Association of Modifiable Lifestyle Factors With Cortical Amyloid Burden and Cerebral Glucose Metabolism in Older Adults With Mild Cognitive Impairment

Key Points Question Are modifiable lifestyle factors associated with cortical amyloid burden or cerebral glucose metabolism in older adults with mild cognitive impairment? Findings This cohort study included 118 older adults with mild cognitive impairment and found that total sleep time was associated with cerebral glucose metabolism after adjusting for covariates and false-discovery rate correction. Meaning In this study, the association of sleep duration with brain function was confirmed in older adults with mild cognitive impairment, thereby strengthening the potential of sleep as an evidence-based intervention for preventing cognitive impairment.


Introduction
Mild cognitive impairment (MCI) is a high-risk factor for dementia 1 and a major public health issue worldwide, posing a serious social and financial burden on patients and caregivers. 2 Although the prevalence of late-life dementia is expected to increase, effective disease-modifying treatments are currently unavailable. Therefore, it is important to elucidate risk or protective factors associated with the cortical amyloid burden or brain function to delay cognitive impairment. Potentially modifiable risk factors for dementia have been identified and include low levels of education, vascular risk factors, lifestyle factors, and hearing loss. [2][3][4][5] In particular, physical inactivity, sleep disturbance, social isolation, and depression are important risk factors for late-life cognitive impairment. [5][6][7][8] Most observational studies have used self-report questionnaires that are of limited utility owing to their poor reliability and consistency, which is attributed to recall bias or misclassification, particularly among older people or those with MCI. 8,9 Wearable sensors have been used to evaluate lifestyle factors, such as physical activity and sleep, in large epidemiological studies. [10][11][12][13][14] Wearable sensors are noninvasive and cost-effective and can objectively measure total daily movement and sleep without recall bias. We have previously reported an association between objectively measured walking steps, conversation time, and global cognitive function in community-dwelling older adults, 14 based on which we hypothesized that these lifestyle factors were associated with cortical amyloid burden or brain function. To our knowledge, only a few studies have examined the association between objectively measured lifestyle factors and the results of positron emission tomography (PET) imaging, including carbon-11 labeled Pittsburgh compound B (PiB)-PET and fluorine-18 fluorodeoxyglucose (FDG)-PET in older adults with MCI. Therefore, the present study aimed to use wearable sensors to explore whether modifiable lifestyle factors are associated with cortical amyloid burden and cerebral glucose metabolism in community-dwelling older adults with MCI.

Ethics
This prospective cohort study was conducted in accordance with the Declaration of Helsinki 15 and approved by the local ethics committee of Oita University Hospital. Written informed consent was obtained from all participants. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Participants
This was a prospective cohort study initiated in 2015 that examined risk and protective lifestyle factors for dementia among older adults in Usuki, Oita Prefecture, Japan. Adults aged 65 years and older account for approximately 38% of the Usuki population. Public servants recruited adults without dementia via public relations initiatives. The inclusion criteria were as follows: (1) aged 65 years and older; (2) living in Usuki; (3) physically and psychologically healthy; (4) without dementia; and (5) independent function in activities of daily living. Participants were required to wear a wristband sensor for a mean of 7 to 14 days per measurement period. Measurement of lifestyle factors repeated every 3 months for 1 year (ie, 4 times per year for 56 days during the study period) to eliminate measurement errors owing to seasonal differences in lifestyle. 16 [11][12] years) satisfied the criteria and had valid sensing data for analysis. 14 Of 855 adults, 118 (13.8%) who were diagnosed with MCI and received PiB-PET and FDG-PET were recruited to this study. The diagnosis of MCI was made according to previous studies, 17 as follows: (1) subjective memory complaints and objective memory impairment, (2) Clinical Dementia Rating score of 0.5, and (3) absence of significant impairment in cognitive function or activities of daily living.

Wearable Sensor Data
All participants wore a wristband sensor (Silmee W20, TDK Corporation) day and night except while bathing. The wearable sensor measured various lifestyle parameters, including walking steps, conversation time, and various sleep parameters, as described previously. 14  were included in the sound data, participation in the conversation was considered an important as a measure of social activity. Sound data, but not the content of conversations, were continuously collected every minute via a microphone on the wearable sensor and analyzed to evaluate the amount of time spent engaged in conversation. The wearable sensor detected sound pressure levels for utterances that originated within a 2-meter radius from the device. The sound pressure level ranged from 55 to 75 A-weighted decibels at this distance. A frequency band corresponding to a human voice from the sound data within the sound pressure range was extracted as a sound frame.
A conversation was defined as a period of 1 minute with more than 4 sound frames. We verified the measurement accuracy for walking steps, conversation time, and sleep time by comparing the sensor data with video observation data in healthy older adults. 14

Imaging Data Acquisition
Static carbon-11 labeled PiB-PET and fluorine-18 FDG-PET findings were acquired using the Biograph mCT (Siemens) in 3-dimensional scanning mode, as previously described. 18 Cognition and Brain Sciences Unit) region of interest (ROI) toolbox for Statistical Parametric Mapping was used to define ROIs for the frontal lobes, temporoparietal lobes, posterior cingulate gyrus, and cerebellum, as described previously. 20 These ROIs included those with amyloid deposition detected using amyloid PET or those with decreased cerebral glucose metabolism detected using FDG-PET in patients with Alzheimer disease. 21,22 The ROI values were averaged across both hemispheres. We assessed PiB and FDG uptake on the basis of a standardized uptake value ratio (SUVR), which was calculated from the voxel number-weighted average of the median uptake in the frontal, temporoparietal, and posterior cingulate ROIs in reference to the ROI in the cerebellum. The mean cortical SUVR in FDG-PET or PiB-PET was represented as the single mean value for all the regions combined.

Statistical Analysis
The association between neuroimaging variables and 7 lifestyle factor variables (walking steps,   Table 2 summarizes the results of the multiple regression model after adjusting for covariates between lifestyle factors and mean PiB uptake. There were no significant associations between the 7 lifestyle factors and mean PiB uptake in the multiple regression model. However, after adjusting for covariates, the change-point regression model showed an inverse association between TST and mean PiB uptake when TST was longer than 325 minutes (B = −0.0018; 95% CI, −0.0031 to −0.0007) (Figure, A and Table 3). The inclination of the graph began to reverse by the boundary of the specified threshold (ie, 325 minutes) for TST, indicating the association between TST and PiB

Discussion
We examined the association between objectively measured lifestyle factors and PET imaging using multiple regression and change-point regression models. While several studies have individually examined the association between physical activity, sleep, or cognitive activity and AD biomarkers among cognitively healthy adults, 28-36 to our knowledge, the present study is the first to clarify the association of various lifestyle factors with PET imaging simultaneously in older adults with MCI. In the present study, the number of adults with MCI and abnormal levels of PiB retention was relatively small compared with that reported in other studies, 37,38 indicating a heterogeneous background pathology. A possible explanation for this discrepancy is the inclusion of MCI adults with non-Alzheimer disease pathology, such as Lewy body disease, transactive response DNA binding protein 43, argyrophilic grains, and hippocampal sclerosis. 39 However, our results provide novel and interesting insights into the mechanisms underlying the association between lifestyle factors and cortical amyloid burden or brain function in older adults with MCI. First, TST was inversely associated with cortical amyloid burden among participants whose sleep duration was longer than 325 minutes.
Second, the association of TST with cerebral glucose metabolism remained significant after adjusting for covariates and correcting for the false-discovery rate. The present study has several strengths, such as including adults with MCI selected from community-dwelling older individuals, objectively measuring various lifestyle factors, and assessing cortical amyloid burden or brain function by PET imaging.  41,42 In younger individuals, diurnal fluctuations in brain interstitial fluid and cerebrospinal fluid 43 indicate that chronic sleep deprivation may increase β-amyloid production and reduce β-amyloid clearance, leading to amyloid plaque formation. 43 These results lead us to hypothesize that sleep duration may be an important lifestyle factor associated with cortical amyloid burden and brain function.
Few studies have examined the association of conversation time and PET imaging. We have previously reported the association between conversation time and cognitive function in older adults. 14 However, conversation time was not associated with cortical amyloid burden or cerebral glucose metabolism in this study. Moreover, objectively measured walking steps were not associated with cortical amyloid burden or cerebral glucose metabolism. Previous studies, 44,45 using an accelerometer, showed that moderately intense physical activity, but not light intensity or vigorous intensity physical activity, was favorably associated with cerebrospinal fluid β-amyloid 42 and cerebral glucose metabolism. These results support our findings because walking is considered a light intensity physical activity.

Limitations
The present study has several limitations that should be considered. First, the study could not determine the causal direction of the association between lifestyle factors and cortical amyloid burden or brain function because of its cross-sectional design. Second, the background noise from television or radio might have been detected as conversation by the detection method, which was based on sound pressure level and frequency. Moreover, conversation time may have included sleep or nap time during television viewing or radio listening. However, according to a previous study, 14 the possibility of including sleeping in the daily conversation time was only 6.4%. Third, we collated clinical data to define the presence or absence of dementia, but patients with possible dementia could not be completely excluded from the study. Fourth, the lack of association among walking steps, sleep time, and cortical amyloid burden might be because of a small number of adults with significant PiB uptake in our cohort. Therefore, this study must be considered preliminary, and further studies with larger sample size with cortical amyloid burden are required.

Conclusions
To our knowledge, this is the first study to confirm the association of sleep duration with cortical amyloid burden and brain function in older adults with MCI. Sleep duration was inversely associated with cerebral glucose metabolism. Moreover, sleep duration was inversely associated with cortical amyloid burden among participants whose sleep duration was longer than 325 minutes. These results may contribute to the development of novel evidence-based interventions for delaying cognitive impairment in older adults.