High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status
Matthew J. Camiolo,
Xiaoying Zhou,
Timothy B. Oriss,
Qi Yan,
Michael Gorry,
William Horne,
John B. Trudeau,
Kathryn Scholl,
Wei Chen,
Jay K. Kolls,
Prabir Ray,
Florian J. Weisel,
Nadine M. Weisel,
Nima Aghaeepour,
Kari Nadeau,
Sally E. Wenzel,
Anuradha Ray
Affiliations
Matthew J. Camiolo
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
Xiaoying Zhou
Sean N Parker Center for Allergy Research and Division of Pulmonary, Allergy, and Critical Care Medicine, Stanford University, Stanford, CA, USA
Timothy B. Oriss
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Qi Yan
Division of Pulmonary Medicine, Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Michael Gorry
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
William Horne
Richard King Mellon Foundation Institute for Pediatric Research, Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
John B. Trudeau
Department of Environmental Medicine and Occupational Health, Graduate School of Public Health, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Kathryn Scholl
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Wei Chen
Division of Pulmonary Medicine, Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Jay K. Kolls
Department of Medicine and Center for Translational Research in Infection and Inflammation Tulane School of Medicine, New Orleans, LA, USA
Prabir Ray
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Florian J. Weisel
Departments of Anesthesiology, Pain, and Peri-operative Medicine and Biomedical Data Sciences, Stanford University, Stanford, CA, USA
Nadine M. Weisel
Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Nima Aghaeepour
Departments of Anesthesiology, Pain, and Peri-operative Medicine and Biomedical Data Sciences, Stanford University, Stanford, CA, USA
Kari Nadeau
Sean N Parker Center for Allergy Research and Division of Pulmonary, Allergy, and Critical Care Medicine, Stanford University, Stanford, CA, USA
Sally E. Wenzel
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Environmental Medicine and Occupational Health, Graduate School of Public Health, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Anuradha Ray
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Corresponding author
Summary: 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)-γ+ T cells, 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−FcεRI+CD127+IL-4+ innate cells in one patient group, contrasting with adaptive immune response in T cells 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.
