Faculty Bibliography

BACKGROUND AND OBJECTIVE/OBJECTIVE:Loneliness is common and its prevalence is rising. The relationship of loneliness with subsequent dementia and the early preclinical course of Alzheimer disease and related dementia (ADRD) remains unclear. Thus, the primary objective of this study was to determine the association of loneliness with 10-year all-cause dementia risk and early cognitive and neuroanatomic imaging markers of ADRD vulnerability. METHODS:Retrospective analysis of prospectively collected data from the population-based Framingham Study cohorts (09/09/1948-12/31/2018). Eligible participants had loneliness assessed and were dementia-free at baseline. Loneliness was recorded using the Center for Epidemiologic Studies Depression Scale; defined conservatively as feeling lonely ≥3 days in the past week. The main outcomes were incident dementia over a 10-year period, cognition, and MRI brain volumes and white-matter injury. RESULTS:Of 2308 participants (mean age, 73 [SD, 9] years; 56% women) who met eligibility in the dementia sample, 14% (329/2308) developed dementia; 6% (144/2308) were lonely. Lonely (versus not lonely) adults had higher 10-year dementia risk (age-, sex-, and education-adjusted hazard ratio, 1.54; 95% CI, 1.06-2.24). Lonely participants younger than age 80 without APOE ε4 alleles had a three-fold greater risk (adjusted hazard ratio, 3.03; 95% CI, 1.63-5.62). Among 1875 persons without dementia who met eligibility in the cognition sample (mean age, 62 [SD, 9] years; 54% women), loneliness associated with poorer executive function, lower total cerebral volume, and greater white-matter injury. DISCUSSION/CONCLUSIONS:Over 10 years of close clinical dementia surveillance in this cohort study, loneliness was associated with increased dementia risk; this tripled in adults whose baseline risk would otherwise be relatively low based on age and genetic risk, representing a majority of the US population. Loneliness was also associated with worse neurocognitive markers of ADRD vulnerability, suggesting an early pathogenic role. These findings may have important clinical and public health implications given observed loneliness trends. CLASSIFICATION OF EVIDENCE/METHODS:This study provides Class I evidence that loneliness increases the 10-year risk of developing dementia.

Importance/UNASSIGNED:Cognitive resilience refers to the general capacity of cognitive processes to be less susceptible to differences in brain structure from age- and disease-related changes. Studies suggest that supportive social networks reduce Alzheimer disease and related disorder (ADRD) risk by enhancing cognitive resilience, but data on specific social support mechanisms are sparse. Objective/UNASSIGNED:To examine the association of individual forms of social support with a global neuroanatomical measure of early ADRD vulnerability and cognition. Design, Setting, and Participants/UNASSIGNED:This retrospective cross-sectional analysis used prospectively collected data from Framingham Study participants without dementia, stroke, or other neurological conditions who underwent brain magnetic resonance imaging and neuropsychological testing at the same visit. Data from this large, population-based, longitudinal cohort were collected from June 6, 1997, to December 13, 1999 (original cohort), and from September 11, 1998, to October 26, 2001 (offspring cohort). Data were analyzed from May 22, 2017, to June 1, 2021. Exposures/UNASSIGNED:Total cerebral volume and, as a modifying exposure variable, self-reported availability of 5 types of social support measured by the Berkman-Syme Social Network Index. Main Outcomes and Measures/UNASSIGNED:The primary outcome was a global measure of cognitive function. Cognitive resilience was defined as the modification of total cerebral volume's association with cognition, such that smaller β estimates (presented in SD units) indicate greater cognitive resilience (ie, better cognitive performance than estimated by lower total cerebral volume). Results/UNASSIGNED:The study included 2171 adults (164 in the original cohort and 2007 in the offspring cohort; mean [SD] age, 63 [10] years; 1183 [54%] female). High listener availability was associated with greater cognitive resilience (β = 0.08, P < .001) compared with low listener availability (β = 0.20, P = .002). Overall findings persisted after adjustment for potential confounders. Other forms of social support were not significant modifiers (advice: β = -0.04; P = .40 for interaction; love-affection: β = -0.07, P = .28 for interaction; emotional support: β = -0.02, P = .73 for interaction; and sufficient contact: β = -0.08; P = .11 for interaction). Conclusions and Relevance/UNASSIGNED:The results of this cross-sectional cohort study suggest that social support in the form of supportive listening is associated with greater cognitive resilience, independently modifying the association between lower total cerebral volume and poorer cognitive function that would otherwise indicate increased ADRD vulnerability at the preclinical stage. A refined understanding of social support mechanisms has the potential to inform strategies to reduce ADRD risk and enhance cognitive resilience.

Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the "brain age index" (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed "sleep cognitive indices" (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined: total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving). We show that SCI decoded information about total cognition (Pearson's r = 0.37) and fluid cognition (Pearson's r = 0.56), while BAI correlated only with crystallized cognition (Pearson's r = - 0.25). Overall, these sleep EEG-derived biomarkers may provide accessible and clinically meaningful indicators of neurocognitive health.

OBJECTIVE:To calibrate cognitive assessment data across multiple waves of the Framingham Heart Study (FHS), addressing study design considerations, ceiling effects, and measurement precision. METHOD/METHODS:FHS participants completed several cognitive assessments including screening instruments and more comprehensive batteries at different study visits. We used expert opinion to assign each cognitive test item to a single domain-memory, executive function, language, visuospatial abilities, or none of the above. As part of a larger cross-study harmonization effort, we calibrated each domain separately using bifactor confirmatory factor analysis (CFA) models, incorporating item parameters for anchor items previously calibrated from other studies and freely estimating item parameters for FHS-specific items. We obtained scores and standard errors (SEs) for each participant at each study visit. We addressed psychometric considerations of ceiling effects and measurement precision. RESULTS:Overall, memory domain scores were the most precisely estimated. Scores for all domains from visits where the Mini-Mental State Examination (MMSE) was the only test administered were imprecisely estimated and suffered from ceiling effects. Scores from visits with a more extensive battery were estimated more precisely and better differentiated between ability levels. CONCLUSIONS:The harmonized and calibrated cognitive data from the FHS should prove useful for future analyses examining cognition and cognitive decline. They will be of particular interest when combining FHS with other studies that have been similarly calibrated. Researchers should be aware of varying levels of measurement precision and the possibility of ceiling effects in their planned analyses of data from the FHS and similar studies. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Background Vascular function is compromised in Alzheimer disease (AD) years before amyloid and tau pathology are detected and a substantial body of work shows abnormal platelet activation states in patients with AD. The aim of our study was to investigate whether platelet function in middle age is independently associated with future risk of AD. Methods and Results We examined associations of baseline platelet function with incident dementia risk in the community-based FHS (Framingham Heart Study) longitudinal cohorts. The association between platelet function and risk of dementia was evaluated using the cumulative incidence function and inverse probability weighted Cox proportional cause-specific hazards regression models, with adjustment for demographic and clinical covariates. Platelet aggregation response was measured by light transmission aggregometry. The final study sample included 1847 FHS participants (average age, 53.0 years; 57.5% women). During follow-up (median, 20.5 years), we observed 154 cases of incident dementia, of which 121 were AD cases. Results from weighted models indicated that platelet aggregation response to adenosine diphosphate 1.0 µmol/L was independently and positively associated with dementia risk, and it was preceded in importance only by age and hypertension. Sensitivity analyses showed associations with the same directionality for participants defined as adenosine diphosphate hyper-responders, as well as the platelet response to 0.1 µmol/L epinephrine. Conclusions Our study shows individuals free of antiplatelet therapy with a higher platelet response are at higher risk of dementia in late life during a 20-year follow-up, reinforcing the role of platelet function in AD risk. This suggests that platelet phenotypes may be associated with the rate of dementia and potentially have prognostic value.

STUDY OBJECTIVES/OBJECTIVE:Alterations in sleep spindles have been linked to cognitive impairment. This finding has contributed to a growing interest in identifying sleep-based biomarkers of cognition and neurodegeneration, including sleep spindles. However, flexibility surrounding spindle definitions and algorithm parameter settings present a methodological challenge. The aim of this study was to characterize how spindle detection parameter settings influence the association between spindle features and cognition and to identify parameters with the strongest association with cognition. METHODS:Adult patients (n=167, 49 ± 18 years) completed the NIH Toolbox Cognition Battery after undergoing overnight diagnostic polysomnography recordings for suspected sleep disorders. We explored 1000 combinations across seven parameters in Luna, an open-source spindle detector, and used four features of detected spindles (amplitude, density, duration, and peak frequency) to fit linear multiple regression models to predict cognitive scores. RESULTS:Spindle features (amplitude, density, duration, and mean frequency) were associated with the ability to predict raw fluid cognition scores (r=0.503) and age-adjusted fluid cognition scores (r=0.315) with the best spindle parameters. Fast spindle features generally showed better performance relative to slow spindle features. Spindle features weakly predicted total cognition and poorly predicted crystallized cognition regardless of parameter settings. CONCLUSION/CONCLUSIONS:Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.

BACKGROUND:As the Hispanic/Latino (HL) population grows, so too does the need for HL family caregivers for persons with dementia. HL caregivers tend to have less education, lower health literacy, and lower income, each uniquely compounding burden. Research is needed to appropriately tailor interventions for this population. OBJECTIVE:A systematic review and meta-analysis was conducted to 1) provide an updated review of non-pharmacologic intervention studies for HL dementia caregivers, 2) characterize promising interventions, and 3) highlight opportunities for future research. METHODS:Databases were searched for articles evaluating non-pharmacologic interventions for HL dementia caregivers. Studies were excluded if target populations did not include HLs or if no intervention was delivered. Data were extracted and random effects meta-analysis was performed on two primary outcomes: caregiver depression and burden. Effect sizes were calculated as pre- and post-intervention standardized mean differences (SMD), and further depression subgroup meta-analysis was performed. Other secondary outcome measures (e.g., perceived social support, caregiver knowledge, anxiety) were evaluated qualitatively. RESULTS:Twenty-three studies were identified. Most included multiple components pertaining to psychosocial support, caregiver education, and community resource facilitation. Many studies were successful in improving caregiver outcomes, though intervention design varied. Meta-analysis revealed minimal to moderate heterogeneity and small effect size in improving depressive symptoms (SMD = -0.31, 95% CI -0.46 to -0.16; I2 = 50.16%) and burden (SMD = -0.28, 95% CI -0.37 to -0.18; I2 = 11.06%). CONCLUSION/CONCLUSIONS:Although intervention components varied, many reported outcome improvements. Future studies may benefit from targeting physical health, addressing sociocultural and economic contexts of caregivers, and leveraging technology.

Social distancing has been a critical public health measure for the COVID-19 pandemic, yet a long history of research strongly suggests that loneliness and social isolation play a major role in several cognitive health issues. What is the true severity and extent of risks involved and what are potential approaches to balance these competing risks? This review aimed to summarize the neurological context of social isolation and loneliness in population health and the long-term effects of social distancing as it relates to neurocognitive aging, health, and Alzheimer's disease and related dementias. The full scope of the underlying causal mechanisms of social isolation and loneliness in humans remains unclear partly because its study is not amenable to randomized controlled trials; however, there are many detailed experimental and observational studies that may provide a hypothesis-generating theoretical framework to better understand the pathophysiology and underlying neurobiology. To address these challenges and inform future studies, we conducted a topical review of extant literature investigating associations of social isolation and loneliness with relevant biological, cognitive, and psychosocial outcomes, and provide recommendations on how to approach the need to fill key knowledge gaps in this important area of research.