GENETIC RISK PROFILE IN LONGITUDINAL SLE COHORTS

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Both genetic and non-genetic factors contribute to the clinical presentations, clinical course, and outcome in SLE. To develop the theme of this SCOR, the genetics of SLE, and to translate the findings to the bedside by characterizing the clinical manifestations associated with the identified genetic markers, we propose to gather a population of well characterized SLE patients by joining efforts with investigators who already have ESTABLISHED longitudinal cohorts and the mechanisms to enroll NEW patients (Drs. Petri, John Hopkins University, MD; Reveille, University of Texas Health Sciences Center, Houston, TX; Ramsey-Goldman, Northwestern University, Chicago, IL) which will constitute the largest single available cohort of SLE patients for such studies (The PROFILE cohort)> With this cohort we will determine the extent to which a given genotype (PROFILE) determines the clinical phenotype. We will also contribute to the constitution of TRIO families for TDT analysis in order to confirm and narrow regions of genetic interest. The specific aims of the study are to: 1) Establish a multi-center common core database of SLE patients from multiple ethnicities comprised of patients who are already in local cohorts (ESTABLISHED) as well as NEW patients to be recruited; 2) Assess the ability of chromosome 1 genes (q21-32, see projects #1-3) to predict disease phenotype [renal, cardiovascular, pulmonary, and central nervous system, (CNS) involvement] in this PROFILE COHORT of SLE patients; 3) Establish a core set of TRIO families and work in conjunction with projects #1-3 and the Genetic Epidemiology and Biostatistics Core to use transmission disequilibrium to confirm the identification of candidate regions and genes in SLE. We have based our power and sample size calculations on the frequency of FcgammaRII H131/H131 in SLE patients with and without renal disease (8% versus 20%) and the frequency of renal disease among lupus patients from one of the center's cohorts. With total number of SLE patients of 600-700, we will have adequate power to demonstrate the skewing of this and other genes in the phenotype of the disease. Descriptive and analytical methods will be used where the phenotype will be the dependent variable and genetic (and other factors) the independent variables. The ability to predict the expression of the disease may have important implications for optimizing therapeutic strategies or developing new therapies for lupus patients.