Advances in Computational Biology for Diagnosing Neurodegenerative Diseases: A Comprehensive Review.

The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to contemporary healthcare. The emergence of artificial intelligence has fundamentally changed the diagnostic picture by providing effective and early means of identifying these crippling illnesses. As a subset of computational intelligence, machine-learning algorithms have become very effective tools for the analysis of large datasets that include genetic, imaging, and clinical data. Moreover, multi-modal data integration, which includes information from brain imaging (MRI, PET scans), genetic profiles, and clinical evaluations, is made easier by computational intelligence. A thorough knowledge of the course of the illness is made possible by this consolidative method, which also facilitates the creation of predictive models for early medical evaluation and outcome prediction. Furthermore, there has been a great deal of promise shown by the use of artificial intelligence to neuroimaging analysis. Sophisticated image processing methods combined with machine learning algorithms make it possible to identify functional and structural anomalies in the brain, which often act as early indicators of neurodegenerative diseases. This chapter examines how computational intelligence plays a critical role in improving the diagnosis of neurodegenerative diseases such as Parkinson's, Alzheimer's, etc. To sum up, computational intelligence provides a revolutionary approach for improving the identification of neurodegenerative illnesses. In the battle against these difficult disorders, embracing and improving these computational techniques will surely pave the path for more individualized therapy and more therapies that are successful.

Central nervous system-derived extracellular vesicles: the next generation of neural circulating biomarkers?

The central nervous system (CNS) is integrated by glial and neuronal cells, and both release extracellular vesicles (EVs) that participate in CNS homeostasis. EVs could be one of the best candidates to operate as nanosized biological platforms for analysing multidimensional bioactive cargos, which are protected during systemic circulation of EVs. Having a window into the molecular level processes that are happening in the CNS could open a new avenue in CNS research. This raises a particular point of interest: can CNS-derived EVs in blood serve as circulating biomarkers that reflect the pathological status of neurological diseases? L1 cell adhesion molecule (L1CAM) is a widely reported biomarker to identify CNS-derived EVs in peripheral blood. However, it has been demonstrated that L1CAM is also expressed outside the CNS. Given that principal data related to neurodegenerative diseases, such as multiple sclerosis, amyotrophic lateral sclerosis, Parkinson's disease and Alzheimer's disease were obtained using L1CAM-positive EVs, efforts to overcome present challenges related to its specificity are required. In this sense, other surface biomarkers for CNS-derived EVs, such as glutamate aspartate transporter (GLAST) and myelin oligodendrocyte glycoprotein (MOG), among others, have started to be used. Establishing a panel of EV biomarkers to analyse CNS-derived EVs in blood could increase the specificity and sensitivity necessary for these types of studies. This review covers the main evidence related to CNS-derived EVs in cerebrospinal fluid and blood samples of patients with neurological diseases, focusing on the reported biomarkers and the technical possibilities for their isolation. EVs are emerging as a mirror of brain physiopathology, reflecting both localized and systemic changes. Therefore, when the technical hindrances for EV research and clinical applications are overcome, novel disease-specific panels of EV biomarkers would be discovered to facilitate transformation from traditional medicine to personalized medicine.

Unveiling brain disorders using liquid biopsy and Raman spectroscopy.

Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.

Advancements in Cerebrospinal Fluid Biosensors: Bridging the Gap from Early Diagnosis to the Detection of Rare Diseases.

Cerebrospinal fluid (CSF) is a body fluid that can be used for the diagnosis of various diseases. However, CSF collection requires an invasive and painful procedure called a lumbar puncture (LP). This procedure is applied to any patient with a known risk of central nervous system (CNS) damage or neurodegenerative disease, regardless of their age range. Hence, this can be a very painful procedure, especially in infants and elderly patients. On the other hand, the detection of disease biomarkers in CSF makes diagnoses as accurate as possible. This review aims to explore novel electrochemical biosensing platforms that have impacted biomedical science. Biosensors have emerged as techniques to accelerate the detection of known biomarkers in body fluids such as CSF. Biosensors can be designed and modified in various ways and shapes according to their ultimate applications to detect and quantify biomarkers of interest. This process can also significantly influence the detection and diagnosis of CSF. Hence, it is important to understand the role of this technology in the rapidly progressing field of biomedical science.

Evaluation of walking activity and gait to identify physical and mental fatigue in neurodegenerative and immune disorders: preliminary insights from the IDEA-FAST feasibility study.

BACKGROUND: Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue. This study explored the relationships between gait characteristics derived from an inertial measurement unit (IMU) and patient-reported fatigue in the IDEA-FAST feasibility study. METHODS: Participants with IMIDs and NDDs (Parkinson's disease (PD), Huntington's disease (HD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjogren's syndrome (PSS), and inflammatory bowel disease (IBD)) wore a lower-back IMU continuously for up to 10 days at home. Concurrently, participants completed PROs (physical fatigue (PF) and mental fatigue (MF)) up to four times a day. Macro (volume, variability, pattern, and acceleration vector magnitude) and micro (pace, rhythm, variability, asymmetry, and postural control) gait characteristics were extracted from the accelerometer data. The associations of these measures with the PROs were evaluated using a generalised linear mixed-effects model (GLMM) and binary classification with machine learning. RESULTS: Data were recorded from 72 participants: PD = 13, HD = 9, RA = 12, SLE = 9, PSS = 14, IBD = 15. For the GLMM, the variability of the non-walking bouts length (in seconds) with PF returned the highest conditional R2, 0.165, and with MF the highest marginal R2, 0.0018. For the machine learning classifiers, the highest accuracy of the current analysis was returned by the micro gait characteristics with an intrasubject cross validation method and MF as 56.90% (precision = 43.9%, recall = 51.4%). Overall, the acceleration vector magnitude, bout length variation, postural control, and gait rhythm were the most interesting characteristics for future analysis. CONCLUSIONS: Counterintuitively, the outcomes indicate that there is a weak relationship between typical gait measures and abnormal fatigue. However, factors such as the COVID-19 pandemic may have impacted gait behaviours. Therefore, further investigations with a larger cohort are required to fully understand the relationship between gait and abnormal fatigue.

Tau, Glial Fibrillary Acidic Protein, and Neurofilament Light Chain as Brain Protein Biomarkers in Cerebrospinal Fluid and Blood for Diagnosis of Neurobiological Diseases.

Neurological damage is the pathological substrate of permanent disability in various neurodegenerative disorders. Early detection of this damage, including its identification and quantification, is critical to preventing the disease's progression in the brain. Tau, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), as brain protein biomarkers, have the potential to improve diagnostic accuracy, disease monitoring, prognostic assessment, and treatment efficacy. These biomarkers are released into the cerebrospinal fluid (CSF) and blood proportionally to the degree of neuron and astrocyte damage in different neurological disorders, including stroke, traumatic brain injury, multiple sclerosis, neurodegenerative dementia, and Parkinson's disease. Here, we review how Tau, GFAP, and NfL biomarkers are detected in CSF and blood as crucial diagnostic tools, as well as the levels of these biomarkers used for differentiating a range of neurological diseases and monitoring disease progression. We also discuss a biosensor approach that allows for the real-time detection of multiple biomarkers in various neurodegenerative diseases. This combined detection system of brain protein biomarkers holds significant promise for developing more specific and accurate clinical tools that can identify the type and stage of human neurological diseases with greater precision.

Serum Markers of Neurodegeneration Are Strongly Linked to Heart Failure Severity and Outcome.

BACKGROUND: Cognitive impairment is prevalent in patients with heart failure with reduced ejection fraction (HFrEF), affecting self-care and outcomes. Novel blood-based biomarkers have emerged as potential diagnostic tools for neurodegeneration. OBJECTIVES: This study aimed to assess neurodegeneration in HFrEF by measuring neurofilament light chain (NfL), total tau (t-tau), amyloid beta 40 (Aß40), and amyloid beta 42 (Aß42) in a large, well-characterized cohort. METHODS: The study included 470 patients with HFrEF from a biobank-linked prospective registry at the Medical University of Vienna. High-sensitivity single-molecule assays were used for measurement. Unplanned heart failure (HF) hospitalization and all-cause death were recorded as outcome parameters. RESULTS: All markers, but not the Aß42:Aß40 ratio, correlated with HF severity, ie, N-terminal pro-B-type natriuretic peptide and NYHA functional class, and comorbidity burden and were significantly associated with all-cause death and HF hospitalization (crude HR: all-cause death: NfL: 4.44 [95% CI: 3.02-6.53], t-tau: 5.04 [95% CI: 2.97-8.58], Aß40: 3.90 [95% CI: 2.27-6.72], and Aß42: 5.14 [95% CI: 2.84-9.32]; HF hospitalization: NfL: 2.48 [95% CI: 1.60-3.85], t-tau: 3.44 [95% CI: 1.95-6.04], Aß40: 3.13 [95% CI: 1.84-5.34], and Aß42: 3.48 [95% CI: 1.93-6.27]; P < 0.001 for all). These associations remained statistically significant after multivariate adjustment including N-terminal pro-B-type natriuretic peptide. The discriminatory accuracy of NfL in predicting all-cause mortality was comparable to the well-established risk marker N-terminal pro-B-type natriuretic peptide (C-index: 0.70 vs 0.72; P = 0.225), whereas the C-indices of t-tau, Aß40, Aß42, and the Aß42:Aß40 ratio were significantly lower (P < 0.05 for all). CONCLUSIONS: Neurodegeneration is directly interwoven with the progression of HF. Biomarkers of neurodegeneration, particularly NfL, may help identify patients potentially profiting from a comprehensive neurological work-up. Further research is necessary to test whether early diagnosis or optimized HFrEF treatment can preserve cognitive function.

Reversible encephalitis-like episodes in fragile X-associated tremor/ataxia syndrome: a case report.

BACKGROUND: Fragile X-associated tremor/ataxia syndrome (FXTAS) is a neurodegenerative disorder caused by CGG repeat expansion of FMR1 gene. Both FXTAS and neuronal intranuclear inclusion disease (NIID) belong to polyglycine diseases and present similar clinical, radiological, and pathological features, making it difficult to distinguish these diseases. Reversible encephalitis-like attacks are often observed in NIID. It is unclear whether they are presented in FXTAS and can be used for differential diagnosis of NIID and FXTAS. CASE PRESENTATION: A 63-year-old Chinese male with late-onset gait disturbance, cognitive decline, and reversible attacks of fever, consciousness impairment, dizziness, vomiting, and urinary incontinence underwent neurological assessment and examinations, including laboratory tests, electroencephalogram test, imaging, skin biopsy, and genetic test. Brain MRI showed T2 hyperintensities in middle cerebellar peduncle and cerebrum, in addition to cerebellar atrophy and DWI hyperintensities along the corticomedullary junction. Lesions in the brainstem were observed. Skin biopsy showed p62-positive intranuclear inclusions. The possibilities of hypoglycemia, lactic acidosis, epileptic seizures, and cerebrovascular attacks were excluded. Genetic analysis revealed CGG repeat expansion in FMR1 gene, and the number of repeats was 111. The patient was finally diagnosed as FXTAS. He received supportive treatment as well as symptomatic treatment during hospitalization. His encephalitic symptoms were completely relieved within one week. CONCLUSIONS: This is a detailed report of a case of FXTAS with reversible encephalitis-like episodes. This report provides new information for the possible and rare features of FXTAS, highlighting that encephalitis-like episodes are common in polyglycine diseases and unable to be used for differential diagnosis.

Sample-to-answer salivary miRNA testing: New frontiers in point-of-care diagnostic technologies.

MicroRNA (miRNA), crucial non-coding RNAs, have emerged as key biomarkers in molecular diagnostics, prognosis, and personalized medicine due to their significant role in gene expression regulation. Salivary miRNA, in particular, stands out for its non-invasive collection method and ease of accessibility, offering promising avenues for the development of point-of-care diagnostics for a spectrum of diseases, including cancer, neurodegenerative disorders, and infectious diseases. Such development promises rapid and precise diagnosis, enabling timely treatment. Despite significant advancements in salivary miRNA-based testing, challenges persist in the quantification, multiplexing, sensitivity, and specificity, particularly for miRNA at low concentrations in complex biological mixtures. This work delves into these challenges, focusing on the development and application of salivary miRNA tests for point-of-care use. We explore the biogenesis of salivary miRNA and analyze their quantitative expression and their disease relevance in cancer, infection, and neurodegenerative disorders. We also examined recent progress in miRNA extraction, amplification, and multiplexed detection methods. This study offers a comprehensive view of the development of salivary miRNA-based point-of-care testing (POCT). Its successful advancement could revolutionize the early detection, monitoring, and management of various conditions, enhancing healthcare outcomes. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices.

Vision-based motion capture for the gait analysis of neurodegenerative diseases: A review.

BACKGROUND: Developments in vision-based systems and human pose estimation algorithms have the potential to detect, monitor and intervene early on neurodegenerative diseases through gait analysis. However, the gap between the technology available and actual clinical practice is evident as most clinicians still rely on subjective observational gait analysis or objective marker-based analysis that is time-consuming. RESEARCH QUESTION: This paper aims to examine the main developments of vision-based motion capture and how such advances may be integrated into clinical practice. METHODS: The literature review was conducted in six online databases using Boolean search terms. A commercial system search was also included. A predetermined methodological criterion was then used to assess the quality of the selected articles. RESULTS: A total of seventeen studies were evaluated, with thirteen studies focusing on gait classification systems and four studies on gait measurement systems. Of the gait classification systems, nine studies utilized artificial intelligence-assisted techniques, while four studies employed statistical techniques. The results revealed high correlations of gait features identified by classifier models with existing clinical rating scales. These systems demonstrated generally high classification accuracies and were effective in diagnosing disease severity levels. Gait measurement systems that extract spatiotemporal and kinematic joint information from video data generally found accurate measurements of gait parameters with low mean absolute errors, high intra- and inter-rater reliability. SIGNIFICANCE: Low cost, portable vision-based systems can provide proof of concept for the quantification of gait, expansion of gait assessment tools, remote gait analysis of neurodegenerative diseases and a point of care system for orthotic evaluation. However, certain challenges, including small sample sizes, occlusion risks, and selection bias in training models, need to be addressed. Nevertheless, these systems can serve as complementary tools, equipping clinicians with essential gait information to objectively assess disease severity and tailor personalized treatment for enhanced patient care.

Prevalence of anti-myelin oligodendrocyte glycoprotein antibodies across neuroinflammatory and neurodegenerative diseases.

Inflammatory central nervous system (CNS) diseases, such as multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD), are characterized by humoral immune abnormalities. Anti-MOG antibodies are not specific to MOGAD, with their presence described in MS. Autoantibodies may also be present and play a role in various neurodegenerative diseases. Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease driven by motor neuron dysfunction. While immune involvement in ALS has been recognized, the presence of antibodies targeting CNS myelin antigens has not been established. We aimed to establish a live cell-based assay for quantification of serum anti-MOG IgG1 in patients with CNS diseases, including MS and ALS. In total, 771 serum samples from the John L. Trotter MS Center and the Northeast ALS Consortium were examined using a live cell-based assay for detection of anti-MOG IgG1. Samples from three cohorts were tested in blinded fashion: healthy control (HC) subjects, patients with clinically diagnosed MOGAD, and an experimental group of ALS and MS patients. All samples from established MOGAD cases were positive for anti-MOG antibodies, while all HC samples were negative. Anti-MOG IgG1 was detected in 65 of 658 samples (9.9%) from MS subjects and 4 of 108 (3.7%) samples from ALS subjects. The presence of serum anti-MOG IgG1 in MS and ALS patients raises questions about the contribution of these antibodies to disease pathophysiology as well as accuracy of diagnostic approaches for CNS inflammatory diseases.

The Miami Framework for ALS and related neurodegenerative disorders: an integrated view of phenotype and biology.

Increasing appreciation of the phenotypic and biological overlap between amyotrophic lateral sclerosis (ALS) and frontotemporal dementia, alongside evolving biomarker evidence for a pre-symptomatic stage of disease and observations that this stage of disease might not always be clinically silent, is challenging traditional views of these disorders. These advances have highlighted the need to adapt ingrained notions of these clinical syndromes to include both the full phenotypic continuum - from clinically silent, to prodromal, to clinically manifest - and the expanded phenotypic spectrum that includes ALS, frontotemporal dementia and some movement disorders. The updated clinical paradigms should also align with our understanding of the biology of these disorders, reflected in measurable biomarkers. The Miami Framework, emerging from discussions at the Second International Pre-Symptomatic ALS Workshop in Miami (February 2023; a full list of attendees and their affiliations appears in the Supplementary Information) proposes a classification system built on: first, three parallel phenotypic axes - motor neuron, frontotemporal and extrapyramidal - rather than the unitary approach of combining all phenotypic elements into a single clinical entity; and second, biomarkers that reflect different aspects of the underlying pathology and biology of neurodegeneration. This framework decouples clinical syndromes from biomarker evidence of disease and builds on experiences from other neurodegenerative diseases to offer a unified approach to specifying the pleiotropic clinical manifestations of disease and describing the trajectory of emergent biomarkers.

The clinical importance of suspected non-Alzheimer disease pathophysiology.

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

Biomarkers of neurodegeneration in schizophrenia: systematic review and meta-analysis.

QUESTION: Does neurodegenerative disease underlie the increased rate of dementia observed in older people with schizophrenia? Several studies have reported a higher prevalence of dementia in people with schizophrenia compared with the general population. This may reflect a higher risk of developing neurodegenerative diseases such as vascular dementia or Alzheimer's disease (AD). Alternatively, this may reflect non-pathological, age-related cognitive decline in a population with low cognitive reserve. STUDY SELECTION AND ANALYSIS: We reviewed papers that compared postmortem findings, hippocampal MRI volume or cerebrospinal fluid (CSF) markers of AD, between patients with schizophrenia with evidence of cognitive impairment (age ≥45 years) with controls. We subsequently performed a meta-analysis of postmortem studies that compared amyloid-ß plaques (APs) or neurofibrillary tangles (NFTs) in cognitively impaired patients with schizophrenia to normal controls or an AD group. FINDINGS: No studies found a significant increase of APs or NFTs in cognitively impaired patients with schizophrenia compared with controls. All postmortem studies that compared APs or NFTs in patients with schizophrenia to an AD group found significantly more APs or NFTs in AD. No studies found a significant differences in CSF total tau or phosphorylated tau between patients with schizophrenia and controls. The two studies which compared CSF Aß42 between patients with schizophrenia and controls found significantly decreased CSF Aß42 in schizophrenia compared with controls. Hippocampal volume findings were mixed. CONCLUSIONS: Studies have not found higher rates of AD-related pathology in cognitively impaired individuals with schizophrenia compared with controls. Higher rates of dementia identified in population studies may reflect a lack of specificity in clinical diagnostic tools used to diagnose dementia.

Fahr's disease with neuropsychiatric symptoms and intermittent course: a case report.

Fahr's disease is a rare neurodegenerative disorder with brain calcifications and neuropsychiatric symptoms. It can have variable phenotypic expression and intermittent symptomatology, making diagnosis challenging. In this report, we describe a young female patient presenting with symptoms of psychosis and confusion, which could be indicative of a delirium superimposed on the cerebral vulnerability associated with Fahr's disease. Notably, about two years prior, she experienced multiple episodes of tonic-clonic seizures that spontaneously resolved without pharmacological intervention. She had no previous psychiatric history. Following comprehensive investigations, other organic causes were ruled out, and Fahr's disease was diagnosed based on bilateral symmetrical brain calcifications seen on a head CT scan. Her treatment regimen encompassed antipsychotics and anticonvulsants. This case highlights the importance of considering Fahr's disease as a differential diagnosis in patients with new-onset neuropsychiatric symptoms. The case also explores the atypical early onset and intermittent nature of symptoms in the absence of a positive family history, highlighting the complexity of Fahr's disease. A multidisciplinary approach and regular follow-up are crucial for optimizing patient care and monitoring disease progression. Further research is needed to enhance our understanding of Fahr's disease and develop standardized treatment strategies for this rare condition.

Tau- and α-synuclein-targeted gold nanoparticles: applications, opportunities, and future outlooks in the diagnosis and therapy of neurodegenerative diseases.

The use of nanomaterials in medicine offers multiple opportunities to address neurodegenerative disorders such as Alzheimer's and Parkinson's disease. These diseases are a significant burden for society and the health system, affecting millions of people worldwide without sensitive and selective diagnostic methodologies or effective treatments to stop their progression. In this sense, the use of gold nanoparticles is a promising tool due to their unique properties at the nanometric level. They can be functionalized with specific molecules to selectively target pathological proteins such as Tau and α-synuclein for Alzheimer's and Parkinson's disease, respectively. Additionally, these proteins are used as diagnostic biomarkers, wherein gold nanoparticles play a key role in enhancing their signal, even at the low concentrations present in biological samples such as blood or cerebrospinal fluid, thus enabling an early and accurate diagnosis. On the other hand, gold nanoparticles act as drug delivery platforms, bringing therapeutic agents directly into the brain, improving treatment efficiency and precision, and reducing side effects in healthy tissues. However, despite the exciting potential of gold nanoparticles, it is crucial to address the challenges and issues associated with their use in the medical field before they can be widely applied in clinical settings. It is critical to ensure the safety and biocompatibility of these nanomaterials in the context of the central nervous system. Therefore, rigorous preclinical and clinical studies are needed to assess the efficacy and feasibility of these strategies in patients. Since there is scarce and sometimes contradictory literature about their use in this context, the main aim of this review is to discuss and analyze the current state-of-the-art of gold nanoparticles in relation to delivery, diagnosis, and therapy for Alzheimer's and Parkinson's disease, as well as recent research about their use in preclinical, clinical, and emerging research areas.

Pathologic and cognitive correlates of plasma biomarkers in neurodegenerative disease.

INTRODUCTION: We investigate pathological correlates of plasma phosphorylated tau 181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) across a clinically diverse spectrum of neurodegenerative disease, including normal cognition (NormCog) and impaired cognition (ImpCog). METHODS: Participants were NormCog (n = 132) and ImpCog (n = 461), with confirmed ß-amyloid (Aß+/-) status (cerebrospinal fluid, positron emission tomography, autopsy) and single molecule array plasma measurements. Logistic regression and receiver operating characteristic (ROC) area under the curve (AUC) tested how combining plasma analytes discriminated Aß+ from Aß-. Survival analyses tested time to clinical dementia rating (global CDR) progression. RESULTS: Multivariable models (p-tau+GFAP+NfL) had the best performance to detect Aß+ in NormCog (ROCAUC = 0.87) and ImpCog (ROCAUC = 0.87). Survival analyses demonstrated that higher NfL best predicted faster CDR progression for both Aß+ (hazard ratio [HR] = 2.94; p = 8.1e-06) and Aß- individuals (HR = 3.11; p = 2.6e-09). DISCUSSION: Combining plasma biomarkers can optimize detection of Alzheimer's disease (AD) pathology across cognitively normal and clinically diverse neurodegenerative disease. HIGHLIGHTS: Participants were clinically heterogeneous, with autopsy- or biomarker-confirmed Aß. Combining plasma p-tau181, GFAP, and NfL improved diagnostic accuracy for Aß status. Diagnosis by plasma biomarkers is more accurate in amnestic AD than nonamnestic AD. Plasma analytes show independent associations with tau PET and post mortem Aß/tau. Plasma NfL predicted longitudinal cognitive decline in both Aß+ and Aß- individuals.

Exosomes for neurodegenerative diseases: diagnosis and targeted therapy.

PURPOSE OF REVIEW: Neurodegenerative diseases are still challenging clinical issues, with no curative interventions available and early, accurate diagnosis remaining difficult. Finding solutions to them is of great importance. In this review, we discuss possible exosomal diagnostic biomarkers and explore current explorations in exosome-targeted therapy for some common neurodegenerative diseases, offering insights into the clinical transformation of exosomes in this field. RECENT FINDINGS: The burgeoning research on exosomes has shed light on their potential applications in disease diagnosis and treatment. As a type of extracellular vesicles, exosomes are capable of crossing the blood - brain barrier and exist in various body fluids, whose components can reflect pathophysiological changes in the brain. In addition, they can deliver specific drugs to brain tissue, and even possess certain therapeutic effects themselves. And the recent advancements in engineering modification technology have further enabled exosomes to selectively target specific sites, facilitating the possibility of targeted therapy for neurodegenerative diseases. The unique properties of exosomes give them great potential in the diagnosis and treatment of neurodegenerative diseases, and provide novel ideas for dealing with such diseases.

Biomarkers for Managing Neurodegenerative Diseases.

Neurological disorders are the leading cause of cognitive and physical disability worldwide, affecting 15% of the global population. Due to the demographics of aging, the prevalence of neurological disorders, including neurodegenerative diseases, will double over the next two decades. Unfortunately, while available therapies provide symptomatic relief for cognitive and motor impairment, there is an urgent unmet need to develop disease-modifying therapies that slow the rate of pathological progression. In that context, biomarkers could identify at-risk and prodromal patients, monitor disease progression, track responses to therapy, and parse the causality of molecular events to identify novel targets for further clinical investigation. Thus, identifying biomarkers that discriminate between diseases and reflect specific stages of pathology would catalyze the discovery and development of therapeutic targets. This review will describe the prevalence, known mechanisms, ongoing or recently concluded therapeutic clinical trials, and biomarkers of three of the most prevalent neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and Parkinson's disease (PD).