Search Results (500)

Glial fibrillary acidic protein (GFAP) has been shown to be a reliable biomarker for detecting neurological disorders. Recently, we developed the Lumipulse G GFAP plasma assay, which is a commercially available tool. Compared to existing assays, the LUMIPLSE G platform offers the high-throughput, rapid, and fully automated quantification of biomarkers, enabling more standardized and accessible clinical study. In this study, we evaluated this assay using cerebrospinal fluid (CSF) samples. Assessing GFAP in CSF may provide more direct insights into central nervous system pathology than plasma and could improve the characterization of Alzheimer’s disease (AD) stages and support treatment monitoring. The LUMIPULSE G system is a chemiluminescent enzyme immunoassay (CLEIA) platform equipped with full automation, utilizing specialized cartridges to process samples within 30 min. The assay, which employs a pair of proprietary monoclonal antibodies targeting GFAP, was evaluated for clinical performance using 30 CSF samples from patients diagnosed with AD, patients with mild cognitive impairment (MCI), and cognitively unimpaired (CU) individuals, with 10 samples from each group. In addition, levels of β-amyloid 1–40 (Aβ40), β-amyloid 1–42 (Aβ42), and pTau181 were simultaneously measured. The Lumipulse G GFAP assay significantly differentiated (p < 0.05) between the amyloid accumulation and non-amyloid accumulation groups, as classified based on the CSF Aβ test. Furthermore, GFAP showed a moderate correlation with pTau181 (r = 0.588), as determined based on Spearman’s rank correlation coefficient. Moreover, receiver operating characteristic (ROC) analysis was performed to determine the performance of GFAP in distinguishing amyloid-positive and amyloid-negative subjects, with an area under the curve (AUC) of 0.72 (0.50–0.93). When stratified by CSF pTau181 positivity, GFAP demonstrated an improved diagnostic accuracy, achieving an AUC of 0.86 (95% CI: 0.68–1.00). This study demonstrates that the Lumipulse G GFAP assay, when applied to CSF samples, has the potential to differentiate AD from non-AD cases, particularly suggesting its utility in detecting tau-related pathology. While GFAP has previously been established as a biomarker for AD, our findings highlight that combining GFAP with other biomarkers such as Aβ40, Aβ42, and pTau181 may enhance the understanding of AD pathogenesis, disease staging, and possibly treatment responses. These findings suggest that GFAP may serve as a complementary biomarker reflecting astroglial reactivity associated with tau positivity, alongside established biomarkers such as Aβ40, Aβ42, and pTau181. However, since GFAP levels may also be elevated in other neurological disorders beyond AD, further investigation into these conditions is required. Full article

Background: Artificial intelligence (AI) is reshaping neuroimaging workflows for Alzheimer’s disease (AD) diagnosis, particularly through PET and MRI analysis advances. Since the FDA approval of Tauvid, a PET tracer targeting tau pathology, there has been a notable increase in studies applying AI to neuroimaging data. This narrative review synthesizes recent, high-impact literature to highlight clinically relevant AI applications in AD imaging. Methods: This review examined peer-reviewed studies published between January 2020 and January 2025, focusing on the use of AI, including machine learning, deep learning, and hybrid models for diagnostic and prognostic tasks in AD using PET and/or MRI. Studies were identified through targeted PubMed, Scopus, and Embase searches, emphasizing methodological diversity and clinical relevance. Results: A total of 111 studies were categorized into five thematic areas: Image preprocessing and segmentation, diagnostic classification, prognosis and disease staging, multimodal data fusion, and emerging innovations. Deep learning models such as convolutional neural networks (CNNs), generative adversarial networks (GANs), and transformer-based architectures were widely employed by the research community in the field of AD. At the same time, several models reported strong diagnostic performance, but methodological challenges such as reproducibility, small sample sizes, and lack of external validation limit clinical translation. Trends in explainable AI, synthetic imaging, and integration of clinical biomarkers are also discussed. Conclusions: AI is rapidly advancing the field of AD imaging, offering tools for enhanced segmentation, staging, and early diagnosis. Multimodal approaches and biomarker-guided models show particular promise. However, future research must focus on reproducibility, interpretability, and standardized validation to bridge the gap between research and clinical practice. Full article

Growing evidence suggests that Reelin signals and cleavages are affected in neurodegenerative diseases, prospecting a potential role for Reelin in the pathogenesis of neurodegenerative processes occurring in insulted retinas. We sought to determine whether Reelin, Aβ1-42, FTH1 and TAU proteins accumulate in ocular fluids of idiopathic epiretinal membrane (iERM) specimens and whether such accumulations depend on disease severity. Comparisons and correlation studies were used to verify the hypothesis of a Reelin, Aβ1-42, TAU and FTH1 marker expressions in this vitreoretinal disease, extending the knowledge on the pathological spectrum of neurodegenerative eye diseases. Aqueous, vitreous and peeled-off ERM samples were collected from patients who had undergone vitrectomy and grouped according to disease severity. We found out that Reelin and Aβ1-42 were expressed in ocular fluids and affected ERMs depending on disease severity. At stage 3, higher Reelin and Aβ1-42 immunofluorescence staining was detected in ERMs, in agreement with the higher Reelin, Aβ1-42, FTH1 and TAU transcript expressions by RT-PCR. Differential expressions of transcripts specific to Aβ1-42, FTH1, GFAP and TAU occurred in vitreal hyalocytes and astrocytes, which selectively responded to vitreal exposure. This is the first study reporting the association between Reelin and ERM disease, highlighting the potential role of Reelin in neurodegenerating and Drusen-affected retinas. The potential association of neurodegenerative mediators with ERM would suggest that part of the neuronal damage activated at the vitreoretinal interphase might be driven by Reelin. Full article

Cathepsins, a family of lysosomal proteases, play critical roles in maintaining cellular homeostasis through protein degradation and modulation of immune responses. In the central nervous system (CNS), their functions extend beyond classical proteolysis, influencing neuroinflammation, synaptic remodeling, and neurodegeneration. Emerging evidence underscores the crucial role of microglial cathepsins in the pathophysiology of several neurological disorders. This review synthesizes current knowledge on the involvement of cathepsins in a spectrum of CNS diseases, including Parkinson’s disease, Alzheimer’s disease, multiple sclerosis, amyotrophic lateral sclerosis, epilepsy, Huntington’s disease, and ischemic stroke. We highlight how specific cathepsins contribute to disease progression by modulating key pathological processes such as α-synuclein and amyloid-β clearance, tau degradation, lysosomal dysfunction, neuroinflammation, and demyelination. Notably, several cathepsins demonstrate both neuroprotective and pathogenic roles depending on disease context and expression levels. Additionally, the balance between cathepsins and their endogenous inhibitors, such as cystatins, emerges as a critical factor in CNS pathology. While cathepsins represent promising biomarkers and therapeutic targets, significant gaps remain in our understanding of their mechanistic roles across diseases. Future studies focusing on their regulation, substrate specificity, and interplay with genetic and epigenetic factors may yield novel strategies for early diagnosis and disease-modifying treatments in neurology. Full article

Background and Objectives: Over the past few years, there has been a significant shift in focus from developing better diagnostic tools to detecting Alzheimer’s disease (AD) earlier and initiating treatment interventions. This review will explore four main objectives: (a) the role of biomarkers in enhancing the diagnostic accuracy of AD, highlighting the major strides that have been made in recent years; (b) the role of neuropsychological testing in identifying biomarkers of AD, including the relationship between cognitive performance and neuroimaging biomarkers; (c) the amyloid hypothesis and possible molecular mechanisms of AD; and (d) the innovative AD therapeutics and the challenges and limitations of AD research. Materials and Methods: We have searched PubMed and Scopus databases for peer-reviewed research articles published in English (preclinical and clinical studies as well as relevant reviews and meta-analyses) investigating the molecular mechanisms, biomarkers, and treatments of AD. Results: Genome-wide association studies (GWASs) discovered 37 loci associated with AD risk. Core 1 biomarkers (α-amyloid Aβ42, phosphorylated tau, and amyloid PET) detect early AD phases, identifying both symptomatic and asymptomatic individuals, while core 2 biomarkers inform the short-term progression risk in individuals without symptoms. The recurrent failures of Aβ-targeted clinical studies undermine the amyloid cascade hypothesis and the objectives of AD medication development. The molecular mechanisms of AD include the accumulation of amyloid plaques and tau protein, vascular dysfunction, neuroinflammation, oxidative stress, and lipid metabolism dysregulation. Significant advancements in drug delivery technologies, such as focused Low-Ultrasound Stem, T cells, exosomes, nanoparticles, transferin, nicotinic and acetylcholine receptors, and glutathione transporters, are aimed at overcoming the BBB to enhance treatment efficacy for AD. Aducanumab and Lecanemab are IgG1 monoclonal antibodies that retard the progression of AD. BACE inhibitors have been explored as a therapeutic strategy for AD. Gene therapies targeting APOE using the CRISPR/Cas9 genome-editing system are another therapeutic avenue. Conclusions: Classic neurodegenerative biomarkers have emerged as powerful tools for enhancing the diagnostic accuracy of AD. Despite the supporting evidence, the amyloid hypothesis has several unresolved issues. Novel monoclonal antibodies may halt the AD course. Advances in delivery systems across the BBB are promising for the efficacy of AD treatments. Full article

Dementia with Lewy bodies (DLB), the second common primary degenerative neurocognitive disorder after Alzheimer disease (AD), frequently presents concurrent co-pathologies that impact clinical presentation and progression. Neuropathological studies have demonstrated a high prevalence of coexistent AD-related neuropathological changes (ADNC), TAR DNA-binding protein 43 (TDP-43) proteinopathies, and cardiac and aging-related disorders, while frontotemporal lobar degeneration (FTLD) and tau-related syndromes play a minor role as DLB-related co-pathologies. Cerebrovascular lesions, including cerebral amyloid angiopathy, are the most prevalent non-neurodegenerative co-pathologies. Cardiovascular disorders, hypertension, and hyperlipidemia are also frequent comorbidities. Due to their high prevalence and clinical impact on DLB patients, clinical trials should account for these and other co-pathologies in their design and selection. Evaluation of these co-pathologies using and interpreting biomarkers may allow greater clinical diagnostic accuracy and the opportunity to better predict clinical progression. Therefore, there is an increasing need for biomarkers in dementia research. This review discusses the kind and frequency of the different co-pathologies in DLB and their clinical impact. It evaluates the possible value of disease-specific biomarkers and how they are helpful in the assessment and prevention of DLB and its co-pathologies. Full article

Tau protein is essential for the structural stability of neurons, particularly through its role in microtubule assembly and axonal transport. However, when abnormally hyperphosphorylated or cleaved, Tau can aggregate into insoluble forms that disrupt neuronal function, contributing to the pathogenesis of neurodegenerative diseases such as Alzheimer’s disease (AD). Emerging evidence suggests that similar Tau-related alterations may occur in individuals with chronic exposure to psychoactive substances. This review compiles experimental, clinical, and postmortem findings that collectively indicate a substance-specific influence on Tau dynamics. Alcohol and opioids, for instance, promote Tau hyperphosphorylation and fragmentation through the activation of kinases such as GSK-3β and CDK5, as well as proteases like caspase-3, leading to neuroinflammation and microglial activation. Stimulants and dissociatives disrupt insulin signaling, increase oxidative stress, and impair endosomal trafficking, all of which can exacerbate Tau pathology. In contrast, cannabinoids and psychedelics may exert protective effects by modulating kinase activity, reducing inflammation, or enhancing neuroplasticity. Psychedelic compounds such as psilocybin and harmine have been demonstrated to decrease Tau phosphorylation and facilitate cognitive restoration in animal models. Although the molecular mechanisms differ across substances, Tau consistently emerges as a convergent target altered in substance-related cognitive disorders. Understanding these pathways may provide not only mechanistic insights into drug-induced neurotoxicity but also identify Tau as a valuable biomarker and potential therapeutic target for the prevention or treatment of cognitive decline associated with substance use. Full article

Oxidative stress is a defining and pervasive driver of neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS). As a molecular accelerant, reactive oxygen species (ROS) and reactive nitrogen species (RNS) compromise mitochondrial function, amplify lipid peroxidation, induce protein misfolding, and promote chronic neuroinflammation, creating a positive feedback loop of neuronal damage and cognitive decline. Despite its centrality in promoting disease progression, attempts to neutralize oxidative stress with monotherapeutic antioxidants have largely failed owing to the multifactorial redox imbalance affecting each patient and their corresponding variation. We are now at the threshold of precision redox medicine, driven by advances in syndromic multi-omics integration, Artificial Intelligence biomarker identification, and the precision of patient-specific therapeutic interventions. This paper will aim to reveal a mechanistically deep assessment of oxidative stress and its contribution to diseases of neurodegeneration, with an emphasis on oxidatively modified proteins (e.g., carbonylated tau, nitrated α-synuclein), lipid peroxidation biomarkers (F2-isoprostanes, 4-HNE), and DNA damage (8-OHdG) as significant biomarkers of disease progression. We will critically examine the majority of clinical trial studies investigating mitochondria-targeted antioxidants (e.g., MitoQ, SS-31), Nrf2 activators (e.g., dimethyl fumarate, sulforaphane), and epigenetic reprogramming schemes aiming to re-establish antioxidant defenses and repair redox damage at the molecular level of biology. Emerging solutions that involve nanoparticles (e.g., antioxidant delivery systems) and CRISPR (e.g., correction of mutations in SOD1 and GPx1) have the potential to transform therapeutic approaches to treatment for these diseases by cutting the time required to realize meaningful impacts and meaningful treatment. This paper will argue that with the connection between molecular biology and progress in clinical hyperbole, dynamic multi-targeted interventions will define the treatment of neurodegenerative diseases in the transition from disease amelioration to disease modification or perhaps reversal. With these innovations at our doorstep, the future offers remarkable possibilities in translating network-based biomarker discovery, AI-powered patient stratification, and adaptive combination therapies into individualized/long-lasting neuroprotection. The question is no longer if we will neutralize oxidative stress; it is how likely we will achieve success in the new frontier of neurodegenerative disease therapies. Full article

Oxidative stress, driven by impaired antioxidant defence systems, is a major contributor to cognitive decline and neurodegenerative processes in brain ageing. This study investigates the neuroprotective effects of a natural compound mixture—composed of Hericium erinaceus, Palmitoylethanolamide, Bilberry extract, and Centella asiatica—using a multi-step in vitro strategy. An initial evaluation in a 3D intestinal epithelial model demonstrated that the formulation preserves barrier integrity and may be bioaccessible, as evidenced by transepithelial electrical resistance (TEER) and the expression of tight junctions. Subsequent analysis in an integrated gut–brain axis model under oxidative stress conditions revealed that the formulation significantly reduces inflammatory markers (NF-κB, TNF-α, IL-1β, and IL-6; about 1.5-fold vs. H₂O₂), reactive oxygen species (about 2-fold vs. H₂O₂), and nitric oxide levels (about 1.2-fold vs. H₂O₂). Additionally, it enhances mitochondrial activity while also improving antioxidant responses. In a co-culture of neuronal and astrocytic cells, the combination upregulates neurotrophic factors such as BDNF and NGF (about 2.3-fold and 1.9-fold vs. H₂O₂). Crucially, the formulation also modulates key biomarkers associated with cognitive decline, reducing APP and phosphorylated tau levels (about 98% and 1.6-fold vs. H₂O₂) while increasing Sirtuin 1 and Nrf2 expression (about 3.6-fold and 3-fold vs. H₂O₂). These findings suggest that this nutraceutical combination may support the cellular pathways involved in neuronal resilience and healthy brain ageing, offering potential as a functional food ingredient or dietary supplement. Full article

Recent findings highlight that Reelin, a glycoprotein involved in neural development, synaptic plasticity, and neuroinflammation, plays some specific roles in neurodegenerative disorders associated with aging, such as age-related macular degeneration (AMD) and Alzheimer’s disease (AD). Reelin modulates synaptic function and guarantees homeostasis in neuronal-associated organs/tissues (brain and retina). The expression of Reelin is dysregulated in these neurological disorders, showing common pathways depending on chronic neurogenic inflammation and/or dysregulation of the extracellular matrix in which Reelin plays outstanding roles. Recently, the relationship between AMD and AD has gained increasing attention as they share many common risk factors (aging, genetic/epigenetic background, smoking, and malnutrition) and histopathological lesions, supporting certain pathophysiological crosstalk between these two diseases, especially regarding neuroinflammation, oxidative stress, and vascular complications. Outside the nervous system, Reelin is largely produced at the gastrointestinal epithelial level, in close association with innervated regions. The expression of Reelin receptors inside the gut suggests interesting aspects in the field of the gut–brain–eye axis, as dysregulation of the intestinal microbiota has been frequently described in neurodegenerative and behavioral disorders (AD, autism, and anxiety and/or depression), most probably linked to inflammatory, neurogenic mediators, including Reelin. Herein we examined previous and recent findings on Reelin and neurodegenerative disorders, offering findings on Reelin’s potential relation with the gut–brain and gut–brain–eye axes and providing novel attractive hypotheses on the gut–brain–eye link through neuromodulator and microbiota interplay. Neurodegenerative disorders will represent the ground for a future starting point for linking the common neurodegenerative biomarkers (β-amyloid and tau) and the new proteins probably engaged in counteracting neurodegeneration and synaptic loss. Full article

With a rapidly growing incidence and prevalence, Alzheimer’s disease (AD) is rapidly becoming one of the most disabling, lethal, and expensive diseases of the century. To diagnose AD as early as possible, the scientific world struggles to find reliable and non-invasive biomarkers that could predict the conversion of mild cognitive impairment to AD and delineate the ongoing pathogenic vicious pathways to be targeted with therapy. Research supports the use of blood biomarkers, such as Aβ_1-42/Aβ_1-40 ratio, phosphorylated tau181, and p-tau217 for diagnostic purposes, although the cut-offs are not clearly established and can depend on the assays used. For more accurate diagnosis, markers of neurodegeneration (neurofilament light) and neuroinflammation (glial fibrillary acidic protein) could be introduced in the biomarker panel. The recent approval of the Lumipulse G p-tau217/Aβ_1-42 plasma ratio by the FDA for the early detection of amyloid plaques associated with Alzheimer’s disease in adult patients, aged 55 years and older, exhibiting signs and symptoms of the disease represents a significant advancement in the diagnosis of Alzheimer’s disease, offering a more accessible and less invasive way to diagnose this devastating disease and allow potentially earlier access to treatment options. Full article

The human Tau protein stands for one of the most conspicuous and crucial hallmarks of Alzheimer’s disease (AD) diagnosis, along with other tauopathies. However, the assay for direct detection of tiny Tau protein concentrations in human samples continues to pose a significant challenge for the early diagnosis of AD. Thus, an amplification-based strategy is required. In this proposed work, we established an impedimetric immunosensor to detect human Tau-441 protein in PBS buffer using a sandwich approach, wherein we employed two distinct monoclonal antibodies (HT7 and BT2) that specifically recognize the amino acids 159–198 of the target protein. Through this strategy, we were able to detect as low as 0.08 pg/mL. These findings were attributed to the use of a biotinylated antibody (BT2)-streptavidin complex, which facilitated the amplification of the normalized signal, resulting in a lower limit of detection in comparison to the directly based immunosensors. Subsequently, we investigated the designed immunosensor to assess the assay’s selectivity in the presence of different off-targets, and no cross-interaction was recorded. The outcomes of our study provide valuable new insights into the application of sandwich-based assay as a highly sensitive and selective immunosensor for the detection of small protein. Full article

Neurodegenerative diseases (NDDs) such as Alzheimer’s, Parkinson’s, ALS, and Huntington’s pose a growing global challenge due to their complex pathobiology and aging demographics. Once considered as cellular debris, small extracellular vesicles (sEVs) are now recognized as active mediators of intercellular signaling in NDD progression. These nanovesicles (~30–150 nm), capable of crossing the blood–brain barrier, carry pathological proteins, RNAs, and lipids, facilitating the spread of toxic species like Aβ, tau, TDP-43, and α-synuclein. sEVs are increasingly recognized as valuable diagnostic tools, outperforming traditional CSF biomarkers in early detection and disease monitoring. On the therapeutic front, engineered sEVs offer a promising platform for CNS-targeted delivery of siRNAs, CRISPR tools, and neuroprotective agents, demonstrating efficacy in preclinical models. However, translational hurdles persist, including standardization, scalability, and regulatory alignment. Promising solutions are emerging, such as CRISPR-based barcoding, which enables high-resolution tracking of vesicle biodistribution; AI-guided analytics to enhance quality control; and coordinated regulatory efforts by the FDA, EMA, and ISEV aimed at unifying identity and purity criteria under forthcoming Minimal Information for Studies of Extracellular Vesicles (MISEV) guidelines. This review critically examines the mechanistic roles, diagnostic potential, and therapeutic applications of sEVs in NDDs, and outlines key strategies for clinical translation. Full article

Background: Mild Cognitive Impairment (MCI) represents an intermediate stage between normal cognitive aging and Alzheimer’s Disease (AD). Early and accurate identification of MCI is crucial for implementing interventions that may delay or prevent further cognitive decline. This study aims to develop a machine learning-based model for differentiating between Cognitively Normal (CN) individuals and MCI patients using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Methods: An ensemble classification approach was designed by integrating Extra Trees, Random Forest, and Light Gradient Boosting Machine (LightGBM) algorithms. Feature selection emphasized clinically relevant biomarkers, including Amyloid-β 42, phosphorylated tau, diastolic blood pressure, age, and gender. The dataset was split into training and held-out test sets. A probability thresholding strategy was employed to flag uncertain predictions for potential deferral, enhancing model reliability in borderline cases. Results: The final ensemble model achieved an accuracy of 83.2%, a recall of 80.2%, and a precision of 86.3% on the independent test set. The probability thresholding mechanism flagged 23.3% of cases as uncertain, allowing the system to abstain from low-confidence predictions. This strategy improved clinical interpretability and minimized the risk of misclassification in ambiguous cases. Conclusions: The proposed AI-driven ensemble model demonstrates strong performance in classifying MCI versus CN individuals using multimodal ADNI data. Incorporating a deferral mechanism through uncertainty estimation further enhances the model’s clinical utility. These findings support the integration of machine learning tools into early screening workflows for cognitive impairment. Full article

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of amyloid-β plaques, tau hyperphosphorylation, and chronic neuroinflammation. Emerging evidence suggests a crucial role of lipid signaling pathways in AD pathogenesis, particularly those mediated by autotaxin (ATX) and lysophosphatidic acid (LPA). ATX, an enzyme responsible for LPA production, has been implicated in neuroinflammatory processes, blood–brain barrier dysfunction, and neuronal degeneration. LPA signaling, through its interaction with specific G-protein-coupled receptors, influences neuroinflammation, synaptic plasticity, and tau pathology, all of which contribute to AD progression. This review synthesizes recent findings on the ATX/LPA axis in AD, exploring its potential as a biomarker and therapeutic target. Understanding the mechanistic links between ATX, LPA, and AD pathology may open new avenues for disease-modifying strategies. Full article