Description

Classification. A classification of biomarkers is shown in Table 1.

Table 1. Classification of Biomarkers

Technologies for discovery of biomarkers of neurologic disorders.

Compared with acute neurologic conditions, biomarker discovery in chronic progressive and relapsing neurodegenerative diseases may be more difficult because the degenerative process may be so slow that the biomarker discovered is released only in small quantities, and it may be difficult to differentiate acute new damage, relevant to prognostic estimates, from already existing background damage. However, a potential advantage in chronic conditions is that there may be sufficient time for the disease to leave a specific signature on the biomarker by the means of post-translational modifications. Hypothesis-driven biomarker discovery, which focuses on post-translational modifications (such as phosphorylation, aggregate formation, or changes in protein stoichiometry) may open new avenues for successful biomarker discovery in chronic and relapsing conditions such as dementia and multiple sclerosis.

In addition to genomics and proteomics, metabolomics provide insights into the metabolic changes and underlying mechanisms involved in the pathogenesis of neurologic disorders. Uncovering characteristic metabolic alterations in neurologic disorders is important for a better understanding of their pathogenesis and for identifying potential biomarkers and drug targets (05).

CNS biomarkers in blood. Plasma or serum is the most convenient source of biomarkers. However, a pathological process in the CNS is not always reflected in the systemic compartments, and the detection of such biomarkers has been mostly limited to neurologic diseases that have an autoimmune or metabolic basis. Refined proteomic technologies are now being used to detect biomarkers of neurodegenerative disorders in the blood.

Antibody-based tests can measure proteins in the blood. Various biomarkers found in blood include glial biomarkers, neuron-specific enolase, myelin basic protein, and C-tau.

Each of the major glia subtypes -- oligodendroglia, astroglia, and microglia -- are related to useful biomarkers, and many assays of central nervous system diseases are based on glial cell function as well as response to injury (16). Well known examples are glial fibrillary acidic protein (GFAP) and S100 protein.

Concentrations of the S100 protein, an acidic calcium-binding protein found in the gray matter of the brain, are elevated in serum after brain damage. Several commercial ELISA assays are available for S100 protein and are useful biochemical markers for the early assessment of brain damage by the quantitative determination of S100 in serum.

CSF biomarkers. CSF is an important source of potential biomarkers for neurologic disorders. CSF is also a rich source of biomarkers of systemic disorders such as peptides and antibodies that can cross the blood-brain barrier. Proteomic technologies such as immunoblotting, isoelectric focusing, 2D gel electrophoresis, and mass spectrometry have proven useful for deciphering the CSF proteome. CSF proteins are generally less abundant than their corresponding serum counterparts, necessitating the development and use of sensitive analytical techniques. Brain extracellular fluid, mostly obtained by cerebral microdialysis and subjected to proteomic analysis along with CSF, is also a good source of biomarkers of CNS disorders (32). Neurochemical biomarkers for cerebral metabolism that can be monitored by cerebral microdialysis are shown in Table 2.

Table 2. Biomarkers of Cerebral Metabolism

Genomic technologies for CNS biomarkers. Due to the complex nature of neurologic disorders, it is difficult to identify the mechanisms using conventional methods wherein only small pathways around specific target genes are investigated. The advent of systems biology approaches has made it possible to study these complex problems from the whole-genome perspective. Genomic technologies have been increasingly applied to the investigation of neurologic disorders and involve investigation of the genome, transcriptome, and epigenome. There are 2 types of technologies available for genomic studies, including sequencing and various array platforms. For the investigation of genomic variation, the samples generally come from peripheral blood although saliva has also been used. For the investigation of transcriptome, brain tissue is the most studied because it is more relevant to the disease mechanism. The peripheral blood and CSF have also been investigated, mostly for the discovery of novel biomarkers. These 3 tissues have also been utilized in the investigation of epigenomic alteration.

Brain imaging for detection of biomarkers. Imaging techniques enable the diagnosis of disease in vivo. Several specialized techniques have evolved during the past quarter of a century for imaging pathology in the living brain. These include CT, MRI, PET, and SPECT.

MRI sensors that directly and rapidly respond to chemicals involved in the brain’s information processing would provide a much more precise measurement of brain activity. An MRI sensor that responds to the neurotransmitter dopamine may significantly improve the specificity and resolution of brain imaging procedures (52). The sensor is derived from the heme domain of the bacterial cytochrome P450-BM3. This new tool connects molecular phenomena in the nervous system with whole brain imaging techniques, enabling precise exploration of processes and relating them to the overall function of the brain. The protein engineering approach can be generalized to create probes for other targets. Molecular fMRI reveals much more specific information about the brain’s activity and circuitry than conventional blood-related fMRI.

Although imaging biomarkers are used in the diagnostic workup of neurologic patients, the use in clinical trials has been limited. Changes in brain pathology, visualized by imaging, can be used as an in vivo guide to the treatment. Brain imaging has an important role to play in detection of biomarkers of neurodegenerative diseases.

Brain imaging, mainly ultrasound and MRI, is useful as a biomarker of brain injury in the newborn due to hypoxia-ischemia, brain hemorrhage, or infection. However, the challenge is to correlate brain structure with function, and new technologies will provide insights into the function of the developing brain. Imaging will play a key role as an early biomarker to facilitate clinical trials of neuroprotective therapies.

Diffusion tensor imaging (DTI) tractography is a biomarker and early endpoint in traumatic brain injury and aneurysmal subarachnoid hemorrhage (aSAH). DTI parameters, assessed at approximately day 12 after injury, correlate with mortality at 6 months in patients with severe traumatic brain injury or aneurysmal subarachnoid hemorrhage with similar patterns for both (50). A prospective study has shown that MRI-based measures of cerebral functional network connectivity in the acute phase of cardiac arrest correlate with functional outcome at 1 year and should be validated as early biomarkers of potential for long-term recovery in patients with anoxic-ischemic encephalopathy (47).

Digital biomarkers of neurologic disorders. Wearable or implanted digital devices for measuring various vital functions or laboratory parameters are being used for monitoring patient health continuously outside the setting of a hospital or a physician’s office. An example is assessment of cognitive biomarkers using data from personal digital devices.

Some of the monitoring devices may be linked to therapy by neuromodulation in a closed loop system. Developments and opportunities for using mobile technology to advance research and treatment of the CNS were discussed at a workshop (National Academy of Sciences 2018). The participants explored innovative approaches for using devices and mobile health technology to predict, diagnose, monitor, assess compliance with, and develop treatments for CNS disorders, including discussion of methodology, analytical techniques, and the evidence needed to validate the data for use in research and clinical practice.

A potential problem with digital biomarkers is that continuous monitoring of disease progression, eg, in Parkinson disease, provides more data points than a neurologist’s evaluation during an office visit and digital may not correlate with neurologist’s clinical evaluation. This may require reassessment of the concepts of “validated” predictive measures for Parkinson disease.

Clinical applications

There are thousands of biomarkers of neurologic disorders under investigation, but few are validated or approved. Biomarkers may represent disturbances of normal function, such as leakage through the blood-brain barrier (which may be associated with several diseases) or adverse reaction of the nervous system to harmful agents, or they may be characteristic of a specific disease process. Examples of biomarkers are discussed below that have potential clinical utility in some neurologic disorders. There are biomarkers of almost all the known diseases that have been documented elsewhere (22).

Biomarkers of disruption of the blood-brain barrier. Two main approaches are used for studying the integrity of human blood-brain barrier in vivo: (1) structural imaging employs contrast agents that only penetrate the blood-brain barrier at sites of damage, and (2) functional imaging is used to study the transport of substances across the blood-brain barrier--both intact and damaged. Structural imaging employs contrast agents with CT scanning and is relatively insensitive. MRI with the contrast agent gadolinium is more sensitive. Functional imaging is done with PET and can quantify cerebral uptake of therapeutic agents, such as cytotoxic agents and monoclonal antibodies. SPECT is less versatile than PET but can provide semiquantitative measurement of blood-brain barrier leakage of albumin or red blood cells. There is a need for biomarkers to detect early changes in the blood-brain barrier.

Loss of integrity of the blood-brain barrier resulting from ischemia or reperfusion is a precursor to hemorrhagic transformation and poor outcome in acute stroke patients. An MRI biomarker has been used to characterize early blood-brain barrier disruption in human focal brain ischemia and its association with reperfusion, hemorrhagic transformation, and poor outcome. Reperfusion was found to be the most powerful independent predictor of early blood-brain barrier disruption and, thus, of hemorrhagic transformation and is important for the decision for acute thrombolytic therapy. Early blood-brain barrier disruption as defined by this imaging biomarker is a promising target for adjunctive therapy to reduce the complications associated with thrombolytic therapy, broaden the therapeutic window, and improve clinical outcome in acute stroke.

The astrocytic protein S100B is a potentially useful peripheral biomarker of blood-brain barrier permeability. Other biomarkers of blood-brain barrier have been discovered by proteomic approaches. These proteins are virtually absent in normal blood, appear in serum from patients with cerebral lesions, and can be easily detected by commercially available ELISA tests. S100B levels in peripheral blood are raised in soldiers under stress, leading to increased blood-brain barrier permeability secondary to immune activation, which is associated with stress-related depression and anxiety (06; 28).

Biomarkers of neurotoxicity. Desirable features of biomarkers of neurotoxicity are:

Glial fibrillary acidic protein as biomarker of neurotoxicity. The glial reaction, gliosis, represents a hallmark of all types of nervous system injury. Therefore, biomarkers of gliosis can be applied for assessment of neurotoxicity. The astroglial protein, glial fibrillary acidic protein (GFAP), can serve as such a biomarker of neurotoxicity in response to a panel of known neurotoxic agents. Qualitative and quantitative analysis of GFAP has shown this biomarker to be a sensitive and specific indicator of the neurotoxicity. The implementation of GFAP and related glial biomarkers in neurotoxicity screens may serve as the basis for further development of molecular signatures predictive of adverse effects on the nervous system.

Single-stranded DNA as a biomarker of neuronal apoptosis. Single-stranded DNA (ssDNA) is a biomarker of apoptosis and programmed cell death, which appears prior to DNA fragmentation during delayed neuronal death. Neuronal immunopositivity for ssDNA can be detected in the brain, independent of the age, gender of subjects, and postmortem interval, and depends on the cause of death. Higher positivity is typically found in the pallidum for delayed brain injury death and fatal carbon monoxide intoxication and in the cerebral cortex, pallidum, and substantia nigra for drug intoxication. The neuronal positivity is usually lower for drowning and acute ischemic disease.

Biomarkers of neuroinflammation. Neuroinflammation plays a role in several neurologic disorders but there is little consensus on how neuroinflammation is a cause as well as a sequel of disease in the brain. There is uncertainty about how to translate increased understanding of the pathomechanisms of neuroinflammation and its manifestations into therapeutics, indicating a need for biomarkers that can be used not only as measures of disease progression but as response to therapies as well. To address these issues, the Forum on Neuroscience and Nervous System Disorders of the National Academies of Sciences, Engineering, and Medicine convened a workshop in 2017 to explore the role and mechanisms of neuroinflammation in neurologic disorders as well as strategies for identification and validation of biomarkers of neuroinflammation in disorders ranging from multiple sclerosis to neuropsychiatric disorders such as depression (01).

Telomere length as a biomarker of neurologic disorders associated with aging. The length of telomeres (ie, protective chromosomal caps) is a biomarker for an individual’s health and aging, and shortened leukocyte telomere length has, for example, been associated with greater susceptibility to age-related diseases, including mild cognitive impairment and Alzheimer disease. Results of a study on healthy adults indicate an association between short-term change in leukocyte telomere length and brain structure, eg, in plasticity of the left precuneus extending to the posterior cingulate cortex (44). Leukocyte telomere shortening was related to cortical thinning, and leukocyte telomere lengthening was related to cortical thickening. Further studies are required to determine potential long-term implications of such change in relation to cellular aging and the development of neurodegenerative disorders. No effect of mental training was noted on telomere length.

Viral infections of the CNS. A study on patients has shown that serum uric acid levels, which are associated with oxidative stress and antioxidant status, are reduced in patients with viral infections of the CNS and are increased by effective therapy. The patients' serum uric acid levels are correlated inversely with outcomes as measured with the Glasgow Outcome Scale (27). Serum uric acid level may be a biomarker for predicting treatment outcomes and prognoses for patients with acute CNS viral infections with inflammatory components.

NeuroCovid-19 due to SARS-CoV-2 infection is well documented. Several biomarkers are being studied in the context of neurologic disorders related to SARS-CoV-2. These biomarkers enable a better understanding of the pathophysiology of Covid-19 as well as the diagnosis of neurologic complications and contribute to the prognostic evaluation of patients (03). Increased CSF and/or plasma levels of glial fibrillary acidic protein, neurofilament light polypeptide, tau, and several inflammatory biomarkers have been reported in Covid-19 patients (11).

Alzheimer disease. Numerous biomarkers are under investigation, including those based on biochemical examinations of body fluids, genomics, and brain imaging. A study of association between brain gene expression, DNA methylation, and alteration of ex vivo MRI transverse relaxation in late-life cognitive decline shows brain gene expression and DNA methylation dysregulations are implicated in the alteration of brain tissue (63). It can be measured in vivo and may eventually serve as a biomarker of aging brain. This association with late-life cognitive decline is in addition to the influence of common neuropathologic conditions.

Brain imaging biomarkers. Techniques available clinically for biomarkers of Alzheimer disease include MRI and PET. MRI shows reduced volume of hippocampus in early cases and global brain shrinkage in advanced Alzheimer disease. PET is used for imaging Aβ deposits in the intact brain and may be considered as a biomarker for presymptomatic diagnosis of Alzheimer disease. Several radiopharmaceuticals have been used to facilitate imaging Aβ deposits. The gold standard for amyloid imaging has been PiB (Pittsburg compound B)-PET. A Cochrane Database review concluded that although good sensitivity achieved in some studies is promising for the value of 11C-PiB-PET, its routine use in clinical practice is not recommended because of the heterogeneity in conduct and interpretation of the test as well as the lack of defined thresholds for determination of test positivity (64). This biomarker is a high-cost investigation; therefore, it is important to clearly demonstrate its accuracy and standardize the method of diagnosis prior to it being widely used. 11C-PiB-PET is being replaced by Florbetapir-PET, Florbetaben-PET and Flutemetamol-PET, which are approved by the United States Food and Drug Administration. However, because of the high cost, it is not routinely used except for special indications and in clinical trials or research studies.

Plasma protein biomarkers of Alzheimer disease. Plasma samples from early Alzheimer disease patients have been examined with proteomic technologies—2-dimensional differential gel electrophoresis combined with matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry, and they have been compared with samples from normal subjects as controls. Two proteins, including apolipoprotein A-4 and fibrinogen gamma chain, were upregulated in plasma of mild Alzheimer disease patients, suggesting that altered expression levels of these proteins may yield candidate biomarkers for the early diagnosis of the disease (25).

Use of biomarkers in clinical trials of Alzheimer disease. As of May 2021, 556 clinical trials of biomarkers of Alzheimer disease are listed on ClinicalTrials.gov. No specific CSF biomarker test system or assay validation process is yet endorsed by the FDA, but the agency recognizes the following exploratory prognostic biomarkers for enrichment in early stage Alzheimer disease clinical trials:

Biomarkers alone cannot predict development of dementia in Alzheimer disease. However, a clinical study has provided biomarker-based prognostic models that may help determine any type of dementia in patients with mild cognitive impairment at the individual level (58).

Parkinson disease. Eosinophilic inclusions (Lewy bodies) were identified in the brains of patients with Parkinson disease and, along with abnormalities in the substantia nigra, became recognized pathologic biomarkers of the disease. As of May 2021, approximately 305 clinical trials listed on ClinicalTrials.gov are relevant to biomarkers of Parkinson disease. Table 3 shows biomarkers of Parkinson disease and the serum autoantibodies that are the most promising for diagnosis.

Table 3. Biomarkers of Parkinson Disease

Alpha-synuclein as biomarker of Parkinson disease. A review of clinical studies carried out on CSF quantification of α-synuclein species in Parkinson disease supports the value of total and oligomeric α-synuclein in diagnosis of Parkinson disease as well as in the differential diagnosis from other types of parkinsonism (41).

Imaging biomarkers of Parkinson disease. Radiotracer imaging of the nigrostriatal dopaminergic system, using 18Ffluorodopa PET, (+)-11Cdihydrotetrabenazine PET, 123Ibeta-CIT SPECT, and 18Ffluorodeoxyglucose PET, provides a widely used but controversial biomarker of Parkinson disease. These imaging techniques help to understand disease biology and facilitate drug discovery and early human trials, relying on the evidence that they are measuring relevant biological processes. The radiotracers fulfill this criterion, although they do not measure the number or density of dopaminergic neurons. Biomarkers used as diagnostic tests, prognostic tools, or surrogate endpoints must have not only biological relevance but also a strong linkage to the clinical outcome of interest. No radiotracers fulfill these criteria, and current evidence does not support the use of imaging as a diagnostic tool in clinical practice or as a surrogate endpoint in clinical trials. Mechanistic information added by radiotracer imaging to clinical trials may be difficult to interpret because of uncertainty about the interaction between the interventions and the tracer.

Olfactory dysfunction is common in Parkinson disease and is more closely correlated with hippocampal dopaminergic denervation than nigrostriatal dopaminergic denervation. Results of multi-tracer PET studies show that odor identification deficits in Parkinson disease are best predicted by cholinergic denervation and to a lesser extent by dopaminergic denervation. Progressive changes in olfaction may be used as a biomarker of cholinergic denervation and cognitive decline in Parkinson disease (04).

Caffeine. Results of a study show that serum levels of caffeine and 9 of its downstream metabolites are significantly decreased even in patients with early Parkinson disease, unrelated to total caffeine intake or disease severity, and without significant genetic variations in CYP1A2 or CYP2E1, encoding cytochrome P450 enzymes primarily involved in metabolizing caffeine in humans (15).

Concluding remarks about biomarkers of Parkinson disease. Considerable progress has been made during the past 2 decades in identifying and assessing biomarkers of Parkinson disease, but no fully validated biomarker is currently available. In view of the multiple genetic causes for Parkinson disease that have already been identified, the marked variability in the loss of dopaminergic biomarkers measured by imaging at the time of onset of motor symptoms and the heterogeneity of clinical symptoms at onset and during clinical progression, it is likely many biomarkers encompassing pathobiology to molecular genetic mechanisms will be necessary to fully map the risk and progression of Parkinson disease. Detection of biomarkers of the disease before clinical onset will be a further challenge. Proteomic technologies are promising for selection and overview of potential protein biomarkers of Parkinson disease. A combination of multiple or at least 2 proteins will be necessary to differentiate Parkinson disease with dementia from other dementing syndromes. A systems biology approach and use of microarrays are promising for discovery and evaluation of biomarkers to detect the early stages of Parkinson disease and identify individuals at risk for developing the disease, for improvement of early diagnosis, for tracking disease progression with precision, and for testing the efficacy of new treatments.

The U.S. FDA recognizes dopamine transporter as a molecular neuroimaging biomarker for clinical trials of Parkinson disease.

Biomarkers of Huntington disease. Although a genetic test is available for Huntington disease, biomarkers of the disease state are still in development as listed in Table 4. Such biomarkers may provide clues to the state of Huntington disease and may be of predictive value in clinical trials. As of May 2021, 50 clinical trials of biomarkers of Huntington disease are listed on ClinicalTrials.gov.

Table 4. Biomarkers of Huntington Disease

Measurement of huntingtin is very important as several potential therapies for Huntington disease are targeted against either huntingtin itself or against some of its functional properties. Measuring huntingtin levels, its physical state, its proteolytic products, or its interactions with other molecules would all have distinct values as biomarkers, especially as pharmacodynamic indicators.

Biomarkers of multiple sclerosis. Several proteins are under investigation as biomarkers of multiple sclerosis corresponding to diverse pathophysiological processes, including neuroinflammation, demyelination, axonal damage, neurodegeneration, and repair mechanisms involved in this complex disease process. These proteins include neurofilaments, tau, 14-3-3 proteins, N-acetylaspartate and Nogo. Furthermore, these processes are not uniformly represented across patient populations but selectively predominate in individual patients, thus, contributing to the heterogeneity in phenotypic expression of the disease as well as its prognosis and response to therapies. However, there are limited biomarkers of multiple sclerosis in serum. CSF, which is more likely to reflect the disease, is obtainable by lumbar puncture only and is not suitable for general screening or monitoring therapy. As of May 2021, 287 clinical trials of biomarkers of multiple sclerosis are listed on ClinicalTrials.gov. A classification of biomarkers of multiple sclerosis is shown in Table 5.

Table 5. Classification of Biomarkers of Multiple Sclerosis

Brain imaging biomarkers of multiple sclerosis. MRI findings are important criteria for the diagnosis of multiple sclerosis, and MRI has been used as a surrogate biomarker in clinical trials of new therapies. Earlier studies of serial MRI scans show new inflammatory activity occurring at a rate 7- to 10-fold greater than the clinical events. Subsequent studies have convincingly demonstrated that the presence of active inflammation, as detected with Gd+ lesions, is associated with a higher likelihood of relapse activity. Numbers and volumes of Gd+ enhancing lesion are among the most robust MRI biomarkers of multiple sclerosis and short-term disability progression (57). However, there is still lack of validated biomarkers of long-term outcomes.

Although decrease in relapse rate or slowing of disability progression are now the primary outcome measures in phase III clinical trials, changes in lesion burden detected by MRI remain important secondary outcome measures. New therapies developed to slow neurodegeneration or promote remyelination in multiple sclerosis will require the use of advanced multimodal MRI techniques that capture structural as well as functional changes, and adoption of these biomarkers into multicenter trials will be technically challenging (53).

Although classically multiple sclerosis lesions are in the white matter of the CNS, pathological and imaging studies have shown that cortical demyelination is common and more extensive than considered previously (43). Three types of cortical lesion described in the cerebral and cerebellar cortices of multiple sclerosis patients are subpial, intracortical, and leukocortical lesions. Cortical demyelination may be the biomarker of progression of the disease with irreversible disability, seizures, and cognitive impairment. Therefore, grey matter damage, global as well as regional, has the potential to become a biomarker of disease activity, complementary to the currently used MRI biomarkers (global brain atrophy and T2 hyperintense lesions). Furthermore, it may improve the prediction of the future disease course and response to therapy in individual patients and may also become a reliable additional surrogate biomarker of treatment effect (21).

Neurofilaments are neuron-specific cytoskeletal proteins that can be released following axonal damage and levels of neurofilament light chain in CSF can predict disease activity as well as response to therapy in relapsing-remitting multiple sclerosis. As an alternative to the invasive lumbar puncture, neurofilament light chain has the potential as a serum biomarker for clinical use based on a follow-up study of patients with relapsing-remitting multiple sclerosis where high neurofilament light chain levels dropped following treatment with interferon beta-1a (59).

Biomarkers of stroke. A blood biomarker of stroke can be any quantifiable entity that reflects the manifestation of a stroke-related process such as cerebral ischemia. Most of the known biomarkers have little practical value in stroke. The most useful application of stroke biomarkers is in areas where information from traditional clinical sources is limited. Routine hematology and biochemical studies are used, but no special tests are usually done for biomarkers.

Biomarkers of risk factors for stroke. Elevated level of homocysteine, a sulfur-containing amino acid derived from metabolism of methionine, is a risk factor for stroke. Antiphospholipid antibodies are biomarkers of an increased risk of stroke, particularly in individuals younger than 50 years of age.

Biomarkers of acute stroke. It is important to identify rapidly and accurately the underlying pathological mechanism leading to ischemic stroke. Special diagnostic procedures include brain imaging with CT or MRI, vascular imaging with CT angiography, Doppler, or magnetic resonance angiography. Although 18F-based PET imaging probes of mitochondrial complex I activity were developed as specific biomarkers of the neuronal death caused by ischemia, MRI is a more reliable neuroimaging technique, as it enables better differentiation of the damaged regions at earlier stages of ischemic injury. A method for rapid detection and real-time monitoring of fluctuations of calcium ions associated with focal ischemia using a molecular functional MRI approach has been described in a transient middle cerebral artery occlusion animal model of ischemic stroke (49). A dinuclear paramagnetic gadolinium(III) complex chelate is used that changes MRI contrast through its reversible interaction with extracellular calcium ions. This method recognizes the onset and follows the dynamics of the ischemic core and penumbra with submillimeter spatial and second-scale temporal resolution, thus paving the way for noninvasive monitoring and development of targeted treatment strategies for cerebral ischemia.

Blood biomarkers of stroke. Use of rapidly measurable blood biomarkers to determine cause of stroke on admission would help to identify patients who need specific secondary preventive measures, such as oral anticoagulation, and, thus, facilitate optimal secondary prevention with improvement of patient outcome. There is a need for etiological biomarkers of acute ischemic stroke to improve the identification of patients who need faster initiation of specific treatments, ultimately leading to a better outcome. PubMed search through 2014 identified the role of 22 selected blood biomarkers in the context of stroke etiology, but most of these are still investigational (56). Further studies are needed before these biomarkers can be validated and introduced in clinical practice. As of May 2021, 519 clinical trials on stroke patients involving biomarkers are listed on ClinicalTrials.gov. The BIOmarker SIGNAture of Stroke AetioLogy Study (BIOSIGNAL), a multicenter international study funded by the Swiss National Science Foundation, which is specifically addressing the question of etiological biomarkers in acute stroke, has been completed, but the results have not been published (NCT02274727).

Proteomic biomarkers of stroke. Retinol-binding protein 4 and GFAP are useful as plasma biomarkers for rapid differentiation of ischemic stroke from intracerebral hemorrhage (29). This differential diagnosis is important for the management of the patient.

Blood levels of the chemokine CCL23 are raised in patients with acute ischemic stroke. It may be a promising biomarker for the early diagnosis of acute cerebral lesions and enable prediction of outcome of stroke patients (55).

MicroRNA biomarkers of stroke. MicroRNAs (miRNAs or miRs) are small non-coding RNA molecules that are endogenous regulators of gene expression. Findings of a clinical study suggest that miR‑150 polymorphisms may contribute to the development of ischemic stroke and may be biomarkers with potential to predict the risk of ischemic stroke (10).

Biomarker of intracranial aneurysm. Arterial wall enhancement on arterial wall MRI, detected more frequently in unruptured intracranial aneurysms, is a biomarker that indicates high risk of rupture along with conventional rupture-related characteristics, including aneurysmal size and location (30).

Biomarkers of traumatic brain injury. Although currently used methods have proven useful for stratifying the magnitude and extent of brain damage, they have limited usefulness for predicting adverse secondary events or detecting subtle brain damage. There is no definitive diagnostic test for traumatic brain injury to help physicians determine the seriousness of injury or the extent of cellular pathology. There is need for discovery and validation of better biomarkers for traumatic brain injury. Numerous biomarkers of traumatic brain injury are under investigation. As of May 2021, 189 clinical trials of biomarkers of traumatic brain injury are listed on ClinicalTrials.gov. Selected biomarkers are described here briefly.

C-tau as biomarker of traumatic brain injury. Tau proteins are microtubular binding proteins localized in the axonal compartment of neurons. Brain injury releases cleaved Tau proteins (C-tau) into the extracellular space where they are transported to the CSF. Tau protein in the CSF has been measured by a sandwich ELISA method. CSF C-tau levels are elevated in patients with traumatic brain injury. Furthermore, the elevation of CSF C-tau levels in a comatose head-injured patient with an unremarkable CT scan indicates that CSF C-tau levels are a more sensitive measure of axonal damage than CT. The correlation between the patient’s clinical condition and CSF C-tau levels suggests that CSF C-tau levels may be a good predictor of severity of head injury and possibly patient outcome after discharge. Animal experimental studies have shown that C-tau is a potential biomarker to evaluate the efficacy of neuroprotective drugs in traumatic brain injury.

Diffusion tensor imaging in traumatic brain injury. Traumatic axonal injury is a common mechanism of traumatic brain injury that is not readily identified using conventional neuroimaging. Diffusion tensor imaging can detect microstructural disruption in white matter of the brain. Diffusion tensor imaging-derived data can be analyzed using methods producing qualitatively comparable results, which are useful in clinical research and eventually in clinical practice (31). Diffusion tensor imaging measures of microstructural integrity appear robust for detecting white matter injury.

Digital biomarker of traumatic brain injury. Abbott Laboratories with Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) has developed Portable Dx TRACK TBI, a handheld portable device that detects real-time brain injuries missed on MRI scans.

Serum S100 beta as biomarker of traumatic brain injury. S100 beta is a 21 kDa c Ca2+-binding protein found mainly in the cytosol of astroglial cells. In the presence of astrocyte damage or necrosis, its concentration increases to micromolar or sub-micromolar due to the passive release of intracellular S100 beta, and its effects become neurotoxic, directly provoking neuronal apoptosis or indirectly stimulating the astrocytic release of nitric oxide. Furthermore, CSF and serum S100B levels have been correlated with outcome of traumatic brain injury. Serum S100 beta is a sensitive biomarker of brain injury and indicates severity of the injury. MRS is capable of measuring S100B protein. Commercial tests are available for measurement of S100 beta levels in serum. Although large extracranial injuries also elevate S100 beta levels, S100 beta has a high negative predictive power, and the finding of a normal S100 beta value shortly after trauma can exclude significant brain injury with a high accuracy. Of all the reported biomarkers, only S100 beta has consistently demonstrated the ability to predict outcome in adults with severe traumatic brain injury. S100 beta protein is a promising biomarker for the diagnosis, monitoring, and prognosis of traumatic brain injury (13).

Exosomes as biomarkers of traumatic brain injury. Neuronal exosomes purified from peripheral blood samples and quantified using standard ELISA methods are a potential diagnostic tool in the setting of traumatic brain injury. Synaptopodin (SYNPO), an actin-associated protein present in postsynaptic spines, was evaluated as a potential biomarker of acute brain injury as well as synaptophysin, neuron-specific enolase, and mitochondrial cytochrome c oxidase (19). The results showed that neural exosomes turn over rapidly enough in the peripheral circulation to be used as a test following acute brain injury; slope of change in SYNPO between 8 and 14 hours appeared to be the most promising biomarker.

Biomarkers of concussion. No routine tests are currently available for objective diagnosis of mild traumatic brain injury or concussion. Previously reported biomarkers for mild traumatic brain injury represented proteins released from the damaged neurons or glia. However, the low levels of these proteins or the complexity of assays used for their detection limits the implementation of these biomarkers in routine practice. A study on patients sustaining a concussion within the preceding 24 hours has identified 4 candidate biomarkers: copeptin, galectin 3, matrix metalloproteinase 9 (MMP9), and occludin (51). Alterations in the blood levels of this panel of 4 biomarkers discerns with high accuracy patients with isolated concussion from uninjured individuals or those with orthopedic injury within the first 8 hours after accident. High levels of MMP9 degrade the tight junction proteins at the blood-brain barrier and allow undesirable substances to access the brain, which may increase neuroinflammation that could be reduced with a treatment that blocks MMP9. Results of a study on collegiate athletes showed that elevated plasma tau concentration within 6 hours following a sports-related concussion was related to prolonged return to play, suggesting the usefulness of tau levels as a biomarker for making the decision about a return to play (18).

SNTF as a biomarker for predicting cognitive decline after mild traumatic brain injury (mTBI). Although mild traumatic brain injury is not typically associated with abnormalities on CT, it can often cause persistent cognitive dysfunction. Therefore, new prognostic biomarkers are needed for mild traumatic brain injury to identify patients at risk of cognitive decline at an early and potentially treatable stage. A study has quantified plasma levels of the neurodegeneration biomarker calpain-cleaved alphaII-spectrin N-terminal fragment (SNTF) from CT-negative mild traumatic brain injury subjects as well as normal uninjured controls, these levels were compared with findings from diffusion tensor imaging and long-term cognitive assessment (54). The blood biomarker test on the day of the mild traumatic brain injury showed 100% sensitivity for predicting persisting cognitive problems and 75% specificity for correctly ruling out functionally harmful concussions. If validated in larger studies, SNTF could be a diagnostic biomarker of mild traumatic brain injury. It could be a prognostic biomarker for the assessment as well as for a decision to return athletes to sports or soldiers to active military duty following mild traumatic brain injury.

In a study of trauma patients with normal mental status, GFAP outperformed UCH-L1 in detecting concussion in both children and adults (40). Blood levels of GFAP and UCH-L1 showed incremental elevations across 3 injury groups, but UCH-L1 was expressed at much higher levels than GFAP in those with nonconcussive trauma, particularly in children, suggesting that UCH-L1 is either not completely brain specific or a manifestation of subconcussive brain injury. A multicenter, prospective, case-control study on sport-related concussion has shown that athletes with concussion and loss of consciousness or posttraumatic amnesia had significantly higher levels of GFAP than athletes with concussion with no loss of consciousness or posttraumatic amnesia (33).

Circulating microRNAs, especially those encapsulated in extracellular vesicles, have been identified as biomarkers of blast-related mTBI, a "signature" injury in veterans of Iraq and Afghanistan wars (17). These microRNAs were mostly associated with pathways involved in neuronal function, vascular remodeling, blood-brain barrier integrity, and neuroinflammation, providing insights into molecular processes associated with the long-term health outcomes associated with blast-related chronic mTBI.

A serum biomarker test for predicting presence or absence of brain lesions on imaging. In 2018, the FDA approved Banyan’s Brain Trauma Indicator, a blood test measuring levels of UCH-L1 (ubiquitin C-terminal hydrolase-L1) and GFAP (glial fibrillary acidic protein), which are released by the brain into the blood circulation following mild traumatic brain injury/concussion in adults. Efficacy was evaluated in a clinical trial (NCT01426919) by comparing blood test results with CT scans in patients within 12 hours following mild traumatic brain injury, which demonstrated that the biomarker was able to predict the presence of lesions on a scan in 97.5% of cases and their absence from scans 99.6% of the time (02). Results of the test can be available in within 3 to 4 hours. This biomarker-based test is expected to reduce the number of patients undergoing unnecessary CT scans, thereby reducing hospital costs and patient radiation exposure.

Chronic traumatic encephalopathy. Changes in the expression profile of biomarkers such as microRNAs in peripheral blood mononuclear cells may reflect molecular alterations following traumatic brain injury that contribute to the onset and progression of traumatic brain injury to chronic traumatic encephalopathy. A postmortem study has found that CCL11, a chemokine previously associated with cognitive decline of aging, is increased in the dorsolateral frontal cortex and CSF of deceased American football players with neuropathologically verified chronic traumatic encephalopathy (09). This increase was also seen to correlate with years of exposure to American football independent of age. CSF CCL11 accurately distinguishes chronic traumatic encephalopathy from Alzheimer disease and should be studied further as an in vivo biomarker of chronic traumatic encephalopathy.

Concluding remarks on biomarkers of traumatic brain injury. Biomarkers are useful as diagnostic, prognostic, and monitoring adjuncts for traumatic brain injury, particularly in the neurointensive care facilities. Biomarkers can help in stratifying patients according to severity level of injury, predicting adverse secondary events or outcomes, and monitoring the effectiveness of therapeutic interventions. As a biomarker source, serum offers several advantages over CSF, including ease of accessibility and reduced risk to the patient. Systems biology approach has been used in a rodent model of concussive injury to understand the impact of traumatic brain injury on gene regulation in the brain (34). Results of this study show that concussive brain injury reprograms genes, which could lead to predisposition to neurologic and psychiatric disorders, and that genomic patterns from peripheral leukocytes has the potential as biomarkers to predict pathogenesis of traumatic brain injury. There is need for discovery of new biomarkers of traumatic brain injury and further clinical studies for validation of known biomarkers. The value of these biomarkers as potential targets for development of neuroprotective therapies should also be explored.

Biomarkers of epilepsy. With so many different types of seizures and causes of epilepsy, there are no universal biomarkers except EEG measurements. Some biomarkers detect diseases that manifest in seizures. There are no characteristic biomarkers of idiopathic epilepsy except those for monitoring seizures and response to treatment. There is a need for diagnostic biomarkers of epilepsy and status epilepticus to support clinical examination, EEG, and neuroimaging. The use of biomarkers is a possible solution to problems of epilepsy prevention trials, which are more complex, lengthy, and costlier than standard epilepsy treatment trials. Development of reliable epilepsy biomarkers would be a major advance in management of epilepsy. As of May 2021, 92 studies relevant to epilepsy and biomarkers are listed on ClinicalTrials.gov. A review of 30 epilepsy biomarker studies covers prognostic biomarkers for the development of epilepsy in subjects with brain insults, predictive biomarkers for outcome of epilepsy surgery, and biomarkers of response to therapy, but the need for epilepsy biomarker discovery using proper, statistically powered study designs and analytical methods still remains (42).

A classification of biomarkers of epilepsy is shown in Table 6.

Table 6. Classification of Biomarkers of Epilepsy

Biochemical markers of epilepsy. Elevated serum prolactin, measured in the appropriate clinical setting at 10 to 20 minutes after a suspected event, is a useful adjunct for the differentiation of generalized tonic-clonic or complex partial seizure from psychogenic nonepileptic seizure among adults and older children. Serum prolactin assay does not distinguish epileptic seizures from syncope and its use has not been established in the evaluation of status epilepticus, repetitive seizures, and neonatal seizures.

Biomarkers of temporal lobe epilepsy. Results of a clinical study suggest that serum biomarkers are predictive of higher frequencies of seizures in temporal lobe epilepsy (08). For example, HSP70 levels showed an inverse correlation with hippocampal volume after controlling for the effect of age. HSP70 may be a stress biomarker in patients with temporal lobe epilepsy in that it correlates inversely with memory scores and hippocampal volume.

Biomarkers of drug-resistant epilepsy. Approximately 30% of epilepsy patients do not respond to antiepileptic drugs, and neuroinflammation plays a pathogenic role in drug-resistant epilepsy. The high-mobility group box 1/TLR4 axis is a key initiator of neuroinflammation following epileptogenic injuries and its activation contributes to seizure generation in animal models (62). The authors also observed early expression of disulfide high-mobility group box 1 in patients with newly diagnosed epilepsy and its persistence was associated with subsequent seizures. Moreover, treatment of animals with antiinflammatory drugs during epileptogenesis prevented both disease progression and blood increase in high-mobility group box 1 isoforms. Experimental data suggest that high-mobility group box 1 isoforms are biomarkers of epileptogenesis and drug-resistant epilepsy in humans. They need evaluation in larger-scale prospective clinical studies.

Imaging biomarkers of epilepsy. Quantitative measurements by MRI of overall brain volume (gray matter, white matter, and CSF) in temporal lobe epilepsy are clinically meaningful biomarkers that are associated with increased cognitive morbidity. New magnetic resonance-based techniques, such as MR spectroscopy, fMRI, and fMRI/EEG, are more frequently being used to increase the yield of MRI in detecting abnormalities associated with epilepsy.

Genetic epilepsies. Considerable progress has been made in the discovery of genes that influence risk for epilepsy. Genotyping may identify individuals with genetic epilepsies. However, these gene discoveries have been in epilepsies with Mendelian modes of inheritance, which comprise only a tiny fraction of all epilepsy. Most people with epilepsy have no affected relatives, suggesting that most of all epilepsies are genetically complex, ie, multiple genes contribute to their etiology, none of which has a major effect on disease risk.

RNA biomarkers of epilepsy. Extracellular microRNAs are potentially ideal biomarkers for neurologic disorders as some of them are uniquely expressed in specific brain regions. Measurement of these biomarkers in CSF has the advantage of a biofluid in close contact with the target tissue and sites of pathology. A study of differential expression of 20 microRNAs in CSF of epilepsy patient groups and controls with validation phase including samples from patients with other neurologic diseases identified lower levels of miR-19b in temporal lobe epilepsy compared to controls, status epilepticus, and other neurologic diseases (45). Levels of miR-451a were higher in status epilepticus compared to other groups whereas miR-21-5p differed in status epilepticus compared to temporal lobe epilepsy but not to other neurologic diseases. Thus, CSF examination for microRNAs can be useful in differential diagnosis of temporal lobe epilepsy and status epilepticus from other neurologic and nonneurologic diseases. miR-134 is elevated in brain tissue after experimental status epilepticus and in human epilepsy cells and its detection in biofluids may serve as a unique biomarker. TORNADO device is capable of accurately quantifying microRNA-134 in plasma from patients with focal epilepsy using an electrochemical quantification approach (46).

Transfer RNAs are a major class of noncoding RNA. Stress-induced cleavage of transfer RNA is highly conserved and results in transfer RNA fragments. Transfer RNA fragments share many features with microRNAs that make them both ideal molecules for use as biomarkers. Small RNA-Seq of plasma samples collected during video EEG monitoring of patients with focal epilepsy identified significant differences in 3 transfer RNA fragments (5′GlyGCC, 5′AlaTGC, and 5′GluCTC) compared with samples from healthy controls (20). The levels of these transfer RNA fragments were higher in preseizure than in postseizure samples, suggesting that they may serve as biomarkers of seizure risk in patients with epilepsy. In vitro studies confirmed that production and extracellular release of transfer RNA fragments were lower after epileptiform-like activity in hippocampal neurons. The authors designed PCR-based assays to quantify transfer RNA fragments in a cohort of pre- and post-seizure plasma samples from patients with focal epilepsy and from healthy controls. Receiver operating characteristic analysis indicated that transfer RNA fragments potently distinguished pre- from post-seizure patients. Elevated levels of transfer RNA fragments were not detected in patients with psychogenic nonepileptic seizures and did not result from medication tapering. This study potentially identifies a new class of epilepsy biomarker and reveals the possible existence of prodromal molecular patterns in blood that could be used to predict seizure risk.

For a biomarker to indicate that onset of seizure is imminent in a patient would require a portable quantification device such as TORNADO, which can rapidly assess transfer RNA fragment levels in whole blood. This might complement other wearable technologies such as seizure detection watches (07). Transfer RNA fragments are quantifiable using standard laboratory-based PCR techniques and may be more specific than microRNAs as biomarkers of epilepsy.

Biomarker of chronic migraine. In a case-controlled study, patients with chronic migraine showed increased iron deposition in red nucleus and periaqueductal gray matter compared to patients with episodic migraine and headache-free controls (12). Iron volume in periaqueductal gray matter, measured with 3T MRI and the NIH software platform ImageJ, correctly identified patients with chronic migraine and was associated with elevated biomarkers of endothelial dysfunction and blood-brain barrier disruption.

Biomarkers of amyotrophic lateral sclerosis (ALS). Although inheritance plays a role in amyotrophic lateral sclerosis, most patients do not have a known genetic biomarker to enable sequence-based genetic testing. Detection of biofluid-based epigenetic changes in amyotrophic lateral sclerosis would enable use of genomic information for disease diagnosis. A commercially available technique, EpiSwitch™ (Oxford Biodynamics), has been used to compare the genomic architecture of healthy and diseased patient samples (blood and tissue) to discover a chromosomal conformation signature (CCS) with diagnostic potential in amyotrophic lateral sclerosis (48). A 3-step biomarker selection process yielded a distinct CCS for amyotrophic lateral sclerosis detectable in blood, comprised of conformation changes in 8 genomic loci. Sensitivity validated in this study was 87.5% and specificity 75.0%, indicating that detection of CCS is a promising approach that can augment current strategies for diagnosing amyotrophic lateral sclerosis.

Deficiencies and excess of essential elements and toxic metals are among the many factors implicated in the etiology of amyotrophic lateral sclerosis. A study with laser to map growth rings that form daily in teeth, which are capture signatures of the environment such as the metabolism of essential elements and toxic metals, provides direct evidence that altered metal uptake during specific early life is associated with adult-onset amyotrophic lateral sclerosis (14).

Biomarkers of myalgic encephalomyelitis/chronic fatigue syndrome. Chronic fatigue syndrome has been defined as clinically evaluated, unexplained, persistent, or relapsing chronic fatigue that is of new or definite onset, is not the result of ongoing exertion, is not substantially alleviated by rest, and results in substantial reduction in previous levels of occupational, educational, social, or personal activities. It is labeled as “myalgic encephalomyelitis,” indicating an underlying pathophysiology. Raised level of plasma alpha-melanocyte-stimulating hormone, caused partly by chronic stress, is a biomarker of this condition.

A metabolic study of biochemical pathways on plasma from patients with chronic fatigue syndrome showed abnormalities in 20 metabolic pathways with 80% decrease (as compared to normal controls) in diagnostic metabolites, which is consistent with a hypometabolic syndrome (38). A criticism of this study is that metabolic differences between patients with chronic fatigue syndrome and healthy controls do not automatically yield a diagnostic test (60).

Role of biomarkers in development of personalized neurology. Biomarkers play an important role in personalized medicine that also applies to personalized neurology. The important points of this role are:

Examples of the usefulness of biomarkers in development of personalized medicine are as follows:

Biomarkers for Huntington disease. Genome-wide gene expression profiles from blood samples of patients with Huntington disease have identified changes in blood mRNAs that clearly distinguish patients with Huntington disease from controls. The elevated mRNAs are significantly reduced in patients with Huntington disease who are involved in a dose-finding study of the histone deacetylase inhibitor sodium phenylbutyrate. These alterations in mRNA expression correlate with disease progression and response to experimental treatment. Such biomarkers may provide clues to the state of Huntington disease and may be of predictive value in clinical trials.

Biomarker of major depressive disorder. Studies on patients with major depressive disorder have shown that levels of endogenously produced acetyl-l-carnitine are markedly reduced as compared to age- as well as sex-matched healthy controls, particularly in patients with poor response to antidepressants (36). These findings indicate that acetyl-l-carnitine could serve as a candidate biomarker to help diagnose a subtype of major depressive disorder, which could be targeted for personalized therapy.

Biomarkers for personalized management of pain. Pain as a subjective symptom is by itself a biomarker of many diseases but there is lack of validated biomarkers of chronic pain syndromes, particularly in psychiatric patients, which is a high-risk group for comorbid pain disorders and increased perception of pain. A blood test has been developed for measuring gene expression biomarkers in psychiatric patients that are predictive of pain state and of future emergency department visits for pain, particularly when personalized by gender and diagnosis (39). One of these, MFAP3, has the most robust empirical evidence from our discovery and validation steps and is a strong predictor for pain in the independent cohorts, particularly in females and males with posttraumatic stress disorder. Other biomarkers with best overall convergent functional evidence for involvement in pain are GNG7, CNTN1, LY9, CCDC144B, and GBP1. Some of the biomarkers have been identified as targets of existing drugs.