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High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status. Cell reports Camiolo, M. J., Zhou, X., Oriss, T. B., Yan, Q., Gorry, M., Horne, W., Trudeau, J. B., Scholl, K., Chen, W., Kolls, J. K., Ray, P., Weisel, F. J., Weisel, N. M., Aghaeepour, N., Nadeau, K., Wenzel, S. E., Ray, A. 2021; 35 (2): 108974

Abstract

Clinical definitions of asthma fail to capture the heterogeneity of immune dysfunction in severe, treatment-refractory disease. Applying mass cytometry and machine learning to bronchoalveolar lavage (BAL) cells, we find that corticosteroid-resistant asthma patients cluster largely into two groups: one enriched in interleukin (IL)-4+ innate immune cells and another dominated by interferon (IFN)-gamma+ Tcells, including tissue-resident memory cells. In contrast, BAL cells of a healthier population are enriched in IL-10+ macrophages. To better understand cellular mediators of severe asthma, we developed the Immune Cell Linkage through Exploratory Matrices (ICLite) algorithm to perform deconvolution of bulk RNA sequencing of mixed-cell populations. Signatures of mitosis and IL-7 signaling in CD206-FcepsilonRI+CD127+IL-4+ innate cells in one patient group, contrasting with adaptive immune response in Tcells in the other, are preserved across technologies. Transcriptional signatures uncovered by ICLite identify T-cell-high and T-cell-poor severe asthma patients in an independent cohort, suggesting broad applicability of our findings.

View details for DOI 10.1016/j.celrep.2021.108974

View details for PubMedID 33852838