A composite biomarker score to predict modified Rodnan skin score in systemic sclerosis: insight from autologous stem cell transplantation international scleroderma trial

  • Stefano Rodolfi*
  • , Kristina Clark
  • , Bahja Ahmed Abdi
  • , Elen Roblin
  • , Medha Kanitkar
  • , Voon H Ong
  • , Alexandre E Voskuyl
  • , Jeska K De Vries-Bouwstra
  • , Jacob M van Laar
  • , Christopher P Denton
  • , Julia Spierings
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background: Skin fibrosis is a cardinal manifestation of systemic sclerosis (SSc) and is routinely measured by modified Rodnan skin score (mRSS), which is however limited by its operator-dependence and may not reflect the complex disease biology at the cutaneous compartment. A recent high dimensional multi-omic analysis identified 3 serum proteins independently associated with mRSS: tenascin C (TENC), cartilage oligomeric matrix protein (COMP), and collagen type IV alpha 1 (COL4A1). The aim of our study was to evaluate the relationship between these analytes as cross-sectional and dynamic biomarkers for skin involvement, as well as to capture potential correlations with type of immunosuppressive treatment. Methods: We selected 21 patients from 2 Dutch centres who participated in the Autologous Stem Cell Transplantation International Scleroderma trial - a phase 3, multicentre, randomized study comparing autologous stem cell transplantation (HSCT) to cyclophosphamide (CYC) in diffuse cutaneous (dc)SSc. Serum concentrations of the three analytes were measured with ELISAs at baseline, 12 and 24 months. We employed linear mixed-effects models to assess cross-sectional correlation between mRSS, analyte concentrations and time. A multivariable linear regression model (independent of time) was used to formulate a composite biomarker score to predict mRSS. Results: There were 11 patients in the CYC arm, and 10 to the HSCT arm. Serum concentrations of COMP and COL4A1, but not TENC, showed significant correlation with mRSS at the mixed model; COL4A1 correlation with mRSS remained significant at multivariable analysis (β = 0.01, p = 0.001). We derived a composite biomarker formula score to predict mRSS with good performance at Bland Altman plot. As dynamic biomarkers, only changes in concentrations of COMP were associated with mRSS change (r = 0.013; p = 0.012). It is notable that there was greater reduction in COL4A1 concentration at 24 months in the HSCT group compared with CYC (-81 ng/mL vs. -27.4 ng/mL in CYC group; p = 0.029). Conclusion: Our composite biomarker score showed a moderate cross-sectional correlation with mRSS and potentially complement mRSS in the assessment of skin activity. The differential variations for serum COL4A1 across treatment groups warrant further evaluation as a predictive marker of immunotherapeutic response in dcSSc.

Original languageEnglish
Article number11
JournalArthritis research & therapy
Volume28
Issue number1
Early online date10 Dec 2025
DOIs
Publication statusPublished - 10 Dec 2025

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