Kudos to Karin Reuter-Rice, associate professor, and her entire team for the submission of her American College of Radiology (U54) subcontract application entitled: “Neuroimaging, Oculomotor, and Blood-Based Biologic Markers of Persistent Concussive Symptoms in the Early and Middle Adolescent Population.” This project requests funding for a five-year period with a start date of July 1 2021. Reuter-Rice and her team at Duke will be responsible for the U54’s genetic data generation, analyses and interpretation from 600 adolescents with concussion and appropriate demographically matched controls. She will also work collaboratively with Jessica Gill at NIH who will examine complementary inflammatory cytokines.

Abstract

Persistent concussive symptoms in the early and middle adolescent (EMA) population often result in decreased academic performance and can lead to reduced quality of life. To generate a truly predictive risk-stratification algorithm at the individual patient level for determining persistent symptoms, quantitative biological measures must be brought to bear that are: 1) relevant to the pathophysiology of injury, 2) capable of producing highly granular “big data” features, and 3) fully translational, i.e., able to characterize underlying mechanisms that can be recapitulated into currently existing or new common data elements (CDEs), as well as practical, efficient, and easily implemented in diverse clinical settings where patients present; e.g., emergency departments, urgent care clinics, sports medicine clinics and primary care offices.

For this proposal, we have strategically chosen biological measures that achieve these requirements and, when combined together, will be ideally suited to fuel data-driven predictive analytic methods that will result in a risk stratification algorithm for persistent concussive symptoms among the EMA population. These biological measures will be derived from: magnetic resonance imaging (MRI), visual/oculomotor function testing and blood-derived biologic analyses, all of which have been applied to study traumatic brain injury (TBI) and measure complementary aspects that may underlie the pathophysiology of persistent concussive-symptoms. This proposal leverages key leadership of the NIH Adolescent Brain Cognitive Development (ABCD) study throughout the project and supporting cores (Clinical Core, Biologic-Signal Processing Core and Biostatistics Core) and will implement ABCD-associated protocols, methods and data informatics/processing pipelines along with strategically chosen methods from TRACK-TBI and NCAA/DoD Care that will facilitate future comparisons between the proposed study, the ABCD developmental database, and other large studies of TBI, thus amplifying the potential significance of these data for future investigative work and data sharing. The American College of Radiology (ACR) will serve as both the Administrative Core and Data Coordinating Core to support the project and ensure proper leadership/study team management as well as proper data collection and routing in order to achieve the aims in this proposal and successfully execute milestones.

We will pursue these goals via three specific aims (SA):

• Specific Aim 1: To acquire high-quality quantitative multi-modal biological measures from an EMA cohort via cross-sequential study design enriched for acute (< 3 days) and persistent (> 3 months) concussive symptoms for the purposes of biologic marker discovery and validation, as well as large-scale data sharing via FITBIR and BioSEND. Several NINDS core TBI CDEs and appropriate unique data elements (UDEs) will be acquired from four target biological measures: MRI, visual/functional oculomotor, and blood based biologic metrics. Additional CDE and UDE measurements will include focused concussive symptom evaluations and an extensive battery of demographic/cognitive/psychiatric measures that parallel participant phenotyping within the ABCD study. The target biological measures, concussive symptom measurement data, and ABCD-level metadata will form the basis for developing and validating biologic markers aimed at prognosing persistent concussive symptoms among EMA participants (see SA2-3).

• Specific Aim 2: Discovery/Validation Phases: To identify the most sensitive and specific biological measures acquired in SA1 for characterizing acute (< 3 days) and persistent (> 3 months) symptoms that result from concussive head impacts within the EMA population using a data-driven predictive analytic approach. This aim will be completed within each of the four biologic measurements to be studied.

• Specific Aim 3: To generate a clinical risk stratification algorithm for persistent concussive symptoms among the EMA population using validated multi-modal biologic markers identified in SA2.