Gene Expression as Predictors of Outcome in the GENISOS (Genetics vs Environm

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Systemic sclerosis (SSc) is a chronic disease characterized by fibrosis, vascular damage, and autoimmune phenomena. The etiology is unknown and the clinical spectrum is highly variable. Our study HYPOTHESIS is that prognosis in SSc can be predicted by gene expression profiling correlated with clinical, serologic and genetic/ethnic factors as well as sociodemographic features. Our SPECIFIC AIMS are as follows: 1) To perform classification analysis of peripheral blood gene-expression-profiles and skin biopsies from patients with early limited SSc, early diffuse SSc and matched healthy controls; 2) To compare these profiles in blood and skin biopsies from patients in the stable chronic phase of diffuse SSc to profiles from early, diffuse SSc both longitudinally (within individual patients) and in cross-sectional fashion (between separate patient groups); 3) to expand the multi-ethnic (Caucasian, Hispanic, and African-American) GENISOS early-disease SSc cohort following subjects longitudinally for disease relevant outcomes: 4) to characterize the cohort according to demographics, racial-ethnic background, clinical disease features, autoantibody subsets, HLA and other genetic testing, and socio-behavioral features; 5) To develop a model using the data from aims 1 through 4 to identify subsets of patients and predict prognosis; and 6) to provide clinical material from this cohort to support Project 1 of this CORT. DESIGN and METHODS: SSc patients with <5 years of disease will be enrolled and followed at defined intervals using standardized forms. Serial blood samples will be obtained on all and skin biopsies will be done on some participants. Custom printed 50-oligonucleotide microarrays representing 19,700 human and 208 Arabidopsis (negative controls) genes will be used and supervised methods and class comparison will be used to discover differentially regulated genes between predefined classes (e.g., early diffuse SSc vs late diffuse SSc).GEE analysis will be used to examine the association between the outcomes (e.g..course of skin disease, pulmonary fibrosis, etc.) and independent variables (e.g., demographic, HLA, microarray data, etc.) LAY LANGUAGE SUMMARY: This project will study patients with the recent onset of scleroderma in order to identify features that distinguish those who will have mild disease from those who will have a more severe course. This information will help physicians and patients decide on a treatment plan that is appropriate for their level of disease.