Christopher C. Giza

Traumatic brain injury (TBI) is a leading cause of death and long-term disability in children, with many experiencing persistent symptoms even after mild TBIs. Exposure to adverse childhood experiences (ACEs) can have physiological effects that may alter how the brain responds to injury, yet the effects of ACEs on white matter injury and recovery processes remain unclear. This study examined whether a history of ACEs is associated with patterns of longitudinal change in white matter microstructure in children with mTBI. Ninety-six concussed adolescents (mean age=14.9 years, range =11.4–17.9, 51% female) from the CARE4Kids consortium completed the Pediatric ACEs and Related Life-Events Screener and underwent diffusion-weighted MRI at baseline (7-35 days after injury) and follow-up (2 months later). Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI), and intracellular volume fraction (ICVF) were estimated using tract-based spatial statistics and harmonized across sites. Differences in the magnitude and direction of change in diffusion metrics over time were examined in 15 tracts of interest. Higher ACE exposure was associated with smaller absolute change in AD, MD, ODI, and ICVF across several white matter tracts, including the corpus callosum, internal and external capsules, corona radiata, and posterior thalamic radiation. Groups did not differ in the direction of white matter change for any tract-metric combination. These findings suggest that ACE exposure may blunt white matter reactivity to injury and/or reorganization during recovery processes.

Importance: Neuroinflammation is a key component of the response to injury after concussion, but direct links between diffusion MRI metrics and specific plasma inflammatory pathways in human concussion have not been established. Objective: To examine associations between diffusion MRI metrics and pathway-level inflammatory proteomic signatures in adolescents during the subacute period after concussion. Design, Setting, and Participants: Cross-sectional analysis of data from the CARE4Kids Consortium, a six-site prospective study. Participants were English-speaking adolescents ages 11–17.99 with concussion and symptoms at 7–35 days post-injury. Data were collected between 2022-2024. Of 370 enrolled participants, 122 had both diffusion MRI and plasma proteomics available for analysis. Exposure: Advanced diffusion MRI metrics were converted to z-scores and participants were grouped by the spatial extent of outlier values (potholes and peaks) across 15 white matter regions of interest. Nine non-redundant groupings were selected for primary analysis. Main Outcomes and Measures: Pathway-level inflammatory profiles derived from gene set enrichment analysis (GSEA) of ∼5,400 plasma proteins measured by Olink proximity extension assay, targeting nine hallmark inflammatory pathways spanning initiation through resolution. Persistent symptoms were assessed 64-115 days post-injury. Results: Diffusion metrics reflecting tissue disorganization were associated with upregulation of the coagulation pathway, consistent with hemostatic-inflammatory signaling. Metrics reflecting reduced tissue complexity and neurite density were associated with upregulation of interferon-α and interferon-γ response pathways, consistent with microstructural remodeling driven by cellular immune activation. Elevated free water content was associated with downregulation of most inflammatory pathways and trend-level transforming growth factor - β upregulation, reflecting inflammatory resolution. Time since injury did not differ between groups based on free water (Kolmogorov-Smirnov p = 0.97), suggesting these differences reflect individual variability in recovery pace. Exploratory analyses showed a trend toward lower odds of persistent symptoms in the group with elevated free water content (odds ratio = 0.51, p = 0.18). Conclusions and Relevance: Multiple diffusion MRI metrics are differentially sensitive to distinct neuroinflammatory states in the subacute period after adolescent concussion. These findings suggest that diffusion imaging could serve as a non-invasive tool for inflammatory phenotyping, with potential implications for identifying patients who may benefit from targeted immunomodulatory intervention. Key Points: Question: Are specific diffusion MRI metrics sensitive to distinct inflammatory pathway signatures in adolescents during the subacute period after concussion? Findings: In this cross-sectional study of 122 adolescents with concussion, multimodal diffusion MRI metrics were associated with mechanistically distinct proteomic signatures rather than a uniform inflammatory response. Metrics reflecting tissue disorganization were associated with hemostatic-inflammatory pathway upregulation, metrics reflecting reduced tissue complexity and neurite density were associated with interferon signaling and coagulation suppression, and elevated free water content was associated with inflammatory pathway downregulation and trend-level resolution-phase signaling. Meaning: Different diffusion MRI metrics are sensitive to qualitatively different neuroinflammatory processes, suggesting that multimodal diffusion imaging may enable non-invasive profiling of the post-injury inflammatory state and inform targeted therapeutic strategies.

OBJECTIVE: We investigated longitudinal trajectories of resting-state fMRI (rsfMRI), autonomic function, and symptoms after sport-related concussion (SRC). BACKGROUND: Limbic circuitry may be particularly vulnerable to traumatic brain injury (TBI), which could explain the affective and autonomic dysfunction some patients develop. Relatively few studies have performed longitudinal rsfMRI analyses in concussion and fewer have combined imaging with autonomic and symptom data. We leveraged published limbic rsfMRI networks centered on the amygdala that include central autonomic structures in frontal and temporal lobes and their visceromotor targets. We hypothesized that frontoamygdala connectivity would differentiate athletes with SRC from matched, in-sport controls (ISC), predict autonomic function, and predict symptom recovery. DESIGN/METHODS: Using independent-samples t -tests, we compared rsfMRI connectivity strength in amygdala networks in college athletes with SRC (SRC: n=31, female=14) at three time points after concussion (T1≤4 days, T2=10-14 days, T3=60-90 days) and healthy, matched controls without a concussion in the same sport (ISC: n=36, female=17). RESULTS: SRC athletes showed significantly greater frontoamygdala connectivity compared to ISCs at the acute and subacute post-injury time points (T1 p =0.003, T2 p =0.014) that normalized to control-level connectivity by the chronic time point (T3 p =0.182). When testing whether autonomic function interacts with network connectivity trajectory, we found that opposing trajectories of frontoamygdala connectivity between SRC athletes with higher versus lower acute heart rate variability (HRV), as measured by pNN50 (percentage of intervals between successive normal sinus beats greater than 50ms). SRC athletes with higher HRV acutely post-injury had significantly greater acute frontoamygdala connectivity compared to ISCs at T1; connectivity in these high-HRV SRC athletes normalized to control level over time (T1 p =0.001, T2 p =0.055, T3 p =0.576). SRC athletes with lower HRV acutely post-injury had control-level frontoamygdala connectivity at T1; connectivity in these low-HRV SRC athletes significantly exceeded control-level connectivity at T3 (T1 p =0.429, T2 p =0.050, T3 p =0.002). Furthermore, those SRC athletes with the greatest frontoamygdala connectivity at T3, had the most persistent symptoms on the graded symptom checklist at T3 (r=0.635, p =0.001). Differences in diffusion-tensor-imaging-based measures of structural connectivity in the uncinate fasciculus, the fiber bundle most critical to our frontoamygdala network, could not account for these relationships. CONCLUSIONS: These results suggest that increased connectivity in amygdala circuitry acutely after a concussion and its normalization over time may be protective or compensatory; acute measures of amygdala network connectivity and measures of HRV may be valuable biomarkers for predicting symptom persistence.

Withdrawal Statement: The authors have withdrawn this manuscript because new data became available and reanalysis was inconsistent. A fresh preprint will be posted with the reanalysis. Therefore, the authors do not wish this work to be cited as a reference for the project. If you have any questions, please contact the corresponding author.

Objective To study longitudinal associations between blood-based neural biomarkers (including total tau, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and ubiquitin C-terminal hydrolase-L1 (UCH-L1)) and white-matter neuroimaging biomarkers in collegiate athletes with sport-related concussion (SRC) from 24-hours post-injury to 1 week after return-to-play. Methods We analyze clinical and imaging data of concussed collegiate athletes in the Concussion Assessment, Research and Education (CARE) Consortium. The CARE participants completed same-day clinical assessments, blood draws, and diffusion tensor imaging (DTI) at 3 time points: 24-48 hours post-injury, point of becoming asymptomatic, and 7 days following return-to-play. DTI probabilistic tractography was performed for each subject at each time point to render 27 subject-specific major white-matter tracts. The microstructural organization of these tracts was characterized by four DTI metrics. Mixed-effects models with random intercepts were applied to test whether white-matter microstructural abnormalities are associated with the blood-based biomarkers at the same time point. An interaction model was used to test if the association varies across time points. A lagged model was used to test if early blood-based biomarkers predict later microstructural changes. Results Data from 77 collegiate athletes were included in the following analyses. Among the 4 blood-based biomarkers, total tau had significant associations with the DTI metrics across the 3 time points. In particular, tau was positively associated with radial diffusivity (RD) in the right corticospinal tract (β=0.25, SE=0.07, p_FDR-adjusted=0.016) and superior thalamic radiation (β=0.21, SE=0.07, p_FDR-adjusted=0.042). NfL and GFAP had time-dependent associations with the DTI metrics. NfL showed significant associations only at the asymptomatic time point (|β|s>0.12, SEsps_FDR-adjusted0.14, SEsps_FDR-adjusted<0.05). The p-values for the associations of early tau and later RD were not significant after multiple comparison adjustment, but were less than 0.1 in seven white-matter tracts. Conclusions This prospective study using data from the CARE Consortium demonstrated that in the early phase of SRC, white-matter microstructural integrity detected by DTI neuroimaging was associated with elevated levels of blood-based biomarkers of traumatic brain injury. Total tau in the blood showed the strongest association with white-matter microstructural changes.

Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences. Significance Statement Data sharing can increase the quality and rigor of scientific claims, but with large scale data sharing comes an increased need to combine non-equivalent measurements across studies. Auditory verbal learning tasks (AVLTs) are one of the most common research and clinical tools to evaluate memory constructs, but numerous distinct AVLTs are in common use, which creates challenges for data aggregation. We report methods to convert raw scores across common verbal learning instruments, constructed using harmonizing data from 53 studies from around the world. This approach can be replicated in other domains to address long standing data compatibility issues for researchers and clinicians.

While traditionally ignored as a region purely responsible for motor function, the cerebellum is increasingly being appreciated for its contributions to higher order functions through various cerebro-cerebellar networks. Traumatic brain injury (TBI) research generally focuses on the cerebrum, in part because acute pathology is not found in the cerebellum as often. Acute pathology is an important predictor of outcome, but neural disruption also evolves over time in ways that have implications for daily-life functioning. Here we examine these changes in a multi-modal, multi-cohort study. Combining 12 datasets from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Pediatric msTBI (moderate-severe TBI) working group, we measured volume of the total cerebellum and 17 subregions using a state-of-the-art, deep learning-based approach for automated parcellation in 598 children and adolescents with or without TBI (msTBI; n = 314 | non-TBI; n = 284; age M = 14.0 ± 3.1 years). Further, we investigated brain-behavior relations between cerebellar volumes and a measure of executive functioning (i.e., Behavioral Rating Inventory of Executive Function [BRIEF]). In a subsample with longitudinal data, we then assessed whether late changes in cerebellar volume were associated with early white matter microstructural organization using diffusion tensor imaging (DTI). Significantly smaller total cerebellar volume was observed in the msTBI group (Cohen’s d = −0.37). In addition, lower regional cerebellar volume was found in posterior lobe regions including crus II, lobule VIIB, lobule VIIIB, vermis VII, and IX (Cohen’s d range = −0.22 to −0.43). Smaller cerebellum volumes were associated with more parent-reported executive function problems. These alterations were primarily driven by participants in the chronic phase of injury (> 6 months). In a subset of participants with longitudinal data (n = 80), we found evidence of altered growth in total cerebellum volume, with younger msTBI participants showing secondary degeneration in the form of volume reductions, and older participants showing disrupted development reflected in slower growth rates. Changes in total cerebellum volume over time were also associated with white matter microstructural organization in the first weeks and months post-injury, such that poorer white matter organization in the first months post-injury was associated with decreases in volume longitudinally. Pediatric msTBI was characterized by smaller cerebellar volumes, primarily in the posterior lobe and vermis. The course of these alterations, along with group differences in longitudinal volume changes as well as injury-specific associations between DTI measures and volume changes, is suggestive of secondary cerebellar atrophy, possibly related to supra-tentorial lesions, and/or disruption in cerebellar structural and functional circuits. Moreover, evidence for robust brain-behavior relationships underscore the potential cognitive and behavioral consequences of cerebellar disruption during a critical period of brain development.

Objective Our study addressed aims (1) to test the hypothesis that moderate-severe traumatic brain injury (TBI) in pediatric patients is associated with widespread white matter (WM) disruption, (2) to test the hypothesis that age and sex affect WM organization after injury, and (3) to examine associations between WM organization and neurobehavioral outcomes. Methods Data from 10 previously enrolled, existing cohorts recruited from local hospitals and clinics were shared with the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Pediatric Moderate/Severe TBI (msTBI) working group. We conducted a coordinated analysis of diffusion MRI (dMRI) data using the ENIGMA dMRI processing pipeline. Results Five hundred seven children and adolescents (244 with complicated msTBI and 263 controls) were included. Patients were clustered into 3 postinjury intervals: acute/subacute, <2 months; postacute, 2 to 6 months; and chronic, ≥6 months. Outcomes were dMRI metrics and postinjury behavioral problems as indexed by the Child Behavior Checklist. Our analyses revealed altered WM diffusion metrics across multiple tracts and all postinjury intervals (effect sizes range d = −0.5 to −1.3). Injury severity is a significant contributor to the extent of WM alterations but explained less variance in dMRI measures with increasing time after injury. We observed a sex-by-group interaction: female patients with TBI had significantly lower fractional anisotropy in the uncinate fasciculus than controls (β = 0.043), which coincided with more parent-reported behavioral problems (β = −0.0027). Conclusions WM disruption after msTBI is widespread, persistent, and influenced by demographic and clinical variables. Future work will test techniques for harmonizing neurocognitive data, enabling more advanced analyses to identify symptom clusters and clinically meaningful patient subtypes.