A four-gene biomarker predicts skin disease in patients with diffuse cutaneous systemic sclerosis

Autor: D. Lafyatis, Giuseppina Farina, Robert Lafyatis, Raphael Lemaire
Rok vydání: 2010
Předmět:
Genetic Markers
Oncology
medicine.medical_specialty
Systemic disease
Sialic Acid Binding Ig-like Lectin 1
Biopsy
Immunology
Cartilage Oligomeric Matrix Protein
Severity of Illness Index
Article
Thrombospondin 1
Rheumatology
Predictive Value of Tests
Transforming Growth Factor beta
Internal medicine
Immunopathology
medicine
Humans
Matrilin Proteins
Immunology and Allergy
Pharmacology (medical)
Genetic Testing
Antigens
Receptors
Immunologic

Glycoproteins
Skin
Cartilage oligomeric matrix protein
Extracellular Matrix Proteins
Membrane Glycoproteins
Scleroderma
Systemic

integumentary system
medicine.diagnostic_test
biology
Surrogate endpoint
business.industry
Reproducibility of Results
medicine.disease
Connective tissue disease
Cytoskeletal Proteins
Skin biopsy
biology.protein
Regression Analysis
Biomarker (medicine)
business
Zdroj: Arthritis & Rheumatism. 62:580-588
ISSN: 1529-0131
0004-3591
DOI: 10.1002/art.27220
Popis: 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 β (TGFβ) and interferon (IFN). These levels were correlated with the MRSS, using multiple regression analyses to obtain best-fit models. Results Skin expression of the TGFβ-regulated genes cartilage oligomeric matrix protein (COMP) and thrombospondin 1 (TSP-1) correlated moderately well with the MRSS, but the addition of other TGFβ-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 R2 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.
Databáze: OpenAIRE