Treelet transform analysis to identify clusters of systemic inflammatory variance in a population with moderate-to-severe traumatic brain injury

•We utilized treelet transform to identify 5 clusters of biomarkers post-TBI.•The adaptive immunity cluster contributed the most variance to the treelet.•Innate and soluble receptor clusters were associated with poor long-term outcome.•Our results explore the intersection of inflammation and outcome...

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Veröffentlicht in:Brain, behavior, and immunity behavior, and immunity, 2021-07, Vol.95, p.45-60
Hauptverfasser: Vijapur, Sushupta M., Vaughan, Leah E., Awan, Nabil, DiSanto, Dominic, McKernan, Gina P., Wagner, Amy K.
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Sprache:eng
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Zusammenfassung:•We utilized treelet transform to identify 5 clusters of biomarkers post-TBI.•The adaptive immunity cluster contributed the most variance to the treelet.•Innate and soluble receptor clusters were associated with poor long-term outcome.•Our results explore the intersection of inflammation and outcomes post-TBI.•We show a methodology which may enhance future studies on immunity post-TBI. Inflammatory cascades following traumatic brain injury (TBI) can have both beneficial and detrimental effects on recovery. Single biomarker studies do not adequately reflect the major arms of immunity and their relationships to long-term outcomes. Thus, we applied treelet transform (TT) analysis to identify clusters of interrelated inflammatory markers reflecting major components of systemic immune function for which substantial variation exists among individuals with moderate-to-severe TBI. Serial blood samples from 221 adults with moderate-to-severe TBI were collected over 1–6 months post-injury (n = 607 samples). Samples were assayed for 33 inflammatory markers using Millipore multiplex technology. TT was applied to standardized mean biomarker values generated to identify latent patterns of correlated markers. Treelet clusters (TC) were characterized by biomarkers related to adaptive immunity (TC1), innate immunity (TC2), soluble molecules (TC3), allergy immunity (TC4), and chemokines (TC5). For each TC, a score was generated as the linear combination of standardized biomarker concentrations and cluster load for each individual in the cohort. Ordinal logistic or linear regression was used to test associations between TC scores and 6- and 12-month Glasgow Outcome Scale (GOS), Disability Rating Scale (DRS), and covariates. When adjusting for clinical covariates, TC5 was significantly associated with 6-month GOS (odds ratio, OR = 1.44; p-value, p = 0.025) and 6-month DRS scores (OR = 1.46; p = 0.013). TC5 relationships were attenuated when including all TC scores in the model (GOS: OR = 1.29, p = 0.163; DRS: OR = 1.33, p = 0.100). When adjusting for all TC scores and covariates, only TC3 was associated with 6- and 12-month GOS (OR = 1.32, p = 0.041; OR = 1.39, p = 0.002) and also 6- and 12-month DRS (OR = 1.38, p = 0.016; OR = 1.58, p = 0.0002). When applying TT to inflammation markers significantly associated with 6-month GOS, multivariate modeling confirmed that TC3 remained significantly associated with GOS. Biomarker cluster membership remained consistent between the GOS
ISSN:0889-1591
1090-2139
DOI:10.1016/j.bbi.2021.01.026