Shared and unique genetic and environmental influences on aging-related changes in multiple cognitive abilities

A Subtype Perspective on Cognitive Trajectories in Healthy Aging

Cognitive aging is a complex and dynamic process characterized by changes due to genetics and environmental factors, including lifestyle choices and environmental exposure, which contribute to the heterogeneity observed in cognitive outcomes. This heterogeneity is particularly pronounced among older adults, with some individuals maintaining stable cognitive function while others experience complex, non-linear changes, making it difficult to identify meaningful decline accurately. Current research methods range from population-level modeling to individual-specific assessments. In this work, we review these methodologies and propose that population subtyping should be considered as a viable alternative. This approach relies on early individual-specific detection methods that can lead to an improved understanding of changes in individual cognitive trajectories. The improved understanding of cognitive trajectories through population subtyping can lead to the identification of meaningful changes and the determination of timely, effective interventions. This approach can aid in informing policy decisions and in developing targeted interventions that promote cognitive health, ultimately contributing to a more personalized understanding of the aging process within society and reducing the burden on healthcare systems.

Prediction of cognitive performance differences in older age from multimodal neuroimaging data

Differences in brain structure and functional and structural network architecture have been found to partly explain cognitive performance differences in older ages. Thus, they may serve as potential markers for these differences. Initial unimodal studies, however, have reported mixed prediction results of selective cognitive variables based on these brain features using machine learning (ML). Thus, the aim of the current study was to investigate the general validity of cognitive performance prediction from imaging data in healthy older adults. In particular, the focus was with examining whether (1) multimodal information, i.e., region-wise grey matter volume (GMV), resting-state functional connectivity (RSFC), and structural connectivity (SC) estimates, may improve predictability of cognitive targets, (2) predictability differences arise for global cognition and distinct cognitive profiles, and (3) results generalize across different ML approaches in 594 healthy older adults (age range: 55-85 years) from the 1000BRAINS study. Prediction potential was examined for each modality and all multimodal combinations, with and without confound (i.e., age, education, and sex) regression across different analytic options, i.e., variations in algorithms, feature sets, and multimodal approaches (i.e., concatenation vs. stacking). Results showed that prediction performance differed considerably between deconfounding strategies. In the absence of demographic confounder control, successful prediction of cognitive performance could be observed across analytic choices. Combination of different modalities tended to marginally improve predictability of cognitive performance compared to single modalities. Importantly, all previously described effects vanished in the strict confounder control condition. Despite a small trend for a multimodal benefit, developing a biomarker for cognitive aging remains challenging.

Today's Older Adults Are Cognitively Fitter Than Older Adults Were 20 Years Ago, but When and How They Decline Is No Different Than in the Past

History-graded increases in older adults' levels of cognitive performance are well documented, but little is known about historical shifts in within-person change: cognitive decline and onset of decline. We combined harmonized perceptual-motor speed data from independent samples recruited in 1990 and 2010 to obtain 2,008 age-matched longitudinal observations (M = 78 years, 50% women) from 228 participants in the Berlin Aging Study (BASE) and 583 participants in the Berlin Aging Study II (BASE-II). We used nonlinear growth models that orthogonalized within- and between-person age effects and controlled for retest effects. At age 78, the later-born BASE-II cohort substantially outperformed the earlier-born BASE cohort (d = 1.20; 25 years of age difference). Age trajectories, however, were parallel, and there was no evidence of cohort differences in the amount or rate of decline and the onset of decline. Cognitive functioning has shifted to higher levels, but cognitive decline in old age appears to proceed similarly as it did two decades ago.

A strong dependency between changes in fluid and crystallized abilities in human cognitive aging

Theories of adult cognitive development classically distinguish between fluid abilities, which require effortful processing at the time of assessment, and crystallized abilities, which require the retrieval and application of knowledge. On average, fluid abilities decline throughout adulthood, whereas crystallized abilities show gains into old age. These diverging age trends, along with marked individual differences in rates of change, have led to the proposition that individuals might compensate for fluid declines with crystallized gains. Here, using data from two large longitudinal studies, we show that rates of change are strongly correlated across fluid and crystallized abilities. Hence, individuals showing greater losses in fluid abilities tend to show smaller gains, or even losses, in crystallized abilities. This observed commonality between fluid and crystallized changes places constraints on theories of compensation and directs attention toward domain-general drivers of adult cognitive decline and maintenance.

Age Trajectories of Perceptual Speed and Loneliness: Separating Between-Person and Within-Person Associations

OBJECTIVES

We aimed at examining between-person and within-person associations across age trajectories of perceptual speed and loneliness in old age.

METHOD

We applied multilevel models to 4 waves of data collected over 6 years from 1,491 participants of the Berlin Aging Study II (60-88 years at baseline, 50% women) to disentangle between-person and within-person associations across age trajectories of perceptual speed and both emotional and social loneliness. Sex and education were considered as relevant individual characteristics and included as covariates in the model.

RESULTS

Analyses revealed that on average perceptual speed exhibited moderate within-person age-related declines, whereas facets of loneliness were rather stable. Perceptual speed did not predict age trajectories of emotional or social loneliness, at either the between- or within-person level. In contrast, loneliness discriminated individuals at the between-person level, such that those feeling emotionally or socially more lonely showed lower cognitive performance than those feeling emotionally or socially less lonely. Predictive effects of social loneliness were stronger for relatively young people (i.e., in their mid to late 60s) than for relatively older participants (i.e., in their 80s). In addition, predictive effects of social loneliness for perceptual speed at the within-person level were modest and deviated in direction and size from between-person social loneliness effects among those in their mid- to late 60s, whereas they did not among those in their 80s.

DISCUSSION

We conclude that loneliness may serve as a precursor for basic cognitive functioning in old age and suggest routes for further inquiry.

Model of brain maintenance reveals specific change-change association between medial-temporal lobe integrity and episodic memory

Brain maintenance has been identified as a major determinant of successful memory aging. However, the extent to which brain maintenance in support of successful memory aging is specific to memory-related brain regions or forms part of a brain-wide phenomenon is unresolved. Here, we used longitudinal brain-wide gray matter MRI volumes in 262 healthy participants aged 55 to 80 years at baseline to investigate separable dimensions of brain atrophy, and explored the links of these dimensions to different dimensions of cognitive change. We statistically adjusted for common causes of change in both brain and cognition to reveal a potentially unique signature of brain maintenance related to successful memory aging. Critically, medial temporal lobe (MTL)/hippocampal change and episodic memory change were characterized by unique, residual variance beyond general factors of change in brain and cognition, and a reliable association between these two residualized variables was established (r = 0.36, p < 0.01). The present study is the first to provide solid evidence for a specific association between changes in (MTL)/hippocampus and episodic memory in normal human aging. We conclude that hippocampus-specific brain maintenance relates to the specific preservation of episodic memory in old age, in line with the notion that brain maintenance operates at both general and domain-specific levels.

Epigenome-wide association study of level and change in cognitive abilities from midlife through late life

Background

Epigenetic mechanisms are important in aging and may be involved in late-life changes in cognitive abilities. We conducted an epigenome-wide association study of leukocyte DNA methylation in relation to level and change in cognitive abilities, from midlife through late life in 535 Swedish twins.

Results

Methylation levels were measured with the Infinium Human Methylation 450 K or Infinium MethylationEPIC array, and all sites passing quality control on both arrays were selected for analysis (n = 250,816). Empirical Bayes estimates of individual intercept (age 65), linear, and quadratic change were obtained from latent growth curve models of cognitive traits and used as outcomes in linear regression models. Significant sites (p < 2.4 × 10^–7) were followed up in between-within twin pair models adjusting for familial confounding and full-growth modeling. We identified six significant associations between DNA methylation and level of cognitive abilities at age 65: cg18064256 (PPP1R13L) with processing speed and spatial ability; cg04549090 (NRXN3) with spatial ability; cg09988380 (POGZ), cg25651129 (-), and cg08011941 (ENTPD8) with working memory. The genes are involved in neuroinflammation, neuropsychiatric disorders, and ATP metabolism. Within-pair associations were approximately half that of between-pair associations across all sites. In full-growth curve models, associations between DNA methylation and cognitive level at age 65 were of small effect sizes, and associations between DNA methylation and longitudinal change in cognitive abilities of very small effect sizes.

Conclusions

Leukocyte DNA methylation was associated with level, but not change in cognitive abilities. The associations were substantially attenuated in within-pair analyses, indicating they are influenced in part by genetic factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01075-9.

Non-alcoholic fatty liver disease and cognitive function in middle-aged adults: the CARDIA study

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is associated with cardiovascular disease (CVD) risk factors that have been linked to cognitive decline. Whether NAFLD is associated with cognitive performance in midlife remains uncertain.

METHODS

Coronary Artery Risk Development in Young Adults study participants with CT examination and cognitive assessment at Y25 (2010-2011; n = 2809) were included. Cognitive function was reassessed at Y30. NAFLD was defined according to liver attenuation and treated both continuously and categorically (using ≤ 40 and ≤ 51 Hounsfield units to define severity) after exclusion for other causes of liver fat. Cognitive tests including the Digit Symbol Substitution (processing speed), Rey Auditory Verbal Learning (verbal memory), and Stroop (executive function) were analyzed with standardized z-scores. Linear models were constructed to (a) examine the cross-sectional associations of NAFLD with cognitive scores and (b) evaluate its predictive role in 5-year change in cognitive performance.

RESULTS

Participants' mean age (Y25) was 50.1 (SD 3.6) years (57% female; 48% black), with 392 (14%) having mild NAFLD and 281 (10%) having severe NAFLD. NAFLD was positively associated with CVD risk factors and inversely associated with cognitive scores. However, after adjustment for CVD risk factors, no associations were shown between NAFLD and cognitive scores (all βs ≈ 0). Similarly, no associations were observed with 5-year cognitive decline. CVD history, hypertension, smoking, diabetes and hypertriglyceridemia showed stronger associations with baseline cognitive scores and were predictive of subsequent cognitive decline (all P ≤ .05).

CONCLUSION

Among middle-aged adults, inverse associations between NAFLD and cognitive scores were attenuated after adjustment for CVD risk factors, with the latter predictive of poorer cognitive performance both at baseline and follow-up.

Metacognitive Awareness Scale, Domain Specific (MCAS-DS): Assessing Metacognitive Awareness During Raven's Progressive Matrices

Metacognition, the cognition about cognition, is closely linked to intelligence and therefore understanding the metacognitive processes underlying intelligence test performance, specifically on Raven's Progressive Matrices, could help advance the knowledge about intelligence. The measurement of metacognition, is often done using domain-general offline questionnaires or domain-specific online think-aloud protocols. This study aimed to investigate the relationship between metacognitive awareness and intelligence via the design and use of a novel Meta-Cognitive Awareness Scale - Domain Specific (MCAS-DS) that encourages reflection of task strategy processes. This domain-specific scale was first constructed to measure participants' awareness of their own metacognition linked to Raven's Progressive Matrices (SPM). Following discriminatory index and Exploratory Factor Analysis, a 15-item scale was derived. Exploratory Factor Analysis showed five factors: Awareness of Engagement in Self-Monitoring, Awareness of Own Ability, Awareness of Responding Speed/Time, Awareness of Alternative Solutions and Awareness of Requisite Problem-Solving Resources. The intelligence level of ninety-eight adults was then estimated using Raven's Standard Progressive Matrices. Participants also completed the MCAS-DS, and further items that examined their test-taking behavior and Confidence level. Metacognitive awareness was positively correlated to standardized IQ scores derived from the SPM whilst Over-Confidence derived using the Confidence level measure was negatively correlated to SPM. Despite some limitations, this study shows promise for elucidating the relationship between metacognitive awareness and intelligence using the task-specific scale.

Continuity and Discontinuity in Human Cortical Development and Change From Embryonic Stages to Old Age

The human cerebral cortex is highly regionalized, and this feature emerges from morphometric gradients in the cerebral vesicles during embryonic development. We tested if this principle of regionalization could be traced from the embryonic development to the human life span. Data-driven fuzzy clustering was used to identify regions of coordinated longitudinal development of cortical surface area (SA) and thickness (CT) (n = 301, 4-12 years). The principal divide for the developmental SA clusters extended from the inferior-posterior to the superior-anterior cortex, corresponding to the major embryonic morphometric anterior-posterior (AP) gradient. Embryonic factors showing a clear AP gradient were identified, and we found significant differences in gene expression of these factors between the anterior and posterior clusters. Further, each identified developmental SA and CT clusters showed distinguishable life span trajectories in a larger longitudinal dataset (4-88 years, 1633 observations), and the SA and CT clusters showed differential relationships to cognitive functions. This means that regions that developed together in childhood also changed together throughout life, demonstrating continuity in regionalization of cortical changes. The AP divide in SA development also characterized genetic patterning obtained in an adult twin sample. In conclusion, the development of cortical regionalization is a continuous process from the embryonic stage throughout life.

Polygenic predictors of age-related decline in cognitive ability

Polygenic scores can be used to distil the knowledge gained in genome-wide association studies for prediction of health, lifestyle, and psychological factors in independent samples. In this preregistered study, we used fourteen polygenic scores to predict variation in cognitive ability level at age 70, and cognitive change from age 70 to age 79, in the longitudinal Lothian Birth Cohort 1936 study. The polygenic scores were created for phenotypes that have been suggested as risk or protective factors for cognitive ageing. Cognitive abilities within older age were indexed using a latent general factor estimated from thirteen varied cognitive tests taken at four waves, each three years apart (initial n = 1091 age 70; final n = 550 age 79). The general factor indexed over two-thirds of the variance in longitudinal cognitive change. We ran additional analyses using an age-11 intelligence test to index cognitive change from age 11 to age 70. Several polygenic scores were associated with the level of cognitive ability at age-70 baseline (range of standardized β-values = -0.178 to 0.302), and the polygenic score for education was associated with cognitive change from childhood to age 70 (standardized β = 0.100). No polygenic scores were statistically significantly associated with variation in cognitive change between ages 70 and 79, and effect sizes were small. However, APOE e4 status made a significant prediction of the rate of cognitive decline from age 70 to 79 (standardized β = -0.319 for carriers vs. non-carriers). The results suggest that the predictive validity for cognitive ageing of polygenic scores derived from genome-wide association study summary statistics is not yet on a par with APOE e4, a better-established predictor.

Social Resources as Compensatory Cognitive Reserve? Interactions of Social Resources With Education in Predicting Late-Life Cognition

OBJECTIVE

Access to social relationships has been linked with better cognitive performance. We examined whether social resources interact with education to predict cognitive outcomes, which could indicate that social resources fulfill a compensatory role in promoting cognitive reserve.

METHOD

We applied multilevel growth models to 6-wave, 13-year longitudinal data from the Berlin Aging Study (aged 70-103 years at first occasion; M = 84.9 years, 50% women) and have taken into account key individual difference factors, including sociodemographic variables, medically diagnosed comorbidities, and depressive symptoms. To account for possible reverse causality, analyses were conducted on a subset of the BASE participants without dementia (n = 368), and in follow-up analyses with the full sample (n = 516) using wave-specific longitudinal assessments of probable dementia status as a covariate.

RESULTS

Larger networks were associated with better performance on tests of perceptual speed and verbal fluency, but did not interact with education, providing little support for a compensatory reserve hypothesis. An interaction of education with emotional loneliness emerged in the prediction of perceptual speed, suggesting that the educational divide in speed was minimal among people who reported lower levels of loneliness.

DISCUSSION

We discuss our results in the context of differential implications of social resources for cognition and consider possible mechanisms underlying our findings.

APOE ε4 allele accelerates age-related multi-cognitive decline and white matter damage in non-demented elderly

Advanced age and apolipoprotein E (APOE) ε4 allele are both associated with increased risk of the Alzheimer’s disease (AD). However, the extent of the joint contribution of APOE ε4 allele and age on the brain white matter integrity, cognition and their relationship are unclear. We assessed the age-related variation differences of major cognitions in 846 non-demented elderly, and brain major white matter tracts in an MRI sub-cohort of 111 individuals between ε4 carriers and noncarriers. We found that: (i) carriers showed a steeper age-related decline after age 50 in general mental status, attention, language, and executive function and performed worse than noncarriers at almost all ages; (ii) main effect of age on anterior fibers, but main effect of APOE ε4 on posterior fibers, and the interactive effect of them existed on anterior and posterior fibers; (iii) carriers showed an accelerated age-related integrity reduction of these fibers compared to noncarriers who had a slight decrease but not significant; and (iv) significant associations of the higher white matter integrity with better multi-cognitive performance in old ε4 carriers. Overall, combining APOE status with age may be useful in assessing possible mechanisms of disease development in AD.

The relationship between cognitive decline and a genetic predictor of educational attainment

Genetic and environmental factors both make substantial contributions to the heterogeneity in individuals’ levels of cognitive ability. Many studies have examined the relationship between educational attainment and cognitive performance and its rate of change. Yet there remains a gap in knowledge regarding whether the effect of genetic predictors on individual differences in cognition becomes more or less prominent over the life course. In this analysis of over 5000 older adults from the Health and Retirement Study (HRS) in the U.S., we measured the change in performance on global cognition, episodic memory, attention & concentration, and mental status over 14 years. Growth curve models are used to evaluate the association between a polygenic risk score for education (education PGS) and cognitive change. Using the most recent education PGS, we find that individuals with higher scores perform better across all measures of cognition in later life. Education PGS is associated with a faster decline in episodic memory in old age. The relationships are robust even after controlling for phenotypic educational attainment, and are unlikely to be driven by mortality bias. Future research should consider genetic effects when examining non-genetic factors in cognitive decline. Our findings represent a need to understand the mechanisms between genetic endowment of educational attainment and cognitive decline from a biological angle.

•

Older adults with higher scores perform better across all measures of cognition.

•

The relationship is robust after controlling for phenotypic educational attainment.

•

The genetic effect on episodic memory diminishes with age.

•

Future research should consider genetic effects when examining cognitive decline.

The CADM2 gene is associated with processing speed performance - evidence among elderly with type 2 diabetes

Objectives: Recent large-scale meta-analysis of genome-wide association studies (GWAS) from multiple cohorts, demonstrated the association of the single nucleotide polymorphism (SNP) rs17518584, with processing speed (measured by the Digit Symbol Substitution Test (DSST) or the Letter Digit Substitution Test (LDST)), at GWAS significance level. This SNP is located within the cell adhesion molecule 2 (CADM2) gene. We aimed to validate this finding in our sample of 944 cognitively normal Jewish elderly individuals with type 2 diabetes (T2D), a population which is at risk for cognitive decline and dementia.Methods: Using linear regression, we studied the association of rs17518584 with DSST performance, adjusting for demographic, T2D-related characteristics and cardiovascular factors. In secondary analyses, associations with performance in four cognitive domains (episodic memory, language/semantic categorisation, attention/working memory and executive function) and overall cognition were examined.Results: Controlling for sex, age at cognitive assessment, years of education and ancestry, we found a significant association of rs17518584 with DSST performance (P = 0.013), consistent with the originally reported effect direction. Results remained significant even when the additional covariates (T2D-related and cardiovascular factors) were included in the analysis (P = 0.034). Moreover, this SNP was significantly associated with performance in the cognitive domains of language/semantic categorisation and executive function, as well as overall cognition.Conclusions: Taken together, irrespective of T2D-related characteristics and cardiovascular factors, our findings provide independent support for the association of CADM2 SNP rs17518584 with processing speed (and demonstrate association with additional cognitive phenotypes), among cognitively normal elderly individuals with T2D.

The Role of Nutrition in Cognitive Function and Brain Ageing in the Elderly

PURPOSE OF REVIEW

The purposes of this review were to examine literature published over the last 5 years and to evaluate the role of nutrition in cognitive function and brain ageing, focussing on the Mediterranean diet (MeDi), Dietary Approaches to Stop Hypertension (DASH), and Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diets.

RECENT FINDINGS

Results suggest that higher adherence to a healthy dietary pattern is associated with preservation of brain structure and function as well as slower cognitive decline, with the MIND diet substantially slowing cognitive decline, over and above the MeDi and DASH diets. Whilst results to-date suggest adherence to a healthy diet, such as the MeDi, DASH, or MIND, is an important modifiable risk factor in the quest to develop strategies aimed at increasing likelihood of healthy brain ageing, further work is required to develop dietary guidelines with the greatest potential benefit for public health; a research topic of increasing importance as the world's population ages.

Coupled cognitive changes in adulthood: A meta-analysis

With advancing age, healthy adults typically exhibit decreases in performance across many different cognitive abilities such as memory, processing speed, spatial ability, and abstract reasoning. However, there are marked individual differences in rates of cognitive decline, with some adults declining steeply and others maintaining high levels of functioning. To move toward a comprehensive understanding of cognitive aging, it is critical to know whether individual differences in longitudinal changes interrelate across different cognitive abilities. We identified 89 effect sizes representing shared variance in longitudinal cognitive change from 22 unique datasets composed of more than 30,000 unique individuals, which we meta-analyzed using a series of multilevel metaregression models. An average of 60% of the variation in cognitive changes was shared across cognitive abilities. Shared variation in changes increased with age, from approximately 45% at age 35 years to approximately 70% at age 85 years. There was a moderate-to-strong correspondence (r = .49, congruence coefficient = .98) between the extent to which a variable indicated general intelligence and the extent to which change in that variable indicated a general factor of aging-related change. Shared variation in changes did not differ substantially across cognitive ability domain classifications. In a sensitivity analysis based on studies that carefully controlled for dementia, shared variation in longitudinal cognitive changes remained at upward of 60%, and age-related increases in shared variation in cognitive changes continued to be evident. These results together provide strong evidence for a general factor of cognitive aging that strengthens with advancing adult age. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Successful Memory Aging

For more than 50 years, psychologists, gerontologists, and, more recently, neuroscientists have considered the possibility of successful aging. How to define successful aging remains debated, but well-preserved age-sensitive cognitive functions, like episodic memory, is an often-suggested criterion. Evidence for successful memory aging comes from cross-sectional and longitudinal studies showing that some older individuals display high and stable levels of performance. Successful memory aging may be accomplished via multiple paths. One path is through brain maintenance, or relative lack of age-related brain pathology. Through another path, successful memory aging can be accomplished despite brain pathology by means of efficient compensatory and strategic processes. Genetic, epigenetic, and lifestyle factors influence memory aging via both paths. Some of these factors can be promoted throughout the life course, which, at the individual as well as the societal level, can positively impact successful memory aging.

Attained SES as a moderator of adult cognitive performance: Testing gene-environment interaction in various cognitive domains

We examined whether attained socioeconomic status (SES) moderated genetic and environmental sources of individual differences in cognitive performance using pooled data from 9 adult twin studies. Prior work concerning SES moderation of cognitive performance has focused on rearing SES. The current adult sample of 12,196 individuals (aged 27-98 years) allowed for the examination of common sources of individual differences between attained SES and cognitive performance (signaling potential gene-environment correlation mechanisms, rGE), as well as sources of individual differences unique to cognitive performance (signaling potential gene-environment interaction mechanisms, G × E). Attained SES moderated sources of individual differences in 4 cognitive domains, assessed via performance on 5 cognitive tests ranging 2,149 to 8,722 participants. Attained SES moderated common sources of influences for 3 domains and influences unique to cognition in all 4 domains. The net effect was that genetic influences on the common pathway tended to be relatively more important at the upper end of attained SES indicating possible active rGE, whereas, genetic influences for the unique pathway were proportionally stable or less important at the upper end of attained SES. As a noted exception, at the upper end of attained SES, genetic influences unique to perceptual speed were amplified and genetic influences on the common pathway were dampened. Accounting for rearing SES did not alter attained SES moderation effects on cognitive performance, suggesting mechanisms germane to adulthood. Our findings suggest the importance of gene-environment mechanisms through which attained SES moderates sources of individual differences in cognitive performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Genetic and environmental influences on household financial distress

Heterogeneity of household financial outcomes emerges from various individual and environmental factors, including personality, cognitive ability, and socioeconomic status (SES), among others. Using a genetically informative data set, we decompose the variation in financial management behavior into genetic, shared environmental and non-shared environmental factors. We find that about half of the variation in financial distress is genetically influenced, and personality and cognitive ability are associated with financial distress through genetic and within-family pathways. Moreover, genetic influences of financial distress are highest at the extremes of SES, which in part can be explained by neuroticism and cognitive ability being more important predictors of financial distress at low and high levels of SES, respectively.

Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker

Machine learning analysis of neuroimaging data can accurately predict chronological age in healthy people. Deviations from healthy brain ageing have been associated with cognitive impairment and disease. Here we sought to further establish the credentials of 'brain-predicted age' as a biomarker of individual differences in the brain ageing process, using a predictive modelling approach based on deep learning, and specifically convolutional neural networks (CNN), and applied to both pre-processed and raw T1-weighted MRI data. Firstly, we aimed to demonstrate the accuracy of CNN brain-predicted age using a large dataset of healthy adults (N = 2001). Next, we sought to establish the heritability of brain-predicted age using a sample of monozygotic and dizygotic female twins (N = 62). Thirdly, we examined the test-retest and multi-centre reliability of brain-predicted age using two samples (within-scanner N = 20; between-scanner N = 11). CNN brain-predicted ages were generated and compared to a Gaussian Process Regression (GPR) approach, on all datasets. Input data were grey matter (GM) or white matter (WM) volumetric maps generated by Statistical Parametric Mapping (SPM) or raw data. CNN accurately predicted chronological age using GM (correlation between brain-predicted age and chronological age r = 0.96, mean absolute error [MAE] = 4.16 years) and raw (r = 0.94, MAE = 4.65 years) data. This was comparable to GPR brain-predicted age using GM data (r = 0.95, MAE = 4.66 years). Brain-predicted age was a heritable phenotype for all models and input data (h² ≥ 0.5). Brain-predicted age showed high test-retest reliability (intraclass correlation coefficient [ICC] = 0.90-0.99). Multi-centre reliability was more variable within high ICCs for GM (0.83-0.96) and poor-moderate levels for WM and raw data (0.51-0.77). Brain-predicted age represents an accurate, highly reliable and genetically-influenced phenotype, that has potential to be used as a biomarker of brain ageing. Moreover, age predictions can be accurately generated on raw T1-MRI data, substantially reducing computation time for novel data, bringing the process closer to giving real-time information on brain health in clinical settings.

Childhood social class and cognitive aging in the Swedish Adoption/Twin Study of Aging

In this report we analyzed genetically informative data to investigate within-person change and between-person differences in late-life cognitive abilities as a function of childhood social class. We used data from nine testing occasions spanning 28 y in the Swedish Adoption/Twin Study of Aging and parental social class based on the Swedish socioeconomic index. Cognitive ability included a general factor and the four domains of verbal, fluid, memory, and perceptual speed. Latent growth curve models of the longitudinal data tested whether level and change in cognitive performance differed as a function of childhood social class. Between-within twin-pair analyses were performed on twins reared apart to assess familial confounding. Childhood social class was significantly associated with mean-level cognitive performance at age 65 y, but not with rate of cognitive change. The association decreased in magnitude but remained significant after adjustments for level of education and the degree to which the rearing family was supportive toward education. A between-pair effect of childhood social class was significant in all cognitive domains, whereas within-pair estimates were attenuated, indicating genetic confounding. Thus, childhood social class is important for cognitive performance in adulthood on a population level, but the association is largely attributable to genetic influences.

A longitudinal twin study of general cognitive ability over four decades

In this longitudinal study we examined the stability of general cognitive ability (GCA), as well as heterogeneity and genetic and environmental influences underlying individual differences in change. We investigated GCA from young adulthood through late midlife in 1,288 Vietnam Era Twin Study of Aging participants at ages ∼20, ∼56, and ∼62 years. The correlations among the 3 occasions ranged from .73 to .85, reflecting substantial stability. The heritability was significant on each of the 3 occasions and ranged from .59 to .66. The influence of the shared environment was not significant at any of the ages. The genetic correlations across the 3 occasions ranged from .95 to .99 and did not differ significantly from 1.0. The nonshared environmental correlations ranged from .21 to .47. Latent growth curve analysis was applied to characterize trajectories over the 42-year period. Slope was significantly different from 0 and indicated that there was modest change over time. There was a significant genetic influence on initial level of GCA (h2 = .67), but not change (h2 = .23). Genetic factors primarily contribute to stability, while change reflects the influence of nonshared environmental influences. There was a significant negative correlation between initial level of GCA and change (r = -.31). Latent class growth analysis identified 4 trajectories. In general, the 4 groups followed parallel trajectories and were differentiated mainly by differences in AFQT performance level at the time of military induction. (PsycINFO Database Record

Continuity of cognitive change across adulthood

Although cross-sectional (between-person) comparisons consistently reveal age-related cognitive declines beginning in early adulthood, significant declines in longitudinal (within-person) comparisons are often not apparent until age 60 or later. The latter results have led to inferences that cognitive change does not begin until late middle age. However, because mean change reflects a mixture of maturational and experiential influences whose contributions could vary with age, it is important to examine other properties of change before reaching conclusions about the relation of age to cognitive change. The present study was designed to examine measures of the stability, variability, and reliability of change, as well as correlations of changes in memory with changes in speed in 2,330 adults between 18 and 80 years of age. Despite substantial power to detect small effects, the absence of significant age differences in these properties suggests that cognitive change represents a qualitatively similar phenomenon across a large range of adulthood.

Do Cognitive and Physical Functions Age in Concert from Age 70 to 76? Evidence from the Lothian Birth Cohort 1936

The present study concerns the relation of mental and bodily characteristics to one another during ageing. The 'common cause' theory of ageing proposes that declines are shared across multiple, seemingly-disparate functions, including both physical and intellectual abilities. The concept of 'reserve' suggests that healthier cognitive (and perhaps bodily) functions from early in life are protective against the effects of senescence across multiple domains. In three waves of physical and cognitive testing data from the longitudinal Lothian Birth Cohort 1936 (n = 1,091 at age 70 years; n = 866 at 73; n = 697 at 76), we used multivariate growth curve modeling to test the 'common cause' and 'reserve' hypotheses. Support for both concepts was mixed: although levels of physical functions and cognitive functions were correlated with one another, physical functions did not decline together, and there was little evidence for shared declines in physical and mental functions. Early-life intelligence, a potential marker of system integrity, made a significant prediction of the levels, but not the slopes, of later life physical functions. These data suggest that common causes, which are likely present within cognitive functions, are not as far-reaching beyond the cognitive arena as has previously been suggested. They also imply that bodily reserve may be similar to cognitive reserve in that it affects the level, but not the slope, of ageing-related declines.

Predictors of ageing-related decline across multiple cognitive functions

It is critical to discover why some people's cognitive abilities age better than others'. We applied multivariate growth curve models to data from a narrow-age cohort measured on a multi-domain IQ measure at age 11 years and a comprehensive battery of thirteen measures of visuospatial, memory, crystallized, and processing speed abilities at ages 70, 73, and 76 years (n = 1091 at age 70). We found that 48% of the variance in change in performance on the thirteen cognitive measures was shared across all measures, an additional 26% was specific to the four ability domains, and 26% was test-specific. We tested the association of a wide variety of sociodemographic, fitness, health, and genetic variables with each of these cognitive change factors. Models that simultaneously included all covariates accounted for appreciable proportions of variance in the cognitive change factors (e.g. approximately one third of the variance in general cognitive change). However, beyond physical fitness and possession of the APOE e4 allele, very few predictors were incrementally associated with cognitive change at statistically significant levels. The results highlight a small number of factors that predict differences in cognitive ageing, and underscore that correlates of cognitive level are not necessarily predictors of decline. Even larger samples will likely be required to identify additional variables with more modest associations with normal-range heterogeneity in aging-related cognitive declines.

Little relation of adult age with cognition after controlling general influences

Both general (i.e., shared across different cognitive measures) and specific (i.e., unique to particular cognitive measures) influences can be postulated to contribute to the relations between adult age and measures of cognitive functioning. Estimates of general and specific influences on measures of memory, speed, reasoning, and spatial visualization were derived in cross-sectional (N = 5,014) and 3-occasion longitudinal (N = 1,353) data in adults between 18 and 99 years of age. Increased age was negatively associated with estimates of general influences on cognitive functioning in both the cross-sectional differences and the longitudinal changes. Furthermore, after statistically controlling general influences, the relations of age on the cognitive measures were much smaller than were those in the original measures. Results from these and other analytical procedures converge on the conclusion that adult age appears to have weak relations with specific measures of cognitive functioning, defined as independent of influences shared across different types of cognitive measures, and that this is true in both cross-sectional and longitudinal comparisons. An implication of these findings is that general, as well as domain-specific, influences should be considered when attempting to explain the relations of age on cognitive functioning. (PsycINFO Database Record

GWAS for executive function and processing speed suggests involvement of the CADM2 gene

To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32,070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.

Aging-related magnification of genetic effects on cognitive and brain integrity

Heritability studies document substantial genetic influences on cognitive performance and decline in old age. Increasing evidence shows that effects of genetic variations on cognition, brain structure, and brain function become stronger as people age. Disproportionate impairments are typically observed for older individuals carrying disadvantageous genotypes of different candidate genes. These data support the resource-modulation hypothesis, which states that genetic effects are magnified in persons with constrained neural resources, such as older adults. However, given that findings are not unequivocal, we discuss the need to address several factors that may resolve inconsistencies in the extant literature (gene-gene and gene-environment interactions, study populations, gene-environment correlations, and epigenetic mechanisms).

Genetic and environmental architecture of changes in episodic memory from middle to late middle age

Episodic memory is a complex construct at both the phenotypic and genetic level. Ample evidence supports age-related cognitive stability and change being accounted for by general and domain-specific factors. We hypothesized that general and specific factors would underlie change even within this single cognitive domain. We examined 6 measures from 3 episodic memory tests in a narrow age cohort at middle and late middle age. The factor structure was invariant across occasions. At both timepoints 2 of 3 test-specific factors (story recall, design recall) had significant genetic influences independent of the general memory factor. Phenotypic stability was moderate to high, and primarily accounted for by genetic influences, except for 1 test-specific factor (list learning). Mean change over time was nonsignificant for 1 test-level factor; 1 declined; 1 improved. The results highlight the phenotypic and genetic complexity of memory and memory change, and shed light on an understudied period of life.

Genetic complexity of episodic memory: a twin approach to studies of aging

Episodic memory change is a central issue in cognitive aging, and understanding that process will require elucidation of its genetic underpinnings. A key limiting factor in genetically informed research on memory has been lack of attention to genetic and phenotypic complexity, as if "memory is memory" and all well-validated assessments are essentially equivalent. Here we applied multivariate twin models to data from late-middle-aged participants in the Vietnam Era Twin Study of Aging to examine the genetic architecture of 6 measures from 3 standard neuropsychological tests: the California Verbal Learning Test-2, and Wechsler Memory Scale-III Logical Memory (LM) and Visual Reproductions (VR). An advantage of the twin method is that it can estimate the extent to which latent genetic influences are shared or independent across different measures before knowing which specific genes are involved. The best-fitting model was a higher order common pathways model with a heritable higher order general episodic memory factor and three test-specific subfactors. More importantly, substantial genetic variance was accounted for by genetic influences that were specific to the latent LM and VR subfactors (28% and 30%, respectively) and independent of the general factor. Such unique genetic influences could partially account for replication failures. Moreover, if different genes influence different memory phenotypes, they could well have different age-related trajectories. This approach represents an important step toward providing critical information for all types of genetically informative studies of aging and memory.

Structure and correlates of cognitive aging in a narrow age cohort

Aging-related changes occur for multiple domains of cognitive functioning. An accumulating body of research indicates that, rather than representing statistically independent phenomena, aging-related cognitive changes are moderately to strongly correlated across domains. However, previous studies have typically been conducted in age-heterogeneous samples over longitudinal time lags of 6 or more years, and have failed to consider whether results are robust to a comprehensive set of controls. Capitalizing on 3-year longitudinal data from the Lothian Birth Cohort of 1936, we took a longitudinal narrow age cohort approach to examine cross-domain cognitive change interrelations from ages 70 to 73 years. We fit multivariate latent difference score models to factors representing visuospatial ability, processing speed, memory, and crystallized ability. Changes were moderately interrelated, with a general factor of change accounting for 47% of the variance in changes across domains. Change interrelations persisted at close to full strength after controlling for a comprehensive set of demographic, physical, and medical factors including educational attainment, childhood intelligence, physical function, APOE genotype, smoking status, diagnosis of hypertension, diagnosis of cardiovascular disease, and diagnosis of diabetes. Thus, the positive manifold of aging-related cognitive changes is highly robust in that it can be detected in a narrow age cohort followed over a relatively brief longitudinal period, and persists even after controlling for many potential confounders.

Hormones as "difference makers" in cognitive and socioemotional aging processes

Aging is associated with well-recognized alterations in brain function, some of which are reflected in cognitive decline. While less appreciated, there is also considerable evidence of socioemotional changes later in life, some of which are beneficial. In this review, we examine age-related changes and individual differences in four neuroendocrine systems-cortisol, estrogen, testosterone, and oxytocin-as "difference makers" in these processes. This suite of interrelated hormonal systems actively coordinates regulatory processes in brain and behavior throughout development, and their level and function fluctuate during the aging process. Despite these facts, their specific impact in cognitive and socioemotional aging has received relatively limited study. It is known that chronically elevated levels of the stress hormone cortisol exert neurotoxic effects on the aging brain with negative impacts on cognition and socioemotional functioning. In contrast, the sex hormones estrogen and testosterone appear to have neuroprotective effects in cognitive aging, but may decrease prosociality. Higher levels of the neuropeptide oxytocin benefit socioemotional functioning, but little is known about the effects of oxytocin on cognition or about age-related changes in the oxytocin system. In this paper, we will review the role of these hormones in the context of cognitive and socioemotional aging. In particular, we address the aforementioned gap in the literature by: (1) examining both singular actions and interrelations of these four hormonal systems; (2) exploring their correlations and causal relationships with aspects of cognitive and socioemotional aging; and (3) considering multilevel internal and external influences on these hormone systems within the framework of explanatory pluralism. We conclude with a discussion of promising future research directions.

The Genetic Basis for Cognitive Ability, Memory, and Depression Symptomatology in Middle-Aged and Elderly Chinese Twins

The genetic influences on aging-related phenotypes, including cognition and depression, have been well confirmed in the Western populations. We performed the first twin-based analysis on cognitive performance, memory and depression status in middle-aged and elderly Chinese twins, representing the world's largest and most rapidly aging population. The sample consisted of 384 twin pairs with a median age of 50 years. Cognitive function was measured using the Montreal Cognitive Assessment (MoCA) scale; memory was assessed using the revised Wechsler Adult Intelligence scale; depression symptomatology was evaluated by the self-reported 30-item Geriatric Depression (GDS-30)scale. Both univariate and multivariate twin models were fitted to the three phenotypes with full and nested models and compared to select the best fitting models. Univariate analysis showed moderate-to-high genetic influences with heritability 0.44 for cognition and 0.56 for memory. Multivariate analysis by the reduced Cholesky model estimated significant genetic (rG = 0.69) and unique environmental (rE = 0.25) correlation between cognitive ability and memory. The model also estimated weak but significant inverse genetic correlation for depression with cognition (-0.31) and memory (-0.28). No significant unique environmental correlation was found for depression with other two phenotypes. In conclusion, there can be a common genetic architecture for cognitive ability and memory that weakly correlates with depression symptomatology, but in the opposite direction.

Multivariate modeling of body mass index, pulse pressure, systolic and diastolic blood pressure in Chinese twins

Systolic and diastolic blood pressure, pulse pressure (PP), and body mass index (BMI) are heritable traits in human metabolic health but their common genetic and environmental backgrounds are not well investigated. The aim of this article was to explore the phenotypic and genetic associations among PP, systolic blood pressure (SBP), diastolic blood pressure (DBP), and BMI. The studied sample contained 615 twin pairs (17-84 years) collected in the Qingdao municipality. Univariate and multivariate structural equation models were fitted for assessing the genetic and environmental contributions. The AE model combining additive genetic (A) and unique environmental (E) factors produced the best fit for each four phenotypes. Heritability estimated in univariate analysis ranged from 0.42 to 0.74 with the highest for BMI (95% CI 0.70-0.78), and the lowest for PP (95% CI 0.34-0.49). The multivariate model estimated (1) high genetic correlations for DBP with SBP (0.87), PP with SBP (0.75); (2) low-moderate genetic correlations between PP and DBP (0.32), each BP component and BMI (0.24-0.37); (3) moderate unique environmental correlation for PP with SBP (0.68) and SBP with DBP (0.63); (4) there was no significant unique environmental correlation between PP and BMI. Overall, our multivariate analyses revealed common genetic and environmental backgrounds for PP, BP, and BMI in Chinese twins.

Genetic and environmental variation in lung function drives subsequent variation in aging of fluid intelligence

Longitudinal studies document an association of pulmonary function with cognitive function in middle-aged and older adults. Previous analyses have identified a genetic contribution to the relationship between pulmonary function with fluid intelligence. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories for pulmonary function and fluid intelligence. Longitudinal data from the Swedish Adoption/Twin Study of Aging were available from 808 twins ranging in age from 50 to 88 years at the first wave. Participants completed up to six assessments covering a 19-year period. Measures at each assessment included spatial and speed factors and pulmonary function. Model-fitting indicated that genetic variance for FEV1 was a leading indicator of variation in age changes for spatial and speed factors. Thus, these data indicate a genetic component to the directional relationship from decreased pulmonary function to decreased function of fluid intelligence.