Cognition and brain health among older adults in Iceland: the AGES-Reykjavik study

Brain health in diverse settings: How age, demographics and cognition shape brain function

Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies. These included power spectrum and aperiodic (1/f slope, knee, offset) metrics, as well as complexity (fractal dimension estimation, permutation entropy, Wiener entropy, spectral structure variability) and connectivity (graph-theoretic mutual information, conditional mutual information, organizational information) from the source space resting-state EEG activity in a diverse sample from the global south and north populations. Brain-phenotype models were computed using EEG metrics reflecting local activity (power spectrum and aperiodic components) and brain dynamics and interactions (complexity and graph-theoretic measures). Electrophysiological brain dynamics were modulated by individual differences despite the varied methods of data acquisition and assessments across multiple centers, indicating that results were unlikely to be accounted for by methodological discrepancies. Variations in brain signals were mainly influenced by age and cognition, while education and sex exhibited less importance. Power spectrum activity and graph-theoretic measures were the most sensitive in capturing individual differences. Older age, poorer cognition, and being male were associated with reduced alpha power, whereas older age and less education were associated with reduced network integration and segregation. Findings suggest that basic individual differences impact core metrics of brain function that are used in standard case-control studies. Considering individual variability and diversity in global settings would contribute to a more tailored understanding of brain function.

Accelerated Aging Induced by an Unhealthy High-Fat Diet: Initial Evidence for the Role of Nrf2 Deficiency and Impaired Stress Resilience in Cellular Senescence

High-fat diets (HFDs) have pervaded modern dietary habits, characterized by their excessive saturated fat content and low nutritional value. Epidemiological studies have compellingly linked HFD consumption to obesity and the development of type 2 diabetes mellitus. Moreover, the synergistic interplay of HFD, obesity, and diabetes expedites the aging process and prematurely fosters age-related diseases. However, the underlying mechanisms driving these associations remain enigmatic. One of the most conspicuous hallmarks of aging is the accumulation of highly inflammatory senescent cells, with mounting evidence implicating increased cellular senescence in the pathogenesis of age-related diseases. Our hypothesis posits that HFD consumption amplifies senescence burden across multiple organs. To scrutinize this hypothesis, we subjected mice to a 6-month HFD regimen, assessing senescence biomarker expression in the liver, white adipose tissue, and the brain. Aging is intrinsically linked to impaired cellular stress resilience, driven by dysfunction in Nrf2-mediated cytoprotective pathways that safeguard cells against oxidative stress-induced senescence. To ascertain whether Nrf2-mediated pathways shield against senescence induction in response to HFD consumption, we explored senescence burden in a novel model of aging: Nrf2-deficient (Nrf2+/-) mice, emulating the aging phenotype. Our initial findings unveiled significant Nrf2 dysfunction in Nrf2+/- mice, mirroring aging-related alterations. HFD led to substantial obesity, hyperglycemia, and impaired insulin sensitivity in both Nrf2+/- and Nrf2+/+ mice. In control mice, HFD primarily heightened senescence burden in white adipose tissue, evidenced by increased Cdkn2a senescence biomarker expression. In Nrf2+/- mice, HFD elicited a significant surge in senescence burden across the liver, white adipose tissue, and the brain. We postulate that HFD-induced augmentation of senescence burden may be a pivotal contributor to accelerated organismal aging and the premature onset of age-related diseases.

Examining the relation between bilingualism and age of symptom onset in frontotemporal dementia

Bilingualism is thought to confer advantages in executive functioning, thereby contributing to cognitive reserve and a later age of dementia symptom onset. While the relation between bilingualism and age of onset has been explored in Alzheimer's dementia, there are few studies examining bilingualism as a contributor to cognitive reserve in frontotemporal dementia (FTD). In line with previous findings, we hypothesized that bilinguals with behavioral variant FTD would be older at symptom onset compared to monolinguals, but that no such effect would be found in patients with nonfluent/agrammatic variant primary progressive aphasia (PPA) or semantic variant PPA. Contrary to our hypothesis, we found no significant difference in age at symptom onset between monolingual and bilingual speakers within any of the FTD variants, and there were no notable differences on neuropsychological measures. Overall, our results do not support a protective effect of bilingualism in patients with FTD-spectrum disease in a U.S. based cohort.

Comparative study of machine learning methods for modeling associations between risk factors and future dementia cases

A substantial portion of dementia risk can be attributed to modifiable risk factors that can be affected by lifestyle changes. Identifying the contributors to dementia risk could prove valuable. Recently, machine learning methods have been increasingly applied to healthcare data. Several studies have attempted to predict dementia progression by using such techniques. This study aimed to compare the performance of different machine-learning methods in modeling associations between known cognitive risk factors and future dementia cases. A subset of the AGES-Reykjavik Study dataset was analyzed using three machine-learning methods: logistic regression, random forest, and neural networks. Data were collected twice, approximately five years apart. The dataset included information from 1,491 older adults who underwent a cognitive screening process and were considered to have healthy cognition at baseline. Cognitive risk factors included in the models were based on demographics, MRI data, and other health-related data. At follow-up, participants were re-evaluated for dementia using the same cognitive screening process. Various performance metrics for all three machine learning algorithms were assessed. The study results indicate that a random forest algorithm performed better than neural networks and logistic regression in predicting the association between cognitive risk factors and dementia. Compared to more traditional statistical analyses, machine-learning methods have the potential to provide more accurate predictions about which individuals are more likely to develop dementia than others.

Brain Health and Cognition in Older Adults: Roadmap and Milestones towards the Implementation of Preventive Strategies

In this narrative review, we delve into the evolving concept of brain health, as recognized by the WHO, focusing on its intersection with cognitive decline. We emphasize the imperative need for preventive strategies, particularly in older adults. We describe the target population that might benefit the most from risk-based approaches-namely, people with subjective cognitive decline. Additionally, we consider universal prevention in cognitively unimpaired middle-aged and older adults. Delving into multidomain personalized preventive strategies, we report on empirical evidence surrounding modifiable risk factors and interventions crucial in mitigating cognitive decline. Next, we highlight the emergence of brain health services (BHS). We explain their proposed role in risk assessment, risk communication, and tailored interventions to reduce the risk of dementia. Commenting on ongoing BHS pilot experiences, we present the inception and framework of our own BHS in Monza, Italy, outlining its operational structure and care pathways. We emphasize the need for global collaboration and intensified research efforts to address the intricate determinants of brain health and their potential impact on healthcare systems worldwide.

Improving Cognitive Function with Nutritional Supplements in Aging: A Comprehensive Narrative Review of Clinical Studies Investigating the Effects of Vitamins, Minerals, Antioxidants, and Other Dietary Supplements

Cognitive impairment and dementia are burgeoning public health concerns, especially given the increasing longevity of the global population. These conditions not only affect the quality of life of individuals and their families, but also pose significant economic burdens on healthcare systems. In this context, our comprehensive narrative review critically examines the role of nutritional supplements in mitigating cognitive decline. Amidst growing interest in non-pharmacological interventions for cognitive enhancement, this review delves into the efficacy of vitamins, minerals, antioxidants, and other dietary supplements. Through a systematic evaluation of randomized controlled trials, observational studies, and meta-analysis, this review focuses on outcomes such as memory enhancement, attention improvement, executive function support, and neuroprotection. The findings suggest a complex interplay between nutritional supplementation and cognitive health, with some supplements showing promising results and others displaying limited or context-dependent effectiveness. The review highlights the importance of dosage, bioavailability, and individual differences in response to supplementation. Additionally, it addresses safety concerns and potential interactions with conventional treatments. By providing a clear overview of current scientific knowledge, this review aims to guide healthcare professionals and researchers in making informed decisions about the use of nutritional supplements for cognitive health.

Exposure factors associated with dementia among older adults in Iceland: the AGES-Reykjavik study

The study aimed to assess whether factors related to cognitive performance were associated with the development of dementia. Additionally, the study aimed to establish whether cognitive performance at baseline or change in cognition between baseline and follow-up (five-year period) had a stronger association with whether an individual would fulfill a dementia criterion at follow-up. The data was collected from 2002 to 2011. Logistic regression was applied to the AGES-Reykjavik Study epidemiological data. The analysis, which builds upon previous data analyses of the same dataset, included 1,491 participants between the ages of 66 and 90. All those included were considered to have normal cognition at baseline; 8.2% (n = 123) of them fulfilled a dementia criterion at follow-up five years later. The study's results indicated that being high on cognitive reserve factors reduced the risk of developing dementia. Compared to other known dementia risk factors, cognitive reserve factors (education level, participation in leisure activities, and self-reported health) were more likely than others to have an association with dementia. Additionally, the study's findings showed that cognitive performance at baseline, rather than change in cognition between baseline and follow-up five years later, had a stronger association with dementia at the follow-up assessment. Together, these findings support the notion that promoting high cognitive reserve throughout the lifespan and reaching high cognitive performance is important in reducing dementia risk.