Brain health and cognitive functioning can be affected by aging. Exercise is a potentially effective method for promoting "successful brain aging" by improving cardiovascular fitness, brain function and possibly sleep quality. This project will measure the effects of exercise on brain health and attempt to develop a better way to track brain health, by measuring brain activity during sleep.
There exists a critical need to develop biomarkers of brain age and for scientifically proven interventions to improve brain health. Previously, a machine learning algorithm, the Brain Age Index (BAI), was developed to predict brain age (BA) based on 510 features derived from an overnight sleep EEG. The algorithm reports how old an individual's sleeping brain activity "looks", called the "brain age" (BA), and compares this with the chronological age (CA). The difference is the BAI: BAI = BA-CA. Prior work suggests that patients with significant neurological or psychiatric disease or hypertension and diabetes exhibit a mean excess brain age, or "brain age index" (BAI), of 4 and 3.5 years relative to healthy controls. Moreover, it has been shown that high BAI is an independent predictor of mortality. Each extra year of BAI yields a 3.3% relative increase in the risk of death. Work from other groups suggest that exercise is potentially effective for promoting "successful brain aging". Studies of exercise effects on cognition include a metanalysis of 18 prior studies that analyzed the results of exercise on cognitive function in older adults. It was found that aerobic fitness training improved performance across several cognitive domains, including executive function, cognitive control, spatial processing, and processing speed, with an average improvement across studies and across all domains of 0.5 standard deviations relative to controls. Improvement was greatest for executive and control processes. The degree of improvement was also related to the length of the fitness-training intervention, duration of training sessions, and gender (females appeared to benefit more). Studies of exercise effects on brain structure include a prior study that enrolled 35 older adults (14 with Mild Cognitive Impairment, 16 healthy controls) to participate in a 12-week moderate-intensity walking program. Subjects' VO2max increased by an average of 8.49%. The degree to which cardiorespiratory fitness (V̇O2peak) improved due to the intervention was strongly positively correlated with widespread changes in cortical thickness. Taken together, these and other studies suggest that aerobic exercise may be an effective intervention to counteract cortical atrophy due to aging and disease and might provide protection against future cognitive decline in at-risk older adults. This study hypothesizes that cognitive performance will increase after 12 weeks of regular exercise (1a), EEG-based BAI will be lower after 12 weeks of regular exercise (1b), and improvements of cognitive measures are predictable from changes in BAI (1c). Additionally, it is hypothesized that an excess BAI will correlate with poor sleep quality, higher pre-existing comorbidities, poor diet, and small social network (2). Sedentary subjects who undergo the 12-week exercise training program are anticipated to show measurable improvements in EEG-based brain age and cognitive function, and that the degree of improvement will be related to the degree of improvement in aerobic fitness. This study will provide preliminary data to support a larger and longer longitudinal study designed to 1) Clinically validate novel, low-cost, and patient-friendly EEG-based biomarkers of brain health; and 2) Assess the effectiveness of interventions aimed at preserving and improving brain health and ultimately extending healthspan.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
PREVENTION
Masking
NONE
Enrollment
26
See description of study arm.
Massachusetts General Hospital
Boston, Massachusetts, United States
Change from baseline in EEG-based Brain Age (as measured via the Brain Age Index algorithm) after a 12-week aerobic exercise program.
The Brain Age Index (BAI) algorithm reports how old an individual's sleeping brain activity "looks", called the "brain age" (BA), and compares this with the chronological age (CA). The difference is the Brain Age Index (BAI), which is calculated by subtracting the Chronological Age (CA) from the calculated Brain Age (BA): BAI = BA-CA. A higher BAI can reflect worse clinical outcomes (e.g. increase mortality risk) while a lower BAI can reflect better clinical outcomes.
Time frame: Baseline, 12 weeks
Change from baseline in cognitive performance (as measured via the National Institutes of Health (NIH) Toolbox Cognition battery) after a 12-week aerobic exercise program.
The NIH Toolbox Cognition battery is a composite of 7 tests \[Picture Vocabulary (PV), Reading Test (RT), Flanker, Dimensional Change Card Sort (DCCS), Picture Sequence Memory (PSM), List Sorting (LS), Pattern Comparison (PC)\] assessing language, receptive vocabulary, executive function, attention, working/short-term/episodic memory, cognitive flexibility, processing speed, prior education, verbal intelligence. Uncorrected, Age-corrected, and Fully-Corrected scores (mean =100,100,50 and StdDev=15,15,10 respectively) are calculated for each test. Composite scores are given for Fluid, Crystallized, and overall Cognitive Function. The Fluid Composite Score is derived by averaging the std. scores of the Flanker, DCCS, PSM, LS and PC tests. The Crystallized Composite Score is derived by averaging the std. scores of the PV \& RT. The Cognitive Function Composite Score is derived by averaging the Fluid \& Crystallized std. scores. Higher scores indicate higher levels of cognitive functioning.
Time frame: Baseline, 12 weeks
Association between brain age index (BAI) and sleep quality (as measured via a home sleep EEG monitoring device).
EEG signals will be collected via a home sleep monitoring device (Prodigy Sleep System) - a portable, wireless, forehead-mounted monitor that utilizes frontal electrodes. From the EEG, sleep depth and fragmentation (markers of sleep quality) will be measured.
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Time frame: Weeks 1-12
Association between brain age index (BAI) and sleep quality (as measured via respiration).
Breathing patterns will be measured via a wearable respiratory sensor device (AirGo) as they vary with sleep stage and depth (markers of sleep quality). The Airgo device measures the expansion and recoil of the patient's chest.
Time frame: Weeks 1-12
Association between brain age index (BAI) and pre-existing co-morbidity (as measured via the Charlson Co-morbidity Index).
The Charlson Co-morbidity Index (CCI) assesses 17 categories that together evaluates a patient's ten-year survival. Each co-morbidity category has an associated weight (from 1 to 6), based on the adjusted risk of mortality or resource use, and the sum of all the weights result in a single co-morbidity score for a patient. A score of zero indicates that no co-morbidities were found. The higher the score, the more likely the predicted outcome will result in mortality or higher resource use.
Time frame: Baseline
Association between brain age index (BAI) and depression (as measured via the Patient Health Questionnaire-2).
The Patient Health Questionnaire scale (PHQ-2) is a 2-item screening measure which ranges from a score of 0 to 6. The higher the score, the more likely there is an underlying depressive disorder.
Time frame: Baseline
Association between brain age index (BAI) and anxiety (as measured via the Generalized Anxiety Disorder Questionnaire-2).
The Generalized Anxiety Disorder (GAD-2) is a 2-item screening measure which ranges from a score of 0 to 6. The higher the score, the more likely there is an underlying anxiety disorder.
Time frame: Baseline
Association between brain age index (BAI) and diet (as measured via the 14-Q Mediterranean Diet Questionnaire).
The 14-item Mediterranean Diet Adherence Screener (MEDAS) is a brief questionnaire assessing adherence to the Mediterranean diet. It consists of a total of 14 questions that characterize key food groups commonly consumed as part of a traditional Mediterranean diet (12 questions about frequency of food consumption; two questions about food intake habits). Answers are summed to a total Mediterranean diet score ranging from 0 to 14, with higher scores indicating greater adherence.
Time frame: Baseline
Association between brain age index (BAI) and social network (as measured via the Social Network Index).
The Cohen's Social Network Index (SNI) assesses the size, diversity, and complexity of a respondent's current social network across 12 types of social relationships. Social network size measures the total number of people with whom the patient has regular contact (at least once every 2 weeks) and is computed by summing across the 12 roles. Social network diversity measures the number of social roles in which the patient has regular with at least 1 person (range 0-12). Social network complexity measures the number of different network domains in which a patient is active (range 0-8). Higher scores represent a larger, more diverse and complex social network.
Time frame: Baseline
Association between brain age index (BAI) and social network (as measured via the University of California, Los Angeles Loneliness Scale).
The University of California, Los Angeles (UCLA) Loneliness Scale is a 20-item scale designed to measure one's subjective feelings of loneliness as well as feelings of social isolation (range 20-80). Higher scores indicate greater degrees of loneliness.
Time frame: Baseline
Association between brain age index (BAI) and socioeconomic status (as measured via The Hollingshead Four Factor Index of Social Status).
The Hollingshead Four Factor Index of Social Status (Hollingshead, 1975) use education, occupation, sex, and marital status to determine a family's composite social status. Education scores (range 1-7), occupation codes (range 1-9) are weighted by 3 and 5 respectively. Raw scores range from 8 to 66, with higher scores reflecting higher socioeconomic status.
Time frame: Baseline