# Predictive Biomarkers & Models Assessing Systemic Response to Injury after Moderate-to-Severe TBI

> **NIH NIH R21** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $444,358

## Abstract

ABSTRACT
Despite improvements in care for individuals with traumatic brain injury (TBI), clinicians have no
neuroprotective treatment options for TBI. Moreover, investigators have limited ability a priori to predict
mortality after TBI. Estradiol (E2) and progesterone (PRO) are well known for their neuroprotective qualities
when studied in pre-clinical TBI models. However, our independent clinical data suggest relative increases in
endogenous sex hormones occur after TBI that are derived from extra-gonadal sources and are the result of
amplified aromatization pathways. These pathways use TNFα to produce E2 and are linked with mortality and
poor outcome. The literature indicates that E2 accumulation may reflect a complex systemic response to injury
that is initiated by the sympathetic nervous system (SNS) and perpetuated by SNS-induced inflammation,
leading to amplified E2 production that is associated with systemic compromise, non-neurological organ
dysfunction (NNOD) and increased mortality and poor outcome risk. Our body of work shows E2 and its extra-
gonadal genomic transcription factor TNFα are important mortality predictors post-TBI and are associated with
systemic complications that contribute to poor outcome. The dichotomy between animal studies and phase III
randomized clinical trials (RCTs) for PRO specifically illustrate important questions requiring further study to
reconcile if/how PRO might be a viable neuroprotective treatment option for subpopulations with TBI and to
understand if/how E2 & TNFα levels can predict heterogeneity of treatment effects (HTE) with PRO therapy.
Our central hypothesis is that serum E2 & TNF-α, reflect the systemic response to TBI, are novel indicators
of baseline risk for mortality/poor outcome, and are sensitive indicators of variable PRO effects. E2 & TNFα
may be effective in characterizing those with very high/low risk (regardless of treatment) as well as those who
might benefit or be harmed by PRO. Using data and samples from the ProTECT III study and the BioProTECT
trial, we have a unique opportunity to delineate biological heterogeneity and other contributors to the null
findings treatment result. These cohorts provide a rigorously developed clinical research platform from which to
test the hypothesis that systemic E2, & TNF-α, reflect the systemic response to TBI and can serve as an
indicator of HTE to PRO therapy. At study conclusion, we will understand how to 1) effectively calculate
heterogeneity in baseline mortality and poor outcome risk after moderate/severe TBI, 2) characterize how
heterogeneity in PRO treatment moderates baseline risk and contributes to distinct, yet variable PRO response
groups, 3) identify if/how post-randomization biomarkers are affected by PRO among treatment response
groups 4) generate a parsimonious baseline risk calculator to test in other TBI populations in support of
effective pre-randomization patient selection in future RCTs. Together this work incorporates basel...

## Key facts

- **NIH application ID:** 9896194
- **Project number:** 1R21NS111063-01A1
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** AMY K WAGNER
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $444,358
- **Award type:** 1
- **Project period:** 2020-02-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9896194

## Citation

> US National Institutes of Health, RePORTER application 9896194, Predictive Biomarkers & Models Assessing Systemic Response to Injury after Moderate-to-Severe TBI (1R21NS111063-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9896194. Licensed CC0.

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