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Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations
Published on: January 19, 2017
Widely divergent transcriptional patterns between SLE patients of different ancestral backgrounds in sorted immune
Shruti Sharma1, Zhongbo Jin2, Elizabeth Rosenzweig1
1University of Chicago, Gwen Knapp Center for Lupus Research.
Abstract:
Systemic lupus erythematosus (SLE) is a complex autoimmune disease of uncertain etiology. Patients from different ancestral backgrounds demonstrate differences in clinical manifestations and autoantibody profiles. We examined genome-wide transcriptional patterns in major immune cell subsets across different ancestral backgrounds. Peripheral blood was collected from African-American (AA) and European-American (EA) SLE patients and controls. CD4 T-cells, CD8 T-cells, monocytes, and B cells were purified by flow sorting, and each cell subset from each subject was run on a genome-wide expression array. Cases were compared to controls of the same ancestral background. The overlap in differentially expressed gene (DEG) lists between different cell types from the same ancestral background was modest (<10%), and only 5-8% overlap in DEG lists was observed when comparing the same cell type between different ancestral backgrounds. IFN-stimulated gene (ISG) expression was not up-regulated synchronously in all cell types from a given patient, for example a given subject could have high ISG expression in T and B cells, but not in monocytes. AA subjects demonstrated more concordance in ISG expression between cell types from the same individual, and AA patients demonstrated significant down-regulation of metabolic gene expression which was not observed in EA patients. ISG expression was significantly decreased in B cells in patients taking immunosuppressants, while ISGs in other cell types did not differ with medication use. In conclusion, gene expression was strikingly different between immune cell subsets and between ancestral backgrounds in SLE patients. These findings emphasize the critical importance of studying multiple ancestral backgrounds and multiple cell types in gene expression studies. Ancestral backgrounds which are not studied will not benefit from personalized medicine strategies in SLE.
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