Journals of Gerontology Series A-Biological Sciences and Medical Sciences最新文献

Background: Studies using heterochronic parabiosis discovered that circulating factors mediate brain aging in animal models.

Methods: We assessed growth differentiation factors (GDF)-11 and GDF-8 using mass spectrometry and inhibitors follistatin and follistatin-like protein-3 (FSTL-3) with ELISA in the Cardiovascular Health Study (CHS; N = 1 506) and the Health, Aging and Body Composition (Health ABC) Study (N = 1 237). CLL-11 and beta-2 microglobulin (β2M) were measured with ELISA in a subset of 400 individuals in Health ABC. Associations were assessed with cognitive function, brain magnetic resonance imaging (MRI) findings (CHS only), and incident dementia using correlations, linear regression, and Cox proportional hazards models.

Results: In CHS, levels of GDF-11, GDF-8, and follistatin were not correlated cross-sectionally with the 3MSE or DSST, brain MRI findings of white matter hyperintensity, atrophy, or small infarcts, nor were they associated with incident dementia. FSTL-3 was modestly correlated with poorer cognitive function, greater white matter hyperintensities, and atrophy on MRI, as well as with incident dementia with an adjusted hazard ratio (HR) of 1.72 (95% CI = 1.13, 2.61) per doubling of FSTL-3. FSTL-3 was not associated with cognition or dementia in Health ABC, but GDF-8 was associated with both. The adjusted HR for incident dementia was 1.50 (95% CI = 1.07, 2.10) per doubling of GDF-8.

Conclusions: Total GDF-11 level was not related to cognition or dementia in older adults. Associations of GDF-8 with cognitive outcomes in Health ABC were not expected, but consistent with animal models. Associations of FSTL-3 with cognition, brain abnormalities, and incident dementia in CHS implicate TGFβ superfamily inhibition in the pathogenesis of dementia.

Background: Older adults with discordant biological and chronological ages (BA and CA) may vary in cognitive and physical function from those with concordant BA and CA.

Methods: To make our approach clinically accessible, we created easy-to-interpret participant groups in the Health, Aging, and Body Composition Study (N = 2 458, 52% female participants, 65% White participants, age: 73.5 ± 2.8) based on medians of CA, and a previously validated BA index comprised of readily available clinical tests. Joint models estimated associations of BA-CA group with cognition (Modified Mini-Mental State Examination [3MS] and Digit Symbol Substitution Test [DSST]) and frailty over 10 years.

Results: The sample included the following: 32%, Young group (BA and CA < median); 21%, Prematurely Aging group (BA ≥ median, CA < median), 27%, Old group (BA and CA ≥ median), and 20%, Resilient group (BA < median, CA ≥ median). In education-adjusted models of cognition, among those with CA < median, the Prematurely Aging group performed worse than the Young at baseline (3MS and DSST p < .0001), but among those with CA ≥ median, the Resilient group did not outperform the Old group (3MS p = .31; DSST p = .25). For frailty, the Prematurely Aging group performed worse than the Young group at baseline (p = .0001), and the Resilient group outperformed the Old group (p = .003). For all outcomes, groups did not differ on change over time based on the same pairwise comparisons (p ≥ .40).

Conclusions: Discordant BA and CA identify groups who have greater cognitive and physical functional decline or are more protected than their CA would suggest. This information can be used for risk stratification.

Background: Multidomain lifestyle interventions may slow aging as captured by deficit accumulation frailty indices; however, it is unknown whether benefits extend beyond intervention delivery.

Methods: We developed a deficit accumulation frailty index (FI-E) to span the 10 years that the Action for Health in Diabetes (Look AHEAD) randomized controlled clinical trial delivered interventions (a multidomain lifestyle intervention focused on caloric restriction, increased physical activity, and diet compared to a control condition) and to extend across an additional 8 years post-delivery. The study cohort included 5 145 individuals, aged 45-76 years at enrollment, who had type 2 diabetes and either obesity or overweight.

Results: Overall, FI-E scores were relatively lower among lifestyle participants throughout follow-up, averaging 0.0130 [95% confidence interval: 0.0104, 0.0156] (p < .001) less across the 18 years. During Years 1-8, the mean relative difference between control and lifestyle participants' FI-E scores was 0.0139 [0.0115, 0.0163], approximately 10% of the baseline level. During Years 9-18, this average difference was 0.0107 [0.0066, 0.0148]. Benefits were comparable for individuals grouped by baseline age and body mass index and sex but were not evident for those entering the trial with a history of cardiovascular disease.

Conclusions: Multidomain lifestyle intervention may slow biological aging long term, as captured by an FI-E. Clinical Trials Registration Number: NCT00017953.

Background: Despite known disparities in health status among older sexual and gender minority adults (OSGM), the prevalence of frailty is unknown. The aim of this study was to develop and validate a deficit-accumulation frailty index (AoU-FI) for the All of Us database to describe and compare frailty between OSGM and non-OSGM participants.

Methods: Developed using a standardized approach, the AoU-FI consists of 33 deficits from baseline survey responses of adults aged 50+. OSGM were self-reported as "not straight" or as having discordant gender and sex assigned at birth. Descriptive statistics characterized the AoU-FI. Regression was used to assess the association between frailty, age, and gender. Validation of the AoU-FI used Cox proportional hazard models to test the association between frailty categories (robust <0.15, 0.15 ≤ pre-frail ≤ 0.25, frail >0.25) and mortality.

Results: There were 9 110 OSGM and 67 420 non-OSGM with sufficient data to calculate AoU-FI; 41% OSGM versus 50% non-OSGM were robust, whereas 34% versus 32% were pre-frail, and 26% versus 19% were frail. Mean AoU-FI was 0.19 (95% confidence interval [CI]: 0.187, 0.191) for OSGM and 0.168 (95% CI: 0.167, 0.169) for non-OSGM. Compared to robust, odds of mortality were higher among frail OSGM (odds ratio [OR] 6.40; 95% CI: 1.84, 22.23) and non-OSGM (OR 3.96; 95% CI: 2.96, 5.29).

Conclusions: The AoU-FI identified a higher burden of frailty, increased risk of mortality, and an attenuated impact of age on frailty among OSGM compared to non-OSGM. Future work is needed to understand how frailty affects the OSGM population.

Alzheimer's disease (AD) is the most prevalent type of dementia globally. The accumulation of amyloid-beta (Aβ) extracellular senile plaques in the brain is one of the hallmark mechanisms found in AD. Aβ42 is the most damaging and aggressively aggregating Aβ isomer produced in the brain. Although Aβ42 has been extensively researched as a crucial peptide connected to the development of the characteristic amyloid fibrils in AD, the specifics of its pathophysiology are still unknown. Therefore, the main objective was to identify novel compounds that could potentially mitigate the negative effects of Aβ42. 3-[[(3S)-1,2,3,4-Tetrahydroisoquinoline-3-carbonyl]amino]propanoic acid (THICAPA) was identified as a ligand for Aβ42 and for reducing fibrillary Aβ42 aggregation. THICAPA also improved cell viability when administered to PC12 neuronal cells that were exposed to Aβ42. Additionally, this compound diminished Aβ42 toxicity in the current AD Drosophila model by rescuing the rough eye phenotype, prolonging the life span, and enhancing motor functions. Through next-generation RNA-sequencing, immune response pathways were downregulated in response to THICAPA treatment. Thus, this study suggests THICAPA as a possible disease-modifying treatment for AD.

Calorie restriction (CR) typically promotes a reduction in body mass, which correlates with increased lifespan. We evaluated the overall changes in survival, body mass dynamics, and body composition following long-term graded CR (580 days/19 months) in male C57BL/6J mice. Control mice (0% restriction) were fed ad libitum in the dark phase only (12-hour ad libitum [12AL]). CR groups were restricted by 10%-40% of their baseline food intake (10CR, 20CR, 30CR, and 40CR). Body mass was recorded daily, and body composition was measured at 8 time points. At 728 days/24 months, all surviving mice were culled. A gradation in survival rate over the CR groups was found. The pattern of body mass loss differed over the graded CR groups. Whereas the lower CR groups rapidly resumed an energy balance with no significant loss of fat or fat-free mass, changes in the 30 and 40CR groups were attributed to higher fat-free mass loss and protection of fat mass. Day-to-day changes in body mass were less variable under CR than for the 12AL group. There was no indication that body mass was influenced by external factors. Partial autocorrelation analysis examined the relationship between daily changes in body masses. A negative correlation between mass on Day 0 and Day +1 declined with age in the 12AL but not the CR groups. A reduction in the correlation with age suggested body mass homeostasis is a marker of aging that declines at the end of life and is protected by CR.

Background: The Health, Aging, and Body Composition Study is a longitudinal cohort study that started just over 25 years ago. This ground-breaking study tested specific hypotheses about the importance of weight, body composition, and weight-related health conditions for incident functional limitation in older adults.

Methods: Narrative review with analysis of ancillary studies, career awards, publications, and citations.

Results: Key findings of the study demonstrated the importance of body composition as a whole, both fat and lean mass, in the disablement pathway. The quality of the muscle in terms of its strength and its composition was found to be a critical feature in defining sarcopenia. Dietary patterns and especially protein intake, social factors, and cognition were found to be critical elements for functional limitation and disability. The study is highly cited and its assessments have been widely adopted in both observational studies and clinical trials. Its impact continues as a platform for collaboration and career development.

Conclusions: The Health ABC provides a knowledge base for the prevention of disability and promotion of mobility in older adults.

Background: Machine learning (ML) models can be used to predict future frailty in the community setting. However, outcome variables for epidemiologic data sets such as frailty usually have an imbalance between categories, that is, there are far fewer individuals classified as frail than as nonfrail, adversely affecting the performance of ML models when predicting the syndrome.

Methods: A retrospective cohort study with participants (50 years or older) from the English Longitudinal Study of Ageing who were nonfrail at baseline (2008-2009) and reassessed for the frailty phenotype at 4-year follow-up (2012-2013). Social, clinical, and psychosocial baseline predictors were selected to predict frailty at follow-up in ML models (Logistic Regression, Random Forest [RF], Support Vector Machine, Neural Network, K-nearest neighbor, and Naive Bayes classifier).

Results: Of all the 4 378 nonfrail participants at baseline, 347 became frail at follow-up. The proposed combined oversampling and undersampling method to adjust imbalanced data improved the performance of the models, and RF had the best performance, with areas under the receiver-operating characteristic curve and the precision-recall curve of 0.92 and 0.97, respectively, specificity of 0.83, sensitivity of 0.88, and balanced accuracy of 85.5% for balanced data. Age, chair-rise test, household wealth, balance problems, and self-rated health were the most important frailty predictors in most of the models trained with balanced data.

Conclusions: ML proved useful in identifying individuals who became frail over time, and this result was made possible by balancing the data set. This study highlighted factors that may be useful in the early detection of frailty.

Background: This study examines the relationship between various domains of sedentary behavior and subsequent cognitive function to evaluate whether different sedentary activities have specific associations with future cognitive performance.

Methods: Data were from 1 261 older adults participating in the Health, Aging, and Body Composition (Health ABC) Study between 1999/2000 and 2006/2007. Total sitting time (hours/day), reading time (hours/week), and TV time (≤27/≥28 h/wk) were self-reported at baseline and 3 years later. At follow-up, cognitive function was evaluated using the Teng Mini-Mental State Examination (3MS) and the Digit Symbol Substitution Test (DSST). Multivariable linear regression modeling examined the independent associations of baseline sedentary behaviors and 3-year change in those behaviors with cognitive function scores at follow-up, adjusting for important covariables.

Results: Baseline total sitting time was positively associated with 3MS (β = 0.14 ± 0.07; p < .05) and DSST (β = 0.20 ± 0.10; p < .05) scores at follow-up, as was reading time (β = 0.09 ± 0.03; p < .05 for 3MS score and β = 0.14 ± 0.04; p < 0.01 for DSST score). Participants who increased their TV watching time over 3 years had a significantly lower 3MS score (β = -1.45 ± 0.71; p < .05) at follow-up, compared with those who maintained a low level of TV time (referent). These findings were independent of age, sex, race, education level, health status, depressive symptoms, and physical activity.

Conclusion: Some types of sedentary behavior may have benefits for cognitive function in older age, thus highlighting the importance of measuring different domains of sitting time.