Journal of Alzheimer's disease reports最新文献

Background: Alzheimer's disease (AD), one of the most prevalent causes of dementia, is mainly sporadic in occurrence but driven by aging and other cofactors. Studies suggest that excessive alcohol consumption may increase AD risk.

Objective: Our study examined the degree to which short-term moderate ethanol exposure leads to molecular pathological changes of AD-type neurodegeneration.

Methods: Long Evans male and female rats were fed for 2 weeks with isocaloric liquid diets containing 24% or 0% caloric ethanol (n = 8/group). The frontal lobes were used to measure immunoreactivity to AD biomarkers, insulin-related endocrine metabolic molecules, and proinflammatory cytokines/chemokines by duplex or multiplex enzyme-linked immunosorbent assays (ELISAs).

Results: Ethanol significantly increased frontal lobe levels of phospho-tau, but reduced Aβ, ghrelin, glucagon, leptin, PAI, IL-2, and IFN-γ.

Conclusions: Short-term effects of chronic ethanol feeding produced neuroendocrine molecular pathologic changes reflective of metabolic dysregulation, together with abnormalities that likely contribute to impairments in neuroplasticity. The findings suggest that chronic alcohol consumption rapidly establishes a platform for impairments in energy metabolism that occur in both the early stages of AD and alcohol-related brain degeneration.

Background: Alzheimer's disease (AD) currently lacks effective disease-modifying treatments. Recent research suggests that ferroptosis could be a potential therapeutic target. Mendelian randomization (MR) is a widely used method for identifying novel therapeutic targets.

Objective: Employ genetic information to evaluate the causal impact of ferroptosis-related genes on the risk of AD.

Methods: 564 ferroptosis-related genes were obtained from FerrDb. We derived genetic instrumental variables for these genes using four brain quantitative trait loci (QTL) and two blood QTL datasets. Summary-data-based Mendelian randomization (SMR) and two-sample MR methods were applied to estimate the causal effects of ferroptosis-related genes on AD. Using extern transcriptomic datasets and triple-transgenic mouse model of AD (3xTg-AD) to further validate the gene targets identified by the MR analysis.

Results: We identified 17 potential AD risk gene targets from GTEx, 13 from PsychENCODE, and 22 from BrainMeta (SMR p < 0.05 and HEIDI test p > 0.05). Six overlapping ferroptosis-related genes associated with AD were identified, which could serve as potential therapeutic targets (PEX10, CDC25A, EGFR, DLD, LIG3, and TRIB3). Additionally, we further pinpointed risk genes or proteins at the blood tissue and pQTL levels. Notably, EGFR demonstrated significant dysregulation in the extern transcriptomic datasets and 3xTg-AD models.

Conclusions: This study provides genetic evidence supporting the potential therapeutic benefits of targeting the six druggable genes for AD treatment, especially for EGFR (validated by transcriptome and 3xTg-AD), which could be useful for prioritizing AD drug development in the field of ferroptosis.

Background: ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) is valuable in Alzheimer's disease (AD) workup.

Objective: To explore the effectiveness of ¹⁸F-FDG PET in differentiating and staging AD and associations between brain glucose metabolism and cognitive functions and vascular risk factors.

Methods: 107 participates including 19 mild cognitive impairment (MCI), 38 mild AD, 24 moderate AD, 15 moderate-severe AD, and 11 frontotemporal dementia (FTD) were enrolled. Visual and voxel-based analysis procedures were utilized. Cognitive conditions, including 6 cognitive function scores and 7 single-domain cognitive performances, and vascular risk factors linked to hypertension, hyperlipidemia, diabetes, and obesity were correlated with glucose metabolism in AD dementia using age as a covariate.

Results: ¹⁸F-FDG PET effectively differentiated AD from FTD and also differentiated MCI from AD subtypes with significantly different hypometabolism (except for mild AD) (height threshold p < 0.001, all puncorr < 0.05, the same below). The cognitive function scores, notably Mini-Mental State Examination and Montreal Cognitive Assessment, correlated significantly with regional glucose metabolism in AD participants (all p < 0.05), whereas the single-domain cognitive performance and vascular risk factors were significantly associated with regional glucose metabolism in MCI patients (all p < 0.05).

Conclusions: This study underlines the vital role of ¹⁸F-FDG PET in identifying and staging AD. Brain glucose metabolism is associated with cognitive status in AD dementia and vascular risk factors in MCI, indicating that ¹⁸F-FDG PET might be promising for predicting cognitive decline and serve as a visual framework for investigating underlying mechanism of vascular risk factors influencing the conversion from MCI to AD.

Background: Decline in renal function impairs systemic clearance of amyloid-β which characterizes Alzheimer's disease while albuminuria is associated with blood-brain barrier disruption due to endothelial damage. Arterial stiffness adversely affects the brain with high pulsatile flow damaging cerebral micro-vessels.

Objective: To examine association between a novel kidney disease index (KDI), which is a composite index of estimated glomerular filtration (eGFR) and urinary albumin-to-creatinine ratio (uACR), and cognitive function with potential mediation by arterial stiffness.

Methods: This was a longitudinal multi-center study of participants with type 2 diabetes (T2D) aged 45 years and above. We assessed cognitive function with Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Pulse wave velocity (PWV), an index of arterial stiffness, was measured using applanation tonometry method. KDI was calculated as geometric mean of 1/eGFR and natural logarithmically-transformed (ln)(ACR*100).

Results: There were 1,303 participants with mean age 61.3±8.0 years. LnKDI was associated with lower baseline RBANS total score with adjusted coefficient -2.83 (95% CI -4.30 to -1.35; p < 0.001). 590 participants were followed over up to 8.6 years. LnKDI was associated with lower follow-up RBANS score in total, immediate memory, visuo-spatial/construction and attention domains with corresponding adjusted coefficients -2.35 (95% CI -4.50 to -0.20; p = 0.032), -2.93 (95% CI -5.84 to -0.02; p = 0.049), -3.26 (95% CI -6.25 to -0.27; p = 0.033) and -4.88 (95% CI -7.95 to -1.82; p = 0.002). PWV accounted for 19.5% of association between and follow-up RBANS total score.

Conclusions: KDI was associated with lower cognitive function globally, and in immediate memory, visuo-spatial/construction and attention domains. Arterial stiffness mediated the association between KDI and cognitive decline in patients with T2D.

Several decades of research on cell and animal models contributed tremendously to understanding human diseases. Particularly, research on rodents and non-human primates revealed that animal research is a major and important component in biomedical research in learning complex pathophysiological processes. Further, animal research helped us to understand human diseases, such as Alzheimer's disease. In addition, animal research has also helped us to test hundreds of drugs and develop treatments for human use. Researchers can gain a better understanding of key biological and physiological processes in humans by comparing them to laboratory animals. Based on their relevance and resemblance to people, or even usual living conditions, scientists rationalize the use of particular animal models in their studies. It is suggested that in the National Institutes of Health and other agencies-funded research, animal models should be carefully selected to study the biology and pathophysiology of human health and diseases such as Alzheimer's disease and other dementias. However, it is critical to use a minimum number of animals for human research. Further, it is also noted that the use and reuse of behavioral,  molecular, and biochemical data from wild-type (WT) control mice with mutant lines of disease models, as long as the genetic background is the same in both WT and disease mice. On the other hand, anonymous readers have challenged the use and reuse of WT mice data for comparison. In the current article, we discuss the minimum utility of animals, covering the 3Rs, Replacement, Reduction, and Refinement, and also discuss the use and reuse of behavioral, molecular, and biochemical data.

Background: Alzheimer's disease (AD) is related to one or more chronic illnesses, which may develop cognitive decline and dementia. Cognitive impairment is increasing, and public health officials must address risk factors for AD to improve the health of rural West Texas communities.

Objective: The purpose of this study was to explore the sociodemographic and chronic disease risk factors related to cognitive impairment among elderly adults living in Cochran, Parmer, and Bailey counties in rural West Texas.

Methods: Statistical methods such as Pearson's chi-squared, proportion tests, univariate binary logistic regression, and a multivariable logistic regression were utilized to analyze data. SPSS software was used to detect the significant relationship between cognitive impairment and risk factors.

Results: Summary statistics were obtained for sociodemographic and chronic diseases by using cross-tabulation analysis and comparing the county respondents with proportion tests. A univariate binary logistic regression method was utilized and found that age group 60-69, anxiety, depression, diabetes, hypertension, and cardiovascular disease were significantly associated with cognitive impairment. Using a multivariable logistic regression approach, it was found that Bailey County (age group 60-69) had a higher likelihood (p = 0.002) of cognitive impairment than Parmer (p = 0.067) and Cochran counties (p = 0.064). The risk of females (p = 0.033) in Parmer County was 78.3% lower compared to males in developing AD.

Conclusions: Identifying significant risk factors for cognitive impairment are important in addressing issues of geographic variations and integrating such factors may guide relevant policy interventions to reduce cognitive impairment incidence in rural communities within West Texas.

Background: As the prevalence of Alzheimer's disease (AD) grows with an aging population, the need for early diagnosis has led to increased focus on electroencephalography (EEG) as a non-invasive diagnostic tool.

Objective: This review assesses advancements in EEG analysis, including the application of machine learning, for detecting AD from 2000 to 2023.

Methods: Following PRISMA guidelines, a search across major databases resulted in 25 studies that met the inclusion criteria, focusing on EEG's application in AD diagnosis and the use of novel signal processing and machine learning techniques.

Results: Progress in EEG analysis has shown promise for early AD identification, with techniques like Hjorth parameters and signal compressibility enhancing detection capabilities. Machine learning has improved the precision of differential diagnosis between AD and mild cognitive impairment. However, challenges in standardizing EEG methodologies and data privacy remain.

Conclusions: EEG stands out as a valuable tool for early AD detection, with the potential to integrate into multimodal diagnostic approaches. Future research should aim to standardize EEG procedures and explore collaborative, privacy-preserving research methods.

We conducted a small, open-label, pilot study of daratumumab to explore target engagement, safety, and potential efficacy in patients with mild to moderate Alzheimer's disease. Daratumumab SC 1800 mg was given subcutaneously weekly for 8 weeks, then every 2 weeks for 16 weeks. Flow cytometry to measure the CD38+ proportion of CD8 + CD4- T cells and cognitive assessments were performed at baseline, day 176, and day 246. Daratumumab significantly reduced CD38 + CD8 + CD4- T cells after 24 weeks and this effect persisted 11 weeks thereafter. There was no hematological toxicity or unexpected adverse events. Responder analysis showed no improvement on cognitive outcome measures.

Background: Earlier research focuses primarily on the cognitive changes due to Alzheimer's disease (AD); however, little is known with regard to changes in language competence across the lifespan.

Objective: The present study aims to investigate the decline of language skills at the grammatical and syntactic levels due to changes in cognitive function.

Methods: We administered the Litmus Sentence Repetition Task (SRT) to 150 native speakers of Greek who fall into five groups: 1) young healthy speakers, 2) cognitively intact elder healthy speakers, 3) speakers with subjective cognitive impairment (SCI), 4) speakers with mild cognitive impairment (MCI); and 5) speakers with AD dementia at the mild/moderate stages. All participants underwent a physical and neurological examination and cognitive screening with a standardized neuropsychological battery to assess cognitive status comprehensively and evaluate aspects like working memory, executive function, attention and memory to appropriately classify them.

Results: The data analysis revealed that the SRT had high discriminatory value in the development of AD; specifically, both accuracy and grammaticality indices were related to cognitive decline. Additionally, syntax significantly affected the performance of speakers with structures such as clitics being particularly challenging and in most structures the performance of speakers with MCI drops significantly compared to speakers with SCI.

Conclusions: Linguistic indices revealed subtle early signs of cognitive decline that can be helpful in the early detection of AD, thus facilitating the clinical process offering support to language-based assessment tools such as sentence repetition, a non-invasive type of assessment to evaluate symptoms of AD.