Purpose of review

"Healthy aging" is the state of the aging process in which a person can maintain physical, social, mental, and spiritual wellness. This literature review presents an overview of recent studies that explore how biological, social, and environmental factors contribute to healthy aging.

Recent findings

A number of genome-wide association studies have been conducted recently for traits related to healthy aging, such as frailty index, healthspan, muscle strength, and parental longevity, leading to the discovery of dozens of genetic variants associated with these traits. In parallel, associations between healthy aging measures and multiple non-biological environmental elements have been identified as key moderators of the aging process, indirectly influencing day-to-day homeostatic processes.

Summary

Individual variations in lifespan and healthspan are influenced by genetic factors, with a heritability of ~ 25% in developed countries. Non-genetic risk variance is explained in part by social, cultural, and lifestyle conditions. Altogether, these factors contribute to a multifaceted state of wellness over time, shaping individual risk to frailty and resilience during the aging process. Notably, "Blue Zone" populations, which are characterized by an abundance in healthy lifestyles across generations, share some commonalities regarding determinants of health.

To generalize findings on the mechanisms and prognosis in Alzheimer's disease and related dementias (ADRD), it is critical for ADRD research to be representative of the population. Sociodemographic and health characteristics across ethnoracial groups included in the National Alzheimer's Coordinating Center sample (NACC) were compared to the nationally representative Health and Retirement Study (HRS).Baseline NACC data (n = 36,639) and the weighted 2010 HRS wave (N = 52,071,840) were included. We assessed covariate balance by calculating standardized mean differences across harmonized covariates (i.e., sociodemographic, health).NACC participants were older, more educated, with worse subjective memory and hearing, but endorsed fewer depressive symptoms compared to HRS participants. While all racial and ethnic groups in NACC differed from HRS participants in the same way overall, these differences were further amplified between racial and ethnic groups.NACC participants do not represent the U.S. population in key demographic and health factors, which differed by race and ethnicity.

Highlights

We examined selection factors included in NACC studies compared to a nationally representative sample.Selection factors included demographic and health factors and self-reported memory concerns.Results suggest that NACC participants are not representative of the U.S. population.Importantly, selection factors differed across racial and ethnic groups.Findings are suggestive of selection bias within NACC studies.

Objective: To investigate whether illiteracy was associated with greater risk of prevalent and incident dementia and more rapid cognitive decline among older adults with low education.

Methods: Analyses included 983 adults (≥65 years old, ≤4 years of schooling) who participated in a longitudinal community aging study. Literacy was self-reported ("Did you ever learn to read or write?"). Neuropsychological measures of memory, language, and visuospatial abilities were administered at baseline and at follow-ups (median [range] 3.49 years [0-23]). At each visit, functional, cognitive, and medical data were reviewed and a dementia diagnosis was made using standard criteria. Logistic regression and Cox proportional hazards models evaluated the association of literacy with prevalent and incident dementia, respectively, while latent growth curve models evaluated the effect of literacy on cognitive trajectories, adjusting for relevant demographic and medical covariates.

Results: Illiterate participants were almost 3 times as likely to have dementia at baseline compared to literate participants. Among those who did not have dementia at baseline, illiterate participants were twice as likely to develop dementia. While illiterate participants showed worse memory, language, and visuospatial functioning at baseline than literate participants, literacy was not associated with rate of cognitive decline.

Conclusion: We found that illiteracy was independently associated with higher risk of prevalent and incident dementia, but not with a more rapid rate of cognitive decline. The independent effect of illiteracy on dementia risk may be through a lower range of cognitive function, which is closer to diagnostic thresholds for dementia than the range of literate participants.

Frontotemporal dementia (FTD) has a complex genetic etiology, where the precise mechanisms underlying the selective vulnerability of brain regions remain unknown. We leveraged summary-based data from genome-wide association studies (GWAS) and performed LD score regression to estimate pairwise genetic correlations between FTD risk and cortical brain imaging. Then, we isolated specific genomic loci with a shared etiology between FTD and brain structure. We also performed functional annotation, summary-data-based Mendelian randomization for eQTL using human peripheral blood and brain tissue data, and evaluated the gene expression in mice targeted brain regions to better understand the dynamics of the FTD candidate genes. Pairwise genetic correlation estimates between FTD and brain morphology measures were high but not statistically significant. We identified 5 brain regions with a strong genetic correlation (rg > 0.45) with FTD risk. Functional annotation identified 8 protein-coding genes. Building upon these findings, we show in a mouse model of FTD that cortical N-ethylmaleimide sensitive factor (NSF) expression decreases with age. Our results highlight the molecular and genetic overlap between brain morphology and higher risk for FTD, specifically for the right inferior parietal surface area and right medial orbitofrontal cortical thickness. In addition, our findings implicate NSF gene expression in the etiology of FTD.

Background

Active lifestyles are related to better cognitive aging outcomes, yet the unique role of different types of activity are unknown.

Objective

To examine the independent contributions of physical (PA) versus cognitive (CA) leisure activities to brain and cognitive aging.

Methods

Independent samples of non-demented older adults from University of California, San Francisco Hillblom Aging Network (UCSF; n = 344 typically aging) and University of California, Davis Diversity cohort (UCD; n = 485 normal to MCI) completed: 1) self-reported engagement in current PA and CA (UCSF: Physical Activity Scale for the Elderly and Cognitive Activity Scale; UCD: Life Experiences Assessment Form); 2) neuropsychological batteries; and 3) neuroimaging total gray matter volume, white matter hyperintensities, and/or global fractional anisotropy. PA and CA were simultaneously entered into multivariable linear regression models, adjusting for demographic characteristics and functional impairment severity.

Results

Brain outcomes: In UCSF, only PA was positively associated with gray matter volume and attenuated the relationship between age and fractional anisotropy. In UCD, only CA was associated with less white matter hyperintensities and attenuated the relationship between age and gray matter volume. Cognitive outcomes: In both cohorts, greater CA, but not PA, related to better cognition, independent of age and brain structure. In UCSF, CA attenuated the relationship between fractional anisotropy and cognition. In UCD, PA attenuated the association between white matter hyperintensities and cognition.

Conclusions

Although their specificity was not easily teased apart, both PA and CA are clearly related to better brain and cognitive resilience markers across cohorts with differing educational, racial, and disease statuses. PA and CA may independently contribute to converging neuroprotective pathways for brain and cognitive aging.

The brain signature concept aims to characterize brain regions most strongly associated with an outcome of interest. Brain signatures derive their power from data-driven searches that select features based solely on performance metrics of prediction or classification. This approach has important potential to delineate biologically relevant brain substrates for prediction or classification of future trajectories. Recent work has used exploratory voxel-wise or atlas-based searches, with some using machine learning techniques to define salient features. These have shown undoubted usefulness, but two issues remain. The preponderance of recent work has been aimed at categorical rather than continuous outcomes, and it is rare for non-atlas reliant voxel-based signatures to be reported that would be useful for modelling and hypothesis testing. We describe a cross-validated signature region model for structural brain components associated with baseline and longitudinal episodic memory across cognitively heterogeneous populations including normal, mild impairment and dementia. We used three non-overlapping cohorts of older participants: from the UC Davis Aging and Diversity cohort (n = 255; mean age 75.3 ± 7.1 years; 128 cognitively normal, 97 mild cognitive impairment, 30 demented and seven unclassified); from Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 (n = 379; mean age 75.1 ± 7.2; 82 cognitively normal, 176 mild cognitive impairment, 121 Alzheimer's dementia); and from ADNI2/GO (n = 680; mean age 72.5 ± 7.1; 220 cognitively normal, 381 mild cognitive impairment and 79 Alzheimer's dementia). We used voxel-wise regression analysis, correcting for multiple comparisons, to generate an array of regional masks corresponding to different association strength levels of cortical grey matter with baseline memory and brain atrophy with memory change. Cognitive measures were episodic memory using Spanish and English Neuropsychological Assessment Scales instruments for UC Davis and ADNI-Mem for ADNI 1 and ADNI2/GO. Performance metric was the adjusted R2 coefficient of determination of each model explaining outcomes in two cohorts other than where it was computed. We compared within-cohort performances of signature models against each other and against other recent signature models of episodic memory. Findings were: (i) two independently generated signature region of interest models performed similarly in a third separate cohort; (ii) a signature region of interest generated in one imaging cohort replicated its performance level when explaining cognitive outcomes in each of other, separate cohorts; and (iii) this approach better explained baseline and longitudinal memory than other recent theory-driven and data-driven models. This suggests our approach can generate signatures that may be easily and robustly applied for modelling and hypothesis testing in mixed cognition cohorts.

STUDY OBJECTIVES: Despite its association with severe health conditions, the etiology of sleep apnea (SA) remains understudied. This study sought to identify genetic variants robustly associated with SA risk. METHODS: We performed a genome-wide association study (GWAS) meta-analysis of SA across five cohorts (NTotal = 523 366), followed by a multi-trait analysis of GWAS (multi-trait analysis of genome-wide association summary statistics [MTAG]) to boost power, leveraging the high genetic correlation between SA and snoring. We then adjusted our results for the genetic effects of body mass index (BMI) using multi-trait-based conditional and joint analysis (mtCOJO) and sought replication of lead hits in a large cohort of participants from 23andMe, Inc (NTotal = 1 477 352; Ncases = 175 522). We also explored genetic correlations with other complex traits and performed a phenome-wide screen for causally associated phenotypes using the latent causal variable method. RESULTS: Our SA meta-analysis identified five independent variants with evidence of association beyond genome-wide significance. After adjustment for BMI, only one genome-wide significant variant was identified. MTAG analyses uncovered 49 significant independent loci associated with SA risk. Twenty-nine variants were replicated in the 23andMe GWAS adjusting for BMI. We observed genetic correlations with several complex traits, including multisite chronic pain, diabetes, eye disorders, high blood pressure, osteoarthritis, chronic obstructive pulmonary disease, and BMI-associated conditions. CONCLUSION: Our study uncovered multiple genetic loci associated with SA risk, thus increasing our understanding of the etiology of this condition and its relationship with other complex traits.

INTRODUCTION: The Brazilian population in the United States (U.S.), a Latinx subgroup, is rapidly growing and aging but remains underrepresented in U.S. health research. In addition to group-specific genetic and environmental risks, Brazilian immigrants and their offspring in the U.S. likely have cumulative risks for health inequities.It is estimated that 71% of Brazilian immigrants in the U.S. are undocumented, which may limit healthcare access/utilization. Furthermore, mental health is reported as a health priority by Brazilian immigrants in the U.S., and there is a lack of research on Alzheimers disease and related dementia (AD/ADRD) in this population. METHODS: We reviewed the scientific literature using traditional (e.g., PubMed) sources and databases generated by U.S. and Brazilian governments, as well as international organizations, and press articles. RESULTS: This perspective review lists recommendations for researchers, health providers, and policymakers to promote greater inclusion of U.S. Brazilian populations in health research and care. The review identifies research areas in need of attention to address health inequities and promote mental/brain health in Brazilian immigrants and their offspring living in the U.S. These research areas are: 1) epidemiological studies to map the prevalence and incidence of mental/brain health conditions; 2) research on aging and AD/ADRD risk factors among Brazilian populations in the U.S.; and 3) the need for greater representation of U.S-residing Brazilian population in other relevant research areas involving genetics, neuropathology, and clinical trials. CONCLUSIONS: The recommendation and research efforts proposed should help to pave the way for the development of community-engagement research and to promote mental/brain health education, improvement of mental/brain health and AD/ADRD services, and the development of culturally-informed intervention to the U.S.-residing Brazilian communities. HIGHLIGHTS: The Brazilian population in the United States is growing but is underrepresented in U.S. health research.Approximately 71% of Brazilian immigrants in the United States are undocumented, with an increased risk for health inequities.Mental health is reported as a central health priority by Brazilian immigrants in the United States.There is a lack of research on Alzheimers disease and other dementias (ADRD) in Brazilian immigrants in the United States.Epidemiological research is needed to map the prevalence/incidence of mental health conditions and ADRD risk factors among Brazilian immigrants in the United States.

Background

As global populations age, cross-national comparisons of cognitive health and dementia risk are increasingly valuable. It remains unclear, however, whether country-level differences in cognitive function are attributable to population differences or bias due to incommensurate measurement. To demonstrate an effective method for cross-national comparison studies, we aimed to statistically harmonize measures of episodic memory and language function across two population-based cohorts of older adults in the United States (HRS HCAP) and India (LASI-DAD).

Methods

Data for 3,496 HRS HCAP (≥65 years) and 3,152 LASI-DAD (≥60 years) participants were statistically harmonized for episodic memory and language performance using confirmatory factor analysis (CFA) methods. Episodic memory and language factor variables were investigated for differential item functioning (DIF) and precision.

Results

CFA models estimating episodic memory and language domains based on a priori adjudication of comparable items fit the data well. DIF analyses revealed that four out of ten episodic memory items and five out of twelve language items measured the underlying construct comparably across samples. DIF-modified episodic memory and language factor scores showed comparable patterns of precision across the range of the latent trait for each sample.

Conclusions

Harmonization of cognitive measures will facilitate future investigation of cross-national differences in cognitive performance and differential effects of risk factors, policies, and treatments, reducing study-level measurement and administrative influences. As international aging studies become more widely available, advanced statistical methods such as those described in this study will become increasingly central to making universal generalizations and drawing valid conclusions about cognitive aging of the global population.

Background and aims

Disentangling the putative impact of cannabis on brain morphology from other comorbid substance use is critical. After controlling for the effects of nicotine, alcohol and multi-substance use, this study aimed to determine whether frequent cannabis use is associated with significantly smaller subcortical grey matter volumes.

Design

Exploratory analyses using mixed linear models, one per region of interest (ROI), were performed whereby individual differences in volume (outcome) at seven subcortical ROIs were regressed onto cannabis and comorbid substance use (predictors).

Setting

Two large population-based twin samples from the United States and Australia.

Participants

A total of 622 young Australian adults [66% female; μ_age  = 25.9, standard deviation SD) = 3.6] and 474 middle-aged US males (μ_age  = 56.1_SD = 2.6 ) of predominately Anglo-Saxon ancestry with complete substance use and imaging data. Subjects with a history of stroke or traumatic brain injury were excluded.

Measurements

Magnetic resonance imaging (MRI) and volumetric segmentation methods were used to estimate volume in seven subcortical ROIs: thalamus, caudate nucleus, putamen, pallidum, hippocampus, amygdala and nucleus accumbens. Substance use measurements included maximum nicotine and alcohol use, total life-time multi-substance use, maximum cannabis use in the young adults and regular cannabis use in the middle-aged males.

Findings

After correcting for multiple testing (P = 0.007), cannabis use was unrelated to any subcortical ROI. However, maximum nicotine use was associated with significantly smaller thalamus volumes in middle-aged males.

Conclusions

In exploratory analyses based on young adult and middle-aged samples, normal variation in cannabis use is unrelated statistically to individual differences in brain morphology as measured by subcortical volume.