Geda, Yonas E

AbstractBackground and AimsPhysical activity (PA) is associated with higher gait speed. We aimed to examine the associations between PA and change in spatial and temporal gait measures as well as fall risk in community‐dwelling individuals free of dementia.MethodsLongitudinal study among 4173 individuals aged ≥50 years (mean age 71 years; 2078 males; median follow‐up 4 years) enrolled in the Mayo Clinic Study of Aging. Self‐reported late‐life PA was used to calculate overall PA and moderate‐vigorous PA (MVPA) scores. Gait was assessed using GAITRite® and Zeno™ systems. Incident falls information was based on diagnostic codes retrieved from medical records. We ran linear mixed effects models to examine associations between z‐scored PA variables and longitudinal gait parameters, adjusted for age, sex, education, body mass index (BMI), medical comorbidities, and including interactions between PA and time since baseline. In secondary analyses, we calculated Cox Proportional hazard models with age as time scale predicting incident falls by PA, adjusting for sex, education, BMI, medical comorbidities, and falls history.ResultsAt baseline, higher PA was associated with higher velocity (overall PA: estimate 2.9935; MVPA: 2.2961; p < 0.001), higher cadence (overall PA: 1.0665; MVPA: 0.9073; p < 0.001), greater stride length (overall PA: 2.0805; MVPA: 1.4726; p < 0.001), shorter double support time (overall PA: −0.0257; MVPA: −0.0205; p < 0.001), and lower stance time variability (overall PA: −0.0204, p < 0.001; MVPA: −0.0152; p = 0.006). Overall PA was longitudinally associated with less decline in cadence, and MVPA with less increase in intraindividual stance time variability. Overall PA (Hazard ratio 0.892, 95% confidence interval 0.828–0.961, p = 0.003) and MVPA (HR 0.901; 95% CI 0.835–0.973, p = 0.008) were associated with a decreased risk of incident falls.ConclusionLate‐life PA was associated with favorable gait outcomes and decreased risk of incident falls. Thus, late‐life PA may help to maintain gait performance and decrease fall risk in old age.

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: 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) ε4 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 ε4 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.

The study included 1,738 Mayo Clinic Study of Aging participants (≥50 years old; 1,460 cognitively unimpaired and 278 with mild cognitive impairment (MCI)) and examined the cross-sectional association between cerebrovascular (CVD) imaging biomarkers (e.g., white matter hyperintensities (WMH), infarctions) and Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) scores, as well as their association with MCI. High (abnormal) WMH burden was significantly associated with having BDI-II>13 and BAI > 7 scores, and both (CVD imaging biomarkers and depression/anxiety) were significantly associated with MCI when included simultaneously in the model, suggesting that both were independently associated with the odds of MCI.

AbstractINTRODUCTIONWe examined associations between plasma‐derived biomarkers of Alzheimer's disease (AD) and neuropsychiatric symptoms (NPS) in community‐dwelling older adults.METHODSCross‐sectional study involving 1005 persons ≥50 years of age (mean 74 years, 564 male, 118 cognitively impaired), who completed plasma‐derived biomarker (amyloid beta 42 [Aβ42]/Aβ40, phosphorylated tau 181 [p‐tau181], p‐tau217, total tau [t‐tau], neurofilament light [NfL]), and NPS assessment.RESULTSP‐tau181 (odds ratio [OR] 2.06, 95% confidence interval [CI] 1.41–3.00, p < 0.001), p‐tau217 (OR 1.70, 95% CI 1.10–2.61, p = 0.016), and t‐tau (OR 1.44, 95% CI 1.08–1.92, p = 0.012) were associated with appetite change. We also found that p‐tau181 and p‐tau217 were associated with increased symptoms of agitation (OR 1.93, 95% CI 1.20–3.11, p = 0.007 and OR 2.04, 95% CI 1.21–3.42, p = 0.007, respectively), and disinhibition (OR 2.39, 95% CI 1.45–3.93, p = 0.001 and OR 2.30, 95% CI 1.33–3.98, p = 0.003, respectively). Aβ42/Aβ40 and NfL were not associated with NPS.CONCLUSIONHigher plasma‐derived p‐tau181 and p‐tau217 levels are associated with increased symptoms of appetite change, agitation, and disinhibition. These findings may support the validity of plasma tau biomarkers for predicting behavioral symptoms that often accompany cognitive impairment.HIGHLIGHTS We studied 1005 community‐dwelling persons aged ≥ 50 years Higher plasma tau levels are associated with increased neuropsychiatric symptoms Aβ42/Aβ40 and NfL are not associated with neuropsychiatric symptoms Clinicians should treat neuropsychiatric symptoms in persons with high plasma‐derived tau

Abstract The observation that aging is regulated by microRNAs (miRNA) and at the same time represents the greatest risk factor for Alzheimer's disease (AD), prompted us to examine the circulating miRNA network in AD beyond aging. We here show that plasma miRNAs in aging are downregulated and predicted to be preferentially targeted to the extracellular vesicle (EV) content. In AD, miRNAs are further downregulated, display altered proportions of motifs relevant to their loading into EVs and secretion propensity, and are forecast to be found exclusively in EVs. The circulating miRNA network in AD, therefore, reflects pathological exacerbation of the aging process whereby physiological suppression of AD pathology by miRNAs becomes insufficient. image

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.