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Review
. 2021 Dec;38(23):3222-3234.
doi: 10.1089/neu.2021.0059. Epub 2021 Jun 10.

Phenotyping the Spectrum of Traumatic Brain Injury: A Review and Pathway to Standardization

Mary Jo Pugh  1   2 , Eamonn Kennedy  1   2 , Eric M Prager  3 , Jeffrey Humpherys  1   2 , Kristen Dams-O'Connor  4 , Dallas Hack  3 , Mary Katherine McCafferty  1   2 , Jessica Wolfe  3 , Kristine Yaffe  5   6   7 , Michael McCrea  8 , Adam R Ferguson  9   10 , Lee Lancashire  3 , Jamshid Ghajar  11   12 , Angela Lumba-Brown  13   12
Affiliations
Review

Phenotyping the Spectrum of Traumatic Brain Injury: A Review and Pathway to Standardization

Mary Jo Pugh et al. J Neurotrauma. 2021 Dec.

Abstract

It is widely appreciated that the spectrum of traumatic brain injury (TBI), mild through severe, contains distinct clinical presentations, variably referred to as subtypes, phenotypes, and/or clinical profiles. As part of the Brain Trauma Blueprint TBI State of the Science, we review the current literature on TBI phenotyping with an emphasis on unsupervised methodological approaches, and describe five phenotypes that appear similar across reports. However, we also find the literature contains divergent analysis strategies, inclusion criteria, findings, and use of terms. Further, whereas some studies delineate phenotypes within a specific severity of TBI, others derive phenotypes across the full spectrum of severity. Together, these facts confound direct synthesis of the findings. To overcome this, we introduce PhenoBench, a freely available code repository for the standardization and evaluation of raw phenotyping data. With this review and toolset, we provide a pathway toward robust, data-driven phenotypes that can capture the heterogeneity of TBI, enabling reproducible insights and targeted care.

Keywords: clinical profiles; clustering; coma; concussion; meta-analysis; phenotypes; subclassification; subtypes; traumatic brain injury.

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Conflict of interest statement

No competing financial interests exist.

Figures

FIG. 1.
FIG. 1.
Conceptual overview of the progression and divergence of traumatic brain injury (TBI) phenotypes. TBI phenotypes (rectangles) emerge statistically (1–4) from the presence and duration of symptoms/impairments. The prevalence (rectangle size) of phenotypes can vary and evolve over time and can signal recovery or decline. Color image is available online.
FIG. 2.
FIG. 2.
PhenoBench data generation and example outputs from a synthetic post-traumatic epilepsy (PTE) data set. (A) Inset table of means and standard deviations for the synthetic data set (N = 1000). Explanation of the variables are provided in the documentation. (B) Heatmap of the correlation matrix for the 11 synthetic variables. (C) PCA two-principal component reduction of the pseudo data set, shown for two random 50/50 split samples of the data (left, right). Trends in the global structure are similar across subsamples, indicating good group stability, but the PTE group differences are not captured by PCA. (D) Like (C), but with a UMAP reduction of the synthetic data set down to two dimensions. Trends in the global structure are broadly similar, and the PTE phenotype is distinct. (E) Phenotypes are shown in a radial plot broken out across the five clusters found by UMAP embedding in (D). PCA, principal component analysis; UMAP, uniform manifold approximation and projection. Color image is available online.
See this image and copyright information in PMC

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