Journal of Alzheimer's disease reports最新文献

Background: White matter hyperintensities (WMHs) are common in older adults and appear as abnormal signal on T2-weighted or fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI). They are often linked to demyelination, axonal damage, and gliosis, as well as vascular changes. WMHs occur in both normal aging and mild cognitive impairment (MCI), where they may contribute to cognitive decline.

Objective: The study objectives were to determine whether advanced diffusion MRI (dMRI) techniques can detect distinct microstructural changes within WMHs in individuals with MCI compared to healthy controls and to evaluate relationships between these measures and cognitive performance.

Methods: Advanced dMRI techniques were used to assess WMH microstructural changes in normal aging (n = 55) and MCI (n = 46) participants from the ADNI database. WMHs and their surrounding penumbra were identified using an automated approach. Microstructural characteristics, derived from free-water (FW) diffusion tensor imaging and diffusion kurtosis imaging, were evaluated between groups and white matter regions. Associations between these measures and cognitive performance (assessed by the Mini-Mental State Exam) were examined.

Results: Across both groups, WMHs showed higher FW and lower FW-fractional anisotropy and kurtosis metrics compared to normal-appearing white matter, indicating widespread microstructural alterations. No groupwise microstructural differences were observed within corresponding tissue types. In the MCI group, kurtosis metrics within WMHs correlated with cognitive performance.

Conclusions: These findings highlight the complexity of WMH-related microstructural changes and suggest that advanced dMRI biomarkers may offer valuable insights into the role of white matter changes in aging and cognitive decline.

Background: This study examines the prevalence and incidence of dementia in Ecuador, with a focus on understanding demographic and social factors associated with increased risk. Data were obtained from the Institute of Neurosciences of Guayaquil, covering patient records from 2010 to 2022.

Objective: The purpose was to identify prevalence trends and key risk factors to inform targeted prevention and early intervention efforts in high-risk groups.

Methods: This observational, correlational study analyzed patient data to estimate dementia prevalence and incidence. Statistical analyses included descriptive statistics to calculate overall and age-specific prevalence rates, while incidence was calculated per 1000 person-years. Correlations and chi-square analyses were used to evaluate associations between dementia and potential risk factors, including age, gender, education level, and marital status.

Results: The overall prevalence of dementia was 3.1%, with higher rates among women (1.8%) compared to men (1.3%). Dementia incidence was calculated at 2.4 per 1000 person-years. Prevalence increased significantly with age, from 1.2% in individuals aged 65-69 to 54.8% in those aged 95 and older. Advanced age, female gender, lower education levels, and lack of a marital partner were associated with higher dementia prevalence.

Conclusions: These findings highlight a rising dementia prevalence in Ecuador, particularly among women and older individuals, with social and educational factors contributing to increased risk. The results underscore the need for tailored dementia prevention and early intervention strategies, especially as prevalence rates continue to rise across Latin America.

Background: Alzheimer's disease and other dementias disproportionally impacts women. Novel treatment makes understanding of early-onset cases unprecedentedly important.

Objective: We aimed to examine Alzheimer's disease and other dementias incidence, DALYs, trends, and risk factors among women aged under 65 years from 1990 to 2021.

Methods: Using Global Burden of Diseases Study, we estimated the trend of Alzheimer's diseases and other dementias age-standardized incidence and disability-adjusted life-years (DALYs) among women aged under 65 years by social development index (SDI) worldwide during 1990 to 2021.

Results: Globally, in 2021 there were 4.3 million prevalent cases among middle-aged women, with the incident cases doubled from 0.4 million to 0.8 million during 1990-2021. The largest increases in incidence and DALYs were found in high-middle SDI countries (0.27%/year) and low-middle SDI countries (0.19%/year), respectively. The incidence rate doubled once with every five years of age increase. The two contributors, which were high body mass index and high fasting plasma glucose, rapidly grew from 1990 to 2021.

Conclusions: The substantial increase of early-onset Alzheimer's disease and other dementias among middle-aged women requires attention, especially targeted at the increasing reversible lifestyle risk factors.

Alzheimer's disease is a chronic progressive neurodegenerative disorder that impairs the meningeal lymphatics, glymphatic system, and compartmental fluid exchange, leading to a decline in cognitive function. Due to the lack of non-pharmacological and physiological treatments, cranial osteopathic manipulation (COM) poses a potential minimally invasive therapeutic choice. To understand the treatment and related effects objectively, we have established a technique to quantify the force applied during COM on an animal model of AD for the first time. Our results indicate that quantified COM can be applied to rodents to study behavioral and biochemical phenotype changes.

Ad-model rationale: The contributing factors of Alzheimer's disease are cerebral vessel disease, insulin resistance, hypometabolism, oxidative stress, abnormal-protein aggregation, and inflammation. Brain insulin resistance is influenced by inflammation, glycemia, and stress, and glucose uptake into the central nervous system is mediated by brain glucose transporter. Glucose hypometabolism leads to oxidative stress. During protein synthesis, DNA is vulnerable to being insulted by reactive oxygen species. If repair fails, the neuron undergoes apoptosis. If the repair is imperfect, it may synthesize an abnormal protein, which could induce an immune response. The resulting inflammation may initiate brain insulin resistance, leading to glucose hypometabolism. Integrating all these major factors forms an AD model. One factor impacts more other factors. This process becomes a vicious cycle, creating a positive feedback loop.

Ad-model application: The AD model should be able to explain the observable AD incidents. The amyloid-β (Aβ) is extracellular, which would induce an immune response. On the contrary, tau and α-synuclein are intracellular proteins, which only cause an immune response if they leak out of the neuron. This is the reason why 2/3 of dementia cases are AD. Besides living longer, women have more immune sensitivity compared to men, and postmenopausal women have higher insulin resistance and endothelial dysfunction due to a decline in estrogen production. This is the reason why women have twice the AD in comparison to men. Removing abnormal proteins or applying an anti-inflammatory agent could reduce inflammation; therefore, one-third of people remain cognitively normal despite the presence of Aβ buildup in the brain.

Lecanemab, an anti-amyloid-β (Aβ) monoclonal antibody, has shown potential in slowing Alzheimer's disease (AD) progression. We report divergent responses in two AD patients with similar backgrounds following lecanemab treatment. Subject 1 showed worsened daily functioning, increased Aβ/tau deposition, and elevated electroencephalogram (EEG) slow/fast wave ratios (>30%) in right fronto-occipital regions (Fp2/F8/O1). Subject 2 improved cognitively, with modest Aβ reduction, marked tau suppression, and mixed EEG frontal declines (F3/F7/O1/Pz) and parietal/occipital gains (P3/P4/T3/T6). EEG alterations corresponded with positron emission tomography findings, suggesting its potential for therapeutic monitoring. Multimodal analysis revealed region-specific lecanemab effects, supporting EEG's role in evaluating treatment efficacy.

The approval of disease-modifying treatments for Alzheimer's disease demands a rethinking of cognitive screening. Drawing on over 180 stakeholder interviews from the NSF National I-Corps program, this perspective highlights barriers in current workflows, from time constraints in primary care to learning effects in long-term care, and presents innovation pathways centered on AI and digital biomarkers. Speech analysis, in particular, offers a scalable and cost-effective screening tool aligned with existing CPT codes. We outline implementation strategies and emphasize the urgent opportunity to align technological innovation with frontline clinical needs to ensure advances translate into meaningful patient and provider benefit.

Background: The prevalence of Alzheimer's disease or dementia is rising among the elderly population in the United States and globally. Sociodemographic, cancer, and neurological disorders are associated with cognitive impairment of people living in rural communities.

Objective: This study identified the association of cognitive impairment with cancer and neurological disorders of the elderly in Cochran and Parmer Counties of rural West Texas.

Methods: Pearson's chi-squared, two-sample independent proportions, binary logistic regression, and multivariable logistic regression methods were utilized to analyze data.

Results: Individuals aged 70 and above experiencing memory loss in Cochran and Parmer Counties had a statistically significant association with cognitive impairment (p < 0.001). In Parmer County, females diagnosed with breast cancer demonstrated a significant relationship with cognitive impairment (p < 0.05). Neurological factors, including muscle strength, cerebellar function, ability to rise from a chair, and Romberg test results, were significantly associated with an increased risk of cognitive impairments among females in both counties. After adjusting for covariates, males aged 60-69 in Parmer County, as well as memory loss among both genders, were significantly associated with cognitive impairment (p < 0.001). Additionally, females with cognitive impairment in Cochran County exhibited higher dependence on mental health services compared to males (p < 0.05).

Conclusions: Examining the association between cognitive impairment or Alzheimer's disease and cancer and neurological disorders is important for developing interventions aimed at reducing their prevalence in underserved rural West Texas Counties.

Background: Alzheimer's disease and related dementias (ADRD) have become a significant public health concern, and the burden is disproportionately concentrated in rural areas.

Objective: To examine rural-urban differences in the prevalence of modifiable dementia risk factors and their treatment among U.S. adults aged 45 years and older, and to investigate how these disparities vary by age group and geographic region.

Methods: This cross-sectional study analyzed nationally representative data from the 2023 National Health Interview Survey in 2025. Prevalence of 11 modifiable dementia risk factors (hypertension, high cholesterol, diabetes, obesity, hearing loss, visual impairment, traumatic brain injury, low education, depression, social isolation, smoking) and 7 corresponding treatments were assessed via self-report. Adjusted rate ratios (aRR) were estimated using robust Poisson regression models.

Results: The study population consisted of 16,981 individuals (mean age: 62.4, 51.6% female, 68.7% non-Hispanic White, 15.5% in rural areas). Rural residents had significantly higher prevalence of hypertension (aRR, 1.11; 95% CI, 1.06-1.17), obesity (aRR, 1.22; 95% CI, 1.15-1.30), diabetes (aRR, 1.29; 95% CI, 1.15-1.45), and hearing loss (aRR, 1.22; 95% CI, 1.12-1.34) compared to urban residents. Disparities were most significant among adults aged 45-64 years and in South/Midwest regions. Treatment rates for cardiometabolic conditions were high (>85%) and similar across regions, but treatment for sensory/behavioral risk factors remained low.

Conclusions: Rural U.S. adults face higher burden of modifiable dementia risk factors, particularly cardiometabolic and sensory impairments. Targeted public health strategies are needed to address structural inequities and improve dementia prevention in rural communities.

Background: Non-invasive biomarkers are key to early Alzheimer's disease (AD) detection. Multiparametric MRI and advanced imaging offer promising, accessible tools for identifying AD-related changes, supporting timely diagnosis and intervention.

Objective: To assess how accurately multiparametric MRI biomarkers identify AD using Aβ-PET imaging as the reference, and to evaluate whether MRI metrics in AD-related brain regions can distinguish between Aβ-positive and Aβ-negative subjects across the AD continuum.

Methods: In this exploratory retrospective study, 44 subjects aged 50-80 years were classified based on their PET and MRI biomarkers following the NIA-AA 2024 framework. MRI metrics included selected regional brain volumes (T1-weighted), mean diffusivity and fractional anisotropy (DTI-MD, DTI-FA), quantitative susceptibility mapping (QSM), and T1rho imaging. These were compared with amyloid load, and diagnostic performance was assessed using area-under-the-curve (AUC) analysis.

Results: 25 subjects were Aβ+ (AD continuum), while 19 were Aβ- (controls). Volumes of the hippocampus, thalamus, amygdala, cingulate, putamen, and corpus callosum and DTI-MD in the hippocampus, corpus callosum, cuneus, and cingulate showed optimal diagnostic performance (AUC ≥ 0.80), with hippocampal volume and hippocampal DTI-MD showing AUCs > 0.90, (both p < 0.05). Combining hippocampal volumetry and hippocampal DTI-MD (AUC = 0.95, p < 0.001) improved diagnostic accuracy by 2.1% compared to using either biomarker alone. LASSO logistic regression analysis showed that amyloid positivity was significantly associated with hippocampal volume (p < 0.001).

Conclusions: Hippocampal volumetry and hippocampal DTI-MD may be superior and more sensitive imaging biomarkers for AD. Their combined use could improve diagnostic accuracy and enhance early AD detection.