Importance

Dementia affects 10% of those 65 years or older and 35% of those 90 years or older, often with profound cognitive, behavioral, and functional consequences. As the baby boomers and subsequent generations age, effective preventive and treatment strategies will assume increasing importance.

Observations

Preventive measures are aimed at modifiable risk factors, many of which have been identified. To date, no randomized clinical trial data conclusively confirm that interventions of any kind can prevent dementia. Nevertheless, addressing risk factors may have other health benefits and should be considered. Alzheimer disease can be treated with cholinesterase inhibitors, memantine, and antiamyloid immunomodulators, with the last modestly slowing cognitive and functional decline in people with mild cognitive impairment or mild dementia due to Alzheimer disease. Cholinesterase inhibitors and memantine may benefit persons with other types of dementia, including dementia with Lewy bodies, Parkinson disease dementia, vascular dementia, and dementia due to traumatic brain injury. Behavioral and psychological symptoms of dementia are best treated with nonpharmacologic management, including identifying and mitigating the underlying causes and individually tailored behavioral approaches. Psychotropic medications have minimal evidence of efficacy for treating these symptoms and are associated with increased mortality and clinically meaningful risks of falls and cognitive decline. Several emerging prevention and treatment strategies hold promise to improve dementia care in the future.

Conclusions and relevance

Although current prevention and treatment approaches to dementia have been less than optimally successful, substantial investments in dementia research will undoubtedly provide new answers to reducing the burden of dementia worldwide.

Introduction

Alzheimer's disease (AD) incidence is disproportionately high in African Americans, yet, recruitment of this community to AD clinical trials is challenging.

Methods

We compared 47 African Americans and 78 whites in their willingness to enroll in a hypothetical preclinical AD trial and examined barriers and facilitators in their decision making.

Results

African American race (OR = 0.45; 95% CI, 0.22-0.93) and score on the research attitude questionnaire (OR = 1.12; 95% CI, 1.04-1.22) were independently associated with willingness to participate. African Americans rated study risks, the requirement of a study partner, study procedures, the ratio of drug to placebo, and study location as more important factors in the decision whether to enroll than did whites.

Discussion

These results suggest that researchers will encounter challenges in recruiting African Americans to preclinical AD trials. Future research will be necessary to understand the optimal means to improve recruitment of underrepresented populations.

Introduction

Amyloid imaging is a tool that has recently become available to dementia specialists evaluating patients with possible Alzheimer's disease. Studies have assessed the impact of amyloid imaging on diagnostic and treatment decisions, but patient and family perspectives have received less attention.

Methods

To examine how amyloid imaging affects the diagnostic experience of patients and families, we interviewed members of 26 patient-caregiver dyads with whom a neurologist discussed the option of amyloid positron emission tomography.

Results

Most participants who chose to undergo amyloid imaging would choose to do so again. Regardless of the scan outcome, patients and caregivers commonly expressed relief on learning the scan results. Some participants expressed expectations that were beyond scan capabilities.

Discussion

Amyloid imaging may provide information that patients and their families find useful. Clinicians must set correct expectations and ensure that families understand the limitations of amyloid imaging.

Introduction

The utility of the Appropriate Use Criteria (AUC) for amyloid imaging is not established.

Methods

Fifty-three cognitively impaired patients with clinical F¹⁸-florbetapir imaging were classified as early and late onset, as well as AUC-consistent or AUC-inconsistent. Chi-square statistics and t test were used to compare demographic characteristics and clinical outcomes as appropriate.

Results

Early-onset patients were more likely to be amyloid positive. Change in diagnosis was more frequent in late-onset cases. Change in therapy was more common in early-onset cases. AUC-consistent and AUC-inconsistent cases had comparable rates of amyloid positivity. We saw no difference in the rate of treatment changes in the AUC-consistent group as opposed to the AUC-inconsistent group.

Discussion

The primary role of amyloid imaging in the early-onset group was to confirm the clinically suspected etiology, and in the late-onset group in detecting amyloid-negative cases. The rate of therapeutic changes was significantly greater in the early-onset cases.

Background

Mild cognitive impairment (MCI) has an uncertain etiology and prognosis and may be challenging for clinicians to discuss with patients and families. Amyloid imaging may aid specialists in determining MCI etiology and prognosis, but creates novel challenges related to disease labeling.

Methods

We convened a workgroup to formulate recommendations for clinicians providing care to MCI patients.

Results

Clinicians should use the MCI diagnosis to validate patient and family concerns and educate them that the patient's cognitive impairment is not normal for his or her age and education level. The MCI diagnosis should not be used to avoid delivering a diagnosis of dementia. For patients who meet Appropriate Use Criteria after standard-of-care clinical workup, amyloid imaging may position specialists to offer more information about etiology and prognosis. Clinicians must set appropriate expectations, including ensuring that patients and families understand the limitations of amyloid imaging. Communication of negative results should include that patients remain at elevated risk for dementia and that negative scans do not indicate a specific diagnosis or signify brain health. Positive amyloid imaging results should elicit further monitoring and conversations about appropriate advance planning. Clinicians should offer written summaries, including referral to appropriate social services.

Conclusions

In patients with MCI, there is a need to devote considerable time and attention to patient education and shared decision-making. Amyloid imaging may be a tool to aid clinicians. Careful management of patient expectations and communication of scan results will be critical to the appropriate use of amyloid imaging information.

Clinical trials for Alzheimers disease (AD) are slower to enroll study participants, take longer to complete, and are more expensive than trials in most other therapeutic areas. The recruitment and retention of a large number of qualified, diverse volunteers to participate in clinical research studies remain among the key barriers to the successful completion of AD clinical trials. An advisory panel of experts from academia, patient-advocacy organizations, philanthropy, non-profit, government, and industry convened in 2020 to assess the critical challenges facing recruitment in Alzheimers clinical trials and develop a set of recommendations to overcome them. This paper briefly reviews existing challenges in AD clinical research and discusses the feasibility and implications of the panels recommendations for actionable and inclusive solutions to accelerate the development of novel therapies for AD.

Alzheimer's disease (AD) is a leading cause of mortality among the elderly. We performed a whole-genome sequencing study of AD in the Chinese population. In addition to the variants identified in or around the APOE locus (sentinel variant rs73052335, P = 1.44 × 10^-14), two common variants, GCH1 (rs72713460, P = 4.36 × 10^-5) and KCNJ15 (rs928771, P = 3.60 × 10^-6), were identified and further verified for their possible risk effects for AD in three small non-Asian AD cohorts. Genotype-phenotype analysis showed that KCNJ15 variant rs928771 affects the onset age of AD, with earlier disease onset in minor allele carriers. In addition, altered expression level of the KCNJ15 transcript can be observed in the blood of AD subjects. Moreover, the risk variants of GCH1 and KCNJ15 are associated with changes in their transcript levels in specific tissues, as well as changes of plasma biomarkers levels in AD subjects. Importantly, network analysis of hippocampus and blood transcriptome datasets suggests that the risk variants in the APOE, GCH1, and KCNJ15 loci might exert their functions through their regulatory effects on immune-related pathways. Taking these data together, we identified common variants of GCH1 and KCNJ15 in the Chinese population that contribute to AD risk. These variants may exert their functional effects through the immune system.

Background

Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.

Methods

The c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification.

Findings

The application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6).

Interpretation

Our results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.

Funding

The specific funding of this article is provided in the acknowledgements section.

Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.