Epigenetic Effects on Pediatric Traumatic Brain Injury Recovery (EETR): An Observational, Prospective, Longitudinal Concurrent Cohort Study Protocol
Bibliographic record
Abstract
Introduction: Unexplained heterogeneity in outcomes following pediatric traumatic brain injury (TBI) is one of the most critical barriers to the development of effective prognostic tools and therapeutics. The addition of personal biological factors to our prediction models may account for a significant portion of unexplained variance and advance the field towards precision rehabilitation medicine. The overarching goal of the Epigenetic Effects on Pediatric Traumatic Brain Injury Recovery (EETR) study is to investigate an epigenetic biomarker involved in both childhood adversity and post-injury neuroplasticity to better understand heterogeneity in neurobehavioral outcomes following pediatric TBI. Our primary hypothesis is that childhood adversity will be associated with worse neurobehavioral recovery in part through an epigenetically mediated reduction in brain-derived neurotrophic factor (BDNF) expression in response to TBI. Methods and analysis: EETR is an observational, prospective, longitudinal concurrent cohort study of children aged 3-18 years with either TBI (n=200) or orthopedic injury (n=100), recruited from the UPMC Children’s Hospital of Pittsburgh. Participants complete study visits acutely and at 6- and 12-months post-injury. Blood and saliva biosamples are collected at all time points—and CSF when available acutely—for epigenetic and proteomic analysis of BDNF. Additional measures assess injury characteristics, pre- and post-injury child neurobehavioral functioning, childhood adversity, and potential covariates/confounders. Recruitment began in July 2017 and will occur for approximately 6 years, with data collection complete by mid-2023. Analyses will characterize BDNF DNA methylation and protein levels over the recovery period and investigate this novel biomarker as a potential biological mechanism underlying the known association between childhood adversity and worse neurobehavioral outcomes following pediatric TBI. Ethics and dissemination: The study received ethics approval from the University of Pittsburgh Institutional Review Board. Participants and their parents provide informed consent/assent. Research findings will be disseminated via local and international conference presentations and manuscripts submitted to peer-reviewed journals. Trial Registration: The study is registered with clinicaltrials.org (ClinicalTrials.gov Identifier: NCT04186429).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".