title: Inflammation Following Traumatic Brain Injury in Humans: Insights from Data-Driven and Mechanistic Models into Survival and Death.
abstract: Inflammation induced by traumatic brain injury (TBI) is a complex mediator of morbidity and mortality. We have previously demonstrated the utility of both data-driven and mechanistic models in settings of traumatic injury. We hypothesized that differential dynamic inflammation programs characterize TBI survivors vs. non-survivors, and sought to leverage computational modeling to derive novel insights into this life/death bifurcation. Thirteen inflammatory cytokines and chemokines were determined using Luminex™ in serial cerebrospinal fluid (CSF) samples from 31 TBI patients over 5 days. In this cohort, 5 were non-survivors (Glasgow Outcome Scale [GOS] score = 1) and 26 were survivors (GOS > 1). A Pearson correlation analysis of initial injury (Glasgow Coma Scale [GCS]) vs. GOS suggested that survivors and non-survivors had distinct clinical response trajectories to injury. Statistically significant differences in interleukin (IL)-4, IL-5, IL-6, IL-8, IL-13, and tumor necrosis factor-α (TNF-α) were observed between TBI survivors vs. non-survivors over 5 days. Principal Component Analysis and Dynamic Bayesian Network inference suggested differential roles of chemokines, TNF-α, IL-6, and IL-10, based upon which an ordinary differential equation model of TBI was generated. This model was calibrated separately to the time course data of TBI survivors vs. non-survivors as a function of initial GCS. Analysis of parameter values in ensembles of simulations from these models suggested differences in microglial and damage responses in TBI survivors vs. non-survivors. These studies suggest the utility of combined data-driven and mechanistic models in the context of human TBI.
authors.affiliation: Department of Surgery, University of Pittsburgh Pittsburgh, PA, USA.
authors.forename: Andrew
authors.initials: A
authors.lastname: Abboud
authors.affiliation: Department of Sports Medicine and Nutrition, University of PittsburghPittsburgh, PA, USA; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of PittsburghPittsburgh, PA, USA.
authors.forename: Qi
authors.initials: Q
authors.lastname: Mi
authors.affiliation: Department of Neurological Surgery, University of Pittsburgh Pittsburgh, PA, USA.
authors.forename: Ava
authors.initials: A
authors.lastname: Puccio
authors.affiliation: Department of Neurological Surgery, University of Pittsburgh Pittsburgh, PA, USA.
authors.forename: David
authors.initials: D
authors.lastname: Okonkwo
authors.affiliation: Department of Mathematics, University of Pittsburgh Bradford, PA, USA.
authors.forename: Marius
authors.initials: M
authors.lastname: Buliga
authors.affiliation: Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of PittsburghPittsburgh, PA, USA; Department of Mathematics and Department of Statistics, University of PittsburghPittsburgh, PA, USA.
authors.forename: Gregory
authors.initials: G
authors.lastname: Constantine
authors.affiliation: Department of Surgery, University of PittsburghPittsburgh, PA, USA; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of PittsburghPittsburgh, PA, USA.
authors.forename: Yoram
authors.initials: Y
authors.lastname: Vodovotz
keywords: TBI outcome; data-driven modeling; inflammation; inflammatory mediators in CNS; mathematical modeling; mortality