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A road map from single-cell transcriptome to patient classification for the immune response to trauma
Tianmeng Chen, Matthew J. Delano, Kong Chen, Jason L. Sperry, Rami A. Namas, Ashley J. Lamparello, Meihong Deng, Julia Conroy, Lyle L. Moldawer, Philip A. Efron, Patricia Loughran, Christopher Seymour, Derek C. Angus, Yoram Vodovotz, Wei Chen, Timothy R. Billiar
Tianmeng Chen, Matthew J. Delano, Kong Chen, Jason L. Sperry, Rami A. Namas, Ashley J. Lamparello, Meihong Deng, Julia Conroy, Lyle L. Moldawer, Philip A. Efron, Patricia Loughran, Christopher Seymour, Derek C. Angus, Yoram Vodovotz, Wei Chen, Timothy R. Billiar
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Research Article Immunology Inflammation

A road map from single-cell transcriptome to patient classification for the immune response to trauma

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Abstract

Immune dysfunction is an important factor driving mortality and adverse outcomes after trauma but remains poorly understood, especially at the cellular level. To deconvolute the trauma-induced immune response, we applied single-cell RNA sequencing to circulating and bone marrow mononuclear cells in injured mice and circulating mononuclear cells in trauma patients. In mice, the greatest changes in gene expression were seen in monocytes across both compartments. After systemic injury, the gene expression pattern of monocytes markedly deviated from steady state with corresponding changes in critical transcription factors, which can be traced back to myeloid progenitors. These changes were largely recapitulated in the human single-cell analysis. We generalized the major changes in human CD14+ monocytes into 6 signatures, which further defined 2 trauma patient subtypes (SG1 vs. SG2) identified in the whole-blood leukocyte transcriptome in the initial 12 hours after injury. Compared with SG2, SG1 patients exhibited delayed recovery, more severe organ dysfunction, and a higher incidence of infection and noninfectious complications. The 2 patient subtypes were also recapitulated in burn and sepsis patients, revealing a shared pattern of immune response across critical illness. Our data will be broadly useful to further explore the immune response to inflammatory diseases and critical illness.

Authors

Tianmeng Chen, Matthew J. Delano, Kong Chen, Jason L. Sperry, Rami A. Namas, Ashley J. Lamparello, Meihong Deng, Julia Conroy, Lyle L. Moldawer, Philip A. Efron, Patricia Loughran, Christopher Seymour, Derek C. Angus, Yoram Vodovotz, Wei Chen, Timothy R. Billiar

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Figure 8

Overview of the transcriptomic changes in PBMCs from trauma patients over time.

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Overview of the transcriptomic changes in PBMCs from trauma patients ove...
(A) Experimental design for human scRNA-Seq experiments. Blood samples for PBMC isolation were obtained within 4 hours of injury and at 24 hours and 72 hours after injury from 10 patients. Blood drawn from a healthy age- and sex-matched uninjured volunteer was used to establish the baseline for each patient. The 72-hour samples from 2 patients are not available, for a total of 38 samples (Ctrl: n = 10; <4 hours: n = 10; 24 hours: n = 10; 72 hours: n = 8). (B) UMAP plot of all human PBMCs are color-coded by major cell types. (C) Expression of major lineage markers in each cell type shown in B. (D) Changes of cell type composition in each patient along with matched control subject. (E) UMAP plot as shown in B wrapped by patients and color-coded by time points. (F) The number of significant DEGs (compared with healthy control, Bonferroni-adjusted P < 0.05) at different time points in major cell types.

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ISSN 2379-3708

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