Brain damage can occur due to various causes including traumatic brain injury, stroke, tumors, infections, and neurodegenerative diseases. Detecting brain damage is crucial for proper diagnosis and management. Neuroimaging techniques like MRI and CT scans are commonly used to detect structural brain damage. However, these techniques are expensive and not readily available in many healthcare settings. A blood test that can detect brain damage quickly and easily would be invaluable. In recent years, researchers have been investigating whether analysis of brain-specific proteins in the blood can reveal neural injury and degeneration. This article reviews the evidence on using blood biomarkers to detect different types of brain damage.
What is a Biomarker?
A biomarker is a biological molecule found in blood, urine, or other tissues/fluids that is a sign of a normal or abnormal process or condition in the body. An ideal biomarker for brain damage would have the following characteristics:
- Specific to the brain tissue
- Released into the blood soon after injury
- Levels correlate with severity of damage
- Sensitive enough to detect mild injuries
- Can identify the location and type of damage
Several protein biomarkers meeting some of these criteria have shown promise for detecting various types of brain injuries.
Evidence for Blood Biomarkers of Traumatic Brain Injury
Traumatic brain injury (TBI) results from a blow or jolt to the head disrupting normal brain function. TBI can range from mild concussions to severe injuries with bleeding and dangerous brain swelling. According to the CDC, in 2014 there were about 2.8 million TBI-related emergency department visits, hospitalizations, and deaths in the U.S. Detecting TBI early is important for prompt treatment and management of complications. The most promising protein biomarkers for TBI are:
S100B
S100B is a calcium-binding protein found primarily in glial cells in the central nervous system. Levels of S100B increase soon after TBI and correlate with injury severity. A meta-analysis found that serum S100B had good sensitivity (88%) within the first 4 hours for detecting CT-visible intracranial injuries. However, it has low specificity (51%) due to extracranial sources and may be elevated in polytrauma patients without TBI. S100B levels can also be used to predict outcomes after head trauma.
Glial Fibrillary Acidic Protein (GFAP)
GFAP is a structural protein in astrocytes of the CNS and a specific marker of brain injury. Multiple studies show serum GFAP is elevated in CT-positive TBI patients. GFAP levels correlate with injury severity and can predict 6-month outcomes. GFAP outperforms S100B for predicting intracranial lesions on CT and disability after head injury. However, GFAP levels appear to peak later than S100B. Combining GFAP measured within 24 hours with S100B may provide the best biomarker profile for detecting TBI.
Tau Proteins
Tau proteins are involved in stabilizing neuronal microtubules. After TBI, tau is released from damaged axons into extracellular fluid and blood. Elevated tau levels correlate with TBI presence and severity. However, tau proteins are not brain-specific and have a longer latency than S100B and GFAP. Tau may be more useful as a subacute biomarker in mild TBI or persistent post-concussive syndrome.
Neurofilament Light Chain (NfL)
NfL is a protein specific to neurons. Serum NfL increases within hours after concussions and severe TBI. High NfL levels can persist for months and are associated with poor recovery. NfL correlates with acute CT abnormalities and predicts chronic white matter damage on MRI. However, more research is needed before NfL can be used clinically.
In summary, GFAP and S100B are the most validated blood biomarkers for diagnosing TBI based on current evidence. NfL and tau show promise but require more prospective validation. Combining biomarkers improves diagnostic accuracy.
Biomarkers in Stroke
Stroke occurs when blood supply to part of the brain is interrupted, causing damage and loss of brain cells. Ischemic stroke from a blood clot makes up 85% of cases. Hemorrhagic stroke caused by bleeding accounts for 15%. Distinguishing between stroke types is necessary for proper treatment. Candidate blood biomarkers for stroke include:
S100B
Like with TBI, S100B is elevated in the first hours after ischemic and hemorrhagic stroke. S100B levels correlate with infarct volume, clinical severity, and functional outcomes. One study found S100B had 92% sensitivity and 95% specificity for detecting CT-confirmed acute stroke when measured within 3 hours of symptom onset. However, S100B has limited utility for distinguishing stroke types.
GFAP
GFAP is also elevated early in both ischemic and hemorrhagic stroke. A few studies report GFAP may be more specific to intracerebral hemorrhage versus ischemic stroke compared to S100B. However, the evidence is limited thus far.
NfL
Serum NfL is increased in acute stroke, particularly after 6-10 days. High NfL levels for months following stroke are associated with poor long-term neurological recovery. But NfL does not distinguish well between stroke types.
Tau
Total tau appears elevated in both major stroke types but may be higher in hemorrhagic stroke. One study found tau accurately differentiated hemorrhagic and ischemic stroke with 85% sensitivity and 78% specificity when measured within 3 hours of onset along with the biomarker FN1. Tau shows promise but requires more validation.
While stroke biomarkers are not definitive yet, S100B and GFAP show the most potential for identifying acute stroke when analyzed along with clinical assessment and neuroimaging. NfL and tau need more prospective evidence. A panel of biomarkers may provide optimal diagnostic accuracy.
Biomarkers in Brain Tumors
Brain tumors are abnormal growths arising from cells in the brain or surrounding structures. Gliomas starting in glial cells account for over 80% of malignant brain tumors. The main biomarkers studied for detecting and monitoring gliomas are:
GFAP
As an astrocyte structural protein, GFAP is often elevated with gliomas and other astrocytic tumors. GFAP levels tend to correlate with tumor grade and size. In one study, serum GFAP distinguished low and high-grade gliomas with 82% sensitivity and 63% specificity. However, GFAP is not specific for brain tumors and can also rise due to non-neoplastic neurological conditions.
S100B
Increased S100B levels are found in patients with gliomas and other brain tumors like meningiomas. But S100B lacks diagnostic specificity. S100B may be more useful for monitoring tumor response to treatment. Decreasing S100B levels over time correlates with positive response to chemotherapy and radiation.
VEGF
Vascular endothelial growth factor (VEGF) stimulates angiogenesis and promotes tumor growth. VEGF is often substantially elevated in high grade and metastatic brain tumors. One meta-analysis reported serum VEGF had a pooled sensitivity of 56% and specificity of 92% for diagnosing gliomas. VEGF levels also reflect treatment response.
MicroRNAs
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. Specific circulating miRNA profiles are associated with different CNS tumor types and grades. For instance, a combination of four miRNAs (miR-21, miR-128, miR-342-3p, and miR-219-5p) distinguished glioblastoma from lower-grade gliomas with 95% sensitivity and 100% specificity in one study. More research is needed before miRNAs can be used clinically.
No single biomarker can definitively diagnose brain tumors or predict prognosis yet. Combining biomarkers like VEGF, GFAP, and miRNA profiles shows promise for aiding diagnosis and monitoring.
Biomarkers in Neurodegenerative Diseases
Neurodegenerative diseases like Alzheimer’s and Parkinson’s disease cause progressive damage and death of neurons in the brain and nervous system. Neurodegeneration leads to accumulation of proteins that are potential biomarkers detectable in blood.
Alzheimer’s Disease
The hallmark signs of Alzheimer’s disease (AD) are amyloid-beta plaques and neurofibrillary tangles of tau proteins in the brain. Plasma levels of amyloid-beta and tau are elevated in AD and mild cognitive impairment patients versus healthy controls. In one major study, a plasma tau/amyloid-beta ratio predicted brain amyloid status with 89% sensitivity and specificity. However, using CSF rather than blood samples improved diagnostic accuracy. More research is needed to establish blood-based biomarkers for AD screening and diagnosis.
Parkinson’s Disease
Alpha-synuclein, DJ-1, and neurofilament light chain levels are increased in the blood of Parkinson’s disease (PD) patients versus controls. But no protein biomarker currently has enough evidence to diagnose PD. Significant challenges include variability between studies and overlap with other neurodegenerative conditions. MicroRNAs show promise as potential future diagnostic and progression biomarkers but need more validation.
ALS
Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease. Specific phosphorylated neurofilament heavy chain isoforms measured in serum and plasma appear to accurately identify ALS patients versus controls. In one study, blood levels of phosphorylated neurofilament heavy chain distinguished ALS with 96% sensitivity and 95% specificity. Neurofilament levels also correlate with disease progression rate. This suggests neurofilament proteins may become useful biomarkers for ALS.
Biomarker research shows great potential for enabling earlier diagnosis of neurodegenerative diseases from blood samples. However, current candidate biomarkers lack the sensitivity and specificity necessary for clinical use. Combining multiple protein and miRNA biomarkers may allow accurate screening and monitoring of progression in the future. Ongoing biomarker discovery and validation efforts are critical.
Challenges and Limitations of Brain Damage Biomarkers
While promising, there are several limitations of current brain injury biomarkers that hinder clinical applicability:
- Most candidate biomarkers lack specificity between different injury mechanisms or neurological conditions.
- Sensitivity for mild injuries or early disease is often insufficient.
- Optimal time windows for measurement are not fully defined.
- Significant variability exists between analytical techniques and platforms.
- Normal reference ranges need to be established for different age groups.
- Standardization and validation across large populations is lacking.
- Effects of comorbidities on biomarker levels need clarification.
- Combining biomarkers and other clinical information will be necessary for accurate diagnosis.
Continued research to address these limitations is essential to translate brain injury biomarkers from bench to bedside. Particularly, large multicenter studies across diverse clinical populations are required to validate biomarker utility.
Future Outlook
The role of blood biomarkers for detecting different types of brain damage holds great promise. Brain-specific proteins like GFAP, S100B, and neurofilaments have shown utility in conditions such as stroke, trauma, tumors, and neurodegeneration. Combining these biomarkers provides greater diagnostic yield than any single marker alone. However, current proteins lack the sensitivity and specificity needed for clinical application in most cases.
Exciting areas of future research include utilizing novel biomarkers and techniques such as:
- Brain-enriched microRNAs
- Exosomes and extracellular vesicles containing brain-derived proteins/RNAs
- High-sensitivity assays and multiplexing platforms
- Multi-modal models incorporating protein biomarkers with clinical data
With further advancements, blood-based biomarkers may soon provide rapid and accurate screening, diagnosis, and monitoring of various neurological disorders at the point of care. This could revolutionize management and improve outcomes for patients with brain damage and disease.
Conclusion
In summary, research demonstrates the promise of blood-based biomarkers for detecting diverse forms of brain injury and degeneration. GFAP and S100B are the most validated protein biomarkers currently, showing utility to identify traumatic brain injury and stroke. Combinations of proteins and miRNAs show potential for improving diagnosis of tumors and neurodegenerative diseases. However, current limitations prevent implementation in clinical practice. With ongoing research to discover novel biomarkers and standardize analytical methods, blood tests could become invaluable tools for managing patients with neurological damage and disorders. While neuroimaging remains the gold standard, blood biomarkers may provide rapid, minimally invasive, and cost-effective adjuncts that improve access and outcomes.
