Treelet transform analysis to identify clusters of systemic inflammatory variance in a population with moderate-to-severe traumatic brain injury
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

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

Filetype[PDF-1.26 MB]


  • English

  • Details:

    • Alternative Title:
      Brain Behav Immun
    • Description:
      Background:

      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.

      Methods:

      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.

      Results:

      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-specific dendrogram and overall dendrogram.

      Conclusions:

      TT effectively characterized chronic, systemic immunity among a cohort of individuals with moderate-to-severe TBI. We posit that chronic chemokine levels are effector molecules propagating cellular immune dysfunction, while chronic soluble receptors are inflammatory damage readouts perpetuated, in part, by persistent dysfunctional cellular immunity to impact neuro-recovery.

    • Pubmed ID:
      33524553
    • Pubmed Central ID:
      PMC9004489
    • Document Type:
    • Collection(s):
    • Main Document Checksum:
    • File Type:

    You May Also Like

    Checkout today's featured content at stacks.cdc.gov