Mild Traumatic Brain Injury (mTBI), or concussion, is a major public health concern. There is controversy in the literature regarding the true incidence of postconcussion syndrome (PCS), with the constellation of physical, cognitive, emotional, and sleep symptoms after mTBI. In the current study, we report on the incidence and evolution of PCS symptoms and patient outcomes after mTBI at 3, 6, and 12 months in a large, prospective cohort of mTBI patients. Participants were identified as part of the prospective, multi-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study. The study population was mTBI patients (Glasgow Coma Scale score of 13-15) presenting to the emergency department, including patients with a negative head computed tomography discharged to home without admission to hospital; 375 mTBI subjects were included in the analysis. At both 6 and 12 months after mTBI, 82% (n=250 of 305 and n=163 of 199, respectively) of patients reported at least one PCS symptom. Further, 44.5 and 40.3% of patients had significantly reduced Satisfaction With Life scores at 6 and 12 months, respectively. At 3 months after injury, 33% of the mTBI subjects were functionally impaired (Glasgow Outcome Scale-Extended score ≤6); 22.4% of the mTBI subjects available for follow-up were still below full functional status at 1 year after injury. The term "mild" continues to be a misnomer for this patient population and underscores the critical need for evolving classification strategies for TBI for targeted therapy.

Biomarkers are important for accurate diagnosis of complex disorders such as traumatic brain injury (TBI). For a complex and multifaceted condition such as TBI, it is likely that a single biomarker will not reflect the full spectrum of the response of brain tissue to injury. Ubiquitin C-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) are among of the most widely studied biomarkers for TBI. Because UCH-L1 and GFAP measure distinct molecular events, we hypothesized that analysis of both biomarkers would be superior to analysis of each alone for the diagnosis and prognosis of TBI. Serum levels of UCH-L1 and GFAP were measured in a cohort of 206 patients with TBI enrolled in a multicenter observational study (Transforming Research and Clinical Knowledge in Traumatic Brain Injury [TRACK-TBI]). Levels of the two biomarkers were weakly correlated to each other (r = 0.364). Each biomarker in isolation had good sensitivity and sensitivity for discriminating between TBI patients and healthy controls (area under the curve [AUC] 0.87 and 0.91 for UCH-L1 and GFAP, respectively). When biomarkers were combined, superior sensitivity and specificity for diagnosing TBI was obtained (AUC 0.94). Both biomarkers discriminated between TBI patients with intracranial lesions on CT scan and those without such lesions, but GFAP measures were significantly more sensitive and specific (AUC 0.88 vs. 0.71 for UCH-L1). For association with outcome 3 months after injury, neither biomarker had adequate sensitivity and specificity (AUC 0.65-0.74, for GFAP, and 0.59-0.80 for UCH-L1, depending upon Glasgow Outcome Scale Extended [GOS-E] threshold used). Our results support a role for multiple biomarker measurements in TBI research. (ClinicalTrials.gov Identifier NCT01565551)

Traumatic brain injury (TBI) is among the leading causes of death and disability worldwide, with enormous negative social and economic impacts. The heterogeneity of TBI combined with the lack of precise outcome measures have been central to the discouraging results from clinical trials. Current approaches to the characterization of disease severity and outcome have not changed in more than three decades. This prospective multicenter observational pilot study aimed to validate the feasibility of implementing the TBI Common Data Elements (TBI-CDEs). A total of 650 subjects who underwent computed tomography (CT) scans in the emergency department within 24 h of injury were enrolled at three level I trauma centers and one rehabilitation center. The TBI-CDE components collected included: 1) demographic, social and clinical data; 2) biospecimens from blood drawn for genetic and proteomic biomarker analyses; 3) neuroimaging studies at 2 weeks using 3T magnetic resonance imaging (MRI); and 4) outcome assessments at 3 and 6 months. We describe how the infrastructure was established for building data repositories for clinical data, plasma biomarkers, genetics, neuroimaging, and multidimensional outcome measures to create a high quality and accessible information commons for TBI research. Risk factors for poor follow-up, TBI-CDE limitations, and implementation strategies are described. Having demonstrated the feasibility of implementing the TBI-CDEs through successful recruitment and multidimensional data collection, we aim to expand to additional study sites. Furthermore, interested researchers will be provided early access to the Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) data set for collaborative opportunities to more precisely characterize TBI and improve the design of future clinical treatment trials. (ClinicalTrials.gov Identifier NCT01565551.)

We evaluated 3T diffusion tensor imaging (DTI) for white matter injury in 76 adult mild traumatic brain injury (mTBI) patients at the semiacute stage (11.2±3.3 days), employing both whole-brain voxel-wise and region-of-interest (ROI) approaches. The subgroup of 32 patients with any traumatic intracranial lesion on either day-of-injury computed tomography (CT) or semiacute magnetic resonance imaging (MRI) demonstrated reduced fractional anisotropy (FA) in numerous white matter tracts, compared to 50 control subjects. In contrast, 44 CT/MRI-negative mTBI patients demonstrated no significant difference in any DTI parameter, compared to controls. To determine the clinical relevance of DTI, we evaluated correlations between 3- and 6-month outcome and imaging, demographic/socioeconomic, and clinical predictors. Statistically significant univariable predictors of 3-month Glasgow Outcome Scale-Extended (GOS-E) included MRI evidence for contusion (odds ratio [OR] 4.9 per unit decrease in GOS-E; p=0.01), ≥1 ROI with severely reduced FA (OR, 3.9; p=0.005), neuropsychiatric history (OR, 3.3; p=0.02), age (OR, 1.07/year; p=0.002), and years of education (OR, 0.79/year; p=0.01). Significant predictors of 6-month GOS-E included ≥1 ROI with severely reduced FA (OR, 2.7; p=0.048), neuropsychiatric history (OR, 3.7; p=0.01), and years of education (OR, 0.82/year; p=0.03). For the subset of 37 patients lacking neuropsychiatric and substance abuse history, MRI surpassed all other predictors for both 3- and 6-month outcome prediction. This is the first study to compare DTI in individual mTBI patients to conventional imaging, clinical, and demographic/socioeconomic characteristics for outcome prediction. DTI demonstrated utility in an inclusive group of patients with heterogeneous backgrounds, as well as in a subset of patients without neuropsychiatric or substance abuse history.

IMPORTANCEAnnually in the United States, at least 3.5 million people seek medical attention for traumatic brain injury (TBI). The development of therapies for TBI is limited by the absence of diagnostic and prognostic biomarkers. Microtubule-associated protein tau is an axonal phosphoprotein. To date, the presence of the hypophosphorylated tau protein (P-tau) in plasma from patients with acute TBI and chronic TBI has not been investigated. OBJECTIVETo examine the associations between plasma P-tau and total-tau (T-tau) levels and injury presence, severity, type of pathoanatomic lesion (neuroimaging), and patient outcomes in acute and chronic TBI. DESIGN, SETTING, AND PARTICIPANTSIn the TRACK-TBI Pilot study, plasma was collected at a single time point from 196 patients with acute TBI admitted to 3 level I trauma centers (<24 hours after injury) and 21 patients with TBI admitted to inpatient rehabilitation units (mean [SD], 176.4 [44.5] days after injury). Control samples were purchased from a commercial vendor. The TRACK-TBI Pilot study was conducted from April 1, 2010, to June 30, 2012. Data analysis for the current investigation was performed from August 1, 2015, to March 13, 2017.MAIN OUTCOMES AND MEASURES Plasma samples were assayed for P-tau (using an antibody that specifically recognizes phosphothreonine-231) and T-tau using ultra-high sensitivity laser-based immunoassay multi-arrayed fiberoptics conjugated with rolling circle amplification. RESULTSIn the 217 patients with TBI, 161 (74.2%) were men; mean (SD) age was 42.5 (18.1) years. The P-tau and T-tau levels and P-tau-T-tau ratio in patients with acute TBI were higher than those in healthy controls. Receiver operating characteristic analysis for the 3 tau indices demonstrated accuracy with area under the curve (AUC) of 1.000, 0.916, and 1.000, respectively, for discriminating mild TBI (Glasgow Coma Scale [GCS] score, 13-15, n = 162) from healthy controls. The P-tau level and P-tau-T-tau ratio were higher in individuals with more severe TBI (GCS, Յ12 vs 13-15). The P-tau level and P-tau-T-tau ratio outperformed the T-tau level in distinguishing cranial computed tomography-positive from -negative cases (AUC = 0.921, 0.923, and 0.646, respectively). Acute P-tau levels and P-tau-T-tau ratio weakly distinguished patients with TBI who had good outcomes (Glasgow Outcome Scale-Extended GOS-E, 7-8) (AUC = 0.663 and 0.658, respectively) and identified those with poor outcomes (GOS-E, Յ4 vs >4) (AUC = 0.771 and 0.777, respectively). Plasma samples from patients with chronic TBI also showed elevated P-tau levels and a P-tau-T-tau ratio significantly higher than that of healthy controls, with both P-tau indices strongly discriminating patients with chronic TBI from healthy controls (AUC = 1.000 and 0.963, respectively).CONCLUSIONS AND RELEVANCE Plasma P-tau levels and P-tau-T-tau ratio outperformed T-tau level as diagnostic and prognostic biomarkers for acute TBI. Compared with T-tau levels alone, P-tau levels and P-tau-T-tau ratios show more robust and sustained el...

The purpose of this study is to investigate whether specific patterns of correlation exist in diffusion tensor imaging (DTI) parameters across white matter tracts in the normal human brain, and whether the relative strengths of these putative microstructural correlations might reflect phylogenetic and functional similarities between tracts. We performed quantitative DTI fiber tracking on 44 healthy adult volunteers to obtain tract-based measures of mean diffusivity (MD), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) from four homologous pairs of neocortical association pathways (arcuate fasciculi, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate fasciculi bilaterally), a homologous pair of limbic association pathways (left and right dorsal cingulum bundles), and a homologous pair of cortical-subcortical projection pathways (left and right corticospinal tracts). From the resulting inter-tract correlation matrices, we show that there are statistically significant correlations of DTI parameters between tracts, and that there are statistically significant variations among these intertract correlations. Furthermore, we observe that many, but by no means all, of the strongest correlations were between homologous tracts in the left and right hemispheres. Even among homologous pairs of tracts, there were wide variations in the degree of coupling. Finally, we generate a data-driven hierarchical clustering of the fiber pathways based on pairwise FA correlations to demonstrate that the neocortical association pathways tended to group separately from the limbic pathways at trend-level statistical significance, and that the projection pathways of the left and right corticospinal tracts comprise the most distant outgroup with high confidence (p<0.01). Hence, specific patterns of microstructural correlation exist between tracts and may reflect phylogenetic and functional similarities between tracts. The study of these microstructural relationships between white matter pathways might aid research on the genetic basis and on the behavioral effects of axonal connectivity, as well as provide a revealing new perspective with which to investigate neurological and psychiatric disorders.

IMPORTANCE The association between poverty and unfavorable cognitive outcomes is robust, but most research has focused on individual household socioeconomic status (SES). There is increasing evidence that neighborhood context explains unique variance not accounted for by household SES. OBJECTIVE To evaluate whether neighborhood poverty (NP) is associated with cognitive function and prefrontal and hippocampal brain structure in ways that are dissociable from household SES. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study used a baseline sample of the ongoing longitudinal Adolescent Brain Cognitive Development (ABCD) Study. The ABCD Study will follow participants for assessments each year for 10 years. Data were collected at 21 US sites, mostly within urban and suburban areas, between September 2019 and October 2018. School-based recruitment was used to create a participant sample reflecting the US population. Data analysis was conducted from March to June 2019. MAIN OUTCOMES AND MEASURES NP and household SES were included as factors potentially associated with National Institutes of Health Toolbox Cognitive Battery subtests and hippocampal and prefrontal (dorsolateral prefrontal cortex [DLPFC], dorsomedial PFC [DMPFC], superior frontal gyrus [SFG]) volumes. Independent variables were first considered individually and then together in mixed-effects models with age, sex, and intracranial volume as covariates. Structural equation modeling (SEM) was used to assess shared variance in NP to brain structure and cognitive task associations. The tested hypotheses were formulated after data collection. RESULTS A total of 11 875 children aged 9 and 10 years (5678 [47.8%] girls) were analyzed. Greater NP was associated with lower scores across all cognitive domains (eg, total composite: β = −0.18;

Reliable diagnosis of traumatic brain injury (TBI) is a major public health need. Glial fibrillary acidic protein (GFAP) is expressed in the central nervous system, and breakdown products (GFAP-BDP) are released following parenchymal brain injury. Here, we evaluate the diagnostic accuracy of elevated levels of plasma GFAP-BDP in TBI. Participants were identified as part of the prospective Transforming Research And Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Study. Acute plasma samples (< 24 h post-injury) were collected from patients presenting with brain injury who had CT imaging. The ability of GFAP-BDP level to discriminate patients with demonstrable traumatic lesions on CT, and with failure to return to pre-injury baseline at 6 months, was evaluated by the area under the receiver operating characteristic curve (AUC). Of the 215 patients included for analysis, 83% had mild, 4% had moderate, and 13% had severe TBI; 54% had acute traumatic lesions on CT. The ability of GFAP-BDP level to discriminate patients with traumatic lesions on CT as evaluated by AUC was 0.88 (95% confidence interval [CI], 0.84-0.93). The optimal cutoff of 0.68 ng/mL for plasma GFAP-BDP level was associated with a 21.61 odds ratio for traumatic findings on head CT. Discriminatory ability of unfavorable 6 month outcome was lower, AUC 0.65 (95% CI, 0.55-0.74), with a 2.07 odds ratio. GFAP-BDP levels reliably distinguish the presence and severity of CT scan findings in TBI patients. Although these findings confirm and extend prior studies, a larger prospective trial is still needed to validate the use of GFAP-BDP as a routine diagnostic biomarker for patient care and clinical research. The term ''mild'' continues to be a misnomer for this patient population, and underscores the need for evolving classification strategies for TBI targeted therapy. (ClinicalTrials.gov number NCT01565551; NIH Grant 1RC2 NS069409)