Biomarkers Differentiate Mild Brain Trauma from Other Types of Injury
By LabMedica International staff writers Posted on 05 Apr 2015 |
A panel of protein biomarkers has been established that can identify patients with mild traumatic brain injury (concussion) and differentiate those patients from healthy individuals and from patients with other injuries including broken bones.
No routine tests currently exist to objectively diagnose mild traumatic brain injury (mTBI). Previously reported biomarkers for this type of injury represented proteins released from the damaged neurons or glia. However, the low levels of these proteins and/or the complexity of assays used for their detection limited the implementation of these biomarkers in routine practice.
In a different approach to the problem of diagnosing mTBI, investigators at Brown University (Providence, RI, USA) sought to identify proteins whose synthesis was altered after mTBI and whose blood levels could be measured using standard immunoassays.
To this end they measured 18 different proinflammatory proteins in three groups of individuals: an experimental group comprising 55 emergency room patients who had mTBI diagnosed by other means, a control group of 44 individuals who were uninjured, and a second control group of 17 patients who had long-bone fractures.
Four candidate biomarkers were identified: copeptin, galectin 3 (LGALS3), matrix metalloproteinase 9 (MMP9), and occludin (OCLN). The plasma concentration of copeptin was found to be lowered by 3.4-fold in mTBI patients within eight hours after accident as compared to uninjured controls. Plasma levels of GALS3, MMP9, and OCLN increased 3.6–4.5-fold within the same time frame post-injury. The levels of at least two biomarkers were altered beyond their respective cutoff values in 90% of mTBI patients, whereas in none of uninjured controls, were the levels of two biomarkers simultaneously changed. A positive correlation between the plasma levels of LGALS3 and OCLN was also found in mTBI patients, whereas in bone injury patients or uninjured subjects, these variables did not correlate. The significance of the four biomarkers for indicating concussion endured regardless of patient age, gender, body-mass index, or other medical characteristics.
"This was a broad spectrum of the population with different genders, different ethnicities, different age, and different physical conditions, and on this background these four biomarkers were not influenced," said contributing author Dr. Joanna Szmydynger-Chodobska, a researcher at Brown University.
The Brown University investigators plan to develop a microfluidic chip that will analyze these biomarkers within two hours, and they have filed for a patent to protect this concept.
The concussion biomarker study was published in the March 20, 2015, online edition of the Journal of Neurotrauma.
Related Links:
Brown University
No routine tests currently exist to objectively diagnose mild traumatic brain injury (mTBI). Previously reported biomarkers for this type of injury represented proteins released from the damaged neurons or glia. However, the low levels of these proteins and/or the complexity of assays used for their detection limited the implementation of these biomarkers in routine practice.
In a different approach to the problem of diagnosing mTBI, investigators at Brown University (Providence, RI, USA) sought to identify proteins whose synthesis was altered after mTBI and whose blood levels could be measured using standard immunoassays.
To this end they measured 18 different proinflammatory proteins in three groups of individuals: an experimental group comprising 55 emergency room patients who had mTBI diagnosed by other means, a control group of 44 individuals who were uninjured, and a second control group of 17 patients who had long-bone fractures.
Four candidate biomarkers were identified: copeptin, galectin 3 (LGALS3), matrix metalloproteinase 9 (MMP9), and occludin (OCLN). The plasma concentration of copeptin was found to be lowered by 3.4-fold in mTBI patients within eight hours after accident as compared to uninjured controls. Plasma levels of GALS3, MMP9, and OCLN increased 3.6–4.5-fold within the same time frame post-injury. The levels of at least two biomarkers were altered beyond their respective cutoff values in 90% of mTBI patients, whereas in none of uninjured controls, were the levels of two biomarkers simultaneously changed. A positive correlation between the plasma levels of LGALS3 and OCLN was also found in mTBI patients, whereas in bone injury patients or uninjured subjects, these variables did not correlate. The significance of the four biomarkers for indicating concussion endured regardless of patient age, gender, body-mass index, or other medical characteristics.
"This was a broad spectrum of the population with different genders, different ethnicities, different age, and different physical conditions, and on this background these four biomarkers were not influenced," said contributing author Dr. Joanna Szmydynger-Chodobska, a researcher at Brown University.
The Brown University investigators plan to develop a microfluidic chip that will analyze these biomarkers within two hours, and they have filed for a patent to protect this concept.
The concussion biomarker study was published in the March 20, 2015, online edition of the Journal of Neurotrauma.
Related Links:
Brown University
Latest Pathology News
- AI Integrated With Optical Imaging Technology Enables Rapid Intraoperative Diagnosis
- HPV Self-Collection Solution Improves Access to Cervical Cancer Testing
- Hyperspectral Dark-Field Microscopy Enables Rapid and Accurate Identification of Cancerous Tissues
- AI Advancements Enable Leap into 3D Pathology
- New Blood Test Device Modeled on Leeches to Help Diagnose Malaria
- Robotic Blood Drawing Device to Revolutionize Sample Collection for Diagnostic Testing
- Use of DICOM Images for Pathology Diagnostics Marks Significant Step towards Standardization
- First of Its Kind Universal Tool to Revolutionize Sample Collection for Diagnostic Tests
- AI-Powered Digital Imaging System to Revolutionize Cancer Diagnosis
- New Mycobacterium Tuberculosis Panel to Support Real-Time Surveillance and Combat Antimicrobial Resistance
- New Method Offers Sustainable Approach to Universal Metabolic Cancer Diagnosis
- Spatial Tissue Analysis Identifies Patterns Associated With Ovarian Cancer Relapse
- Unique Hand-Warming Technology Supports High-Quality Fingertip Blood Sample Collection
- Image-Based AI Shows Promise for Parasite Detection in Digitized Stool Samples
- Deep Learning Powered AI Algorithms Improve Skin Cancer Diagnostic Accuracy
- Microfluidic Device for Cancer Detection Precisely Separates Tumor Entities