Alzheimer's disease is the leading cause of dementia and among the top ten leading causes of death in high-income countries. Exponential advances in epidemiology, genetics, diagnostic imaging and fluid biomarkers, treatment, and prevention in the last decade reinforce the notion that we are entering a new era in the clinical management of Alzheimer's disease. However, far from triumphalism, this momentum should be accelerated to achieve the goals of preventing Alzheimer's disease and arresting its progression. In this Seminar, we summarise this progress and highlight unmet needs and areas of research priority.

Dans une première partie nous décrivons la clinique neurologique des fonctions cognitives. Il s’agit d’une part essentielle de la neurologie, fondée sur l'anamnèse et l'observation d'un patient souvent incapable d'analyser lui-même son handicap, et qu'aucun examen complémentaire ne peut remplacer. Après avoir décrit les étapes cliniques préliminaires du diagnostic d'un déficit des fonctions cognitives, nous précisons la démarche neuropsychologique des spécialistes : médecin, psychologue ou orthophoniste. Dans une deuxième partie, nous analysons quatre situations fréquentes dans lesquelles cette démarche clinique pourtant indispensable n’est pas toujours correctement assurée : plainte de mémoire faisant craindre l'entrée dans la maladie d’Alzheimer, séquelles d'accidents vasculaires cérébraux y compris mineurs, traumatismes crâniens et modifications comportementales pouvant évoquer à tort un trouble psychogène. Dans une troisième partie nous décrivons les moyens et les lacunes de cette expertise neuropsychologique, tels que décrits par les professionnels concernés. Nous terminons par une série de recommandations visant à donner à la neuropsychologie clinique la place qui lui est nécessaire dans la pratique médicale pour une prise en charge adéquate de tous les patients atteints de troubles cognitifs : renforcement des moyens, amélioration de la formation et réflexion sur la nomenclature concernant certains actes professionnels.

The introduction of disease-modifying therapies for Alzheimer’s disease (AD-DMTs) is reshaping clinical practice, raising critical questions about patient selection, diagnostic pathways, treatment appropriateness, and equity of access. Frailty, a multidimensional condition of reduced physiological reserve and increased vulnerability to stressors, is common in older adults with AD, yet has not been systematically assessed in AD-DMTs trials, limiting the generalizability of trial findings to real-world populations.In this review, we examine the role of frailty in the emerging era of AD-DMTs, summarizing evidence on its prevalence and prognostic relevance, approaches to its assessment, and its potential impact on treatment safety and effectiveness. We propose that regular frailty assessment should inform decision-making in both clinical trials and clinical practice, while frailty-informed management—including medication review and multidomain interventions—may support more appropriate, individualized care.

Alzheimer's disease is the leading cause of dementia and among the top ten leading causes of death in high-income countries. Exponential advances in epidemiology, genetics, diagnostic imaging and fluid biomarkers, treatment, and prevention in the last decade reinforce the notion that we are entering a new era in the clinical management of Alzheimer's disease. However, far from triumphalism, this momentum should be accelerated to achieve the goals of preventing Alzheimer's disease and arresting its progression. In this Seminar, we summarise this progress and highlight unmet needs and areas of research priority.

Background: Alzheimer's disease (AD) patients are characterized by an early decline of episodic memory due to hippocampal damage. Nonetheless, besides the classical negative symptoms related to episodic memory deficits, i.e. failure to retrieve information, it has been shown that AD patients can also suffer from positives symptoms, i.e. confabulations. Some theoretical accounts have been proposed to explain the cognitive mechanisms underlying confabulation. Yet, even if most of these models have lead to some research trying to validate cognitive deficits in some cognitive domains, in particular executive functions, to our knowledge, none has yet tried to determine the specific cognitive profile of confabulatory patients. In the present study the main aim is to characterize the specific cognitive profile of confabulatory patients. Thus, given that AD patients' cognitive profile is well known and documented, we compare mild to moderate AD patients with and without confabulations. Methods: 37 healthy control (HC) and 35 individuals with mild to moderate AD were recruited at the Pitie Salpetriere University Hospital. All participants were evaluated on Dalla Barba's Confabulation Battery to determine their tendency to produce provoked confabulations. Thus, among AD patients, we distinguish between those who produced confabulations in episodic memory questions, and those who did not. Accordingly 27 AD patients were considered free of confabulations (ADC-), and 8 as confabulators (ADC+) (none HC met the criteria). All participants were assessed on a comprehensive neuropsychological battery. Results: Statistical analyses showed a significant difference between HC participants and the two groups of AD patients, in almost all cognitive domains assessed. However, when comparing the two AD groups, they did not show distinct profiles. Moreover, regarding the type of confabulations, ADC+ produced significantly more confabulations to the Episodic questions (both concerning past and future). Conclusions: By not demonstrating cognitive differences between patients with and without confabulations, our results cast doubts on some confabulation models, which assume a unique and sufficient cognitive (e.g. executive) deficit underlying the onset of confabulations. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of Pitie Salpetriere Hospital gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Importance:Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective:To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources:PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection:Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis:Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures:Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results:This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I2 = 80%). Conclusions and Relevance:In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Abnormal brain accumulation of amyloid-β peptides, represents one of the earliest biological indicators of Alzheimer’s disease (AD) risk. Estimation on amyloid positivity (A+) prevalence among older adults without dementia are needed to assess the epidemiological impact of AD diagnosis solely through biological markers. We combined data from the French MEMENTO clinical cohort, where amyloid status was assessed through reference procedures, with the nationally representative SHARE-HCAP survey. Using stabilized inverse odds of selection weights, we adjusted the MEMENTO sample to estimate the prevalence of A+ in the French population aged 65–85 without dementia and their five-year risk of developing AD dementia. A+ prevalence was 21.4% (95% CI: 18.4–24.7) in French adults aged 65–85 without dementia i.e. approximately 2.5 million individuals, reaching 27.5% in the 80–85 age group. Over five years of follow-up, the cumulative incidence of AD dementia was 22.7% among A+ individuals, 8.0% among cognitively normal A+ adults and 62.3% among those with mild cognitive impairment. While A+ is common in older adults without dementia, most do not develop dementia within five years. Defining AD by A+ could substantially increase diagnoses, raising major public health, ethical, and health system challenges, especially as new anti-amyloid therapies emerge.

Objective Retinal biomarkers accessible via non-invasive optical coherence tomography (OCT) could facilitate early detection of Alzheimer’s disease (AD), complementing current invasive or costly diagnostic methods. This review evaluates the evidence for spectral-domain OCT (SD-OCT) and OCT angiography (OCT-A) in identifying retinal changes associated with preclinical and early AD.Methods and analysis We conducted a systematic review registered in PROSPERO and aligned with Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. PubMed/MEDLINE was searched up to April 2025, complemented by reference list screening and citation tracking. Eligible studies assessed SD-OCT and/or OCT-A in biomarker-defined preclinical or early AD, mild cognitive impairment or mild AD. Data were synthesised narratively by disease stage, and methodological quality was appraised with the Newcastle-Ottawa Scale.Results 22 studies met inclusion criteria. Reported alterations included thinning of the peripapillary retinal nerve fibre layer and retinal ganglion cell layer, macular and choroidal thickness changes and microvascular alterations on OCT-A. However, findings were heterogeneous: some studies observed early thickening or increased vascular density, possibly reflecting inflammatory or compensatory mechanisms, while others reported thinning and rarefaction more consistent with neurodegeneration. Most studies were of moderate quality, limited by small sample sizes, cross-sectional designs and incomplete control for ocular/systemic confounders.Conclusion SD-OCT and OCT-A hold promise as candidate biomarkers of early AD, but current evidence remains variable, non-specific and methodologically constrained. Further research is needed to standardise imaging protocols, validate findings in biomarker-confirmed longitudinal cohorts and compare OCT-based measures across dementia subtypes. Integration with other biomarkers (eg, plasma or metabolomics) may improve diagnostic specificity and support translation of OCT/OCT-A into clinical practice.PROSPERO registration number CRD42024600456.

Alzheimer's disease involves a drastic departure from the cognitive, functional, and behavioural trajectory of normal ageing, and is both a dreaded and highly prevalent cause of disability to individuals, and a leading source of health and social care expenditure for society. Before the advent of biomarkers, post-mortem examination was the only method available to establish a definitive diagnosis. In this first paper of the Series, we review state-of-the-art diagnostic practices and the typical patient journey in specialist settings, where clinicians engage in a differential diagnosis to establish whether Alzheimer's pathology (cerebral deposition of β-amyloid and hyperphosphorylated tau) is a contributor to cognitive impairment. Biomarkers indicating dysregulation of β-amyloid and tau homeostasis, measured with PET and cerebrospinal fluid analysis, allow a molecular-level diagnosis—a mandatory step in defining eligibility for the recently approved anti-amyloid treatments. We anticipate that easily accessible blood biomarkers, already available in some countries, will lead to a new diagnostic revolution and bring about major changes in health-care systems worldwide.

BACKGROUND:Socio-cognitive assessment in neurocognitive disorders (NCDs) is rare in clinical practice and no consensus exists as to a uniform operationalization of socio-cognitive measures for NCDs in memory clinics. The SIGNATURE initiative aims to optimize the use of socio-cognitive measures in memory clinics, defining expert recommendations. We report consortium guidelines for the use of socio-cognitive measures in NCDs based on available evidence from the literature and the current state of practices in memory clinics. METHODS:Using a Delphi consensus method supported by a literature review and the results of an international survey, 22 specialists defined recommendations for the context of use, relevance in NCD diagnosis, priorities for future research and facilitators/obstacles of socio-cognitive assessment in major and mild NCDs. RESULTS:Overall, panelists recommended social cognition testing in routine diagnostic assessment to evaluate both socio-cognitive and socio-behavioral alterations. A set of clinical, methodological, implementation and external factors facilitating or hampering the use of socio-cognitive tasks was identified. CONCLUSIONS:This is the first focused endeavor to favor the implementation of socio-cognitive assessment, which is required by DSM-5 but seldom performed despite clear evidence of its clinical relevance for diagnosis and care. Our results provide an initial set of recommendations, refinable through the future actions of the SIGNATURE initiative. Future collaborative clinical research projects should overcome current limitations and foster the use of ecological and cross-culturally validated measures in clinics.

BackgroundMetabolic biomarkers can potentially be used for early diagnosis, prognostic risk stratification and/or early treatment and prevention of individuals at risk to develop Alzheimer's disease (AD).ObjectiveOur goal was to evaluate changes in metabolite concentration levels associated with AD to identify biomarkers that could support early and accurate diagnosis and therapeutic interventions by using targeted mass spectrometry and machine learning approaches.MethodsSerum samples collected from a total of 107 individuals, including 55 individuals diagnosed with AD and 52 healthy controls (HC) enrolled previously to ADDIA cohort were analyzed using the biocrates AbsoluteIDQ® p400 HR kit metabolite and lipid panel. Several machine learning models including Least Absolute Shrinkage and Selection Operator (LASSO), Partial Least Squares (PLS), Random Forest, and XGBoost were trained to classify AD and HC. Repeated cross-validation was used to ensure performance evaluation.ResultsThe LASSO and PLS models showed the strongest classification performance on the test set, achieving area under the ROC curve (AUC) values of 0.84 and 0.90, respectively. A refined model based on only the top 5 metabolites maintained strong performance, and the inclusion of Apolipoprotein E (APOE) genotype information notably improved classification accuracy, particularly by reducing false negatives in AD cases.ConclusionsThese results highlight important metabolic signatures that could help to reduce misdiagnosis and support the development of metabolomic panels to detect AD. The combination of multiple serum metabolic biomarkers and APOE genotyping can significantly improve classification accuracy and potentially assist in making non-invasive, cost-effective diagnostic approach.

The widespread availability of biomarkers of Alzheimer’s pathology (BAP) opens new diagnostic considerations for those who have not clinically expressed the disease but who are identified as being at increased risk based on their BAP. The International Working Group (IWG) updated their recommendations within a patient-centered nosographic approach that considers clinical evaluation as a cornerstone with attention to risk and resilience factors, patterns of biomarkers, comorbidities, genetics, and other test results (Dubois B, et al. JAMA Neurol 2024). They stratify risk and tie it to a specific clinical patient journey, including the communication of risk, tailored management of modifiable risk factors, counselling, multidomain lifestyle interventions, and treatment research considerations. For these updated IWG recommendations, an evidence review of available literature between July 1, 2020 and March 2024 was undertaken with a variety of biomarker search terms and AD. The search included a review of papers focused on near term and lifetime risks of progression to AD dementia in cognitively unimpaired people with different BAP patterns. These IWG recommendations provide a risk stratification framework for unimpaired individuals with classification into “Asymptomatic At-Risk” and “Presymptomatic”. The majority of cognitively unimpaired individuals with BAP, including those with an amyloid or AD pathophysiological biomarker, will not express clinical AD in their lifetime. The Presymptomatic group includes those with fully penetrant monogenic mutations, Down syndrome, or alternatively patterns of positive amyloid biomarker with neocortical tau PET biomarkers that reach the threshold of near certainty of clinical expression of AD. Prioritizing the testing of preventive disease modifying treatments is identified as urgent for this Presymptomatic group. Furthermore, it is expected that this group will expand as new evidence and patterns of biomarkers reach the necessary thresholds for their inclusion. Management plans can be further tailored to this classification framework. This IWG risk stratification classification recommends against diagnosis of AD based on BAP alone without its clinical expression. This AD classification lends itself to a tailored management approach and specific patient journeys for each of its groups.

Anti-amyloid antibodies for the treatment of Alzheimer´s disease (AD) are currently being evaluated for approval and reimbursement in Europe. An approval brings opportunities, but also challenges to health care systems across Europe. The objective of this position paper is to provide guidance from experts in the field in terms of navigating implementation. Members of the European Alzheimer's Disease Consortium and a representative of Alzheimer Europe convened to formulate recommendations covering key areas related to the possible implementation of anti-amyloid antibodies in AD through online discussions and 2 rounds of online voting with an 80

ImportanceDepressive symptoms are associated with cognitive decline in older individuals. Uncertainty about underlying mechanisms hampers diagnostic and therapeutic efforts. This large-scale study aimed to elucidate the association between depressive symptoms and amyloid pathology.ObjectiveTo examine the association between depressive symptoms and amyloid pathology and its dependency on age, sex, education, and APOE genotype in older individuals without dementia.Design, Setting, and ParticipantsCross-sectional analyses were performed using data from the Amyloid Biomarker Study data pooling initiative. Data from 49 research, population-based, and memory clinic studies were pooled and harmonized. The Amyloid Biomarker Study has been collecting data since 2012 and data collection is ongoing. At the time of analysis, 95 centers were included in the Amyloid Biomarker Study. The study included 9746 individuals with normal cognition (NC) and 3023 participants with mild cognitive impairment (MCI) aged between 34 and 100 years for whom data on amyloid biomarkers, presence of depressive symptoms, and age were available. Data were analyzed from December 2022 to February 2024.Main Outcomes and MeasuresAmyloid-β1-42 levels in cerebrospinal fluid or amyloid positron emission tomography scans were used to determine presence or absence of amyloid pathology. Presence of depressive symptoms was determined on the basis of validated depression rating scale scores, evidence of a current clinical diagnosis of depression, or self-reported depressive symptoms.ResultsIn individuals with NC (mean [SD] age, 68.6 [8.9] years; 5664 [58.2%] female; 3002 [34.0%] APOE ε4 carriers; 937 [9.6%] had depressive symptoms; 2648 [27.2%] had amyloid pathology), the presence of depressive symptoms was not associated with amyloid pathology (odds ratio [OR], 1.13; 95% CI, 0.90-1.40; P = .29). In individuals with MCI (mean [SD] age, 70.2 [8.7] years; 1481 [49.0%] female; 1046 [44.8%] APOE ε4 carriers; 824 [27.3%] had depressive symptoms; 1668 [55.8%] had amyloid pathology), the presence of depressive symptoms was associated with a lower likelihood of amyloid pathology (OR, 0.73; 95% CI 0.61-0.89; P = .001). When considering subgroup effects, in individuals with NC, the presence of depressive symptoms was associated with a higher frequency of amyloid pathology in APOE ε4 noncarriers (mean difference, 5.0%; 95% CI 1.0-9.0; P = .02) but not in APOE ε4 carriers. This was not the case in individuals with MCI.Conclusions and RelevanceDepressive symptoms were not consistently associated with a higher frequency of amyloid pathology in participants with NC and were associated with a lower likelihood of amyloid pathology in participants with MCI. These findings were not influenced by age, sex, or education level. Mechanisms other than amyloid accumulation may commonly underlie depressive symptoms in late life.

Prediction-powered inference (PPI) (Angelopoulos et al., Science 382(6671):669-674, 2023) and its subsequent development called PPI++ (Angelopoulos et al., 2023) provide a novel approach to standard statistical estimation, leveraging machine learning systems, to enhance unlabeled data with predictions. We use this paradigm in clinical trials. The predictions are provided by disease progression models, providing prognostic scores for all the participants as a function of baseline covariates. The proposed method would empower clinical trials by providing untreated digital twins of the treated patients while remaining statistically valid. The potential implications of this new estimator of the treatment effect in a two-arm randomized clinical trial (RCT) are manifold. First, it leads to an overall reduction of the sample size required to reach the same power as a standard RCT. Secondly, it advocates for an imbalance of controls and treated patients, requiring fewer controls to achieve the same power. Finally, this technique directly transfers any disease prediction model trained on large cohorts to practical and scientifically valid use. In this paper, we demonstrate the theoretical properties of this estimator and illustrate them through simulations. We show that it is asymptotically unbiased for the Average Treatment Effect and derive an explicit formula for its variance. We then compare this estimator to a regression-based linear covariate adjustment method. An application to an Alzheimer's disease clinical trial showcases the potential to reduce the sample size.

Biofluid and imaging biomarkers for Alzheimer’s disease can identify disease pathology in cognitively unimpaired people, a substantial proportion of whom will not clinically express the disease. The International Working Group offers a risk stratification framework for management directed at the prevention of the clinical expression of Alzheimer’s disease.