Rapid, Accurate, Cost-effective Assessment of Blood Biomarkers for Diagnosis of Concussion

Overview

The goal of this observational study is to test if a biosensor can accurately measure a blood biomarker in adult patients presenting to the emergency department with concussion. The main questions it aims to answer are: * Does the biosensor measure the blood biomarker of interest with the same accuracy as the current gold-standard assay technique? * Do relationships exist between blood biomarker measurements from the biosensor and any psychological or physical symptoms of concussion? Participants will be asked to provide blood samples at initial visit and 2-, 6-, and 12-weeks after injury while completing questionnaires at each visit, along with a brief (2 min) daily symptom inventory. Researchers will compare the concussion group to a muscle/skeletal injury group to see if measurements from the biosensor are exclusive to concussion.

BACKGROUND It is estimated 100-300/100,000 people worldwide present to a hospital with traumatic brain injury (TBI) annually, the majority of which are classified as mild. TBI is a disruption in normal brain function caused by external biomechanical forces transmitted directly or indirectly to the head, and is a leading cause of death and disability in Canada. Approximately 1 in 450 Canadians report brain injury as their most significant injury associated with disability in the previous year. Mild traumatic brain injury (mTBI) is operationalized under clinical severity by a Glasgow Coma Scale (GCS) score of 13-15 and is often used interchangeably with concussion, though the most recent consensus definition of concussion is precluded by positive findings on standard neuroimaging techniques. Although labelled as mild with typical recovery times within two weeks of injury for adults and four weeks for youth, up to 30% of patients with concussion experience prolonged symptoms (headache, fatigue, dizziness, insomnia, depression, anxiety, poor balance, and cognitive deficits, etc.) contributing to significant functional impairment and disease burden. Furthermore, in 2016 approximately 10% of diagnosed concussions in Ontario returned to the emergency department within 14 days of injury, increasing demands on the health care system. Lending to its identity as one of the most complex injuries to diagnose and manage, concussion currently relies on subjective measures and symptom reports as clinical indices of injury. There has been accelerated interest in addressing this limitation through research efforts working to establish objective measures of injury including advanced neuroimaging imaging techniques, machine learning of basic physiological functions (brain waves, heart rate, blood pressure, etc.), and blood biomarkers. Blood biomarkers have shown promising results regarding their ability to detect or predict severe and moderate TBI, but results in mTBI are mixed and require further investigation. Two biomarkers of brain injury - glial fibrillary acidic protein (GFAP) and ubiquitin c-terminal hydrolase L1 (UCH-L1) - were recently FDA approved to help identify necessity of a CT scan for adult mTBI patients who might have intracranial lesions. However, beyond the currently insufficient level of evidence regarding blood biomarker applications for concussion diagnosis or prognosis, an additional hurdle for future implementation in a clinical setting remains the high cost and time-consuming assay methodologies for marker detection. Single molecule array technology (SIMOA) is a fully automated immunoassay capable of biomarker detection at the femtogram level, approximately 900x more sensitive than conventional enzyme-linked immunosorbent assays. As the current gold-standard for low concentration biomarker detection, significant monetary and procedural costs may limit SIMOA's future applications for concussion biomarker detection in clinical settings. Fortunately, technological advancements are pushing the boundaries of conventional assay approaches to minimize cost and maximize efficiency, progressing towards point-of-care assay devices. The investigators have developed a GFAP nano-biosensor capable of measuring GFAP concentrations in similar orders of magnitude as SIMOA. Briefly, the GFAP electrochemical biosensor was developed using nano-porous carbon on screen-printed electrodes with hydroxylamine (NH2OH). The nano-coated and functionalized electrodes were immobilized with monoclonal anti-human GFAP capture antibody, then blocked with bovine serum albumin. GFAP binding frequency was translated to serum concentration levels using electrochemical impedance spectroscopy (EIS). The nano-porous biosensor provided ultrasensitive GFAP detection in a wide operational range of 100 fg/mL - 10 ng/mL concentrations in the human serum. It selectively detected GFAP when tested against other biomarkers released after brain injury, and revealed a clinical sensitivity for detection of patients across TBI severities (total n=70; TBI n=26, healthy control n=44) at 84.62% (95%CI, 65.1% to 95.6%) and specificity at 61.36% (CI, 45.5% to 75.6%). The limit of detection of the GFAP biosensor was measured to be 86.6 fg/mL in serum. Additionally, our nano-biosensor demonstrated \<2% intra-variation and \<1% inter-variation, tackling the concern of reproducible biosensor production needed for clinical detection. This research seeks to validate the nano-biosensor in concussion patients presenting to the Emergency Department. OBJECTIVES Primary Aim: Establish the clinical accuracy of the GFAP nano-biosensor in patients with concussion presenting to the emergency department from diagnosis to recovery. Secondary Aim: Assess sensitivity and specificity of the GFAP nano-biosensor for identification of concussion by comparing concussion patients to musculoskeletal (MSK) injury controls. Tertiary Aim: Assess relationships between GFAP nano-biosensor concentrations and psychological (depression, anxiety), physical (headache, sleep disturbances, etc.) symptoms of concussion from diagnosis to recovery. Quaternary aim: Assess correlation between female menstrual cycle hormone concentrations (progesterone, estrogen) and GFAP nano-biosensor concentrations. METHODS This study has a recruitment target of 150 (equal sex representation) acute concussion patients presenting to the emergency department (ED) at foothills medical centre ages 18 through 65. Additionally, a group of 75 (equal sex representation) musculoskeletal (MSK) injury controls will be recruited from the same ED within the same age range. In a repeated measures prospective cohort design, concussion patients will complete an initial visit within 1 week of injury, then follow-up visits at 2-, 6-, and 12-weeks post-injury or until recovered. Control (MSK) patients will complete all measures at a single visit. Concussion patients who are not recovered by 12 weeks post-injury will be asked to complete questionnaires at 6 months post-injury. Study measures include clinical outcome assessments of quality of life, global health, depression, anxiety, sleep, and concussion symptoms, along with blood draws. Concussion patients will be asked to complete the post concussion symptom scale (PCSS) daily via an online link sent to them each morning to monitor recovery. For the purposes of this study, a patient will be deemed recovered if all symptoms have resolved and indicating 100% on a sliding scale that asks how recovered the patient feels from the concussion. All other questionnaires will be completed prior to initial and follow-up blood draws. Researchers will also be providing concussion patients with a QR code linked to the investigators website where patients will have access to concussion education resources to understand the injury. The two assay techniques will be compared using mean detection and distribution curves and Bland-Altman analysis. The performance of the GFAP biosensing kit in detection of uncomplicated concussion patients and monitoring their recovery will be assessed in plasma and serum. The clinical sensitivity and specificity of the GFAP biosensor in plasma and serum will be evaluated using the receiver operating characteristic (ROC) curve in comparison to SIMOA.