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BackgroundThe key Alzheimer’s disease (AD) biomarkers are traditionally measured with techniques/exams that are either expensive (amyloid-positron emission tomography (PET) and tau-PET), invasive (cerebrospinal fluid Aβ42and p-tau181), or poorly specific (atrophy on MRI and hypometabolism on fluorodeoxyglucose-PET). Recently developed plasma biomarkers could significantly enhance the efficiency of the diagnostic pathway in memory clinics and improve patient care. This study aimed to: (1) confirm the correlations between plasma and traditional AD biomarkers, (2) assess the diagnostic accuracy of plasma biomarkers as compared with traditional biomarkers, and (3) estimate the proportion of traditional exams potentially saved thanks to the use of plasma biomarkers.MethodsParticipants were 200 patients with plasma biomarkers and at least one traditional biomarker collected within 12 months.ResultsOverall, plasma biomarkers significantly correlated with biomarkers assessed through traditional techniques: up tor=0.50 (pr=0.43 (p=0.002) among tau, andr=−0.23 (p=0.001) among neurodegeneration biomarkers. Moreover, plasma biomarkers showed high accuracy in discriminating the biomarker status (normal or abnormal) determined by using traditional biomarkers: up to area under the curve (AUC)=0.87 for amyloid, AUC=0.82 for tau, and AUC=0.63 for neurodegeneration status. The use of plasma as a gateway to traditional biomarkers using cohort-specific thresholds (with 95% sensitivity and 95% specificity) could save up to 49% of amyloid, 38% of tau, and 16% of neurodegeneration biomarkers.ConclusionThe implementation of plasma biomarkers could save a remarkable proportion of more expensive traditional exams, making the diagnostic workup more cost-effective and improving patient care.

The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE e4-related sporadic AD and APOE e4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD. The amyloid hypothesis has been the dominant model for the pathogenesis of Alzheimer disease for several decades. In this Perspective, Giovanni Frisoni and colleagues examine evidence for and against this hypothesis before outlining an alternative model, the probabilistic model of Alzheimer disease.

Observational population studies indicate that prevention of dementia and cognitive decline is being accomplished, possibly as an unintended result of better vascular prevention and healthier lifestyles. Population aging in the coming decades requires deliberate efforts to further decrease its prevalence and societal burden. Increasing evidence supports the efficacy of preventive interventions on persons with intact cognition and high dementia risk. We report recommendations for the deployment of second-generation memory clinics (Brain Health Services) whose mission is evidence-based and ethical dementia prevention in at-risk individuals. The cornerstone interventions consist of (i) assessment of genetic and potentially modifiable risk factors including brain pathology, and risk stratification, (ii) risk communication with ad-hoc protocols, (iii) risk reduction with multi-domain interventions, and (iv) cognitive enhancement with cognitive and physical training. A roadmap is proposed for concept validation and ensuing clinical deployment.

Background: Subjective Cognitive Decline (SCD) is characterized by subjective cognitive complaints without objective cognitive impairment and is considered a risk factor for cognitive decline and dementia. However, most SCD patients will not develop neurodegenerative disorders, yet they may suffer from minor psychiatric, neurological, or somatic comorbidities. The aim of the present study is to provide a taxonomy of the heterogeneous SCD entity by isolating homogenous SCD subgroups with specific clinical features and cognitive trajectories. Methods: Participants were fifty-five SCD individuals consecutively recruited at the Geneva Memory Center. Based on clinical reports, they were classified into three clinically pre-defined subgroups: (i) those with psychological or psychiatric comorbidities (Psy), (ii) those with somatic comorbidities (SomCom), (iii) and those with no apparent cause (NAC). Baseline demographics, clinical, cognitive, and biomarker differences among the SCD subgroups were assessed. Longitudinal cognitive changes (average 3 years follow-up) were modeled using a linear mixed model. Results: Out of the 55 SCD cases, 16 were SomCom, 18 Psy, and 21 NAC. 47% were female, mean age was 71 years. We observed higher frequency of APOE ε4 carriers in NAC (53%) compared to SomCom (14%) and Psy (0%, P=0.023) and lower level of plasma Aβ42 in NAC (6.8±1.0) compared to SomCom (8.4±1.1; P=0.031). SomCom subjects were older (74 years) than Psy (67 years, P=0.011), and had greater medial temporal lobe atrophy (1.0±1.0) than Psy (0.2±0.6) and NAC (0.4±0.5, P=0.005). SomCom have worse episodic memory performances (14.5±3.5) than Psy (15.8±0.4) and SomCom (15.1±0.7, P=0.032). We observed a slightly steeper, yet not statistically significant, cognitive decline in NAC (β=-0.48) compared to Psy (β=-0.28) and SomCom (β=-0.24). Conclusions: NAC feature higher proportion of APOE ε4 carriers, lower plasma Aβ42, worse memory performance, and a trend towards steeper cognitive decline than SomCom and Psy. Taken together, these findings suggest that NAC are at higher risk of cognitive decline due to AD. The proposed clinical taxonomy might be implemented in clinical practice to identify SCD at higher risk. However, such taxonomy should be tested on an independent cohort with larger sample size.

Importance Individuals who are amyloid-positive with subjective cognitive decline and clinical features increasing the likelihood of preclinical Alzheimer disease (SCD+) are at higher risk of developing dementia. Some individuals with SCD+ undergo amyloid-positron emission tomography (PET) as part of research studies and frequently wish to know their amyloid status; however, the disclosure of a positive amyloid-PET result might have psychological risks. Objective To assess the psychological outcomes of the amyloid-PET result disclosure in individuals with SCD+ and explore which variables are associated with a safer disclosure in individuals who are amyloid positive. Design, Setting, and Participants This prospective, multicenter study was conducted as part of The Amyloid Imaging to Prevent Alzheimer Disease Diagnostic and Patient Management Study (AMYPAD-DPMS) (recruitment period: from April 2018 to October 2020). The setting was 5 European memory clinics, and participants included patients with SCD+ who underwent amyloid-PET. Statistical analysis was performed from July to October 2022. Exposures Disclosure of amyloid-PET result. Main Outcomes and Measures Psychological outcomes were defined as (1) disclosure related distress, assessed using the Impact of Event Scale–Revised (IES-R; scores of at least 33 indicate probable presence of posttraumatic stress disorder [PTSD]); and (2) anxiety and depression, assessed using the Hospital Anxiety and Depression scale (HADS; scores of at least 15 indicate probable presence of severe mood disorder symptoms). Results After disclosure, 27 patients with amyloid-positive SCD+ (median [IQR] age, 70 [66-74] years; gender: 14 men [52%]; median [IQR] education: 15 [13 to 17] years, median [IQR] Mini-Mental State Examination [MMSE] score, 29 [28 to 30]) had higher median (IQR) IES-R total score (10 [2 to 14] vs 0 [0 to 2]; P P P P P = .06) and Depression (–1.0 [–2.0 to 0.0] vs –1.0 [–3.0 to 0.0]; P = .46) deltas (score after disclosure – scores at baseline). In patients with amyloid-positive SCD+, despite the small sample size, higher education was associated with lower disclosure-related distress (ρ = –0.43; P = .02) whereas the presence of study partner was associated with higher disclosure-related distress (W = 7.5; P = .03). No participants with amyloid-positive SCD+ showed probable presence of PTSD or severe anxiety or depression symptoms at follow-up. Conclusions and Relevance The disclosure of a positive amyloid-PET result to patients with SCD+ was associated with a bigger psychological change, yet such change did not reach the threshold for clinical concern.

Background: The introduction of tau positron emission tomography (PET) ligands has allowed for the in vivo assessment of tau pathology in Alzheimer’s disease (AD). The recent development and FDA approval of [18F]flortaucipir (FTP) reader guidelines has enabled standardized visual assessment of FTP PET scans as showing negative, moderate or advanced AD tau patterns, thereby facilitating implementation of FTP scans in clinical practice. Although various studies have reported associations between regional FTP signal and neurodegeneration, the relationship between the standardized visual FTP AD patterns and markers of neurodegeneration has not yet been studied. This study aims to understand how FTP AD visual patterns relate to markers of neurodegeneration from structural MRI and FDG-PET scans. Specifically, it focusses on characterizing regional neurodegeneration associated with the moderate AD pattern, both in cognitively normal (CN) and cognitively impaired participants (CI). Method: Participants from five cohorts were included: the Alzheimer’s Disease Neuroimaging Initiative, Harvard Aging Brain Study, A4 study, the Geneva Memory Clinic cohort and AVID’s A05 study. These cohorts include CN participants, mild cognitively impaired and AD dementia patients who have available FTP, MRI and/or FDG scans, a subset also received follow-up MRI scans. Furthermore, Centiloid values are available for all participants to quantitatively determine amyloid-β (Aβ) positivity. All FTP scans are currently independently evaluated by three trained readers, blinded to clinical and imaging information. Majority read is used to assign scans to the negative, moderate or advanced AD tau pattern groups. Result: A total of 1948 participants underwent baseline FTP PET and MRI scans, a subset of 462 participants also underwent FDG-PET scans. Between-group differences in MRI- and FDG-derived patterns of neurodegeneration are evaluated cross-sectionally. In addition, the value of FTP AD patterns for predicting longitudinal neurodegeneration using MRI-derived atrophy measures is assessed using Linear Mixed Models. All analyses are conducted separately for CN and CI participants, as well as stratified by Aβ (positive vs. negative) status. NB. Results of these analyses will be presented during the conference. Conclusion: This study will contribute to our understanding of the clinical relevance and prognostic value of the moderate and advanced FTP AD patterns in CN and CI individuals.

Background: The advent of positron emission tomography (PET) imaging with tracers such as [18F]flortaucipir (FTP) has allowed in-vivo visualization of aggregated tau in Alzheimer’s disease (AD). Recently, a clinically applicable visual interpretation method for FTP PET yielding negative, moderate, and advanced AD visual patterns was developed, leading to its subsequent approval by the US Food and Drug Administration (FDA). Yet, the prevalence and longitudinal clinical outcomes of the different AD-associated visual patterns, in particular the moderate AD pattern, have not been investigated systematically across the clinical spectrum of AD. Method: We included cognitively normal individuals and patients with mild cognitive impairment and AD dementia from five observational cohort studies — Alzheimer’s Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain study (HABS), A4 study, AVID’s A05 study and Geneva Memory Clinic cohort — all of which had available FTP PET scans. Furthermore, Aβ status, established with Aβ PET, was available in 1924 participants (98%), and longitudinal clinical and cognitive data was obtained for 968 participants over an average follow-up time of 2.2 years. Three readers, blinded to clinical and imaging information, will independently evaluate each FTP PET scan, and an individual’s FTP uptake pattern will be interpreted as negative, moderate, or advanced AD tau pattern, based on the majority read of the three readers. Multinomial generalized additive models (GAM) will be fitted to provide prevalence estimates of each FTP AD pattern. Mixed models for repeated measures (MMRM) will be used to estimate cognitive decline trajectories. Result: A total of 1963 participants had available FTP PET scans. We will investigate the prevalence of the different FTP AD patterns as a function of age per diagnostic group, stratifying participants by β-amyloid status and APOE genotype. Further, in the subset of participants with available longitudinal clinical data, we will explore how the different FTP patterns associate with clinical decline across the aforementioned diagnostic groups. Conclusion: Our large-scale study will contribute significantly to elucidating the clinical relevance of FTP visual reads across the AD spectrum, potentially widening its applicability and promoting its use in patient assessment and in clinical prevention trials.

Background Subjective cognitive decline (SCD) is the subjective perception of a decline in memory and/or other cognitive functions in the absence of objective evidence. Some SCD individuals however may suffer from very early stages of neurodegenerative diseases (such as Alzheimer’s disease, AD), minor psychiatric conditions, neurological, and/or somatic comorbidities. Even if a theoretical framework has been established, the etiology of SCD remains far from elucidated. Clinical observations recently lead to the hypothesis that individuals with incipient AD may have overestimated metacognitive judgements of their own cognitive performance, while those with psychiatric disorders typically present underestimated metacognitive judgements. Moreover, brain connectivity changes are known correlates of AD and psychiatric conditions and might be used as biomarkers to discriminate SCD individuals of different etiologies. The aim of the COSCODE study is to identify metacognition, connectivity, behavioral, and biomarker profiles associated with different etiologies of SCD. Here we present its rationale and study design. Methods COSCODE is an observational, longitudinal (4 years), prospective clinical cohort study involving 120 SCD, and 80 control study participants (40 individuals with no cognitive impairment, and 40 living with mild cognitive impairment - MCI, or dementia due to AD), all of which will undergo diffusion magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) as well as behavioral and biomarker assessments at baseline and after 1 and 2 years. Both hypothesis-driven and data-driven cluster analysis approaches will be used to identify SCD sub-types based on metacognition, connectivity, behavioral, and biomarker features. Conclusion COSCODE will allow defining and interpreting the constellation of signs and symptoms associated with different etiologies of SCD, paving the way to the development of cost-effective risk assessment and prevention protocols.

We conducted a cross-sectional pilot study to explore the biological substrate of the Motoric Cognitive Risk (MCR) syndrome in a Memory Clinic cohort, using a multimodal imaging approach. Twenty participants were recruited and classified as MCR+/−. Amyloid- and tau-PET uptakes, temporal atrophy, white matter hyperintensities, lateral ventricular volume (LVV), and diffusion tensor parameters were compared between groups. No significant differences were found in imaging features related to Alzheimer’s disease or gross vascular damage. MCR+ patients had increased LVV and altered diffusion parameters in the superior corona radiata. Ventricular enlargement and microstructural damage of the surrounding white matter tracts could contribute to MCR pathophysiology.

In analogy to the friction ridges of a human finger, the functional connectivity patterns of the human brain can be used to identify a given individual from a population. In other words, functional connectivity patterns constitute a marker of human identity, or a ‘brain fingerprint’. Notably, very little is known about whether brain fingerprints are preserved in brain ageing and in the presence of cognitive decline. Using fMRI data of 96 memory clinic subjects, here we show that individuals functional connectivity profiles remain unique even when cognitive impairment occurs. Yet, the patterns of functional connectivity that make the healthy subjects more identifiable change during cognitive decline, suggesting that the brain undergoes functional reconfiguration. Notably, the functional connections that were the most reliable in healthy cohorts disappeared during cognitive decline, leaving room for other stable connections, adapting to the process of neurodegeneration. We believe that these findings could help in moving towards a more personalised medicine and treatment during cognitive decline, and we hope they will set the ground for clinical fingerprinting of brain disease.

Background subjective cognitive decline (SCD) refers to the subjective experience of cognitive decline in the absence of detectable cognitive impairment. SCD has been largely studied as a risk condition for cognitive decline. Empirical observations suggest that persons with SCD are heterogeneous, including individuals with early Alzheimer’s disease and others with psychological vulnerabilities and/or physical comorbidity. The semiology of SCD is still in its infancy, and the features predicting cognitive decline are poorly defined. The present study aims to identify subgroups of SCD using a data-driven approach and study their clinical evolution across 8 years. Methods the study population is the InveCe.Ab population-based cohort, including cognitively unimpaired people aged 70–74 years and followed for 8 years. Hierarchical cluster analysis (HCA) was carried out to identify distinct SCD subgroups based on nine clinical and cognitive features. Longitudinal changes by baseline SCD status were estimated using linear mixed models for cognitive decline and Cox proportional-hazard model for all-cause dementia risk. Results out of 956 individuals, 513 were female (54%); and the mean age was 72.1 (SD = 1.3), education was 7.2 (3.3), and 370 (39%) reported cognitive complaints (SCD). The HCA resulted in two clusters (SCD1 and SCD2). SCD2 were less educated and had more comorbidities, cardiovascular risk and depressive symptoms than SCD1 and controls. SCD2 presented steeper cognitive decline (Mini-Mental State Examination; β = −0.31) and increased all-cause dementia risk (hazard-ratio = 3.4). Conclusions at the population level, basic clinical information can differentiate individuals with SCD at higher risk of developing dementia, underlining the heterogeneous nature of this population even in a sample selected for a narrow age range, in a specific geographic area.

International audience; SimulAD is a computational disease progression model (DPM) originally developed on the ADNI database to simulate the evolution of clinical and imaging markers characteristic of AD, and to quantify the disease severity (DS) of a subject. In this work, we assessed the validity of this estimated DS, as well as the generalization of the DPM, by applying SimulAD on a new cohort from the Geneva Memory Center (GMC). The differences between the estimated DS of healthy, mild cognitive impairment and AD dementia groups were statistically significant (p-values < 0.05; d ≥ 0.8). DS correlated with MMSE (ρ =-0.55), hippocampal atrophy (ρ =-0.62), glucose hypometabolism (ρ =-0.67), amyloid burden (ρ = 0.31) and tau deposition (ρ = 0.62) (p-values < 0.01). Based on the dynamics estimated on the ADNI cohort, we simulated a DPM for the subjects of the GMC cohort. The difference between the temporal evolution of similar biomarkers simulated on the ADNI and GMC cohorts remained below 10%. This study illustrates the robustness and good generalization of SimulAD, highlighting its potential for clinical and pharmaceutical studies.

The A/T/N model is a research framework proposed to investigate Alzheimer’s disease (AD) pathological bases (i.e., amyloidosis A, neurofibrillary tangles T, and neurodegeneration N). The application of this system on clinical populations is still limited. The aim of the study is to evaluate the topography of T distribution by 18F-flortaucipir PET in relation to A and N and to describe the A/T/N status through imaging biomarkers in memory clinic patients. Eighty-one patients with subjective and objective cognitive impairment were classified as A+/A− and N+/N− through amyloid PET and structural MRI. Tau deposition was compared across A/N subgroups at voxel level. T status was defined through a global cut point based on A/N subgroups and subjects were categorized following the A/T/N model. A+N+ and A+N− subgroups showed higher tau burden compared to A−N− group, with A+N− showing significant deposition limited to the medial and lateral temporal regions. Global cut point discriminated A+N+ and A+N− from A−N− subjects. On A/T/N classification, 23% of patients showed a negative biomarker profile, 58% fell within the Alzheimer’s continuum, and 19% of the sample was characterized by non-AD pathologic change. Medial and lateral temporal regions represent a site of significant tau accumulation in A+ subjects and possibly a useful marker of early clinical changes. This is the first study in which the A/T/N model is applied using 18F-flortaucipir PET in a memory clinic population. The majority of patients showed a profile consistent with the Alzheimer’s continuum, while a minor percentage showed a profile suggestive of possible other neurodegenerative diseases. These results support the applicability of the A/T/N model in clinical practice.

Cognitive complaints in the absence of objective cognitive impairment, observed in patients with subjective cognitive decline (SCD), are common in old age. The first step to postpone cognitive decline is to use techniques known to improve cognition, i.e., cognitive enhancement techniques.We aimed to provide clinical recommendations to improve cognitive performance in cognitively unimpaired individuals, by using cognitive, mental, or physical training (CMPT), non-invasive brain stimulations (NIBS), drugs, or nutrients. We made a systematic review of CMPT studies based on the GRADE method rating the strength of evidence.CMPT have clinically relevant effects on cognitive and non-cognitive outcomes. The quality of evidence supporting the improvement of outcomes following a CMPT was high for metamemory; moderate for executive functions, attention, global cognition, and generalization in daily life; and low for objective memory, subjective memory, motivation, mood, and quality of life, as well as a transfer to other cognitive functions. Regarding specific interventions, CMPT based on repeated practice (e.g., video games or mindfulness, but not physical training) improved attention and executive functions significantly, while CMPT based on strategic learning significantly improved objective memory.We found encouraging evidence supporting the potential effect of NIBS in improving memory performance, and reducing the perception of self-perceived memory decline in SCD. Yet, the high heterogeneity of stimulation protocols in the different studies prevent the issuing of clear-cut recommendations for implementation in a clinical setting. No conclusive argument was found to recommend any of the main pharmacological cognitive enhancement drugs (“smart drugs”, acetylcholinesterase inhibitors, memantine, antidepressant) or herbal extracts (Panax ginseng, Gingko biloba, and Bacopa monnieri) in people without cognitive impairment.Altogether, this systematic review provides evidence for CMPT to improve cognition, encouraging results for NIBS although more studies are needed, while it does not support the use of drugs or nutrients.

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was −0.22[IQR = 0.50] for LGA-SPM8, −0.12[0.57] for LGA-SPM12, −0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies.

Purpose Assess the individual and combined diagnostic value of amyloid-PET and tau-PET in a memory clinic population. Methods Clinical reports of 136 patients were randomly assigned to two diagnostic pathways: AMY-TAU, amyloid-PET is presented before tau-PET; and TAU-AMY, tau-PET is presented before amyloid-PET. Two neurologists independently assessed all reports with a balanced randomized design, and expressed etiological diagnosis and diagnostic confidence (50–100%) three times: (i) at baseline based on the routine diagnostic workup, (ii) after the first exam (amyloid-PET for the AMY-TAU pathway, and tau-PET for the TAU-AMY pathway), and (iii) after the remaining exam. The main outcomes were changes in diagnosis (from AD to non-AD or vice versa) and in diagnostic confidence. Results Amyloid-PET and tau-PET, when presented as the first exam, resulted in a change of etiological diagnosis in 28% (p = 0.006) and 28% (p p p p > 0.05). We observed a stronger impact of a negative amyloid-PET versus a negative tau-PET (p = 0.014). When added as the second exam, amyloid-PET and tau-PET resulted in a further change in etiological diagnosis in 6% (p = 0.077) and 9% (p = 0.149) of cases, and diagnostic confidence increased by 4% (p p p > 0.05). Conclusion Amyloid-PET and tau-PET significantly impacted diagnosis and diagnostic confidence in a similar way, although a negative amyloid-PET has a stronger impact on diagnosis than a negative tau-PET. Adding either of the two as second exam further improved diagnostic confidence. Trial number PB 2016-01346.

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 Aβ42/P-tau distribution and cutoff extraction by applying mixture models with covariates. The Aβ42/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 Aβ42 and Aβ42/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.

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.