Mendoza AE, Raju Paul S, El Hechi M, Naar L, Nederpelt C, Mikdad S, van Erp I, Hess JM, Velmahos GC, Poznansky M, Reeves P. Deep immune profiling of whole blood to identify early immune signatures that correlate to patient outcome after major trauma.
J Trauma Acute Care Surg 2021;
90:959-966. [PMID:
33755643 DOI:
10.1097/ta.0000000000003170]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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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