The journals of gerontology. Series A, Biological sciences and medical sciences最新文献

Background: Blood-based biomarkers for Alzheimer's disease (AD) pathology are appealing options in large population-based studies due to their low cost, minimal invasiveness, and feasibility of collection in non-clinical settings. Despite these benefits, blood-based biomarkers have lower test-retest reliability than neuroimaging measures like amyloid positron emission tomography (amyloid-PET) Centiloids; trade-offs in power and bias remain unexplored.

Methods: We use data from Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) studies, which include both amyloid-PET and blood-based measures, to assess differences in statistical power, required sample size, and bias when replacing a neuroimaging measure with a blood-based measure. We use simulations parameterized based on these studies to show potential implications of using plasma p-tau 181 or p-tau 217, blood-based AD biomarkers, in place of Centiloids from amyloid-PET, when the biomarker is either the exposure or the outcome in an analysis of interest.

Results: We demonstrated that substituting amyloid-PET Centiloids with a blood-based measure of p-tau can substantially reduce power, requiring 1.5 to 6.5 times the sample size to achieve 80% power compared to amyloid-PET. In addition, using a blood-based biomarker as the exposure can introduce significant regression dilution bias, attenuating estimated associations.

Conclusions: While blood-based biomarkers are lower cost and easier to collect than neuroimaging measures, their use as proxies for AD pathology may introduce substantial methodological challenges, depending on the p-tau isoform. Consideration of the sample sizes they necessitate and their potential for bias is critical for the design and interpretation of studies employing these biomarkers.

The cerebellum, traditionally recognized for motor coordination, may also contribute to cognitive and emotional regulation, as recent evidence indicates. However, the molecular and structural changes in the human cerebellum during healthy aging remain poorly understood. This study systematically investigated the molecular trajectories and structural alterations in the human cerebellum across the adult lifespan (20-80 years) by integrating cerebella transcriptomic data from 456 non-disease brains and MRI structural neuroimaging data from 264 disease-free subjects. Fuzzy clustering analyses uncovered nonlinear expression trajectories involving synaptic plasticity, metabolic regulation, and protein homeostasis, highlighting multiple critical biological turning points across different age periods. Differential gene expression analyses identified early downregulation of immediate early genes (eg, FOS, NPAS4, EGR1-3) and sustained activation of stress-response pathways changes that precede observable functional decline. Moreover, we identified an integrated "synaptic plasticity-stress homeostasis" module, where immediate early genes and heat shock proteins exhibit coordinated regulation whose efficiency progressively declines with age. MRI analyses showed a pronounced acceleration of cerebellar gray matter (GM) loss after age 70, with multiple subregions affected, highlighting the nonlinear trajectory of cerebellar structural aging. In combination with the transcriptomic findings, these results indicate that cerebellar aging comprises complex, stage-dependent molecular alterations accompanied by GM reductions in later decades. This collective evidence advances our understanding of cerebellar aging biology and highlights the synaptic-stress module as a promising molecular axis that may inform future strategies to support cerebellar function in older adults.

Background: Aging alters oral structures, affecting chewing and swallowing function. Oral function is increasingly recognized as an important component of systemic health outcomes in older individuals. Understanding age-related changes in oral function is crucial for oral health care. This study comprehensively evaluated the various oral function determinants and their age-related changes, identified key factors, and estimated the prevalence of poor oral functions.

Methods: A cross-sectional study of older individuals (n = 206) participated. Oral functions were objectively assessed through dental status, saliva secretion, orofacial muscle strength, masticatory performance, and swallowing function. Correlation analysis, cluster analysis, and multiple regression were employed to explore the complexities of oral function determinants and their interrelationships and to estimate the prevalence of poor oral functions.

Results: Correlation analysis showed significantly (p < .001) strong (rs = -0.79) to low (rs = -0.11) correlations between determinants of oral function. The cluster analysis successfully identified three major groups of oral function. Further, the multiple linear regression and backward elimination showed that chewing strokes, natural teeth, and tongue pressure (p < .001) were significant predictors of age. Additionally, the prevalence of older individuals with poor dental status, reduced tongue pressure strength, and low saliva secretion rate was estimated at 9.7%, 14.6%, and 8.3%, respectively.

Conclusions: Oral function determinants show age-related changes and have the potential to estimate the prevalence of poor oral functions in older individuals. These findings may be critical in identifying the phenotypic profile of people with poor oral function.

Background: Poor oral health among older adults may contribute to cardiovascular and dementia risk via systemic inflammation and cardiometabolic comorbidities. Financial constraints are a major driver of unmet dental care needs for older individuals. This study investigates whether having dental care needs that were unmet due to cost is associated with subsequent incidence of cardiovascular disease (CVD) or dementia among adults aged 55 and older.

Methods: Participants in the All of Us cohort (N = 98 787) who responded to a survey question on dental care needs that were unmet due to cost were followed up to 5.3 years via electronic health records for onset of myocardial infarction (MI), stroke, heart failure (HF), or dementia. We estimated outcome-specific hazard ratios (HRs), using Cox proportional-hazards models, adjusting for demographic, behavioral, and clinical covariates.

Results: After adjustment for demographic factors, individuals who reported unmet dental needs due to cost had relatively higher incidence of HF (HR = 1.45; 95% CI, 1.30-1.63), MI (HR = 1.37; 95% CI, 1.17-1.61), stroke (HR = 1.45; 95% CI, 1.24-1.70), and dementia (HR = 1.37; 95% CI, 1.05-1.76). These associations were attenuated after further adjusting for socioeconomic, behavioral, and clinical factors. We did not observe differences by gender, racial and ethnic identity, or periodontitis diagnosis. The estimated population attributable fraction suggested that eliminating financial barriers to dental care could prevent 2%-4% of each outcome among older adults.

Conclusion: Financial barriers to dental care may be an important determinant of CVD and dementia among aging populations.

Background: The impact of exposure to fine particulate matter (PM2.5) on post-discharge recovery in older adults already hospitalized for heart failure remains unclear. We evaluated associations between exposure to PM2.5 and days spent at home (DAH) as well as mortality in a nationwide representative sample of U.S. adults aged 65 years and older.

Methods: Data from 66 854 Medicare Fee-for-service beneficiaries with heart failure hospitalization (2017-2019) were linked with validated, model-derived mean PM2.5 concentrations at Zip Code Tabulation Areas level during the month of hospital admission. Post-discharge 180-day DAH was defined as days alive minus days spent in inpatient hospitals, hospital observation units, nursing facilities, or emergency departments. All-cause mortality was assessed as time from hospital discharge to death within 180 days. Quantile regression and Cox proportional regression models, adjusted for covariates, were used to quantify associations.

Results: Exposure to the highest quartile PM2.5 level (>8.61 µg/m3) was associated with 5.05 fewer DAH (95% CI: -8.61, -1.48; p = .006) after discharge at the 20th percentile of DAH, compared with those exposed to the lowest PM2.5 quartile (≤5.90 µg/m3). Exposure to the highest quartile PM2.5 levels was also associated with higher risk of all-cause mortality within 180 days after hospitalization as compared to the lowest PM2.5 quartile (hazard ratio = 1.05, 95% CI: 1.004-1.10, p = .033).

Conclusions: Particulate air pollution may negatively impact recovery more strongly at the lower tail of recovery than at the median or higher tail, highlighting the need for targeted intervention strategies to protect the most vulnerable patients.

Aging is a heterogeneous phenomenon provoked by biological processes that still need to be fully understood. Frailty is a relevant outcome of aging reflecting biological decline that can be quantified through indices measuring the accumulation of functional deficits. Age-related declines may occur across multiple domains of functioning, and longitudinal study designs may better characterize decline within aging individuals. Thus, it is imperative to characterize how frailty indices that capture different functional domains associate with one another over the natural lifespan and across study designs. Here, the clinical frailty index (CFI) and the mouse social frailty index (mSFI) were applied to male and female mice both longitudinally and cross-sectionally over the lifespan. An overall similar association with aging was apparent: within each cohort, both CFI and mSFI were strongly positively associated with age. The utility of the CFI and mSFI as age predictors within the longitudinal study was confirmed. Critically, a model developed within the longitudinal study based on CFI scores, mSFI scores, and sex was able to predict age better than alternative models using only one of the indices. This result suggests that the CFI and the mSFI capture intrinsically different elements of deficit accumulation with age. The same model also showed a good performance in predicting the age of mice in the cross-sectional study. Overall, these results demonstrate that the information captured by both frailty indices is relevant to aging, relationships between indices vary across study design, and both frailty domains are needed to produce better age predictions.

Background: Frailty has been increasingly recognized as a significant contributor to adverse cardiovascular outcomes. However, the metabolic mechanisms underlying this relationship remain unclear. This study aimed to identify metabolomic signatures of frailty and their mediating roles in cardiovascular disease (CVD) risk.

Methods: Using data from 95 770 UK Biobank participants, we applied elastic net regularized regression to construct a frailty-related metabolomic signature score comprising 43 plasma metabolites across lipids, amino acids, fatty acids, and energy metabolism. Cox proportional hazards models were used to assess the association between this metabolomic signatures score and incident CVD, coronary heart disease (CHD), and stroke over a median follow-up of 13.81 years. Mediation analysis under a counterfactual framework was conducted to quantify the extent to which the metabolomic signatures mediated the frailty-CVD association.

Results: High metabolomic signature scores were significantly associated with increased risks of CVD (hazard ratio [HR] = 1.44; 95% confidence interval [CI]: 1.36-1.53), CHD (HR = 1.50; 95% CI: 1.41-1.61), and stroke (HR = 1.45; 95% CI: 1.37-1.54). Mediation analysis indicated that the metabolomic signature accounted for 14.9% of the association between frailty and overall CVD, 16.0% for CHD, and 16.9% for stroke. Pathway enrichment analysis revealed 7 metabolic pathways significantly enriched in frailty, with the primary associations implicating carbohydrate and amino acid metabolism.

Conclusions: This study highlights a distinct frailty-related metabolic profile that independently predicts cardiovascular risk and partially mediates the frailty-CVD association. These findings underscore the value of metabolomic profiling in guiding early detection and prevention strategies for frailty-related cardiovascular outcomes.

Background: Chronic inflammation in older adults is a key contributor to functional decline and mortality. Although anti-inflammatory medications have shown limited success in improving physical function, emerging targeted approaches offer new promise. We applied machine learning to identify clusters of older adults with shared patterns of inflammatory and cardiometabolic dysregulation and evaluated their responses to specific interventions.

Methods: We conducted a secondary analysis of the Enabling Reduction of low-grade Inflammation in Seniors (ENRGISE) multicenter, double-blind, placebo-controlled, factorial trial. This trial assessed the effects of losartan, omega-3, combination therapy, or placebo on interleukin-6 (IL-6) levels and 400-m walking speed. Key variables were selected using least absolute shrinkage and selection operator (LASSO), followed by linear regression to identify those significantly affecting the outcome slope. The optimal intervention was defined as the one that maximized the estimated slope improvement.

Results: We included 287 participants (47.4% female; mean age 77.6 ± 5.4 years) with a baseline IL-6 of 4.81 pg/mL. If all participants had received the recommended interventions, the estimated mean IL-6 slope would be -0.70 pg/mL/year (95% CI, -3.71, 1.41), compared to -0.51 pg/mL/year (-1.47, 0.35) among those randomized. The estimated improvement in walking speed was +0.0017 m/s/year (-0.0336, 0.0407) for the recommended interventions versus +0.0015 m/s/year (-0.0145, 0.0154) observed in the trial. For grip strength, the slope was -1.02 kg/year (-2.63, 0.57) for the recommended group and -1.02 kg/year (-1.79, -0.45) for the trial group.

Conclusion: Although results were not significant, our findings suggest that tailored interventions based on individuals' unique profiles may yield more favorable effects compared to non-tailored approaches. However, further powered studies should continue to explore precision medicine analytics and their potential to help identify more effective and personalized interventions.

Oxidative stress (OS) is a major feature of aging and is first brought on when the generation of Reactive oxygen species (ROS) surpasses the capacity of antioxidant defenses to neutralize them. Long-term exposure to ROS gradually damages vital biomolecules, resulting in the development of measurable biomarkers that indicate the degree of OS. Some forms of protein oxidation that impair enzymatic activity and interfere with cellular signaling are carbonyl compounds and advanced oxidation protein products. DNA is susceptible to OS, which can cause lesions like 8-hydroxy-2-deoxyguanosine, which indicates genomic instability and leads to cellular senescence and reduced function. Increased levels of lipid peroxidation byproducts, such as Malondialdehyde, 4-hydroxynonenal, and isoprostanes, indicate disturbed cellular balance and compromised membrane integrity. Additional information about the redox state can be found in antioxidant defenses. While important enzymatic antioxidants like glutathione peroxidase, catalase, and superoxide dismutase frequently show altered activity as one ages, indicating a reduced ability to counteract ROS, non-enzymatic antioxidants like glutathione, vitamins C and E, uric acid, bilirubin, and beta carotene provide extra defense but diminish with age. Combined, these biomarkers show how oxidative damage accumulates gradually and how the body's cellular defenses progressively deteriorate. By mapping their trajectories, we can better understand the biology of aging and develop targeted interventions and early detection tools to promote healthy aging. In this review, we summarized various OS biomarkers that help in the prediction of aging and age-related diseases.