Secreted Peptides for Diagnostic Trajectory Assessments in Brain Injury Rehabilitation

Academic Article

Abstract

  • Background: Rehabilitation following traumatic brain injury (TBI) significantly improves outcomes; yet TBI heterogeneity raises the need for molecular evidence of brain recovery processes to better track patient progress, evaluate therapeutic efficacy, and provide prognostication. Objective: Here, we assessed whether the trajectory of TBI-responsive peptides secreted into urine can produce a predictive model of functional recovery during TBI rehabilitation. Methods: The multivariate urinary peptidome of 12 individuals with TBI was examined using quantitative peptidomics. Measures were assessed upon admission and discharge from inpatient rehabilitation. A combination of Pavlidis template matching and partial least-squares discriminant analysis was used to build models on Disability Rating Scale (DRS) and Functional Independence Measure (FIM) scores, with participants bifurcated into more or less functional improvement groups. Results: The produced models exhibited high sensitivity and specificity with the area under the receiver operator curve being 0.99 for DRS- and 0.95 for FIM-based models using the top 20 discriminant peptides. Predictive ability for each model was assessed using robust leave-one-out cross-validation with Q2 statistics of 0.64 (P =.00012) and 0.62 (P =.011) for DRS- and FIM-based models, respectively, both with a high predictive accuracy of 0.875. Identified peptides that discriminated improved functional recovery reflected heightened neuroplasticity and synaptic refinement and diminished cell death and neuroinflammation, consistent with postacute TBI pathobiology. Conclusions: Produced models of urine-based peptide measures reflective of ongoing recovery pathobiology can inform on rehabilitation progress after TBI, warranting further study to assess refined stratification across a larger population and efficacy in assessing therapeutic interventions.
  • Published In

    Digital Object Identifier (doi)

    Author List

  • Patel PD; Stafflinger JE; Marwitz JH; Niemeier JP; Ottens AK
  • Start Page

  • 169
  • End Page

  • 184
  • Volume

  • 35
  • Issue

  • 2