Feasibility and usability of remote monitoring in Alzheimer's disease.

Introduction: Remote monitoring technologies (RMTs) can measure cognitive and functional decline objectively at-home, and offer opportunities to measure passively and continuously, possibly improving sensitivity and reducing participant burden in clinical trials. However, there is skepticism that age and cognitive or functional impairment may render participants unable or unwilling to comply with complex RMT protocols. We therefore assessed the feasibility and usability of a complex RMT protocol in all syndromic stages of Alzheimer's disease and in healthy control participants. Methods: For 8 weeks, participants (N = 229) used two activity trackers, two interactive apps with either daily or weekly cognitive tasks, and optionally a wearable camera. A subset of participants participated in a 4-week sub-study (N = 45) using fixed at-home sensors, a wearable EEG sleep headband and a driving performance device. Feasibility was assessed by evaluating compliance and drop-out rates. Usability was assessed by problem rates (e.g., understanding instructions, discomfort, forgetting to use the RMT or technical problems) as discussed during bi-weekly semi-structured interviews. Results: Most problems were found for the active apps and EEG sleep headband. Problem rates increased and compliance rates decreased with disease severity, but the study remained feasible. Conclusions: This study shows that a highly complex RMT protocol is feasible, even in a mild-to-moderate AD population, encouraging other researchers to use RMTs in their study designs. We recommend evaluating the design of individual devices carefully before finalizing study protocols, considering RMTs which allow for real-time compliance monitoring, and engaging the partners of study participants in the research.

Contributions of amyloid beta and cerebral small vessel disease in clinical decline.

INTRODUCTION: We assessed whether co-morbid small vessel disease (SVD) has clinical predictive value in preclinical or prodromal Alzheimer's disease. METHODS: In 1090 non-demented participants (65.4 ± 10.7 years) SVD was assessed with magnetic resonance imaging and amyloid beta (Aß) with lumbar puncture and/or positron emission tomography scan (mean follow-up for cognitive function 3.1 ± 2.4 years). RESULTS: Thirty-nine percent had neither Aß nor SVD (A-V-), 21% had SVD only (A-V+), 23% Aß only (A+V-), and 17% had both (A+V+). Pooled cohort linear mixed model analyses demonstrated that compared to A-V- (reference), A+V- had a faster rate of cognitive decline. Co-morbid SVD (A+V+) did not further increase rate of decline. Cox regression showed that dementia risk was modestly increased in A-V+ (hazard ratio [95% confidence interval: 1.8 [1.0-3.2]) and most strongly in A+ groups. Also, mortality risk was increased in A+ groups. DISCUSSION: In non-demented persons Aß was predictive of cognitive decline, dementia, and mortality. SVD modestly predicts dementia in A-, but did not increase deleterious effects in A+. HIGHLIGHTS: Amyloid beta (Aß; A) was predictive for cognitive decline, dementia, and mortality. Small vessel disease (SVD) had no additional deleterious effects in A+. SVD modestly predicted dementia in A-. Aß should be assessed even when magnetic resonance imaging indicates vascular cognitive impairment.

Augmented reality versus standard tests to assess cognition and function in early Alzheimer's disease.

Augmented reality (AR) apps, in which the virtual and real world are combined, can recreate instrumental activities of daily living (IADL) and are therefore promising to measure cognition needed for IADL in early Alzheimer's disease (AD) both in the clinic and in the home settings. The primary aim of this study was to distinguish and classify healthy controls (HC) from participants with AD pathology in an early AD stage using an AR app. The secondary aims were to test the association of the app with clinical cognitive and functional tests and investigate the feasibility of at-home testing using AR. We furthermore investigated the test-retest reliability and potential learning effects of the task. The digital score from the AR app could significantly distinguish HC from preclinical AD (preAD) and prodromal AD (proAD), and preAD from proAD, both with in-clinic and at-home tests. For the classification of the proAD group, the digital score (AUCclinic_visit = 0.84 [0.75-0.93], AUCat_home = 0.77 [0.61-0.93]) was as good as the cognitive score (AUC = 0.85 [0.78-0.93]), while for classifying the preAD group, the digital score (AUCclinic_visit = 0.66 [0.53-0.78], AUCat_home = 0.76 [0.61-0.91]) was superior to the cognitive score (AUC = 0.55 [0.42-0.68]). In-clinic and at-home tests moderately correlated (rho = 0.57, p < 0.001). The digital score was associated with the clinical cognitive score (rho = 0.56, p < 0.001). No learning effects were found. Here we report the AR app distinguishes HC from otherwise healthy Aß-positive individuals, both in the outpatient setting and at home, which is currently not possible with standard cognitive tests.

Correction: Ethical challenges of using remote monitoring technologies for clinical research: A case study of the role of local research ethics committees in the RADAR-AD study.

[This corrects the article DOI: 10.1371/journal.pone.0285807.].

Ethical challenges of using remote monitoring technologies for clinical research: A case study of the role of local research ethics committees in the RADAR-AD study.

INTRODUCTION: Clinical research with remote monitoring technologies (RMTs) has multiple advantages over standard paper-pencil tests, but also raises several ethical concerns. While several studies have addressed the issue of governance of big data in clinical research from the legal or ethical perspectives, the viewpoint of local research ethics committee (REC) members is underrepresented in the current literature. The aim of this study is therefore to find which specific ethical challenges are raised by RECs in the context of a large European study on remote monitoring in all syndromic stages of Alzheimer's disease, and what gaps remain. METHODS: Documents describing the REC review process at 10 sites in 9 European countries from the project Remote Assessment of Disease and Relapse-Alzheimer's Disease (RADAR-AD) were collected and translated. Main themes emerging in the documents were identified using a qualitative analysis approach. RESULTS: Four main themes emerged after analysis: data management, participant's wellbeing, methodological issues, and the issue of defining the regulatory category of RMTs. Review processes differed across sites: process duration varied from 71 to 423 days, some RECs did not raise any issues, whereas others raised up to 35 concerns, and the approval of a data protection officer was needed in half of the sites. DISCUSSION: The differences in the ethics review process of the same study protocol across different local settings suggest that a multi-site study would benefit from a harmonization in research ethics governance processes. More specifically, some best practices could be included in ethical reviews across institutional and national contexts, such as the opinion of an institutional data protection officer, patient advisory board reviews of the protocol and plans for how ethical reflection is embedded within the study.

Digital endpoints in clinical trials of Alzheimer's disease and other neurodegenerative diseases: challenges and opportunities.

Alzheimer's disease (AD) and other neurodegenerative diseases such as Parkinson's disease (PD) and Huntington's disease (HD) are associated with progressive cognitive, motor, affective and consequently functional decline considerably affecting Activities of Daily Living (ADL) and quality of life. Standard assessments, such as questionnaires and interviews, cognitive testing, and mobility assessments, lack sensitivity, especially in early stages of neurodegenerative diseases and in the disease progression, and have therefore a limited utility as outcome measurements in clinical trials. Major advances in the last decade in digital technologies have opened a window of opportunity to introduce digital endpoints into clinical trials that can reform the assessment and tracking of neurodegenerative symptoms. The Innovative Health Initiative (IMI)-funded projects RADAR-AD (Remote assessment of disease and relapse-Alzheimer's disease), IDEA-FAST (Identifying digital endpoints to assess fatigue, sleep and ADL in neurodegenerative disorders and immune-mediated inflammatory diseases) and Mobilise-D (Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement) aim to identify digital endpoints relevant for neurodegenerative diseases that provide reliable, objective, and sensitive evaluation of disability and health-related quality of life. In this article, we will draw from the findings and experiences of the different IMI projects in discussing (1) the value of remote technologies to assess neurodegenerative diseases; (2) feasibility, acceptability and usability of digital assessments; (3) challenges related to the use of digital tools; (4) public involvement and the implementation of patient advisory boards; (5) regulatory learnings; and (6) the significance of inter-project exchange and data- and algorithm-sharing.

The reporting of neuropsychiatric symptoms in electronic health records of individuals with Alzheimer's disease: a natural language processing study.

BACKGROUND: Neuropsychiatric symptoms (NPS) are prevalent in the early clinical stages of Alzheimer's disease (AD) according to proxy-based instruments. Little is known about which NPS clinicians report and whether their judgment aligns with proxy-based instruments. We used natural language processing (NLP) to classify NPS in electronic health records (EHRs) to estimate the reporting of NPS in symptomatic AD at the memory clinic according to clinicians. Next, we compared NPS as reported in EHRs and NPS reported by caregivers on the Neuropsychiatric Inventory (NPI). METHODS: Two academic memory clinic cohorts were used: the Amsterdam UMC (n = 3001) and the Erasmus MC (n = 646). Patients included in these cohorts had MCI, AD dementia, or mixed AD/VaD dementia. Ten trained clinicians annotated 13 types of NPS in a randomly selected training set of n = 500 EHRs from the Amsterdam UMC cohort and in a test set of n = 250 EHRs from the Erasmus MC cohort. For each NPS, a generalized linear classifier was trained and internally and externally validated. Prevalence estimates of NPS were adjusted for the imperfect sensitivity and specificity of each classifier. Intra-individual comparison of the NPS classified in EHRs and NPS reported on the NPI were conducted in a subsample (59%). RESULTS: Internal validation performance of the classifiers was excellent (AUC range: 0.81-0.91), but external validation performance decreased (AUC range: 0.51-0.93). NPS were prevalent in EHRs from the Amsterdam UMC, especially apathy (adjusted prevalence = 69.4%), anxiety (adjusted prevalence = 53.7%), aberrant motor behavior (adjusted prevalence = 47.5%), irritability (adjusted prevalence = 42.6%), and depression (adjusted prevalence = 38.5%). The ranking of NPS was similar for EHRs from the Erasmus MC, although not all classifiers obtained valid prevalence estimates due to low specificity. In both cohorts, there was minimal agreement between NPS classified in the EHRs and NPS reported on the NPI (all kappa coefficients < 0.28), with substantially more reports of NPS in EHRs than on NPI assessments. CONCLUSIONS: NLP classifiers performed well in detecting a wide range of NPS in EHRs of patients with symptomatic AD visiting the memory clinic and showed that clinicians frequently reported NPS in these EHRs. Clinicians generally reported more NPS in EHRs than caregivers reported on the NPI.

Physical activity levels in cognitively normal and cognitively impaired oldest-old and the association with dementia risk factors: a pilot study.

BACKGROUND: Research assessing the relationship of physical activity and dementia is usually based on studies with individuals younger than 90 years of age. The primary aim of this study was to determine physical activity levels of cognitively normal and cognitively impaired adults older than 90 years of age (oldest-old). Our secondary aim was to assess if physical activity is associated with risk factors for dementia and brain pathology biomarkers. METHODS: Physical activity was assessed in cognitively normal (N = 49) and cognitively impaired (N = 12) oldest-old by trunk accelerometry for a 7-day period. We tested physical performance parameters and nutritional status as dementia risk factors, and brain pathology biomarkers. Linear regression models were used to examine the associations, correcting for age, sex and years of education. RESULTS: Cognitively normal oldest-old were on average active for a total duration of 45 (SD 27) minutes per day, while cognitively impaired oldest-old seemed less physically active with 33 (SD 21) minutes per day with a lower movement intensity. Higher active duration and lower sedentary duration were related to better nutritional status and better physical performance. Higher movement intensities were related to better nutritional status, better physical performance and less white matter hyperintensities. Longer maximum walking bout duration associated with more amyloid binding. CONCLUSION: We found that cognitively impaired oldest-old are active at a lower movement intensity than cognitively normal oldest-old individuals. In the oldest-old, physical activity is related to physical parameters, nutritional status, and moderately to brain pathology biomarkers.

Social cognition deficits and biometric signatures in the behavioural variant of Alzheimer's disease.

The behavioural variant of Alzheimer's disease (bvAD) is characterized by early predominant behavioural changes, mimicking the behavioural variant of frontotemporal dementia (bvFTD), which is characterized by social cognition deficits and altered biometric responses to socioemotional cues. These functions remain understudied in bvAD. We investigated multiple social cognition components (i.e. emotion recognition, empathy, social norms and moral reasoning), using the Ekman 60 faces test, Interpersonal Reactivity Index, empathy eliciting videos, Social Norms Questionnaire and moral dilemmas, while measuring eye movements and galvanic skin response. We compared 12 patients with bvAD with patients with bvFTD (n = 14), typical Alzheimer's disease (tAD, n = 13) and individuals with subjective cognitive decline (SCD, n = 13), using ANCOVAs and age- and sex-adjusted post hoc testing. Patients with bvAD (40.1 ± 8.6) showed lower scores on the Ekman 60 faces test compared to individuals with SCD (49.7 ± 5.0, P < 0.001), and patients with tAD (46.2 ± 5.3, P = 0.05) and higher scores compared to patients with bvFTD (32.4 ± 7.3, P = 0.002). Eye-tracking during the Ekman 60 faces test revealed no differences in dwell time on the eyes (all P > 0.05), but patients with bvAD (18.7 ± 9.5%) and bvFTD (19.4 ± 14.3%) spent significantly less dwell time on the mouth than individuals with SCD (30.7 ± 11.6%, P < 0.01) and patients with tAD (32.7 ± 12.1%, P < 0.01). Patients with bvAD (11.3 ± 4.6) exhibited lower scores on the Interpersonal Reactivity Index compared with individuals with SCD (15.6 ± 3.1, P = 0.05) and similar scores to patients with bvFTD (8.7 ± 5.6, P = 0.19) and tAD (13.0 ± 3.2, P = 0.43). The galvanic skin response to empathy eliciting videos did not differ between groups (all P > 0.05). Patients with bvAD (16.0 ± 1.6) and bvFTD (15.2 ± 2.2) showed lower scores on the Social Norms Questionnaire than patients with tAD (17.8 ± 2.1, P < 0.05) and individuals with SCD (18.3 ± 1.4, P < 0.05). No group differences were observed in scores on moral dilemmas (all P > 0.05), while only patients with bvFTD (0.9 ± 1.1) showed a lower galvanic skin response during personal dilemmas compared with SCD (3.4 ± 3.3 peaks per min, P = 0.01). Concluding, patients with bvAD showed a similar although milder social cognition profile and a similar eye-tracking signature to patients with bvFTD and greater social cognition impairments and divergent eye movement patterns compared with patients with tAD. Our results suggest reduced attention to salient facial features in these phenotypes, potentially contributing to their emotion recognition deficits.

A Multiplexing Activity-Based Protein-Profiling Platform for Dissection of a Native Bacterial Xyloglucan-Degrading System.

Bacteria and yeasts grow on biomass polysaccharides by expressing and excreting a complex array of glycoside hydrolase (GH) enzymes. Identification and annotation of such GH pools, which are valuable commodities for sustainable energy and chemistries, by conventional means (genomics, proteomics) are complicated, as primary sequence or secondary structure alignment with known active enzymes is not always predictive for new ones. Here we report a "low-tech", easy-to-use, and sensitive multiplexing activity-based protein-profiling platform to characterize the xyloglucan-degrading GH system excreted by the soil saprophyte, Cellvibrio japonicus, when grown on xyloglucan. A suite of activity-based probes bearing orthogonal fluorophores allows for the visualization of accessory exo-acting glycosidases, which are then identified using biotin-bearing probes. Substrate specificity of xyloglucanases is directly revealed by imbuing xyloglucan structural elements into bespoke activity-based probes. Our ABPP platform provides a highly useful tool to dissect xyloglucan-degrading systems from various sources and to rapidly select potentially useful ones. The observed specificity of the probes moreover bodes well for the study of other biomass polysaccharide-degrading systems, by modeling probe structures to those of desired substrates.

Mechanism-based heparanase inhibitors reduce cancer metastasis in vivo.

Heparan sulfate proteoglycans (HSPGs) mediate essential interactions throughout the extracellular matrix (ECM), providing signals that regulate cellular growth and development. Altered HSPG composition during tumorigenesis strongly aids cancer progression. Heparanase (HPSE) is the principal enzyme responsible for extracellular heparan sulfate catabolism and is markedly up-regulated in aggressive cancers. HPSE overactivity degrades HSPGs within the ECM, facilitating metastatic dissemination and releasing mitogens that drive cellular proliferation. Reducing extracellular HPSE activity reduces cancer growth, but few effective inhibitors are known, and none are clinically approved. Inspired by the natural glycosidase inhibitor cyclophellitol, we developed nanomolar mechanism-based, irreversible HPSE inhibitors that are effective within physiological environments. Application of cyclophellitol-derived HPSE inhibitors reduces cancer aggression in cellulo and significantly ameliorates murine metastasis. Mechanism-based irreversible HPSE inhibition is an unexplored anticancer strategy. We demonstrate the feasibility of such compounds to control pathological HPSE-driven malignancies.

Assessment of Social Behavior Using a Passive Monitoring App in Cognitively Normal and Cognitively Impaired Older Adults: Observational Study.

BACKGROUND: In people with cognitive impairment, loss of social interactions has a major impact on well-being. Therefore, patients would benefit from early detection of symptoms of social withdrawal. Current measurement techniques such as questionnaires are subjective and rely on recall, in contradiction to smartphone apps, which measure social behavior passively and objectively. OBJECTIVE: This study uses the remote monitoring smartphone app Behapp to assess social behavior, and aims to investigate (1) the association between social behavior, demographic characteristics, and neuropsychiatric symptoms in cognitively normal (CN) older adults, and (2) if social behavior is altered in cognitively impaired (CI) participants. In addition, we explored in a subset of individuals the association between Behapp outcomes and neuropsychiatric symptoms. METHODS: CN, subjective cognitive decline (SCD), and CI older adults installed the Behapp app on their own Android smartphone for 7 to 42 days. CI participants had a clinical diagnosis of mild cognitive impairment (MCI) or Alzheimer-type dementia. The app continuously measured communication events, app use and location. Neuropsychiatric Inventory (NPI) total scores were available for 20 SCD and 22 CI participants. Linear models were used to assess group differences on Behapp outcomes and to assess the association of Behapp outcomes with the NPI. RESULTS: We included CN (n=209), SCD (n=55) and CI (n=22) participants. Older cognitively normal participants called less frequently and made less use of apps (P<.05). No sex effects were found. Compared to the CN and SCD groups, CI individuals called less unique contacts (ß=-0.7 [SE 0.29], P=.049) and contacted the same contacts relatively more often (ß=0.8 [SE 0.25], P=.004). They also made less use of apps (ß=-0.83 [SE 0.25], P=.004). Higher total NPI scores were associated with further traveling (ß=0.042 [SE 0.015], P=.03). CONCLUSIONS: CI individuals show reduced social activity, especially those activities that are related to repeated and unique behavior, as measured by the smartphone app Behapp. Neuropsychiatric symptoms seemed only marginally associated with social behavior as measured with Behapp. This research shows that the Behapp app is able to objectively and passively measure altered social behavior in a cognitively impaired population.

Activity-based protein profiling reveals dynamic substrate-specific cellulase secretion by saprotrophic basidiomycetes.

BACKGROUND: Fungal saccharification of lignocellulosic biomass occurs concurrently with the secretion of a diverse collection of proteins, together functioning as a catalytic system to liberate soluble sugars from insoluble composite biomaterials. How different fungi respond to different substrates is of fundamental interest to the developing biomass saccharification industry. Among the cornerstones of fungal enzyme systems are the highly expressed cellulases (endo-ß-glucanases and cellobiohydrolases). Recently, a cyclophellitol-derived activity-based probe (ABP-Cel) was shown to be a highly sensitive tool for the detection and identification of cellulases. RESULTS: Here we show that ABP-Cel enables endo-ß-glucanase profiling in diverse fungal secretomes. In combination with established ABPs for ß-xylanases and ß-D-glucosidases, we collected multiplexed in-gel fluorescence activity-based protein profiles of 240 secretomes collected over ten days from biological replicates of ten different basidiomycete fungi grown on maltose, wheat straw, or aspen pulp. Our results reveal the remarkable dynamics and unique enzyme fingerprints associated with each species substrate combination. Chemical proteomic analysis identifies significant arsenals of cellulases secreted by each fungal species during growth on lignocellulosic biomass. Recombinant production and characterization of a collection of probe-reactive enzymes from GH5, GH10, and GH12 confirm that ABP-Cel shows broad selectivity towards enzymes with endo-ß-glucanase activity. CONCLUSION: Using small-volume samples with minimal sample preparation, the results presented here demonstrate the ready accessibility of sensitive direct evidence for fungal enzyme secretion during early stages of growth on complex lignocellulosic substrates.

Remote monitoring technologies in Alzheimer's disease: design of the RADAR-AD study.

BACKGROUND: Functional decline in Alzheimer's disease (AD) is typically measured using single-time point subjective rating scales, which rely on direct observation or (caregiver) recall. Remote monitoring technologies (RMTs), such as smartphone applications, wearables, and home-based sensors, can change these periodic subjective assessments to more frequent, or even continuous, objective monitoring. The aim of the RADAR-AD study is to assess the accuracy and validity of RMTs in measuring functional decline in a real-world environment across preclinical-to-moderate stages of AD compared to standard clinical rating scales. METHODS: This study includes three tiers. For the main study, we will include participants (n = 220) with preclinical AD, prodromal AD, mild-to-moderate AD, and healthy controls, classified by MMSE and CDR score, from clinical sites equally distributed over 13 European countries. Participants will undergo extensive neuropsychological testing and physical examination. The RMT assessments, performed over an 8-week period, include walk tests, financial management tasks, an augmented reality game, two activity trackers, and two smartphone applications installed on the participants' phone. In the first sub-study, fixed sensors will be installed in the homes of a representative sub-sample of 40 participants. In the second sub-study, 10 participants will stay in a smart home for 1 week. The primary outcome of this study is the difference in functional domain profiles assessed using RMTs between the four study groups. The four participant groups will be compared for each RMT outcome measure separately. Each RMT outcome will be compared to a standard clinical test which measures the same functional or cognitive domain. Finally, multivariate prediction models will be developed. Data collection and privacy are important aspects of the project, which will be managed using the RADAR-base data platform running on specifically designed biomedical research computing infrastructure. RESULTS: First results are expected to be disseminated in 2022. CONCLUSION: Our study is well placed to evaluate the clinical utility of RMT assessments. Leveraging modern-day technology may deliver new and improved methods for accurately monitoring functional decline in all stages of AD. It is greatly anticipated that these methods could lead to objective and real-life functional endpoints with increased sensitivity to pharmacological agent signal detection.

Development of Non-Hydrolysable Oligosaccharide Activity-Based Inactivators for Endoglycanases: A Case Study on α-1,6 Mannanases.

There is a vast genomic resource for enzymes active on carbohydrates. Lagging far behind, however, are functional chemical tools for the rapid characterization of carbohydrate-active enzymes. Activity-based probes (ABPs) offer one chemical solution to these issues with ABPs based upon cyclophellitol epoxide and aziridine covalent and irreversible inhibitors representing a potent and widespread approach. Such inhibitors for enzymes active on polysaccharides are potentially limited by the requirement for several glycosidic bonds, themselves substrates for the enzyme targets. Here, it is shown that non-hydrolysable trisaccharide can be synthesized and applied even to enzymes with challenging subsite requirements. It was found that incorporation of carbasugar moieties, which was accomplished by cuprate-assisted regioselective trans-diaxial epoxide opening of carba-mannal synthesised for this purpose, yields inactivators that act as powerful activity-based inhibitors for α-1,6 endo-mannanases. 3-D structures at 1.35-1.47 Šresolutions confirm the design rationale and binding to the enzymatic nucleophile. Carbasugar oligosaccharide cyclophellitols offer a powerful new approach for the design of robust endoglycosidase inhibitors, while the synthesis procedures presented here should allow adaptation towards activity-based endoglycosidase probes as well as configurational isosteres targeting other endoglycosidase families.

Application of the ATN classification scheme in a population without dementia: Findings from the EPAD cohort.

BACKGROUND: We classified non-demented European Prevention of Alzheimer's Dementia (EPAD) participants through the amyloid/tau/neurodegeneration (ATN) scheme and assessed their neuropsychological and imaging profiles. MATERIALS AND METHODS: From 1500 EPAD participants, 312 were excluded. Cerebrospinal fluid cut-offs of 1000 pg/mL for amyloid beta (Aß)1-42 and 27 pg/mL for p-tau181 were validated using Gaussian mixture models. Given strong correlation of p-tau and t-tau (R2  = 0.98, P < 0.001), neurodegeneration was defined by age-adjusted hippocampal volume. Multinomial regressions were used to test whether neuropsychological tests and regional brain volumes could distinguish ATN stages. RESULTS: Age was 65 ± 7 years, with 58% females and 38% apolipoprotein E (APOE) ε4 carriers; 57.1% were A-T-N-, 32.5% were in the Alzheimer's disease (AD) continuum, and 10.4% suspected non-Alzheimer's pathology. Age and cerebrovascular burden progressed with biomarker positivity (P < 0.001). Cognitive dysfunction appeared with T+. Paradoxically higher regional gray matter volumes were observed in A+T-N- compared to A-T-N- (P < 0.001). DISCUSSION: In non-demented individuals along the AD continuum, p-tau drives cognitive dysfunction. Memory and language domains are affected in the earliest stages.

Activity-Based Protein Profiling of Retaining α-Amylases in Complex Biological Samples.

Amylases are key enzymes in the processing of starch in many kingdoms of life. They are important catalysts in industrial biotechnology where they are applied in, among others, food processing and the production of detergents. In man amylases are the first enzymes in the digestion of starch to glucose and arguably also the preferred target in therapeutic strategies aimed at the treatment of type 2 diabetes patients through down-tuning glucose assimilation. Efficient and sensitive assays that report selectively on retaining amylase activities irrespective of the nature and complexity of the biomaterial studied are of great value both in finding new and effective human amylase inhibitors and in the discovery of new microbial amylases with potentially advantageous features for biotechnological application. Activity-based protein profiling (ABPP) of retaining glycosidases is inherently suited for the development of such an assay format. We here report on the design and synthesis of 1,6-epi-cyclophellitol-based pseudodisaccharides equipped with a suite of reporter entities and their use in ABPP of retaining amylases from human saliva, murine tissue as well as secretomes from fungi grown on starch. The activity and efficiency of the inhibitors and probes are substantiated by extensive biochemical analysis, and the selectivity for amylases over related retaining endoglycosidases is validated by structural studies.

Correction: Glycosylated cyclophellitol-derived activity-based probes and inhibitors for cellulases.

[This corrects the article DOI: 10.1039/D0CB00045K.].

Prediction of Alzheimer's disease biomarker status defined by the 'ATN framework' among cognitively healthy individuals: results from the EPAD longitudinal cohort study.

BACKGROUND: The Amyloid/Tau/Neurodegeneration (ATN) framework has been proposed as a means of evidencing the biological state of Alzheimer's disease (AD). Predicting ATN status in pre-dementia individuals therefore provides an important opportunity for targeted recruitment into AD interventional studies. We investigated the extent to which ATN-defined biomarker status can be predicted by known AD risk factors as well as vascular-related composite risk scores. METHODS: One thousand ten cognitively healthy older adults were allocated to one of five ATN-defined biomarker categories. Multinomial logistic regression tested risk factors including age, sex, education, APOE4, family history of dementia, cognitive function, vascular risk indices (high systolic blood pressure, body mass index (BMI), high cholesterol, physical inactivity, ever smoked, blood pressure medication, diabetes, prior cardiovascular disease, atrial fibrillation and white matter lesion (WML) volume), and three vascular-related composite scores, to predict five ATN subgroups; ROC curve models estimated their added value in predicting pathology. RESULTS: Age, APOE4, family history, BMI, MMSE and white matter lesions (WML) volume differed between ATN biomarker groups. Prediction of Alzheimer's disease pathology (versus normal AD biomarkers) improved by 7% after adding family history, BMI, MMSE and WML to a ROC curve that included age, sex and APOE4. Risk composite scores did not add value. CONCLUSIONS: ATN-defined Alzheimer's disease biomarker status prediction among cognitively healthy individuals is possible through a combination of constitutional and cardiovascular risk factors but established dementia composite risk scores do not appear to add value in this context.

Manno-epi-cyclophellitols Enable Activity-Based Protein Profiling of Human α-Mannosidases and Discovery of New Golgi Mannosidase II Inhibitors.

Golgi mannosidase II (GMII) catalyzes the sequential hydrolysis of two mannosyl residues from GlcNAcMan5GlcNAc2 to produce GlcNAcMan3GlcNAc2, the precursor for all complex N-glycans, including the branched N-glycans associated with cancer. Inhibitors of GMII are potential cancer therapeutics, but their usefulness is limited by off-target effects, which produce α-mannosidosis-like symptoms. Despite many structural and mechanistic studies of GMII, we still lack a potent and selective inhibitor of this enzyme. Here, we synthesized manno-epi-cyclophellitol epoxide and aziridines and demonstrate their covalent modification and time-dependent inhibition of GMII. Application of fluorescent manno-epi-cyclophellitol aziridine derivatives enabled activity-based protein profiling of α-mannosidases from both human cell lysate and mouse tissue extracts. Synthesized probes also facilitated a fluorescence polarization-based screen for dGMII inhibitors. We identified seven previously unknown inhibitors of GMII from a library of over 350 iminosugars and investigated their binding modalities through X-ray crystallography. Our results reveal previously unobserved inhibitor binding modes and promising scaffolds for the generation of selective GMII inhibitors.