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Alzheimer's disease (AD) treatment is freely available in the Brazilian public health system. However, the prescription pattern and its associated factors have been poorly studied in our country. We reviewed all granted requests for AD treatment in the public health system in October 2021 in the Rio Grande do Sul (RS) state, Southern Brazil. We performed a spatial autocorrelation analysis with the population-adjusted patients receiving any AD medication as the outcome and correlated it with several socioeconomic variables. 2382 patients with AD were being treated during the period analyzed. The distribution of the outcome variable was not random (Moran's I 0.17562, P <.0001), with the most developed regions having a higher number of patients/100,000 receiving any AD medication. We show that although AD medications are available through the public health system, there is a clear disparity between regions of RS state. Factors related to socioeconomic development partly explain this finding.
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Doença de Alzheimer , Humanos , Brasil , Prescrições , Saúde Pública , Análise EspacialRESUMO
Introduction: Subjective cognitive decline (SCD) may be an early symptom of Alzheimer's disease. We aimed to estimate the prevalence of SCD in Brazil and its association with dementia modifiable risk factors. Methods: We used data of 8138 participants from the Brazilian Longitudinal Study of Aging (ELSI-Brazil), a population-based study that included clinical and demographic variables of individuals across the country. We calculated the prevalence of SCD and its association with dementia modifiable risk factors. Results: We found that the prevalence of SCD in Brazil was 29.21% (28.22%-30.21%), varying according to region, sex, and age. SCD was strongly associated with hearing loss, low education, psychological distress, Brown/Pardo and Black races. Discussion: The prevalence of SCD in Brazil is higher than in high-income countries. Brown/Black races and dementia modifiable risk factors were associated with SCD. Public strategies that target SCD may help mitigate the incidence of dementia.
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BACKGROUND: Human genetics research lacks diversity; over 80% of genome-wide association studies have been conducted on individuals of European ancestry. In addition to limiting insights regarding disease mechanisms, disproportionate representation can create disparities preventing equitable implementation of personalized medicine. OBJECTIVE: This systematic review provides an overview of research involving Parkinson's disease (PD) genetics in underrepresented populations (URP) and sets a baseline to measure the future impact of current efforts in those populations. METHODS: We searched PubMed and EMBASE until October 2021 using search strings for "PD," "genetics," the main "URP," and and the countries in Latin America, Caribbean, Africa, Asia, and Oceania (excluding Australia and New Zealand). Inclusion criteria were original studies, written in English, reporting genetic results on PD from non-European populations. Two levels of independent reviewers identified and extracted information. RESULTS: We observed imbalances in PD genetic studies among URPs. Asian participants from Greater China were described in the majority of the articles published (57%), but other populations were less well studied; for example, Blacks were represented in just 4.0% of the publications. Also, although idiopathic PD was more studied than monogenic forms of the disease, most studies analyzed a limited number of genetic variants. We identified just nine studies using a genome-wide approach published up to 2021, including URPs. CONCLUSION: This review provides insight into the significant lack of population diversity in PD research highlighting the immediate need for better representation. The Global Parkinson's Genetics Program (GP2) and similar initiatives aim to impact research in URPs, and the early metrics presented here can be used to measure progress in the field of PD genetics in the future. © 2022 International Parkinson and Movement Disorder Society.
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Doença de Parkinson , China , Previsões , Estudo de Associação Genômica Ampla , Humanos , Nova Zelândia , Doença de Parkinson/epidemiologia , Doença de Parkinson/genéticaRESUMO
BACKGROUND: Changes in soluble amyloid-beta (Aß) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer's disease (AD). However, whether Aß levels can predict downstream AD pathological features in cognitively unimpaired (CU) individuals remains unclear. With this in mind, we aimed at investigating whether a combination of soluble Aß isoforms can predict tau pathology (T+) and neurodegeneration (N+) positivity. METHODS: We used CSF measurements of three soluble Aß peptides (Aß1-38, Aß1-40 and Aß1-42) in CU individuals (n = 318) as input features in machine learning (ML) models aiming at predicting T+ and N+. Input data was used for building 2046 tuned predictive ML models with a nested cross-validation technique. Additionally, proteomics data was employed to investigate the functional enrichment of biological processes altered in T+ and N+ individuals. RESULTS: Our findings indicate that Aß isoforms can predict T+ and N+ with an area under the curve (AUC) of 0.929 and 0.936, respectively. Additionally, proteomics analysis identified 17 differentially expressed proteins (DEPs) in individuals wrongly classified by our ML model. More specifically, enrichment analysis of gene ontology biological processes revealed an upregulation in myelinization and glucose metabolism-related processes in CU individuals wrongly predicted as T+. A significant enrichment of DEPs in pathways including biosynthesis of amino acids, glycolysis/gluconeogenesis, carbon metabolism, cell adhesion molecules and prion disease was also observed. CONCLUSIONS: Our results demonstrate that, by applying a refined ML analysis, a combination of Aß isoforms can predict T+ and N+ with a high AUC. CSF proteomics analysis highlighted a promising group of proteins that can be further explored for improving T+ and N+ prediction.
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Proteomics and metabolomics are two emerging fields that hold promise to shine light on the molecular mechanisms causing neurodegenerative diseases. Research in this area may reveal and quantify specific metabolites and proteins that can be targeted by therapeutic interventions intended at halting or reversing the neurodegenerative process. This review aims at providing a general overview on the current status of proteomic and metabolomic profiling in neurodegenerative diseases. We focus on the most common neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. We discuss the relevance of state-of-the-art metabolomics and proteomics approaches and their potential for biomarker discovery. We critically review advancements made so far, highlighting how metabolomics and proteomics may have a significant impact in future therapeutic and biomarker development. Finally, we further outline technologies used so far as well as challenges and limitations, placing the current information in a future-facing context.