Combining H-FABP and GFAP increases the capacity to differentiate between CT-positive and CT-negative patients with mild traumatic brain injury

Mild traumatic brain injury (mTBI) patients may have trauma-induced brain lesions detectable using CT scans. However, most patients will be CT-negative. There is thus a need for an additional tool to detect patients at risk. Single blood biomarkers, such as S100B and GFAP, have been widely studied in mTBI patients, but to date, none seems to perform well enough. In many different diseases, combining several biomarkers into panels has become increasingly interesting for diagnoses and to enhance classification performance. The present study evaluated 13 proteins individually—H-FABP, MMP-1, MMP-3, MMP-9, VCAM, ICAM, SAA, CRP, GSTP, NKDA, PRDX1, DJ-1 and IL-10—for their capacity to differentiate between patients with and without a brain lesion according to CT results. The best performing proteins were then compared and combined with the S100B and GFAP proteins into a CT-scan triage panel. Patients diagnosed with mTBI, with a Glasgow Coma Scale score of 15 and one additional clinical symptom were enrolled at three different European sites. A blood sample was collected at hospital admission, and a CT scan was performed. Patients were divided into two two-centre cohorts and further dichotomised into CT-positive and CT-negative groups for statistical analysis. Single markers and panels were evaluated using Cohort 1. Four proteins—H-FABP, IL-10, S100B and GFAP—showed significantly higher levels in CT-positive patients. The best-performing biomarker was H-FABP, with a specificity of 32% (95% CI 23–40) and sensitivity reaching 100%. The best-performing two-marker panel for Cohort 1, subsequently validated in Cohort 2, was a combination of H-FABP and GFAP, enhancing specificity to 46% (95% CI 36–55). When adding IL-10 to this panel, specificity reached 52% (95% CI 43–61) with 100% sensitivity. These results showed that proteins combined into panels could be used to efficiently classify CT-positive and CT-negative mTBI patients

Interleukin 10 and Heart Fatty Acid-Binding Protein as Early Outcome Predictors in Patients With Traumatic Brain Injury

Background: Patients with traumatic brain injury (TBI) exhibit a variable and unpredictable outcome. The proteins interleukin 10 (IL-10) and heart fatty acid-binding protein (H-FABP) have shown predictive values for the presence of intracranial lesions. Aim: To evaluate the individual and combined outcome prediction ability of IL-10 and H-FABP, and to compare them to the more studied proteins S100β, glial fibrillary acidic protein (GFAP), and neurofilament light (NF-L), both with and without clinical predictors. Methods: Blood samples from patients with acute TBI (all severities) were collected &lt;24 h post trauma. The outcome was measured &gt;6 months post injury using the Glasgow Outcome Scale Extended (GOSE) score, dichotomizing patients into: (i) those with favorable (GOSE≥5)/unfavorable outcome (GOSE ≤ 4) and complete (GOSE = 8)/incomplete (GOSE ≤ 7) recovery, and (ii) patients with mild TBI (mTBI) and patients with TBIs of all severities. Results: When sensitivity was set at 95-100%, the proteins' individual specificities remained low. H-FABP showed the best specificity (%) and sensitivity (100%) in predicting complete recovery in patients with mTBI. IL-10 had the best specificity (50%) and sensitivity (96%) in identifying patients with favorable outcome in patients with TBIs of all severities. When individual proteins were combined with clinical parameters, a model including H-FABP, NF-L, and ISS yielded a specificity of 56% and a sensitivity of 96% in predicting complete recovery in patients with mTBI. In predicting favorable outcome, a model consisting IL-10, age, and TBI severity reached a specificity of 80% and a sensitivity of 96% in patients with TBIs of all severities. Conclusion: Combining novel TBI biomarkers H-FABP and IL-10 with GFAP, NF-L and S100β and clinical parameters improves outcome prediction models in TBI.</p

INTERLEUKIN 10 AND HEART FATTY-ACID BINDING PROTEIN AS EARLY OUTCOME PREDICTORS IN PATIENTS WITH TRAUMATIC BRAIN INJURY

Background: Patients with traumatic brain injury (TBI) exhibit a variable and unpredictable outcome. The proteins interleukin 10 (IL-10) and heart fatty acid-binding protein (H-FABP) have shown predictive values for the presence of intracranial lesions. Aim: To evaluate the individual and combined outcome prediction ability of IL-10 and H-FABP, and to compare them to the more studied proteins S100β, glial fibrillary acidic protein (GFAP), and neurofilament light (NF-L), both with and without clinical predictors. Methods: Blood samples from patients with acute TBI (all severities) were collected 6 months post injury using the Glasgow Outcome Scale Extended (GOSE) score, dichotomizing patients into: (i) those with favorable (GOSE≥5)/unfavorable outcome (GOSE ≤ 4) and complete (GOSE = 8)/incomplete (GOSE ≤ 7) recovery, and (ii) patients with mild TBI (mTBI) and patients with TBIs of all severities. Results: When sensitivity was set at 95–100%, the proteins' individual specificities remained low. H-FABP showed the best specificity (%) and sensitivity (100%) in predicting complete recovery in patients with mTBI. IL-10 had the best specificity (50%) and sensitivity (96%) in identifying patients with favorable outcome in patients with TBIs of all severities. When individual proteins were combined with clinical parameters, a model including H-FABP, NF-L, and ISS yielded a specificity of 56% and a sensitivity of 96% in predicting complete recovery in patients with mTBI. In predicting favorable outcome, a model consisting IL-10, age, and TBI severity reached a specificity of 80% and a sensitivity of 96% in patients with TBIs of all severities. Conclusion: Combining novel TBI biomarkers H-FABP and IL-10 with GFAP, NF-L and S100β and clinical parameters improves outcome prediction models in TBI

Interleukin 10 and Heart Fatty Acid-Binding Protein as Early Outcome Predictors in Patients With Traumatic Brain Injury

Background:Patients with traumatic brain injury (TBI) exhibit a variable and unpredictable outcome. The proteins interleukin 10 (IL-10) and heart fatty acid-binding protein (H-FABP) have shown predictive values for the presence of intracranial lesions. Aim:To evaluate the individual and combined outcome prediction ability of IL-10 and H-FABP, and to compare them to the more studied proteins S100 beta, glial fibrillary acidic protein (GFAP), and neurofilament light (NF-L), both with and without clinical predictors. Methods:Blood samples from patients with acute TBI (all severities) were collected 6 months post injury using the Glasgow Outcome Scale Extended (GOSE) score, dichotomizing patients into: (i) those with favorable (GOSE >= 5)/unfavorable outcome (GOSE <= 4) and complete (GOSE = 8)/incomplete (GOSE <= 7) recovery, and (ii) patients with mild TBI (mTBI) and patients with TBIs of all severities. Results:When sensitivity was set at 95-100%, the proteins' individual specificities remained low. H-FABP showed the best specificity (%) and sensitivity (100%) in predicting complete recovery in patients with mTBI. IL-10 had the best specificity (50%) and sensitivity (96%) in identifying patients with favorable outcome in patients with TBIs of all severities. When individual proteins were combined with clinical parameters, a model including H-FABP, NF-L, and ISS yielded a specificity of 56% and a sensitivity of 96% in predicting complete recovery in patients with mTBI. In predicting favorable outcome, a model consisting IL-10, age, and TBI severity reached a specificity of 80% and a sensitivity of 96% in patients with TBIs of all severities. Conclusion:Combining novel TBI biomarkers H-FABP and IL-10 with GFAP, NF-L and S100 beta and clinical parameters improves outcome prediction models in TBI

Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI

Blood biomarkers in acute brain injury disorders

Acute brain injury disorders, such as mild traumatic brain injury (mTBI) and stroke, affect millions of people every year. Biomarkers have been suggested as decision tools to facilitate and optimize clinician's decision-making for diagnosis, treatment and prognosis in both diseases. In this project, proteomic methods were used to discover, verify and validate proteins as potential biomarkers. The results showed that H-FABP and IL-10 could be used to rapidly and safely discharge mTBI patients without a brain lesion and thereby avoid harmful CT-scans. In stroke, PRDX-1 was shown capable of helping clinicians to administer the best treatment by indicating the time of onset. The proteins VCAM and e-selectin could early identify stroke patients with poor outcome, permitting rapid and adapted care increasing patient's chances of good recovery. Taken together, these findings show that the use of biomarkers in different clinical applications could be clearly beneficial for mTBI and stroke patients care-taking

E-selectin and vascular cell adhesion molecule-1 as biomarkers of 3-month outcome in cerebrovascular diseases

Inflammation is known to worsen cerebral damage at the acute phase of stroke. In this setting, cell adhesion molecules (CAMs) play a crucial role mediating migration of immune cells into the infarcted area. However, their value in long-term outcome prediction for patients with cerebrovascular diseases (CVD) is less described

Diagnostic performance of peroxiredoxin 1 to determine time-of-onset of acute cerebral infarction

Accurately determining time-of-onset of cerebral infarction is important to clearly identify patients who could benefit from reperfusion therapies. We assessed the kinetics of peroxiredoxin 1 (PRDX1), a protein involved in oxidative stress during the acute phase of ischemia, and its ability to determine stroke onset in a population of patients with known onset of less than 24 hours and in a control group. Median PRDX1 levels were significantly higher in stroke patients compared to controls. PRDX1 levels were also higher from blood samples withdrawn before vs. after 3 hours following stroke onset, and before vs. after 6 hours. ROC analysis with area under the curve (AUC), sensitivity (Se) and specificity (Sp) determined from the Youden index was performed to assess the ability of PRDX1 levels to determine onset. Diagnostic performances of PRDX1 levels were defined by an AUC of 69%, Se of 53% and Sp of 86% for identifying cerebral infarction occurring <3 hours, and an AUC of 68%, Se of 49% and Sp of 88% for cerebral infarction occurring <6 hours. These first results suggest that PRDX1 levels could be the basis of a new method using biomarkers for determining cerebral infarction onset

Early measurement of interleukin-10 predicts the absence of CT scan lesions in mild traumatic brain injury

Traumatic brain injury is a common event where 70%–90% will be classified as mild TBI (mTBI). Among these, only 10% will have a brain lesion visible via CT scan. A triage biomarker would help clinicians to identify patients with mTBI who are at risk of developing a brain lesion and require a CT scan. The brain cells damaged by the shearing, tearing and stretching of a TBI event set off inflammation cascades. These cause altered concentrations of a high number of both pro-inflammatory and anti-inflammatory proteins. This study aimed to discover a novel diagnostic biomarker of mTBI by investigating a broad panel of inflammation biomarkers and their capacity to correctly identify CT-positive and CT-negative patients. Patients enrolled in this study had been diagnosed with mTBI, had a GCS score of 15 and suffered from at least one clinical symptom. There were nine patients in the discovery group, 45 for verification, and 133 mTBI patients from two different European sites in the validation cohort. All patients gave blood samples, underwent a CT scan and were dichotomised into CT-positive and CT-negative groups for statistical analyses. The ability of each protein to classify patients was evaluated with sensitivity set at 100%. Three of the 92 inflammation proteins screened—MCP-1, MIP-1alpha and IL-10 –were further investigated in the verification group, and at 100% sensitivity their specificities reached 7%, 0% and 31%, respectively. IL-10 was validated on a larger cohort in comparison to the most studied mTBI diagnostic triage protein to date, S100B. Levels of both proteins were significantly higher in CT-positive than in CT-negative patients (p < 0.001). S100B’s specificity at 100% sensitivity was 18% (95% CI 10.8–25.2), whereas IL-10 reached a specificity of 27% (95% CI 18.9–35.1). These results showed that IL-10 might be an interesting and clinically useful diagnostic tool, capable of differentiating between CT-positive and CT-negative mTBI patients.Peer reviewe

Admission Levels of Interleukin 10 and Amyloid β 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury.

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1-40 (Aβ40) and 1-42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale-Extended 5-8, n = 49) and unfavorable (Glasgow Outcome Scale-Extended 1-4, n = 33) groups. The outcome was assessed 6-12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90-100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9-100) and specificity of 22.4% (95% CI: 10.2-32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1-4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7-6.2) with a sensitivity of 90.9% (95% CI: 81.8-100) and specificity of 59.2% (95% CI: 40.8-69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI