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Plasma metabolomic biomarkers accurately classify acute mild traumatic brain injury from controls.

ABSTRACT: Past and recent attempts at devising objective biomarkers for traumatic brain injury (TBI) in both blood and cerebrospinal fluid have focused on abundance measures of time-dependent proteins. Similar independent determinants would be most welcome in diagnosing the most common form of TBI, mild TBI (mTBI), which remains difficult to define and confirm based solely on clinical criteria. There are currently no consensus diagnostic measures that objectively define individuals as having sustained an acute mTBI. Plasma metabolomic analyses have recently evolved to offer an alternative to proteomic analyses, offering an orthogonal diagnostic measure to what is currently available. The purpose of this study was to determine whether a developed set of metabolomic biomarkers is able to objectively classify college athletes sustaining mTBI from non-injured teammates, within 6 hours of trauma and whether such a biomarker panel could be effectively applied to an independent cohort of TBI and control subjects. A 6-metabolite panel was developed from biomarkers that had their identities confirmed using tandem mass spectrometry (MS/MS) in our Athlete cohort. These biomarkers were defined at ?6 hours following mTBI and objectively classified mTBI athletes from teammate controls, and provided similar classification of these groups at the 2, 3, and 7 days post-mTBI. The same 6-metabolite panel, when applied to a separate, independent cohort provided statistically similar results despite major differences between the two cohorts. Our confirmed plasma biomarker panel objectively classifies acute mTBI cases from controls within 6 hours of injury in our two independent cohorts. While encouraged by our initial results, we expect future studies to expand on these initial observations.

SUBMITTER: Fiandaca MS

PROVIDER: S-EPMC5909890 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Plasma metabolomic biomarkers accurately classify acute mild traumatic brain injury from controls.

Fiandaca Massimo S MS Mapstone Mark M Mahmoodi Amin A Gross Thomas T Macciardi Fabio F Cheema Amrita K AK Merchant-Borna Kian K Bazarian Jeffrey J Federoff Howard J HJ

PloS one 20180420 4

Past and recent attempts at devising objective biomarkers for traumatic brain injury (TBI) in both blood and cerebrospinal fluid have focused on abundance measures of time-dependent proteins. Similar independent determinants would be most welcome in diagnosing the most common form of TBI, mild TBI (mTBI), which remains difficult to define and confirm based solely on clinical criteria. There are currently no consensus diagnostic measures that objectively define individuals as having sustained an ...[more]

PMID: 29677216

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Project description:Objective: To investigate the longitudinal evolution of three blood biomarkers: neurofilament light (NFL), glial fibrillary acidic protein (GFAP) and tau, in out-patients and hospitalized patients with mild traumatic brain injury (mTBI) compared to controls, along with their associations-in patients-with clinical injury characteristics and demographic variables, and ability to discriminate patients with mTBI from controls. Methods: A longitudinal observation study including 207 patients with mTBI, 84 age and sex-matched community controls (CCs) and 52 trauma controls (TCs). Blood samples were collected at 5 timepoints: acute (<24 h), 72 h (24-72 h post-injury), 2 weeks, 3 and 12 months. Injury-related, clinical and demographic variables were obtained at inclusion and brain MRI within 72 h. Results: Plasma GFAP and tau were most elevated acutely and NFL at 2 weeks and 3 months. The group of patients with mTBI and concurrent other somatic injuries (mTBI+) had the highest elevation in all biomarkers across time points, and were more likely to be victims of traffic accidents and violence. All biomarkers were positively associated with traumatic intracranial findings on MRI obtained within 72 h. Glial fibrillary acidic protein and NFL levels were associated with Glasgow Coma Scale (GCS) score and presence of other somatic injuries. Acute GFAP concentrations showed the highest discriminability between patients and controls with an Area Under the Curve (AUC) of 0.92. Acute tau and 2-week NFL concentrations showed moderate discriminability (AUC = 0.70 and AUC = 0.75, respectively). Tau showed high discriminability between mTBI+ and TCs (AUC = 0.80). Conclusions: The association of plasma NFL with traumatic intracranial MRI findings, together with its later peak, could reflect ongoing secondary injury or repair mechanisms, allowing for a protracted diagnostic time window. Patients experiencing both mTBI and other injuries appear to be a subgroup with greater neural injury, differing from both the mTBI without other injuries and from both control groups. Acute GFAP concentrations showed the highest discriminability between patients and controls, were highly associated with intracranial traumatic injury, and showed the largest elevations compared to controls at the acute timepoint, suggesting it to be the most clinically useful plasma biomarker of primary CNS injury in mTBI.

Project description:Purpose: High throughput small RNA-Seq analysis from circulating biofluids is crucial in driving the discovery of non-invasive miRNA biomarkers for TBI. In this study, we focused our analysis on acute post-TBI alterations in plasma miRNA profiles in adult, male Sprague-Dawley rats. We compared the plasma miRNA profiles from naive, sham-operated controls and rats with mild and severe TBI. The aim was to identify a miRNA signature that would distinguish the rats with mTBI from the naive and sham-operated controls. Next, we compared the rats with mild and severe TBIs to investigate if a dose-dependent increase would occur in the plasma miRNA levels with corresponding increase in injury severities. Finally, we analysed if the sham surgery itself results in alterations in circulating miRNA profiles, by comparing the naive and sham-operated controls. Methods: TBI was induced with the lateral fluid percussion injury (FPI) model. Tail-vein plasma was collected at 2 days post-TBI from 31 adult male, Sprague-Dawley rats (5 naive, 8 sham-operated controls, 10 mTBI and 8 sTBI) under inhalation of isoflurane anesthesia. Small RNA-Seq was performed from plasma samples of a subset of 20 rats (5 cases each from naive, sham-operated controls, mTBI and sTBI groups). For each case, RNA was isolated from 200 µL plasma using the miRNeasy serum/plasma kit. The extracted RNA was subjected to qPCR-based quality control (QC). Small RNA library preparation was performed with the QIASeq miRNA library kit for Illumina NGS systems. Single-end sequencing of 75 bp reads was performed at a depth of 12M, with one sample/lane in the Illumina NextSeq 550. One naive plasma sample failed at the library preparation step. Hence, small RNA-Seq was succesful for 19/20 cases. The raw fastq files obtained from small RNA-Seq were first manually inspected with FastQC (v0.11.3) to check the overall quality of the sequencing data. For primary quantification of read counts, the fastq files were then uploaded to the Qiagen Geneglobe Data analysis center (DAC), a freely available web resource to analyze data from Qiagen’s QIASeq NGS library kits (https://geneglobe.qiagen.com/in/analyze/). Mapping was performed in the DAC portal with bowtie, using the rat reference genome RGSC Rnor_6.0. Annotation of miRNAs was performed with miRBase v21. Following primary quantification, differential expression analysis for miRNAs was performed with DESeq2 (v1.22.2) in R environment (v3.5.3). Logistic regression (LR) with feature selection utilizing nested leave-one-out cross-validation was also performed to identify miRNAs (“features”) contributing most to groupwise differences (differences between naïve, sham, mTBI, sTBI, sTBI + mTBI and naïve + sham). Results: A total of 748 miRNAs were detected across all samples, out of which 723 (97%) were expressed in all the four groups (naive, sham-operated, mTBI and sTBI). Based on the differential expression and logistic regression analyses, we identified five miRNA candidates that contributed most to the seperation between the mTBI and naive groups: rno-miR-9a-3p, rno-miR-153-3p, rno-miR-15a-3p, rno-miR-136-3p and rno-miR-434-3p. We validated the small RNA-Seq data for these miRNA candidates with miRCURY reverse transcriptase quantitative PCR (RT-qPCR). We could succesfully validate elevated levels of miR-9a-3p, miR-136-3p and miR-434-3p in the mTBI group in comparison to naive. When analysed from the whole cohort, the elevated levels of these miRNAs were consistently observed in the mTBI group compared to the naive, both with RT-qPCR and droplet digital PCR (ddPCR). Further, all the three miRNAs revealed elevated plasma levels in the sTBI group in comparison to the mTBI. Conclusions: Elevated plasma miRNA signature of miR-9a-3p, miR-136-3p and miR-434-3p distinguishes rats with mTBI from the naive, in the lateral FPI model of TBI. Further, all these miRNAs exhibit a dose-dependent increase in plasma levels with increase in injury severities.

Project description:IntroductionDynamic functional network connectivity (dFNC), derived from magnetic resonance imaging (fMRI), is an important technique in the search for biomarkers of brain diseases such as mild traumatic brain injury (mTBI). At the individual level, mTBI can affect cognitive functions and change personality traits. Previous research aimed at detecting significant changes in the dFNC of mTBI subjects. However, one of the main concerns in dFNC analysis is the appropriateness of methods used to correct for subject movement. In this work, we focus on the effect that rearranging movement correction at different points of the processing pipeline has in dFNC analysis utilizing mTBI data.MethodsThe sample cohort consists of 50 mTBI patients and matched healthy controls. A 5-min resting-state run was completed by each participant. Data were preprocessed using different pipeline alternatives varying with the place where motion-related variance was removed. In all pipelines, group-independent component analysis (gICA) followed by dFNC analysis was performed. Additional tests were performed varying the detection of temporal spikes, the number of gICA components, and the sliding-window size. A linear support vector machine was used to test how each pipeline affects classification accuracy.ResultsResults suggest that correction for motion variance before spatial smoothing, but leaving correction for spiky time courses after gICA produced the best mean classification performance. The number of gICA components and the sliding-window size were also important in determining classification performance. Variance in spikes correction affected some pipelines more than others with fewer significant differences than the other parameters.ConclusionThe sequence of preprocessing steps motion regression, smoothing, gICA, and despiking produced data most suitable for differentiating mTBI from healthy subjects. However, the selection of optimal preprocessing parameters strongly affected the final results.

Project description:Heterogeneity of injury severity among children with traumatic brain injury (TBI) classified by the Glasgow Coma Scale (GCS) makes comparisons across research cohorts, enrollment in clinical trials, and clinical predictions of outcomes difficult. The present study uses latent class analysis (LCA) to distinguish severity subgroups from a prospective cohort of 433 children 2.5-15 years of age with TBI who were recruited from two level 1 pediatric trauma centers. Indicator variables available within 48 h post-injury including emergency department (ED) GCS, hospital motor GCS, Abbreviated Injury Score (AIS), Rotterdam Score, hypotension in the ED, and pre-hospital loss of consciousness, intubation, seizures, and sedation were evaluated to define subgroups. To understand whether latent class subgroups were predictive of clinically meaningful outcomes, the Pediatric Injury Functional Outcome Scale (PIFOS) at 6 and 12 months, and the Behavior Rating Inventory of Executive Function at 12 months, were compared across subgroups. Then, outcomes were examined by GCS (primary) and AIS (secondary) classification alone to assess whether LCA provided improved outcome prediction. LCA identified four distinct increasing severity subgroups (1-4). Unlike GCS classification, mean outcome differences on PIFOS at 6 months showed decreasing function across classes. PIFOS differences relative to the lowest latent class (LC1) were: LC2 2.27 (0.83, 3.72), LC3 3.99 (1.88, 6.10), and LC4 11.2 (7.04, 15.4). Differences in 12 month outcomes were seen between the most and least severely injured groups. Differences in outcomes in relation to AIS were restricted to the most and less severely injured at both time points. This study distinguished four latent classes that are clinically meaningful, distinguished a more homogenous severe injury group, and separated children by 6-month functional outcomes better than GCS alone. Systematic reporting of these variables would allow comparisons across research cohorts, potentially improve clinical predictions, and increase sensitivity to treatment effects in clinical trials.

Project description:Mild traumatic brain injury is a relatively common event in contact sports and there is increasing interest in the long-term neurocognitive effects. The diagnosis largely relies on symptom reporting and there is a need for objective tools to aid diagnosis and prognosis. There are recent reports that blood biomarkers could potentially help triage patients with suspected injury and normal CT findings. We have measured plasma concentrations of glial and neuronal proteins and explored their potential in the assessment of mild traumatic brain injury in contact sport. We recruited a prospective cohort of active male rugby players, who had pre-season baseline plasma sampling. From this prospective cohort, we recruited 25 players diagnosed with mild traumatic brain injury. We sampled post-match rugby players without head injuries as post-match controls. We measured plasma neurofilament light chain, tau and glial fibrillary acidic protein levels using ultrasensitive single molecule array technology. The data were analysed at the group and individual player level. Plasma glial fibrillary acidic protein concentration was significantly increased 1-h post-injury in mild traumatic brain injury cases compared to the non-injured group (P = 0.017). Pairwise comparison also showed that glial fibrillary acidic protein levels were higher in players after a head injury in comparison to their pre-season levels at both 1-h and 3- to 10-day post-injury time points (P = 0.039 and 0.040, respectively). There was also an increase in neurofilament light chain concentration in brain injury cases compared to the pre-season levels within the same individual at both time points (P = 0.023 and 0.002, respectively). Tau was elevated in both the non-injured control group and the 1-h post-injury group compared to pre-season levels (P = 0.007 and 0.015, respectively). Furthermore, receiver operating characteristic analysis showed that glial fibrillary acidic protein and neurofilament light chain can separate head injury cases from control players. The highest diagnostic power was detected when biomarkers were combined in differentiating 1-h post-match control players from 1-h post-head injury players (area under curve 0.90, 95% confidence interval 0.79-1.00, P < 0.0002). The brain astrocytic marker glial fibrillary acidic protein is elevated in blood 1 h after mild traumatic brain injury and in combination with neurofilament light chain displayed the potential as a reliable biomarker for brain injury evaluation. Plasma total tau is elevated following competitive rugby with and without a head injury, perhaps related to peripheral nerve trauma and therefore total tau does not appear to be suitable as a blood biomarker.

Project description:To investigate longitudinal changes in global and regional brain volume in patients 1 year after mild traumatic brain injury (MTBI) and to correlate such changes with clinical and neurocognitive metrics.This institutional review board-approved study was HIPAA compliant. Twenty-eight patients with MTBI (with 19 followed up at 1 year) with posttraumatic symptoms after injury and 22 matched control subjects (with 12 followed up at 1 year) were enrolled. Automated segmentation of brain regions to compute regional gray matter (GM) and white matter (WM) volumes was performed by using three-dimensional T1-weighted 3.0-T magnetic resonance imaging, and results were correlated with clinical metrics. Pearson and Spearman rank correlation coefficients were computed between longitudinal brain volume and neurocognitive scores, as well as clinical metrics, over the course of the follow-up period.One year after MTBI, there was measurable global brain atrophy, larger than that in control subjects. The anterior cingulate WM bilaterally and the left cingulate gyrus isthmus WM, as well as the right precuneal GM, showed significant decreases in regional volume in patients with MTBI over the 1st year after injury (corrected P < .05); this was confirmed by means of cross-sectional comparison with data in control subjects (corrected P < .05). Left and right rostral anterior cingulum WM volume loss correlated with changes in neurocognitive measures of memory (r = 0.65, P = .005) and attention (r = 0.60, P = .01). At 1-year follow-up, WM volume in the left cingulate gyrus isthmus correlated with clinical scores of anxiety (Spearman rank correlation r = -0.68, P = .007) and postconcussive symptoms (Spearman rank correlation r = -0.65, P = .01).These observations demonstrate structural changes to the brain 1 year after injury after a single concussive episode. Regional brain atrophy is not exclusive to moderate and severe traumatic brain injury but may be seen after mild injury. In particular, the anterior part of the cingulum and the cingulate gyrus isthmus, as well as the precuneal GM, may be distinctively vulnerable 1 year after MTBI.

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Plasma metabolomic biomarkers accurately classify acute mild traumatic brain injury from controls.

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Plasma metabolomic biomarkers accurately classify acute mild traumatic brain injury from controls.

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