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32 Altered Resting State EEG Spectral Properties in Older Individuals at High Risk for Alzheimer’s Disease
- Jessica J. Zakrzewski, Zachary Gemelli, Laura Korthauer
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 241-242
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Objective:
Onset of Alzheimer’s disease (AD) pathology is estimated to begin 20-30 years prior to clinical symptom onset. Resting state EEG may yield useful early biomarkers of pathology, but its use along the AD clinical continuum is still limited, especially in individuals who are at high risk for AD but have yet to show symptoms. EEG waveform oscillations are classified based by frequency range (alpha, beta, theta, delta). Changes within these frequency bands have been identified in individuals with AD-dementia as compared to those with MCI and normal aging. Typical changes involve increases in low frequency power bands of delta and theta and decreases in beta and alpha frequencies, particularly in more posterior brain regions. However, these methods have yet to be explored in cognitively normal individuals who are at high risk for AD, as work has shown between individuals with MCI and healthy older adults.
Participants and Methods:We compared differences in resting state EEG between older adults (age 60+) at high risk for AD (positive family history, genetic risk defined as carrying 1 + ApoE ε4 alleles) and individuals at low risk (negative family history, no ε4 allele). We collected 1) neuropsychological test performance; 2) self-report measures of subjective cognitive complaints and cognitive reserve; and 3) five minutes of eyes-open resting state EEG using 64-channel active electrodes. Clusters of three electrodes were average for regions and absolute power within 5 frequency bands was calculated. Theta/beta ratio was calculated by dividing absolute power of bands at its respective site. Correlations between absolute power for specific regions, self-report measures, and neuropsychological test scores.
Results:Analysis of 20 individuals collected to date (14 high risk, 6 low risk) found associations (p<0.05) between risk group and beta and gamma power across multiple electrode clusters, with high-risk individuals having higher power. Significant correlations were also found between calculated measures of cognitive reserve and posterior theta/beta ratio, subjective cognitive complaints and beta power, and neuropsychological test composites of learning performance with delta and executive functioning with frontal theta power.
Conclusions:This work provides preliminary evidence for differences in resting state EEG activity in those at risk for AD, prior to onset of clinical symptoms. Future work will examine patients with mild cognitive impairment as a comparison group to characterize resting state EEG across the early AD continuum.
31 Understanding Health Beliefs and Health Behaviors in Older Adults at Risk for Alzheimer’s Disease
- Jessica J. Zakrzewski, Zachary Gemelli, Jennifer Davis, Laura Korthauer
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, p. 343
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- Article
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- You have access Access
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Objective:
Given the aging population, there are significant public health benefits to delaying the onset of Alzheimer’s disease (AD) in individuals at risk. However, adherence to health behaviors (e.g., diet, exercise, sleep hygiene) is low in the general population. The Health Belief Model proposes that beliefs such as perceived threat of disease, perceived benefits and barriers to behavior change, and cues to action are mediators of behavior change. The aim of this study was to gain additional information on current health behaviors and beliefs for individuals at risk for developing AD. This information can then be used to inform behavioral interventions and individualized strategies to improve health behaviors that may reduce AD risk or delay symptom onset.
Participants and Methods:Surveys were sent to the Rhode Island AD Prevention Registry, which is enriched for at-risk, cognitively normal adults (i.e., majority with a family history and/or an APOE e4 allele). A total of 177 individuals participated in this study. Participants were 68% female; 93% Caucasian and non-Hispanic; mean age of 69.2; 74% with family history of dementia; 40% with subjective memory decline. The survey included measures from the Science of Behavior Change (SoBC) Research Network to measure specific health belief factors, including individual AD risk, perceived future time remaining in one’s life, generalized self-efficacy, deferment of gratification, consideration of future consequences as well as dementia risk awareness and a total risk score for dementia calculated from a combination demographic, health and lifestyle behaviors.
Results:Participants who were older had higher scores for dementia risk (r=0.78), lower future time perspective (r=-0.33), and lower generalized self-efficacy (r=-0.31) (all at p<0.001). Higher education correlated with higher consideration of future consequences (r=-.31, p<0.001) and lower overall dementia risk score (r=-0.23, p=0.006). Of all scales examined, only generalized self-efficacy had a significant linear relationship to both frequency (r2=0.06) and duration (r2=0.08) of weekly physical activity (p<0.001). Total dementia risk score also had significant linear relationships (r2=0.19) with future time perspective (p<0.001) and generalized self-efficacy (p=0.48).
Conclusions:Overall, individuals who rated themselves higher in self-efficacy were more likely to exercise more frequently and for a longer duration. Individuals who had lower overall risk for dementia due to both demographic and behavioral factors were more likely to endorse higher self-efficacy and more perceived time remaining in their lives. Increasing self-efficacy and targeting perceived future time limitations may be key areas to increase motivation and participation in behavioral strategies to reduce AD risk. Developing individual profiles based on these scales may further allow for individually tailored intervention opportunities.