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

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.

Evaluating the Cross-Sectional and Longitudinal Relationships Predicting Suicidal Ideation Following Traumatic Brain Injury.

OBJECTIVE: Characterize relationships among substance misuse, depression, employment, and suicidal ideation (SI) following moderate to severe traumatic brain injury (TBI). DESIGN: Prospective cohort study. SETTING: Inpatient rehabilitation centers with telephone follow-up; level I/II trauma centers in the United States. PARTICIPANTS: Individuals with moderate to severe TBI with data in both the National Trauma Data Bank and the Traumatic Brain Injury Model Systems National Database, aged 18 to 59 years, with SI data at year 1 or year 2 postinjury (N = 1377). MAIN OUTCOME MEASURE: Primary outcome of SI, with secondary employment, substance misuse, and depression outcomes at years 1 and 2 postinjury. RESULTS: Cross-lagged structural equation modeling analysis showed that year 1 unemployment and substance misuse were associated with a higher prevalence of year 1 depression. Depression was associated with concurrent SI at years 1 and 2. Older adults and women had a greater likelihood of year 1 depression. More severe overall injury (injury severity score) was associated with a greater likelihood of year 1 SI, and year 1 SI was associated with a greater likelihood of year 2 SI. CONCLUSIONS: Substance misuse, unemployment, depression, and greater extracranial injury burden independently contributed to year 1 SI; in turn, year 1 SI and year 2 depression contributed to year 2 SI. Older age and female sex were associated with year 1 depression. Understanding and mitigating these risk factors are crucial for effectively managing post-TBI SI to prevent postinjury suicide.

Interrelationships Between Post-TBI Employment and Substance Abuse: A Cross-lagged Structural Equation Modeling Analysis.

OBJECTIVE: To describe the interrelationship of postinjury employment and substance abuse (SA) among individuals with traumatic brain injury. DESIGN: Structural equation model (SEM) and logistic regression analytic approach using a merged database of the National Trauma Data Bank (NTDB) and Traumatic Brain Injury Model Systems (TBIMS) National Database, with acute care and rehabilitation hospitalization data and 1, 2, and 5 year follow-up data. SETTING: United States Level I/II trauma centers and inpatient rehabilitation centers with telephone follow-up. PARTICIPANTS: Individuals in the TBIMS National Database successfully matched to their NTDB data, aged 18-59 years, with trauma severity, age, sex, employment, and SA data at 1, 2, and/or 5 years postinjury (N=2890). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Employment status (employed/unemployed) and SA (present/absent) at year 1, year 2, and year 5 postinjury. RESULTS: SEM analysis showed older age at injury predicted lower likelihood of employment at all time points postinjury (ßYR1=-0.016; ßYR2=-0.006; ßYR5=-0.016; all P<.001), while higher injury severity score (ISS) predicted lower likelihood of employment (ß=-0.008; P=.027) and SA (ß=-0.007; P=.050) at year 1. Male sex predicted higher likelihood of SA at each follow-up (ßYR1=0.227; ßYR2=0.184; ßYR5=0.161; all P<.100). Despite associations of preinjury unemployment with higher preinjury SA, postinjury employment at year 1 predicted SA at year 2 (ß=0.118; P=.028). Employment and SA during the previous follow-up period predicted subsequent employment and SA, respectively. CONCLUSIONS: Employment and SA have unique longitudinal interrelationships and are additionally influenced by age, sex, and ISS. The present work suggests the need for more research on causal, confounding, and mediating factors and appropriate screening and intervention tools that minimize SA and facilitate successful employment-related outcomes.

Employment Stability in the First 5 Years After Moderate-to-Severe Traumatic Brain Injury.

OBJECTIVE: To characterize employment stability and identify predictive factors of employment stability in working-age individuals after moderate-to-severe traumatic brain injury (TBI) that may be clinically addressed. DESIGN: Longitudinal observational study of an inception cohort from the Traumatic Brain Injury Model Systems National Database (TBIMS-NDB) using data at years 1, 2, and 5 post-TBI. SETTING: Inpatient rehabilitation centers with telephone follow-up. PARTICIPANTS: Individuals enrolled in the TBIMS-NDB since 2001, aged 18-59, with employment data at 2 or more follow-up interviews at years 1, 2, and 5 (N=5683). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Employment stability, categorized using post-TBI employment data as no paid employment (53.25%), stably (27.20%), delayed (10.24%), or unstably (9.31%) employed. RESULTS: Multinomial regression analyses identified predictive factors of employment stability, including younger age, white race, less severe injuries, preinjury employment, higher annual earnings, male sex, higher education, transportation independence postinjury, and no anxiety or depression at 1 year post-TBI. CONCLUSIONS: Employment stability serves as an important measure of productivity post-TBI. Psychosocial, clinical, environmental, and demographic factors predict employment stability post-TBI. Notable predictors include transportation independence as well as the presence of anxiety and depression at year 1 post-TBI as potentially modifiable intervention targets.

Early chronic systemic inflammation and associations with cognitive performance after moderate to severe TBI.

BACKGROUND: Cognitive dysfunction adversely effects multiple functional outcomes and social roles after TBI. We hypothesize that chronic systemic inflammation exacerbates cognitive deficits post-injury and diminishes functional cognition and quality of life (QOL). Yet few studies have examined relationships between inflammation and cognition after TBI. Associations between early chronic serum inflammatory biomarker levels, cognitive outcomes, and QOL 6-months and 12-months after moderate-to-severe TBI were identified using unweighted (uILS) and weighted (wILS) inflammatory load score (ILS) formation. METHODS: Adults with moderate-to-severe TBI (n â€‹= â€‹157) completed neuropsychological testing, the Functional Impairment Measure Cognitive Subscale (FIM-Cog) and self-reported Percent Back to Normal scale 6 months (n â€‹= â€‹139) and 12 months (n â€‹= â€‹136) post-injury. Serial serum samples were collected 1-3 months post-TBI. Cognitive composite scores were created as equally weighted means of T-scores derived from a multidimensional neuropsychological test battery. Median inflammatory marker levels associated with 6-month and 12-month cognitive composite T-scores (p â€‹< â€‹0.10) were selected for ILS formation. Markers were quartiled, and quartile ranks were summed to generate an uILS. Marker-specific ß-weights were derived using penalized ridge regression, multiplied by standardized marker levels, and summed to generate a wILS. ILS associations with cognitive composite scores were assessed using multivariable linear regression. Structural equation models assessed ILS influences on functional cognition and QOL using 12-month FIM-Cog and Percent Back to Normal scales. RESULTS: ILS component markers included: IL-1ß, TNF-α, sIL-4R, sIL-6R, RANTES, and MIP-1ß. Increased sIL-4R levels were positively associated with overall cognitive composite T-scores in bivariate analyses, while remaining ILS markers were negatively associated with cognition. Multivariable receiver operator curves (ROC) showed uILS added 14.98% and 31.93% relative improvement in variance captured compared to the covariates only base model (age, sex, education, Glasgow Coma Scale score) when predicting cognitive composite scores at 6 and 12 months, respectively; wILS added 33.99% and 36.87% relative improvement in variance captured. Cognitive composite mediated wILS associations with FIM-Cog scores at 12 months, and both cognitive composite and FIM-Cog scores mediated wILS associations with QOL. CONCLUSIONS: Early chronic inflammatory burden is associated with cognitive performance post-TBI. wILS explains greater variance in cognitive composite T-scores than uILS. Linking inflammatory burden associated with cognitive deficits to functional outcome post-TBI demonstrates the potential impact of immunotherapy interventions aimed at improving cognitive recovery post-TBI.

Temporal Acute Serum Estradiol and Tumor Necrosis Factor-α Associations and Risk of Death after Severe Traumatic Brain Injury.

Severe traumatic brain injury (TBI) activates a robust systemic response that involves inflammatory and other factors, including estradiol (E2), associated with increased deaths. Tumor necrosis factor-alpha (TNFα) is a significant mediator of systemic shock, and it is an extra-gonadal transcription factor for E2 production. The study objectives were to test the hypotheses: (1) a positive feedback relationship exists between acute serum TNFα and E2; and (2) acute concentrations of E2 and TNFα are prognostic indicators of death after severe TBI. This prospective cohort study included N = 157 adults with severe TBI. Serum samples were collected for the first five days post-injury. The TNFα and E2 levels were averaged into two time epochs: first 72 h (T1) and second 72 h post-injury (T2). A cross-lag panel analysis conducted between T1 and T2 TNFα and E2 levels showed significant cross-lag effects: T1 TNFα and T1 E2 were related to T2 E2 and T2 TNFα, respectively. Cox proportional hazards multi variable regression models determined that increases in T1 E2 (hazard ratio [HR] = 1.79, 95% confidence interval [CI]: 1.15, 2.81), but not T2 E2 (HR = 0.91, 95% CI: 0.56, 1.47), were associated with increased risk of death. Increased T2 TNFα (HR = 2.47, 95% CI: 1.35, 4.53), and T1 TNFα (HR = 1.47, 95% CI: 0.99, 2.19), to a lesser degree, were associated with increased risk of death. Relationships of death with T2 TNFα and T1 E2 were mediated partially by cardiovascular, hepatic, and renal dysfunction. Both E2 and TNFα are systemic, reciprocally related biomarkers that may be indicative of systemic compromise and increased risk of death after severe TBI.