Mild traumatic brain injury (mTBI) is a costly injury due to its high prevalence and effects on patients' emotional, cognitive, and occupational functioning. Efforts to identify the neurobiological effects of mTBI and develop effective treatments are hampered by limitations in current operational definitions of the injury. This problem stems from heterogeneity in patients' responses to mTBI and conventions to aggregate diffuse, nonspecific symptoms into a single diagnostic category. Although current clinical and research practices treat mTBI as unitary, emerging evidence indicates that clinical presentation following injury is multidimensional, with distinct elements that may be more informative when measured separately. The proposed R03 project will apply modern quantitative methods to establish distinct clinical phenotypes of mTBI with higher potential to inform translational mTBI research.
The aims of the study are to (1) identify the optimal phenotypic model of clinical presentation in both athlete and civilian mTBI patients and (2) test hypotheses regarding sex differences in mTBI phenotypes. The project will be innovative in its application of diverse, advanced quantitative modeling approaches to identify mTBI phenotypes and to compare multiple groups of interest (males and females, athlete and civilians). The proposed work is made possible by the recent availability of sufficiently large, longitudinal datasets of athletes and civilians with mTBI and the collaboration of our team of investigators with diverse clinical, empirical, and methodological expertise relevant to the proposed project. The findings will be significant in yielding novel phenotypic models that (a) could change how the field diagnoses and classifies mTBI and (b) could yield novel clinical targets with tighter or more consistent linkages to neurobiological systems. The long-term goal of this research is to use the findings derived from this project to accelerate efforts to identify the neurobiological mechanisms underlying mTBI and to develop personalized interventions to maximize patients' recoveries from mTBI.
The proposed project is relevant to public health, because mild traumatic brain injury (mTBI) is a highly prevalent and costly injury for which diagnosis is difficult and no effective treatments have yet to be developed. This research proposes to use a novel analytic approach to improve the clinical classification of patients with mTBI and thereby provide evidence-based methods for diagnosing and classifying patients. This could reveal important sources of variability in patients' responses to injury and could yield improved targets that will accelerate neurobiological and treatment research for mTBI.