Prevalence Of Alzheimer's Disease Research Articles

A systematic review/meta-analysis of prevalence and incidence rates illustrates systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research.

We investigate Alzheimer's disease and related dementia (ADRD) prevalence, incidence rate, and risk factors in individuals racialized as Asian and/or Asian-American and assess sample representation. Prevalence, incidence rate, risk factors, and heterogeneity of samples were assessed. Random-effects meta-analysis was conducted, generating pooled estimates. Of 920 records across 14 databases, 45 studies were included. Individuals racialized as Asian and/or Asian-American were mainly from Eastern and Southern Asia, had higher education, and constituted a smaller sample relative to non-Hispanic white cohorts. The average prevalence was 10.9%, ranging from 0.4% to 46%. The average incidence rate was 20.03 (12.01-33.8) per 1000 person-years with a range of 75.19-13.59 (12.89-14.33). Risk factors included physiological, genetic, psychological, behavioral, and social factors. This review underscores the systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research and the need for inclusive approaches accounting for culture, language, and immigration status. HIGHLIGHTS: There is considerable heterogeneity in the prevalence of ADRD among studies of Asian-Americans. There is limited data on group-specific risk factors for ADRD among Asian-Americans. The average prevalence of (ADRD) among Asian-Americans was found to be 7.4%, with a wide range from 0.5% to 46%.

Multi-Template Meta-Information Regularized Network for Alzheimer's Disease Diagnosis Using Structural MRI.

Structural magnetic resonance imaging (sMRI) has been widely applied in computer-aided Alzheimer's disease (AD) diagnosis, owing to its capabilities in providing detailed brain morphometric patterns and anatomical features in vivo. Although previous works have validated the effectiveness of incorporating metadata (e.g., age, gender, and educational years) for sMRI-based AD diagnosis, existing methods solely paid attention to metadata-associated correlation to AD (e.g., gender bias in AD prevalence) or confounding effects (e.g., the issue of normal aging and metadata-related heterogeneity). Hence, it is difficult to fully excavate the influence of metadata on AD diagnosis. To address these issues, we constructed a novel Multi-template Meta-information Regularized Network (MMRN) for AD diagnosis. Specifically, considering diagnostic variation resulting from different spatial transformations onto different brain templates, we first regarded different transformations as data augmentation for self-supervised learning after template selection. Since the confounding effects may arise from excessive attention to meta-information owing to its correlation with AD, we then designed the modules of weakly supervised meta-information learning and mutual information minimization to learn and disentangle meta-information from learned class-related representations, which accounts for meta-information regularization for disease diagnosis. We have evaluated our proposed MMRN on two public multi-center cohorts, including the Alzheimer's Disease Neuroimaging Initiative (ADNI) with 1,950 subjects and the National Alzheimer's Coordinating Center (NACC) with 1,163 subjects. The experimental results have shown that our proposed method outperformed the state-of-the-art approaches in both tasks of AD diagnosis, mild cognitive impairment (MCI) conversion prediction, and normal control (NC) vs. MCI vs. AD classification.

Alzheimer Disease Associated Loci: APOE Single Nucleotide Polymorphisms in Marmara Region

Alzheimer’s disease (AD) is a major global health challenge, especially among individuals aged 65 or older. According to population health studies, Turkey has the highest AD prevalence in the Middle East and Europe. To accurately determine the frequencies of common and rare APOE single nucleotide polymorphisms (SNPs) in the Turkish population residing in the Marmara Region, we conducted a retrospective study analyzing APOE variants in 588 individuals referred to the Bursa Uludag University Genetic Diseases Evaluation Center. Molecular genotyping, clinical exome sequencing, bioinformatics analysis, and statistical evaluation were employed to identify APOE polymorphisms and assess their distribution. The study revealed the frequencies of APOE alleles as follows: ε4 at 9.94%, ε2 at 9.18%, and ε3 at 80.68%. The gender-based analysis in our study uncovered a tendency for females to exhibit a higher prevalence of mutant genotypes across various SNPs. The most prevalent haplotype observed was ε3/ε3, while rare APOE SNPs were also identified. These findings align with global observations, underscoring the significance of genetic diversity and gender-specific characteristics in comprehending health disparities and formulating preventive strategies.

Cognitively healthy centenarians are genetically protected against Alzheimer's disease.

Alzheimer's disease (AD) prevalence increases with age, yet a small fraction of the population reaches ages > 100 years without cognitive decline. We studied the genetic factors associated with such resilience against AD. Genome-wide association studies identified 86 single nucleotide polymorphisms (SNPs) associated with AD risk. We estimated SNP frequency in 2281 AD cases, 3165 age-matched controls, and 346 cognitively healthy centenarians. We calculated a polygenic risk score (PRS) for each individual and investigated the functional properties of SNPs enriched/depleted in centenarians. Cognitively healthy centenarians were enriched with the protective alleles of the SNPs associated with AD risk. The protective effect concentrated on the alleles in/near ANKH, GRN, TMEM106B, SORT1, PLCG2, RIN3, and APOE genes. This translated to>5-fold lower PRS in centenarians compared to AD cases (P=7.69×10-71), and 2-fold lower compared to age-matched controls (P=5.83×10-17). Maintaining cognitive health until extreme ages requires complex genetic protection against AD, which concentrates on the genes associated with the endolysosomal and immune systems. Cognitively healthy cent enarians are enriched with the protective alleles of genetic variants associated with Alzheimer's disease (AD). The protective effect is concentrated on variants involved in the immune and endolysosomal systems. Combining variants into a polygenic risk score (PRS) translated to>5-fold lower PRS in centenarians compared to AD cases, and ≈ 2-fold lower compared to middle-aged healthy controls.

Pathophysiology characterization of Alzheimer's disease in South China's aging population: for the Greater-Bay-Area Healthy Aging Brain Study (GHABS).

The Guangdong-Hong Kong-Macao Greater-Bay-Area of South China has an 86million population and faces a significant challenge of Alzheimer's disease (AD). However, the characteristics and prevalence of AD in this area are still unclear due to the rarely available community-based neuroimaging AD cohort. Following the standard protocols of the Alzheimer's Disease Neuroimaging Initiative, the Greater-Bay-Area Healthy Aging Brain Study (GHABS) was initiated in 2021. GHABS participants completed clinical assessments, plasma biomarkers, genotyping, magnetic resonance imaging (MRI), β-amyloid (Aβ) positron emission tomography (PET) imaging, and tau PET imaging. The GHABS cohort focuses on pathophysiology characterization and early AD detection in the Guangdong-Hong Kong-Macao Greater Bay Area. In this study, we analyzed plasma Aβ42/Aβ40 (A), p-Tau181 (T), neurofilament light, and GFAP by Simoa in 470 Chinese older adults, and 301, 195, and 70 had MRI, Aβ PET, and tau PET, respectively. Plasma biomarkers, Aβ PET, tau PET, hippocampal volume, and temporal-metaROI cortical thickness were compared between normal control (NC), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia groups, controlling for age, sex, and APOE-ε4. The prevalence of plasma A/T profiles and Aβ PET positivity were also determined in different diagnostic groups. The aims, study design, data collection, and potential applications of GHABS are summarized. SCD individuals had significantly higher plasma p-Tau181 and plasma GFAP than the NC individuals. MCI and dementia patients showed more abnormal changes in all the plasma and neuroimaging biomarkers than NC and SCD individuals. The frequencies of plasma A+/T+ (NC; 5.9%, SCD: 8.2%, MCI: 25.3%, dementia: 64.9%) and Aβ PET positivity (NC: 25.6%, SCD: 22.5%, MCI: 47.7%, dementia: 89.3%) were reported. The GHABS cohort may provide helpful guidance toward designing standard AD community cohorts in South China. This study, for the first time, reported the pathophysiology characterization of plasma biomarkers, Aβ PET, tau PET, hippocampal atrophy, and AD-signature cortical thinning, as well as the prevalence of Aβ PET positivity in the Guangdong-Hong Kong-Macao Greater Bay Area of China. These findings provide novel insights into understanding the characteristics of abnormal AD pathological changes in South China's older population.

236 Association Between Gait Limitation and Alzheimer’s Disease: Comparison among Elderly in Puerto Rico and Mainland U.S.

OBJECTIVES/GOALS: In 2022, 116,000 Puerto Ricans were estimated to be affected by Alzheimer’s disease (AD). Gait limitation (GL) has been associated with different stages of AD. We study the GL-AD association in two elderly populations: Hispanics residing in PR and Americans in the mainland U.S., and identify the effects, and social determinants of health. METHODS/STUDY POPULATION: We propose a cross-sectional study involving data analysis from elderly (>65 years) Hispanics in PR and Americans in the U.S. Data will come from the National Alzheimer Coordinating Center (NACC) and a cohort of AD in PR. Our analysis will consider gait parameters, cognitive performance assessments, and AD stage (mild, moderate, and severe) as determined by the Alzheimer’s Association. We will examine social determinants of health and their association with GL and cognitive performance by AD. RESULTS/ANTICIPATED RESULTS: Our analysis will evaluate data about GL and AD stages to 1) investigate the association between GL and the distinct stages of AD and 2) evaluate the effects of social determinants of health in the association between GL and AD. We seek to profoundly understand how these factors interact within elderly populations. This exploration encompasses a diverse demographic, including elderly individuals in the U.S. and PR. We seek to identify disparities in social determinants among elderly individuals experiencing GL and AD by comparing PR and US populations. Through this association analysis, our study aspires to offer insight into the connections between GL and AD while considering the effects of social determinants of health in diverse populations. DISCUSSION/SIGNIFICANCE: The prevalence of AD is higher among Hispanic populations (e.g., Puerto Ricans) in the USA when compared to other ethnic groups. Experiencing GL may affect their daily lives, leading to exacerbating AD stages. The findings from this study will contribute to possible interventions to improve their GL and AD progression.

Predictive models for Alzheimer's disease diagnosis and MCI identification: The use of cognitive scores and artificial intelligence algorithms

The paper presents a comprehensive study on predictive models for Alzheimer's disease (AD) and Mild cognitive impairment (MCI) diagnosis, implementing a combination of cognitive scores and artificial intelligence algorithms. The research includes detailed analyses of clinical and demographic variables such as age, education, and various cognitive and functional scores, investigating their distributions and correlations with AD and MCI. The study utilizes several machine-learning classifiers, comparing their performance through metrics like accuracy, precision, and area under the ROC curve (AUC). Key findings include the influence of gender on AD prevalence, the potential protective effect of education, and the significance of functional decline and cognitive performance scores in the models. The results demonstrate the effectiveness of ensemble methods and the robustness of the models across different data subsets, highlighting the potential of artificial intelligence in enhancing diagnostic accuracy for Alzheimer's disease and Mild cognitive impairment.

Alzheimer’s Incidence and Prevalence with and without Asthma: A Medicare cohort study

International data suggest that asthma, like other inflammatory diseases, might increase Alzheimer's disease (AD) risk. To explore risk pathways and future mitigation strategies by comparing diagnostic claims-based AD incidence and prevalence among US patients with asthma to non-asthma patients. This cohort study included a national Medicare 20% random sample 2013-2015. Adult patients with >12 months continuous Medicare with asthma were compared to non-asthma subjects overall and as matched. Asthma was defined by one inpatient or two outpatient codes for asthma. The main outcomes were two-year incident or prevalent AD defined as any codes for ICD-9 331.0 or ICD-10 G30.0, G30.1, G30.8, G30.9. Among 5,460,732 total beneficiaries, 678,730 patients were identified with baseline asthma and more often identified as Black or Hispanic, were Medicaid eligible, or resided in a highly disadvantaged neighborhood than those without asthma. Two-year incidence of AD was 1.4% with asthma vs 1.1% without; prevalence was 7.8% vs 5.4% (both p=<0.001). Per 100,000 patients over two years, 303 more incident AD diagnoses occurred in asthma, with 2,425 more prevalent cases (p<0.001). Multivariable models showed asthma had greater odds of two-year AD incidence [AOR 1.33 (1.29-1.36); matched 1.2 (1.17-1.24)] and prevalence [AOR 1.48 (1.47-1.50); matched 1.25 (1.22-1.27)). Asthma was associated with 20-33% increased two-year incidence and 25-48% increased prevalence of claims-based Alzheimer's disease in this nationally representative US sample. Future research should investigate risk pathways of underlying comorbidities and social determinants, as well as whether there are potential asthma treatments that may preserve brain health.

Deep Brain Stimulation for Alzheimer’s Disease: A Review of a Potential Treatment in Neurosurgery

Background: Alzheimer’s disease (AD) is still a disease with abundant enigma. Moreover, the prevalence of AD increases every year by about 10 million new cases. This disease is well known for its degenerative feature with age being the most influencing factor. Pathophysiologically, the deposition of beta-amyloid and tau proteins is the culprit for disrupting the neural connections in the brains of AD patients. Some studies have stated that drug medications are not effective in treating AD patients.Content: Currently, there is no drug to cure the disease. In conditions in which drugs fail to take effect, there is a therapy called deep brain stimulation (DBS), which allows the brain to be stimulated electrically using electrodes that are implanted into certain brain areas as targets. In AD patients, the nucleus basalis of meynert (NBM) and fornix are frequently selected as targets in DBS. This intervention is performed surgically by the neurosurgeon. Several potential mechanisms of this treatment include controlling connections among neurons, decreasing beta-amyloid and tau protein levels, and inhibiting the inflammation process in the brain.Conclusion: DBS can improve AD patients, both clinically and molecularly. Despite the promising effects of DBS, this treatment has limitations, so it cannot be applied to every patient with AD.

Long-term exposure to major constituents of fine particulate matter and neurodegenerative diseases: A population-based survey in the Pearl River Delta Region, China

BackgroundExposure to PM2.5 has been linked to neurodegenerative diseases, with limited understanding of constituent-specific contributions. ObjectivesTo explore the associations between long-term exposure to PM2.5 constituents and neurodegenerative diseases. MethodsWe recruited 148,274 individuals aged ≥ 60 from four cities in the Pearl River Delta region, China (2020 to 2021). We calculated twenty-year average air pollutant concentrations (PM2.5 mass, black carbon (BC), organic matter (OM), ammonium (NH4+), nitrate (NO3-) and sulfate (SO42-)) at the individuals' home addresses. Neurodegenerative diseases were determined by self-reported doctor-diagnosed Alzheimer’s disease (AD) and Parkinson’s disease (PD). Generalized linear mixed models were employed to explore associations between pollutants and neurodegenerative disease prevalence. ResultsPM2.5 and all five constituents were significantly associated with a higher prevalence of AD and PD. The observed associations generally exhibited a non-linear pattern. For example, compared with the lowest quartile, higher quartiles of BC were associated with greater odds for AD prevalence (i.e., the adjusted odds ratios were 1.81; 95% CI, 1.45–2.27; 1.78; 95% CI, 1.37–2.32; and 1.99; 95% CI, 1.54–2.57 for the second, third, and fourth quartiles, respectively). ConclusionsLong-term exposure to PM2.5 and its constituents, particularly combustion-related BC, OM, and SO42-, was significantly associated with higher prevalence of AD and PD in Chinese individuals. Environmental implicationPM2.5 is a routinely regulated mixture of multiple hazardous constituents that can lead to diverse adverse health outcomes. However, current evidence on the specific contributions of PM2.5 constituents to health effects is scarce. This study firstly investigated the association between PM2.5 constituents and neurodegenerative diseases in the moderately to highly polluted Pearl River Delta region in China, and identified hazardous constituents within PM2.5 that have significant impacts. This study provides important implications for the development of targeted PM2.5 prevention and control policies to reduce specific hazardous PM2.5 constituents.

Serum high-sensitivity C-reactive protein and dementia in a community-dwelling Japanese older population (JPSC-AD)

In recent years, the association between neuroinflammatory markers and dementia, especially Alzheimer’s disease (AD), has attracted much attention. However, the evidence for the relationship between serum-hs-CRP and dementia including AD are inconsistent. Therefore, the relationships of serum high-sensitivity CRP (hs-CRP) with dementia including AD and with regions of interest of brain MRI were investigated. A total of 11,957 community residents aged 65 years or older were recruited in eight sites in Japan (JPSC-AD Study). After applying exclusion criteria, 10,085 participants who underwent blood tests and health-related examinations were analyzed. Then, serum hs-CRP levels were classified according to clinical cutoff values, and odds ratios for the presence of all-cause dementia and its subtypes were calculated for each serum hs-CRP level. In addition, the association between serum hs-CRP and brain volume regions of interest was also examined using analysis of covariance with data from 8614 individuals in the same cohort who underwent brain MRI. After multivariable adjustment, the odds ratios (ORs) for all-cause dementia were 1.04 (95% confidence interval [CI] 0.76–1.43), 1.68 (95%CI 1.08–2.61), and 1.51 (95%CI 1.08–2.11) for 1.0–1.9 mg/L, 2.0–2.9 mg/L, and ≥ 3.0 mg/L, respectively, compared to < 1.0 mg/L, and those for AD were 0.72 (95%CI 0.48–1.08), 1.76 (95%CI 1.08–2.89), and 1.61 (95%CI 1.11–2.35), for 1.0–1.9 mg/L, 2.0–2.9 mg/L, and ≥ 3.0 mg/L, respectively, compared to < 1.0 mg/L. Multivariable-adjusted ORs for all-cause dementia and for AD prevalence increased significantly with increasing serum hs-CRP levels (p for trend < 0.001 and p = 0.001, respectively). In addition, the multivariable-adjusted temporal cortex volume/estimated total intracranial volume ratio decreased significantly with increasing serum hs-CRP levels (< 1.0 mg/L 4.28%, 1.0–1.9 mg/L 4.27%, 2.0–2.9 mg/L 4.29%, ≥ 3.0 mg/L 4.21%; p for trend = 0.004). This study’s results suggest that elevated serum hs-CRP levels are associated with greater risk of presence of dementia, especially AD, and of temporal cortex atrophy in a community-dwelling Japanese older population.

Sildenafil as a Candidate Drug for Alzheimer's Disease: Real-World Patient Data Observation and Mechanistic Observations from Patient-Induced Pluripotent Stem Cell-Derived Neurons.

Alzheimer's disease (AD) is a chronic neurodegenerative disease needing effective therapeutics urgently. Sildenafil, one of the approved phosphodiesterase-5 inhibitors, has been implicated as having potential effect in AD. To investigate the potential therapeutic benefit of sildenafil on AD. We performed real-world patient data analysis using the MarketScan® Medicare Supplemental and the Clinformatics® databases. We conducted propensity score-stratified analyses after adjusting confounding factors (i.e., sex, age, race, and comorbidities). We used both familial and sporadic AD patient induced pluripotent stem cells (iPSC) derived neurons to evaluate the sildenafil's mechanism-of-action. We showed that sildenafil usage is associated with reduced likelihood of AD across four new drug compactor cohorts, including bumetanide, furosemide, spironolactone, and nifedipine. For instance, sildenafil usage is associated with a 54% reduced incidence of AD in MarketScan® (hazard ratio [HR] = 0.46, 95% CI 0.32- 0.66) and a 30% reduced prevalence of AD in Clinformatics® (HR = 0.70, 95% CI 0.49- 1.00) compared to spironolactone. We found that sildenafil treatment reduced tau hyperphosphorylation (pTau181 and pTau205) in a dose-dependent manner in both familial and sporadic AD patient iPSC-derived neurons. RNA-sequencing data analysis of sildenafil-treated AD patient iPSC-derived neurons reveals that sildenafil specifically target AD related genes and pathobiological pathways, mechanistically supporting the beneficial effect of sildenafil in AD. These real-world patient data validation and mechanistic observations from patient iPSC-derived neurons further suggested that sildenafil is a potential repurposable drug for AD. Yet, randomized clinical trials are warranted to validate the causal treatment effects of sildenafil in AD.

Light on Alzheimer's disease: from basic insights to preclinical studies.

Alzheimer's disease (AD), referring to a gradual deterioration in cognitive function, including memory loss and impaired thinking skills, has emerged as a substantial worldwide challenge with profound social and economic implications. As the prevalence of AD continues to rise and the population ages, there is an imperative demand for innovative imaging techniques to help improve our understanding of these complex conditions. Photoacoustic (PA) imaging forms a hybrid imaging modality by integrating the high-contrast of optical imaging and deep-penetration of ultrasound imaging. PA imaging enables the visualization and characterization of tissue structures and multifunctional information at high resolution and, has demonstrated promising preliminary results in the study and diagnosis of AD. This review endeavors to offer a thorough overview of the current applications and potential of PA imaging on AD diagnosis and treatment. Firstly, the structural, functional, molecular parameter changes associated with AD-related brain imaging captured by PA imaging will be summarized, shaping the diagnostic standpoint of this review. Then, the therapeutic methods aimed at AD is discussed further. Lastly, the potential solutions and clinical applications to expand the extent of PA imaging into deeper AD scenarios is proposed. While certain aspects might not be fully covered, this mini-review provides valuable insights into AD diagnosis and treatment through the utilization of innovative tissue photothermal effects. We hope that it will spark further exploration in this field, fostering improved and earlier theranostics for AD.

Ultrathin Parylene C-based sensitivity-gain nanoplasmonic sensor integrated on VCSEL for Aβ42 detection

As Alzheimer's disease prevalence continues to rise, there is an increasing demand for efficient on-chip biosensors capable of early biomarker detection. This study presents a novel biosensor chip leveraging vertical cavity surface emitting laser (VCSEL) technology, with Parylene C serving as the antibody coupling layer and utilizing a streamlined one-step antibody modification method. Integration of Parylene C enhances chip sensitivity from 34.28 μW/RIU to 40.32 μW/RIU. Moreover, post-testing removal of Parylene C enables chip reusability without significant alteration of results. The sensor demonstrates effective detection of Aβ42, an Alzheimer's biomarker, exhibiting a linear range of 1–200 ng/mL and a detection limit of 0.26 ng/mL. These findings underscore the reusability and reliability of the ultrathin Parylene C-based VCSEL biosensor chip, highlighting its potential for point-of-care Alzheimer's disease diagnosis.

Healthy Aging in Menopause: Prevention of Cognitive Decline, Depression and Dementia through Physical Exercise

The aging of the global population is a significant and complex phenomenon with far-reaching implications for healthcare systems and society. By 2030, it is projected that the number of individuals over the age of 65 will increase by nearly 1 billion, largely due to advancements in healthcare and improvements in quality of life. Aging is a multifaceted process that encompasses a wide array of changes, spanning from the cellular level to the intricate physiological systems of the human body. At the central nervous system level, aging represents a major risk factor for conditions such as depression and cognitive impairment, which are likely linked to neuroinflammatory processes and can potentially lead to more severe dementias, including Alzheimer’s disease (AD). The higher prevalence of AD in women compared to men has led to speculation that the onset of menopause and associated phenomena, particularly the decline in estrogen levels, may play a role in the development of the disease. Furthermore, research has shown that physical exercise confers both physical and mental health benefits to older adults, with women potentially experiencing the greatest advantages. Understanding the multifaceted nature of aging and its implications for health will ensure that older adults receive the support and care essential for maintaining their health and quality of life.

Nutritional Interventions for the Prevention of Cognitive Decline in Patients With Mild Cognitive Impairment and Alzheimer Disease: Protocol for a Network Meta-Analysis of Randomized Controlled Trials.

Mild cognitive impairment (MCI) is the stage between cognitive decline due to physiological aging and the severity of decline seen in neurodegenerative disorders like Alzheimer disease (AD), which is among the most prevalent neurodegenerative disorders characterized by cognitive impairment. People with MCI are at increased risk of developing AD. Although MCI and AD are incurable, nutritional interventions can potentially delay or prevent their onset. Consequently, effective interventions used to decelerate or alleviate the progress of cognitive impairment in older people are a significant focus in geriatric care. Given the synergistic effects of nutrition on health, assessing the effectiveness of nutritional supplements or dietary composition in preventing MCI or AD is essential for developing interventional strategies. Our study aims to assess the effectiveness of various nutritional interventions, including special dietary types, dietary patterns, specific foods, nutritional intake, and nutritional supplements, in preventing cognitive decline among patients diagnosed with MCI or AD. To achieve this, we will use a comprehensive approach, including network meta-analysis, pairwise meta-analysis, and systematic review of randomized controlled trials (RCTs). The review will follow the Population, Intervention, Comparison, Outcome (PICO) model and the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines. Two investigators will independently search PubMed electronically. Data extraction will follow the inclusion criteria, and data will be assessed for risk of bias using a revised tool. Additionally, evidence quality will be evaluated using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework. The outcomes of interest are assessing the cognitive outcomes in patients with MCI or AD. A systematic literature search will be conducted, identifying randomized controlled trials that investigate the impact of these nutritional interventions on cognitive function decline in individuals with MCI and AD. Network meta-analyses (random-effects model) and pairwise meta-analyses will then estimate the relative effectiveness of different nutritional interventions. We included 51 studies, published between 1999 and 2023 (27 studies for AD and 24 studies for MCI) and involving 8420 participants. We completed data extraction for all 51 studies by December 2023. Currently, we are actively engaged in data analysis and manuscript preparation. We plan to finalize the manuscript and publish the comprehensive results by the end of 2024. Our study holds significant clinical relevance given the rising prevalence of AD and the potential influence of nutritional interventions on cognitive function in individuals with MCI and AD. By investigating this relationship, our research aims to inform evidence-based decision-making in the development of prevention strategies for MCI and AD. The outcomes are expected to contribute to the establishment of reliable recommendations for MCI or AD management, providing substantial support in the field. PROSPERO CRD42022331173; http://tinyurl.com/3snjp7a4. PRR1-10.2196/47196.

Alzheimer's Disease - A Comprehensive Review

Introduction: Alzheimer's disease (AD) remains a pervasive and challenging neurodegenerative disorder with profound implications for individuals, families, and societies. As the most prevalent cause of dementia globally, AD's prevalence is set to rise significantly in the context of an aging population. This introductory section emphasizes the urgent need for a comprehensive understanding of the disease, encompassing both its molecular intricacies and the socio-economic burden. With age being the primary risk factor, recent research has delved into the complex interplay of genetic predisposition and environmental influences, reshaping our understanding of AD from a multifactorial perspective.&#x0D; Current State of Knowledge: Advancements in Alzheimer's research have led to a nuanced understanding of its pathology. Traditionally characterized by amyloid-beta plaques and tau tangles, recent insights from neuroimaging and biomarker studies have revealed the intricate nature of these pathologies and their roles in disease progression. Genetic studies, including genome-wide association analyses, have identified susceptibility loci, notably the APOE gene. Simultaneously, environmental factors, such as air pollution and lifestyle choices, are recognized contributors to AD risk. The therapeutic landscape has evolved, with ongoing investigations into anti-amyloid and anti-tau therapies, lifestyle interventions, and precision medicine approaches. The synthesis of these diverse findings highlights the dynamic nature of Alzheimer's research and its potential to shape future treatment modalities.&#x0D; Summary: In summary, this article provides a comprehensive overview of the current state of knowledge regarding Alzheimer's disease. From understanding its evolving pathology to exploring the interplay of genetic and environmental factors, the multifactorial nature of AD is underscored. The therapeutic landscape is actively advancing, presenting a hopeful outlook for future treatments.  

Review of the determinants contributing to the demographics of Alzheimer’s syndrome: Prevention techniques, risk factors, and insights for public health

Alzheimer's disease (AD) is the leading cause of memory loss, accounting for 80% of cases and severely impacting daily life and social interactions. The prevalence of AD is expected to grow over the globe as life expectancy improves and the population ages in developing countries will result in a costly disease burden. A combination of societal circumstances and inherent sensitivity that extends throughout a person’s lifetime can cause AD, a challenging and varied disorder. This study aims to provide a comprehensive analysis of the factors that shape the demographics of AD, with a focus on prevention measures. risk factors and their public health consequences. Interventions aimed at addressing multiple risk indicators in non-demented older adults, including those in their middle age, can be able to prevent or postpone the development of AD since the illness is thought to begin generations before clinical evidence appears. Addressing the intricate connection between social and psychological characteristics and Alzheimer’s demography is critical for devising effective preventative measures, early treatments and individualized care for at-risk communities. AD is known to be associated with genetic variables, particularly the APOE ε4 allele. Identifying the disease’s genetic causes is essential for specific preventive and early intervention methods. A balanced diet, frequent physical exercise, cognitive stimulation and social involvement are the preventative treatments for AD. Early identification and intervention hold promise for reducing disease development and public health measures that promote knowledge as well as healthy lives are essential.

Structural characterization of E22G Aβ1-42 fibrils via1H detected MAS NMR.

Amyloid fibrils have been implicated in the pathogenesis of several neurodegenerative diseases, the most prevalent example being Alzheimer's disease (AD). Despite the prevalence of AD, relatively little is known about the structure of the associated amyloid fibrils. This has motivated our studies of fibril structures, extended here to the familial Arctic mutant of Aβ1-42, E22G-Aβ1-42. We found E22G-AβM0,1-42 is toxic to Escherichia coli, thus we expressed E22G-Aβ1-42 fused to the self-cleavable tag NPro in the form of its EDDIE mutant. Since the high surface activity of E22G-Aβ1-42 makes it difficult to obtain more than sparse quantities of fibrils, we employed 1H detected magic angle spinning (MAS) nuclear magnetic resonance (NMR) experiments to characterize the protein. The 1H detected 13C-13C methods were first validated by application to fully protonated amyloidogenic nanocrystals of GNNQQNY, and then applied to fibrils of the Arctic mutant of Aβ, E22G-Aβ1-42. The MAS NMR spectra indicate that the biosynthetic samples of E22G-Aβ1-42 fibrils comprise a single conformation with 13C chemical shifts extracted from hCH, hNH, and hCCH spectra that are very similar to those of wild type Aβ1-42 fibrils. These results suggest that E22G-Aβ1-42 fibrils have a structure similar to that of wild type Aβ1-42.

Association between myasthenia gravis and Alzheimer's disease.

Myasthenia gravis (MG) and Alzheimer's disease (AD) are two of the most important diseases where the dysregulation of acetylcholine activity plays a crucial role. In the first, this dysregulation happens at the level of the neu-romuscular junction and in the second, in the central nervous system (CNS). To analyze the possible relationship between these two pathologies, analyzing the prevalence and the odds ratio of AD within patients previously diagnosed with MG. We will compare these data with respect to the prevalence of AD in the general population. We examined the data obtained by the electronic medical records of patients in the health care system of Castilla La Mancha using the Natural Language Process provided by a clinical platform of artificial intelligence known as the Savana Manager?. We identified 970,503 patients over the age of 60 years, of which 1,028 were diagnosed with MG. The proportion of the patients diagnosed with AD within this group (4.28%) was greater than the rest of the population (2.82%) (p = 0,0047) with an odds ratio of 1.54 (confidence interval at 95% 1.13-2.08; p = 0.0051) without finding significant differences in the bivariate analysis for the rest of the most important actual known risk factors for AD. Our results suggest that there might be an increase in the prevalence of AD in patients previously diagnosed with MG.