Examining cross-sectional and longitudinal relationships between multidomain physical fitness metrics, education, and cognition in Black older adults.

A limited number of studies examine cognitive aging in Black or African American older adults. The purpose of this study was to explore the relationship between health-related fitness metrics, education, and cognition at baseline and over a 4-year follow-up in a sample of 321 Black or African American older adults in the Health and Retirement Study (HRS). Physical fitness was assessed with measures of gait speed, peak expiratory flow, grip strength, and body mass index. Global cognition was assessed with an adapted version of the Telephone Interview for Cognitive Status (TICS). Analyses of relative importance and hierarchical multiple regression were used to examine baseline cross-sectional relationships. Multiple logistic regression was used to examine prospective relationships with longitudinal cognitive status. Education was the strongest predictor of global cognition at baseline and follow-up. More years of education significantly increased the odds of maintaining cognitive status at 4-year follow-up. After accounting for education, gait speed was independently associated with baseline cognitive performance and accounted for additional variance. Grip strength, peak expiratory flow, and body mass index were not significantly associated with cognition. The results indicated that modifiable variables, including years of educational attainment and gait speed, were more strongly associated with global cognition than other modifiable variables including body mass index, grip strength, and peak expiratory flow. The lack of observed associations between other fitness variables and cognition may be attributable to the brief assessment methods implemented, which was necessitated by the large-scale, epidemiological approach of the HRS.

Partial Least Squares Regression Analysis of Alzheimer's Disease Biomarkers, Modifiable Health Variables, and Cognitive Change in Older Adults with Mild Cognitive Impairment.

BACKGROUND: Prior work has shown that certain modifiable health, Alzheimer's disease (AD) biomarker, and demographic variables are associated with cognitive performance. However, less is known about the relative importance of these different domains of variables in predicting longitudinal change in cognition. OBJECTIVE: Identify novel relationships between modifiable physical and health variables, AD biomarkers, and slope of cognitive change over two years in a cohort of older adults with mild cognitive impairment (MCI). METHODS: Metrics of cardiometabolic risk, stress, inflammation, neurotrophic/growth factors, and AD pathology were assessed in 123 older adults with MCI at baseline from the Alzheimer's Disease Neuroimaging Initiative (mean age = 73.9; SD = 7.6; mean education = 16.0; SD = 3.0). Partial least squares regression (PLSR)-a multivariate method which creates components that best predict an outcome-was used to identify whether these physiological variables were important in predicting slope of change in episodic memory or executive function over two years. RESULTS: At two-year follow-up, the two PLSR models predicted, respectively, 20.0% and 19.6% of the variance in change in episodic memory and executive function. Baseline levels of AD biomarkers were important in predicting change in both episodic memory and executive function. Baseline education and neurotrophic/growth factors were important in predicting change in episodic memory, whereas cardiometabolic variables such as blood pressure and cholesterol were important in predicting change in executive function. CONCLUSION: These data-driven analyses highlight the impact of AD biomarkers on cognitive change and further clarify potential domain specific relationships with predictors of cognitive change.

Individual Variability in Performance Reflects Selectivity of the Multiple Demand Network among Children and Adults.

Executive function (EF) is essential for humans to effectively engage in cognitively demanding tasks. In adults, EF is subserved by frontoparietal regions in the multiple demand (MD) network, which respond to various cognitively demanding tasks. However, children initially show poor EF and prolonged development. Do children recruit the same network as adults? Is it functionally and connectionally distinct from adjacent language cortex, as in adults? And is this activation or connectivity dependent on age or ability? We examine task-dependent (spatial working memory and passive language tasks) and resting state functional data in 44 adults (18-38 years, 68% female) and 37 children (4-12 years, 35% female). Subject-specific functional ROIs (ss-fROIs) show bilateral MD network activation in children. In both children and adults, these MD ss-fROIs are not recruited for linguistic processing and are connectionally distinct from language ss-fROIs. While MD activation was lower in children than in adults (even in motion- and performance-matched groups), both showed increasing MD activation with better performance, especially in right hemisphere ss-fROIs. We observe this relationship even when controlling for age, cross-sectionally and in a small longitudinal sample of children. These data suggest that the MD network is selective to cognitive demand in children, is distinct from adjacent language cortex, and increases in selectivity as performance improves. These findings show that neural structures subserving domain-general EF emerge early and are sensitive to ability even in children. This research advances understanding of how high-level human cognition emerges and could inform interventions targeting cognitive control.SIGNIFICANCE STATEMENT This study provides evidence that young children already show differentiated brain network organization between regions that process cognitive demand and language. These data support the hypothesis that children recruit a similar network as adults to process cognitive demand; and despite immature characteristics, children's selectivity looks more adult-like as their executive function ability increases. Mapping early stages of network organization furthers our understanding of the functional architecture underlying domain-general executive function. Determining typical variability underlying cognitive processing across developmental periods helps establish a threshold for executive dysfunction. Early markers of dysfunction are necessary for effective early identification, prevention, and intervention efforts for individuals struggling with deficits in processing cognitive demand.

Partial Least Squares Analysis of Alzheimer's Disease Biomarkers, Modifiable Health Variables, and Cognition in Older Adults with Mild Cognitive Impairment.

OBJECTIVES: To identify novel associations between modifiable physical and health variables, Alzheimer's disease (AD) biomarkers, and cognitive function in a cohort of older adults with Mild Cognitive Impairment (MCI). METHODS: Metrics of cardiometabolic risk, stress, inflammation, neurotrophic/growth factors, AD, and cognition were assessed in 154 MCI participants (Mean age = 74.1 years) from the Alzheimer's Disease Neuroimaging Initiative. Partial Least Squares analysis was employed to examine associations among these physiological variables and cognition. RESULTS: Latent variable 1 revealed a unique combination of AD biomarkers, neurotrophic/growth factors, education, and stress that were significantly associated with specific domains of cognitive function, including episodic memory, executive function, processing speed, and language, representing 45.2% of the cross-block covariance in the data. Age, body mass index, and metrics tapping basic attention or premorbid IQ were not significant. CONCLUSIONS: Our data-driven analysis highlights the significant relationships between metrics associated with AD pathology, neuroprotection, and neuroplasticity, primarily with tasks tapping episodic memory, executive function, processing speed, and verbal fluency rather than more basic tasks that do not require mental manipulation (basic attention and vocabulary). These data also indicate that biological metrics are more strongly associated with episodic memory, executive function, and processing speed than chronological age in older adults with MCI.