Inflammation biomarkers IL‑6 and IL‑10 may improve the diagnostic and prognostic accuracy of currently authorized traumatic brain injury tools

Systemic and cerebro-cardiac biomarkers following traumatic brain injury: an interim analysis of randomized controlled clinical trial of early administration of beta blockers

This is an interim analysis of the Beta-blocker (Propranolol) use in traumatic brain injury (TBI) based on the high-sensitive troponin status (BBTBBT) study. The BBTBBT is an ongoing double-blind placebo-controlled randomized clinical trial with a target sample size of 771 patients with TBI. We sought, after attaining 50% of the sample size, to explore the impact of early administration of beta-blockers (BBs) on the adrenergic surge, pro-inflammatory cytokines, and the TBI biomarkers linked to the status of high-sensitivity troponin T (HsTnT). Patients were stratified based on the severity of TBI using the Glasgow coma scale (GCS) and HsTnT status (positive vs negative) before randomization. Patients with positive HsTnT (non-randomized) received propranolol (Group-1; n = 110), and those with negative test were randomized to receive propranolol (Group-2; n = 129) or placebo (Group-3; n = 111). Propranolol was administered within 24 h of injury for 6 days, guided by the heart rate (> 60 bpm), systolic blood pressure (≥ 100 mmHg), or mean arterial pressure (> 70 mmHg). Luminex and ELISA-based immunoassays were used to quantify the serum levels of pro-inflammatory cytokines (Interleukin (IL)-1β, IL-6, IL-8, and IL-18), TBI biomarkers [S100B, Neuron-Specific Enolase (NSE), and epinephrine]. Three hundred and fifty patients with comparable age (mean 34.8 ± 9.9 years) and gender were enrolled in the interim analysis. Group 1 had significantly higher baseline levels of IL-6, IL-1B, S100B, lactate, and base deficit than the randomized groups (p = 0.001). Group 1 showed a significant temporal reduction in serum IL-6, IL-1β, epinephrine, and NSE levels from baseline to 48 h post-injury (p = 0.001). Patients with severe head injuries had higher baseline levels of IL-6, IL-1B, S100B, and HsTnT than mild and moderate TBI (p = 0.01). HsTnT levels significantly correlated with the Injury Severity Score (ISS) (r = 0.275, p = 0.001), GCS (r = - 0.125, p = 0.02), and serum S100B (r = 0.205, p = 0.001). Early Propranolol administration showed a significant reduction in cytokine levels and TBI biomarkers from baseline to 48 h post-injury, particularly among patients with positive HsTnT, indicating the potential role in modulating inflammation post-TBI.Trial registration: ClinicalTrials.gov NCT04508244. It was registered first on 11/08/2020. Recruitment started on 29 December 2020 and is ongoing. The study was partly presented at the 23rd European Congress of Trauma and Emergency Surgery (ECTES), April 28-30, 2024, in Estoril, Lisbon, Portugal.

Plasma profiles of inflammatory cytokines in children with moderate to severe traumatic brain injury: a prospective cohort study

The role of inflammatory cytokines in children with moderate to severe TBI (m-sTBI) is still incompletely understood. We aimed to investigate the associations between early plasma expression profiles of inflammatory cytokines and clinical outcomes in children with m-sTBI. We prospectively recruited children admitted to the intensive care unit (ICU) of a tertiary pediatric hospital due to m-sTBI from November 2022 to May 2023. Plasma interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17A, interferon (IFN)-α, IFN-γ and tumor necrosis factor (TNF)-α concentrations were detected by flow cytometry on admission and on days 5 to 7. The primary outcome was in-hospital mortality. The secondary outcome was the 6-month functional outcome assessed by the Glasgow Outcome Scale Extended-Pediatrics (GOS-E Peds) score, dichotomized as favorable (1-4) or unfavorable (5-8). Fifty patients and 20 healthy controls were enrolled. Baseline IL-6, IL-8 and IL-10 levels were significantly higher in TBI patients than in healthy controls. Twelve patients died in the hospital. Compared with survivors, nonsurvivors had significantly increased baseline IL-6 and IL-8 levels. Baseline IL-5, IL-6 and IL-8 levels were also significantly greater in children with unfavorable versus favorable outcomes. The area under the receiver operating characteristic curve (AUC) of the IL-6 and IL-8 levels and motor Glasgow Coma Scale (GCS) score for predicting in-hospital mortality was 0.706, 0.754, and 0.776, respectively. Baseline IL-1β, IL-2, IL-4, IL-10, IL-12p70, IL-17A, IFN-γ, IFN-α and TNF-α levels were not associated with in-hospital mortality or an unfavorable 6-month outcome. On days 5 to 7, the IL-6 and IL-8 levels were significantly decreased in survivors but increased in nonsurvivors compared to their respective baselines.

CONCLUSION

After m-sTBI, the plasma profiles of inflammatory cytokines are markedly altered in children. The trends of IL-6 and IL-8 expression vary among m-sTBI children with different outcomes. Elevated plasma IL-6 and IL-8 levels are related to in-hospital mortality and unfavorable 6-month outcomes.

TRIAL REGISTRATION

This trial was registered in the Chinese Clinical Trial Registry (Registration number: ChiCTR2200065505). Registered November 7, 2022.

WHAT IS KNOWN

• Inflammation is an important secondary physiological response to TBI.

WHAT IS NEW

• The plasma profiles of inflammatory cytokines are markedly altered in children with m-sTBI. Elevated IL-6 and IL-8 levels are related to mortality and unfavorable outcomes.

Differences in Eotaxin Serum Levels between Polytraumatized Patients with and without Concomitant Traumatic Brain Injury-A Matched Pair Analysis

Background/Objectives: Early detection of traumatic brain injury (TBI) is crucial for minimizing secondary neurological damage. Our study aimed to assess the potential of IL-4, IL-6, IL-7, IL-8, IL-10, TNF, and eotaxin serum levels-as a single clinical tool or combined into a panel-for diagnosing TBI in multiple injured patients. Methods: Out of 110 prospectively enrolled polytrauma victims (median age, 39 years; median ISS, 33; 70.9% male) admitted to our level I trauma center over four years, we matched 41 individuals with concomitant TBI (TBI cohort) to 41 individuals without TBI (non-TBI cohort) based on age, gender, Injury Severity Score (ISS), and mortality. Patients' protein levels were measured upon admission (day 0) and on days 1, 3, 5, 7, and 10 during routine blood withdrawal using one separation gel tube each time. Results: The median serum levels of IL-4, IL-6, IL-7, IL-8, IL-10, and TNF exhibited non-similar time courses in the two cohorts and showed no significant differences on days 0, 1, 3, 5, and 7. However, the median eotaxin levels had similar trend lines in both cohorts, with consistently higher levels in the TBI cohort, reaching significance on days 0, 3, and 5. In both cohorts, the median eotaxin level significantly decreased from day 0 to day 1, then significantly increased until day 10. We also found a significant positive association between day 0 eotaxin serum levels and the presence of TBI, indicating that for every 20 pg/mL increase in eotaxin level, the odds of a prevalent TBI rose by 10.5%. ROC analysis provided a cutoff value of 154 pg/mL for the diagnostic test (sensitivity, 0.707; specificity, 0.683; AUC = 0.718). Conclusions: Our findings identified the brain as a significant source, solely of eotaxin release in humans who have suffered a TBI. Nevertheless, the eotaxin serum level assessed upon admission has limited diagnostic value. IL-4, IL-6, IL-7, IL-8, IL-10, and TNF do not indicate TBI in polytraumatized patients.

Multiplexed Quantitative Proteomics Reveals Proteomic Alterations in Two Rodent Traumatic Brain Injury Models

In many cases of traumatic brain injury (TBI), conspicuous abnormalities, such as scalp wounds and intracranial hemorrhages, abate over time. However, many unnoticeable symptoms, including cognitive, emotional, and behavioral dysfunction, often last from several weeks to years after trauma, even for mild injuries. Moreover, the cause of such persistence of symptoms has not been examined extensively. Recent studies have implicated the dysregulation of the molecular system in the injured brain, necessitating an in-depth analysis of the proteome and signaling pathways that mediate the consequences of TBI. Thus, in this study, the brain proteomes of two TBI models were examined by quantitative proteomics during the recovery period to determine the molecular mechanisms of TBI. Our results show that the proteomes in both TBI models undergo distinct changes. A bioinformatics analysis demonstrated robust activation and inhibition of signaling pathways and core proteins that mediate biological processes after brain injury. These findings can help determine the molecular mechanisms that underlie the persistent effects of TBI and identify novel targets for drug interventions.

Fluid-Based Protein Biomarkers in Traumatic Brain Injury: The View from the Bedside

There has been an explosion of research into biofluid (blood, cerebrospinal fluid, CSF)-based protein biomarkers in traumatic brain injury (TBI) over the past decade. The availability of very large datasets, such as CENTRE-TBI and TRACK-TBI, allows for correlation of blood- and CSF-based molecular (protein), radiological (structural) and clinical (physiological) marker data to adverse clinical outcomes. The quality of a given biomarker has often been framed in relation to the predictive power on the outcome quantified from the area under the Receiver Operating Characteristic (ROC) curve. However, this does not in itself provide clinical utility but reflects a statistical association in any given population between one or more variables and clinical outcome. It is not currently established how to incorporate and integrate biofluid-based biomarker data into patient management because there is no standardized role for such data in clinical decision making. We review the current status of biomarker research and discuss how we can integrate existing markers into current clinical practice and what additional biomarkers do we need to improve diagnoses and to guide therapy and to assess treatment efficacy. Furthermore, we argue for employing machine learning (ML) capabilities to integrate the protein biomarker data with other established, routinely used clinical diagnostic tools, to provide the clinician with actionable information to guide medical intervention.