244 (2011).

    Article  Google Scholar 

  90. Malattia, C. et al. Whole-body MRI in the assessment of disease activity in juvenile dermatomyositis. Ann. Rheum. Dis. 73, 1083–1090 (2014).

    Article  PubMed  Google Scholar 

  91. Gunawardena, H., Betteridge, Z. E. & McHugh, N. J. Myositis-specific autoantibodies: their clinical and pathogenic significance in disease expression. Rheumatology (Oxford) 48, 607–612 (2009).

    Article  CAS  Google Scholar 

  92. Tansley, S. L., McHugh, N. J. & Wedderburn, L. R. Adult and juvenile dermatomyositis: are the distinct clinical features explained by our current understanding of serological subgroups and pathogenic mechanisms? Arthritis Res. Ther. 15, 211 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Gunawardena, H. et al. Clinical associations of autoantibodies to a p155/140 kDa doublet protein in juvenile dermatomyositis. Rheumatology (Oxford) 47, 324–328 (2008).

    Article  CAS  Google Scholar 

  94. Rider, L. G. et al. The myositis autoantibody phenotypes of the juvenile idiopathic inflammatory myopathies. Medicine (Baltimore) 92, 223–243 (2013).

    Article  CAS  Google Scholar 

  95. Rider, L. G., Katz, J. D. & Jones, O. Y. Developments in the classification and treatment of the juvenile idiopathic inflammatory myopathies. Rheum. Dis. Clin. North Am. 39, 877–904 (2013).

    Article  PubMed  Google Scholar 

  96. Bingham, A. et al. Predictors of acquired lipodystrophy in juvenile-onset dermatomyositis and a gradient of severity. Medicine (Baltimore) 87, 70–86 (2008).

    Article  Google Scholar 

  97. Espada, G., Maldonado Cocco, J. A., Fertig, N. & Oddis, C. V. Clinical and serologic characterization of an Argentine pediatric myositis cohort: identification of a novel autoantibody (anti-MJ) to a 142-kDa protein. J. Rheumatol. 36, 2547–2551 (2009).

    Article  CAS  PubMed  Google Scholar 

  98. Gunawardena, H. et al. Autoantibodies to a 140-kD protein in juvenile dermatomyositis are associated with calcinosis. Arthritis Rheum. 60, 1807–1814 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Huber, A. M. et al. Early illness features associated with mortality in the juvenile idiopathic inflammatory myopathies. Arthritis Care Res. (Hoboken) 66, 732–740 (2014).

    Article  Google Scholar 

  100. Rouster-Stevens, K. A. & Pachman, L. M. Autoantibody to signal recognition particle in African American girls with juvenile polymyositis. J. Rheumatol. 35, 927–929 (2008).

    CAS  PubMed  Google Scholar 

  101. Sato, S. et al. RNA helicase encoded by melanoma differentiation-associated gene 5 is a major autoantigen in patients with clinically amyopathic dermatomyositis: association with rapidly progressive interstitial lung disease. Arthritis Rheum. 60, 2193–2200 (2009).

    Article  CAS  PubMed  Google Scholar 

  102. Kobayashi, I. et al. Anti-melanoma differentiation-associated gene 5 antibody is a diagnostic and predictive marker for interstitial lung diseases associated with juvenile dermatomyositis. J. Pediatr. 158, 675–677 (2011).

    Article  CAS  PubMed  Google Scholar 

  103. Tansley, S. et al. Anti-MDA5 autoantibodies in juvenile dermatomyositis identify a distinct clinical phenotype: a prospective cohort study. Arthritis Res. Ther. 16, R138 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  104. Aggarwal, R. et al. Predictors of clinical improvement in rituximab-treated refractory adult and juvenile dermatomyositis and adult polymyositis. Arthritis Rheumatol. 66, 740–749 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Peixoto, D., Costa, J., Ferretti, M., Malattia, C. & Martini, A. New autoantibodies and their clinical associations in juvenile myositis—a systematic review. Acta Reumatol. Port. 38, 234–241 (2013).

    PubMed  Google Scholar 

  106. Shah, M. et al. The clinical phenotypes of the juvenile idiopathic inflammatory myopathies. Medicine (Baltimore) 92, 25–41 (2013).

    Article  CAS  Google Scholar 

  107. Wedderburn, L. R. et al. HLA class II haplotype and autoantibody associations in children with juvenile dermatomyositis and juvenile dermatomyositis-scleroderma overlap. Rheumatology (Oxford) 46, 1786–1791 (2007).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

A.R. and A.C. wrote the manuscript and contributed substantially to discussions of its content. All authors (A.R., A.C., G.C.V. and A.M.) researched data for the article and undertook review or editing of the manuscript before submission.

Corresponding author

Correspondence to Angelo Ravelli.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Consolaro, A., Varnier, G., Martini, A. et al. Advances in biomarkers for paediatric rheumatic diseases. Nat Rev Rheumatol 11, 265–275 (2015). https://doi.org/10.1038/nrrheum.2014.208

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrrheum.2014.208

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research