Cognitive Polygenic Index is Associated with Occupational Complexity over and above Brain Morphometry.

Although the impact of occupation on cognitive skills has been extensively studied, there is limited research examining if genetically predicted cognitive score may influence occupation. We examined the association between Cognitive Polygenic Index (PGI) and occupation, including the role of brain measures. Participants were recruited for the Reference Ability Neural Network and the Cognitive Reserve studies. Occupational complexity ratings for Data, People, or Things came from the Dictionary of Occupational Titles. A previously-created Cognitive PGI and linear regression models were used for the analyses. Age, sex, education, and the first 20 genetic Principal Components (PCs) of the sample were covariates. Total cortical thickness and total gray matter volume were further covariates. We included 168 white-ethnicity participants, 20-80 years old. After initial adjustment, higher Cognitive PGI was associated with higher Data complexity (B=-0.526, SE = 0.227, Beta= -0.526 p = 0.022, R2 = 0.259) (lower score implies higher complexity). Associations for People or Things were not significant. After adding brain measures, association for Data remained significant (B=-0.496, SE: 0.245, Beta= -0.422, p = 0.045, R2 = 0.254). Similarly, for a further, fully-adjusted analysis including all the three occupational complexity measures (B=-0.568, SE = 0.237, Beta= -0.483, p = 0.018, R2 = 0.327). Cognitive genes were associated with occupational complexity over and above brain morphometry. Working with Data occupational complexity probably acquires higher cognitive status, which can be significantly genetically predetermined.

Polygenic indices for cognition in healthy aging; the role of brain measures.

Background: Genome-wide association studies (GWAS) have identified large numbers of genetic variants associated with cognition. However, little is known about how these genetic discoveries impact cognitive aging. Methods: We conducted polygenic-index (PGI) analysis of cognitive performance in n = 168 European-ancestry adults aged 20-80. We computed PGIs based on GWAS of cognitive performance in young/middle-aged and older adults. We tested associations of the PGI with cognitive performance, as measured through neuropsychological evaluation. We explored whether these associations were accounted for by magnetic resonance imaging (MRI) measures of brain-aging phenotypes: total gray matter volume (GM), cortical thickness (CT), and white matter hyperintensities burden (WMH). Results: Participants with higher PGI values performed better on cognitive tests (B = 0.627, SE = 0.196, p = 0.002) (age, sex, and principal components as covariates). Associations remained significant with inclusion of covariates for MRI measures of brain aging; B = 0.439, SE: 0.198, p = 0.028). PGI associations were stronger in young and middle-aged (age<65) as compared to older adults. For further validation, linear regression for Cog PGI and cognition in the fully adjusted model and adding the interaction between age group and Cog PGI, showed significant results (B = 0.892, SE: 0.325, p = 0.007) driven by young and middle-aged adults (B = -0.403, SE: 0.193, p = 0.039). In ancillary analysis, the Cognitive PGI was not associated with any of the brain measures. Conclusions: Genetics discovered in GWAS of cognition are associated with cognitive performance in healthy adults across age, but most strongly in young and middle-aged adults. Associations were not explained by brain-structural markers of brain aging. Genetics uncovered in GWAS of cognitive performance may contribute to individual differences established relatively early in life and may not reflect genetic mechanisms of cognitive aging.

Remote neuropsychological evaluation of older adults.

The use of technological means in the process of neuropsychological assessment has been proposed as a technique with promising results in the field of detection of neurocognitive disorders for community-dwelling older adults. Especially during the pandemic period due to COVID-19, telemedicine assumed to be vital in the field of early diagnosis of cognitive disorders and highlighted the clinical utility of remote methods of neuropsychological assessmentby video-conference. This descriptive study presents the development of a remote neuropsychological assessment protocol by selecting appropriate validated tests as part of a more comprehensive evaluation for older adults dwelling in the community. We recruited participants from the Athens Alzheimer's Association center in collaboration with the Hellenic Neuropsychological Society, in Athens, Greece, regarding the period between April 2020 and October 2021. 90 individuals, tested for the first time, were categorized into three groups according to their diagnosis which included: (a) Mild Cognitive Impairment (MCI), (b) Alzheimer's disease, (c) cognitively healthy older adults. The presented protocol outlines the main considerations of a framework about remote neuropsychological assessment, which can maximize the effectiveness of interventions and continuity regarding the care of older adults. The recommendations outlined in the presented protocol highlight strengths and limitations that should be taken into account in remote control procedures. Although the protocol was created in response to pandemic restrictions, tele-neuropsychology shows promise as a way to improve access opportunity to neurodiagnostic services for rural aging and underserved populations, which lack specialized healthcare services. Further application to different populations will add validity to the presented descriptive protocol.

Polygenic score for sleep duration. Association with cognition.

STUDY OBJECTIVES: Age-related changes in sleep include a reduction in total sleep time and a greater incidence of sleep disorders, and are also an integral part of neurodegenerations. In the present study, we aimed to: a) identify common genetic variants that may influence self-reported sleep duration, and b) examine the association between the identified genetic variants and performance in different cognitive domains. METHODS: A sample of 197 cognitively healthy participants, aged 20-80 years, mostly non-Hispanic Whites (69%), were selected from the Reference Abilities Neural Network and the Cognitive Reserve study. Each participant underwent an evaluation of sleep function and assessment of neuropsychological performance on global cognition and four different domains (memory, speed of processing, fluid reasoning, language). Published GWAS summary statistics from a Polygenic Score (PS) for sleep duration in a large European ancestry cohort (N = 30,251) were used to derive a PS in our study sample. Multivariate linear models were used to test the associations between the PS and sleep duration and cognitive performance. Age, sex, and education were used as covariates. Secondary analyses were conducted in three age-groups (young, middle, old). RESULTS: Higher PS was linked to longer sleep duration and was also associated with better performance in global cognition, fluid reasoning, speed of processing, and language, but not memory. Results especially for fluid reasoning, language, and global cognition were driven mostly by the young group. CONCLUSIONS: Our study replicated the previously reported association between sleep-PS and longer sleep duration. We additionally found a significant association between the sleep-PS and cognitive function. Our results suggest that common genetic variants may influence the link between sleep duration and cognitive health.

Dataset on the associations between sleep quality/duration and cognitive performance in cognitively healthy older adults.

In the present data, we provide the details of the cross-sectional study examining the associations between sleep quality/sleep duration and cognitive performance. Data are from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD). A total of 1484 older adults (65 y.o. or older) took part in the study. Sleep measurements were drawn from the sleep scale of the Medical Outcomes Study (MOS). Cognition was used as a z-score drawn by different tests. The domains examined were: executive function, visuo-spatial ability, language, attention- speed of processing, as well as the composite z-score of all the cognitive domains (including memory). Linear regression models were conducted to investigate the associations between sleep quality and cognition, and sleep duration and cognition as well. We also conducted linear regression analyses for the associations between sleep quality/duration and cognitive domains/composite cognitive score based on the status of the Apolipoprotein E-ε4 (ApoE-ε4) genotype. Analyses were performed excluding both the demented and the Mild Cognitive Impairment (MCI) participants. Adjustments conducted for multiple covariates. For further analyses and enhanced discussion, see original article: "Sleep quality and duration in relation to memory in the elderly: initial results from the Hellenic Longitudinal Investigation of Aging and Diet" by Tsapanou et al. [1].

Sleep quality and duration in relation to memory in the elderly: Initial results from the Hellenic Longitudinal Investigation of Aging and Diet.

BACKGROUND: Sleep is crucial for cognition, particularly for memory, given its complex association with neurodegenerative processes. The aim of the present study was to examine the association between sleep quality as well as sleep duration and memory performance in a Greek elderly population. SETTING: Cross-sectional design in the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD), a population representative study of Greek elderly (65years or older). METHODS: Data from 1589 participants free of sleep medication were included. Sleep quality was estimated by using the Sleep Scale from the Medical Outcomes Study. An extensive neuropsychological assessment examining memory was administered to each participant. Linear regression analyses were used to examine whether sleep quality (higher score, poor quality) and/or sleep duration were associated with memory expressed in the form of a z-score. Age, sex, education, and body mass index were included as covariates. The main analyses were conducted first on the total sample, then with the exclusion of demented participants, and finally with the exclusion of both demented and participants with Mild Cognitive Impairment (MCI). We then conducted further analyses on the non-demented, non-MCI group, initially stratified by Apolipoprotein E-ε4 gene. We further examined the role of co-morbidities, as well as the association between sleep duration groups and memory. We also explored any interaction effect between sex and sleep quality/duration on memory. We then examined the associations between components of sleep measures and memory scores. Lastly, we examined the associations between sleep quality/duration and verbal/non-verbal memory separately. RESULTS: In the total sample, we noted significant associations between sleep duration and memory (B=-0.001, p≤0.0001), but not for sleep quality and memory (B=-0.038, p=0.121). After excluding the demented participants, the associations were significant for: sleep quality and memory (B=-0.054, p=0.023), and sleep duration and memory (B=-0.001, p≤0.0001). After excluding both the MCI and the demented subjects, the associations between sleep quality and memory (B=-0.065, p=0.006), and sleep duration and memory (B=-0.001, p=0.003) were still significant. The association between the sleep duration groups and memory function was also significant, such that poor memory performance was associated with the longer sleep duration group. The results remained significant even after controlling for the co-morbidities, as well as after adding in the model anxiety and depression as covariates. Associations between sleep quality and memory, and sleep duration and memory were present in the ApoE-ε4 non-carriers. The individual sleep questions that were probably shown to be driving the associations between sleep and memory were: time to fall asleep, sleep not quiet, getting enough sleep to feel rested upon waking in the morning, and getting the amount of sleep needed. Sleep duration was associated with both verbal and non-verbal memory, while sleep quality was only associated with verbal memory. CONCLUSION: Poor sleep quality and longer sleep duration were linked to low memory performance, independent of demographic and clinical factors, in a large sample of cognitively healthy older Greek adults. Other parameters than sleep and memory measurements could play an important role on the association. Levels of melatonin, or circadian rhythms dysregulation might play a crucial role in the above associations.