Episodic memory performance in a multi-ethnic longitudinal study of 13,037 elderly

Determinants of semantic and episodic memory decline among older adults in Ghana: Evidence from the WHO study on global AGEing and adult health Ghana wave 2

Objective

Determined factors associated with semantic (SM) and episodic memory (EM) among older adults aged 50 years and older in Ghana.

Methods

Data from WHO Study on Global AGEing and Adult Health (SAGE) Ghana Wave 2 was used for this study. Semantic memory (SM) and Episodic memory (EM) were the main study outcomes separately. The study employed Nested Ordinary Least Square regression analysis by sequentially adding 6 blocks of variables and comparison tests between the nested models.

Results

The study involved 3575 adult Ghanaians aged 50 years and older with a mean ± standard deviation of 62.6 ± 18.4 years. The overall mean ± SD of EM and SM were 5.86 ± 2.51 and 11.69 ± 8.59 respectively. Overall, analysis from block 6 showed a significant variation in SM by approximately 16.9%(ΔR2 = 1.17%) where increasing age, never married (β = -1.55; 95% CI = -2.41-0.69), being resident in Greater Accra (regional disparity) (β = -3.45; 95% CI = -4.73-2.20), underweight (β = -0.81;95% CI = -1.34-0.27), and moderate self-rated health (SRH) (β = -0.98; 95% CI = -1.52-0.45) significantly decreased SM. Similarly, increasing age, separated/divorced (β = -0.22; 95% CI = -0.35-0.87), being resident in Greater Accra (β = -0.53; 95% CI = -0.80-0.26), and moderate SRH (β = -0.20; 95% CI = -0.36--0.04) significantly decrease EM with an overall significant variation of approximately 22.9%(ΔR2 = 2.7%).

Conclusions

Increasing age, sex, marital status, regional disparity, and poor SRH significantly decreased both Semantic memory and Episodic memory. Higher educational attainment and life satisfaction significantly influenced SM and EM. These provide pointers to important socio-demographic determinants of SM and EM with implications for the implementation of the Ghana national ageing policy 2010, 'ageing with security and dignity', and as a key consideration for healthy ageing towards 2030.

Nativity differences in the relationship between handgrip strength and cognitive impairment in older Mexican Americans over 20 years of follow-up

PURPOSE

To examine nativity differences in the relationship between handgrip strength (HGS) and cognitive impairment among Mexican Americans aged ≥ 65 years with normal or high cognitive function at baseline over a 20-year period.

METHODS

Prospective cohort study of 2,155 non-institutionalized Mexican Americans aged ≥ 65 years from the Hispanic Established Population for the Epidemiological Study of the Elderly) who scored ≥ 21 in the Mini Mental State Examination (MMSE) at baseline. Measures included socio-demographics, body mass index, medical conditions, depressive symptoms, physical function, disability, HGS quartiles (sex-adjusted), and MMSE. We used generalized estimating equation models to estimate the odds ratio (OR) and 95% Confidence Interval (CI) of cognitive impairment (MMSE < 21) as a function of HGS quartile by nativity and adjusted for covariates.

RESULTS

US-born and foreign-born participants in the 4th quartile (highest) of HGS at baseline had lower odds of cognitive impairment over time compared with those in the 1st (lowest) HGS quartile (OR=0.95, 95% CI=0.90-0.99 and OR=0.93, 95% CI=0.89-0.98, respectively), after controlling for all covariates. When we analyzed HGS quartiles as time-varying, we found that US-born participants in the 3rd and 4th HGS quartile had 25% and 30% lower odds of cognitive impairment, respectively, while foreign-born participants in the 3rd and 4th HGS quartile had 27% and 49% lower odds of cognitive impairment over time, respectively, after controlling for all covariates.

CONCLUSION

Foreign-born older Mexican Americans who performed high in HGS experienced 7% lower odds of cognitive impairment over time compared with US-born older Mexican Americans.

Longitudinal episodic memory trajectories in older adults with normal cognition

OBJECTIVE

To determine the longitudinal trajectories and normative standards of episodic memory in older adults.

METHODS

Participants were drawn from the cognitively normal(CN) subgroup of the population-based HELIAD cohort, a fairly representative cohort of the older Greek population. Verbal and non-verbal memory were assessed using the Greek Verbal Learning Test and Medical College of Georgia-Complex Figure Test. Baseline and longitudinal associations of memory performance with age, sex and formal education were explored with linear regression analysis and generalized estimated equations.

RESULTS

A total of 1607 predominantly female (60%) individuals (73.82 ± 5.43 years), with a mean educational attainment of 8.17(±4.86) years were CN at baseline. Baseline analysis revealed a continuum of memory decline with aging and lower educational attainment. Women performed better in composite and verbal memory measures, while men performed better in non-verbal memory tasks. A subgroup of 761 participants with available assessments after 3.07(±0.82) years remained CN at follow-up. Composite memory scores yearly diminished by an additional 0.007 of a SD for each additional year of age at baseline. Regarding verbal learning, immediate free verbal recall, delayed free verbal recall and delayed cued verbal recall, an additional yearly decrease of 0.107, 0.043, 0.036 and 0.026 words were respectively recorded at follow-up, for each additional year of age at baseline. Women underwent steeper yearly decreases of 0.227 words in delayed cued verbal recall. No significant longitudinal associations emerged for immediate non-verbal memory, delayed non-verbal memory and immediate cued verbal recall.

CONCLUSIONS

In the present study, aging (but not educational attainment) was consistently associated with steeper verbal memory decline.

Supplemental data for this article is available online at https://doi.org/10.1080/13854046.2022.2059011 .

Integration of GWAS and brain transcriptomic analyses in a multiethnic sample of 35,245 older adults identifies DCDC2 gene as predictor of episodic memory maintenance

Identifying genes underlying memory function will help characterize cognitively resilient and high-risk declining subpopulations contributing to precision medicine strategies. We estimated episodic memory trajectories in 35,245 ethnically diverse older adults representing eight independent cohorts. We conducted apolipoprotein E (APOE)-stratified genome-wide association study (GWAS) analyses and combined individual cohorts' results via meta-analysis. Three independent transcriptomics datasets were used to further interpret GWAS signals. We identified DCDC2 gene significantly associated with episodic memory (Pmeta = 3.3 x 10^-8 ) among non-carriers of APOE ε4 (N = 24,941). Brain transcriptomics revealed an association between episodic memory maintenance and (1) increased dorsolateral prefrontal cortex DCDC2 expression (P = 3.8 x 10^-4 ) and (2) lower burden of pathological Alzheimer's disease (AD) hallmarks (paired helical fragment tau P = .003, and amyloid beta load P = .008). Additional transcriptomics results comparing AD and cognitively healthy brain samples showed a downregulation of DCDC2 levels in superior temporal gyrus (P = .007) and inferior frontal gyrus (P = .013). Our work identified DCDC2 gene as a novel predictor of memory maintenance.

Longitudinal resting-state functional connectivity and regional brain atrophy-based biomarkers of preclinical cognitive impairment in healthy old adults

BACKGROUND

Intervention against age-related neurodegenerative diseases may be difficult once extensive structural and functional deteriorations have already occurred in the brain.

AIM

Investigating 6-year longitudinal changes and implications of regional brain atrophy and functional connectivity in the triple-network model as biomarkers of preclinical cognitive impairment in healthy aging.

METHODS

We acquired longitudinal cognitive scores and magnetic resonance imaging (MRI) data from 74 healthy old adults. Resting-state functional MRI (rs-fMRI) analysis was conducted using FSL6.0.1 to examine functional connectivity changes and regional brain morphometries were quantified using FreeSurfer5.3. Finally, we cross-validated and compared two support vector machine (SVM) regression models to predict future 6-year cognition score from the baseline regional brain atrophy and resting-state functional connectivity (rs-FC) measures.

RESULTS

After a 6-year follow-up, our results (P < 0.05-corrected) indicated significant connectivity reduction within all the three brain networks, significant differences in regional brain volumes and cortical thickness. We also observed significant improvement in episodic memory and significant decline in executive functions. Finally, comparing the two models, we observed that regional brain atrophy predictors were more efficient in approximating future 6-year cognitive scores (R = 0.756, P < 0.0001) than rs-FC predictors (R = 0.6, P < 0.0001).

CONCLUSION

This study used longitudinal data to keep subject variability low and to increase the validity of the results. We demonstrated significant changes in structural and functional MRI over 6 years. Our findings present a potential neuroimaging-based biomarker to detect cognitive impairment and prevent risks of neurodegenerative diseases in healthy old adults.

APOE Gene Associated with Cholesterol-Related Traits in the Hispanic Population

Genetic variants in the apolipoprotein E (APOE) gene are associated with lipid metabolism and lipid-related traits in the non-Hispanic population. There have been limited studies regarding the association between the APOE gene and hypercholesterolemia in the Hispanic population; therefore, our aim for this study is to examine the APOE gene’s associations with cholesterol level and its related phenotypes. The APOE gene consists of three different alleles, ε2, ε3, and ε4, with ε4 being associated with dementia and cardiovascular diseases. A total of 1,382 subjects were collected from the Texas Alzheimer’s Research and Care Consortium (TARCC, N = 1320) and the Initial Study of Longevity and Dementia from the Rio Grande Valley (ISLD-RGV, N = 62). Questionnaires on demographics, medical history, and blood/saliva samples were collected and APOE genotypes were performed. We observed allele frequencies of the APOE ε3 (96.7%), ε4 (22.6%) and ε2 (6.8%) alleles, respectively. Multivariable logistic regression revealed a significant association between the APOE ε4 allele and hypercholesteremia (p = 1.8 × 10⁻⁴) in our studied Hispanic population. We prove for the first time, that the APOE ε4 allele increases the risk for hypercholesterol in Hispanics. Further research is needed to confirm and supports our current findings.

Ambient Air Pollution and Long-Term Trajectories of Episodic Memory Decline among Older Women in the WHIMS-ECHO Cohort

BACKGROUND

Episodic memory decline varies by age and underlying neuropathology. Whether ambient air pollution contributes to the heterogeneity of episodic memory decline in older populations remains unclear.

OBJECTIVES

We estimated associations between air pollution exposures and episodic memory decline according to pollutant, exposure time window, age, and latent class subgroups defined by episodic memory trajectories.

METHODS

Participants were from the Women's Health Initiative Memory Study-Epidemiology of Cognitive Health Outcomes. Older women (n = 2,056 ; 74-92 years of age) completed annual (2008-2018) episodic memory assessments using the telephone-based California Verbal Learning Test (CVLT). We estimated 3-y average fine particulate matter [PM with an aerodynamic diameter of ≤ 2.5 μ m (PM 2.5 )] and nitrogen dioxide (NO 2 ) exposures at baseline and 10 y earlier (recent and remote exposures, respectively), using regionalized national universal kriging. Separate latent class mixed models were used to estimate associations between interquartile range increases in exposures and CVLT trajectories in women ≤ 80 and > 80  years of age , adjusting for covariates.

RESULTS

Two latent classes were identified for women ≤ 80  years of age (n = 828 ), "slow-decliners" {slope = - 0.12 / y [95% confidence interval (CI): - 0.23 , - 0.01 ] and "fast-decliners" [slope = - 1.79 / y (95% CI: - 2.08 , - 1.50 )]}. In the slow-decliner class, but not the fast-decliner class, PM 2.5 exposures were associated with a greater decline in CVLT scores over time, with a stronger association for recent vs. remote exposures [- 0.16 / y (95% CI: - 2.08 , - 0.03 ) per 2.88   μ g / m 3 and - 0.11 / y (95% CI: - 0.22 , 0.01) per 3.27   μ g / m 3 , respectively]. Among women ≥ 80  years of age (n = 1,128 ), the largest latent class comprised "steady-decliners" [slope = - 1.35 / y (95% CI: - 1.53 , - 1.17 )], whereas the second class, "cognitively resilient", had no decline in CVLT on average. PM 2.5 was not associated with episodic memory decline in either class. A 6.25 -ppb increase in recent NO 2 was associated with nonsignificant acceleration of episodic memory decline in the ≤ 80 -y-old fast-decliner class [- 0.21 / y (95% CI: - 0.45 , 0.04)], and in the > 80 -y-old cognitively resilient class [- 0.10 / y (95% CI: - 0.24 , 0.03)] and steady-decliner class [- 0.11 / y (95% CI: - 0.27 , 0.05)]. Associations with recent NO 2 exposure in women > 80  years of age were stronger and statistically significant when 267 women with incident probable dementia were excluded [e.g., - 0.12 / y (95% CI: - 0.22 , - 0.02 ) for the cognitively resilient class]. In contrast with changes in CVLT over time, there were no associations between exposures and CVLT scores during follow-up in any subgroup.

DISCUSSION

In a community-dwelling U.S. population of older women, associations between late-life exposure to ambient air pollution and episodic memory decline varied by age-related cognitive trajectories, exposure time windows, and pollutants. https://doi.org/10.1289/EHP7668.

Efficient and Explainable Risk Assessments for Imminent Dementia in an Aging Cohort Study

As the aging US population grows, scalable approaches are needed to identify individuals at risk for dementia. Common prediction tools have limited predictive value, involve expensive neuroimaging, or require extensive and repeated cognitive testing. None of these approaches scale to the sizable aging population who do not receive routine clinical assessments. Our study seeks a tractable and widely administrable set of metrics that can accurately predict imminent (i.e., within three years) dementia onset. To this end, we develop and apply a machine learning (ML) model to an aging cohort study with an extensive set of longitudinal clinical variables to highlight at-risk individuals with better accuracy than standard rudimentary approaches. Next, we reduce the burden needed to achieve accurate risk assessments for those deemed at risk by (1) predicting when consecutive clinical visits may be unnecessary, and (2) selecting a subset of highly predictive cognitive tests. Finally, we demonstrate that our method successfully provides individualized prediction explanations that retain non-linear feature effects present in the data. Our final model, which uses only four cognitive tests (less than 20 minutes to administer) collected in a single visit, affords predictive performance comparable to a standard 100-minute neuropsychological battery and personalized risk explanations. Our approach shows the potential for an efficient tool for screening and explaining dementia risk in the general aging population.

MEF2C Common Genetic Variation Is Associated With Different Aspects of Cognition in Non-Hispanic White and Caribbean Hispanic Non-demented Older Adults

OBJECTIVES

Myocyte Enhancer Factor 2C (MEF2C) is identified as a candidate gene contributing to the risk of developing Alzheimer's disease. However, little is known about whether MEF2C plays a role in specific aspects of cognition among older adults. The current study investigated the association of common variants in the MEF2C gene with four cognitive domains including memory, visuospatial functioning, processing speed and language among non-demented individuals.

METHOD

Participants from two ethnic groups, Non-Hispanic White (NHW; n = 537) and Caribbean Hispanic (CH; n = 1,197) from the Washington Heights-Inwood Community Aging Project (WHICAP) study, were included. Genetic association analyses using WHICAP imputed genome-wide data (GWAS) were conducted for the various cognition domains.

RESULTS

Single nucleotide polymorphisms (SNP) variants in the MEF2C gene showed nominally significant associations in all cognitive domains but for different SNPs across both the ethnic groups. In NHW participants, the strongest associations were present for memory (rs302484), language (rs619584), processing speed (rs13159808), and visuospatial functioning (several SNPs). In CH, strongest associations were observed for memory (rs34822815), processing speed (rs304141), visuospatial functioning (rs10066711 and rs10038371), and language (rs304153).

DISCUSSION

MEF2C variant-cognitive associations shed light on an apparent role for MEF2C in both memory and non-memory aspects of cognition in individuals from NHW and CH ancestries. However, the little overlap in the specific SNP-cognition associations in CH versus NHW highlights the differences in genetic architectural variations among those from different ancestries that should be considered while studying the MEF2C gene.

Developing an Explainable Machine Learning-Based Personalised Dementia Risk Prediction Model: A Transfer Learning Approach With Ensemble Learning Algorithms

Alzheimer's disease (AD) has its onset many decades before dementia develops, and work is ongoing to characterise individuals at risk of decline on the basis of early detection through biomarker and cognitive testing as well as the presence/absence of identified risk factors. Risk prediction models for AD based on various computational approaches, including machine learning, are being developed with promising results. However, these approaches have been criticised as they are unable to generalise due to over-reliance on one data source, poor internal and external validations, and lack of understanding of prediction models, thereby limiting the clinical utility of these prediction models. We propose a framework that employs a transfer-learning paradigm with ensemble learning algorithms to develop explainable personalised risk prediction models for dementia. Our prediction models, known as source models, are initially trained and tested using a publicly available dataset (n = 84,856, mean age = 69 years) with 14 years of follow-up samples to predict the individual risk of developing dementia. The decision boundaries of the best source model are further updated by using an alternative dataset from a different and much younger population (n = 473, mean age = 52 years) to obtain an additional prediction model known as the target model. We further apply the SHapely Additive exPlanation (SHAP) algorithm to visualise the risk factors responsible for the prediction at both population and individual levels. The best source model achieves a geometric accuracy of 87%, specificity of 99%, and sensitivity of 76%. In comparison to a baseline model, our target model achieves better performance across several performance metrics, within an increase in geometric accuracy of 16.9%, specificity of 2.7%, and sensitivity of 19.1%, an area under the receiver operating curve (AUROC) of 11% and a transfer learning efficacy rate of 20.6%. The strength of our approach is the large sample size used in training the source model, transferring and applying the "knowledge" to another dataset from a different and undiagnosed population for the early detection and prediction of dementia risk, and the ability to visualise the interaction of the risk factors that drive the prediction. This approach has direct clinical utility.

Does the association between cognition and education differ between older adults with gradual or rapid trajectories of cognitive decline?

Education is associated with improved baseline cognitive performance in older adults, but the association with maintenance of cognitive function is less clear. Education may be associated with different types of active cognitive reserve in those following different cognitive trajectories. We used data on n = 5642 adults aged >60 from the English Longitudinal Study of Aging (ELSA) over 5 waves (8 years). We used growth mixture models to test if the association between educational attainment and rate of change in verbal fluency or immediate recall varied by latent class trajectory. For recall, 91.5% (n = 5164) of participants were in a gradual decline class and 8.5% (n = 478) in a rapid decline class. For fluency, 90.0% (n = 4907) were in a gradual decline class and 10.0% (n = 561) were in a rapid decline class. Educational attainment was associated with improved baseline performance for both verbal fluency and recall. In the rapidly declining classes, educational attainment was not associated with rate of change for either outcome. In the verbal fluency gradual decline class, education was associated with higher (an additional 0.05-0.38 words per 2 years) or degree level education (an additional 0.04-0.42 words per 2 years) when compared to those with no formal qualifications. We identified no evidence of a protective effect of education against rapid cognitive decline. There was some evidence of active cognitive reserve for verbal fluency but not recall, which may reflect a small degree of domain-specific protection against age-related cognitive decline.

Longitudinal Characterization and Biomarkers of Age and Sex Differences in the Decline of Spatial Memory

The current longitudinal study examined factors (sex, physical function, response to novelty, ability to adapt to a shift in light/dark cycle, brain connectivity), which might predict the emergence of impaired memory during aging. Male and female Fisher 344 rats were tested at 6, 12, and 18 months of age. Impaired spatial memory developed in middle-age (12 months), particularly in males, and the propensity for impairment increased with advanced age. A reduced response to novelty was observed over the course of aging, which is inconsistent with cross-sectional studies. This divergence likely resulted from differences in the history of environmental enrichment/impoverishment for cross-sectional and longitudinal studies. Animals that exhibited lower level exploration of the inner region on the open field test exhibited better memory at 12 months. Furthermore, males that exhibited a longer latency to enter a novel environment at 6 months, exhibited better memory at 12 months. For females, memory at 12 months was correlated with the ability to behaviorally adapt to a shift in light/dark cycle. Functional magnetic resonance imaging of the brain, conducted at 12 months, indicated that the decline in memory was associated with altered functional connectivity within different memory systems, most notably between the hippocampus and multiple regions such as the retrosplenial cortex, thalamus, striatum, and amygdala. Overall, some factors, specifically response to novelty at an early age and the capacity to adapt to shifts in light cycle, predicted spatial memory in middle-age, and spatial memory is associated with corresponding changes in brain connectivity. We discuss similarities and differences related to previous longitudinal and cross-sectional studies, as well as the role of sex differences in providing a theoretical framework to guide future longitudinal research on the trajectory of cognitive decline. In addition to demonstrating the power of longitudinal studies, these data highlight the importance of middle-age for identifying potential predictive indicators of sexual dimorphism in the trajectory in brain and cognitive aging.