Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer's dementia

Present and Future of Blood-Based Biomarkers of Alzheimer's Disease: Beyond the Classics

The field of blood-based biomarkers for Alzheimer's disease (AD) has advanced at an incredible pace, especially after the development of sensitive analytic platforms that can facilitate large-scale screening. Such screening will be important when more sophisticated diagnostic methods are scarce and expensive. Thus, blood-based biomarkers can potentially reduce diagnosis inequities among populations from different socioeconomic contexts. This large-scale screening can be performed so that older adults at risk of cognitive decline assessed using these methods can then undergo more complete assessments with classic biomarkers, increasing diagnosis efficiency and reducing costs to the health systems. Blood-based biomarkers can also aid in assessing the effect of new disease-modifying treatments. This paper reviews recent advances in the area, focusing on the following leading candidates for blood-based biomarkers: amyloid-beta (Aβ), phosphorylated tau isoforms (p-tau), neurofilament light (NfL), and glial fibrillary acidic (GFAP) proteins, as well as on new candidates, Neuron-Derived Exosomes contents (NDEs) and Transactive response DNA-binding protein-43 (TDP-43), based on data from longitudinal observational cohort studies. The underlying challenges of validating and incorporating these biomarkers into routine clinical practice and primary care settings are also discussed. Importantly, challenges related to the underrepresentation of ethnic minorities and socioeconomically disadvantaged persons must be considered. If these challenges are overcome, a new time of cost-effective blood-based biomarkers for AD could represent the future of clinical procedures in the field and, together with continued prevention strategies, the beginning of an era with a lower incidence of dementia worldwide.

Phosphoproteome Microarray Analysis of Extracellular Particles as a Tool to Explore Novel Biomarker Candidates for Alzheimer's Disease

Phosphorylation plays a key role in Alzheimer's disease (AD) pathogenesis, impacting distinct processes such as amyloid-beta (Aβ) peptide production and tau phosphorylation. Impaired phosphorylation events contribute to senile plaques and neurofibrillary tangles' formation, two major histopathological hallmarks of AD. Blood-derived extracellular particles (bdEP) can represent a disease-related source of phosphobiomarker candidates, and hence, in this pilot study, bdEP of Control and AD cases were analyzed by a targeted phosphoproteomics approach using a high-density microarray that featured at least 1145 pan-specific and 913 phosphosite-specific antibodies. This approach, innovatively applied to bdEP, allowed the identification of 150 proteins whose expression levels and/or phosphorylation patterns were significantly altered across AD cases. Gene Ontology enrichment and Reactome pathway analysis unraveled potentially relevant molecular targets and disease-associated pathways, and protein-protein interaction networks were constructed to highlight key targets. The discriminatory value of both the total proteome and the phosphoproteome was evaluated by univariate and multivariate approaches. This pilot experiment supports that bdEP are enriched in phosphotargets relevant in an AD context, holding value as peripheral biomarker candidates for disease diagnosis.

Structural, static, and dynamic functional MRI predictors for conversion from mild cognitive impairment to Alzheimer's disease: Inter-cohort validation of Shanghai Memory Study and ADNI

Mild cognitive impairment (MCI) is a critical prodromal stage of Alzheimer's disease (AD), and the mechanism underlying the conversion is not fully explored. Construction and inter-cohort validation of imaging biomarkers for predicting MCI conversion is of great challenge at present, due to lack of longitudinal cohorts and poor reproducibility of various study-specific imaging indices. We proposed a novel framework for inter-cohort MCI conversion prediction, involving comparison of structural, static, and dynamic functional brain features from structural magnetic resonance imaging (sMRI) and resting-state functional MRI (fMRI) between MCI converters (MCI_C) and non-converters (MCI_NC), and support vector machine for construction of prediction models. A total of 218 MCI patients with 3-year follow-up outcome were selected from two independent cohorts: Shanghai Memory Study cohort for internal cross-validation, and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort for external validation. In comparison with MCI_NC, MCI_C were mainly characterized by atrophy, regional hyperactivity and inter-network hypo-connectivity, and dynamic alterations characterized by regional and connectional instability, involving medial temporal lobe (MTL), posterior parietal cortex (PPC), and occipital cortex. All imaging-based prediction models achieved an area under the curve (AUC) > 0.7 in both cohorts, with the multi-modality MRI models as the best with excellent performances of AUC > 0.85. Notably, the combination of static and dynamic fMRI resulted in overall better performance as relative to static or dynamic fMRI solely, supporting the contribution of dynamic features. This inter-cohort validation study provides a new insight into the mechanisms of MCI conversion involving brain dynamics, and paves a way for clinical use of structural and functional MRI biomarkers in future.

Recommendations for reproducibility of cerebrospinal fluid extracellular vesicle studies

Cerebrospinal fluid (CSF) is a clear, transparent fluid derived from blood plasma that protects the brain and spinal cord against mechanical shock, provides buoyancy, clears metabolic waste and transports extracellular components to remote sites in the brain. Given its contact with the brain and the spinal cord, CSF is the most informative biofluid for studies of the central nervous system (CNS). In addition to other components, CSF contains extracellular vesicles (EVs) that carry bioactive cargoes (e.g., lipids, nucleic acids, proteins), and that can have biological functions within and beyond the CNS. Thus, CSF EVs likely serve as both mediators of and contributors to communication in the CNS. Accordingly, their potential as biomarkers for CNS diseases has stimulated much excitement for and attention to CSF EV research. However, studies on CSF EVs present unique challenges relative to EV studies in other biofluids, including the invasive nature of CSF collection, limited CSF volumes and the low numbers of EVs in CSF as compared to plasma. Here, the objectives of the International Society for Extracellular Vesicles CSF Task Force are to promote the reproducibility of CSF EV studies by providing current reporting and best practices, and recommendations and reporting guidelines, for CSF EV studies. To accomplish this, we created and distributed a world-wide survey to ISEV members to assess methods considered 'best practices' for CSF EVs, then performed a detailed literature review for CSF EV publications that was used to curate methods and resources. Based on responses to the survey and curated information from publications, the CSF Task Force herein provides recommendations and reporting guidelines to promote the reproducibility of CSF EV studies in seven domains: (i) CSF Collection, Processing, and Storage; (ii) CSF EV Separation/Concentration; (iii) CSF EV Size and Number Measurements; (iv) CSF EV Protein Studies; (v) CSF EV RNA Studies; (vi) CSF EV Omics Studies and (vii) CSF EV Functional Studies.

A meta-analysis of neurogenic exosomes in the diagnosis of Alzheimer's disease

Background

Alzheimer's disease (AD) is an irreversible and difficult-to-treat neurodegenerative disease. It is necessary to search for reliable biomarkers for the early diagnosis of AD in a timely and effective manner in high-risk or preclinical AD populations. Studies have shown that neurogenic exosomes in the blood can be effectively used as biomarkers for AD.

Objective

In this meta-analysis, we aimed to find reliable biomarkers (Aβ42, T-tau, and P-tau181 in peripheral blood neurogenic exosomes) for the early diagnosis of AD to provide theoretical support for the early diagnosis of high-risk or preclinical AD populations.

Methods

By searching the literature database, relevant studies on AD diagnostic markers were collected. The study period was from April 1, 2012, to April 1, 2022. The average concentrations of Aβ42, T-tau, and P-tau181 in the exosomes of the AD group and healthy control group were compared using RevMan 5.3 software.

Results

A total of 13 studies were screened, including 842 subjects. Meta-analysis showed that the combined SMD value of neurogenic exosome Aβ42 was 1.70 (95% CI = [1.20,2.20], Z = 6.69, P < 0.05). The combined SMD value of T-tau was 1.02 (95% CI = [0.27,1.77], Z = 2.67, P < 0.05). The combined SMD value of P-tau181 was 1.75 (95% CI = [1.16, 2.35], Z = 5.75, P < 0.05). The levels of neurogenic exosomes Aβ42, T-tau, and P-tau181 in AD patients were significantly higher than those in healthy controls.

Conclusion

Aβ42, T-tau, and P-tau181 in blood neurogenic exosomes can be effectively used as biomarkers for AD and can be applied in the diagnosis, screening, prognosis prediction and disease monitoring of AD.

Disparity of smell tests in Alzheimer's disease and other neurodegenerative disorders: a systematic review and meta-analysis

Background

There are discrepancies of olfactory impairment between Alzheimer's disease (AD) and other neurodegenerative disorders. Olfactory deficits may be a potential marker for early and differential diagnosis of AD. We aimed to assess olfactory functions in patients with AD and other neurodegenerative disorders, to further evaluate the smell tests using subgroup analysis, and to explore moderating factors affecting olfactory performance.

Methods

Cross-sectional studies relating to olfactory assessment for both AD and other neurodegenerative disorders published before 27 July 2022 in English, were searched on PubMed, Embase and Cochrane. After literature screening and quality assessment, meta-analyses were conducted using stata14.0 software.

Results

Forty-two articles involving 12 smell tests that evaluated 2,569 AD patients were included. It was revealed that smell tests could distinguish AD from mild cognitive impairment (MCI), Lewy body disease (LBD), depression, and vascular dementia (VaD), but not from diseases such as frontotemporal dementia (FTD). Our finding indicated that in discriminating AD from MCI, the University of Pennsylvania Smell Identification Test (UPSIT) was most frequently used (95%CI: -1.12 to -0.89), while the Brief Smell Identification Test (B-SIT), was the most widely used method in AD vs. LBD group. Further subgroup analyses indicated that the methods of smell test used contributed to the heterogeneity in olfactory threshold and discrimination scores in group AD vs. MCI. While the moderating variables including age, MMSE scores, education years in AD vs. LBD, were account for heterogeneity across studies.

Conclusion

Our finding suggests smell tests have potential value in early differential diagnosis of AD. UPSIT and its simplified variant, B-SIT, are widely used methods in the analyses.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php? RecordID = 357970 (PROSPERO, registration number CRD42022357970).

A new diagnostic tool for brain disorders: extracellular vesicles derived from neuron, astrocyte, and oligodendrocyte

Brain disorders are the leading cause of disability worldwide, affecting people's quality of life and causing economic burdens. The current clinical diagnosis of brain disorders relies solely on individual phenotypes and lacks accurate molecular biomarkers. An emerging field of research centers around extracellular vesicles (EVs), nanoscale membrane vesicles which can easily cross the blood-brain barrier. EVs in the blood are derived from various tissues, including the brain. Therefore, purifying central nervous system (CNS)-derived EVs from the blood and analyzing their contents may be a relatively non-invasive way to analyze brain molecular alterations and identify biomarkers in brain disorders. Recently, methods for capturing neuron-derived EVs (NDEs), astrocyte-derived EVs (ADEs), and oligodendrocyte-derived EVs (ODEs) in peripheral blood were reported. In this article, we provide an overview of the research history of EVs in the blood, specifically focusing on biomarker findings in six major brain disorders (Alzheimer's disease, Parkinson's disease, schizophrenia, bipolar disorder, depression, and autism spectrum disorder). Additionally, we discuss the methodology employed for testing CNS-derived EVs. Among brain disorders, Alzheimer's disease has received the most extensive attention in EV research to date. Most studies focus on specific molecules, candidate proteins, or miRNAs. Notably, the most studied molecules implicated in the pathology of these diseases, such as Aβ, tau, and α-synuclein, exhibit good reproducibility. These findings suggest that CNS-derived EVs can serve as valuable tools for observing brain molecular changes minimally invasively. However, further analysis is necessary to understand the cargo composition of these EVs and improve isolation methods. Therefore, research efforts should prioritize the analysis of CNS-derived EVs' origin and genome-wide biomarker discovery studies.

Properties of odor identification testing in screening for early-stage Alzheimer's disease

Odor identification (OI) is impaired in the early stages of Alzheimer's disease (AD). However, data regarding the diagnostic properties of OI tests are lacking, preventing their clinical use. We aimed to explore OI and determine the accuracy of OI testing in screening for patients with early AD. In total, 30 participants with mild cognitive impairment due to AD (MCI-AD), 30 with mild dementia due to AD (MD-AD), and 30 cognitively normal elderly participants (CN) were enrolled, and cognitive examination (CDR, MMSE, ADAS-Cog 13, and verbal fluency tests) and assessment of OI (Burghart Sniffin' Sticks odor identification test) were performed. MCI-AD patients scored significantly worse in OI than CN participants, and MD-AD patients had worse OI scores than MCI-AD patients. The ratio of OI to ADAS-Cog 13 score had good diagnostic accuracy in differentiating AD patients from CN participants and in differentiating MCI-AD patients from CN participants. Substitution of ADAS-Cog 13 score with the ratio of OI to ADAS-Cog 13 score in a multinomial regression model improved the classification accuracy, especially of MCI-AD cases. Our results confirmed that OI is impaired during the prodromal stage of AD. OI testing has a good diagnostic quality and can improve the accuracy of screening for early-stage AD.

Biomarkers for parkinsonian disorders in CNS-originating EVs: promise and challenges

Extracellular vesicles (EVs), including exosomes, microvesicles, and oncosomes, are nano-sized particles enclosed by a lipid bilayer. EVs are released by virtually all eukaryotic cells and have been shown to contribute to intercellular communication by transporting proteins, lipids, and nucleic acids. In the context of neurodegenerative diseases, EVs may carry toxic, misfolded forms of amyloidogenic proteins and facilitate their spread to recipient cells in the central nervous system (CNS). CNS-originating EVs can cross the blood-brain barrier into the bloodstream and may be found in other body fluids, including saliva, tears, and urine. EVs originating in the CNS represent an attractive source of biomarkers for neurodegenerative diseases, because they contain cell- and cell state-specific biological materials. In recent years, multiple papers have reported the use of this strategy for identification and quantitation of biomarkers for neurodegenerative diseases, including Parkinson's disease and atypical parkinsonian disorders. However, certain technical issues have yet to be standardized, such as the best surface markers for isolation of cell type-specific EVs and validating the cellular origin of the EVs. Here, we review recent research using CNS-originating EVs for biomarker studies, primarily in parkinsonian disorders, highlight technical challenges, and propose strategies for overcoming them.

Progress in blood biomarkers of subjective cognitive decline in preclinical Alzheimer's disease

ABSTRACT

Alzheimer's disease (AD) is a neurodegenerative disease that gradually impairs cognitive functions. Recently, there has been a conceptual shift toward AD to view the disease as a continuum. Since AD is currently incurable, effective intervention to delay or prevent pathological cognitive decline may best target the early stages of symptomatic disease, such as subjective cognitive decline (SCD), in which cognitive function remains relatively intact. Diagnostic methods for identifying AD, such as cerebrospinal fluid biomarkers and positron emission tomography, are invasive and expensive. Therefore, it is imperative to develop blood biomarkers that are sensitive, less invasive, easier to access, and more cost effective for AD diagnosis. This review aimed to summarize the current data on whether individuals with SCD differ reliably and effectively in subjective and objective performances compared to cognitively normal elderly individuals, and to find one or more convenient and accessible blood biomarkers so that researchers can identify SCD patients with preclinical AD in the population as soon as possible. Owing to the heterogeneity and complicated pathogenesis of AD, it is difficult to make reliable diagnoses using only a single blood marker. This review provides an overview of the progress achieved to date with the use of SCD blood biomarkers in patients with preclinical AD, highlighting the key areas of application and current challenges.

The Potential Roles of Exosomes Carrying APP and Tau Cleavage Products in Alzheimer's Disease

Alzheimer's disease (AD) is the leading cause of dementia throughout the world. It is characterized by major amyloid plaques and neurofibrillary tangles (NFTs), which are composed of amyloid-β (Aβ) peptide and hyperphosphorylated Tau (p-Tau), respectively. Exosomes, which are secreted by cells, are single-membrane lipid bilayer vesicles found in bodily fluids and they have a diameter of 30-150 nm. Recently, they have been considered as critical carriers and biomarkers in AD, as they facilitate communication between cells and tissues by delivering proteins, lipids, and nucleic acids. This review demonstrates that exosomes are natural nanocontainers that carry APP as well as Tau cleavage products secreted by neuronal cells and that their formation is associated with the endosomal-lysosomal pathway. Moreover, these exosomes can transfer AD pathological molecules and participate in the pathophysiological process of AD; therefore, they have potential diagnostic and therapeutic value for AD and might also provide novel insights for screening and prevention of the disease.

Pathological (Dis)Similarities in Neuronal Exosome-Derived Synaptic and Organellar Marker Levels Between Alzheimer's Disease and Frontotemporal Dementia

BACKGROUND

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are pathologically distinct neurodegenerative disorders with certain overlap in cognitive and behavioral symptoms. Both AD and FTD are characterized by synaptic loss and accumulation of misfolded proteins, albeit, in different regions of the brain.

OBJECTIVE

To investigate the synaptic and organellar markers in AD and FTD through assessment of the levels of synaptic protein, neurogranin (Ng) and organellar proteins, mitofusin-2 (MFN-2), lysosomal associated membrane protein-2 (LAMP-2), and golgin A4 from neuronal exosomes.

METHODS

Exosomes isolated from the plasma of healthy controls (HC), AD and FTD subjects were characterized using transmission electron microscopy. Neurodegenerative status was assessed by measurement of neurofilament light chain (NfL) using Simoa. The pooled exosomal extracts from each group were analyzed for Ng, MFN-2, LAMP-2, and golgin A4 by western blot analysis using enhanced chemiluminescence method of detection.

RESULTS

The densitometric analysis of immunoreactive bands demonstrated a 65% reduction of Ng in AD and 53% in FTD. Mitochondrial protein MFN-2 showed a significant reduction by 32% in AD and 46% in FTD. Lysosomal LAMP-2 and Golgi complex associated golgin A4 were considerably increased in both AD and FTD.

CONCLUSION

Changes in Ng may reflect the ongoing synaptic degeneration that are linked to cognitive disturbances in AD and FTD. Importantly, the rate of synaptic degeneration was more pronounced in AD. Changes to a similar extent in both the dementia groups in organellar proteins indicates shared mechanisms of protein accumulation/degradation common to both AD and FTD.

Odor Discrimination as a Marker of Early Alzheimer's Disease

BACKGROUND

Olfactory dysfunction is an early symptom of Alzheimer's disease (AD). However, olfactory tests are rarely performed in clinical practice because their diagnostic efficacy in detecting early AD is unclear.

OBJECTIVE

To investigate odor discrimination in patients with early AD and the efficacy of olfactory discrimination tests in differentiating these patients from subjects with normal cognition (CN).

METHODS

Thirty patients each with mild dementia due to AD (MD-AD) and mild cognitive impairment due to AD (MCI-AD) and 30 older subjects with CN were enrolled. All participants underwent cognitive examinations (CDR, MMSE, ADAS-Cog 13, and verbal fluency) and odor discrimination tests (Sniffin' Sticks test, Burghart®, Germany).

RESULTS

The MD-AD group achieved significantly worse scores on the olfactory discrimination test than the MCI-AD group, and the MCI-AD group achieved significantly worse results than the CN group (p < 0.05). A cut-off score of≤10 had a diagnostic accuracy of 94.44% (95% CI, 87.51-98.17%) in differentiating patients with MCI-AD/MD-AD from subjects with CN and of 91.67% (95% CI, 81.61-97.24%) in differentiating those with MCI-AD from subjects with CN. Our multinomial logistic regression model with demographic data and ADAS-Cog 13 scores as predictor variables correctly classified 82.2% of the cases (CN, 93.3%; MC-AD, 70%; MD-AD, 83.3%); on adding the olfactory discrimination score to the model, the percentage increased to 92.2% (CN, 96.7%; MCI-AD, 86.7%; MD-AD, 93.3%).

CONCLUSION

Odor discrimination is impaired in cases of early AD and continues to deteriorate as the disease progresses. The olfactory discrimination test showed good diagnostic efficacy in detecting early AD.

Utilizing Reduced Labeled Proton Clearance to Identify Preclinical Alzheimer Disease with 3D ASL MRI

Addressing the seminal pathophysiology in Alzheimer disease (AD) is the next logical focus for effective intervention, given the initial disappointing and more recent possibly encouraging results of monoclonal antibody trials. Endothelial cell dysfunction-induced blood-brain barrier leak with associated prolonged capillary mean transit time (cMTT) and glymphatic outflow dysfunction is the most proximal events in the degeneration cascade. Sensitive and reproducible markers are required to both identify early disease and assess future treatment trial outcomes. Two participants, with mild cognitive impairment (MCI) and one with AD, were evaluated clinically prior to MRI in this small case series report. From seven 3D turbo gradient and spin echo (TGSE) pulsed arterial spin echo (PASL) MRI sequences six homologous region of interest in bitemporal, bifrontal, and biparietal lobes for each sequence were examined and plotted against time. By choosing late perfusion times during cMTT phase of perfusion linear analysis of signal decay could be utilized. A reference axial FLAIR sequence was also obtained. Slope of the linear analysis correlated to the rate of labeled proton clearance with reduced clearance occurring in AD participants compared to normal participants in our previous study. Whether similar differences in clearance rate extend to either MCI or early AD was investigated. Participants were categorized by clinical phenotype before MRI and compared to previously published phenotype cohorts: n = 18 normal/healthy, n = 6 AD, n = 3 MCI. Significant differences in labeled proton clearance rates between AD and MCI/control phenotypes within bilateral temporal lobes (left p = 0.004, right p = 0.002) and within bilateral frontal lobes AD versus controls (left p = 0.001, right p = 0.008) and AD versus MCI (left p = 0.001, right p = 0.001) were found. This noninvasive MRI technique has potential for identifying MCI transition to AD.

Soluble TREM2 levels associate with conversion from mild cognitive impairment to Alzheimer's disease

BACKGROUNDSoluble triggering receptor expressed on myeloid cells 2 (sTREM2) plays an important role in the clearance of pathological amyloid-β (Aβ) in Alzheimer's disease (AD). This study aimed to explore sTREM2 as a central and peripheral predictor of the conversion from mild cognitive impairment (MCI) to AD.METHODSsTREM2 and Aβ1-42 levels in cerebrospinal fluid (CSF) and florbetapir-PET (AV45) images were analyzed for healthy control (HCs), patients with MCI, and patients with AD from the ADNI database. Peripheral plasma sTREM2 and Aβ1-42 levels were determined for our Neurology database of Ruijin Hospital for Alzheimer's Disease (NRHAD) cohort, and patients with MCI were reevaluated at follow-up visits to assess for progression to AD. The association between CSF and plasma sTREM2 levels was analyzed in data from the Chinese Alzheimer's Biomarker and Lifestyle (CABLE) database.RESULTSThe results showed that patients with MCI who had low levels of CSF sTREM2 and Aβ1-42 were more likely to develop AD. Among participants with positive Aβ deposition, as assessed by AV45 imaging, elevated CSF sTREM2 levels were associated with a decreased risk of MCI-to-AD conversion. Meanwhile, in the NRHAD cohort, individuals in the MCI group with high sTREM2 levels in plasma were at a greater risk for AD, whereas low Aβ1-42 with high sTREM2 levels in plasma were associated with a faster cognitive decline. In addition, CSF sTREM2 levels were highly correlated with plasma sTREM2 levels in the CABLE database.CONCLUSIONThese findings suggest that sTREM2 may be useful as a potential predictive biomarker of MCI-to-AD conversion.FUNDINGThis study was supported by grants from the National Natural Science Foundation of China (grant nos. 82001341, 82071415, 81873778, and 82201392); the Shanghai Sailing Program (grant no. 22YF1425100); and the China Postdoctoral Science Foundation funded project (grant no. 2021M702169).

Extracellular vesicles in the study of Alzheimer's and Parkinson's diseases: Methodologies applied from cells to biofluids

Extracellular vesicles (EVs) are gaining increased importance in fundamental research as key players in disease pathogenic mechanisms, but also in translational and clinical research due to their value in biomarker discovery, either for diagnostics and/or therapeutics. In the first research scenario, the study of EVs isolated from neuronal models mimicking neurodegenerative diseases can open new avenues to better understand the pathological mechanisms underlying these conditions or to identify novel molecular targets for diagnosis and/or therapeutics. In the second research scenario, the easy availability of EVs in body fluids and the specificity of their cargo, which can reflect the cell of origin or disease profiles, turn these into attractive diagnostic tools. EVs with exosome-like characteristics, circulating in the bloodstream and other peripheral biofluids, constitute a non-invasive and rapid alternative to study several conditions, including brain-related disorders. In both cases, several EVs isolation methods are already available, but each neuronal model or biofluid presents its own challenges. Herein, a literature overview on EVs isolation methodologies from distinct neuronal models (cellular culture and brain tissue) and body fluids (serum, plasma, cerebrospinal fluid, urine and saliva) was carried out. Focus was given to approaches employed in the context of Alzheimer's and Parkinson's diseases, and the main research findings discussed. The topics here revised will facilitate the choice of EVs isolation methodologies and potentially prompt new discoveries in EVs research and in the neurodegenerative diseases field.

Diagnostic and Therapeutic Roles of Extracellular Vesicles in Aging-Related Diseases

Aging shows a decline in overall physical function, and cellular senescence is the powerful catalyst leading to aging. Considering that aging will be accompanied with the emergence of various aging-related diseases, research on new antiaging drugs is still valuable. Extracellular vesicles (EVs), as tools for intercellular communication, are important components of the senescence-associated secretory phenotype (SASP), and they can play pathological roles in the process of cellular senescence. In addition, EVs are similar to their original cells in functions. Therefore, EVs derived from pathological tissues or body fluids may be closely related to the progression of diseases and become potential biomarkers, while those from healthy cells may have therapeutic effects. Moreover, EVs are satisfactory drug carriers. At present, numerous studies have supported the idea that engineered EVs could improve drug targeting ability and utilization efficiency. Here, we summarize the characteristics of EVs and cellular senescence and focus on the diagnostic and therapeutic potential of EVs in various aging-related diseases, including Alzheimer disease, osteoporosis, cardiovascular disease, diabetes mellitus and its complications, and skin aging.

Improved prediction of early cognitive impairment in multiple sclerosis combining blood and imaging biomarkers

Disability in multiple sclerosis is generally classified by sensory and motor symptoms, yet cognitive impairment has been identified as a frequent manifestation already in the early disease stages. Imaging- and more recently blood-based biomarkers have become increasingly important for understanding cognitive decline associated with multiple sclerosis. Thus, we sought to determine the prognostic utility of serum neurofilament light chain levels alone and in combination with MRI markers by examining their ability to predict cognitive impairment in early multiple sclerosis. A comprehensive and detailed assessment of 152 early multiple sclerosis patients (Expanded Disability Status Scale: 1.3 ± 1.2, mean age: 33.0 ± 10.0 years) was performed, which included serum neurofilament light chain measurement, MRI markers (i.e. T₂-hyperintense lesion volume and grey matter volume) acquisition and completion of a set of cognitive tests (Symbol Digits Modalities Test, Paced Auditory Serial Addition Test, Verbal Learning and Memory Test) and mood questionnaires (Hospital Anxiety and Depression scale, Fatigue Scale for Motor and Cognitive Functions). Support vector regression, a branch of unsupervised machine learning, was applied to test serum neurofilament light chain and combination models of biomarkers for the prediction of neuropsychological test performance. The support vector regression results were validated in a replication cohort of 101 early multiple sclerosis patients (Expanded Disability Status Scale: 1.1 ± 1.2, mean age: 34.4 ± 10.6 years). Higher serum neurofilament light chain levels were associated with worse Symbol Digits Modalities Test scores after adjusting for age, sex Expanded Disability Status Scale, disease duration and disease-modifying therapy (B = −0.561; SE = 0.192; P = 0.004; 95% CI = −0.940 to −0.182). Besides this association, serum neurofilament light chain levels were not linked to any other cognitive or mood measures (all P-values > 0.05). The tripartite combination of serum neurofilament light chain levels, lesion volume and grey matter volume showed a cross-validated accuracy of 88.7% (90.8% in the replication cohort) in predicting Symbol Digits Modalities Test performance in the support vector regression approach, and outperformed each single biomarker (accuracy range: 68.6–75.6% and 68.9–77.8% in the replication cohort), as well as the dual biomarker combinations (accuracy range: 71.8–82.3% and 72.6–85.6% in the replication cohort). Taken together, early neuro-axonal loss reflects worse information processing speed, the key deficit underlying cognitive dysfunction in multiple sclerosis. Our findings demonstrate that combining blood and imaging measures improves the accuracy of predicting cognitive impairment, highlighting the clinical utility of cross-modal biomarkers in multiple sclerosis.

Comparison of Rapid Cognitive Screen against Montreal Cognitive Assessment in screening for cognitive impairment in the old and old-old

BACKGROUND

The Montreal Cognitive Assessment (MoCA) was developed as a screening tool for mild cognitive impairment (MCI). Given the need for a rapid screening test in settings such as primary care, we compare the validity of the Rapid Cognitive Screen (RCS) against the MoCA, and determine cut-off scores in the old and old-old.

METHODS

Cross-sectional study involving community-dwelling 'old' (65 to 79 years old) and 'old-old' (≥ 80 years old) without dementia. Cognitive impairment was defined by MoCA score 17 to 22. Validation was done using the receiver operating characteristic (ROC) curve analysis: area under the curve (AUC), sensitivity (Sn), and specificity (Sp).

RESULTS

Of the 183 participants (mean age 72.1 ± 5.2 years),15.8% (n = 29) were classified as cognitively impaired. The overall ROC curve had an AUC of 0.82 (95% CI 0.75-0.90, P < 0.01) with an optimal cut-off of 7/8 on RCS (Sn 0.77, Sp 0.72). The 'old' and 'old-old' group had AUC of 0.82 (95% CI 0.74-0.91, P < 0.01) with 8/9 as optimal cut-off (Sn 0.51, Sp 0.96) and AUC of 0.85 (95% CI 0.66-1.03, P < 0.01) with 7/8 as optimal cut-off (Sn 0.71, Sp 1.00) respectively. In multivariate analysis, age was associated with 0.05 (95% CI -0.10-0.00, P < 0.04) point decrement, while >6 years of education was associated with 0.82 (95% CI 0.32-1.33, P < 0.01) point increment in RCS scores.

CONCLUSION

The three-item RCS is quick and easy to administer. Although RCS met the criterion for good validity against MoCA in predicting cognitive impairment, its utility as a first-line screening tool needs to be further validated in a large-scale population study.

DNA damage in dementia: Evidence from patients affected by severe Chronic Obstructive Pulmonary Disease (COPD) and meta-analysis of most recent literature

Oxidative stress that leads to oxidatively damaged DNA, plays a crucial role in chronic obstructive pulmonary disease (COPD) as well as in the onset of neurodegenerative diseases. The consequent genomic instability is the first neuropathological event found in the preclinical phase of cognitive impairment (CI), and the level of DNA damage is closely related to the degree of dementia. Since CI has been associated with COPD, we investigated the extent of DNA damage in isolated lymphocytes with the Comet assay, in a group of severe COPD patients with cognitive function measured by the Mini-Mental State Examination (MMSE). An increase in DNA damage was observed in COPD patients with dementia (MMSE≤24), although the difference was only borderline (22.4 ± 6.9 vs. 18.5 ± 7.1; p = 0.055). Meta-analysis, including the results of the current study, confirmed that patients with MMSE≤ 24 showed higher level of DNA damage than patients with MMSE> 24. We observed a significant reduction (p < 0.001) in the MMSE score in patients with cognitive decline in areas I (Orientation), III (Attention and Calculus) and V (Language). Only the temporal orientation category in area I was also associated with the level of oxidative damage, with higher levels of MDA (p < 0.01) and DNA damage (p < 0.03). Patients with the lowest temporal orientation score had a 12% higher mean DNA damage (Odds Ratio=1.12; 95% confidence interval (95%CI) 1.01-1.25; p < 0.036). Temporal orientation is a component of most screening tests for the diagnosis of cognitive impairment, on the bases that disorientation is a common factor in dementia. Present results show that each component of cognitive decline can have a different etiopathogenesis and clinical relevance. A more thorough assessment of the cognitive functions of patients starting COPD rehabilitation, together with the assessment of DNA and the level of oxidative stress, can provide essential information to adapt and customize the rehabilitation project.

β-Amyloid in blood neuronal-derived extracellular vesicles is elevated in cognitively normal adults at risk of Alzheimer's disease and predicts cerebral amyloidosis

Background

Blood biomarkers that can be used for preclinical Alzheimer’s disease (AD) diagnosis would enable trial enrollment at a time when the disease is potentially reversible. Here, we investigated plasma neuronal-derived extracellular vesicle (nEV) cargo in patients along the Alzheimer’s continuum, focusing on cognitively normal controls (NCs) with high brain β-amyloid (Aβ) loads (Aβ+).

Methods

The study was based on the Sino Longitudinal Study on Cognitive Decline project. We enrolled 246 participants, including 156 NCs, 45 amnestic mild cognitive impairment (aMCI) patients, and 45 AD dementia (ADD) patients. Brain Aβ loads were determined using positron emission tomography. NCs were classified into 84 Aβ− NCs and 72 Aβ+ NCs. Baseline plasma nEVs were isolated by immunoprecipitation with an anti-CD171 antibody. After verification, their cargos, including Aβ, tau phosphorylated at threonine 181, and neurofilament light, were quantified using a single-molecule array. Concentrations of these cargos were compared among the groups, and their receiver operating characteristic (ROC) curves were constructed. A subset of participants underwent follow-up cognitive assessment and magnetic resonance imaging. The relationships of nEV cargo levels with amyloid deposition, longitudinal changes in cognition, and brain regional volume were explored using correlation analysis. Additionally, 458 subjects in the project had previously undergone plasma Aβ quantification.

Results

Only nEV Aβ was included in the subsequent analysis. We focused on Aβ₄₂ in the current study. After normalization of nEVs, the levels of Aβ₄₂ were found to increase gradually across the cognitive continuum, with the lowest in the Aβ− NC group, an increase in the Aβ+ NC group, a further increase in the aMCI group, and the highest in the ADD group, contributing to their diagnoses (Aβ− NCs vs. Aβ+ NCs, area under the ROC curve values of 0.663; vs. aMCI, 0.857; vs. ADD, 0.957). Furthermore, nEV Aβ₄₂ was significantly correlated with amyloid deposition, as well as longitudinal changes in cognition and entorhinal volume. There were no differences in plasma Aβ levels among NCs, aMCI, and ADD individuals.

Conclusions

Our findings suggest the potential use of plasma nEV Aβ₄₂ levels in diagnosing AD-induced cognitive impairment and Aβ+ NCs. This biomarker reflects cortical amyloid deposition and predicts cognitive decline and entorhinal atrophy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01010-x.

A pragmatic dementia risk score for patients with mild cognitive impairment in a memory clinic population: Development and validation of a dementia risk score using routinely collected data

Introduction

This study aimed to develop and validate a 3-year dementia risk score in individuals with mild cognitive impairment (MCI) based on variables collected in routine clinical care.

Methods

The prediction score was trained and developed using data from the National Alzheimer's Coordinating Center (NACC). Selection criteria included aged 55 years and older with MCI. Cox models were validated externally using two independent cohorts from the Prospective Registry of Persons with Memory Symptoms (PROMPT) registry and the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

Results

Our Mild Cognitive Impairment to Dementia Risk (CIDER) score predicted dementia risk with c-indices of 0.69 (95% confidence interval [CI] 0.66-0.72), 0.61 (95% CI 0.59-0.63), and 0.72 (95% CI 0.69-0.75), for the internally validated and the external validation PROMPT, and ADNI cohorts, respectively.

Discussion

The CIDER score could be used to inform clinicians and patients about the relative probabilities of developing dementia in patients with MCI.

Predicting conversion from MCI to AD by integration of rs-fMRI and clinical information using 3D-convolutional neural network

PURPOSE

Alzheimer's is the most common irreversible neurodegenerative disease. Its symptoms range from memory impairments to degradation of multiple cognitive abilities and ultimately death. Mild cognitive impairment (MCI) is the earliest detectable stage that happens between normal aging and early dementia, and even though MCI subjects have a chance of changing back to cognitively normal or even staying the same, there is a risk that their condition progresses to Alzheimer's disease (AD) annually. Therefore predicting AD among MCI subjects is pivotal for starting treatments at an opportune time in case of progression, and if staying stable is the case, the need for consistent medical observations would eliminate. Thus, we aim to diagnose possible conversion from MCI to AD by exploiting a class of deep learning (DL) methods called convolutional neural network (CNN).

METHODS

We proposed a three-dimensional CNN (3D-CNN) to combine and analyze resting-state functional magnetic resonance imaging (rs-fMRI), clinical assessment results, and demographic information to predict conversion from MCI to AD in an average 5-years interval. Initially, a 3D-CNN was developed based on fMRI single volumes of 266 samples from 81 subjects; then, we used neuron layers to combine clinical data with fMRI to improve the results.

RESULTS

At first, the CNN model demonstrated an AUC of 87.67% and an accuracy of 85.7%, then after combining clinical and rs-fMRI features, we observed the following improved scores: an AUC of 91.72%, an accuracy of 87.6%, a sensitivity of 75.58% and a specificity of 92.57%.

CONCLUSION

Our developed algorithm managed to predict prognosis from MCI to AD with high levels of accuracy, proving the potential of DL approaches in solving the matter and the efficiency of integrating clinical information with imaging according to the proposed method.

International consensus statement on allergy and rhinology: Olfaction

BACKGROUND

The literature regarding clinical olfaction, olfactory loss, and olfactory dysfunction has expanded rapidly over the past two decades, with an exponential rise in the past year. There is substantial variability in the quality of this literature and a need to consolidate and critically review the evidence. It is with that aim that we have gathered experts from around the world to produce this International Consensus on Allergy and Rhinology: Olfaction (ICAR:O).

METHODS

Using previously described methodology, specific topics were developed relating to olfaction. Each topic was assigned a literature review, evidence-based review, or evidence-based review with recommendations format as dictated by available evidence and scope within the ICAR:O document. Following iterative reviews of each topic, the ICAR:O document was integrated and reviewed by all authors for final consensus.

RESULTS

The ICAR:O document reviews nearly 100 separate topics within the realm of olfaction, including diagnosis, epidemiology, disease burden, diagnosis, testing, etiology, treatment, and associated pathologies.

CONCLUSION

This critical review of the existing clinical olfaction literature provides much needed insight and clarity into the evaluation, diagnosis, and treatment of patients with olfactory dysfunction, while also clearly delineating gaps in our knowledge and evidence base that we should investigate further.

Biomarkers and Tools for Predicting Alzheimer's Disease in the Preclinical Stage

Alzheimer's disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Over the past decade, a string of disappointing clinical trial results has forced us to shift our focus to the preclinical stage of AD, which represents the most promising therapeutic window. However, the accurate diagnosis of preclinical AD requires the presence of brain β- amyloid deposition determined by cerebrospinal fluid or amyloid-positron emission tomography, significantly limiting routine screening and diagnosis in non-tertiary hospital settings. Thus, an easily accessible marker or tool with high sensitivity and specificity is highly needed. Recently, it has been discovered that individuals in the late stage of preclinical AD may not be truly "asymptomatic" in that they may have already developed subtle or subjective cognitive decline. In addition, advances in bloodderived biomarker studies have also allowed the detection of pathologic changes in preclinical AD. Exosomes, as cell-to-cell communication messengers, can reflect the functional changes of their source cell. Methodological advances have made it possible to extract brain-derived exosomes from peripheral blood, making exosomes an emerging biomarker carrier and liquid biopsy tool for preclinical AD. The eye and its associated structures have rich sensory-motor innervation. In this regard, studies have indicated that they may also provide reliable markers. Here, our report covers the current state of knowledge of neuropsychological and eye tests as screening tools for preclinical AD and assesses the value of blood and brain-derived exosomes as carriers of biomarkers in conjunction with the current diagnostic paradigm.

Exosomes in Age-Related Cognitive Decline: Mechanistic Insights and Improving Outcomes

Aging is the most prominent risk factor for cognitive decline, yet behavioral symptomology and underlying neurobiology can vary between individuals. Certain individuals exhibit significant age-related cognitive impairments, while others maintain intact cognitive functioning with only minimal decline. Recent developments in genomic, proteomic, and functional imaging approaches have provided insights into the molecular and cellular substrates of cognitive decline in age-related neuropathologies. Despite the emergence of novel tools, accurately and reliably predicting longitudinal cognitive trajectories and improving functional outcomes for the elderly remains a major challenge. One promising approach has been the use of exosomes, a subgroup of extracellular vesicles that regulate intercellular communication and are easily accessible compared to other approaches. In the current review, we highlight recent findings which illustrate how the analysis of exosomes can improve our understanding of the underlying neurobiological mechanisms that contribute to cognitive variation in aging. Specifically, we focus on exosome-mediated regulation of miRNAs, neuroinflammation, and aggregate-prone proteins. In addition, we discuss how exosomes might be used to enhance individual patient outcomes by serving as reliable biomarkers of cognitive decline and as nanocarriers to deliver therapeutic agents to the brain in neurodegenerative conditions.

L1CAM-associated extracellular vesicles: A systematic review of nomenclature, sources, separation, and characterization

When released into biological fluids like blood or saliva, brain extracellular vesicles (EVs) might provide a window into otherwise inaccessible tissue, contributing useful biomarkers of neurodegenerative and other central nervous system (CNS) diseases. To enrich for brain EVs in the periphery, however, cell-specific EV surface markers are needed. The protein that has been used most frequently to obtain EVs of putative neuronal origin is the transmembrane L1 cell adhesion molecule (L1CAM/CD171). In this systematic review, we examine the existing literature on L1CAM and EVs, including investigations of both neurodegenerative disease and cancer through the lens of the minimal information for studies of EVs (MISEV), specifically in the domains of nomenclature usage, EV sources, and EV separation and characterization. Although numerous studies have reported L1CAM-associated biomarker signatures that correlate with disease, interpretation of these results is complicated since L1CAM expression is not restricted to neurons and is also upregulated during cancer progression. A recent study has suggested that L1CAM epitopes are present in biofluids mostly or entirely as cleaved, soluble protein. Our findings on practices and trends in L1CAM-mediated EV separation, enrichment, and characterization yield insights that may assist with interpreting results, evaluating rigor, and suggesting avenues for further exploration.

The potential utility of smell testing to screen for neurodegenerative disorders

INTRODUCTION

Loss of smell is a common early feature of neurodegenerative diseases including Alzheimer's and Parkinson's disease. Identifying these conditions in their early stages is important to understand more about early pathophysiological events and the development of disease modifying therapies. Smell testing may be an effective future tool for screening large populations for early neurodegeneration.

AREAS COVERED

: In this review, we appraise the evidence for, and discuss the likelihood of, the use of smell testing in large screening programs to detect early neurodegeneration. We evaluate the predictive power of smell tests for neurodegenerative disease, compare performance to other established screening programs, and discuss ethical and practical considerations and limitations.

EXPERT OPINION

: Even if disease modifying therapies were available for neurodegenerative disease, smell tests alone are unlikely to have high enough predictive power to be used in a future screening program. However, we believe they could be a valuable component of a short battery of tests or part of a stepwise process that together could more accurately identify early neurodegeneration in large populations.

Neuropsychiatric Symptoms Mediated the Relationship Between Odor Identification and Cognition in Alzheimer's Disease Spectrum: A Structural Equation Model Analysis

Background: Odor identification dysfunction is an early predictor of the development of Alzheimer's disease (AD), but neuropsychiatric symptoms (NPS), which are common in AD and mild cognitive impairment (MCI), are also associated with odor identification dysfunction. Whether NPS affect the specificity of using odor identification dysfunction to predict cognitive decline in AD and MCI remains unclear.

Methods: Patients (233 with MCI and 45 with AD) and 45 healthy controls (HCs) underwent assessments of odor identification (Sniffin' Sticks), NPS (Neuropsychiatric Inventory-12), and cognitive function (global cognition, memory, language, executive function, visual-spatial skill, and attention). Structural equation modeling (SEM) with bootstrapping estimation was conducted to explore the relationships between odor identification, NPS, and cognition.

Results: Patients with NPS showed significantly worse performance in odor identification and cognition than patients without NPS and HCs. The SEM showed odor identification to be positively associated with cognition, and cognition had special indirect effects on odor identification through affective and psychosis symptoms (two factors extracted from Neuropsychiatric Inventory-12). Additionally, affective and psychosis symptoms partially mediated the effect of cognition on odor identification.

Conclusion: Neuropsychiatric symptoms are associated with odor identification dysfunction in patients with AD and MCI. Studies exploring the relationship between odor identification dysfunction and cognitive decline in patients with AD and MCI should include an assessment of affective and psychosis symptoms, and adjust their confounding effects.

Modulation of Amyloid-β and Tau in Alzheimer's Disease Plasma Neuronal-Derived Extracellular Vesicles by Cerebrolysin® and Donepezil

BACKGROUND

Plasma neuronal-derived extracellular vesicles (NDEV) contain proteins of pathological, diagnostic, and therapeutic relevance.

OBJECTIVE

We investigated the associations of six plasma NDEV markers with Alzheimer's disease (AD) severity, cognition and functioning, and changes in these biomarkers after Cerebrolysin®, donepezil, and a combination therapy in AD.

METHODS

Plasma NDEV levels of Aβ42, total tau, P-T181-tau, P-S393-tau, neurogranin, and REST were determined in: 1) 116 mild to advanced AD patients and in 20 control subjects; 2) 110 AD patients treated with Cerebrolysin®, donepezil, or combination therapy in a randomized clinical trial (RCT). Samples for NDEV determinations were obtained at baseline in the NDEV study and at baseline and study endpoint in the RCT. Cognition and functioning were assessed at the same time points.

RESULTS

NDEV levels of Aβ42, total tau, P-T181-tau, and P-S393-tau were higher and those of neurogranin and REST were lower in mild-to-moderate AD than in controls (p < 0.05 to p < 0.001). NDEV total tau, neurogranin, and REST increased with AD severity (p < 0.05 to p < 0.001). NDEV Aβ42 and P-T181-tau correlated negatively with serum BDNF (p < 0.05), and total-tau levels were associated to plasma TNF-α (p < 0.01) and cognitive impairment (p < 0.05). Combination therapy reduced NDEV Aβ42 with respect to monotherapies (p < 0.05); and NDEV total tau, P-T181-tau, and P-S396-tau were decreased in Cerebrolysin-treated patients compared to those on donepezil monotherapy (p < 0.05).

CONCLUSION

The present results demonstrate the utility of NDEV determinations of pathologic and synaptic proteins as effective AD biomarkers, as markers of AD severity, and as potential tools for monitoring the effects of anti-AD drugs.

The Effect of Olfactory Training on Olfaction, Cognition, and Brain Function in Patients with Mild Cognitive Impairment

BACKGROUND

The olfactory system is affected very early in Alzheimer's disease and olfactory loss can already be observed in patients with mild cognitive impairment (MCI), an early stage of AD.

OBJECTIVE

The aim of this randomized, prospective, controlled, blinded study was to evaluate whether olfactory training (OT) may have an effect on olfactory function, cognitive impairment, and brain activation in MCI patients after a 4-month period of frequent short-term exposure to various odors.

METHODS

A total of 38 MCI outpatients were randomly assigned to OT or a control training condition, which were performed twice a day for 4 months. Olfactory testing, comprehensive neuropsychological assessment, and magnetic resonance imaging were performed before and after training.

RESULTS

The results suggested that OT exhibited no significant effect on olfaction and cognitive function. However, OT exhibited a positive effect on frontal lobe activation (left middle frontal gyrus and orbital-frontal cortex) but exhibited no effect on grey matter volume. Moreover, the change of olfactory scores was positively associated with the change of frontal activation.

CONCLUSION

OT was found to have a limited effect on olfaction and cognition in patients with MCI compared to a non-OT condition but increased their functional response to odors in frontal area.

A potential biomarker of preclinical Alzheimer's disease: The olfactory dysfunction and its pathogenesis-based neural circuitry impairments

The olfactory dysfunction can signal and act as a potential biomarker of preclinical AD. However, the precise regulatory mechanism of olfactory function on the neural pathogenesis of AD is still unclear. The impairment of neural networks in olfaction system has been shown to be tightly associated with AD. As key brain regions of the olfactory system, the olfactory bulb (OB) and the piriform cortex (PCx) have a profound influence on the olfactory function. Therefore, this review will explore the mechanism of olfactory dysfunction in preclinical AD in the perspective of abnormal neural networks in the OB and PCx and their associated brain regions, especially from two aspects of aberrant oscillations and synaptic plasticity damages, which help better understand the underlying mechanism of olfactory neural network damages related to AD.

Exosomes in Alzheimer's Disease: From Being Pathological Players to Potential Diagnostics and Therapeutics

Exosomes (EXOs) were given attention as an extracellular vesicle (EV) with a pivotal pathophysiological role in the development of certain neurodegenerative disorders (NDD), such as Parkinson's and Alzheimer's disease (AD). EXOs have shown the potential to carry pathological and therapeutic cargo; thus, researchers have harnessed EXOs in drug delivery applications. EXOs have shown low immunogenicity as natural drug delivery vehicles, thus ensuring efficient drug delivery without causing significant adverse reactions. Recently, EXOs provided potential drug delivery opportunities in AD and promising future clinical applications with the diagnosis of NDD and were studied for their usefulness in disease detection and prediction prior to the emergence of symptoms. In the future, the microfluidics technique will play an essential role in isolating and detecting EXOs to diagnose AD before the development of advanced symptoms. This review is not reiterative literature but will discuss why EXOs have strong potential in treating AD and how they can be used as a tool to predict and diagnose this disorder.

Comparison of the predictive accuracy of multiple definitions of cognitive impairment for incident dementia: a 20-year follow-up of the Whitehall II cohort study

BACKGROUND

Studies generally use cognitive assessment done at one timepoint to define cognitive impairment in order to examine conversion to dementia. Our objective was to examine the predictive accuracy and conversion rate of seven alternate definitions of cognitive impairment for dementia.

METHODS

In this prospective study, we included participants from the Whitehall II cohort study who were assessed for cognitive impairment in 2007-09 and were followed up for clinically diagnosed dementia. Algorithms based on poor cognitive performance (defined using age-specific and sex-specific thresholds, and subsequently thresholds by education or occupation levels) and objective cognitive decline (using data from cognitive assessments in 1997-99, 2002-04, and 2007-09) were used to generate seven alternate definitions of cognitive impairment. We compared predictive accuracy using Royston's R 2, the Akaike information criterion (AIC), sensitivity, specificity, and Harrell's C-statistic.

FINDINGS

5687 participants, with a mean age of 65·7 years (SD 5·9) in 2007-09, were included and followed up for a median of 10·5 years (IQR 10·1-10·9). Over follow-up, 270 (4·7%) participants were clinically diagnosed with dementia. Cognitive impairment defined using both cognitive performance and decline had higher hazard ratios (from 5·08 [95% CI 3·82-6·76] to 5·48 [4·13-7·26]) for dementia than did definitions based on cognitive performance alone (from 3·25 [2·52-4·17] to 3·39 [2·64-4·36]) and cognitive decline alone (3·01 [2·37-3·82]). However, all definitions had poor predictive performance (C-statistic ranged from 0·591 [0·565-0·616] to 0·631 [0·601-0·660]), primarily due to low sensitivity (21·6-48·4%). A predictive model containing age, sex, and education without measures of cognitive impairment had better predictive performance (C-statistic 0·783 [0·758-0·809], sensitivity 74·2%, specificity 72·2%) than all seven definitions of cognitive impairment (all p<0·0001).

INTERPRETATION

These findings suggest that cognitive impairment in early old age might not be useful for dementia prediction, even when it is defined using longitudinal data on cognitive decline and thresholds of poor cognitive performance additionally defined by education or occupation.

FUNDING

National Institutes of Health, UK Medical Research Council.

An Improved Deep Residual Network Prediction Model for the Early Diagnosis of Alzheimer's Disease

The early diagnosis of Alzheimer's disease (AD) can allow patients to take preventive measures before irreversible brain damage occurs. It can be seen from cross-sectional imaging studies of AD that the features of the lesion areas in AD patients, as observed by magnetic resonance imaging (MRI), show significant variation, and these features are distributed throughout the image space. Since the convolutional layer of the general convolutional neural network (CNN) cannot satisfactorily extract long-distance correlation in the feature space, a deep residual network (ResNet) model, based on spatial transformer networks (STN) and the non-local attention mechanism, is proposed in this study for the early diagnosis of AD. In this ResNet model, a new Mish activation function is selected in the ResNet-50 backbone to replace the Relu function, STN is introduced between the input layer and the improved ResNet-50 backbone, and a non-local attention mechanism is introduced between the fourth and the fifth stages of the improved ResNet-50 backbone. This ResNet model can extract more information from the layers by deepening the network structure through deep ResNet. The introduced STN can transform the spatial information in MRI images of Alzheimer's patients into another space and retain the key information. The introduced non-local attention mechanism can find the relationship between the lesion areas and normal areas in the feature space. This model can solve the problem of local information loss in traditional CNN and can extract the long-distance correlation in feature space. The proposed method was validated using the ADNI (Alzheimer's disease neuroimaging initiative) experimental dataset, and compared with several models. The experimental results show that the classification accuracy of the algorithm proposed in this study can reach 97.1%, the macro precision can reach 95.5%, the macro recall can reach 95.3%, and the macro F1 value can reach 95.4%. The proposed model is more effective than other algorithms.

Exosomes: Innocent Bystanders or Critical Culprits in Neurodegenerative Diseases

Extracellular vesicles (EVs) are nano-sized membrane-enclosed particles released by cells that participate in intercellular communication through the transfer of biologic material. EVs include exosomes that are small vesicles that were initially associated with the disposal of cellular garbage; however, recent findings point toward a function as natural carriers of a wide variety of genetic material and proteins. Indeed, exosomes are vesicle mediators of intercellular communication and maintenance of cellular homeostasis. The role of exosomes in health and age-associated diseases is far from being understood, but recent evidence implicates exosomes as causative players in the spread of neurodegenerative diseases. Cells from the central nervous system (CNS) use exosomes as a strategy not only to eliminate membranes, toxic proteins, and RNA species but also to mediate short and long cell-to-cell communication as carriers of important messengers and signals. The accumulation of protein aggregates is a common pathological hallmark in many neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, and prion diseases. Protein aggregates can be removed and delivered to degradation by the endo-lysosomal pathway or can be incorporated in multivesicular bodies (MVBs) that are further released to the extracellular space as exosomes. Because exosome transport damaged cellular material, this eventually contributes to the spread of pathological misfolded proteins within the brain, thus promoting the neurodegeneration process. In this review, we focus on the role of exosomes in CNS homeostasis, their possible contribution to the development of neurodegenerative diseases, the usefulness of exosome cargo as biomarkers of disease, and the potential benefits of plasma circulating CNS-derived exosomes.

Odor identification impairment and cholinesterase inhibitor treatment in Alzheimer's disease

INTRODUCTION

This study evaluated acute change in odor identification following atropine nasal spray challenge, and 8-week change in odor identification ability, as a predictor of long-term improvement in patients with mild to moderate Alzheimer's disease (AD) who received open-label cholinesterase inhibitor treatment.

METHODS

In patients with clinical AD, the University of Pennsylvania Smell identification Test (UPSIT) was administered before and after an anticholinergic atropine nasal spray challenge. Patients were then treated with donepezil for 52 weeks.

RESULTS

In 21 study participants, acute atropine-induced decrease in UPSIT was not associated with change in the Alzheimer's Disease Assessment Scale - Cognitive Subscale (ADAS-Cog) or Selective Reminding Test (SRT). Decline in odor identification performance from baseline to week 8 was indicative of a future decline in cognitive performance over 52 weeks.

DISCUSSION

Change in odor identification with atropine challenge is not a useful predictor of treatment response to cholinesterase inhibitors. Short-term change in odor identification performance needs further investigation as a potential predictor of cognitive improvement with cholinesterase inhibitor treatment.

The Diagnostic Value of Exosome-Derived Biomarkers in Alzheimer's Disease and Mild Cognitive Impairment: A Meta-Analysis

Background: Alzheimer's disease (AD) diagnoses once depended on neuropathologic examination. Now, many widely used, validated biomarkers benefits for monitoring of AD neuropathologic changes. Exosome-derived biomarker studies have reported them to be significantly related to AD's early occurrence and development, although the findings are inconclusive. The aim of this meta-analysis was to identify exosome-derived biomarkers for the diagnosis of AD and mild cognitive impairment (MCI).

Methods: PubMed, PubMed Central, Web of Science, Embase, Google Scholar, Cochrane Library, the Chinese National Knowledge Infrastructure (CNKI), and the Chinese Biomedical Literature Database (CBM) were searched for studies assessing the diagnostic value of biomarkers, including data describing the pooled sensitivity (SEN), specificity (SPE), positive diagnostic likelihood ratio (DLR+), negative diagnostic likelihood ratio (DLR–), diagnostic odds ratio (DOR), and area under the curve (AUC). The quality of the included studies was assessed using RevMan 5.3 software. Publication bias was analyzed.

Results: In total, 19 eligible studies, including 3,742 patients, were selected for this meta-analysis. The SEN, SPE, DLR+, DLR–, DOR, and AUC (95% confidence intervals) of exosome-derived biomarkers in the diagnosis of AD or MCI were 0.83 (0.76–0.87), 0.82 (0.77–0.86), 4.53 (3.46–5.93), 0.21 (0.15–0.29), 17.27 (11.41–26.14), and 0.89 (0.86–0.92), respectively. Sub-group analyses revealed that studies based on serum or microRNA (miRNA) analysis, and those of Caucasian populations, AD patients, patient sample size >50, neuron-derived exosomes (NDE) from plasma and p-tau had higher sensitivity, specificity, and AUC values.

Conclusion: Exosome-derived biomarkers have shown potential diagnostic value in AD and MCI, although further research is required for confirmation.