Microgravity-induced Cognitive Decline

Cognitive, social, and physical activities, collectively linked to cognitive reserve, are associated with better late-life cognitive outcomes. To better understand the building of cognitive reserve, we investigated which of these activities, during which stages of life, had the strongest associations with late-life cognitive performance. From the Sydney Memory and Aging Study, 546 older Australians, who were community-dwelling and without a dementia diagnosis at recruitment (Mage 80.13 years, 52.2% female), were asked about their engagement in social, physical, and cognitive activities throughout young adulthood (YA), midlife (ML), and late-life (LL). Comprehensive neuropsychological testing administered biennially over 6 years measured baseline global cognition and cognitive decline. In our study, YA, but not ML nor LL, cognitive activity was significantly associated with late-life global cognition (β = 0.315, p < .001). A follow-up analysis pointed to the formal education component of the YA cognitive activity measure, rather than YA cognitive leisure activities, as a significant predictor of better late-life global cognition (β = 0.146, p = .003). YA social activity and LL cognitive activity were significantly associated with less cognitive decline (β = 0.023, p < .001, and β = 0.016, p = .022, respectively). Physical activity was not found to be associated with global cognition or cognitive decline. Overall, YA cognitive activity was associated with better late-life cognition, and YA social and LL cognitive activities were associated with less cognitive decline. Formal education emerges as the key contributor in the association between YA cognitive activity and late-life global cognition.

Differential Association of Concurrent, Baseline, and Average Depressive Symptoms With Cognitive Decline in Older Adults

BackgroundThe mapping between risk factors and biomarkers with cognitive performance and decline in the older adults is complex and varies significantly across different age and sex groups. Our goals were to (i) develop a machine learning (ML) model to predict baseline cognition and cognitive decline over a 5‐year follow‐up using only baseline assessments, and (ii) identify important modifiable and non‐modifiable predictors of cognitive decline across different age strata.MethodWe utilized longitudinal data from 2219 participants (mean age (SD): 70 (12) years, 49% male) from Mayo Clinic Study of Aging who had 43 features belonging to cardiovascular health, plasma, MRI (diffusion and structural), and lifestyle measures. Cognition was measured using a global cognition z‐score. We built ML models to predict baseline cognition and rate of cognitive decline over 5‐years (linear regression slopes over all individual followup measurements for each participant) using baseline assessments as inputs. We then built a model for each category separately and as a pooled model with all measures included, incorporating education and sex as demographic features in all models (Fig. 1). We applied a multi‐layer stack ensemble ML technique that utilized repeated k‐fold bagging to maximize accuracy. Importance of the top predictors were assessed in three age strata (55‐65 years (31%), 65‐80 years (46%), 80‐95 years (23%)).ResultThe pooled model explained the largest variance for prediction of baseline cognition and cognitive decline (Fig. 2). In individuals ≤80 years, lower NfL was most predictive of higher baseline cognition. A combination of imaging and plasma features predicted the 5‐year cognitive decline. Additionally, in individuals ≤65 years, diabetes and hypertension were important predictors of faster cognitive decline and in those &gt;80, lower BMI and midlife physical/cognitive activity was an important predictor of faster cognitive decline (Fig. 3).ConclusionThe plasma model was best for baseline cognition prediction and imaging model was best for cognitive decline prediction. There was significant heterogeneity in important features across the age strata. In individuals &gt;65 years, plasma GFAP was the most important predictor of cognitive decline. Our model allowed identification of key risk factors that predicted cognitive decline.

Social connectedness and cognitive decline

Application of chemical exchange saturation transfer (CEST) MRI in acute stroke to visualize tissue acidosis and infarction risk

There has yet to be a large-scale study quantifying the association between white matter microstructure and cognitive performance and decline in aging and Alzheimer disease (AD). To investigate the associations between tract-specific white matter microstructure and cognitive performance and decline in aging and AD-related cognitive impairment. This prognostic study of aging and AD, a secondary data analysis of multisite cohort studies, acquired data from 9 cohorts between September 2002 and November 2022. Participants were eligible if they had diffusion-weighted magnetic resonance imaging (dMRI) data, domain-specific cognitive composite z scores, demographic and clinical data, were aged 50 years or older, and passed neuroimaging quality control. Demographic and clinical covariates included age, sex, education, race and ethnicity, APOE haplotype status (ε2, ε3, ε4), and clinical status. The present study was conducted from June 2024 to February 2025. White matter microstructure and cognitive performance and decline. Clinical diagnosis, imaging measures (dMRI, T1-weighted MRI, and amyloid and tau positron emission tomography), and cognitive tests. Of 4467 participants who underwent 9208 longitudinal cognitive sessions, 2698 (60.4%) were female, and the mean age (SD) was 74.3 (9.2) years; 3213 were cognitively unimpaired, 972 had mild cognitive impairment, and 282 had AD dementia. White matter free water (FW) showed the strongest associations with cross-sectional cognitive performance and longitudinal cognitive decline across all domains, particularly memory. FW in limbic tracts, such as the cingulum, presented the strongest associations with both memory performance (cingulum: β = -0.718; P < .001; fornix: β = -1.069; P < .001) and decline (cingulum: β = -0.115; P < .001; fornix: β = -0.153; P < .001). White matter FW measures interacted with baseline diagnosis, gray matter atrophy, APOE ε4 status, and amyloid positivity to predict poorer cognitive performance and accelerated cognitive decline. Noteworthy interactions include fornix FW and hippocampal volume (β = 10.598; P < .001), cingulum FW and SPARE-AD index (β = -0.532; P < .001), and inferior temporal gyrus transcallosal tract FW and baseline diagnosis (β = -0.537; P < .001), all predicting poorer memory performance. White matter microstructural changes, particularly FW, play a critical role in cognitive decline in aging and AD-related cognitive impairment. These findings highlight the importance of FW correction in dMRI studies and highlight the limbic system, especially the cingulum and fornix, as key regions associated with cognitive decline; the interaction models highlight that integrating FW-corrected metrics with other AD biomarkers may further elucidate the biological mechanisms of neurodegeneration in aging.

The study aimed to evaluate and quantify the temporal link between cognitive and functional decline, and assess the impact of the apolipoprotein E4 (APOE-e4) genotype on Alzheimer's disease (AD) progression. A nonlinear mixed-effects Emax model was developed using longitudinal data from 659 patients with dementia due to AD sourced from the Alzheimer's disease neuroimaging initiative (ADNI) database. A cognitive decline model was first built using a cognitive subscale of the AD assessment scale (delayed word recall) as the endpoint, followed by a functional decline model, using the functional assessment questionnaire (FAQ) as the endpoint. Individual and population cognitive decline from the first model drove a functional decline in the second model. The impact of the APOE-e4 genotype status on the dynamics of AD progression was evaluated using the model. Mixed-effects Emax models adequately quantified population average and individual disease trajectories. The model captured a higher initial cognitive impairment and final functional impairment in APOE-e4 carriers than non-carriers. The age at cognitive decline and diagnosis of dementia due to AD was significantly lower in APOE-e4 carriers than that of non-carriers. The average [standard deviation] time shift between cognitive and functional decline, i.e. the time span between half of the maximum cognitive decline and half of the maximum functional decline, was estimated as 1.5 [1.6] years. The present analysis quantifies the temporal link between a cognitive and functional decline in AD progression at the population and individual level, and provides information about the potential benefits of pre-clinical AD treatments on both cognition and function.

To simultaneously examine the influence of functional disability on the development of cognitive impairment and the influence of cognitive status on the development of functional disability over time and compare findings across ethnic groups. A population-based longitudinal study. Galveston County, Texas. Three hundred sixty-five community-dwelling Hispanic Americans, African Americans, and non-Hispanic whites, aged 75 and older. Baseline measures included demographics, self-reported chronic medical conditions, functional disability, and cognitive status. Longitudinal measures included functional decline and cognitive decline. Substantial functional decline was associated with each additional error on the mental status measure; substantial cognitive decline was associated with each additional antecedent disability. These findings were evident across all three ethnic groups, even when taking into account the effects of demographic factors and chronic health conditions, although the specific chronic health conditions that influenced cognitive and functional decline were found to vary across the three ethnic groups. Our findings suggest that, rather than simply being correlated markers of increasing frailty, cognitive and functional decline appear to influence the development of one another. Clinicians need to be aware of these associations, which may affect the direction of preventive care and rehabilitation in the oldest old. Appropriate intervention may result in the prevention or delay of functional disability and cognitive decline. Awareness of the specific chronic health conditions that increase the risk for cognitive or functional decline in various ethnic groups, and the effect of comorbid disease, may also help efforts to prevent decline in older adults.

The aims of this study were to investigate risk factors for cognitive and functional decline among 193 patients with Alzheimer’s disease dementia (AD), and to conduct pharmacogenetic analysis on cerebrovascular metabolism modulators, taking into account APOE haplotypes and the genotypes of ACE, CETP, LDLR and the LXR-β gene. For all patients, later age at AD onset was the most important risk factor for faster cognitive and functional decline, while the late-life coronary heart disease risk was inversely related to cognitive decline only for carriers of APOE4+ haplotypes. Schooling was protective against cognitive decline only for women and carriers of APOE4+ haplotypes, while higher body mass index in late life was protective against cognitive decline only for men. Carriers of the APOE-e4/e4 haplotype had earlier AD onset, whereas genotypes of CETP and LDLR that had traditionally been associated with higher risk of AD were associated with later onset of dementia. Angiotensin-converting enzyme inhibitors caused a 50% reduction in Mini-Mental State Examination score changes, and had better disease-modifying properties than did centrally-acting angiotensin-converting enzyme inhibitors alone. Angiotensin receptor blockers had genetically mediated effects that led to faster cognitive and functional decline, while patients with genetic tendencies towards faster cognitive and functional decline had maximum benefits when they used lipophilic statins, and vice versa.

Whether carotid artery disease is a cause of cognitive impairment in persons who have not had stroke is unknown. If this is the case, diminished performance on the Modified Mini-Mental State Examination should be more common in persons with left carotid artery disease than in those with right carotid artery disease. To determine whether left carotid artery disease is associated with cognitive impairment. Cross-sectional and cohort study. Four U.S. communities participating in the Cardiovascular Health Study. 4006 right-handed men and women 65 years of age or older without history of stroke, transient ischemic attack, or carotid endarterectomy. Internal carotid artery stenosis and intima-media thickness of the common carotid artery were assessed by using duplex ultrasonography. Cognitive impairment was defined as a score less than 80 on the Modified Mini-Mental State Examination, and cognitive decline was defined as an average decrease of more than 1 point annually in Modified Mini-Mental State Examination score during up to 5 years of follow-up. Multivariate logistic regression models were used to estimate the risk for cognitive impairment and decline associated with left internal carotid artery stenosis and intima-media thickness, after adjustment for measures of right-sided disease and risk factors for vascular disease. After adjustment for right-sided stenosis, high-grade (> or =75% narrowing of diameter) stenosis of the left internal carotid artery (32 patients) was associated with cognitive impairment (odds ratio, 6.7 [95% CI, 2.4 to 18.1] compared with no stenosis) and cognitive decline (odds ratio, 2.6 [CI, 1.1 to 6.3]). Intima-media thickness of the left common carotid artery was associated with cognitive impairment and decline in univariate analysis, but this effect did not persist after adjustment. Cognitive impairment and decline are associated with asymptomatic high-grade stenosis of the left internal carotid artery. The persistence of the association after adjustment for right-sided stenosis indicates that the association is not due to underlying vascular risk factors or atherosclerosis in general.

Openness to experience and cognitive functioning and decline in older adults: The mediating role of cognitive reserve

The time course of motor and cognitive decline in older adults and their associations with brain pathologies: a multicohort study

Determining the long-term impact of COVID-19 on cognition is important to inform immediate steps in COVID-19 research and health policy. To investigate the 1-year trajectory of cognitive changes in older COVID-19 survivors. This cohort study recruited 3233 COVID-19 survivors 60 years and older who were discharged from 3 COVID-19-designated hospitals in Wuhan, China, from February 10 to April 10, 2020. Their uninfected spouses (N = 466) were recruited as a control population. Participants with preinfection cognitive impairment, a concomitant neurological disorder, or a family history of dementia were excluded, as well as those with severe cardiac, hepatic, or kidney disease or any kind of tumor. Follow-up monitoring cognitive functioning and decline took place at 6 and 12 months. A total of 1438 COVID-19 survivors and 438 control individuals were included in the final follow-up. COVID-19 was categorized as severe or nonsevere following the American Thoracic Society guidelines. The main outcome was change in cognition 1 year after patient discharge. Cognitive changes during the first and second 6-month follow-up periods were assessed using the Informant Questionnaire on Cognitive Decline in the Elderly and the Telephone Interview of Cognitive Status-40, respectively. Based on the cognitive changes observed during the 2 periods, cognitive trajectories were classified into 4 categories: stable cognition, early-onset cognitive decline, late-onset cognitive decline, and progressive cognitive decline. Multinomial and conditional logistical regression models were used to identify factors associated with risk of cognitive decline. Among the 3233 COVID-19 survivors and 1317 uninfected spouses screened, 1438 participants who were treated for COVID-19 (691 male [48.05%] and 747 female [51.95%]; median [IQR] age, 69 [66-74] years) and 438 uninfected control individuals (222 male [50.68%] and 216 female [49.32%]; median [IQR] age, 67 [66-74] years) completed the 12-month follow-up. The incidence of cognitive impairment in survivors 12 months after discharge was 12.45%. Individuals with severe cases had lower Telephone Interview of Cognitive Status-40 scores than those with nonsevere cases and control individuals at 12 months (median [IQR]: severe, 22.50 [16.00-28.00]; nonsevere, 30.00 [26.00-33.00]; control, 31.00 [26.00-33.00]). Severe COVID-19 was associated with a higher risk of early-onset cognitive decline (odds ratio [OR], 4.87; 95% CI, 3.30-7.20), late-onset cognitive decline (OR, 7.58; 95% CI, 3.58-16.03), and progressive cognitive decline (OR, 19.00; 95% CI, 9.14-39.51), while nonsevere COVID-19 was associated with a higher risk of early-onset cognitive decline (OR, 1.71; 95% CI, 1.30-2.27) when adjusting for age, sex, education level, body mass index, and comorbidities. In this cohort study, COVID-19 survival was associated with an increase in risk of longitudinal cognitive decline, highlighting the importance of immediate measures to deal with this challenge.

Dual decline in gait speed and cognition has been found to be associated with increased dementia risk in previous studies. However, it is unclear if risks are conferred by a decline in domain-specific cognition and gait. To examine associations between dual decline in gait speed and cognition (ie, global, memory, processing speed, and verbal fluency) with risk of dementia. This cohort study used data from older adults in Australia and the US who participated in a randomized clinical trial testing low-dose aspirin between 2010 and 2017. Eligible participants in the original trial were aged 70 years or older, or 65 years or older for US participants identifying as African American or Hispanic. Data analysis was performed between October 2020 and November 2021. Gait speed, measured at 0, 2, 4, and 6 years and trial close-out in 2017. Cognitive measures included Modified Mini-Mental State examination (3MS) for global cognition, Hopkins Verbal Learning Test-Revised (HVLT-R) for memory, Symbol Digit Modalities (SDMT) for processing speed, and Controlled Oral Word Association Test (COWAT-F) for verbal fluency, assessed at years 0, 1, 3, 5, and close-out. Participants were classified into 4 groups: dual decline in gait and cognition, gait decline only, cognitive decline only, and nondecliners. Cognitive decline was defined as membership of the lowest tertile of annual change. Gait decline was defined as a decline in gait speed of 0.05 m/s or greater per year across the study. Dementia (using Diagnostic and Statistical Manual of Mental Disorders [Fourth Edition] criteria) was adjudicated by an expert panel using cognitive tests, functional status, and clinical records. Cox proportional hazard models were used to estimate risk of dementia adjusting for covariates, with death as competing risk. Of 19 114 randomized participants, 16 855 (88.2%) had longitudinal gait and cognitive data for inclusion in this study (mean [SD] age, 75.0 [4.4] years; 9435 women [56.0%], 7558 participants [44.8%] with 12 or more years of education). Compared with nondecliners, risk of dementia was highest in the gait plus HVLT-R decliners (hazard ratio [HR], 24.7; 95% CI, 16.3-37.3), followed by the gait plus 3MS (HR, 22.2; 95% CI, 15.0-32.9), gait plus COWAT-F (HR, 4.7; 95% CI, 3.5-6.3), and gait plus SDMT (HR, 4.3; 95% CI, 3.2-5.8) groups. Dual decliners had a higher risk of dementia than those with either gait or cognitive decline alone for 3MS and HVLT-R. Of domains examined, the combination of decline in gait speed with memory had the strongest association with dementia risk. These findings support the inclusion of gait speed in dementia risk screening assessments.

While body mass index (BMI) is higher in black compared to white persons, little is known about BMI and change in cognition in cohorts with a large proportion of blacks. We examine relations of BMI with decline in global cognition and five cognitive domains, in older blacks and whites, and determine whether relations differ by race. Participants were 2,134 persons without baseline dementia (33% black; 75% women; mean age =77.9 [range 53-100] and education = 14.7 years, Mini-Mental State Examination = 28.0), enrolled in one of two longitudinal, community-based cohort studies of aging (Minority Aging Research Study; Rush Memory and Aging Project). Summary scores of global cognition and five domains were based on 19 neuropsychological tests administered annually. Mixed-effects models, controlling for age, sex, education, and race, were used to examine the relation of baseline BMI to change in cognition. Baseline BMI = 28.4 units (30.3 in blacks [95% confidence interval (CI): 27.2-27.7]; 27.4 in whites [95% CI: 29.8-30.7]). During a mean annual follow-up of 6 years (SD = 4), lower baseline BMI was related to faster decline in global cognition (p = .002), and semantic memory (p < .001) and episodic memory (p = .004), but not working memory, perceptual speed, or visuospatial ability (all p > .08). The relationship of BMI with change in cognition was not modified by race (all p > .09). Late-life lower BMI relates to faster rates of decline in cognition, specifically semantic memory and episodic memory, in both blacks and whites. The effect of BMI on cognition appears to be similar in both racial groups.