The Journal of Prevention of Alzheimer's Disease最新文献

Background: A new era of Alzheimer's disease (AD) research is beginning with multiple approved anti-amyloid monoclonal antibodies (mABs). These drugs are currently not widely used, but may be soon, especially at clinical trial sites. Putative disease-modifying therapies (DMTs) may alter the progression rate, potentially reducing our ability to detect effects on top of mABs. Co-administration of amyloid-targeted agents may diminish benefit (antagonism, due to the overlapping mechanism of action); alternatively, complementary treatment mechanisms may increase benefit (synergy).

Method: We consider several clinical trial design scenarios: a 2-arm trial added-on to a mAB, a 2-arm combination compared to double placebo, and a 4-arm full factorial trial. We calculate the required sample sizes for the shortest practical study for secondary prevention (prevention of AD clinical diagnosis in biomarker positive individuals, 2-year study), early AD (18-months), and mild-to-moderate AD (1-year). We consider additivity, antagonism, and synergy.

Result: The expected interaction between investigational and mAB treatment can have a large effect on power and study design. Antagonistic treatment effects often require double the sample size of synergistic effects. The 4-arm scenario required ∼10-fold increase compared to a 2-arm combination study.

Conclusion: Studies evaluating investigational therapies as add-on to mABs are complex, and their cost will depend on the interaction between treatments. An inescapable fact in add-on trials is the slower progression of the control arm; and it is difficult to further slow already slow progression. Treatments that are likely to work better with amyloid removal will be easier to study due to their complementary MOA. Symptomatic treatments may require fewer additional subjects than disease-modifying treatments since they are less affected by the presence or absence of mABs.

Importance: Despite the emergence of anti-amyloid therapies for Alzheimer's disease, targeting modifiable risk factors remains the most effective primary prevention strategy for dementia. While cognitive benefits of multimodal lifestyle interventions have been demonstrated, the underlying effects on brain structure remain unclear, likely due to heterogeneity in brain structure among at-risk individuals.

Objective: To investigate how distinct subgroups of at-risk individuals, defined by cortical and subcortical grey matter (GM) patterns, differ in their response to the FINGER intervention, as well as in their demographic, vascular, and lifestyle profiles.

Design: Observational study employing unsupervised clustering of MRI-based cortical thickness and subcortical volume metrics, followed by longitudinal assessment of a lifestyle intervention.

Setting: The FINGER randomized controlled trial (RCT), a population-based, multidomain lifestyle intervention targeting older adults (aged 60-77) with elevated cardiovascular risk (CAIDE score ≥ 6) and average to slightly below-average cognitive performance.

Participants: A total of 120 participants (61 intervention, 59 control) with available baseline MRI data.

Intervention: Participants were randomly assigned (1:1, double-blind) to a 2-year multidomain lifestyle intervention group - targeting diet, physical activity, cognitive training, social engagement, and metabolic and vascular risk management - or to a control group receiving standard health advice.

Main outcomes and measures: Sociodemographic, vascular, and lifestyle factors, medical comorbidities, and cognitive performance, were assessed at baseline (pre-intervention). Additionally, brain structural outcomes (mean cortical thickness, Alzheimer's disease and resilience-related cortical signatures, hippocampal volume), and cognition (global, executive function, processing speed, memory) were analysed post-intervention using hierarchical linear models stratified by GM cluster.

Results: Clusters with diffuse or frontal-predominant cortical thinning, but with more favourable vascular profiles, characterized by lower blood pressure and reduced obesity, showed significantly less cortical thinning (mean thickness, AD-signature, and resilience-signature regions; all p < 0.05) following the intervention.

Conclusions and relevance: Stratifying at-risk individuals by GM patterns and vascular risk revealed differential brain responses to the FINGER intervention. These findings underscore the value of brain-based subtyping to optimize personalized dementia prevention strategies in heterogeneous at-risk populations.

Trial registration: ClinicalTrials.gov Identifier: NCT01041989.

Background: This study aimed to evaluate cortical mean diffusivity (cMD) as a sensitive biomarker for early neurodegenerative changes in familial frontotemporal lobar degeneration (FTLD) associated with C9orf72, GRN, and MAPT mutations. We compared cMD with cortical thickness (cTH) in detecting subtle microstructural alterations and examined its association with clinical severity and neurofilament light chain (NFL) concentrations.

Methods: We analyzed data from 322 participants, including symptomatic carriers of C9orf72 (n = 85), GRN (n = 56), and MAPT (n = 58) mutations, along with 123 healthy controls. Cortical microstructure was assessed using both cTH and cMD. Clinical severity was evaluated with the CDR plus NACC FTLD scale, and plasma NFL was measured as a marker of neuroaxonal injury.

Results: C9orf72 carriers exhibited the most widespread cortical thinning and increased cMD, while GRN and MAPT carriers showed more regionally restricted alterations. Across all mutation groups, cMD demonstrated higher sensitivity than cTH in detecting early changes. Furthermore, cMD values were significantly correlated with CDR plus NACC FTLD scores and NFL concentrations, underscoring its relevance to disease progression.

Conclusion: Cortical mean diffusivity outperforms cortical thickness in detecting early microstructural changes in familial FTLD. Its strong association with both clinical severity and neurodegeneration biomarkers highlights its potential utility for early diagnosis, disease monitoring, and individualized therapeutic strategies in FTLD.

Background: The cognitive consequences of cerebral microbleeds (CMBs) in memory clinic population with a diverse cognitive spectrum remain unclear.

Objectives: This study aimed to investigate how CMBs at different locations are associated with cognitive performance in a memory clinic population and whether these associations are independent of related small vessel disease (SVD) markers.

Design: A cross-sectional study.

Setting: A university hospital memory clinic. Data were collected from December 2004 to September 2014 and analyzed in June 2024.

Participants: A total of 910 participants, composed of 64 individuals with subjective cognitive decline, 399 with mild cognitive impairment (MCI), 339 with Alzheimer disease dementia (AD), 58 with vascular dementia and mixed dementia, and 50 with other types of dementia, were included.

Main outcomes and measures: Summary scores for global cognition, memory, language, visuospatial function, and executive function measured by the Consortium to Establish a Registry for Alzheimer's disease (CERAD) neuropsychological battery.

Results: In the overall population, the presence of deep/infratentorial CMBs was significantly associated with executive dysfunction; however, this association was attenuated after adjusting for related SVD markers. When stratified by diagnostic subgroup, strictly lobar CMBs were significantly associated with impairments in global cognition and memory in the MCI group, independent of related SVD markers. In contrast, no significant associations between CMBs and cognitive domains were observed in the AD group.

Conclusions: These findings, based on memory clinic population with a broad cognitive spectrum, suggest that CMBs, depending on their location, may have different implications for cognitive function.

Alzheimer's disease remains one of the most complex and contested domains in biomedicine, characterized by fragmented findings, competing hypotheses, and limited translational success. We propose that AI can offer not just technical acceleration but a deeper epistemic contribution: reconciliation. Rather than optimizing predictive performance or replicating existing assumptions, the goal is to align disparate data, methods, and mechanistic insights into coherent models that explain how the disease emerges, progresses, and can be treated. This approach centers on digital twins, not as monolithic models, but as flexible, testable architectures grounded in homeostasis, destabilization, and multiscale coherence. Through an iterative, interoperable AI architecture, digital twins integrate evidence, resolve contradictions, and highlight where critical gaps remain. This framework moves beyond incremental progress within the prevailing model to catalyzing a paradigm shift in how Alzheimer's is understood. Reconciliation, in this sense, is not a method but a guiding principle for transforming both the science and its applications.

Breakthroughs in biomarkers for amyloid (A), tau (T), and neurodegeneration (N) have advanced the prospects of accurate Alzheimer's disease (AD) diagnosis. However, presence of pathology does not always translate into clinical expression and there are still clear knowledge gaps as to whether someone with AD biological indicators will lead to clinically apparent disease necessary to warrant drug treatments that carry toxicity risk. Reliance on decades-old assessment tools inhibits detection and monitoring at preclinical and early disease stages when new treatments could prove most effective. Evidence has accumulated that digital measures provide accurate detection of disease at early stages. We call for a re-evaluation of the A/T/N diagnostic framework, with digital evaluation measures complementing non-AD specific neurodegeneration markers, and even potentially replacing those non-specific to AD, to provide a clinically relevant feature critical to clinical trial advances and treatment decisions. Achieving this will only be possible if further research into novel digital evaluation tools is pursued with the same support and consideration as amyloid and tau.

There is considerable opportunity to fast-track novel treatments for Alzheimer's Disease (AD) through repurposing of existing licensed medications as a way of complementing ongoing drug discovery efforts. Given the complex interplay between AD neuropathological mechanisms, there is also a strong rationale that treatment benefits may be enhanced by examining combinations of treatments to identify potential synergies that would address multiple disease-modifying mechanisms. A Delphi consensus programme combined with a pragmatic analysis of primary care data has identified a series of individual and combined therapies that warrant further investigation in pre-clinical and clinical trials. These include treatments which target well-established neurodegeneration pathways and more explorative agents, including hormonal and anti-infective agents, which align to emerging hypotheses relating to endocrine and immune pathways in AD. Whilst caution is critical when considering combined therapy due to the risks of interaction and polypharmacy, this study provides valuable indications of potential synergistic drug pairs that warrant further investigation.

Background: Cholinergic basal forebrain (cBF) atrophy is a critical early marker of neurodegeneration in Alzheimer's disease (AD). While cBF degeneration is linked to cognitive decline, the role of cortical thinning in this process, especially during the preclinical phase of AD, remains underexplored. Additionally, the impact of amyloid-β (Aβ) pathology on these relationships warrants further examination.

Methods: We analyzed longitudinal structural MRI and PIB-PET data from 230 cognitively normal older adults enrolled in the Harvard Aging Brain Study, with a mean follow-up of six years. cBF volume and cortical thickness were quantified using FreeSurfer. Cognitive performance was assessed with the Preclinical Alzheimer Cognitive Composite-5 (PACC5). Linear mixed-effects models were used to investigate the longitudinal associations between cBF atrophy, cortical thinning, and cognitive decline. Mediation analyses explored whether cortical thinning mediated the relationship between cBF degeneration and cognitive decline, and the moderating role of Aβ burden was examined.

Results: Progressive cortical thinning in multiple cognition-related regions was significantly associated with cBF atrophy. Mediation analysis revealed that cortical thinning accounted for approximately 44 % of the relationship between cBF degeneration and cognitive decline. These associations were more pronounced in individuals with elevated Aβ, suggesting a synergistic interaction between amyloid pathology and cholinergic system degeneration.

Conclusions: Our findings suggest that cBF atrophy accelerates cognitive decline through its impact on cortical thinning, with Aβ pathology further exacerbating these effects. These results highlight the potential of cBF and cortical thinning as early biomarkers for preclinical AD and underscore the importance of targeting cholinergic dysfunction in early intervention strategies.