Mixed-effects association of single cells identifies an expanded effector CD4(+) T cell subset in rheumatoid arthritis.

Mixed-effects association of single cells identifies an expanded effector CD4(+) T cell subset in rheumatoid arthritis.
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DOI:
10.1126/scitranslmed.aaq0305
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发表时间:
2018-10-17
影响因子:
17.1
通讯作者:
Raychaudhuri S
Raychaudhuri S
中科院分区:
医学1区
文献类型:
--
作者:
Fonseka CY;Rao DA;Teslovich NC;Korsunsky I;Hannes SK;Slowikowski K;Gurish MF;Donlin LT;Lederer JA;Weinblatt ME;Massarotti EM;Coblyn JS;Helfgott SM;Todd DJ;Bykerk VP;Karlson EW;Ermann J;Lee YC;Brenner MB;Raychaudhuri S

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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 (OR = 1.7; p = 1.1 × 10−3). 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 (meta-analysis p = 2.3 × 10−4). 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 IFN-γ and granzyme A protein upon stimulation. We propose that MASC is a broadly applicable method to identify disease-associated cell populations in high-dimensional single cell data. Mixed-effects regression of single-cell data accounts for confounding variation and reveals an expanded CD4+ T cell population in rheumatoid arthritis.
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