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Background: Studies that assess cognition prospectively and study in detail anxiety history in the participants' medical records within the context of brain aging and Alzheimer's disease are limited., Objective: To examine the associations of anxiety and unspecified emotional distress (UED) acquired throughout a person's life with prospectively collected cognitive outcomes., Methods: Mayo Clinic Study of Aging participants who were cognitively unimpaired at baseline were included. Anxiety and UED data were abstracted from the medical record using the Rochester Epidemiology Project (REP) resources and were run separately as predictors in our models. The data were analyzed using Cox proportional hazards models for the outcomes of incident mild cognitive impairment (MCI) and dementia and using linear mixed effects models for the outcomes of global and domain specific cognitive z-scores and included key covariates., Results: The study sample (n = 1,808) had a mean (standard deviation) age of 74.5 (7.3) years and 51.4% were male. Anxiety was associated with increased risk of MCI and dementia and was associated with lower baseline cognitive z-scores and accelerated decline over time in the global, memory, and attention domains. UED was associated with faster decline in all domains except visuospatial but did not show evidence of association with incident cognitive outcomes. These results varied by medication use and timing of anxiety., Conclusions: Anxiety and UED both showed inverse associations with cognition. Utilization of anxiety and UED data from across the life course, as available, from the REP system adds robustness to our results.

Background: Population-based research on the prevalence and determinants of dementia, Alzheimer's disease, and cognitive impairment is scarce in East Africa., Objective: To provide an overview of community- and population-based studies among older adults on the prevalence of dementia and cognitive impairment in East Africa, and identify research gaps., Methods: We carried out a literature search using three electronic databases (PubMed, Scopus, Google Scholar) using pertinent search terms., Results: After screening 445 publications, we identified four publications on the population-based prevalence of dementia, and three on cognitive impairment. Prevalence rates varied from 6- 23% for dementia, and 7- 44% for cognitive impairment, among participants aged≥50-70 years. Old age and a lower education level were risk factors for dementia and cognitive impairment. Physical inactivity, lack of a ventilated kitchen, and history of central nervous system infections and chronic headache were associated with increased odds of dementia. Female sex, depression, having no spouse, increased lifetime alcohol consumption, low income, rural residence, and low family support were associated with increased odds of cognitive impairment. Potential misclassification and non-standardized data collection methods are research gaps that should be addressed in future studies., Conclusions: Establishing collaborative networks and partnering with international research institutions may enhance the capacity for conducting population-based studies on dementia and cognitive impairment in East Africa. Longitudinal studies may provide valuable insights on incidence, as well as potential risk and protective factors of dementia and cognitive impairment, and may inform the development of targeted interventions including preventive strategies in the region.

There is a growing interest in the application of machine learning (ML) in Alzheimer's disease (AD) research. However, neuropsychiatric symptoms (NPS), frequent in subjects with AD, mild cognitive impairment (MCI), and other related dementias have not been analyzed sufficiently using ML methods. To portray the landscape and potential of ML research in AD and NPS studies, we present a comprehensive literature review of existing ML approaches and commonly studied AD biomarkers. We conducted PubMed searches with keywords related to NPS, AD biomarkers, machine learning, and cognition. We included a total of 38 articles in this review after excluding some irrelevant studies from the search results and including 6 articles based on a snowball search from the bibliography of the relevant studies. We found a limited number of studies focused on NPS with or without AD biomarkers. In contrast, multiple statistical machine learning and deep learning methods have been used to build predictive diagnostic models using commonly known AD biomarkers. These mainly included multiple imaging biomarkers, cognitive scores, and various omics biomarkers. Deep learning approaches that combine these biomarkers or multi-modality datasets typically outperform single-modality datasets. We conclude ML may be leveraged to untangle the complex relationships of NPS and AD biomarkers with cognition. This may potentially help to predict the progression of MCI or dementia and develop more targeted early intervention approaches based on NPS.

Background: Considering the world's rapidly increasing life expectancy, with people working and maintaining active lifestyles longer than ever before, addressing the effects of aging on cognition is of utmost importance. A greater understanding of cognitive aging may also be critical in distinguishing natural cognitive aging from pre-clinical stages of Alzheimer's disease and related cognitive disorders., Objective: To systematically examine the association between aging and cognitive performance in a cognitively and otherwise healthy probability population-based sample using a computer-based method., Methods: This cross-sectional study enrolled 673 cognitively and otherwise healthy participants aged 25-89 years (mean age 52.3±14.2 years, 52.5% of whom were female) from the Kardiovize study cohort. Mild cognitive impairment and dementia cases were excluded, followed by measurement of cognitive performance with the computer-administered Cogstate Brief Battery. We used ANCOVA and Modified Signed-Likelihood Ratio tests to examine patterns of cognition across age groups., Results: We found a gradual decrease in cognitive performance across the lifespan, which required two decades to demonstrate significant changes. In contrast to attention and learning, psychomotor speed and working memory showed the most significant age-related decrease and variability in performance. The established pattern of cognitive aging was not altered by sex or education., Conclusion: These findings corroborate, validate, and extend the current understanding of natural cognitive aging and pinpoint specific cognitive domains with the most extensive age-related interindividual differences. This will contribute to the development of strategies to preserve cognition with aging and may also serve to improve early diagnostics of cognitive disorders using computer-based methods.

Background: Little is known about the association between physical activity (PA) and cognitive trajectories in older adults., Objective: To examine the association between PA and change in memory, language, attention, visuospatial skills, and global cognition, and a potential impact of sex or Apolipoprotein E (APOE) ɛ4 status., Methods: Longitudinal study derived from the population-based Mayo Clinic Study of Aging, including 2,060 cognitively unimpaired males and females aged ≥70 years. Engagement in midlife (ages 50-65) and late-life (last year) PA was assessed using a questionnaire. Neuropsychological testing was done every 15 months (mean follow-up 5.8 years). We ran linear mixed-effect models to examine whether mid- or late-life PA at three intensities (mild, moderate, vigorous) was associated with cognitive z-scores., Results: Light intensity midlife PA was associated with less decline in memory function compared to the no-PA reference group (time x light PA; estimate [standard error] 0.047 [0.016], p = 0.004). Vigorous late-life PA was associated with less decline in language (0.033 [0.015], p = 0.030), attention (0.032 [0.017], p = 0.050), and global cognition (0.039 [0.016], p = 0.012). Females who were physically inactive in midlife experienced more pronounced cognitive decline than females physically active in midlife and males regardless of PA (p-values for time interaction terms with midlife PA levels and sex were all p < 0.05 for global cognition). APOE ɛ4 carriership did not moderate the association between PA and cognition., Conclusion: Engaging in PA, particularly of vigorous intensity in late-life, was associated with less pronounced decline in global and domain-specific cognition. This association may differ by sex.

We conducted a prospective cohort study derived from the population-based Mayo Clinic Study of Aging. We investigated if leisure-time physical activity among individuals with mild cognitive impairment (MCI) was associated with a decreased risk of developing dementia. 280 persons aged≥70 years (median 81 years, 165 males) with MCI and available data from neurologic evaluation, neuropsychological testing, and questionnaire-based physical activity assessment, were followed for a median of 3 years to the outcomes of incident dementia or censoring variables. We conducted Cox proportional hazards regression analyses with age as a time scale and adjusted for sex, education, medical comorbidity, depression, and APOE ɛ4 status. Moderate intensity midlife physical activity among MCI participants was significantly associated with a decreased risk of incident dementia (HR = 0.64; 95% CI, 0.41-0.98). There was a non-significant trend for a decreased risk of dementia for light and vigorous intensity midlife physical activity, as well as light and moderate intensity late-life physical activity. In conclusion, we observed that physical activity may be associated with a reduced risk of dementia among individuals with MCI. Furthermore, intensity and timing of physical activity may be important factors when investigating this association.

Altered cortical thickness has been observed in aging and various neurodegenerative disorders. Furthermore, reduced hippocampal volume has been reported in late-life depression. Even mild depressive symptoms are common in the elderly. However, little is known about the structural MRI measures of depressive symptoms in normal cognitive aging. Thus we sought to examine the association between depressive symptoms with cortical thickness and hippocampal volume as measured by brain MRI among community-dwelling participants. We conducted a cross-sectional study derived from the ongoing population-based Mayo Clinic Study of Aging, involving cognitively normal participants (N = 1,507) aged≥70 years. We observed that depressive symptoms were associated with lower global cortical thickness and lower thickness in specific prefrontal and temporal cortical regions, labeled by FreeSurfer software, version 5.3. As expected, the strength of correlation was very small, given that participants were community-dwelling with only mild depressive symptoms. We did not observe associations between hippocampal volume and depressive symptoms. These findings may provide insight into the structural correlates of mild depressive symptoms in elderly participants.

One of the key research agenda of the field of aging is investigation of presymptomatic Alzheimer's disease (AD). Furthermore, abnormalities in brain glucose metabolism (as measured by FDG-PET) have been reported among cognitively normal elderly persons. However, little is known about the association of FDG-PET abnormalities with neuropsychiatric symptoms (NPS) in a population-based setting. Thus, we conducted a cross-sectional study derived from the ongoing population-based Mayo Clinic Study of Aging in order to examine the association between brain glucose metabolism and NPS among cognitively normal (CN) persons aged > 70 years. Participants underwent FDG-PET and completed the Neuropsychiatric Inventory Questionnaire (NPI-Q), Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI). Cognitive classification was made by an expert consensus panel. We conducted multivariable logistic regression analyses to compute odds ratios (OR) and 95% confidence intervals after adjusting for age, sex, and education. For continuous variables, we used linear regression and Spearman rank-order correlations. Of 668 CN participants (median 78.1 years, 55.4% males), 205 had an abnormal FDG-PET (i.e., standardized uptake value ratio < 1.32 in AD-related regions). Abnormal FDG-PET was associated with depression as measured by NPI-Q (OR = 2.12; 1.23-3.64); the point estimate was further elevated for APOE ɛ4 carriers (OR = 2.59; 1.00-6.69), though marginally significant. Additionally, we observed a significant association between abnormal FDG-PET and depressive and anxiety symptoms when treated as continuous measures. These findings indicate that NPS, even in community-based samples, can be an important additional tool to the biomarker-based investigation of presymptomatic AD.