Достижения в области циркуляции биомаркеров нейродегенеративных заболеваний, травматологических травм мозга и опухолей центральной нервной системы.

INTRODUCTION

Neurological disorders, including neurodegenerative diseases, traumatic brain injuries (TBIs), and central nervous system (CNS) tumors, are complex and often devastating conditions that affect millions of people worldwide. Timely diagnosis and monitoring are crucial for improving patient outcomes and driving the search for reliable biomarkers.

Biomarkers can be found in various body fluids, including the cerebrospinal fluid (CSF) and blood. CSF has traditionally been the primary source of neurological biomarkers but can only be obtained via the invasive lumbar puncture. Blood-based circulating biomarkers offer a minimally invasive alternative and have become increasingly important in neurological research and clinical practice. Technologies for detecting these biomarkers have rapidly evolved and progressed to highly sensitive and specific technologies, such as single-molecule arrays (Simoa) and mass spectrometry. This review discusses the advances in circulating biomarkers of neurodegenerative diseases, TBI, and CNS tumors, assay technologies, and the analytical considerations that are crucial for their effective use.

EVOLUTION OF BIOMARKER DETECTION TECHNOLOGIES

The earliest methods for detecting biomarkers were based on immunoblotting techniques, such as western blotting, which continues to be used in research laboratories for biomarker discovery and characterization. The development of the enzyme-linked immunosorbent assay (ELISA) was a significant advancement over immunoblotting [ 1 ]. ELISA allows for quantitative biomarker detection in a more straightforward and scalable format and has been widely used in clinical and research settings with automation options [ 2 ]. The antibody-conjugated signal emission system can range from an enzyme-coupled reaction to chemiluminescence, as in the chemiluminescent immunoassay (CLIA). ELISA and CLIA have limitations, particularly in terms of their sensitivity and dynamic range of detection, and are often insufficient for detecting low-abundance biomarkers in blood, in which concentrations can be several orders of magnitude lower than in CSF.

Electrochemiluminescence (ECL) assays represented another leap forward in biomarker detection technology [ 3 ]. ECL assays combine the principles of electrochemistry and luminescence to provide a highly sensitive detection method. In ECL assays, the binding of an antibody to its antigen triggers an electrochemical reaction that produces light. The intensity of the emitted light is directly proportional to the concentration of the biomarker in the sample. ECL assays offer several advantages over ELISA and CLIA, including greater sensitivity, allowing the detection of concentrations below the femtomolar (10–15 mol/L) level, and multiplexability, allowing the simultaneous measurement of multiple biomarkers in a single sample.

The most recent and advanced development in biomarker immunoassay detection is the single-molecule array (Simoa) technology [ 4 , 5 ]. Simoa is a digital immunoassay platform that allows for the detection of individual protein molecules, providing unparalleled sensitivity. This technology uses arrays of femtoliter-sized wells, each capable of capturing and isolating a single biomarker molecule. When the biomarker is detected, the well produces a fluorescent signal, and the number of fluorescent wells corresponds to the number of biomarker molecules in the sample. This capability is vital for neurological disorders, for which many biomarkers are present in the blood in very low concentrations. For instance, Simoa has enabled the quantification of tau protein in blood at concentrations relevant to Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), and other neurodegenerative conditions [ 6 ].

Although immunoassays are widely used because of their ease of automation and ability to handle samples in a high-throughput manner, mass spectrometry-based assays, such as liquid chromatography tandem mass spectrometry (LC-MS/MS), provide greater accuracy and specificity. In LC-MS/MS, an LC system first separates complex mixtures of biomolecules based on their chemical properties, such as polarity or molecular size. This separation ensures that the compounds of interest are isolated from interfering substances before entering the mass spectrometer, in which the analytes are ionized and passed through two stages of mass filtering. The first mass spectrometer selects ions of specific mass-to-charge ratios (m/z), which are then fragmented in a collision cell. The resulting fragments are analyzed by the second mass spectrometer, enabling precise target identification and quantification. This approach is particularly powerful in distinguishing similar biomarker isoforms, particularly those that undergo post-translational modifications, allowing for highly accurate detection and characterization [ 7 ].

APPLICATION OF BIOMARKERS IN NEURODEGENERATIVE DISEASES

AD

Neurodegenerative diseases, such as AD, are marked by the progressive degeneration of neurons, characterized by pathological hallmarks of extracellular amyloid-beta (Aβ) plaques and intracellular tau tangles, leading to cognitive and motor dysfunction. These pathologies are necessary to make a definitive diagnosis post-mortem. Positron emission tomography (PET) imaging enables the visualization of localized Aβ and tau pathologies and is deemed the gold standard of in vivo AD diagnosis owing to its high concordance with CSF pathology.

In addition to PET, biomarker measurement plays a critical role in diagnosing these diseases, monitoring their progression, and evaluating the efficacy of treatments. In AD, primary biomarkers that have been extensively studied include Aβ peptides, total tau (t-tau), and phosphorylated tau (p-tau). These biomarkers have been measured in CSF in clinical laboratories. For example, the Roche automated CSF biomarker assay is used to measure CSF Aβ protein (1–42) (Aβ 42 ), p-tau181, and t-tau in adults aged 55 yrs or older being evaluated for AD or other causes of cognitive impairment. The t-tau/Aβ 42 and p-tau181/Aβ 42 ratios reflect specific AD pathologies, i.e., the accumulation of abnormal Aβ 42 and tau in plaques and neurofibrillary tangles, which are key processes in neurodegeneration [ 8 ].

Recent advances in biomarker technology have enabled the detection of these markers in blood, offering a less invasive alternative to CSF sampling [ 9 ]. One of the challenges in detecting Aβ peptides (Aβ 42 and Aβ 40 ) in the blood is that the differences in plasma Aβ peptide levels between AD patients and healthy controls (10%–15%) are substantially smaller than those in CSF (40%–50%) [ 10 ]. However, researchers have found that normalizing Aβ 42 to Aβ 40 improves the correlation with amyloid plaque burden in the brain, as measured with PET [ 11 ]. In 2020, C2N Diagnostics developed the first commercially available blood test, PrecivityAD, using a proprietary immunoprecipitation and LC-MS/MS platform to measure the Aβ 42 /Aβ 40 ratio and an apolipoprotein E isoform-specific peptide, providing a score based on the Aβ 42 /Aβ 40 ratio, ApoE level, and age that indicates the probability of amyloid plaque presence. PrecivityAD was compared with the gold standard of amyloid PET for the diagnosis of brain amyloidosis in two independent cohorts with mild cognitive impairment (MCI) or mild dementia, with an area under the curve (AUC) of 0.88 (95% confidence interval [CI], 0.85–0.91), discriminating between individuals with and without brain amyloidosis [ 12 ]. Although it cannot provide a definitive diagnosis of AD, PrecivityAD can help enhance confidence in clinical assessments by estimating the likelihood of amyloid plaque formation in the brain at diagnosis, and importantly, for amyloid-targeting therapies, biomarker confirmation of amyloid positivity is required [ 13 ].

p-Tau, another essential AD biomarker, is detectable in the blood and has shown high accuracy in identifying AD pathology, particularly in differentiating AD from other neurodegenerative conditions. Studies of large cohorts ranging from >100 to >500 patients have demonstrated that p-tau levels in the blood strongly correlate with both amyloid and tau PET [ 14 , 15 ]. Blood p-tau181 levels increase incrementally from preclinical AD to MCI and dementia stages and predicted positive tau PET results with an AUC of 0.87–0.91 for different brain regions. Blood p-tau181 differentiates AD dementia from non-AD neurodegenerative diseases with an accuracy similar to that of tau PET and CSF p-tau181 (AUC=0.94–0.98). p-tau181 assays using Simoa and ECL-based technologies are commercially available. In 2021, the FDA granted Breakthrough Device designation to the Simoa p-tau181 assay, recognizing its potential to improve early AD diagnosis. In patients at risk of early-onset familial AD associated with hereditary mutations, including in the genes encoding presenilin 1 and 2 and amyloid precursor protein, and patients with the APOE4 form, this test enables evaluation in the asymptomatic stage.

Other advanced Simoa-based prototype assays have been developed to measure different p-tau isoforms, such as p-tau212, p-tau217, and p-tau231. Several commercial laboratories are advancing these p-tau assays, including Eli Lilly (Indianapolis, IN, USA) and Quanterix (SP-X; Billerica, MA, USA). Among 1,402 participants from three cohorts, blood p-tau217 differentiated AD from non-AD with an AUC of 0.89 (95% CI, 0.81–0.97) and with higher accuracy than p-tau181 [ 16 ]. In a study with 593 participants, p-tau217 had comparable or slightly better diagnostic performance in differentiating AD from frontotemporal lobar degeneration (AUC=0.93 vs. 0.91) and better correlated with amyloid PET positivity than p-tau181 [ 17 ]. In May 2025, the FDA cleared Fujirebio’s Lumipulse (Tokyo, Japan) G p-tau217/β-Amyloid 1-42 Plasma Ratio as the first in vivo blood test for diagnosing AD. Using the Lumipulse G platform, a chemiluminescent enzyme immunoassay, 499 plasma samples from adults experiencing MCI were tested and compared with CSF and PET-scan evaluations for the presence of amyloid plaques. Results showed that 91.7% of individuals with positive blood tests had a positive amyloid PET scan or CSF test result, while 97.3% of individuals with negative blood tests had a negative amyloid PET scan or CSF test result [ 18 ]. Lumipulse offers patients a non-invasive alternative for more accurately diagnosing the causes of their cognitive impairment.

β-Synuclein, a presynaptic protein marker of synaptic degeneration, is another potential biomarker for neurodegeneration. This marker is measurable in both the CSF and plasma and has been linked to synaptic degeneration in AD. Advances in MS have enabled the detection of elevated β-synuclein levels in patients with AD [ 19 ]. The ability to detect this marker in blood is particularly significant for the early diagnosis and monitoring of AD, as plasma β-synuclein levels are reportedly elevated in preclinical AD and increase with MCI and AD dementia, reducing the need for invasive procedures such as lumbar puncture to collect CSF [ 20 ]. As presynaptic β-synuclein level elevation can be observed as early as in the preclinical AD stage, it can help identify high-risk individuals that may benefit from therapy in clinical studies. Using β-synuclein levels to identify individuals at risk of AD in an early stage may improve clinical trial design and facilitate determining the effectiveness of a candidate drug or disease-modifying therapy [ 9 ].

Parkinson’s disease (PD)

PD pathology prominently features abnormal α-synuclein (α-syn) protein aggregation, resulting in the formation of Lewy bodies, which are linked to dopaminergic neuron death [ 21 ], as observed in other synucleinopathies. Different α-syn forms, such as oligomeric (o-α-syn; small, soluble aggregates of α-syn) and phosphorylated α-syn (p-α-syn), show distinct aggregation patterns in the CSF and may correlate with PD progression. Both genetic factors and post-translational modifications contribute to α-syn misfolding and the subsequent formation of oligomers, amyloid-like fibrils, and Lewy bodies. CSF total α-syn (t-α-syn) levels tend to be lower in PD patients than in healthy individuals; however, because of overlap with other neurodegenerative diseases such as multiple system atrophy (MSA) and dementia with Lewy bodies (DLB), t-α-syn alone is insufficient for PD diagnosis [ 22 ].

Reduced CSF Aβ42 levels in PD patients can signal cognitive decline, as observed in AD. However, this marker is insufficiently effective for the differentiation between PD and AD or other neurodegenerative diseases. t-tau and p-tau have been inconsistently associated with PD, with increased levels appearing mostly in patients with advanced dementia. The combination of Aβ and tau biomarkers shows potential for predicting cognitive decline but requires further refinement for reliable PD diagnostics [ 22 ]. In a study of 73 patients with PD classified into tremor-dominant (TD) and postural instability gait difficulty (PIGD) subtypes, the PIGD subtype was characterized by reduced plasma Aβ-42 levels and increased plasma α-syn levels compared with those in the TD subtype [ 23 ].

Neurofilament light chain (NfL), an axonal damage marker, has been studied as a biomarker for neurodegeneration. CSF and plasma NfL levels are significantly higher in aggressive disorders, such as MSA and progressive supranuclear palsy, than in PD, and the difference is more evident in the CSF than in plasma [ 24 ]. Among patients with PD, high NfL levels correlate with motor and cognitive impairment but are also influenced by age, complicating interpretation [ 25 ].

Other potential diagnostic and prognostic markers of PD include lysosomal enzymes and inflammatory biomarkers. Multiple CSF biomarkers can be combined to achieve an accurate diagnostic and prognostic model. Combinations of α-syn species and NfL have been investigated as markers for the differential diagnosis of PD versus atypical parkinsonian disorders, and for disease monitoring [ 26 ]. The autophagy-lysosomal pathway, critical for cellular waste processing, is disrupted in PD, particularly in patients with mutations in the glucocerebrosidase gene ( GBA ) affecting the glucocerebrosidase (GCase) enzyme. Lower GCase activity in the CSF in GBA mutation carriers has been linked to PD and more severe symptoms [ 27 , 28 ]. Other lysosomal dysfunction markers, such as those encoded by CTSD , SLC17A5 , and ASAH1 , show potential diagnostic value, particularly when combined with other PD markers [ 29 ]. Neuroinflammation, triggered by α-syn, also plays a role in PD. Various inflammatory biomarkers in the CSF, including monocyte chemoattractant protein-1 [ 30 ] and chitinase-3-like protein 1 [ 31 ], correlate with PD symptom progression, although alone, they lack diagnostic power. Combining inflammatory markers in diagnostic panels may enhance sensitivity, particularly in aggressive PD subtypes. Pedersen, et al . [ 32 ] reported a seven-biomarker PD panel that could distinguish PD from DLB and AD with an AUC of 0.82. However, evidence on the counterparts of these markers in peripheral circulation is limited.

Collectively, α-syn, tau, NfL, lysosomal enzymes, and inflammatory markers show promise for developing a biomarker panel to improve PD diagnosis and track disease progression. α-Syn species have the strongest rationale for use and should constitute the basis of composite biomarker panels. In recent years, two novel protein amplification assays, protein misfolding cyclic amplification [ 33 ] and real-time quaking-induced conversion [ 34 ], have been developed and demonstrated capability to detect aggregated and misfolded α-syn in CSF with high diagnostic accuracy. The feasibility of evaluating α-syn aggregation in blood samples remains to be explored. CSF Aβ42 has demonstrated prognostic value for cognitive impairment in PD. Other biomarkers related to axonal damage (tau proteins and NfL) are not specific for PD diagnosis but can help assess PD progression.

Multiple sclerosis (MS)

MS is a neurological disorder characterized by neuroinflammation and neurodegeneration. One important biomarker currently used in the clinic is the presence of lipid-specific oligoclonal IgM bands (LS-OCMBs) in the CSF, which are associated with aggressive disease progression. Iparraguirre, et al . [ 35 ] explored peripheral blood mononuclear cells as a substitute specimen type for CSF. Through transcriptome analysis, they identified several circular and linear RNA biomarkers that were differentially expressed in patients with MS. Validation using qPCR revealed two circular RNAs (hsa_circ_0000478 and hsa_circ_0116639) and two linear RNAs (IRF5 and MTRNR2L8) that significantly differed in levels between LS-OCMB-positive and negative patients, providing potential non-invasive biomarkers for monitoring MS progression.

MS pathogenesis is tightly associated with two viruses. Epstein-Barr virus (EBV) is considered a major trigger for MS and can be detected through cell-free (cf) DNA analysis of the CSF or plasma [ 36 ]. John Cunningham virus (JCV) is associated with progressive multifocal leukoencephalopathy, a serious condition in patients with MS caused by JCV reactivation during immunosuppressive treatments. JCV DNA can be detected in the CSF using PCR assays, aiding in diagnosis [ 37 ].

Exosomes, small vesicles derived from body fluids such as serum, plasma, and CSF, have also been explored as biomarkers for MS. Exosomes from patients with active relapsing-remitting MS (RRMS) had increased levels of EBV proteins, including the nuclear antigen EBNA1 and latent membrane proteins LMP1 and LMP2A, compared with that in healthy controls and stable RRMS patients [ 38 ]. Selmaj, et al . found reduced levels of specific microRNAs (miRNAs; hsa-miR-122-5p, hsa-miR-196b-5p, hsa-miR-301a-3p, and hsa-miR-532-5p), which play roles in cell-to-cell communication, in RRMS patients [ 39 ]. However, these studies did not report clinical sensitivity and specificity for these MS markers. Additionally, increased miR-155-5p levels were detected in exosomes from urine, plasma, and CSF just days before disease onset in a study in both model mice and humans with timed specimen collection [ 40 ]. Further research is warranted to validate miR-155-5p as the first, non-invasive source of diagnostic miRNA in pre-symptomatic stages of MS.

NfL plasma levels are increased in numerous neurological conditions. While not specific to any one disease, NfL has been proposed as a valuable broad biomarker for screening neurological damage and monitoring disease progression [ 41 ]. The high correlation between plasma and CSF NfL levels makes it a promising candidate for broader neurological screening. In 2022, Simoa NfL received FDA Breakthrough Device designation for the diagnosis of MS.

ALS

ALS is a progressive neurodegenerative disease marked by motor neuron loss. NfL has emerged as a key biomarker, with elevated levels in the blood and CSF indicating neuronal damage. The development of the Simoa technology has enhanced the detection of NfL, enabling earlier diagnosis and more precise monitoring of ALS progression. In a study in two cohorts of patients with sporadic ALS and healthy controls, CSF, serum, and plasma NfL identified ALS patients with a sensitivity of 97%, 89%, and 90% and specificity of 95%, 75%, and 71%, respectively. Blood NfL levels correlated with disease severity and predicted survival in patients with ALS [ 42 ]. Another important biomarker is the phosphorylated neurofilament heavy chain (pNfH), which can be detected in both the CSF and blood. Advances in detection techniques have improved the reliability of pNfH as a tool for assessing ALS progression and treatment response [ 43 ].

Epigenetic biomarkers in both the CSF and peripheral circulation have also been explored. A study of circulating cfDNA in CSF and plasma of patients with ALS identified a differentially methylated region in the rhomboid 5 homolog 2 ( RHBDF2 ) gene, suggesting its potential as a neurodegeneration marker [ 44 ]. Joilin, et al . identified a serum-based biomarker signature of non-coding RNAs, including hsa-miR-16-5p and hsa-miR-21-5p, which successfully differentiated ALS from non-ALS cases. In sporadic ALS, miRNAs such as hsa-miR-4299 and hsa-miR-4649-5p are differentially expressed in plasma and CSF samples [ 45 ].

TBI

TBI is a significant public health issue, often leading to long-term neurological deficits. Biomarkers have been investigated as tools for assessing TBI severity, predicting outcomes, and guiding treatment decisions. NfL is one of the most studied biomarkers in TBI. Elevated blood levels of NfL have been associated with the severity of injury and long-term outcomes. For instance, in brain trauma that occurs as a result of sports injuries, NfL levels increase with increasing grade of TBI severity [ 46 ]. Plasma NfL levels in the early phase of TBI are associated with the presence of diffuse axonal injury in later phases [ 47 ]. Using NfL as a biomarker for measuring brain damage can help guide long-term management and treatment plans for athletes, leading to a more precise recovery timeline [ 46 ]. The advent of high-sensitivity assays such as ECL and Simoa has enabled the detection of even slight increases in NfL levels, which can provide valuable information about ongoing neuronal damage even when traditional imaging results appear normal [ 48 ]. This is particularly important for mild TBIs, for which imaging might not detect subtle injuries; however, elevated NfL levels can help guide clinical decisions, such as the need to avoid premature exposure to additional trauma [ 49 ].

Glial fibrillary acidic protein (GFAP) is primarily found in brain astrocytes and has gained attention as a biomarker for both TBI and AD. GFAP is released into the blood following astroglial injury, a common occurrence in TBI. Blood GFAP levels correlate with TBI severity and can predict the likelihood of poor neurological outcomes [ 50 ]. This biomarker is being integrated into clinical practice and research to improve the management of TBI patients.

In 2018, the FDA approved the Banyan Brain Trauma Indicator, which measures GFAP and ubiquitin C-terminal hydrolase-L1 (UCH-L1), both markers of neuronal damage, for use in diagnosing mild TBI. This blood test, developed under the Breakthrough Devices Program, helps physicians assess the likelihood of intracranial trauma. In 2021, Abbott released a similar test that delivers results within 15 mins and has a high negative predictive value for ruling out intracranial trauma [ 51 ]. Currently, this test is available as a point-of-care testing device, using whole blood as the sample type. GFAP and UCH-L1 tests are expected to become even more widely available as high-throughput systems and point-of-care whole-blood tests to streamline diagnostic processes [ 52 ].

Fig. 1 summarizes representative blood-based biomarkers for the major neurological disorders covered in this review. Table 1 summarizes the clinical applications of promising blood-based biomarkers and sources of evidence.

CIRCULATING BIOMARKERS OF CNS TUMORS

Primary CNS tumors are diverse, ranging from benign to malignant, with gliomas being the most common malignant type. Glioblastoma multiforme (GBM), the most aggressive form of glioma, is particularly prevalent in adults. GBM is notoriously difficult to treat, with a 5-yr survival rate of only 5%, relative to 35% for other CNS tumors. Consequently, significant research has focused on liquid biopsy techniques for GBM, examining biomarkers including extracellular vesicles (EVs), cfDNA, RNA, and circulating tumor cells [ 53 , 54 ].

In a retrospective case–control study of 698 patients [ 55 ], patients with glioma had a higher neutrophil/lymphocyte ratio (NLR), systemic immune-inflammation index, and pan-immune-inflammation value but a lower lymphocyte/monocyte ratio, with NLR showing the greatest accuracy, with an AUC of 0.7490 (95% CI, 0.6482–0.8498). In EVs isolated from blood and CSF, the isocitrate dehydrogenase 1 ( IDH1 ) mutation IDH1R 132H is associated with tumor recurrence post-resection [ 56 ]. In a study of 35 paired primary low-grade astrocytoma cases, IDH1R 132H was associated with a longer recurrence-free period (RFP) than that of the wild type and independently predicted a longer RFP (hazard ratio, 1.073) [ 57 ]. Certain miRNAs in the CSF, such as miR-2 and miR-15b, can distinguish GBM from primary CNS lymphoma with high accuracy. A nine-miRNA signature correlating with tumor volume has been identified, and EV miRNAs may help monitor chemotherapy response and drug resistance in patients with GBM [ 58 , 59 ]. Circulating tumor DNA (ctDNA) in CSF is also a valuable biomarker. Tumor suppressor genes such as TP53 and PTEN are expressed in CSF ctDNA in all recurrent gliomas, providing insights into tumor progression and recurrence [ 60 ]. In a cohort of 33 brain cancer patients, 70% of patients with glial tumors had promotor methylation of at least one of MGMT , RASSF1A , CDKN2B , and CDKN2A in serum ctDNA [ 61 ].

ANALYTICAL CONSIDERATIONS AND CHALLENGES

The rapid advancement of biomarker detection technologies has significantly enhanced our ability to study and manage neurological disorders; however, several analytical challenges remain to be addressed to fully realize their potential. Newer technologies offer greater sensitivity but often come with a specificity trade-off. High sensitivity can sometimes result in the detection of non-specific signals or cross-reactivity with other proteins, leading to false positives. Rigorous assay validation and the development of highly specific antibodies are essential to minimize these issues. Standardization across laboratories is a significant challenge, particularly as these technologies are applied in clinical settings. Variability in sample handling, assay protocols, and data analysis can lead to inconsistent results. Efforts are underway to establish standardized protocols and reference materials to improve reproducibility. The utility of biomarkers in clinical practice depends on their ability to detect disease, as well as their ability to provide meaningful information over time. Longitudinal studies are critical for understanding how biomarker levels change with disease progression and treatment. Such studies require robust, high-throughput assays that can be consistently applied over long periods.

CONCLUSIONS

The evolution of biomarker detection technologies, from immunoblotting to Simoa, has revolutionized the study and management of neurological disorders. These advancements have enabled the detection and quantifying of biomarkers in blood, providing a less invasive alternative to CSF sampling. As these technologies continue to improve, they hold the promise of earlier diagnosis, better monitoring of disease progression, and the development of more personalized treatment strategies for patients with neurological disorders.

However, several challenges remain, including the requirement for enhanced specificity, standardization, and longitudinal validation. Addressing these challenges will be essential for successfully translating biomarker research into clinical practice, ultimately improving outcomes for patients with neurological diseases.