Faculty Bibliography

Neurologic conditions are a leading cause of morbidity and mortality within the United States and worldwide. Brain health is a global concern, and the American Academy of Neurology's Brain Health Initiative promises to drive progress in this field over the next decades. Neurologists with detailed training and insight into brain function are uniquely positioned to apply emerging preventive health data to promote healthy brain development and maintain optimal brain function throughout the lifespan. The neurologist's role in promoting brain health is also vital in patients with active neurologic disease, in whom preventive measures may reduce recurrence or slow progression of disease and may enhance quality of life and overall function. In this Emerging Issues in Neurology article, we present the factors that may protect brain function and frame a practical approach to screening assessments and preventive interventions that neurology clinicians may consider to improve the brain health of patients at all life stages.

AIM/OBJECTIVE:The current study aims to investigate the association of serum brain-derived neurotrophic factor (BDNF) levels with symptoms of depression in adults with and without prevalent cardiovascular disease (CVD), an often burdensome comorbidity. METHODS:This cross-sectional study included participants from FHS (Framingham Heart Study) who had available serum BDNF levels. Depressive symptoms were assessed using the Center for Epidemiological Studies-Depression Scale (CES-D) with a score ≥16 indicating mild to moderate and ≥21 severe depression. Participants taking antidepressant medications were excluded from the study. RESULTS:Altogether 3716 FHS participants were included in the final analysis (mean age, 64.3 ± 11.5 years; 55% women). After adjusting for potential confounders, greater BDNF levels were associated with reduced severe depression risk (odds ratio [OR], 0.78 [95% CI, 0.64-0.96]; P = 0.016). Among participants with CVD, greater BDNF levels were related to lower risk of depressive symptoms (CES-D ≥ 16 OR, 0.63 [95% CI, 0.45-0.89], P = 0.008; CES-D ≥ 21 OR, 0.49 [95% CI, 0.31-0.76], P = 0.002). The inverse relationship between BDNF and depressive symptom risk was present in women with CVD (CES-D ≥ 16 OR, 0.63 [95% CI, 0.40-0.99], P = 0.047; CES-D ≥ 21 OR, 0.38 [95% CI, 0.21-0.70], P = 0.002) but not in men. CONCLUSION/CONCLUSIONS:Lower serum BDNF levels are associated with a higher risk of depressive symptoms in CVD, particularly among women. These findings implicate BDNF in the complex biological mechanisms that underlie prior associations observed between CVD and depression. To reduce the burden of depression in the large proportion of midlife and older adults with CVD, a better understanding of how BDNF may modify these pathways is merited.

BACKGROUNDS/BACKGROUND:Sleep disturbances are prevalent among elderly individuals. While polysomnography (PSG) serves as the gold standard for sleep monitoring, its extensive setup and data analysis procedures impose significant costs and time constraints, thereby restricting the long-term application within the general public. Our laboratory introduced an innovative biomarker, utilizing artificial intelligence algorithms applied to PSG data to estimate brain age (BA), a metric validated in cohorts with cognitive impairments. Nevertheless, the potential of exercise, which has been a recognized means of enhancing sleep quality in middle-aged and older adults to reduce BA, remains undetermined. METHODS:We conducted an exploratory study to evaluate whether 12 weeks of moderate-intensity exercise can improve cognitive function, sleep quality, and the brain age index (BAI), a biomarker computed from overnight sleep electroencephalogram (EEG), in physically inactive middle-aged and older adults. Home wearable devices were used to monitor heart rate and overnight sleep EEG over this period. The NIH Toolbox Cognition Battery, in-lab overnight polysomnography, cardiopulmonary exercise testing, and a multiplex cytokines assay were employed to compare pre- and post-exercise brain health, exercise capacity, and plasma proteins. RESULTS:In total, 26 participants completed the initial assessment and exercise program, and 24 completed all procedures. Data are presented as mean [lower 95% CI of mean, upper 95% CI of mean]. Participants significantly increased maximal oxygen consumption (Pre: 21.11 [18.98, 23.23], Post 22.39 [20.09, 24.68], mL/kg/min; effect size: -0.33) and decreased resting heart rate (Pre: 66.66 [63.62, 67.38], Post: 65.13 [64.25, 66.93], bpm; effect size: -0.02) and sleeping heart rate (Pre: 64.55 [61.87, 667.23], Post: 62.93 [60.78, 65.09], bpm; effect size: -0.15). Total cognitive performance (Pre: 111.1 [107.6, 114.6], Post: 115.2 [111.9, 118.5]; effect size: 0.49) was significantly improved. No significant differences were seen in BAI or measures of sleep macro- and micro-architecture. Plasma IL-4 (Pre: 0.24 [0.18, 0.3], Post: 0.33 [0.24, 0.42], pg/mL; effect size: 0.49) was elevated, while IL-8 (Pre: 5.5 [4.45, 6.55], Post: 4.3 [3.66, 5], pg/mL; effect size: -0.57) was reduced. CONCLUSIONS:max) and plasma cytokine profiles. However, we found no measurable effects on sleep architecture or BAI. It remains to be seen whether a study with a larger sample size and more intensive or more prolonged exercise exposure can demonstrate a beneficial effect on sleep quality and brain age.

BACKGROUND/UNASSIGNED:Loneliness has been declared an "epidemic" associated with negative physical, mental, and cognitive health outcomes such as increased dementia risk. Less is known about the relationship between loneliness and advanced neuroimaging correlates of Alzheimer's disease (AD). OBJECTIVE/UNASSIGNED:To assess whether loneliness was associated with advanced neuroimaging markers of AD using neuroimaging data from Framingham Heart Study (FHS) participants without dementia. METHODS/UNASSIGNED:In this cross-sectional observational analysis, we used functional connectivity MRI (fcMRI), amyloid-β (Aβ) PET, and tau PET imaging data collected between 2016 and 2019 on eligible FHS cohort participants. Loneliness was defined as feeling lonely at least one day in the past week. The primary fcMRI marker was Default Mode Network intra-network connectivity. The primary PET imaging markers were Aβ deposition in precuneal and FLR (frontal, lateral parietal and lateral temporal, retrosplenial) regions, and tau deposition in the amygdala, entorhinal, and rhinal regions. RESULTS/UNASSIGNED:Of 381 participants (mean age 58 [SD 10]) who met inclusion criteria for fcMRI analysis, 5% were classified as lonely (17/381). No association was observed between loneliness status and network changes. Of 424 participants (mean age 58 [SD = 10]) meeting inclusion criteria for PET analyses, 5% (21/424) were lonely; no associations were observed between loneliness and either Aβ or tau deposition in primary regions of interest. CONCLUSIONS/UNASSIGNED:In this cross-sectional study, there were no observable associations between loneliness and select fcMRI, Aβ PET, and tau PET neuroimaging markers of AD risk. These findings merit further investigation in prospective studies of community-based cohorts.

Brain health is crucial to optimizing both the function and well-being of every person at each stage of life and is key to both individual and social progress. As a concept, brain health is complex and requires a multidisciplinary collaborative approach between many professional and public organizations to bring into effect meaningful change. Neurologists are uniquely positioned to serve as specialists in brain health and to advance the newly evolving field of preventive neurology, which aims to identify individuals at high risk of brain disorders and other neurologic conditions and offer strategies to mitigate disease emergence or progression. For decades, the American Academy of Neurology (AAN) has demonstrated a commitment to brain health through its public outreach and advocacy. The AAN's Brain Health Initiative launched in 2022 with a strategic plan prioritizing brain health as a key aspect of public engagement and positioning the AAN and neurologists as champions of brain health in collaboration with a broad range of other brain health providers. In this study, we present (1) the new definition of brain health developed by the AAN for neurologists, patients, partners in health care, and the public; (2) the strategic objectives of the AAN Brain Health Initiative; and (3) the AAN Brain Health Platform and Action Plan framework, including key positions on brain health, its 3 ambitious goals, and a national brain health vision. The top-line priorities of the AAN Brain Health Action Plan highlight the need for research, education, public policy, and direct-to-public messaging across the individual's life span and will serve as a catalyst for future cross-disciplinary collaborations within each epoch and longitudinally. The AAN Brain Health Platform is designed to communicate the AAN's vision for brain health and provide a blueprint toward achieving the future of optimal brain health across the life span for all. Through this position statement, we call upon neurologists and other stakeholders in brain health to join our collective efforts to accomplish the ultimate goal of transforming the current trajectory of public health of an increasing burden of neurologic disorders-from both illness and injury-to achieving optimal brain health for all.

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.