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Mixed-Effects Association of Single Cells Identifies an Expanded Effector CD4+ T Cell Subset in Rheumatoid Arthritis

ABSTRACT: Mixed-Effects Association of Single Cells Identifies an Expanded Effector CD4+ T Cell Subset in Rheumatoid Arthritis

PROVIDER: PRJNA484871 | ENA |

REPOSITORIES: ENA

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Mixed-Effects Association of Single Cells Identifies an Expanded Effector CD4+ T Cell Subset in Rheumatoid Arthritis

Project description:High dimensional single-cell analyses have improved the ability to resolve complex mixtures of cells from human disease samples; however, identifying disease-associated cell types or cell states in patient samples remains challenging due to technical and inter-individual variation. Here we present Mixed-Effects modeling of Associations of Single Cells (MASC), a reverse single cell association strategy for testing whether case-control status influences the membership of single cells in any of multiple cellular subsets while accounting for technical confounders and biological variation. Applying MASC to mass cytometry analyses of CD4+ T cells from the blood of rheumatoid arthritis (RA) patients and controls revealed a significantly expanded population of CD4+ T cells, identified as CD27- HLA-DR+ effector memory cells, in RA patients. The frequency of CD27- HLA-DR+ cells was similarly elevated in blood samples from a second RA patient cohort, and CD27- HLA-DR+ cell frequency decreased in RA patients who responded to immunosuppressive therapy. Mass cytometry and flow cytometry analyses indicated that CD27- HLA-DR+ cells were associated with RA. Compared to peripheral blood, synovial fluid and synovial tissue samples from RA patients contained ~5-fold higher frequencies of CD27- HLA-DR+ cells, which comprised ~10% of synovial CD4+ T cells. CD27- HLA-DR+ cells expressed a distinctive effector memory transcriptomic program with Th1- and cytotoxicity-associated features, and produced abundant IFNg and granzyme A protein upon stimulation. Thus MASC identified the expansion of a unique effector memory CD4+ T cell population in RA. We propose that MASC is a broadly applicable method to identify disease-associated cell populations in high-dimensional single cell data.

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