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.

Cognitive, psychological, and physiological effects of a web-based mindfulness intervention in older adults during the COVID-19 pandemic: an open study.

BACKGROUND: The development of effective strategies to maintain good mental health of older adults is a public health priority. Mindfulness-based interventions have the potential to improve psychological well-being and cognitive functions of older adults, but little is known about the effect of such interventions when delivered through internet. During the COVID-19 pandemic we evaluated short- and long-term cognitive, psychological, and physiological effects of a mindfulness-based intervention (MBI) delivered via web-based videoconference in healthy older adults. METHODS: Fifty older adults participated in an 8-week MBI, which comprised structured 2-h weekly group sessions. A comprehensive evaluation encompassing cognitive (verbal memory, attention and processing speed, executive functions) and psychological assessments (depression and anxiety symptoms, mindfulness, worries, emotion regulation strategies, well-being, interoceptive awareness and sleep) was conducted. Additionally, electroencephalography (EEG) data were recorded before and after the MBI and at the 6-month follow-up (T6). Data were analyzed using an intention-to-treat approach, using linear mixed models adjusted for age. The effect size for time was computed as omega squared. RESULTS: We observed significant improvements from pre-MBI to post-MBI and at the T6 across several measures. These improvements were notable in the areas of verbal memory (California Verbal Learning Test, p ≤ .007), attention and executive functions (Trail Making Test A and BA, p < .050), interoceptive awareness (Multidimensional Assessment of Interoceptive Awareness, p = .0002 for self-regulation and p < .05 for noticing, body listening, and trusting dimensions), and rumination (Heidelberg Form for Emotion Regulation Strategies, p = .018). These changes were associated with low to medium effect size. Moreover, we observed significant changes in EEG patterns, with a decrease in alpha1 (p = .004) and an increase in alpha2 (p < .0001) from pre-MBI to T6. Notably, improvements in TMTBA and rumination were correlated with the decrease in alpha1 (p < .050), while improvements in TMTA were linked to the increase in alpha2 (p = .025). CONCLUSIONS: The results of our study show that a web-based MBI in older adults leads to improvements in cognitive and psychological measures, with associated modulations in specific brain rhythms. While these findings are promising, further controlled studies are required to validate these preliminary results. TRIAL REGISTRATION: The trial has been registered with the United States National Library of Medicine at the National Institutes of Health Registry of Clinical Trials under the code NCT05941143 on July 12, 2023.

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.

Disclosure of Genetic Risk Factors for Alzheimer's Disease to Cognitively Healthy Individuals-From Current Practice towards a Personalised Medicine Scenario.

Alzheimer's disease (AD) is a genetically complex disorder. In addition to the relatively small number of pathogenic variants causing autosomal dominant AD, many others have been associated with the much more common sporadic form. The E4 allele of the Apolipoprotein E (APOE) is the first discovered genetic risk factor for AD. In addition, more than 70 genetic risk loci contributing to AD have been identified. Current guidelines do not recommend AD susceptibility genetic testing in cognitively healthy adults because the implications for clinical care are limited. However, secondary prevention clinical trials of disease-modifying therapies enrol individuals based on genetic criteria, and participants are often informed of APOE testing results. Moreover, the availability of direct-to-consumer genetic testing allows individuals to learn their own AD genetic risk profile without medical supervision. A number of research protocols for AD susceptibility genetic testing have been proposed. In Italy, disclosure processes and protocols beyond those developed for inherited dementia have not been established yet. We reviewed the literature on the current practice and clinical issues related to disclosing AD genetic risk to cognitively healthy individuals and provide suggestions that may help to develop specific guidelines at the national level.

A low-dimensional cognitive-network space in Alzheimer's disease and frontotemporal dementia.

BACKGROUND: Alzheimer's disease (AD) and frontotemporal dementia (FTD) show network dysfunctions linked with cognitive deficits. Within this framework, network abnormalities between AD and FTD show both convergent and divergent patterns. However, these functional patterns are far from being established and their relevance to cognitive processes remains to be elucidated. METHODS: We investigated the relationship between cognition and functional connectivity of major cognitive networks in these diseases. Twenty-three bvFTD (age: 71±10), 22 AD (age: 72±6), and 20 controls (age: 72±6) underwent cognitive evaluation and resting-state functional MRI. Principal component analysis was used to describe cognitive variance across participants. Brain network connectivity was estimated with connectome analysis. Connectivity matrices were created assessing correlations between parcels within each functional network. The following cognitive networks were considered: default mode (DMN), dorsal attention (DAN), ventral attention (VAN), and frontoparietal (FPN) networks. The relationship between cognition and connectivity was assessed using a bootstrapping correlation and interaction analyses. RESULTS: Three principal cognitive components explained more than 80% of the cognitive variance: the first component (cogPC1) loaded on memory, the second component (cogPC2) loaded on emotion and language, and the third component (cogPC3) loaded on the visuo-spatial and attentional domains. Compared to HC, AD and bvFTD showed impairment in all cogPCs (p<0.002), and bvFTD scored worse than AD in cogPC2 (p=0.031). At the network level, the DMN showed a significant association in the whole group with cogPC1 and cogPC2 and the VAN with cogPC2. By contrast, DAN and FPN showed a divergent pattern between diagnosis and connectivity for cogPC2. We confirmed these results by means of a multivariate analysis (canonical correlation). CONCLUSIONS: A low-dimensional representation can account for a large variance in cognitive scores in the continuum from normal to pathological aging. Moreover, cognitive components showed both convergent and divergent patterns with connectivity across AD and bvFTD. The convergent pattern was observed across the networks primarily involved in these diseases (i.e., the DMN and VAN), while a divergent FC-cognitive pattern was mainly observed between attention/executive networks and the language/emotion cognitive component, suggesting the co-existence of compensatory and detrimental mechanisms underlying these components.

Cognitive and biological effects of citrus phytochemicals in subjective cognitive decline: a 36-week, randomized, placebo-controlled trial.

BACKGROUND: Auraptene (AUR) and naringenin (NAR) are citrus-derived phytochemicals that influence several biological mechanisms associated with cognitive decline, including neuronal damage, oxidative stress and inflammation. Clinical evidence of the efficacy of a nutraceutical with the potential to enhance cognitive function in cohorts at risk of cognitive decline would be of great value from a preventive perspective. The primary aim of this study is to determine the cognitive effects of a 36-week treatment with citrus peel extract standardized in levels of AUR and NAR in older adults experiencing subjective cognitive decline (SCD). The secondary aim is to determine the effects of these phytochemicals on blood-based biomarkers indicative of neuronal damage, oxidative stress, and inflammation. METHODS: Eighty older persons with SCD will be recruited and randomly assigned to receive the active treatment (400 mg of citrus peel extract containing 0.1 mg of AUR and 3 mg of NAR) or the placebo at a 1:1 ratio for 36 weeks. The primary endpoint is a change in the Repeatable Battery for the Assessment of Neuropsychological Status score from baseline to weeks 18 and 36. Other cognitive outcomes will include changes in verbal and nonverbal memory, attention, executive and visuospatial functions. Blood samples will be collected from a consecutive subsample of 60 participants. The secondary endpoint is a change in interleukin-8 levels over the 36-week period. Other biological outcomes include changes in markers of neuronal damage, oxidative stress, and pro- and anti-inflammatory cytokines. CONCLUSION: This study will evaluate whether an intervention with citrus peel extract standardized in levels of AUR and NAR has cognitive and biological effects in older adults with SCD, facilitating the establishment of nutrition intervention in people at risk of cognitive decline. TRIAL REGISTRATION: The trial is registered with the United States National Library of Medicine at the National Institutes of Health Registry of Clinical Trials under the code NCT04744922 on February 9th, 2021 ( https://www. CLINICALTRIALS: gov/ct2/show/NCT04744922 ).

Psychological Impact of Predictive Genetic Testing for Inherited Alzheimer Disease and Frontotemporal Dementia: The IT-DIAfN Protocol.

AIM: Our aim was to evaluate the psychological impact of predictive genetic testing in individuals at-risk for inherited dementia who underwent a structured counseling and testing protocol. METHODS: Participants were healthy at-risk relatives from families with at least one affected patient, in whom a disease-associated genetic variant had been ascertained. A comprehensive psychological assessment (personality, anxiety and depression, quality of life, coping strategies, resilience and health-related beliefs) was administered at baseline, at 6 months and 12 months follow-up. RESULTS: Twenty-four participants from 13 families were included. Sixteen participants underwent blood sampling and genetic analysis; 6 resulted to be carriers of pathogenic variants (1 in PSEN1, 1 in PSEN2, 4 in GRN). Carriers showed higher score on the Resilience Scale for Adults (RSA) - social competence, and on Multidimensional Health Locus of Control - internal, than noncarriers (P=0.03 for both). Ten at-risk relatives who completed the follow-up showed improvement in RSA - planned future (P=0.01) with respect to baseline. DISCUSSION: Our case series showed that at-risk individuals undergoing predictive testing showed benefit on personal life and no detrimental impact on a broad range of psychological outcomes. Higher social skills and lower internal health locus of control in carriers may be an early psychological correlate of preclinical dementia.

Brain network modulation in Alzheimer's and frontotemporal dementia with transcranial electrical stimulation.

The default mode (DMN) and the salience (SN) networks show functional hypo-connectivity in Alzheimer's disease (AD) and the behavioral variant of frontotemporal dementia (bvFTD), respectively, along with patterns of hyper-connectivity. We tested the clinical and neurobiological effects of noninvasive stimulation over these networks in 45 patients (AD and bvFTD) who received either anodal (target network: DMN in AD, SN in bvFTD) or cathodal stimulation (target network: SN in AD, DMN in bvFTD). We evaluated changes in clinical, cognitive, functional and structural connectivity, and perfusion measures. In both patient groups, cathodal stimulation was followed by behavioral improvement, whereas anodal stimulation led to cognitive improvement. Neither functional connectivity nor perfusion showed significant effects. A significant interaction between DMN and SN functional connectivity changes and stimulation protocol was reported in AD. These results suggest a protocol-dependent response, whereby the protocols studied show divergent effects on cognitive and clinical measures, along with a divergent modulatory pattern of connectivity in AD.

Norms for Automatic Estimation of Hippocampal Atrophy and a Step Forward for Applicability to the Italian Population.

INTRODUCTION: Hippocampal volume is one of the main biomarkers of Alzheimer's Dementia (AD). Over the years, advanced tools that performed automatic segmentation of Magnetic Resonance Imaging (MRI) T13D scans have been developed, such as FreeSurfer (FS) and ACM-Adaboost (AA). Hippocampal volume is considered abnormal when it is below the 5th percentile of the normative population. The aim of this study was to set norms, established from the Alzheimer's Disease Neuroimaging Initiative (ADNI) population, for hippocampal volume measured with FS v.6.0 and AA tools in the neuGRID platform (www.neugrid2.eu) and demonstrate their applicability for the Italian population. METHODS: Norms were set from a large group of 545 healthy controls belonging to ADNI. For each pipeline, subjects with segmentation errors were discarded, resulting in 532 valid segmentations for FS and 421 for AA (age range 56-90 years). The comparability of ADNI and the Italian Brain Normative Archive (IBNA), representative of the Italian general population, was assessed testing clinical variables, neuropsychological scores and normalized hippocampal volumes. Finally, percentiles were validated using the Italian Alzheimer's disease Repository Without Borders (ARWiBo) as external independent data set to evaluate FS and AA generalizability. RESULTS: Hippocampal percentiles were checked with the chi-square goodness of fit test. P-values were not significant, showing that FS and AA algorithm distributions fitted the data well. Clinical, neuropsychological and volumetric features were similar in ADNI and IBNA (p > 0.01). Hippocampal volumes measured with both FS and AA were associated with age (p < 0.001). The 5th percentile thresholds, indicating left/right hippocampal atrophy were respectively: (i) below 3,223/3,456 mm3 at 56 years and 2,506/2,415 mm3 at 90 years for FS; (ii) below 4,583/4,873 mm3 at 56 years and 3,831/3,870 mm3 at 90 years for AA. The average volumes computed on 100 cognitively intact healthy controls (CN) selected from ARWiBo were close to the 50th percentiles, while those for 100 AD patients were close to the abnormal percentiles. DISCUSSION: Norms generated from ADNI through the automatic FS and AA segmentation tools may be used as normative references for Italian patients with suspected AD.

Genetic counselling and testing for inherited dementia: single-centre evaluation of the consensus Italian DIAfN protocol.

BACKGROUND: A consensus protocol for genetic counselling and testing of familial dementia, the Italian Dominantly Inherited Alzheimer's and Frontotemporal Network (IT-DIAfN) protocol, has been developed in Italy by a network of expert dementia centres. The aim of this study is to evaluate feasibility and acceptability of the genetic counselling and testing process, as undertaken according to the IT-DIAfN protocol in one of the IT-DIAfN dementia research centres. METHODS: The protocol was tested by a multidisciplinary team at the IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy, on affected individuals with suspected inherited forms of Alzheimer's disease (AD) or frontotemporal dementia (FTD), and to healthy at-risk relatives. The genetic counselling and testing process consisted of (i) pre-test consultation and psychological assessment (ii) genetic testing, (iii) genetic test result disclosure and (iv) follow-up consultation and psychological assessment. RESULTS: Twenty affected individuals from 17 families fulfilled the family history criteria of the IT-DIAfN protocol for suspected inherited dementia (17 for AD, 2 for FTD, 1 for inclusion body myopathy with Paget disease of bone and frontotemporal dementia) and were included in the protocol. Nineteen out of 20 affected individuals received the genetic test result (one left after the pre-test consultation being not ready to cope with an unfavourable outcome). A pathogenic mutation was found in 6 affected individuals (1 in PSEN1, 2 in PSEN2, 1 in GRN, 1 in MAPT, 1 in VCP). Eleven healthy at-risk relatives asked to undergo predictive testing and were included in the protocol. Three completed the protocol, including follow-up; one did not ask for the genetic test result after genetic testing; and eight withdrew before the genetic testing, mainly due to an increased awareness about the possible consequences of an unfavourable test result. To date, no catastrophic reactions were reported at the follow-up. CONCLUSIONS: Our case series shows that a structured genetic counselling and testing protocol for inherited dementia can be implemented in both affected individuals and at-risk relatives in a research setting. The procedure was shown to be safe in terms of occurrence of catastrophic events. A formal validation in larger cohorts is needed.

Medical Informatics Platform (MIP): A Pilot Study Across Clinical Italian Cohorts.

Introduction: With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify-CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup. Methods: We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, n = 432), Mild Cognitive Impairment (MCI, n = 456), and AD (n = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools. Results: The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from "slight" to "significant" in 80% of the cases. Discussion: GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology.

CSF cutoffs for MCI due to AD depend on APOEε4 carrier status.

Amyloid and tau pathological accumulation should be considered for Alzheimer's disease (AD) definition and before subjects' enrollment in disease-modifying trials. Although age, APOEε4, and sex influence cerebrospinal fluid (CSF) biomarker levels, none of these variables are considered by current normality/abnormality cutoffs. Using baseline CSF data from 2 independent cohorts (PharmaCOG/European Alzheimer's Disease Neuroimaging Initiative and Alzheimer's Disease Neuroimaging Initiative), we investigated the effect of age, APOEε4 status, and sex on CSF Aß42/P-tau distribution and cutoff extraction by applying mixture models with covariates. The Aß42/P-tau distribution revealed the presence of 3 subgroups (AD-like, intermediate, control-like) and 2 cutoffs. The identification of the intermediate subgroup and of the higher cutoff was APOEε4 dependent in both cohorts. APOE-specific classification (higher cutoff for APOEε4+, lower cutoff for APOEε4-) showed higher diagnostic accuracy in identifying MCI due to AD compared to single Aß42 and Aß42/P-tau cutoffs. APOEε4 influences amyloid and tau CSF markers and AD progression in MCI patients supporting i) the use of APOE-specific cutoffs to identify MCI due to AD and ii) the utility of considering APOE genotype for early AD diagnosis.

Age at onset reveals different functional connectivity abnormalities in prodromal Alzheimer's disease.

Age at symptom onset (AAO) underlies different Alzheimer's disease (AD) clinical variants: late-onset AD (LOAD) is characterized by memory deficits, while early-onset AD (EOAD) presents predominantly with non-memory symptoms. The involvement of different neural networks may explain these distinct clinical phenotypes. In this study, we tested the hypothesis of an early and selective involvement of neural networks based on AAO in AD. Twenty memory clinic patients with prodromal AD (i.e., mild cognitive impairment with an AD-like cerebrospinal fluid profile) and 30 healthy controls underwent a cognitive evaluation and a resting state functional MRI exam. Independent component analysis was performed to assess functional connectivity (FC) in the following networks: default mode, frontoparietal, limbic, visual, and sensorimotor. Patients were stratified into late-onset (pLOAD) and early-onset (pEOAD) prodromal AD according to the AAO and controls were stratified into younger and older groups accordingly. Decreased FC within the default mode and the limbic networks was observed in pLOAD, while pEOAD showed lower FC in the frontoparietal and visual networks. The sensorimotor network did not show differences between groups. A significant association was found between memory and limbic network FC in pLOAD, and between executive functions and frontoparietal network FC in pEOAD, although the latter association did not survive multiple comparison correction. Our findings indicate that aberrant connectivity in memory networks is associated with pLOAD, while networks underlying executive and visuo-spatial functions are affected in pEOAD. These findings are in line with the hypothesis that the pathophysiological mechanisms underlying EOAD and LOAD are distinct.

Randomized controlled trial on the efficacy of a multilevel non-pharmacologic intervention in older adults with subjective memory decline: design and baseline findings of the E.Mu.N.I. study.

BACKGROUND: Alzheimer's Disease (AD) is a multifactorial disorder driven by genetic and modifiable lifestyle risk factors. Lifestyle primary prevention initiatives may reduce the prevalence and incidence of dementia in older adults. OBJECTIVES: The E.Mu.N.I study is a randomized controlled trial investigating the effect of multilevel non-pharmacologic interventions on cognitive performances (primary outcome) and structural and vascular brain MRI markers (secondary outcome), as well as markers of brain functional connectivity change (exploratory outcome), in older adults with subjective memory decline (SMD). Here, we present the study design and the baseline features of the sample. METHODS: Cognitively intact older adults with SMD, enrolled between February 2016 and June 2017, were randomly assigned to one of the 3 interventions for 1 year: Active Control Intervention (ACI), i.e., educational lessons; Partial Intervention (PI), i.e., homotaurine administration (100 mg/die) and lessons on the Mediterranean diet; Multilevel Intervention (MI), i.e., PI plus computerized cognitive training and physical exercise training. RESULTS: One-hundred and twenty-eight eligible participants were enrolled (66% female; age: 68 ± 5 years). Eighty-two percent of the sample was composed of volunteers with SMD from the community. Participants were randomly allocated to the interventions as follows: ACI (N = 40), PI (N = 44), MI (N = 44). No significant differences among groups emerged on socio-demographic, clinical-neuropsychological variables and MRI markers at baseline. CONCLUSIONS: The outcomes obtained from the E.Mu.N.I. study will clarify the efficacy of multilevel non-pharmacologic interventions on cognitive and neuroimaging markers in SMD individuals. This is a crucial step forward for the development of cost-effective non-pharmacologic primary prevention initiatives for AD.

Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling study.

BACKGROUND: Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia. METHODS: In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models-a demographics model, a hippocampal volume model, and a CSF biomarkers model-by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework. FINDINGS: We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59-0·65), validated hippocampal volume model (0·67, 0·62-0·72), and updated CSF biomarkers model (0·72, 0·68-0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71-0·76). INTERPRETATION: We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour. FUNDING: ZonMW-Memorabel.

Prognostic value of Alzheimer's biomarkers in mild cognitive impairment: the effect of age at onset.

OBJECTIVE: The aim of this study is to assess the impact of age at onset on the prognostic value of Alzheimer's biomarkers in a large sample of patients with mild cognitive impairment (MCI). METHODS: We measured Aß42, t-tau, hippocampal volume on magnetic resonance imaging (MRI) and cortical metabolism on fluorodeoxyglucose-positron emission tomography (FDG-PET) in 188 MCI patients followed for at least 1 year. We categorised patients into earlier and later onset (EO/LO). Receiver operating characteristic curves and corresponding areas under the curve (AUCs) were performed to assess and compar the biomarker prognostic performances in EO and LO groups. Linear Model was adopted for estimating the time-to-progression in relation with earlier/later onset MCI groups and biomarkers. RESULTS: In earlier onset patients, all the assessed biomarkers were able to predict cognitive decline (p < 0.05), with FDG-PET showing the best performance. In later onset patients, all biomarkers but t-tau predicted cognitive decline (p < 0.05). Moreover, FDG-PET alone in earlier onset patients showed a higher prognostic value than the one resulting from the combination of all the biomarkers in later onset patients (earlier onset AUC 0.935 vs later onset AUC 0.753, p < 0.001). Finally, FDG-PET showed a different prognostic value between earlier and later onset patients (p = 0.040) in time-to-progression allowing an estimate of the time free from disease. DISCUSSION: FDG-PET may represent the most universal tool for the establishment of a prognosis in MCI patients and may be used for obtaining an onset-related estimate of the time free from disease.

Biomarker Matrix to Track Short Term Disease Progression in Amnestic Mild Cognitive Impairment Patients with Prodromal Alzheimer's Disease.

BACKGROUND: Assessment of human brain atrophy in temporal regions using magnetic resonance imaging (MRI), resting state functional MRI connectivity in the left parietal cortex, and limbic electroencephalographic (rsEEG) rhythms as well as plasma amyloid peptide 42 (Aß42) has shown that each is a promising biomarker of disease progression in amnestic mild cognitive impairment (aMCI) patients with prodromal Alzheimer's disease (AD). However, the value of their combined use is unknown. OBJECTIVE: To evaluate the association with cognitive decline and the effect on sample size calculation when using a biomarker composite matrix in prodromal AD clinical trials. METHODS: Multicenter longitudinal study with follow-up of 2 years or until development of incident dementia. APOE ɛ4-specific cerebrospinal fluid (CSF) Aß42/P-tau cut-offs were used to identify aMCI with prodromal AD. Linear mixed models were performed 1) with repeated matrix values and time as factors to explain the longitudinal changes in ADAS-cog13, 2) with CSF Aß42/P-tau status, time, and CSF Aß42/P-tau status×time interaction as factors to explain the longitudinal changes in matrix measures, and 3) to compute sample size estimation for a trial implemented with the selected matrices. RESULTS: The best composite matrix included the MRI volumes of hippocampal dentate gyrus and lateral ventricle. This matrix showed the best sensitivity to track disease progression and required a sample size 31% lower than that of the best individual biomarker (i.e., volume of hippocampal dentate gyrus). CONCLUSION: Optimal matrices improved the statistical power to track disease development and to measure clinical progression in the short-term period. This might contribute to optimize the design of future clinical trials in MCI.

Head-to-Head Comparison among Semi-Quantification Tools of Brain FDG-PET to Aid the Diagnosis of Prodromal Alzheimer's Disease.

BACKGROUND: Several automatic tools have been implemented for semi-quantitative assessment of brain [18]F-FDG-PET. OBJECTIVE: We aimed to head-to-head compare the diagnostic performance among three statistical parametric mapping (SPM)-based approaches, another voxel-based tool (i.e., PALZ), and a volumetric region of interest (VROI-SVM)-based approach, in distinguishing patients with prodromal Alzheimer's disease (pAD) from controls. METHODS: Sixty-two pAD patients (MMSE score = 27.0±1.6) and one hundred-nine healthy subjects (CTR) (MMSE score = 29.2±1.2) were enrolled in five centers of the European Alzheimer's Disease Consortium. The three SPM-based methods, based on different rationales, included 1) a cluster identified through the correlation analysis between [18]F-FDG-PET and a verbal memory test (VROI-1), 2) a VROI derived from the comparison between pAD and CTR (VROI-2), and 3) visual analysis of individual maps obtained by the comparison between each subject and CTR (SPM-Maps). The VROI-SVM approach was based on 6 VROI plus 6 VROI asymmetry values derived from the pAD versus CTR comparison thanks to support vector machine (SVM). RESULTS: The areas under the ROC curves between pAD and CTR were 0.84 for VROI-1, 0.83 for VROI-2, 0.79 for SPM maps, 0.87 for PALZ, and 0.95 for VROI-SVM. Pairwise comparisons of Youden index did not show statistically significant differences in diagnostic performance between VROI-1, VROI-2, SPM-Maps, and PALZ score whereas VROI-SVM performed significantly (p < 0.005) better than any of the other methods. CONCLUSION: The study confirms the good accuracy of [18]F-FDG-PET in discriminating healthy subjects from pAD and highlights that a non-linear, automatic VROI classifier based on SVM performs better than the voxel-based methods.