OBJECTIVE: Improved outcome measures in systemic sclerosis (SSc) are critical to finding active therapeutics for this disease. The modified Rodnan skin thickness score (MRSS) is the current standard for evaluating skin disease in SSc, but it is not commonly used in the clinical setting, in part because it requires specialized training to perform accurately and consistently. The purpose of this study was to investigate whether skin gene expression might serve as a more objective surrogate outcome measure to supplement skin score evaluations. METHODS: Skin RNAs from a group of patients with diffuse cutaneous SSc were studied for expression levels of genes known to be regulated by transforming growth factor beta (TGFbeta) and interferon (IFN). These levels were correlated with the MRSS, using multiple regression analyses to obtain best-fit models. RESULTS: Skin expression of the TGFbeta-regulated genes cartilage oligomeric matrix protein (COMP) and thrombospondin 1 (TSP-1) correlated moderately well with the MRSS, but the addition of other TGFbeta-regulated genes failed to significantly improve best-fit models. IFN-regulated genes were also found to correlate with the MRSS, and the addition of interferon-inducible 44 (IFI44) and sialoadhesin (Siglec-1) to COMP and TSP-1 in multiple regression analyses significantly improved best-fit models, achieving an R(2) value of 0.89. These results were validated using an independent group of skin biopsy samples. Longitudinal scores using this 4-gene biomarker indicated that it detects change over time that corresponds to changes in the MRSS. CONCLUSION: We describe a 4-gene predictor of the MRSS and validate its performance. This objective measure of skin disease could provide a strong surrogate outcome measure for patient care and for clinical trials.
OBJECTIVE: Improved outcome measures in systemic sclerosis (SSc) are critical to finding active therapeutics for this disease. The modified Rodnan skin thickness score (MRSS) is the current standard for evaluating skin disease in SSc, but it is not commonly used in the clinical setting, in part because it requires specialized training to perform accurately and consistently. The purpose of this study was to investigate whether skin gene expression might serve as a more objective surrogate outcome measure to supplement skin score evaluations. METHODS: Skin RNAs from a group of patients with diffuse cutaneous SSc were studied for expression levels of genes known to be regulated by transforming growth factor beta (TGFbeta) and interferon (IFN). These levels were correlated with the MRSS, using multiple regression analyses to obtain best-fit models. RESULTS: Skin expression of the TGFbeta-regulated genes cartilage oligomeric matrix protein (COMP) and thrombospondin 1 (TSP-1) correlated moderately well with the MRSS, but the addition of other TGFbeta-regulated genes failed to significantly improve best-fit models. IFN-regulated genes were also found to correlate with the MRSS, and the addition of interferon-inducible 44 (IFI44) and sialoadhesin (Siglec-1) to COMP and TSP-1 in multiple regression analyses significantly improved best-fit models, achieving an R(2) value of 0.89. These results were validated using an independent group of skin biopsy samples. Longitudinal scores using this 4-gene biomarker indicated that it detects change over time that corresponds to changes in the MRSS. CONCLUSION: We describe a 4-gene predictor of the MRSS and validate its performance. This objective measure of skin disease could provide a strong surrogate outcome measure for patient care and for clinical trials.
Authors: Mallika Kaviratne; Matthias Hesse; Mary Leusink; Allen W Cheever; Stephen J Davies; James H McKerrow; Lalage M Wakefield; John J Letterio; Thomas A Wynn Journal: J Immunol Date: 2004-09-15 Impact factor: 5.422
Authors: H Gardner; D Strehlow; L Bradley; R Widom; A Farina; A de Fougerolles; J Peyman; V Koteliansky; J H Korn Journal: Clin Exp Rheumatol Date: 2004 Jan-Feb Impact factor: 4.473
Authors: Elizabeth Gore-Hyer; Daniel Shegogue; Malgorzata Markiewicz; Shianlen Lo; Debra Hazen-Martin; Eddie L Greene; Gary Grotendorst; Maria Trojanowska Journal: Am J Physiol Renal Physiol Date: 2002-10
Authors: Shi-wen Xu; Sarah L Howat; Elisabetta A Renzoni; Alan Holmes; Jeremy D Pearson; Michael R Dashwood; George Bou-Gharios; Christopher P Denton; Roland M du Bois; Carol M Black; Andrew Leask; David J Abraham Journal: J Biol Chem Date: 2004-03-23 Impact factor: 5.157