Advances in proteomic and metabolomic profiling of neurodegenerative diseases

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

Subjective cognitive decline in Brazil : prevalence and association with dementia modifiable risk factors in a population-based study

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

Race-related population attributable fraction of preventable risk factors of dementia : a latino population-based study

Background: risk factors for dementia have distinct frequency and impact in relation to race. Our aim was to identify differences in modifiable risk factors of dementia related to races and estimate their population attributable fraction (PAF). Methods: an epidemiological cohort was used to estimate the prevalence of 10 modifiable risk factors for dementia among five races—White, Black, Brown, Asian, and Indigenous. Sample weighting was used to estimate the prevalence and PAF of each risk factor in each race. Results:a total of 9070 individuals were included. Overall adjusted PAF was the lowest in Indigenous (38.9%), and Asian individuals (41.2%). Race-related prevalence of individual risk factors was widely variable in our population, but hearing loss was the most important contributor to the overall PAF in all races. Conclusions Public policies aiming to reduce preventable risk factors for dementia should take into consideration the race of the target populations

Disparity in the use of Alzheimer's disease treatment in Southern Brazil

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

Soluble amyloid-beta isoforms predict downstream Alzheimer’s disease pathology

Background: Changes in soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer’s disease (AD). However, whether Aβ 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 Aβ isoforms can predict tau pathology (T+) and neurodegeneration (N+) positivity. Methods: We used CSF measurements of three soluble Aβ peptides (Aβ1–38, Aβ1–40 and Aβ1–42) 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 Aβ 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 Aβ 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

A three-range approach enhances the prognostic utility of CSF biomarkers in Alzheimer's disease

Introduction: Alzheimer's disease consensus recommends biomarker dichotomization, a practice with well-described clinical strengths and methodological limitations. Although neuroimaging studies have explored alternative biomarker interpretation strategies, a formally defined three-range approach and its prognostic impact remains under-explored for cerebrospinal fluid (CSF) biomarkers. Methods: With two-graph receiver-operating characteristics based on different reference schemes, we derived three-range cut-points for CSF Elecsys biomarkers. According to baseline CSF status, we assessed the prognostic utility of this in predicting risk of clinical progression and longitudinal trajectories of cognitive decline and amyloid–beta (Aβ) positron emission tomography (PET) accumulation in non-demented individuals (Alzheimer's Disease Neuroimaging Initiative [ADNI]; n = 1246). In all analyses, we compared herein-derived three-range CSF cut-points to previously described binary ones. Results: In our main longitudinal analyses, we highlight CSF p-tau181/Aβ1-42 three-range cut-points derived based on the cognitively normal Aβ-PET negative versus dementia Aβ-PET positive reference scheme for best depicting a prognostically relevant biomarker abnormality range. Longitudinally, our approach revealed a divergent intermediate cognitive trajectory undetected by dichotomization and a clearly abnormal group at higher risk for cognitive decline, with power analyses suggesting the latter group as potential trial enrichment candidates. Furthermore, we demonstrate that individuals with intermediate-range CSF status have similar rates of Aβ deposition to those in the clearly abnormal group. Discussion: The proposed approach can refine clinico-biological prognostic assessment and potentially enhance trial recruitment, as it captures faster biomarker-related cognitive decline in comparison to binary cut-points. Although this approach has implications for trial recruitment and observational studies, further discussion is needed regarding clinical practice applications

Underrepresented Populations in Parkinson's Genetics Research: Current Landscape and Future Directions

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

A simulação computacional como ferramenta de aplicação da teoria das restrições para estudo de capacidade numa indústria de propriedade em bateladas

O presente artigo utiliza a simulação computacional como ferramenta de aplicação da Teoria das Restrições (TOC) e conceitos da classificação de indústrias de forma e propriedade para desenvolver um plano de aumento de capacidade numa indústria do ramo tabagista localizada no Rio Grande do Sul.The present paper uses computing simulation as a tool for applying the Theory of Constraints (TOC) and concepts of “process classification in form and property” to develop a capacity increase plan in a tobacco industry located in Rio Grande do Sul, Brazil

A simulação computacional como ferramenta de aplicação da teoria das restrições para estudo de capacidade numa indústria de propriedade em bateladas

O presente artigo utiliza a simulação computacional como ferramenta de aplicação da Teoria das Restrições (TOC) e conceitos da classificação de indústrias de forma e propriedade para desenvolver um plano de aumento de capacidade numa indústria do ramo tabagista localizada no Rio Grande do Sul.The present paper uses computing simulation as a tool for applying the Theory of Constraints (TOC) and concepts of “process classification in form and property” to develop a capacity increase plan in a tobacco industry located in Rio Grande do Sul, Brazil