Dataset Information

Improving the clinical management of traumatic brain injury through the pharmacokinetic modeling of peripheral blood biomarkers.

ABSTRACT:

Background

Blood biomarkers of neurovascular damage are used clinically to diagnose the presence severity or absence of neurological diseases, but data interpretation is confounded by a limited understanding of their dependence on variables other than the disease condition itself. These include half-life in blood, molecular weight, and marker-specific biophysical properties, as well as the effects of glomerular filtration, age, gender, and ethnicity. To study these factors, and to provide a method for markers' analyses, we developed a kinetic model that allows the integrated interpretation of these properties.

Methods

The pharmacokinetic behaviors of S100B (monomer and homodimer), Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase L1 were modeled using relevant chemical and physical properties; modeling results were validated by comparison with data obtained from healthy subjects or individuals affected by neurological diseases. Brain imaging data were used to model passage of biomarkers across the blood-brain barrier.

Results

Our results show the following: (1) changes in biomarker serum levels due to age or disease progression are accounted for by differences in kidney filtration; (2) a significant change in the brain-to-blood volumetric ratio, which is characteristic of infant and adult development, contributes to variation in blood concentration of biomarkers; (3) the effects of extracranial contribution at steady-state are predicted in our model to be less important than suspected, while the contribution of blood-brain barrier disruption is confirmed as a significant factor in controlling markers' appearance in blood, where the biomarkers are typically detected; (4) the contribution of skin to the marker S100B blood levels depends on a direct correlation with pigmentation and not ethnicity; the contribution of extracranial sources for other markers requires further investigation.

Conclusions

We developed a multi-compartment, pharmacokinetic model that integrates the biophysical properties of a given brain molecule and predicts its time-dependent concentration in blood, for populations of varying physical and anatomical characteristics. This model emphasizes the importance of the blood-brain barrier as a gatekeeper for markers' blood appearance and, ultimately, for rational clinical use of peripherally-detected brain protein.

SUBMITTER: Dadas A

PROVIDER: S-EPMC5402680 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Publications

Improving the clinical management of traumatic brain injury through the pharmacokinetic modeling of peripheral blood biomarkers.

Dadas Aaron A Washington Jolewis J Marchi Nicola N Janigro Damir D

Fluids and barriers of the CNS 20161130 1

<h4>Background</h4>Blood biomarkers of neurovascular damage are used clinically to diagnose the presence severity or absence of neurological diseases, but data interpretation is confounded by a limited understanding of their dependence on variables other than the disease condition itself. These include half-life in blood, molecular weight, and marker-specific biophysical properties, as well as the effects of glomerular filtration, age, gender, and ethnicity. To study these factors, and to provid ...[more]

PMID: 27903281

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Project description:There is substantial interest in the potential for traumatic brain injury to result in progressive neurological deterioration. While blood biomarkers such as glial fibrillary acid protein (GFAP) and neurofilament light have been widely explored in characterizing acute traumatic brain injury (TBI), their use in the chronic phase is limited. Given increasing evidence that these proteins may be markers of ongoing neurodegeneration in a range of diseases, we examined their relationship to imaging changes and functional outcome in the months to years following TBI. Two-hundred and three patients were recruited in two separate cohorts; 6 months post-injury (n = 165); and >5 years post-injury (n = 38; 12 of whom also provided data ∼8 months post-TBI). Subjects underwent blood biomarker sampling (n = 199) and MRI (n = 172; including diffusion tensor imaging). Data from patient cohorts were compared to 59 healthy volunteers and 21 non-brain injury trauma controls. Mean diffusivity and fractional anisotropy were calculated in cortical grey matter, deep grey matter and whole brain white matter. Accelerated brain ageing was calculated at a whole brain level as the predicted age difference defined using T1-weighted images, and at a voxel-based level as the annualized Jacobian determinants in white matter and grey matter, referenced to a population of 652 healthy control subjects. Serum neurofilament light concentrations were elevated in the early chronic phase. While GFAP values were within the normal range at ∼8 months, many patients showed a secondary and temporally distinct elevations up to >5 years after injury. Biomarker elevation at 6 months was significantly related to metrics of microstructural injury on diffusion tensor imaging. Biomarker levels at ∼8 months predicted white matter volume loss at >5 years, and annualized brain volume loss between ∼8 months and 5 years. Patients who worsened functionally between ∼8 months and >5 years showed higher than predicted brain age and elevated neurofilament light levels. GFAP and neurofilament light levels can remain elevated months to years after TBI, and show distinct temporal profiles. These elevations correlate closely with microstructural injury in both grey and white matter on contemporaneous quantitative diffusion tensor imaging. Neurofilament light elevations at ∼8 months may predict ongoing white matter and brain volume loss over >5 years of follow-up. If confirmed, these findings suggest that blood biomarker levels at late time points could be used to identify TBI survivors who are at high risk of progressive neurological damage.

Project description:Traumatic brain injury (TBI) has a complex pathology in which the initial injury releases damage associated proteins that exacerbate the neuroinflammatory response during the chronic secondary injury period. One of the major pathological players in the inflammatory response after TBI is the inflammasome. Increased levels of inflammasome proteins during the acute phase after TBI are associated with worse functional outcomes. Previous studies reveal that the level of inflammasome proteins in biological fluids may be used as promising new biomarkers for the determination of TBI functional outcomes. In this study, we provide further evidence that inflammatory cytokines and inflammasome proteins in serum may be used to determine injury severity and predict pathological outcomes. In this study, we analyzed blood serum from TBI patients and respective controls utilizing Simple Plex inflammasome and V-PLEX inflammatory cytokine assays. We performed statistical analyses to determine which proteins were significantly elevated in TBI individuals. The receiver operating characteristics (ROC) were determined to obtain the area under the curve (AUC) to establish the potential fit as a biomarker. Potential biomarkers were then compared to documented patient Glasgow coma scale scores via a correlation matrix and a multivariate linear regression to determine how respective biomarkers are related to the injury severity and pathological outcome. Inflammasome proteins and inflammatory cytokines were elevated after TBI, and the apoptosis-associated speck like protein containing a caspase recruitment domain (ASC), interleukin (IL)-18, tumor necrosis factor (TNF)-α, IL-4 and IL-6 were the most reliable biomarkers. Additionally, levels of these proteins were correlated with known clinical indicators of pathological outcome, such as the Glasgow coma scale (GCS). Our results show that inflammatory cytokines and inflammasome proteins are promising biomarkers for determining pathological outcomes after TBI. Additionally, levels of biomarkers could potentially be utilized to determine a patient's injury severity and subsequent pathological outcome. These findings show that inflammation-associated proteins in the blood are reliable biomarkers of injury severity that can also be used to assess the functional outcomes of TBI patients.

Project description:Background and Objectives: The annual global incidence of traumatic brain injury (TBI) is over 10 million. An estimated 29% of TBI patients with negative computed tomography (CT-) have positive magnetic resonance imaging (MRI+) findings. Judicious use of serum biomarkers with MRI may aid in diagnosis of CT-occult TBI. The current manuscript aimed to evaluate the diagnostic, therapeutic and risk-stratification utility of known biomarkers and intracranial MRI pathology. Materials and Methods: The PubMed database was queried with keywords (plasma OR serum) AND (biomarker OR marker OR protein) AND (brain injury/trauma OR head injury/trauma OR concussion) AND (magnetic resonance imaging/MRI) (title/abstract) in English. Seventeen articles on TBI biomarkers and MRI were included: S100 calcium-binding protein B (S100B; N = 6), glial fibrillary acidic protein (GFAP; N = 3), GFAP/ubiquitin carboxyl-terminal hydrolase-L1 (UCH-L1; N = 2), Tau (N = 2), neurofilament-light (NF-L; N = 2), alpha-synuclein (N = 1), and alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor peptide (AMPAR; N = 1). Results: Acute GFAP distinguished CT-/MRI+ from CT-/MRI- (AUC = 0.777, 0.852 at 9-16 h). GFAP discriminated CT-/diffuse axonal injury (DAI+) from controls (AUC = 0.903). Tau correlated directly with number of head strikes and inversely with white matter fractional anisotropy (FA), and a cutoff > 1.5 pg/mL discriminated between DAI+ and DAI- (sensitivity = 74%/specificity = 69%). NF-L had 100% discrimination of DAI in severe TBI and correlated with FA. Low alpha-synuclein was associated with poorer functional connectivity. AMPAR cutoff > 0.4 ng/mL had a sensitivity of 91% and a specificity of 92% for concussion and was associated with minor MRI findings. Low/undetectable S100B had a high negative predictive value for CT/MRI pathology. UCH-L1 showed no notable correlations with MRI. Conclusions: An acute circulating biomarker capable of discriminating intracranial MRI abnormalities is critical to establishing diagnosis for CT-occult TBI and can triage patients who may benefit from outpatient MRI, surveillance and/or follow up with TBI specialists. GFAP has shown diagnostic potential for MRI findings such as DAI and awaits further validation. Tau shows promise in detecting DAI and disrupted functional connectivity. Candidate biomarkers should be evaluated within the context of analytical performance of the assays used, as well as the post-injury timeframe for blood collection relative to MRI abnormalities.

Dataset Information

Improving the clinical management of traumatic brain injury through the pharmacokinetic modeling of peripheral blood biomarkers.

Background

Methods

Results

Conclusions

Publications

Improving the clinical management of traumatic brain injury through the pharmacokinetic modeling of peripheral blood biomarkers.

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