Search Results (70)

Background: Blood-based biomarkers offer an accessible alternative to cerebrospinal fluid or positron emission tomography (PET) imaging for Alzheimer’s disease (AD) screening and diagnosis. This study evaluated the diagnostic performance of the fully automated HISCL plasma Aβ42/40 assay in a real-world clinical setting. Methods: We retrospectively enrolled 127 participants, stratified into cognitively normal (CN), mild cognitive impairment (MCI), AD, and Non-AD subgroups. Plasma Aβ42/40 levels were quantified using the HISCL and Simoa platforms. Additionally, plasma oligomerized Aβ (OAβ), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) were measured. Results: The HISCL plasma Aβ42/40 ratio was significantly lower in the AD continuum (MCI + AD) compared to the CN subgroup (p < 0.001). The HISCL assay demonstrated robust diagnostic performance (AUC = 0.747), yielding a comparably higher AUC value compared to the Simoa Aβ42/40 ratio (AUC = 0.687). Although method comparison showed a proportional difference between HISCL and Simoa, the HISCL assay maintained high discriminative capability. Notably, integrating plasma GFAP and NfL with the HISCL Aβ42/40 ratio significantly enhanced the diagnostic accuracy (AUC = 0.823, p = 0.046). Method comparison between heparinized and EDTA plasma in the HISCL assay confirmed assay stability, showing a significant correlation and a regression slope near unity. Conclusions: The HISCL plasma Aβ42/40 assay demonstrates reliable diagnostic performance for identifying AD pathology in clinical practice, showing stability across sample types. Furthermore, its combination with neurodegeneration markers significantly improves predictive accuracy, supporting its utility as a robust screening tool and foundational component of future multimarker diagnostic panels. Full article

Relapsing–remitting multiple sclerosis (RRMS) is characterized by neuroaxonal damage, astrogliosis and inflammation. These mechanisms may already be active from early disease stages, underscoring the need for sensitive biomarkers capable of capturing treatment-related biological effects beyond conventional clinical measures. In this multicenter, ambispective, observational real-world study, the longitudinal effects of ozanimod on serum biomarkers were evaluated, during the first year of treatment in patients with low-to-moderate activity RRMS. Serum neurofilament light chain (sNfL), glial fibrillary acidic protein (sGFAP) and cytokines associated with immune activity (IFN-γ, IL-17, IL-6, IL-10, and IL-1β) were quantified at baseline, 6 months, and 12 months using an ultrasensitive single-molecule array (SIMOA). Ozanimod was associated with significant reductions in sNfLs and sGFAP at 12 months. Concomitantly, significant decreases in IFN-γ and IL-1β were observed. IL-17 levels remained unchanged in the overall cohort but decreased in patients with higher baseline IL-17 levels. These findings demonstrate coordinated modulation of biomarkers reflecting neuroaxonal damage, astroglial activation, and inflammatory activity under ozanimod treatment in early RRMS in real-world conditions. These results highlight the biological relevance of early intervention within a therapeutic window of opportunity and support the potential utility of serum biomarkers for monitoring biological treatment effects in clinical practice. Full article

Alzheimer’s disease (AD) is increasingly recognized as a biological continuum characterized by early neuropathological and molecular changes that precede the onset of clinical symptoms. Fluid biomarkers have transformed the diagnostic landscape by enabling the in vivo detection of core AD pathologies, particularly amyloid-β deposition and tau-related neurodegeneration. Despite the rapid expansion of candidate biomarkers, however, only a limited number have successfully translated into clinical practice. Discovery-phase approaches, primarily driven by mass spectrometry-based proteomics, enable the unbiased identification of novel biomarker candidates across multiple biological pathways. Research-phase methods, including immunoassays such as enzyme-linked immunosorbent assay (ELISA), electrochemiluminescence immunoassays (ECLIA), microfluidic platforms, and ultrasensitive technologies such as single-molecule array (SIMOA), support analytical and clinical validation in well-characterized cohorts. Clinical implementation has been advanced by fully automated platforms, including Lumipulse and Elecsys, which have obtained regulatory approval for cerebrospinal fluid biomarkers and, more recently, blood-based biomarkers. These developments represent a paradigm shift toward minimally invasive and scalable diagnostic strategies that may reduce dependence on neuroimaging techniques. Nevertheless, major challenges remain, including assay standardization, inter-platform variability, demonstration of clinical utility, and barriers to widespread clinical adoption. This review provides a comprehensive overview of analytical methods used to measure AD fluid biomarkers in cerebrospinal fluid and plasma, structured according to the biomarker development pipeline from discovery to clinical implementation. Overall, the review highlights a fit-for-purpose approach to biomarker development and emphasizes the complementary roles of diverse analytical technologies across the different phases of biomarker translation. Full article

Background/Objectives: Serum neurofilament light chain (sNfL) is an early and sensitive biomarker of polyneuropathy. This study compared the UmanDiagnostics enzyme-linked immunosorbent assay (ELISA), and Meso Scale Discovery (MSD) R-PLEX assay with the current gold-standard single-molecule array (Simoa) assay for sNfL measurement. Methods: sNfL levels were measured with Simoa, ELISA, and MSD R-PLEX in 330 serum samples from 73 individuals with a pathogenic transthyretin gene variant (TTRv) and in 165 healthy controls (HC) with ELISA and MSD R-PLEX. Results: Median sNfL levels, assessed in serum samples from TTRv individuals, differed across all assays (all p < 0.001). Passing–Bablok regression slopes were 1.01 (Simoa–ELISA), 1.00 (Simoa–MSD R-PLEX), and 1.02 (MSD R-PLEX-ELISA), with very strong correlations (all r > 0.8). Bland–Altman analysis showed mean differences of 0.1 ± 0.2 pg/mL (Simoa–ELISA), 0.7 ± 0.1 pg/mL (Simoa–MSD R-PLEX), and −0.6 ± 0.2 pg/mL (MSD R-PLEX-ELISA). In HC, sNfL levels positively correlated with age. Z-score normalization allowed for inter-assay comparison. Conclusions: The ELISA and MSD R-PLEX assays provide suitable alternatives for the Simoa assay to measure sNfL levels in carriers of a pathogenic TTR-gene variant. The differences in concentrations defined by the assays directly relate to the internal standard provided with the assays. Full article

Major depressive disorder (MDD) has been associated with an increased risk of cognitive decline and neurodegenerative disorders like Alzheimer’s disease (AD), prompting interest in peripheral biomarkers related to amyloid metabolism as well as neuroaxonal and astroglial injury. However, evidence regarding circulating markers in MDD remains inconsistent. In this cross-sectional study, we simultaneously assessed plasma levels of amyloid-β peptides (Aβ40 and Aβ42), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) in MDD patients and healthy controls (HC) using ultrasensitive single-molecule array (SIMOA) technology. Associations with clinical and cognitive scales were examined. Plasma concentrations of Aβ40 and Aβ42 were significantly lower in MDD patients, whereas no group differences were observed for NfL and GFAP, after correcting for age and sex. However, both Aβ peptides were not significantly associated with depressive symptom severity, whereas the Aβ42/Aβ40 ratio was negatively associated with anhedonia. NfL and GFAP levels were primarily influenced by age. In the absence of a reduced Aβ42/Aβ40 ratio, these findings suggest that reduced plasma Aβ levels in MDD may reflect systemic or metabolic factors associated with MDD, including lifestyle or treatment-related effects. Therefore, these findings should be interpreted with caution and further examined in longitudinal studies to prevent potential confounding factors. Full article

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease. Quantifying neuronal damage is a critical step for patient care. Neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) are the most promising serum biomarkers reflecting neuronal damage and astroglial activation, respectively. This study analyzed sNfL and sGFAP in 177 MS patients and 71 healthy controls (HCs) using SIMOA technology, classifying patients as responders (Rs) or non-responders (NRs) based on “No Evidence of Disease Activity 3” (NEDA-3) status during two years of treatment. Longitudinal analyses were performed for Dimethyl fumarate (DMF) and Ocrelizumab (OCRE) treatment. Biomarker–age correlation analysis in HCs confirmed correlation between both NfL and GFAP, with age and cut-off values specific for age decades being calculated. Both biomarkers were higher in MS patients compared to HCs. sNfL showed a significant increase in NR patients overall. In contrast, sGFAP was elevated in the low-to-moderate-efficacy treatment agents (LETAs) NR group and also in the DMF NR subgroup, suggesting that it monitors persistent astrogliosis. Longitudinal analysis showed that both biomarkers decreased during DMF treatment after one year. During OCRE treatment, sNfL rapidly reduced to HC levels within one year, while sGFAP decreased only after two years. This highlights that OCRE acts differently on the pathological processes linked to the two biomarkers. Full article

The HIV-1 envelope glycoprotein gp120 is prominently exposed on the surface of both HIV-1 virions and infected host cells, serving as a key marker of infection. gp120 plays a pivotal role in viral entry by interacting with the primary receptor, CD4, on host cells. Therapeutic strategies targeting the HIV-1 reservoir, such as anti-gp120 antibodies that trigger antibody-dependent cellular cytotoxicity (ADCC) and chimeric antigen receptor T (CAR-T) cells, rely on the presence of gp120 on the surface of infected cells to exert their effects. Consequently, accurate monitoring of gp120 expression on infected cells is essential for evaluating the pharmacological efficacy of these interventions. In this study, a sensitive, specific, and inexpensive enzyme-linked immunosorbent assay (ELISA) for quantifying HIV-1 gp120 glycoprotein was developed using a selected pair of anti-gp120 antibodies. The assay achieved a lower limit of quantitation (LLOQ) of 0.16 pM, demonstrating sensitivity comparable to that of the digital single molecule array (Simoa) platform, which exhibited a LLOQ of 0.23 pM and requires specialized instrumentation. The binding specificity of the antibodies used in the novel assay was confirmed using liquid chromatography–mass spectrometry (LC-MS), and the assay was pharmacologically validated with lysates obtained from 2D10 and MOLT IIIB cell lines. Furthermore, treatment of HIV-infected human primary CD4⁺ T cells with a targeted activator of cell kill (TACK) compound significantly reduced gp120 concentration in CD4⁺ T cell lysate compared to controls. The gp120 marker from infected cell lysates correlated with the number of gp120-positive cells detected by immunocytochemistry, as well as with HIV-1 p24 levels and cell-associated viral RNA measurements. In summary, a novel, simple, and sensitive HIV-1 gp120 ELISA has been developed and validated. This assay holds potential for investigating HIV-1 persistence and evaluating the efficacy of therapeutic agents targeting infected cells. Full article

Background: The clinical–radiological paradox in multiple sclerosis (MS) underscores the need for biomarkers that better reflect neurodegenerative pathology. Serum neurofilament light chain (sNfL) is a dynamic marker of neuroaxonal injury, while brain volumetry provides structural assessment of disease impact. However, the precise link between sNfL and regional atrophy patterns, as well as their combined utility for patient stratification and prediction, remains underexplored. Objective: This study aimed to establish a multimodal biomarker framework by integrating sNfL with comprehensive volumetric MRI to define neurodegenerative endophenotypes and predict neuroaxonal injury using Bayesian inference and machine learning. Methods: In a cohort of 57 MS patients, sNfL levels were measured using single-molecule array (Simoa) technology. Brain volumes for 42 regions were quantified via automated deep learning segmentation (mdbrain software). We employed (1) Bayesian correlation to quantify evidence for sNfL–volumetric associations; (2) mediation analysis to test whether grey matter atrophy mediates the EDSS–sNfL (Expanded Disability Status Scale) relationship; (3) unsupervised K-means clustering to identify patient subtypes based on combined sNfL–volumetric profiles; and (4) supervised machine learning (Elastic Net and Random Forest regression) to predict sNfL from volumetric features. Results: Bayesian analysis revealed strong evidence linking sNfL to total grey matter volume (r = −0.449, BF₁₀ = 0.022) and lateral ventricular volume (r = 0.349, BF₁₀ = 0.285). Mediation confirmed that grey matter atrophy significantly mediates the relationship between EDSS and sNfL (indirect effect = 0.45, 95% CI [0.20, 0.75]). Unsupervised clustering identified three distinct endophenotypes: “High Neurodegeneration” (elevated sNfL, severe atrophy, high disability), “Moderate Injury,” and “Benign Volumetry” (low sNfL, preserved volumes, mild disability). Supervised models predicted sNfL with high accuracy (R² = 0.65), identifying total grey matter volume, ventricular volume, and age as top predictors. Conclusions: This integrative multi-method analysis demonstrates that sNfL is robustly associated with global grey matter and ventricular volumes, and that these measures define clinically meaningful neurodegenerative subtypes in MS. Machine learning confirms that a concise set of volumetric features can effectively predict neuroaxonal injury. These findings advance a pathobiology-driven subtyping framework and provide a validated model for using routine MRI volumetry to assess neuroaxonal health, with implications for prognosis and personalised therapeutic strategies. Full article

Background: Neuromyelitis optica spectrum disorder (NMOSD) involves demyelinating astrocytopathy. Most cases have autoantibodies against aquaporin-4 (AQP4 ab), but AQP4 ab-negative patients may also meet NMOSD criteria. Overlapping clinical phenotypes of CNS inflammatory demyelinating diseases (IDDs) complicate understanding NMOSD mechanisms. Objectives: Investigate molecules related to neuroinflammation and astrocyte function as potential biomarkers of NMOSD and other IDDs by using clinical data and in vitro assays. Methods: Subjects (176) with different IDDs (NMOSD (37), MS (125), MOGAD (3), ADEM (3) and eight radiologic isolated syndromes (RIS)) were studied. Plasma concentrations of TGF-β and other cytokines were measured by single molecule array (SIMOA), Luminex and ELISA assays. Functional assays used in vitro cultured human astrocytes exposed to NMOSD subjects’ serum, followed by immunolabeling. Results: TGF-β levels were higher in NMOSD patients during attacks compared to inactive phases. AQP4+ groups in inactive phases had lower TGF-β levels than AQP4− groups. No significant difference was found for IL-1β, IL-8, IL-10, IL-17A and Thrombospondin plasma concentrations, with a minor difference for VEGF in the AQP4+ group. Astrocytes exposed to NMOSD AQP4+ and AQP4− subjects serum, with or without TGF-β1, showed no changes in C3, NFkB and HMGB1. However, the content of GLT-1 decreased in AQP4+ serum-treated astrocytes, reversed by TGF-β1. Conclusions: TGF-β may be a potential NMOSD activity biomarker, indicating different disease mechanisms based on AQP4 ab presence. Full article

Background: The search for reliable aging biomarkers using proteomic databases and large-scale proteomic studies presents a significant challenge in biogerontology. Existing proteomic databases and studies contain valuable information; however, there is inconsistency in approaches to biomarker selection and data integration. This creates barriers to translating existing knowledge into clinical practice and use in biomedical research. This work analyzed experimental proteomic studies, the content of proteomic databases, and proposed recommendations for optimization and improvement of proteomic database formation and enrichment. Methods: The study utilized publications devoted to proteomic data acquisition methods, proteomic databases, and experimental studies. Results: Methods for obtaining proteomic data were analyzed (Protein Pathway Array (PPA), Tissue Microarray (TMA), Luminex (Bead Array), MSD (Meso Scale Discovery), Simoa (Quanterix), SOMAscan (SomaLogic), Olink (PEA), Alamar NULISA (PEA+), and Oxford Nanopore. A total of 16 proteomic databases were investigated (HAGR, KEGG, STRING, Aging Atlas, HALL, Human Protein Atlas, UniProt, AgeAnnoMO, AgeFactDB, AgingBank, iProX, jMorp, jPOSTrepo, MassIVE, MetaboAge DB, PRIDE Archive). Additionally, 22 proteomic studies devoted to aging and age-associated diseases were analyzed. Conclusions: Proteomic databases and experimental studies individually contain valuable information about aging biomarkers. Using data from different sources within biomedical research poses challenges for improving and optimizing methodological solutions for publication selection, database formation, and marker development. Full article

Background and Objectives: Neuromyelitis optica spectrum disorder (NMOSD) and MOG antibody-associated disease (MOGAD) are distinct autoimmune demyelinating disorders of the central nervous system, characterized by different pathological and clinical features. Reliable biomarkers are essential for accurate diagnosis and monitoring of disease activity. Glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are promising candidates, reflecting astrocytic and axonal damage, respectively. Materials and Methods: To investigate the relationship between astroglial (GFAP) and neuronal (NfL) protein levels in the peripheral blood, 89 plasma samples were analyzed using Simoa immunoassays. The concentrations of pNfL and pGFAP were measured in three groups: AQP4-IgG-positive NMOSD patients (n = 18), MOGAD patients (n = 12), and healthy controls (HCs, n = 19). Statistical analyses assessed group differences, correlations, and the predictive value of biomarkers for disease activity. Results: Both NMOSD and MOGAD patients exhibited elevated pNfL compared with controls, indicating neuroaxonal injury. No significant differences in pNfL, pGFAP, or pGFAP/pNfL ratios were observed between patient groups. The pGFAP levels and the pGFAP/pNfL ratio were significantly higher in NMOSD patients, particularly during attacks, indicating prominent astrocyte damage. Correlations revealed associations between biomarker levels, disability, and disease duration. pNfL demonstrated high accuracy in predicting recent relapses (AUC = 0.906), whereas pGFAP showed moderate predictive capacity (AUC = 0.638). Elevated pNfL and pGFAP levels were associated with an increased likelihood of relapse within six months. Conclusions: Plasma NfL and GFAP are promising biomarkers for assessing tissue injury and disease activity in NMOSD and MOGAD. NfL predicts relapses, while GFAP primarily reflects astrocytic damage in NMOSD. Longitudinal studies are warranted to validate these biomarkers and establish clinical thresholds for disease management. Full article

Alzheimer’s disease (AD) is a progressive neurodegenerative condition representing the most common cause of dementia and currently affects millions of people worldwide. The clinical presentation includes memory impairment, cognitive decline, and neuropsychiatric symptoms, reflecting pathological hallmarks such as β-amyloid (Aβ) plaques, neurofibrillary tangles, synaptic dysfunction, and neuroinflammation. Despite being the gold standard for detecting amyloid and tau pathologies in vivo, cerebrospinal fluid (CSF) biomarkers and positron emission tomography (PET) imaging are not widely used in the clinical setting because of invasiveness, high costs, and restricted accessibility. Recent advances in blood-based biomarkers offer a promising and minimally invasive tool for early detection, diagnosis, and monitoring of AD. Ultra-sensitive analytical platforms, including single-molecule arrays (Simoa) and immunoprecipitation-mass spectrometry, now enable reliable quantification of plasma Aβ isoforms, phosphorylated tau variants (p-Tau181, p-Tau217, p-Tau231), neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). In addition, blood biomarkers reflecting oxidative stress, neuroinflammation, synaptic disruption and metabolic dysfunction are under active investigation. This narrative review synthesizes current evidence on blood-based biomarkers in AD, emphasizing their biological relevance, diagnostic accuracy, and clinical applications. Finally, we highlight forthcoming challenges, such as standardization, and future directions, including the use of artificial intelligence in precision medicine. Full article

Background: Neurofilament light chain (NfL) is a promising biomarker of neuroaxonal injury, increasingly used to monitor neurodegeneration in Alzheimer’s disease (AD). Multiple analytical platforms are available for NfL quantification in cerebrospinal fluid (CSF), but data on cross-platform consistency remain limited. Objective: This pilot study aimed to provide CSF NfL concentrations measured using Simoa and Lumipulse immunoassays in patients with biologically confirmed AD. Methods: Twenty-eight patients with cognitive impairment fulfilling the biological criteria for AD were enrolled. CSF NfL levels were measured using both Simoa and Lumipulse immunoassays. Statistical analyses assessed intra-individual agreement, correlation between platforms, and associations with cognitive status. Results: NfL concentrations measured with Simoa and Lumipulse showed a strong positive correlation between platforms (Spearman’s ρ = 0.965, p < 0.001), demonstrating excellent analytical concordance. Conclusions: In this pilot study, Simoa and Lumipulse yielded strongly correlated CSF NfL measurements, providing initial evidence of cross-platform consistency. However, these findings require confirmation in larger and diverse cohorts before definitive validation. Full article

Background and Objectives: Multiple sclerosis (MS) is a chronic autoimmune, inflammatory, and neurodegenerative central nervous system disease. Neurodegeneration plays a central role in long-term disease progression. Materials and Methods: This cross-sectional study examined the relationship between neurodegenerative biomarkers, namely plasma neurofilament light chain (pNfL) levels and MRI-derived brain volume measurements, and clinical outcomes in 49 patients with relapsing–remitting multiple sclerosis (RRMS). Plasma NfL levels were quantified using Simoa technology, while MRI data was analyzed via FreeSurfer to measure volumes of grey and white matter, specific brain structures, and ventricular sizes. Cognitive performance was assessed using the Symbol Digit Modalities Test (SDMT) and Brief Visuospatial Memory Test-Revised (BVMT-R). Disability was evaluated using the Expanded Disability Status Scale (EDSS). Results: The results indicated significant positive correlations between SDMT scores and volumes of grey matter, white matter, and various subcortical structures, suggesting that preserved brain volume is linked to better cognitive performance. Negative correlations were observed between SDMT scores and ventricular volumes, as well as between SDMT scores and EDSS scores, implying that cognitive decline corresponds with structural brain deterioration and increased disability. No significant associations were found between BVMT-R scores and imaging data or disability measures. Plasma NfL levels showed significant correlations with early disease relapses and enlargement of the third and fourth ventricles, but not with brain volume, cognitive tests, or EDSS scores. Conclusions: These findings indicate that MRI-based brain volumetrics, particularly grey and white matter measures, are stronger indicators of cognitive function and disability in RRMS than plasma NfL. Full article

Background: There is growing interest in the potential role of manganese (Mn) in the development of Alzheimer’s Disease and related dementias (ADRD). Methods: In this nested pilot study of a ferroalloy worker cohort, we investigated the impact of chronic occupational Mn exposure on cognitive function through β-amyloid (Aβ) deposition and multi-omics profiling. We evaluated six male Mn-exposed workers (median age 63, exposure duration 31 years) and five historical controls (median age: 60 years), all of whom had undergone brain PET scans. Exposed individuals showed significantly higher Aβ deposition in exposed individuals (p < 0.05). The average annual cumulative respirable Mn was 329.23 ± 516.39 µg/m³ (geometric mean 118.59), and plasma Mn levels were significantly elevated in the exposed group (0.704 ± 0.2 ng/mL) compared to controls (0.397 ± 0.18 in controls). Results: LC-MS/MS-based pathway analyses revealed disruptions in olfactory signaling, mitochondrial fatty acid β-oxidation, biogenic amine synthesis, transmembrane transport, and choline metabolism. Simoa analysis showed notable alterations in ADRD-related plasma biomarkers. Protein microarray revealed significant differences (p < 0.05) in antibodies targeting neuronal and autoimmune proteins, including Aβ (25–35), GFAP, serotonin, NOVA1, and Siglec-1/CD169. Conclusion: These findings suggest Mn exposure is associated with neurodegenerative biomarker alterations and disrupted biological pathways relevant to cognitive decline. Full article