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Background: Coupling digital technology with traditional neuropsychological test performance allows collection of high-precision metrics that can clarify and/or define underlying constructs related to brain and cognition.Objective: To identify graphomotor and information processing trajectories using a digitally administered version of the Digit Symbol Substitution Test (DSST).Methods: A subset of Long Life Family Study participants (n = 1,594) completed the DSST. Total time to draw each symbol was divided into 'writing' and non-writing or 'thinking' time. Bayesian clustering grouped participants by change in median time over intervals of eight consecutively drawn symbols across the 90 s test. Clusters were characterized based on sociodemographic characteristics, health and physical function data, APOE genotype, and neuropsychological test scores.Results: Clustering revealed four 'thinking' time trajectories, with two clusters showing significant changes within the test. Participants in these clusters obtained lower episodic memory scores but were similar in other health and functional characteristics. Clustering of 'writing' time also revealed four performance trajectories where one cluster of participants showed progressively slower writing time. These participants had weaker grip strength, slower gait speed, and greater perceived physical fatigability, but no differences in cognitive test scores.Conclusion: Digital data identified previously unrecognized patterns of 'writing' and 'thinking' time that cannot be detected without digital technology. These patterns of performance were differentially associated with measures of cognitive and physical function and may constitute specific neurocognitive biomarkers signaling the presence of subtle to mild dysfunction. Such information could inform the selection and timing of in-depth neuropsychological assessments and help target interventions. [ABSTRACT FROM AUTHOR]

Introduction: Dependence in Alzheimer disease has been proposed as a holistic, transparent, and meaningful representation of disease severity. Modeling clusters in dependence trajectories can help understand changes in disease course and care cost over time.Methods: Sample consisted of 199 initially community-living patients with probable Alzheimer disease recruited from 3 academic medical centers in the United States followed for up to 10 years and had ≥2 Dependence Scale recorded. Nonparametric K-means cluster analysis for longitudinal data (KmL) was used to identify dependence clusters. Medicare expenditures data (1999-2010) were compared between clusters.Results: KmL identified 2 distinct Dependence Scale clusters: (A) high initial dependence, faster decline, and (B) low initial dependence, slower decline. Adjusting for patient characteristics, 6-month Medicare expenditures increased over time with widening between-cluster differences.Discussion: Dependence captures dementia care costs over time. Better characterization of dependence clusters has significant implications for understanding disease progression, trial design and care planning. [ABSTRACT FROM AUTHOR]

Maintaining good cognitive function at older age is important, but our knowledge of patterns and predictors of cognitive aging is still limited. We used Bayesian model-based clustering to group 5064 participants of the Long Life Family Study (ages 49–110 years) into clusters characterized by distinct trajectories of cognitive change in the domains of episodic memory, attention, processing speed, and verbal fluency. For each domain, we identified 4 or 5 large clusters with representative patterns of change ranging from rapid decline to exceptionally slow change. We annotated the clusters by their correlation with genetic and molecular biomarkers, non-genetic risk factors, medical history, and other markers of aging to discover correlates of cognitive changes and neuroprotection. The annotation analysis discovered both predictors of multi-domain cognitive change such as gait speed and predictors of domain-specific cognitive change such as IL6 and NTproBNP that correlate only with change of processing speed or APOE genotypes that correlate only with change of processing speed and logical memory. These patterns also suggest that cognitive decline starts at young age and that maintaining good physical function correlates with slower cognitive decline. To better understand the agreement of cognitive changes across multiple domains, we summarized the results of the cluster analysis into a score of cognitive function change. This score showed that extreme patterns of change affecting multiple cognitive domains simultaneously are rare in this study and that specific signatures of biomarkers of inflammation and metabolic disease predict severity of cognitive changes. The substantial heterogeneity of change patterns within and between cognitive domains and the net of correlations between patterns of cognitive aging and other aging traits emphasizes the importance of measuring a wide range of cognitive functions and the need for studying cognitive aging in concert with other aging traits. [ABSTRACT FROM AUTHOR]

Objectives The main objective of this study was to estimate effects of dementia on Medicaid expenditures in an ethnically diverse community. Methods The sample included 1,211 Medicare beneficiaries who did not have any Medicaid coverage and 568 who additionally had full Medicaid coverage enrolled in the Washington Heights-Inwood Columbia Aging Project (WHICAP), a multiethnic, population-based, prospective study of cognitive aging in northern Manhattan (1999–2010). Individuals' dementia status was determined using a rigorous clinical protocol. Relationship between dementia and Medicaid coverage and expenditures were estimated using a two-part model. Results In participants who had full Medicaid coverage, average annual Medicaid expenditures were substantially higher for those with dementia than those without dementia ($50,270 vs. $21,966, p <.001), but Medicare expenditures did not differ by dementia status ($8,458 vs. $9,324, p =.19). In participants who did not have any Medicaid coverage, average annual Medicare expenditures were substantially higher for those with dementia than those without dementia ($12,408 vs. $8,113, p =.02). In adjusted models, dementia was associated with a $6,278 increase in annual Medicaid spending per person after controlling for other characteristics. Discussion Results highlight Medicaid's contribution to covering the cost of dementia care in addition to Medicare. Studies that do not include Medicaid are unlikely to accurately reflect the true cost of dementia. [ABSTRACT FROM AUTHOR]

Background: Fatigability is a construct that measures whole-body tiredness anchored to activities of a fixed intensity and duration; little is known about its epidemiology and heritability.Methods: Two generations of family members enriched for exceptional longevity and their spouses were enrolled (2006-2009) in the Long Life Family Study (LLFS). At Visit 2 (2014-2017, N = 2,355) perceived physical fatigability was measured using the 10-item self-administered Pittsburgh Fatigability Scale (PFS), along with demographic, medical, behavioral, physical, and cognitive risk factors.Results: Residual genetic heritability of fatigability was 0.263 (p = 6.6 × 10-9) after adjustment for age, sex, and field center. PFS physical scores (mean ± SD) and higher physical fatigability prevalence (% PFS ≥ 15) were greater with each age strata: 60-69 (n = 1,009, 11.0 ± 7.6, 28%), 70-79 (n = 847, 12.5 ± 8.1, 37%), 80-89 (n = 253, 19.3 ± 9.9, 65.2%), and 90-108 (n = 266, 28.6 ± 9.8, 89.5%), p < .0001, adjusted for sex, field center, and family relatedness. Women had a higher prevalence of perceived physical fatigability compared to men, with the largest difference in the 80-89 age strata, 74.8% versus 53.5%, p < .0001. Those with greater body mass index, worse physical and cognitive function, and lower physical activity had significantly higher perceived physical fatigability.Conclusions: Perceived physical fatigability is highly prevalent in older adults and strongly associated with age. The family design of LLFS allowed us to estimate the genetic heritability of perceived physical fatigability. Identifying risk factors associated with higher perceived physical fatigability can inform the development of targeted interventions for those most at risk, including older women, older adults with depression, and those who are less physically active. [ABSTRACT FROM AUTHOR]

Background: The Long Life Family Study (LLFS) enrolled families exhibiting exceptional longevity. The goal of this article was to determine the prevalence and predictors of remaining independent after 7 years in the oldest generation.Methods: We examined 7-year change in physical (free of activities of daily living difficulty), cognitive (Mini-Mental State Examination score ≥ 24), and overall independence (physically/cognitively independent) in adults aged 90.3 ± 6.3 from LLFS's oldest generation. Potential predictors (n = 28) of remaining independent included demographics, diseases, biomarkers, anthropometrics, and physical and cognitive performance tasks and were determined using generalized estimating equations (α: p < .05). This was a discovery/exploratory analysis, so no multiple testing correction was employed and the results require independent replication.Results: At baseline (n = 1442), 67.3%, 83.8%, and 79.7% were overall, physically, and cognitively independent, respectively. After 7 years, 66% died, 7.5% were lost to follow-up, and the prevalence of overall independence decreased to 59.1% in survivors (-8.2%, 95% confidence interval: -14.1%, 2.2%). Of those with baseline independence, 156/226 (69.0%) remained independent. Predictors of remaining physically independent included younger age, better Short Physical Performance Battery score and lung function, smaller waist circumference, and lower soluble receptor for advanced glycation end-product levels (p < .05). Predictors of remaining cognitively independent included no cancer history, better Digit Symbol Substitution Test performance, and higher body weight (p < .05).Conclusions: The prevalence of independence decreased by only 8.2% after 7 years, demonstrating the close correspondence between disability and mortality. Further, despite a mean baseline age of 90 years, a large proportion of survivors remained independent, suggesting this exceptional subgroup may harbor protective mechanisms. [ABSTRACT FROM AUTHOR]

Objectives: Patients with essential tremor exhibit heterogeneous cognitive functioning. Although the majority of patients fall under the broad classification of cognitively "normal," essential tremor is associated with increased risk for mild cognitive impairment and dementia. It is possible that patterns of cognitive performance within the wide range of normal functioning have predictive utility for mild cognitive impairment or dementia. These cross-sectional analyses sought to determine whether cognitive patterns, or "clusters," could be identified among individuals with essential tremor diagnosed as cognitively normal. We also determined whether such clusters, if identified, were associated with demographic or clinical characteristics of patients. Methods: Elderly subjects with essential tremor (age >55 years) underwent comprehensive neuropsychological testing. Domain means (memory, executive function, attention, visuospatial abilities, and language) from 148 individuals diagnosed as cognitively normal were partitioned using k -means cluster analysis. Individuals in each cluster were compared according to cognitive functioning (domain means and test scores), demographic factors, and clinical variables. Results: There were three clusters. Cluster 1 (n = 64) was characterized by comparatively low memory scores (p <.001), Cluster 2 (n = 39) had relatively low attention and visuospatial scores (p <.001), and Cluster 3 (n = 45) exhibited consistently high performance across all domains. Cluster 1 had lower Montreal Cognitive Assessment scores and reported more prescription medication use and lower balance confidence. Conclusions: Three patterns of cognitive functioning within the normal range were evident and tracked with certain clinical features. Future work will examine the extent to which such patterns predict conversion to mild cognitive impairment and/or dementia. [ABSTRACT FROM AUTHOR]