Biomarkers For Neurological Disorders Research Articles

The GFAP proteoform puzzle: How to advance GFAP as a fluid biomarker in neurological diseases.

Glial fibrillary acidic protein (GFAP) is a well-established biomarker of reactive astrogliosis in the central nervous system because of its elevated levels following brain injury and various neurological disorders. The advent of ultra-sensitive methods for measuring low-abundant proteins has significantly enhanced our understanding of GFAP levels in the serum or plasma of patients with diverse neurological diseases. Clinical studies have demonstrated that GFAP holds promise both as a diagnostic and prognostic biomarker, including but not limited to individuals with Alzheimer's disease. GFAP exhibits diverse forms and structures, herein referred to as its proteoform complexity, encompassing conformational dynamics, isoforms and post-translational modifications (PTMs). In this review, we explore how the proteoform complexity of GFAP influences its detection, which may affect the differential diagnostic performance of GFAP in different biological fluids and can provide valuable insights into underlying biological processes. Additionally, proteoforms are often disease-specific, and our review provides suggestions and highlights areas to focus on for the development of new assays for measuring GFAP, including isoforms, PTMs, discharge mechanisms, breakdown products, higher-order species and interacting partners. By addressing the knowledge gaps highlighted in this review, we aim to support the clinical translation and interpretation of GFAP in both CSF and blood and the development of reliable, reproducible and specific prognostic and diagnostic tests. To enhance disease pathology comprehension and optimise GFAP as a biomarker, a thorough understanding of detected proteoforms in biofluids is essential.

Neurofilaments as biomarkers in neurological disorders - towards clinical application.

Neurofilament proteins have been validated as specific body fluid biomarkers of neuro-axonal injury. The advent of highly sensitive analytical platforms that enable reliable quantification of neurofilaments in blood samples and simplify longitudinal follow-up has paved the way for the development of neurofilaments as a biomarker in clinical practice. Potential applications include assessment of disease activity, monitoring of treatment responses, and determining prognosis in many acute and chronic neurological disorders as well as their use as an outcome measure in trials of novel therapies. Progress has now moved the measurement of neurofilaments to the doorstep of routine clinical practice for the evaluation of individuals. In this Review, we first outline current knowledge on the structure and function of neurofilaments. We then discuss analytical and statistical approaches and challenges in determining neurofilament levels in different clinical contexts and assess the implications of neurofilament light chain (NfL) levels in normal ageing and the confounding factors that need to be considered when interpreting NfL measures. In addition, we summarize the current value and potential clinical applications of neurofilaments as a biomarker of neuro-axonal damage in a range of neurological disorders, including multiple sclerosis, Alzheimer disease, frontotemporal dementia, amyotrophic lateral sclerosis, stroke and cerebrovascular disease, traumatic brain injury, and Parkinson disease. We also consider the steps needed to complete the translation of neurofilaments from the laboratory to the management of neurological diseases in clinical practice.

Platelet Dynamics in Neurodegenerative Disorders: Investigating the Role of Platelets in Neurological Pathology.

Background: Neurological disorders, particularly those associated with aging, pose significant challenges in early diagnosis and treatment. The identification of specific biomarkers, such as platelets (PLTs), has emerged as a promising strategy for early detection and intervention in neurological health. This systematic review aims to explore the intricate relationship between PLT dynamics and neurological health, focusing on their potential role in cognitive functions and the pathogenesis of cognitive disorders. Methods: Adhering to PRISMA guidelines, a comprehensive search strategy was employed in the PubMed and Scholar databases to identify studies on the role of PLTs in neurological disorders published from 2013 to 2023. The search criteria included studies focusing on PLTs as biomarkers in neurological disorders, their dynamics, and their potential in monitoring disease progression and therapy effectiveness. Results: The systematic review included 104 studies, revealing PLTs as crucial biomarkers in neurocognitive disorders, acting as inflammatory mediators. The findings suggest that PLTs share common features with altered neurons, which could be utilised for monitoring disease progression and evaluating the effectiveness of treatments. PLTs are identified as significant biomarkers for detecting neurological disorders in their early stages and understanding the pathological events leading to neuronal death. Conclusions: The systematic review underscores the critical role of PLTs in neurological disorders, highlighting their potential as biomarkers for the early detection and monitoring of disease progression. However, it also emphasises the need for further research to solidify the use of PLTs in neurological disorders, aiming to enhance early diagnosis and intervention strategies.

Biomarkers of Neurological Diseases: A Comprehensive Review of Literature

Biomarkers of Neurological Diseases: A Comprehensive Review of Literature

Nesfatin-1: A Biomarker and Potential Therapeutic Target in Neurological Disorders.

Nesfatin-1 is a novel adipocytokine consisting of 82 amino acids with anorexic and anti-hyperglycemic properties. Further studies of nesfatin-1 have shown it to be closely associated with neurological disorders. Changes in nesfatin-1 levels are closely linked to the onset, progression and severity of neurological disorders. Nesfatin-1 may affect the development of neurological disorders and can indicate disease evolution and prognosis, thus informing the choice of treatment options. In addition, regulation of the expression or level of nesfatin-1 can improve the level of neuroinflammation, apoptosis, oxidative damage and other indicators. It is demonstrated that nesfatin-1 is involved in neuroprotection and may be a therapeutic target for neurological disorders. In this paper, we will also discuss the role of nesfatin-1 as a biomarker in neurological diseases and its potential mechanism of action in neurological diseases, providing new ideas for the diagnosis and treatment of neurological diseases.

Number of kinesins engaged in axonal cargo transport: A novel biomarker for neurological disorders

Kinesin motor proteins play crucial roles in anterograde transport of cargo vesicles in neurons, moving them along axons from the cell body towards the synaptic region. Not only the transport force and velocity of single motor protein, but also the number of kinesin molecules involved in transporting a specific cargo, is pivotal for synapse formation. This collective transport by multiple kinesins ensures stable and efficient cargo transport in neurons. Abnormal increases or decreases in the number of engaged kinesin molecules per cargo could potentially act as biomarkers for neurodegenerative diseases such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis (ALS), spastic paraplegia, polydactyly syndrome, and virus transport disorders. We review here a model constructed using physical measurements to quantify the number of kinesin molecules associated with their cargo, which could shed light on the molecular mechanisms of neurodegenerative diseases related to axonal transport.

Magnetic transferrin nanoparticles (MTNs) assay as a novel isolation approach for exosomal biomarkers in neurological diseases

BackgroundBrain-derived exosomes released into the blood are considered a liquid biopsy to investigate the pathophysiological state, reflecting the aberrant heterogeneous pathways of pathological progression of the brain in neurological diseases. Brain-derived blood exosomes provide promising prospects for the diagnosis of neurological diseases, with exciting possibilities for the early and sensitive diagnosis of such diseases. However, the capability of traditional exosome isolation assays to specifically isolate blood exosomes and to characterize the brain-derived blood exosomal proteins by high-throughput proteomics for clinical specimens from patients with neurological diseases cannot be assured. We report a magnetic transferrin nanoparticles (MTNs) assay, which combined transferrin and magnetic nanoparticles to isolate brain-derived blood exosomes from clinical samples.MethodsThe principle of the MTNs assay is a ligand-receptor interaction through transferrin on MTNs and transferrin receptor on exosomes, and electrostatic interaction via positively charged MTNs and negatively charged exosomes to isolate brain-derived blood exosomes. In addition, the MTNs assay is simple and rapid (< 35 min) and does not require any large instrument. We confirmed that the MTNs assay accurately and efficiently isolated exosomes from serum samples of humans with neurodegenerative diseases, such as dementia, Parkinson's disease (PD), and multiple sclerosis (MS). Moreover, we isolated exosomes from serum samples of 30 patients with three distinct neurodegenerative diseases and performed unbiased proteomic analysis to explore the pilot value of brain-derived blood protein profiles as biomarkers.ResultsUsing comparative statistical analysis, we found 21 candidate protein biomarkers that were significantly different among three groups of neurodegenerative diseases.ConclusionThe MTNs assay is a convenient approach for the specific and affordable isolation of extracellular vesicles from body fluids for minimally-invasive diagnosis of neurological diseases.

TRNA fragment biomarkers of Neurological Disease: Challenges and Opportunities

Transfer RNAs play a crucial role in protein translation where they bring amino acids to the ribosome to be incorporated into nascent polypeptide chains. During stress conditions tRNAs can be cleaved to generate tRNA-derived fragments. Several ribonucleases have been identified that cleave tRNA, however mutations in the stress-induced ribonuclease Angiogenin have been identified in a range of neurological disorders including Amyotrophic Lateral Sclerosis, Parkinson’s Disease, and Alzheimer’s Disease, suggesting that tRNA cleavage may be dysregulated in neurological disease. tRNA fragments have been detected in biofluids indicating they may be of use as biomarkers for neurological diseases. There is considerable variability in the methods used to quantify tRFs from size selection, adapter ligation, removal of RNA modifications, and sequence analysis approaches which can make it difficult to reconcile multiple studies. Here we review the biology of transfer RNAs and the biogenesis of tRNA-derived fragments, with a focus on the methods used to identify and quantify tRNA fragments and how different methodological approaches can influence tRNA fragment detection. We provide an overview of current literature on the identification of tRNA fragments in neurological disease models and patient samples, with a focus on circulating tRNA fragments as potential biomarkers of neurological diseases.

XCL1, a serum biomarker in neurological diseases; HTLV-1-associated myelopathy and multiple sclerosis.

The XCL1-XCR1 axis has a potential role in the recruitment of immune cells to the site of inflammation. The present study aimed to examine the relation of XCL1 serum levels with Multiple sclerosis (MS) and HTLV-1-associated myelopathy (HAM), as chronic inflammatory diseases of the central nervous system (CNS). DNA was extracted to evaluate HTLV-1 proviral load (PVL) using real-time PCR. Serum levels of XCL1 was determined by using an ELISA assay. The serum level of XCL1 was significantly higher in patients with HAM than that of asymptomatic carriers (ACs) and healthy controls (HCs) (p<0.001 and p<0.0001, respectively) and was also higher in MS patients compared to HCs (p<0.0001). Moreover, the concentration of XCL1 serum level was significantly different between the ACs and HCs group (p<0.0001). In conclusion, increased expression of XCL1 might contribute to the migration of autoreactive T cells to the central nervous system and play a critical role in the development and pathogenesis of inflammatory neurological diseases including HAM and MS.

MRI data quality assessment for the RIN - Neuroimaging Network using the ACR phantoms

PurposeGenerating big-data is becoming imperative with the advent of machine learning. RIN-Neuroimaging Network addresses this need by developing harmonized protocols for multisite studies to identify quantitative MRI (qMRI) biomarkers for neurological diseases. In this context, image quality control (QC) is essential. Here, we present methods and results of how the RIN performs intra- and inter-site reproducibility of geometrical and image contrast parameters, demonstrating the relevance of such QC practice. MethodsAmerican College of Radiology (ACR) large and small phantoms were selected. Eighteen sites were equipped with a 3T scanner that differed by vendor, hardware/software versions, and receiver coils. The standard ACR protocol was optimized (in-plane voxel, post-processing filters, receiver bandwidth) and repeated monthly. Uniformity, ghosting, geometric accuracy, ellipse’s ratio, slice thickness, and high-contrast detectability tests were performed using an automatic QC script. ResultsMeasures were mostly within the ACR tolerance ranges for both T1- and T2-weighted acquisitions, for all scanners, regardless of vendor, coil, and signal transmission chain type. All measurements showed good reproducibility over time. Uniformity and slice thickness failed at some sites. Scanners that upgraded the signal transmission chain showed a decrease in geometric distortion along the slice encoding direction. Inter-vendor differences were observed in uniformity and geometric measurements along the slice encoding direction (i.e. ellipse’s ratio). ConclusionsUse of the ACR phantoms highlighted issues that triggered interventions to correct performance at some sites and to improve the longitudinal stability of the scanners. This is relevant for establishing precision levels for future multisite studies of qMRI biomarkers.

Experimental and Clinical Biomarkers for Progressive Evaluation of Neuropathology and Therapeutic Interventions for Acute and Chronic Neurological Disorders.

This article describes commonly used experimental and clinical biomarkers of neuronal injury and neurodegeneration for the evaluation of neuropathology and monitoring of therapeutic interventions. Biomarkers are vital for diagnostics of brain disease and therapeutic monitoring. A biomarker can be objectively measured and evaluated as a proxy indicator for the pathophysiological process or response to therapeutic interventions. There are complex hurdles in understanding the molecular pathophysiology of neurological disorders and the ability to diagnose them at initial stages. Novel biomarkers for neurological diseases may surpass these issues, especially for early identification of disease risk. Validated biomarkers can measure the severity and progression of both acute neuronal injury and chronic neurological diseases such as epilepsy, migraine, Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, traumatic brain injury, amyotrophic lateral sclerosis, multiple sclerosis, and other brain diseases. Biomarkers are deployed to study progression and response to treatment, including noninvasive imaging tools for both acute and chronic brain conditions. Neuronal biomarkers are classified into four core subtypes: blood-based, immunohistochemical-based, neuroimaging-based, and electrophysiological biomarkers. Neuronal conditions have progressive stages, such as acute injury, inflammation, neurodegeneration, and neurogenesis, which can serve as indices of pathological status. Biomarkers are critical for the targeted identification of specific molecules, cells, tissues, or proteins that dramatically alter throughout the progression of brain conditions. There has been tremendous progress with biomarkers in acute conditions and chronic diseases affecting the central nervous system.

N-terminal and mid-region tau fragments as fluid biomarkers in neurological diseases

Brain-derived tau secreted into CSF and blood consists of different N-terminal and mid-domain fragments, which may have a differential temporal course and thus, biomarker potential across the Alzheimer’s disease continuum or in other neurological diseases. While current clinically validated total tau assays target mid-domain epitopes, comparison of these assays with new biomarkers targeting N-terminal epitopes using the same analytical platform may be important to increase the understanding of tau pathophysiology.We developed three total tau immunoassays targeting specific N-terminal (NTA and NTB total tau) or mid-region (MR total tau) epitopes, using single molecule array technology. After analytical validation, the diagnostic performance of these biomarkers was evaluated in CSF and compared with the Innotest total tau (and as proof of concept, with N-p-tau181 and N-p-tau217) in three clinical cohorts (n = 342 total). The cohorts included participants across the Alzheimer’s disease continuum (n = 276), other dementias (n = 22), Creutzfeldt–Jakob disease (n = 24), acute neurological disorders (n = 18) and progressive supranuclear palsy (n = 22). Furthermore, we evaluated all three new total tau biomarkers in plasma (n = 44) and replicated promising findings with NTA total tau in another clinical cohort (n = 50).In CSF, all total tau biomarkers were increased in Alzheimer’s disease compared with controls (P < 0.0001) and correlated with each other (rs = 0.53−0.95). NTA and NTB total tau, but not other total tau assays, distinguished amyloid-positive and amyloid-negative mild cognitive impairment with high accuracies (AUCs 84% and 82%, P < 0.001) matching N-p-tau217 (AUC 83%; DeLong test P = 0.93 and 0.88). All total tau assays were excellent in differentiating Alzheimer’s disease from other dementias (P < 0.001, AUCs 89–100%). In Creutzfeldt–Jakob disease and acute neurological disorders, N-terminal total tau biomarkers had significantly higher fold changes versus controls in CSF (45–133-fold increase) than Innotest or MR total tau (11–42-fold increase, P < 0.0001 for all). In progressive supranuclear palsy, CSF concentrations of all total tau biomarkers were similar to those in controls. Plasma NTA total tau concentrations were increased in Alzheimer’s disease compared with controls in two independent cohorts (P = 0.0056 and 0.0033), while Quanterix total tau performed poorly (P = 0.55 and 0.44).Taken together, N-terminal-directed CSF total tau biomarkers increase ahead of standard total tau alternatives in the Alzheimer’s disease continuum, increase to higher degrees in Creutzfeldt–Jakob disease and acute neurological diseases and show better potential than Quanterix total tau as Alzheimer’s disease blood biomarkers. For progressive supranuclear palsy, other tau biomarkers should continue to be investigated.

Single Extracellular Vesicle Analysis Using Flow Cytometry for Neurological Disorder Biomarkers

Extracellular vesicles (EVs) are membrane vesicles released from cells to the extracellular space, involved in cell-to-cell communication by the horizontal transfer of biomolecules such as proteins and RNA. Because EVs can cross the blood-brain barrier (BBB), circulating through the bloodstream and reflecting the cell of origin in terms of disease prognosis and severity, the contents of plasma EVs provide non-invasive biomarkers for neurological disorders. However, neuronal EV markers in blood plasma remain unclear. EVs are very heterogeneous in size and contents, thus bulk analyses of heterogeneous plasma EVs using Western blot and ELISA have limited utility. In this study, using flow cytometry to analyze individual neuronal EVs, we show that our plasma EVs isolated by size exclusion chromatography are mainly CD63-positive exosomes of endosomal origin. As a neuronal EV marker, neural cell adhesion molecule (NCAM) is highly enriched in EVs released from induced pluripotent stem cells (iPSCs)-derived cortical neurons and brain organoids. We identified the subpopulations of plasma EVs that contain NCAM using flow cytometry-based individual EV analysis. Our results suggest that plasma NCAM-positive neuronal EVs can be used to discover biomarkers for neurological disorders.

Biochemical and Genetic Markers in Neurological Trauma and Tumors: Review Article

CNS traumas and tumors are major health problems. They lead to serious health and economic burdens. They are major causes of disability, or death all over the world. Nowadays, the order of causes of trauma-related death has beenchanged from multiorgan affection to CNS trauma. Assessment of severity and predicting the outcome in a patient with a head, or spinal cord injury, is a must. Most of severity assessment scales depend on the clinical data of the patient. Using of biochemical, and genetic markers that have correlations with severity and outcome in CNS trauma is necessary ofand helpful in clinical field. Ubiquitin C-terminal hydrolase-L1 is an enzyme that is present in the cytoplasm of neurons, and forms about to 1–2% from the proteins found within the human brain, and it is supposed to be a promising biomarker in neurological diseases especially trauma. Neuroglobin (Ngb), is a protein which is distributed mainly in central and peripheral nervous systems, and it has neuroprotective effects against oxidative stress. It is an important biomarker in neurological trauma and tumors.CNS tumors have psychological burden beside their health and economic effects as they may affect personality and both physical and cognitive independence. Various types of mutations have a role in pathogenesis of CNS tumors. Isocitrate dehydrogenase enzyme isoform 1 (IDH1) mutations are frequently identified in primary CNS tumors. Aim of this review: is to give an overview about neurological trauma and tumors as being major health problems, and to spot light on biochemical and genetic markers of promising role as regard pathogenesis, diagnosis, or prognosis of such disorders, with more details about UCHL-1, Ngb, and IDH1.

Combined multivariate pattern analysis with frequency-dependent intrinsic brain activity to identify essential tremor

Essential tremor (ET) is the most common tremor disorder, and the intrinsic brain activity changes and diagnostic biomarkers of ET remain unclear. Combined multivariate pattern analysis (MVPA) with resting-state functional MRI (Rs-fMRI) data provides the most promising way to identify individual subjects, reveal brain activity changes, and further establish diagnostic biomarkers in neurological diseases. Using voxel-level amplitude of low-frequency fluctuations (ALFF) and local (regional homogeneity, ReHo) and global (degree centrality, DC) brain connectivity mappings based on three frequency bands (classical band: 0.01–0.10 Hz; slow-5: 0.01–0.023 Hz; slow-4: 0.023–0.073 Hz) of 162 ET patients and 153 well-matched healthy controls (HCs) as input features, MVPA (binary support vector machine, SVM) was performed to differentiate ET from HCs. Each modality achieved good classification performance, except for ReHo based on the slow-4 band with a sensitivity, specificity and total accuracy of 58.64%, 65.36%, 61.90%, respectively (P < 0.05). The classification performance with slow-4 bands was poorer than that with slow-5 and classical bands, but slow-4 bands could be used to reveal the spatial distribution changes in subcortical structures, especially the thalamus. The significant discriminative features were mostly located in the cerebello-thalamo-cortical pathway, and partial correlation analyses showed that significant discriminative features in the cerebello-thalamo-cortical pathway could be used to explain the clinical features of tremor in ET patients. Our findings revealed that voxel-level frequency-dependent ALFF, ReHo and DC could be used to discriminate ET from HCs and help to reveal intrinsic brain activity changes, further acting as potential diagnostic biomarkers.

Group linear non-Gaussian component analysis with applications to neuroimaging

Independent component analysis (ICA) is an unsupervised learning method popular in functional magnetic resonance imaging (fMRI). Group ICA has been used to search for biomarkers in neurological disorders including autism spectrum disorder and dementia. However, current methods use a principal component analysis (PCA) step that may remove low-variance features. Linear non-Gaussian component analysis (LNGCA) enables simultaneous dimension reduction and feature estimation including low-variance features in single-subject fMRI. A group LNGCA model is proposed to extract group components shared by more than one subject. Unlike group ICA methods, this novel approach also estimates individual (subject-specific) components orthogonal to the group components. To determine the total number of components in each subject, a parametric resampling test is proposed that samples spatially correlated Gaussian noise to match the spatial dependence observed in data. In simulations, estimated group components achieve higher accuracy compared to group ICA. The method is applied to a resting-state fMRI study on autism spectrum disorder in 342 children (252 typically developing, 90 with autism), where the group signals include resting-state networks. The discovered group components appear to exhibit different levels of temporal engagement in autism versus typically developing children, as revealed using group LNGCA. This novel approach to matrix decomposition is a promising direction for feature detection in neuroimaging.

The Value of Optical Coherence Tomography Angiography (OCT-A) in Neurological Diseases.

Optical coherence tomography angiography (OCT-A) was commercially introduced in 2014. OCT-A allows a fast, non-invasive, three-dimensional analysis of the retinal vasculature from the vitreoretinal interface to the choriocapillaris. The results can be evaluated separately in automated or custom-defined retinal layers. Since its introduction, OCT-A has also been used in patients with neurological diseases in order to find and characterize retinal biomarkers. Many neurological diseases have retinal manifestations, often preceding the key symptoms of the neurological disease. Anatomically and developmentally, the retina is a part of the brain. In contrast to the brain, the retina is easily accessible for imaging methods; moreover, retinal imaging is more cost-effective than brain imaging. In this review, the current knowledge about OCT-A findings and possible OCT-A biomarkers in neurological diseases is summarized and discussed regarding the value of OCT-A as a diagnostic tool in neurological diseases.

Blood GFAP as an emerging biomarker in brain and spinal cord disorders.

Blood-derived biomarkers for brain and spinal cord diseases are urgently needed. The introduction of highly sensitive immunoassays led to a rapid increase in the number of potential blood-derived biomarkers for diagnosis and monitoring of neurological disorders. In 2018, the FDA authorized a blood test for clinical use in the evaluation of mild traumatic brain injury (TBI). The test measures levels of the astrocytic intermediate filament glial fibrillary acidic protein (GFAP) and neuroaxonal marker ubiquitin carboxy-terminal hydrolase L1. In TBI, blood GFAP levels are correlated with clinical severity and extent of intracranial pathology. Evidence also indicates that blood GFAP levels hold the potential to reflect, and might enable prediction of, worsening of disability in individuals with progressive multiple sclerosis. A growing body of evidence suggests that blood GFAP levels can be used to detect even subtle injury to the CNS. Most importantly, the successful completion of the ongoing validation of point-of-care platforms for blood GFAP might ameliorate the decision algorithms for acute neurological diseases, such as TBI and stroke, with important economic implications. In this Review, we provide a systematic overview of the evidence regarding the utility of blood GFAP as a biomarker in neurological diseases. We propose a model for GFAP concentration dynamics in different conditions and discuss the limitations that hamper the widespread use of GFAP in the clinical setting. In our opinion, the clinical use of blood GFAP measurements has the potential to contribute to accelerated diagnosis and improved prognostication, and represents an important step forward in the era of precision medicine.

Signal complexity indicators of health status in clinical EEG

Brain signal variability changes across the lifespan in both health and disease, likely reflecting changes in information processing capacity related to development, aging and neurological disorders. While signal complexity, and multiscale entropy (MSE) in particular, has been proposed as a biomarker for neurological disorders, most observations of altered signal complexity have come from studies comparing patients with few to no comorbidities against healthy controls. In this study, we examined whether MSE of brain signals was distinguishable across patient groups in a large and heterogeneous set of clinical-EEG data. Using a multivariate analysis, we found unique timescale-dependent differences in MSE across various neurological disorders. We also found MSE to differentiate individuals with non-brain comorbidities, suggesting that MSE is sensitive to brain signal changes brought about by metabolic and other non-brain disorders. Such changes were not detectable in the spectral power density of brain signals. Our findings suggest that brain signal complexity may offer complementary information to spectral power about an individual’s health status and is a promising avenue for clinical biomarker development.

Promising candidate cerebrospinal fluid biomarkers of seizure disorder, infection, inflammation, tumor, and traumatic brain injury in pediatric patients.

Cerebrospinal fluid (CSF) is a dynamic metabolically active body fluid that has many important roles and is commonly analyzed in pediatric patients, mainly to diagnose central nervous system infection and inflammation disorders. CSF components have been extensively evaluated as biomarkers of neurological disorders in adult patients. Circulating microRNAs in CSF are a promising class of biomarkers for various neurological diseases. Due to the complexity of pediatric neurological disorders and difficulty in acquiring CSF samples from pediatric patients, there are challenges in developing CSF biomarkers of pediatric neurological disorders. This review aimed to provide an overview of novel CSF biomarkers of seizure disorders, infection, inflammation, tumor, traumatic brain injuries, intraventricular hemorrhage, and congenital hydrocephalus exclusively observed in pediatric patients.