Alzheimer's Research & Therapy最新文献

Background: As understanding of biomarkers for genetic frontotemporal dementia (FTD) advances, there is a need to develop onset-predictive biomarker tests (OPBTs) to detect changes before the onset of symptoms. OPBTs can be used to recruit carriers or individuals at 50% risk of carriership into clinical trials of investigational therapies targeting the preclinical and prodromal phases of FTD. OPBT results should be disclosed as part of the informed consent process, with positive results indicating that symptom onset is likely in the next few years. This information can be psychologically burdensome, especially in individuals at 50% risk, for whom a positive OPBT result would reveal their genetic status. There is a need for ethical guidance for disclosure processes to help researchers implement disclosure of OPBT results responsibly at their study sites.

Methods: Existing literature on disclosure of genetic and biomarker results in neurodegenerative conditions informed the design of this disclosure process for OPBT in FTD. Drafts were discussed with the multidisciplinary research team, scientific and clinical FTD experts across European countries, and other stakeholders and revised accordingly.

Results: The suggested disclosure process provides guidance for first-time or repeated disclosure of OPBT results to carriers or individuals at 50% risk of genetic FTD in research settings.

Conclusions: Researchers involved in clinical trials using OPBTs can adopt this disclosure process as a framework for responsible communication of OPBT results at their study site. The process was designed for international applicability and facilitates the alignment of disclosure processes for clinical trial recruitment across European countries.

Background: Multidomain lifestyle interventions have shown effectiveness in preventing dementia, but identifying high-risk groups most likely to benefit remains unclear.

Methods: We re-evaluated the SUPERBRAIN-MEET multidomain intervention study in mild cognitive impairment (MCI) patients, incorporating polygenic risk scores (PRS) for Alzheimer's disease and APOE ε4 status using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) total index as the primary outcome.

Results: Both intervention and control groups showed cognitive improvement over 24 weeks, with greater gains in the intervention arm. Relative intervention efficacy (RIE) increased with higher genetic risk, being most pronounced among APOE ε4 carriers and individuals with high PRS. When both factors were considered jointly, APOE ε4 carriers with high PRS exhibited the largest RIE (β = 7.54, SE = 2.59, p = 0.005), driven by markedly greater improvement in the intervention group. The secondary outcomes did not show as consistent results as RBANS total index.

Discussion: These findings suggest that MCI individuals who are APOE ε4 carriers with high PRS may benefit most from multidomain interventions. These results support the complementary use of PRS and APOE status for identifying high-risk subgroups most likely to benefit from multidomain interventions.

Trial registration: ClinicalTrials.gov identifier: NCT05023057. Registered on 26 August 2021.

Background: Early identification of cognitive impairment and brain pathology associated with Alzheimer's disease (AD) is essential to maximize benefits from lifestyle interventions and emerging pharmacologic disease-modifying treatments (DMT). Digital cognitive assessments (DCAs) can quickly capture an array of metrics that can be used to train machine-learning (ML) models to concurrently evaluate different outcomes. DCAs have the potential to optimize clinical workflows and enable efficient assessment of cognitive function and the likelihood of a given underlying pathology.

Methods: We assessed the ability of a multimodal ML-enabled DCA, the Digital Clock and Recall (DCR), to concurrently estimate brain amyloid-beta (Aβ) status and detect cognitive impairment, as compared with traditional cognitive assessments, including the MMSE, RAVLT, a DCA, Cognivue^®, and blood-based biomarkers in 930 participants from the Bio-Hermes-001 clinical study.

Results: Aβ42/40, p-tau181, APS, and p-tau217 poorly classified cognitive impairment (AUCs: 0.61; 0.63; 0.63; 0.70, respectively), but accurately classified Aβ status (AUCs: 0.81; 0.78; 0.85, 0.89, respectively). MMSE, RAVLT, and Cognivue poorly classified Aβ status (AUCs: 0.70, 0.73, 0.70, respectively). However, separate multimodal, DCR-based ML classification models, run in parallel, accurately classified both cognitive impairment (AUC = 0.83) and Aβ-PET status (AUC = 0.81).

Conclusions: DCAs that leverage digital technologies to generate advanced metrics, such as the DCR, enable accurate and efficient detection of cognitive impairment associated with AD pathology. They have the potential to empower health systems and primary care providers to help their patients make timely treatment decisions.

Background: Although past screening cohorts have suggested a decline in the risk of dementia, it is important to monitor the population-level incidence and survival of diagnosed dementia, to inform care utilization and public health policies. This study provides nationwide analyses on time trends in the incidence of dementia diagnosis in Sweden between 2007 and 2022, as well as 5-year survival after a dementia diagnosis.

Methods: Data from the total Swedish population aged ≥ 61 years during the period 2007-2022 were used. Incident dementia diagnoses were identified from specialist care and dispensed anti-dementia drugs. The annual incidence rate of dementia diagnosis was calculated for the period 2007-2022. The proportion of individuals that survived 5 years after dementia diagnosis was compared across years of diagnosis. Health status at dementia diagnosis was assessed by calculating Charlson Comorbidity Index and Hospital Frailty Risk Score.

Results: Annual incidence rate of dementia diagnosis decreased from early 2010s and onwards, particularly among older age groups of 80-89 and ≥ 90 years. Mean age at dementia diagnosis remained constant, i.e., 82.2 years during 2007-2009 and 82.2 years during 2019-2022. The proportion of individuals with frailty at diagnosis increased from 74.3% in 2007-2009 to 80.6% in 2019-2022 (odds ratio (OR) = 1.42, 95% confidence interval (CI): 1.39-1.46); the proportion of individuals with comorbidities also increased over the same period. The proportion that survived 5 years since dementia diagnosis remained constant at 33% during 2007-2017 but improved over time when accounting for comorbidity and frailty level at diagnosis.

Conclusions: While the incidence of dementia diagnosis has declined from early 2010s and onwards, patients diagnosed today are on average frailer and more comorbid than those diagnosed 15 years ago, which partly explains the lack of improvement in dementia survival over time. Enhancing healthcare planning for people with dementia diagnosis and improving their survival is still highly relevant.

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.

Background: The development of effective disease-modifying therapies for Alzheimer's disease (AD) remains a critical unmet need. While Mendelian randomization (MR) has been leveraged to identify genetic variants to accelerate AD target discovery, previous studies have been limited by narrow phenotypic coverage, insufficient multiomics validation, and inadequate mechanistic exploration. This study aims to overcome these limitations via comprehensive MR to identify robust therapeutic targets.

Methods: We performed an integrative multiomics MR analysis leveraging over 50 genome-wide association study (GWAS) datasets spanning AD, cerebrospinal fluid (CSF) biomarkers (Aβ42, p-tau), neuroimaging endophenotypes, cognitive traits, and risk factors. Blood/CSF/brain protein quantitative trait loci (pQTLs) from large-scale proteomics studies were analyzed to identify druggable targets. A rigorous validation cascade was subsequently performed: Bayesian colocalization was performed to assess whether the same variants are associated with the protein and other traits; summary-data-based MR was performed to distinguish pleiotropy from linkage; mediation analysis was performed to quantify biomarker-driven causal pathways; integrated analysis of multiomics (single-cell RNA-seq and proteome) data was performed to resolve cellular specificity, and (PPI) interaction networks were generated; phenome-wide MR (Phe-MR) was performed across 679 traits to evaluate on-target side effects; and structure-based druggability screening was conducted.

Results: Proteome-wide MR analysis revealed 15 potential drug targets for AD; six of these targets (PILRA, GRN, ACE, TIMD3, TREM2) were validated as Tier 1 (highest-confidence targets with external validation and causal consistency). Mediation analysis revealed that IDUA reduced the risk of AD through Aβ42 and p-tau in the CSF, whereas Siglec-7/9 increased the risk of AD through p-tau in the CSF. Additional targets revealed associations with AD biomarkers, neuroimaging, and cognitive function. Single-cell analysis highlighted the enrichment of key microglial and astrocyte targets. PPI network analysis revealed interaction pathways between seven drug targets and four AD therapeutics, and druggability assessment revealed seven potential therapeutics.

Conclusions: This study established a comprehensive AD target atlas, revealing mechanism-anchored targets that were validated across multiomics analyses and a clinically actionable framework integrating efficacy, biology, and safety profiling. Overall, these results advance AD drug discovery by revealing prioritized targets with causal biological support and providing a validated development roadmap.

Introduction: Sleep and circadian rhythm disturbances have been related to cognitive decline and increased risk of Alzheimer's disease (AD). These disruptions are also closely associated with biological ageing processes. Telomere shortening, a key marker of cellular ageing, has been implicated in various age-related diseases, including AD. Although sleep disturbances have been linked to shorter telomere length (TL), the effects of sleep, its variability, and circadian rhythms on telomere dynamics (over 18 months) remain unknown. Furthermore, the interplay between these factors and AD risk has yet to be investigated in healthy older adults. Therefore, the objective of this study was to explore how sleep, sleep variability, and circadian rhythms affect telomere dynamics in healthy older adults and the influence of AD risk on these relationships.

Methods: Data from 124 healthy older adults (mean age ± SD: 69.27 ± 3.73y) from the Age-Well interventional trial (NCT02977819) were analyzed. Blood samples were collected to determine three TL metrics (50th and 20th percentile TL, and percentage of critically short telomeres (%CST) at baseline and after 18-month follow-up). Sleep and its variability were assessed using the Somno-Art^® device over 5 nights (n = 77), and circadian rhythms using actigraphy for 1 week (n = 123). Multiple linear regressions examined whether baseline sleep and circadian rhythm measures predicted TL changes over time. Interaction analyses assessed the modulatory effects of amyloid (Aβ) status, assessed using Forbetapir-PET imaging, and APOE4 status on these relationships. Age, sex, education, BMI, and intervention group were included as covariates.

Results: Poor sleep quality (characterized by lower sleep efficiency and higher wake after sleep onset) and greater variability in sleep efficiency predicted an increase in %CST. Greater regularity in sleep/wake patterns was associated with a decrease in 50th and 20th percentile TL and an increase in %CST. In Aβ-positive individuals, longer latency of rapid eye movement sleep predicted a reduction in 20th percentile TL and an increase in %CST.

Conclusions: This study suggests that poor sleep quality, sleep variability and circadian rhythm disturbances may accelerate cellular ageing through telomere shortening in older adults. Our results highlight the potential value of sleep interventions in mitigating biological ageing and reducing vulnerability to age-related diseases.