Parsimonious immune-response endotypes and global outcome in patients with traumatic brain injury

Abstract

Background: The inflammatory response in patients with traumatic brain injury (TBI) offers opportunities for stratification and intervention. Previous unselected approaches to immunomodulation in patients with TBI have not improved patient outcomes.

Methods: Serum and plasma samples from two prospective, multi-centre observational studies of patients with TBI were used to discover (Collaborative European NeuroTrauma Effectiveness Research [CENTER-TBI], Europe) and validate (Transforming Research and Clinical Knowledge in Traumatic Brain Injury [TRACK-TBI] Pilot, USA) individual variations in the immune response using a multiplex panel of 30 inflammatory mediators. Mediators that were associated with unfavourable outcomes (Glasgow outcome score-extended [GOS-E] ≤ 4) were used for hierarchical clustering to identify patients with similar signatures.

Findings: Two clusters were identified in both the discovery and validation cohorts, termed early-inflammatory and pauci-inflammatory. The early-inflammatory phenotype had higher concentrations of interleukin-6 (IL-6), IL-15, and monocyte chemoattractant protein 1 (MCP1). Patients with the early-inflammatory phenotype were older and more likely to have an unfavourable GOS-E at 6 months. There were no differences in the baseline injury severity scores between patients in each phenotype. A combined IL-15 and MCP1 signature identified patients with the early-inflammatory phenotype in both cohorts. Inflammatory processes mediated outcomes in older patients with moderate-severe TBI.

Interpretation: Our findings offer a precision medicine approach for future clinical trials of immunomodulation in patients with TBI, by using inflammatory signatures to stratify patients.

Funding: CENTER-TBI study was supported by the European Union 7th Framework Programme. TRACK-TBI is supported by the National Institute of Neurological Disorders and Stroke.

Keywords: Clustering; Inflammation; Stratified medicine; Traumatic brain injury.

Fig. 1

Flow diagram demonstrating the number of samples used for analysis in each cohort (CENTER-TBI n = 135, TRACK-TBI n = 33).

Fig. 2

The concentrations and distributions of inflammatory mediators in patients with moderate-severe TBI, at the time of admission to hospital that were significantly associated with unfavourable outcomes in the discovery cohort (CENTER-TBI, n = 135, single samples, no biological or technical replicates). Points are individual patient values. The distributions of the data are demonstrated by the box plot (box: median, IQR; whiskers: 1.5∗IQR) and violin plots (kernel density estimate).

Fig. 3

The inflammatory mediators associated with outcomes in TBI are related to divergent inflammatory processes. (a) Network analysis of the cytokines associated with outcomes using Metacore software which identified STAT1 and STAT3 as being central transcription factors closely related to IL-6, IL-8, IL-15 and MCP1. (b) Heatmaps showing the scaled values of inflammatory mediators in each cluster, alongside patient outcomes, in both cohorts (CENTER-TBI n = 135, TRACK-TBI n = 33). There was a consistent higher concentration of IL-15 in both early-inflammatory clusters (CENTER-TBI n = 106, TRACK-TBI n = 23). (c) Stacked bar charts showing the relative proportions of patients at each functional outcome level for the GOS-E score for patients in each cluster, in both the discovery and validation cohorts. Although we dichotomised outcomes at a binary level in our analysis (favourable = GOS-E > 4), it is apparent that a greater proportion of patients in the pauci-inflammatory cluster had favourable outcomes at all levels of the GOS-E in both cohorts (CENTER-TBI p = 0.0036, TRACK-TBI p = 0.036).

Fig. 4

Directed acyclic graph demonstrating the causal model used to describe the relationships between TBI, outcome at 6 months and inflammation whilst accounting for important confounders such as age and major extracranial injury (MEI). Age was found to confound both inflammation and GFAP with respect to outcome, whilst MEI was conditionally independent of GFAP concentrations. The orange and blue lines demonstrate the direct and mediated causal paths respectively. Mediation analysis was used to calculate the contribution of inflammatory processes on patient outcomes.

Fig. 5

Principal component analysis loadings plot of the brain injury biomarkers (GFAP, NFL, NSE, S100B, Tau, UCH L1) and inflammatory mediators (IL-6, IL-8, IL-15, IL-16, MCP1) measured in patients recruited to CENTER-TBI (n = 135). Brain injury biomarkers were colinear with each other, as were the inflammatory mediators that defined the early-inflammatory cluster. However, as two different sets of protein biomarkers they appear to be orthogonal, primarily separated in the second principal component (PC). To assess whether they were orthogonal across all principal components, we calculated the dot product of the brain injury biomarker and inflammatory mediator loadings, weighted by their relative explained variances. The calculated dot product was equal to −0.019 (95% CI −0.074 to +0.035) which was consistent with an orthogonal relationship across all PCs.

Fig. 6

Visual summary of the study findings, highlighting the patient population that was studied, key components that defined the inflammatory endotypes and their relationship with confounding variables (age, major extracranial injury) and patient outcomes.