Search

Brain health refers to the state of a person’s brain function across various domains, including cognitive, behavioral and motor functions. Healthy brains are associated with better individual health, increased creativity, and enhanced productivity. A person’s brain health is intricately connected to personal, social and environmental factors. Racial, ethnic, and social disparities affect brain health and on the global scale these disparities within and between regions present a hurdle to brain health. To overcome global disparities, greater collaboration between practitioners and healthcare providers and the people they serve is essential. This requires cultural humility driven by empathy. Empathy is a core prosocial value, a cognitive-emotional skill that helps us understand ourselves and others. This position paper aims to provide an overview of the vital roles of empathy, cooperation, and interdisciplinary partnerships. By consciously integrating this understanding in practice, leaders can better position themselves to address the diverse challenges faced by communities, promote inclusivity in policies and practices, and further more equitable solutions to the problem of global brain health.

Abstract Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment. Here, we describe scalable, repeatable, relatively non-invasive and comparatively inexpensive strategies for detecting the earliest markers of cognitive decline. These approaches are characterized by simple data collection protocols conducted in locations outside the laboratory: measurements are collected passively, by the participants themselves or by non-experts. The analysis of these data is, in contrast, often performed in a centralized location using sophisticated techniques. Recent developments allow neuropathology associated with potential cognitive decline to be accurately detected from peripheral blood samples. Advances in smartphone technology facilitate unobtrusive passive measurements of speech, fine motor movement and gait, that can be used to predict cognitive decline. Specific cognitive processes can be assayed using ‘gamified’ versions of standard laboratory cognitive tasks, which keep users engaged across multiple test sessions. High quality brain data can be regularly obtained, collected at-home by users themselves, using portable electroencephalography. Although these methods have great potential for addressing an important health challenge, there are barriers to be overcome. Technical obstacles include the need for standardization and interoperability across hardware and software. Societal challenges involve ensuring equity in access to new technologies, the cost of implementation and of any follow-up care, plus ethical issues.

Abstract Background Blood-based biomarkers for Alzheimer’s disease (AD) are highly needed in clinic practice. So far, the gold standards for AD diagnosis are brain neuroimaging and beta-amyloid peptide, total tau, and phosphorylated tau in cerebrospinal fluid (CSF); however, they are not attractive for large-scale screening. Blood-based biomarkers allow an initial large-scale screening of patients under suspicion that could later be tested for the already established CSF biomarkers. To this regard, in this study, we evaluated whether plasma ADAM10 levels would be predictors of declines in cognition in community-dwelling older adults after a 3-year period follow-up. Methods This was a 3-year longitudinal cohort study that included 219 community-dwelling older adults. Sociodemographic, clinical, lifestyle, depressive symptoms (GDS), and cognitive data (Mini-Mental State Examination, MMSE; Clock Drawing test, CDT) were gathered. The measurement of ADAM10 plasma levels was performed using a sandwich ELISA kit. Bivariate comparisons between groups were performed using Wilcoxon-Mann-Whitney for continuous data and Pearson’s chi-square tests with Yates continuity correction for categorical data. Longitudinal analyzes of changes in the MMSE scores were performed using linear mixed-effects modeling. Results Baseline MMSE scores and ADAM10 levels were significantly associated with MMSE scores on the follow-up assessment. When analyzing the interaction with time, normal MMSE scores and the ADAM10 plasma levels at baseline presented a significant and independent negative association with MMSE score values on the follow-up assessment. The analyses also showed that the predictive effect of ADAM10 plasma levels on decreasing MMSE scores on follow-up seems to be more pronounced in participants with normal MMSE, when compared with those with altered MMSE scores at baseline. Conclusions Considering that ADAM10 increase in plasma is detected as soon as in mild cognitive impairment (MCI) patients, the results presented here may support the complementary clinical use of this biomarker, in addition to the classical AD biomarkers. Taken together, these results provide the first direct evidence that changes in ADAM10 plasma levels are predictors of cognitive worsening in older adults. Moreover, this work can shed light on the study of blood biomarkers for AD and contribute to the advancement of the area.

Abstract Background The complex physiology underpinning the frailty syndrome is responsible for the absence of robust biomarkers that can be used for screening, diagnostic and/or prognostic purposes and has made clinical implementation difficult. Considering socially vulnerable populations, who have poor health status and increased morbidity and mortality, this scenario is even more complex. However, to the best of our knowledge, there are no studies available to investigate frailty biomarkers in socially vulnerable populations. Thus, the aim of this cross-sectional study was to identify potential blood-based biomarkers of frailty in a socially vulnerable population. Methods A sample consisting of 347 community-dwelling older people living in a context of high social vulnerability was divided into non-frail (robust), pre-frail and frail groups, according to modified Fried frailty phenotype criteria. Blood samples were collected and analyzed for basic metabolic parameters and for inflammatory cytokines. Results Levels of Interleukin-1α (IL-1α) and Tumor Necrosis Factor α (TNF-α) were significantly higher in pre-frail subjects, compared to non-frail ones. Tumor Necrosis Factor β (TNF-β) levels presented higher values in the frail compared to non-frail individuals. Interleukin-6 (IL-6) levels in pre-frail and frail subjects were significantly higher compared to the levels of non-frail subjects. Using an ordinal regression analysis, we observed that socially vulnerable older people at higher risk of developing frailty were subjects above 80 years old (OR: 2.5; 95% CI: 1.1–5.6) and who presented higher levels of TNF-β (≥0.81 pg/mL, OR: 2.53; 95% CI: 1.3–4.9). Conclusion As vulnerable populations continue to age, it is imperative to have a greater understanding of the frailty condition, identifying novel potential blood-based biomarkers. The results presented here could help to implement preventive healthcare strategies by evaluating frailty and at the same time measuring a set of inflammatory biomarkers, paying special attention to TNF-β plasmatic levels.

This study aimed to investigate a vulnerable population living in the context of poverty in a Brazilian municipality, in order to identify the factors that are associated with frailty syndrome in elderly people. From the total population living in the area, a random sample of 363 community-dwelling people, 60 years and older, age and gender-stratified, was selected to participate in the research. After losses, a sample of 304 older adults was classified as non-frail, pre-frail and frail. According to the Fried frailty criteria, the prevalence was 12.2% for non-frail individuals, 60.5% pre-frail and 27.3% frail. The main factors associated with frailty in the studied sample were low level of physical activity (OR: 5.2, 95%CI: 2.5-11.0), the occurrence of two or more falls within 12 months (OR: 3.1, 95%CI: 1.4-7.1), mobility deficits (OR: 3.0, 95%CI: 1.5-5.8), and depressive symptoms (OR: 1.9, 95%CI: 1.1-3.7). This study identified the most important factors that must be evaluated to identify frailty syndrome in a socially vulnerable population in the context of poverty. The data should help to encourage effective strategies concerning public health policies for this population., Competing Interests: None