Personalized Medicine in Systemic Sclerosis: Facts and Promises

Part of the following topical collections:
  1. Topical Collection on Scleroderma


The concept of personalized medicine has led to a paradigm shift in recent years. It integrates multiple clinical and biological levels of investigation aimed at offering the best possible and patient-tailored healthcare. This holds great potential in a rare and heterogeneous disease such as systemic sclerosis (SSc). The development of validated clinical screening algorithms and the identification of predictors for disease outcomes can help in stratifying patients according to their individual risk of progression. The ongoing search for biomarkers and key pathogenic molecules has brought valuable insights into molecular networks operative in SSc. In parallel, genetic and genomic studies have revealed new SSc susceptibility loci and validated gene expression profiles that might identify patients benefiting from specific therapies. In this review, we focus on recent findings relevant for the concept of personalized medicine in patients with SSc.


Systemic sclerosis Scleroderma Personalized medicine P4 medicine Patient-centered Genomic Genetic Intrinsic subset Gene expression Targeted treatment Treatment response Predictors Prognosis Screening Organ involvement 


Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Tutton R. Personalizing medicine: futures, present and past. Soc Sci Med. 2012;75(10):1721–8.PubMedCrossRefGoogle Scholar
  2. 2.•
    Personalized medicine for the European Citizen. Towards more precise medicine for the diagnosis, treatment and prevention of disease. Available at Accessed October 2013. This defines personalized medicine as a priority for European research.
  3. 3.
    Varga J. Systemic sclerosis. An update. Bull NYU Hosp Jt Dis. 2008;66(3):198–202.PubMedGoogle Scholar
  4. 4.
    Chifflot H, Fautrel B, Sordet C, et al. Incidence and prevalence of systemic sclerosis: a systematic literature review. Semin Arthritis Rheum. 2008;37(4):223–35.PubMedCrossRefGoogle Scholar
  5. 5.
    Minier T, Péntek M, Brodszky V, et al. Cost-of-ilness of patients with systemic sclerosis in a tertiary care center. Rheumatology (Oxford). 2010;49(10):1920–8.CrossRefGoogle Scholar
  6. 6.
    Allanore Y, Avouac J, Kahan A. Systemic sclerosis: an update in 2008. Joint Bone Spine. 2008;75(6):650–5.PubMedCrossRefGoogle Scholar
  7. 7.
    Steen V. Targeted therapy for systemic sclerosis. Autoimmun Rev. 2006;5(2):122–4.PubMedCrossRefGoogle Scholar
  8. 8.
    Derk C. Disease-modifying drugs for systemic sclerosis: why have we not found them yet? Expert Rev Clin Immunol. 2011;7(4):399–401.PubMedCrossRefGoogle Scholar
  9. 9.
    Maurer B, Distler O. Emerging targeted therapies in scleroderma lung and skin fibrosis. Best Pract Res Clin Rheumatol. 2011;25(6):843–58.PubMedCrossRefGoogle Scholar
  10. 10.
    Iwamoto N, Distler O. Molecular targets for therapy in systemic sclerosis. Fibrogenesis Tissue Repair. 2012;5 Suppl 1:S19.PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Jordan S, Chung J, Distler O. Preclinical and translational research to discover potentially effective antifibrotic therapies in systemic sclerosis. Curr Opin Rheumatol. 2013;25(6):679–85.PubMedCrossRefGoogle Scholar
  12. 12.
    Abigano G, Buch M, Emery P. Biomarkers in the management of scleroderma: an update. Curr Rheumatol Rep. 2011;13(1):4–12.CrossRefGoogle Scholar
  13. 13.
    Merkel PA, Silliman NP, Clements PJ, et al. Patterns and predictors of change in outcome measures in clinical trials in scleroderma an individual patient meta-analysis of 629 subjects with diffuse scleroderma. Arthritis Rheum. 2012;64(10):3420–9.PubMedCentralPubMedCrossRefGoogle Scholar
  14. 14.
    Castro S, Jimenez S. Biomarkers in systemic sclerosis. Biomarkers Med. 2010;4(1):133–47.CrossRefGoogle Scholar
  15. 15.
    Shand L, Lunt M, Nihtyanova S, et al. Relationship between change in skin score and disease outcome in diffuse cutaneous systemic sclerosis. Application of a latent linear trajectory model. Arthritis Rheum. 2007;56(7):2422–31.PubMedCrossRefGoogle Scholar
  16. 16.••
    Maurer B, Graf N, Michel B, et al. Prediction of worsening of skin fibrosis in patients with diffuse cutaneous systemic sclerosis using the EUSTAR database. Ann Rheum Dis 2014, in revision. This EUSTAR study developed evidence-based models to predict worsening of skin fibrosis. Google Scholar
  17. 17.
    Celeste S, Santaniello A, Caronni M, et al. Carbohydrate antigen 15.3 as a serum biomarker of interstitial lung disease in systemic sclerosis patients. Eur J Intern Med. 2013;24(7):671–6.PubMedCrossRefGoogle Scholar
  18. 18.
    Lee CG, Herzog EL, Ahangari F, et al. Chitinase 1 is a biomarker for and therapeutic target in scleroderma-associated interstitial lung disease that augments TGF-b1 signaling. J Immunol. 2012;189(5):2635–44.PubMedCrossRefGoogle Scholar
  19. 19.
    van Bon L, Affandi AJ, Broen J, et al. Proteome-wide analysis and CXCL4 as a biomarker in systemic sclerosis. N Engl J Med. 2014;370(5):433–43.PubMedCentralPubMedCrossRefGoogle Scholar
  20. 20.
    Tiev KP, Hua-Huy T, Rivière S, et al. High alveolar concentration of nitric oxide is associated with alveolitis in scleroderma. Nitric Oxide. 2013;28:65–70.PubMedCrossRefGoogle Scholar
  21. 21.
    Nihtyanova SI, Schreiber BE, Ong VH, et al. Prediction of pulmonary complications and long term survival in systemic sclerosis. Arthritis Rheumatol. 2014 Mar 3. [Epub ahead of print].Google Scholar
  22. 22.••
    Moore OA, Goh N, Corte T, et al. Extent of disease on high-resolution computed tomography lung is a predictor of decline and mortality in systemic sclerosis-related interstitial lung disease. Rheumatology (Oxford). 2013;52(1):155–60. Confirms results from Goh et al. (23) that advanced lung involvement on HRCT is a major prognostic factor in SSc-ILD.CrossRefGoogle Scholar
  23. 23.
    Goh NS, Desai SR, Veeraraghavan S, et al. Interstitial lung disease in systemic sclerosis: a simple staging system. Am J Respir Crit Care Med. 2008;177(11):1248–54.PubMedCrossRefGoogle Scholar
  24. 24.
    Kowal-Bielecka O, Landewe R, Avouac J, et al. EULAR recommendations for the treatment of systemic sclerosis: a report from the EULAR Scleroderma Trials and Research group (EUSTAR). Ann Rheum Dis. 2009;68(5):620–8.PubMedCrossRefGoogle Scholar
  25. 25.
    Mihai C, Landewé R, van der Heijde D, et al. Predictive value of history of digital ulcers in a EUSTAR cohort of patients with systemic sclerosis. [abstract 13-3570]. Presented at EULAR, 12–15 June 2013, Madrid, Spain.Google Scholar
  26. 26.
    Avouac J, Meune C, Ruiz B, et al. Angiogenic biomarkers predict the occurrence of digital ulcers in systemic sclerosis. Ann Rheum Dis. 2012;71(3):394–9.PubMedCrossRefGoogle Scholar
  27. 27.
    Alivernini S, De Santis M, Tolusso B, et al. Skin ulcers in systemic sclerosis: determinants of presence and predictive factors of healing. J Am Acad Dermatol. 2009;60(3):426–35.PubMedCrossRefGoogle Scholar
  28. 28.
    Khan K, Xu S, Nihtyanova S, et al. Clinical and pathological significance of interleukin 6 overexpression in systemic sclerosis. Ann Rheum Dis. 2012;71(7):1235–42.PubMedCrossRefGoogle Scholar
  29. 29.
    Sebastiani M, Manfredi A, Vukatana G, et al. Predictive role of capillaroscopic skin ulcer risk index in systemic sclerosis: a multicentre validation study. Ann Rheum Dis. 2012;71(1):67–70.PubMedCrossRefGoogle Scholar
  30. 30.
    Sebastiani M, Manfredi A, Lo Monaco A, et al. Capillaroscopic Skin Ulcers Risk Index (CSURI) calculated with different videocapillaroscopy devices: how its predictive values change. Clin Exp Rheumatol. 2013;31(2 Suppl 76):115–7.PubMedGoogle Scholar
  31. 31.
    Smith V, De Keyser F, Pizzorni C, et al. Nailfold capillaroscopy for day-to-day clinical use: construction of a simple scoring modality as a clinical prognostic index for digital trophic lesions. Ann Rheum Dis. 2011;70(1):180–3.PubMedCrossRefGoogle Scholar
  32. 32.
    Cutolo M, Herrick A, Distler O, et al. Nailfold videocapillaroscopy and other predictive factors associated with new digital ulcers in systemic sclerosis: results from the CAP study. [abstract PS04]. Presented at the 3rd Systemic Sclerosis World Congress. Rome, Italy; February 6–8, 2014.Google Scholar
  33. 33.
    Lefévre G, Dauchet L, Hachulla E, et al. Survival and prognostic factors in systemic sclerosis–associated pulmonary hypertension: a systematic review and meta-analysis. Arthritis Rheum. 2013;65(9):2412–23.PubMedCrossRefGoogle Scholar
  34. 34.
    Chung L, Domsic R, Bharathi L, et al. Survival and predictors of mortality in systemic sclerosis associated pulmonary arterial hypertension: outcomes from the pulmonary hypertension assessment and recognition of outcomes in scleroderma registry. Arthritis Care Res. 2014;66(3):489–95.CrossRefGoogle Scholar
  35. 35.
    Gladue H, Altorok N, Towsend W, et al. Screening and diagnostic modalities for connective tissue disease - associated pulmonary arterial hypertension: a systematic review. Semin Arthritis Rheum. 2014;43(4):536–41.PubMedCrossRefGoogle Scholar
  36. 36.
    Codullo V, Caporali R, Cuomo G, et al. Stress doppler echocardiography in systemic sclerosis. Evidence for a role in the prediction of pulmonary hypertension. Arthritis Rheum. 2013;65(9):2403–11.PubMedCrossRefGoogle Scholar
  37. 37.
    Coghlan JG. Stress echocardiography and Cochin risk prediction score for the prediction of pulmonary arterial hypertension in scleroderma: not yet ready for prime time. Arthritis Rheum. 2013;65(9):2236–9.PubMedCrossRefGoogle Scholar
  38. 38.••
    Coghlan JG, Denton C, Grünig E, et al. Evidence-based detection of pulmonary arterial hypertension in systemic sclerosis:the DETECT study. Ann Rheum Dis. 2013 May 18. [Epub ahead of print]. The DETECT study developed an evidence-based algorithm for the early detection of PAH in high-risk patients with SSc. Google Scholar
  39. 39.
    Khanna D, Gladue H, Channick R, et al. Recommendations for screening and detection of connective tissue disease–associated pulmonary arterial hypertension. Arthritis Rheum. 2013;65(12):3194–201.PubMedCrossRefGoogle Scholar
  40. 40.
    Avouac J, Airò P, Meune C, et al. Prevalence of pulmonary hypertension in systemic sclerosis in European Caucasians and metaanalysis of 5 studies. J Rheumatol. 2010;37(11):2290–8.PubMedCrossRefGoogle Scholar
  41. 41.
    Avouac J, Huscher D, Furst DE, et al. Expert consensus for performing right heart catheterisation for suspected pulmonary arterial hypertension in systemic sclerosis: a Delphi consensus study with cluster analysis. Ann Rheum Dis. 2014;73(1):191–7.PubMedCrossRefGoogle Scholar
  42. 42.
    Mayes MD. The genetics of scleroderma: looking into the postgenomic era. Curr Opin Rheumatol. 2012;24(6):677–84.PubMedCentralPubMedCrossRefGoogle Scholar
  43. 43.
    Allanore Y, Saad M, Dieude P, et al. Genome-wide scan identifies TNIP1, PSORS1C1, and RHOB as novel risk loci for systemic sclerosis. PLoS Genet. 2011;7(7):e1002091.PubMedCentralPubMedCrossRefGoogle Scholar
  44. 44.
    Radstake TR, Gorlova O, Rueda B, et al. Genome-wide association study of systemic sclerosis identifies CD247 as a new susceptibility locus. Nat Genet. 2010;42(5):426–9.PubMedCentralPubMedCrossRefGoogle Scholar
  45. 45.
    Zhou X, Lee JE, Arnett FC, et al. HLA-DPB1 and DPB2 are genetic loci for systemic sclerosis: a genome-wide association study in Koreans with replication in North Americans. Arthritis Rheum. 2009;60(12):3807–14.PubMedCentralPubMedCrossRefGoogle Scholar
  46. 46.
    Gorlova O, Martin JE, Rueda B, et al. Identification of novel genetic markers associated with clinical phenotypes of systemic sclerosis through a genome-wide association strategy. PLoS Genet. 2011;7(7):e1002178.PubMedCentralPubMedCrossRefGoogle Scholar
  47. 47.
    Assassi S, Radstake TR, Mayes MD, et al. Genetics of scleroderma: implications for personalized medicine? BMC Med. 2013;11:9.PubMedCentralPubMedCrossRefGoogle Scholar
  48. 48.
    Milano A, Pendergrass SA, Sargent JL, et al. Molecular subsets in the gene expression signatures of scleroderma skin. PLoS One. 2008;3(7):e2696.PubMedCentralPubMedCrossRefGoogle Scholar
  49. 49.
    Pendergrass A, Lemaire R, Francis IP, et al. Intrinsic gene expression subsets of diffuse cutaneous systemic sclerosis are stable in serial skin biopsies. J Invest Dermatol. 2012;132(5):1363–73.PubMedCentralPubMedCrossRefGoogle Scholar
  50. 50.
    Hinchcliff M, Wood T, Mahoney JM, et al. SSc intrinsic subset classification in patients that demonstrate clinical improvement during treatment. [abstract S.1.7]. Presented at the 3rd Systemic Sclerosis World Congress. Rome, Italy; February 6–8, 2014.Google Scholar
  51. 51.
    Bhattacharyya S, Sargent JL, Du P, et al. Egr-1 induces a profibrotic injury/repair gene program associated with systemic sclerosis. PLoS One. 2011;6(9):e23082.PubMedCentralPubMedCrossRefGoogle Scholar
  52. 52.
    Greenblatt MB, Aliprantis AO. The Immune Pathogenesis of Scleroderma: context is everything. Curr Rheumatol Rep. 2013;15(1):297.PubMedCentralPubMedCrossRefGoogle Scholar
  53. 53.
    Hunzelmann N, Brinckmann J. What are the new milestones in the pathogenesis of systemic sclerosis? Ann Rheum Dis. 2010;69(Suppl I):i52–6.PubMedCrossRefGoogle Scholar
  54. 54.
    Sargent JL, Milano A, Bhattacharyya S, et al. A TGFb-responsive gene signature is associated with a subset of diffuse scleroderma with increased disease severity. J Invest Dermatol. 2010;130(3):694–705.PubMedCrossRefGoogle Scholar
  55. 55.
    Farina G, Lafyatis D, Lemaire R, et al. A four-gene biomarker predicts skin disease in patients with diffuse cutaneous systemic sclerosis. Arthritis Rheum. 2010;62(2):580–8.PubMedCentralPubMedCrossRefGoogle Scholar
  56. 56.
    Greenblatt MB, Sargent JL, Farina G, et al. Interspecies comparison of human and murine scleroderma reveals IL-13 and CCL-2 as disease subset-specific targets. Am J Pathol. 2012;180(3):1080–94.PubMedCentralPubMedCrossRefGoogle Scholar
  57. 57.
    Leask A. Egr-ly awaiting a “personalized medicine” approach to treat scleroderma. J Cell Commun Signal. 2012;6(2):111–3.PubMedCentralPubMedCrossRefGoogle Scholar
  58. 58.
    Sargent JL, Milano A, Connolly MK, et al. Scleroderma gene expression and pathway signatures. Curr Rheumatol Rep. 2008;10(3):205–11.PubMedCrossRefGoogle Scholar
  59. 59.•
    Hsu E, Shi H, Jordan RM, et al. Lung tissues in systemic sclerosis have gene expression patterns unique to pulmonary fibrosis and pulmonary artery hypertension. Arthritis Rheum. 2011;63(3):783–94. First study describing gene expression patterns based on arrays in lung tissue from SSc patients.PubMedCentralPubMedCrossRefGoogle Scholar
  60. 60.
    Liao WL, Tsai FJ. Personalized medicine: a paradigm shift in healthcare. BioMedicine. 2013;3(2):66–72.CrossRefGoogle Scholar
  61. 61.
    Sargent J, Whitfield M. Capturing the heterogeneity in systemic sclerosis with genomewide expression profiling. Expert Rev Clin Immunol. 2011;7(4):463–73.PubMedCentralPubMedCrossRefGoogle Scholar
  62. 62.
    Chung L, Fiorentino DF, Benbarak MJ, et al. Molecular framework for response to Imatinib mesylate in systemic sclerosis. Arthritis Rheum. 2009;60(2):584–91.PubMedCentralPubMedCrossRefGoogle Scholar
  63. 63.
    Maurer B, Distler A, Dees C, et al. Levels of target activation predict antifibrotic responses to tyrosine kinase inhibitors. Ann Rheum Dis. 2013;72(12):2039–46.PubMedCrossRefGoogle Scholar
  64. 64.•
    Hinchcliff M, Huang CC, Wood TA, et al. Molecular signatures in skin associated with clinical improvement during mycophenolate treatment in systemic sclerosis. J Invest Dermatol. 2013;133(8):1979–89. This paper shows a correlation between the gene expression profile and response to MMF treatment.PubMedCentralPubMedCrossRefGoogle Scholar
  65. 65.
    Roth MD, Tseng CH, Clements PJ, et al. Predicting treatment outcomes and responder subsets in scleroderma-related intesrtitial lung disease. Arthritis Rheum. 2011;63(9):2797–808.PubMedCentralPubMedCrossRefGoogle Scholar
  66. 66.
    Lambova S, Muller-Ladner U. Chapter79: Systemic Sclerosis. Genomic and Personalized Medicine 2nd Edition. Edited by Ginsburg GS and Willard HF. Oxford: Academic Press; 2012:955–69.Google Scholar
  67. 67.
    Tashkin DP, Elashoff R, Clements PJ, et al. Cyclophosphamide versus placebo in scleroderma lung disease. N Engl J Med. 2006;354(25):2655–66.PubMedCrossRefGoogle Scholar
  68. 68.
    Rueda B, Gourh P, Broen J, et al. BANK1 functional variants are associated with susceptibility to diffuse systemic sclerosis in Caucasians. Ann Rheum Dis. 2010;69(4):700–5.PubMedCentralPubMedCrossRefGoogle Scholar
  69. 69.
    Bossini-Castillo L, Broen JC, Simeon CP, et al. A replication study confirms the association of TNFSF4 (OX40L) polymorphisms with systemic sclerosis in a large European cohort. Ann Rheum Dis. 2011;70(4):638–41.PubMedCrossRefGoogle Scholar
  70. 70.
    Dieudé P, Guedj M, Wipff J, et al. Association between the IRF5 rs2004640 functional polymorphism and systemic sclerosis: a new perspective for pulmonary fibrosis. Arthritis Rheum. 2009;60(1):225–33.PubMedCrossRefGoogle Scholar
  71. 71.
    Dieudé P, Guedj M, Wipff J, et al. Association of the TNFAIP3 rs5029939 variant with systemic sclerosis in the European Caucasian population. Ann Rheum Dis. 2010;69(11):1958–64.PubMedCrossRefGoogle Scholar
  72. 72.
    Bossini-Castillo L, Martin JE, Broen J, et al. Confirmation of TNIP1 but not RHOB and PSORS1C1 as systemic sclerosis risk factors in a large independent replication study. Ann Rheum Dis. 2013;72(4):602–7.PubMedCrossRefGoogle Scholar
  73. 73.
    Dieudé P, Bouaziz M, Guedj M, et al. Evidence of the contribution of the X chromosome to systemic sclerosis susceptibility: association with the functional IRAK1 196Phe/532Ser haplotype. Arthritis Rheum. 2011;63(12):3979–87.PubMedCrossRefGoogle Scholar
  74. 74.
    Carmona FD, Cénit MC, Diaz-Gallo LM, et al. New insight on the Xq28 association with systemic sclerosis. Ann Rheum Dis. 2013;72(12):2032–8.PubMedCrossRefGoogle Scholar
  75. 75.
    Cénit MC, Simeon CP, Vonk MC, et al. Influence of the IL6 gene in susceptibility to systemic sclerosis. J Rheumatol. 2012;39(12):2294–302.PubMedCrossRefGoogle Scholar
  76. 76.
    Martin JE, Broen JC, Carmona FD, et al. Identification of CSK as a systemic sclerosis genetic risk factor through Genome Wide Association Study follow-up. Hum Mol Genet. 2012;21(12):2825–35.PubMedCentralPubMedCrossRefGoogle Scholar
  77. 77.
    Bossini-Castillo L, Martin JE, Broen J, et al. A GWAS follow-up study reveals the association of the IL12RB2 gene with systemic sclerosis in Caucasian populations. Hum Mol Genet. 2012;21(4):926–33.PubMedCentralPubMedCrossRefGoogle Scholar
  78. 78.
    Manetti M, Allanore Y, Saad M, et al. Evidence for caveolin-1 as a new susceptibility gene regulating tissue fibrosis in systemic sclerosis. Ann Rheum Dis. 2012;71(6):1034–41.PubMedCrossRefGoogle Scholar
  79. 79.
    Diaz-Gallo LM, Simeon C, Broen J, et al. Implication of IL-2/IL-21 region in systemic sclerosis genetic susceptibility. Ann Rheum Dis. 2013;72(7):1233–8.PubMedCrossRefGoogle Scholar
  80. 80.
    Bossini-Castillo L, Simeon C, Beretta L, et al. A multicenter study confirms CD226 gene association with systemic sclerosis-related pulmonary fibrosis. Arthritis Res Ther. 2012;14(2):R85.PubMedCentralPubMedCrossRefGoogle Scholar
  81. 81.
    Manetti M, Allanore Y, Revillod L, et al. A genetic variation located in the promoter region of the UPAR (CD87) gene is associated with the vascular complications of systemic sclerosis. Arthritis Rheum. 2011;63(1):247–56.PubMedCrossRefGoogle Scholar
  82. 82.
    Wipff J, Dieudé P, Guedj M, et al. Association of a KCNA5 gene polymorphism with systemic sclerosis–associated pulmonary arterial hypertension in the European Caucasian population. Arthritis Rheum. 2010;62(10):3093–100.PubMedCrossRefGoogle Scholar
  83. 83.
    Sharif R, Mayes M, Tan FK, et al. IRF5 polymorphism predicts prognosis in patients with systemic sclerosis. Ann Rheum Dis. 2012;71(7):1197–202.PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Rucsandra Dobrota
    • 1
    • 2
  • Carina Mihai
    • 2
  • Oliver Distler
    • 1
  1. 1.Division of RheumatologyUniversity Hospital ZurichZurichSwitzerland
  2. 2.Department of Internal Medicine and Rheumatology, Dr.I. Cantacuzino HospitalCarol Davila University of Medicine and PharmacyBucharestRomania

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