M Nikpour1, A A Dempsey, M B Urowitz, D D Gladman, D A Barnes. 1. University of Toronto Lupus Clinic and Centre for Prognosis Studies in Rheumatic Diseases, Toronto Western Hospital, Toronto, Ontario, Canada.
Abstract
OBJECTIVE: To determine whether peripheral blood gene expression of patients with systemic lupus erythaematosus (SLE) correlates with disease activity measured using the SLE Disease Activity Index 2000 (SLEDAI-2K). METHODS: RNA was isolated from peripheral blood of 269 patients with SLE and profiled on a custom microarray. Hierarchical clustering and a heat map were used to categorise samples into major clusters based on gene expression pattern. Correlates, including demographic and disease-related characteristics such as SLEDAI-2K score, of the major sample clusters were compared using multivariate regression models. RESULTS: A set of 31 interferon (IFN)-regulated genes were seen to be driving the separations of samples into two clusters, one characterised by a relatively high IFN-regulated gene signature (n = 150) and the other by a relatively low IFN-regulated gene signature (n = 119). Disease activity measured using the SLEDAI-2K was significantly correlated with the high IFN gene signature. In multivariate regression analysis the immunological component of the SLEDAI-2K was a significant correlate of the high IFN gene signature as was presence of antibodies to U1RNP. There were no discernable correlates of the 156 non-IFN regulated genes profiled on the custom array. CONCLUSION: Peripheral blood gene expression profiling (GEP) in SLE allows patients to be categorised into two groups based on a high or low IFN gene signature. Disease activity measured using the SLEDAI-2K is correlated with the high IFN gene signature, indicating that GEP may be a useful biomarker of disease activity in SLE.
OBJECTIVE: To determine whether peripheral blood gene expression of patients with systemic lupus erythaematosus (SLE) correlates with disease activity measured using the SLE Disease Activity Index 2000 (SLEDAI-2K). METHODS: RNA was isolated from peripheral blood of 269 patients with SLE and profiled on a custom microarray. Hierarchical clustering and a heat map were used to categorise samples into major clusters based on gene expression pattern. Correlates, including demographic and disease-related characteristics such as SLEDAI-2K score, of the major sample clusters were compared using multivariate regression models. RESULTS: A set of 31 interferon (IFN)-regulated genes were seen to be driving the separations of samples into two clusters, one characterised by a relatively high IFN-regulated gene signature (n = 150) and the other by a relatively low IFN-regulated gene signature (n = 119). Disease activity measured using the SLEDAI-2K was significantly correlated with the high IFN gene signature. In multivariate regression analysis the immunological component of the SLEDAI-2K was a significant correlate of the high IFN gene signature as was presence of antibodies to U1RNP. There were no discernable correlates of the 156 non-IFN regulated genes profiled on the custom array. CONCLUSION: Peripheral blood gene expression profiling (GEP) in SLE allows patients to be categorised into two groups based on a high or low IFN gene signature. Disease activity measured using the SLEDAI-2K is correlated with the high IFN gene signature, indicating that GEP may be a useful biomarker of disease activity in SLE.
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