Deep immune profiling of whole blood to identify early immune signatures that correlate to patient outcome after major trauma.

J Trauma Acute Care Surg

From the Division of Trauma, Emergency Surgery & Surgical Critical Care, Department of Surgery (A.E.M., M.E.H., L.N., C.N., S.M., I.v.E., G.C.V.), and Vaccine and Immunotherapy Center, Division of Infectious Diseases, Department of Medicine (S.R.P., J.H., M.P., P.R.), Massachusetts General Hospital, Boston, Massachusetts.

Published: June 2021

AI Article Synopsis

  • Major injuries trigger an immune response that can lead to a higher risk of infections and complications, making early identification of immune signatures crucial for predicting patient outcomes.
  • In a study of 17 trauma patients, blood samples were analyzed at Days 1 and 3 post-injury, revealing immune cell clusters linked to clinical outcomes and patient recovery.
  • Results showed that certain immune cells, like immature neutrophils and classical monocytes, correlated with longer hospital stays, while specific T-cell subsets (Th17) were associated with better outcomes, such as fewer ventilator days and less kidney injury.

Article Abstract

Background: Major injury results in an early cascade of immunologic responses that increase susceptibility to infection and multiorgan dysfunction. Detailed immune profiling by mass cytometry has the potential to identify immune signatures that correspond to patient outcomes. Our objective was to determine the prognostic value of immune signatures early after major trauma injury.

Methods: Trauma patients (n = 17) were prospectively enrolled between September 2018 and December 2019. Serial whole blood samples were obtained from trauma patients (mean Injury Severity Score, 26.2; standard error of the mean, 3.7) at Days 1 and 3 after injury, and from age- and sex-matched uninjured controls using a standardized protocol for fixation, storage, and labeling. Computational analyses including K-nearest neighbor automated clustering of immune cells and Spearman's correlation analysis were used to identify correlations between cell populations, clinical measures, and patient outcomes.

Results: Analysis revealed nine immune cell clusters that correlated with one or more clinical outcomes. On Days 1 and 3 postinjury, the abundance of immature neutrophil and classical monocytes exhibited a strong positive correlation with increased intensive care unit and hospital length of stay. Conversely, the abundance of CD4 T-cell subsets, namely Th17 cells, is associated with improved patient outcomes including decreased ventilator days (r = -0.76), hospital-acquired pneumonia (r = -0.69), and acute kidney injury (r = -0.73).

Conclusion: Here, we provide a comprehensive multitime point immunophenotyping analysis of whole blood from patients soon after traumatic injury to determine immune correlates of adverse outcomes. Our findings indicate that alterations in myeloid-origin cell types may contribute to immune dysfunction after injury. Conversely, the presence of effector T cell populations corresponds with decreased hospital length of stay and organ dysfunction. Overall, these data identify novel immune signatures following traumatic injury that support the view that monitoring of immune (sub)-populations may provide clinical decision-making support for at-risk patients early in their hospital course.

Level Of Evidence: Prognostic/Epidemiologic, Level IV.

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Source
http://dx.doi.org/10.1097/TA.0000000000003170DOI Listing

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