Biological Age Research Articles

Associations Between Deficit Accumulation Frailty and Baseline Markers of Lifestyle in the US POINTER Trial.

Multidomain lifestyle interventions may have the potential to slow biological aging as captured by deficit accumulation frailty indices. We describe the distribution and composition of the 49-component frailty index (FI) developed by the U.S. POINTER clinical trial team of investigators and assess its cross-sectional associations with sociodemographic factors and markers chosen to be representative of behaviors targeted by the trial's multidomain interventions. We draw baseline data from the 2111 volunteers enrolled in U.S. POINTER who were ages 60-79 years and at increased risk for cognitive decline. Frailty components were grouped into nine domains. Associations that FI scores and their domains had with behavioral markers were described with correlations and canonical correlation. The 25th, 50th, and 75th percentiles of the frailty index score distribution were 0.153, 0.189, and 0.235. Higher frailty scores tended to occur among individuals who were older, male, and living in areas of greater deprivation (all p<0.001). They were also associated with poorer self-reported diet, less physical activity, and higher Framingham risk scores (all p<0.001). Associations were diffusely distributed among the frailty component domains, indicating that no individual domain was dominating associations. The U.S. POINTER deficit accumulation frailty index had expected relationships with sociodemographic factors and sensitivity to the behaviors targeted by the trial's interventions. Our analysis supports its use as a secondary outcome to assess whether the multidomain interventions differentially impact an established marker of biological aging.

The role of patient-specific variables in protein corona formation and therapeutic efficacy in nanomedicine.

Despite their potential, the adoption of nanotechnology in therapeutics remains limited, with only around eighty nanomedicines approved in the past 30years. This disparity is partly due to the "one-size-fits-all" approach in medical design, which often overlooks patient-specific variables such as biological sex, genetic ancestry, disease state, environment, and age that influence nanoparticle behavior. Nanoparticles (NPs) must be transported through systemic, microenvironmental, and cellular barriers that vary across heterogeneous patient populations. Key patient-dependent properties impacting NP delivery include blood flow rates, body fat distribution, reproductive organ vascularization, hormone and protein levels, immune responses, and chromosomal differences. Understanding these variables is crucial for developing effective, patient-specific nanotechnologies. The formation of a protein corona around NPs upon exposure to biological fluids significantly alters NP properties, affecting biodistribution, pharmacokinetics, cytotoxicity, and organ targeting. The dynamics of the protein corona, such as time-dependent composition and formation of soft and hard coronas, depend on NP characteristics and patient-specific serum components. This review highlights the importance of understanding protein corona formation across different patient backgrounds and its implications for NP design, including sex, ancestry, age, environment, and disease state. By exploring these variables, we aim to advance the development of personalized nanomedicine, improving therapeutic efficacy and patient outcomes.

Through the Lens of Age: Using Dog Photographs to Uncover Welfare and Stress

This study evaluated the potential of using dogs’ apparent age, judged from photographs, as a non-invasive tool for assessing their welfare. Traditional welfare assessment methods often rely on behavioral and physiological indicators, which can be resource-intensive and invasive. This research explored whether apparent age, a measure used in humans to predict health and longevity, can also serve as an indicator of welfare in dogs by investigating its association with relative telomere length (RTL), a biomarker of biological aging. Photographs of 60 domestic dogs were evaluated by canine specialists and general volunteers via the citizen science platform Zooniverse. Participants estimated the age of 20 dogs from three different age categories: young (0–2 years), adult (2–5 years), and senior (6+ years). The accuracy of these predictions was compared to the dogs’ chronological ages and RTLs. Generalized linear models were used to assess factors influencing prediction accuracy, including the dogs’ age, sex, and origin. Results indicated that both specialists and volunteers reliably estimated the age of senior dogs, with no significant differences in accuracy between groups. Dogs with accurate apparent age estimates had RTLs matching their chronological age, while those with premature aging signs had shorter RTLs. This suggests apparent age could be a practical, non-invasive welfare assessment tool, offering a potentially accessible method for new welfare assessment protocols.

The Notable Role of Telomere Length Maintenance in Complex Diseases

Telomere length function serves as a critical biomarker for biological aging and overall health. Its maintenance is linked to cancer, neurodegenerative conditions, and reproductive health. This review mainly examines genetic variations and environmental influences on telomere dynamics, highlighting key regulatory genes and mechanisms. Advances in telomere measurement methodologies are also reviewed, underscoring the importance of precise telomere assessment for disease prevention and treatment. Telomerase activation offers potential for cellular lifespan extension and anti-aging effects, whereas its inhibition emerges as a promising therapeutic approach for cancer. Regulatory mechanisms of tumor suppressor genes on telomerase activity are analyzed, with a comprehensive overview of the current state and future potential of telomerase inhibitors. In addition, the association between telomeres and neurodegenerative diseases is discussed, detailing how telomere attrition heightens disease risk and outlining multiple pathways by which telomerase protects neurons from damage and apoptosis.

Human Supplementation with AM3, Spermidine, and Hesperidin Enhances Immune Function, Decreases Biological Age, and Improves Oxidative–Inflammatory State: A Randomized Controlled Trial

The positive effect of AM3, spermidine, and hesperidin, which have antioxidant and anti-inflammatory properties, on immunity is known, but their effect on the rate of aging, known as biological age (BA), is unclear. This work aims to test if the intake of a blend of AM3 (150 mg), spermidine (0.6 mg), and hesperidin (50 mg) for 2 months could decrease BA and improve immunity, redox, and inflammatory states. For this, 41 participants (30–63 years) were randomly divided into placebo and supplement groups. The supplement group took two capsules daily with AM3, spermidine, and hesperidin for two months, while the placebo group took capsules containing only calcium phosphate and talcum powder. Before and after the treatment, peripheral blood was collected. Immune function was assessed in leukocytes, redox state in whole-blood cells, erythrocytes, and plasma, and cytokine concentration in both mononuclear cell cultures and plasma. Finally, the Immunity Clock model was applied to determine BA. The results show that the intake of this blend improves the immune functions that constitute the Immunity Clock, decreasing BA by 11 years and reducing the oxidative–inflammatory state of the participants. Therefore, this supplement can be proposed as a strategy to rejuvenate BA and achieve healthy aging.

Adolescents and young adults with sickle cell disease exhibit accelerated aging with elevated T-cell p16INK4a expression.

People living with sickle cell disease (SCD) experience complications indicative of an accelerated aging phenotype typified by early decline in physical function and increased risk for age-related conditions. Cellular senescence, measured by expression of p16INK4a in peripheral T-lymphocytes, is recognized as one of the underlying contributors to organismal aging. To examine if cellular senescence is increased in SCD patients, we cross-sectionally measured and compared expression of p16 mRNA in peripheral blood T lymphocytes in 18 adolescents and young adults with SCD to 27 similarly aged individuals without SCD. Expression of p16 was dramatically higher in individuals with SCD vs. without SCD (10.1 vs. 8.7 log2 p16 units, respectively, p < 0.001) - a gap of 43 years in biological age - consistent with accelerated aging in the SCD population. Race was not associated with the increased p16 expression in the SCD group. These initial results suggest that individuals with SCD have a significantly higher cellular senescence burden which may contribute to premature aging, physiological decline, and excess morbidities. Additional longitudinal assessment and consideration for trials of senolytic therapies among individuals living with SCD and high p16 expression are warranted to improve their health span.

Sexual dimorphism, altered hippocampal glutamatergic neurotransmission, and cognitive impairment in APP knock-in mice.

It is well established that glutamatergic neurotransmission plays an essential role in learning and memory. Previous studies indicate that glutamate dynamics shift with Alzheimer's disease (AD) progression, contributing to negative cognitive outcomes. In this study, we characterized hippocampal glutamatergic signaling with age and disease progression in a knock-in mouse model of AD (APPNL-F/NL--F). At 2-4 and 18+ months old, male and female APPNL/NL, APPNL-F/NL-F, and C57BL/6 mice underwent cognitive assessment using Morris water maze (MWM) and Novel Object Recognition (NOR). Then, basal and 70 mM KCl stimulus-evoked glutamate release was measured in the dentate gyrus (DG), CA3, and CA1 regions of the hippocampus using a glutamate-selective microelectrode in anesthetized mice. Glutamate recordings support elevated stimulus-evoked glutamate release in the DG and CA3 of young APPNL-F/NL-F male mice that declined with age compared to age-matched control mice. Young female APPNL-F/NL-F mice exhibited increased glutamate clearance in the CA1 that slowed with age compared to age-matched control mice. Male and female APPNL-F/NL-F mice exhibited decreased CA1 basal glutamate levels, while males also showed depletion in the CA3. Cognitive assessment demonstrated impaired spatial cognition in aged male and female APPNL-F/NL-F mice, but only aged females displayed recognition memory deficits compared to age-matched control mice. These findings confirm a sex-dependent hyper-to-hypoactivation glutamatergic paradigm in APPNL-F/NL-F mice. Further, data illustrate a sexually dimorphic biological aging process resulting in a more severe cognitive phenotype for female APPNL-F/NL-F mice than their male counterparts. Research outcomes mirror that of human AD pathology and provide further evidence of divergent AD pathogenesis between sexes.

Aging and frailty are associated with inflammatory endotypic shifts in patients with chronic rhinosinusitis.

Frailty and aging are associated with a shift toward non-type 2 inflammation in chronic rhinosinusitis (CRS). Frailty-related shifts in sinonasal inflammatory mediators may be linked to biological senescence. Understanding the role of aging and frailty in CRS may have important treatment implications.

Migrant Deaths in California’s Borderlands, 2018–2023

Executive Summary We examine the deaths of undocumented migrants in southern California (i.e., San Diego and Imperial counties) for fiscal years (FYs) 2018–2023 using data obtained from the San Diego County Medical Examiner’s Office (SDCMEO) and Imperial County Coroner’s Office (ICCO). We recorded 314 deaths of undocumented migrants, with 157 in San Diego County (SDC) and 157 in Imperial County (IC). We describe trend fluctuations in migrant deaths and both the overall and county-specific proportions as they relate to causes of death and demographic characteristics (biological sex and age at death). Additionally, to capture the potential effects of the 2019 border wall expansion and COVID-19 pandemic on migrant deaths, we examined differences in these factors between two periods: FY 2018–2019 and FY 2020–2023. We conclude by comparing migrant deaths reported by the medicolegal authorities to estimates published by US Customs and Border Protection’s (CBP) Border Patrol for southern California. From 2018 to 2020, there were approximately 30 known migrant fatalities annually in California. This increased to about 88 deaths per year in 2021 and 2022 before dropping to 50 in 2023. Across the study period, the leading causes of death were drowning (35.4 percent), environmental exposure (23.6 percent), and blunt force trauma (16.9 percent), with the latter cause being largely associated with falls from the border wall. However, we found significant differences between SDC and IC. For instance, 51.6 percent of migrant deaths in IC were due to drowning, compared to 19.1 percent in SDC. Conversely, 21.7 percent of deaths in SDC were due to blunt force trauma, while just 12.1 percent of deaths in IC occurred in this manner. Overall, we found that 75.2 percent of decedents were male, 20.4 percent were female, and 4.5 percent were of unknown sex. Among cases in which a precise age at death was listed, the average age was 34.6 years. Nevertheless, sex and age differed by county in that SDC had a higher proportion of female decedents (28 percent in SDC vs. 12.7 percent in IC) and a higher average age at death (SDC x¯ = 36.8 vs. IC x¯ = 32.0). We also found significant differences between the two periods examined. Perhaps most striking, deaths due to blunt force trauma increased from 3.4 percent of cases in FY 2018–2019 to 19.9 percent of cases in FY 2020–2023. Decedent characteristics also appear to have changed across time. The share of male decedents decreased from 84.5 percent to 73.0 percent, while the share of females increased from 5.2 percent to 23.8 percent between the two periods, while the proportion of decedents ages 50 to 64 years increased significantly (from 4.7 percent to 12.7 percent). Finally, for FYs 2018–2022, CBP reported 25.6 percent fewer migrant deaths than medicolegal authorities in southern California. High numbers of migrant deaths in 2021 and 2022 can be attributed to circumstances during and following the COVID-19 pandemic, including a Trump Administration policy aimed at blocking access to the US asylum system. The expansion of the border wall during the Trump era may also explain increased migrant mortality in 2021 and 2022. Decreases in deaths in California in 2023 may be because of a novel entry location in the San Judas Break or result from a shift in migration trends toward other border states (i.e., Arizona, New Mexico, and Texas). County differences in drowning and blunt force trauma deaths were likely due to the presence of the All-American Canal in IC (drowning), and greater coverage of the pedestrian border wall in SDC (blunt force trauma), respectively. Although speculatory, the higher percentage of female decedents and older age of decedents in SDC may be because these vulnerable individuals perceive San Diego to be a safer route. Changes between FYs 2018–2019 and FYs 2020–2023 in blunt force trauma deaths (3.4 percent to 19.9 percent) are a result of falls from the newly expanded and constructed border wall. We suggest that after more than 30 years of implementation, the United States should eliminate the use of “deterrence” strategies to prevent further and unnecessary loss of life. Additionally, the following actions could reduce migrant mortality in California: installing buoys or other anti-drowning devices in the All-American Canal, making potentially life-saving resources (e.g., blankets and water) available on known migrant routes, and reducing the height of or removing the border barrier. We call for both CBP and medicolegal authorities to provide disaggregated data on migrant fatalities, which would facilitate an accurate accounting these deaths, increase understanding of where and why deaths occur, and therefore be used to support policy changes.

Abstract 4139115: Genomic, Phenomic, and Geographic Relationships with Leukocyte Telomere Length in the U.S. Yields New Insights for Neoplasms and Cardiometabolic Disease

Background: Leukocyte telomere length (LTL) is an age-related marker strongly associated with neoplasms and cardiometabolic disease. LTL is also intimately linked with clonal hematopoiesis of indeterminate potential (CHIP), a recently described risk factor for cardiovascular disease (CVD). However, population-scale investigations of LTL in diverse backgrounds are limited, and geolocational variance has not been studied. Method: LTL and CHIP were derived using blood-derived whole genome sequencing data from 244,819 diverse U.S. residents in the NIH All of Us Research Program (AoU). We performed association analyses of LTL with CHIP and other available health-related traits, Phecode, as well as geolocation data by ZIP code. Genome-wide association study (GWAS) of LTL in AoU and meta-analysis with UK Biobank were performed. All association tests were adjusted for age, sex, sequencing site, and the first 10 genetic principal components with multiple test corrections. Mediation analysis was adjusted for additional risk factors for CVD. Result: Among 244,819 AoU participants, 146,717 (59.9%) were female with mean (standard deviation) age 51.8 (±16) years. Estimated LTL correlated strongly with age, sex, and genetic ancestry in AoU. Socioeconomic status, lifestyle variables, anthropometry, blood biomarkers (e.g., lipids and glucose), and vital signs were associated with LTL in AoU. Phecode analysis showed LTL is associated with neoplasms and age-related conditions, including CVDs. LTL mediated some of the observed increased coronary artery disease risk among individuals with hematologic malignancies ( P &lt; 2 × 10 -16 ). Significantly longer LTL clustered in the West Coast and Central Midwest ( P = 0.001 and 0.033, respectively), while significantly shorter LTL clustered in the Southeast ( P = 0.001) (Figure). GWAS meta-analyses identified 197 loci, of which 36 (18%) were novel, including ancestry-specific loci. Rare variant aggregation test found 9 novel associated genes. Conclusions: LTL is a marker of biological age that is associated and interacts with neoplasms, CVDs, and its various risk factors, with notable geographic variability within the U.S. Germline genetic analyses of LTL yield new insights into drivers of LTL.

Persistent elevation of plasma markers of cellular senescence after hip fracture: a pilot longitudinal study

IntroductionHip fractures may result from and contribute to accelerated biological aging. We aimed to evaluate the impact of hip fracture and its surgery on the senescence-associated secretory phenotype (SASP) index, a composite of peripheral protein markers where higher scores are thought to indicate greater levels of cellular senescence and accelerated aging.MethodsWe examined the SASP index in plasma over 12 weeks post-surgery and its prediction of long-term post-surgical functional outcomes. We included 60 older adults: 20 recruited immediately after hip fracture surgery, and 40 comparison individuals who were either healthy or suffering chronic psychosocial stress (caregiving). We assessed 22 SASP biomarkers and calculated the SASP index score for each hip fracture participant immediately following fracture surgery and 4 and 12 weeks later. Functional recovery was assessed at 12, 26, and 52 weeks after hip replacement surgery.ResultsThe hip fracture group had higher SASP index scores than the comparison groups, after adjusting for potential confounding variables (p = 0.021). SASP index scores in hip fracture patients increased further by week 4 after surgery (p &amp;lt; 0.001), declining by week 12 but remaining elevated overall. However, the SASP index scores were not significantly associated with functional recovery after hip replacement surgery at 26 or 52 weeks after surgery. In conclusion, after hip fracture surgery SASP scores are elevated, continue to rise over time, and do not return to normal by 12 weeks post-surgery.DiscussionOur findings support the need to investigate this phenomenon of post-operative senescence, including whether novel interventions such as senolytics would help older adults facing major surgery.

Plasma proteomics-based brain aging signature and incident dementia risk.

Investigating brain-enriched proteins with machine learning methods may enable a brain-specific understanding of brain aging and provide insights into the molecular mechanisms and pathological pathways of dementia. The study aims to analyze associations of brain-specific plasma proteomic aging signature with risks of incident dementia. In 45,429 dementia-free UK Biobank participants at baseline, we generated a brain-specific biological age using 63 brain-enriched plasma proteins with machine learning methods. The brain age gap was estimated, and Cox proportional hazards models were used to study the association with incident all-cause dementia, Alzheimer's disease (AD), and vascular dementia. Per-unit increment in the brain age gap z-score was associated with significantly higher risks of all-cause dementia (hazard ratio [95% confidence interval], 1.67 [1.56-1.79], P < 0.001), AD (1.85 [1.66-2.08], P < 0.001), and vascular dementia (1.86 [1.55-2.24], P < 0.001), respectively. Notably, 2.1% of the study population exhibited extreme old brain aging defined as brain age gap z-score > 2, correlating with over threefold increased risks of all-cause dementia and vascular dementia (3.42 [2.25-5.20], P < 0.001, and 3.41 [1.05-11.13], P = 0.042, respectively), and fourfold increased risk of AD (4.45 [2.32-8.54], P < 0.001). The associations were stronger among participants with healthier lifestyle factors (all P-interaction < 0.05). These findings were corroborated by magnetic resonance imaging assessments showing that a higher brain age gap aligns global pathophysiology of dementia, including global and regional atrophy in gray matter, and white matter lesions (P < 0.001). The brain-specific proteomic age gap is a powerful biomarker of brain aging, indicative of dementia risk and neurodegeneration.

Healthy and Unhealthy Aging and the Human Microbiome.

An altered gut microbiome is a feature of many multifactorial diseases, and microbiome effects on host metabolism, immune function, and possibly neurological function are implicated. Increased biological age is accompanied by a change in the gut microbiome. However, age-related health loss does not occur uniformly across all subjects but rather depends on differential loss of gut commensals and gain of pathobionts. In this article, we summarize the known and possible effects of the gut microbiome on the hallmarks of aging and describe the most plausible mechanisms. Understanding and targeting these factors could lead to prolonging health span by rationally maintaining the gut microbiome.

Inflammaging, a targetable pathway for preventing cardiovascular diseases.

Inflammaging, characterized by persistent chronic inflammation in older adults, has emerged as a critical factor linked to age-related diseases such as cardiovascular diseases (CVDs), metabolic disorders, and cognitive decline, which collectively contribute to the leading causes of death globally. Elevated levels of cytokines, chemokines, and others inflammatory mediators characterize inflammaging and serve as indicators of biological age. Among the causes of inflammaging, deterioration of the immune system, mitochondrial dysfunction, dysbiosis, accumulation of DAMPs, together with genetic or epigenetic factors, contribute to inflammaging not only in CVD but also in other age-related conditions. This review examines the causes and consequences of inflammaging, particularly its implications for atherosclerosis and heart failure with preserved ejection fraction (HFpEF) and explores potential strategies to mitigate it in the onset of CVD.

Abstract 4121454: Machine-extractable Markers in Chest Radiograph to Predict Cardiovascular Risk in Screening Population

Introduction: Recent research has shown that AI is able to assess biological aging and cardiovascular disease (CVD) risk using chest radiographs. However, the lack of explainability of such deep learning algorithms hinders clinical utility and adoption. This motivates the current study which searches for and tests the use of machine extractable quantitative features in chest radiographs to predict CVD risk in population screening. Method: Chest radiograph measurements characterizing cardiomediastinal geometry, aortic calcification and tortuosity were handpicked for development of a segmentation-based feature extraction algorithm. The algorithm was applied on the PLCO lung screening dataset for analysis. The association between measurement-based imaging features, clinical characteristics (age, sex, BMI, smoking status, hypertension, diabetes, liver disease) with CVD mortality and 10-year major adverse cardiovascular events (MACE) were analysed by using proportional hazard regression, with feature selection done by LASSO. Result: Of 29,453 eligible subjects, 5693 subjects from a single study centre were used for fitting of all models. The median follow-up time was 19 years. A total of 32 imaging features were extracted and analysed. For both 10-year MACE and CVD mortality, model using imaging features, age, and sex performed similarly to model using conventional risk factors, and a deep learning chest radiograph CVD risk model. Two imaging features, mediastinal width at valve-level [HR 1.36 (1.23-1.50)] and maximal lateral displacement of descending aorta [HR 1.29 (1.18-1.42)] were found to be prognostic. To the best of our knowledge, these features have not been reported previously. Conclusion: Quantitative imaging features can predict CVD risk in chest radiograph similar to deep learning models while providing feature interpretability and explainability. Two novel imaging features prognostic of CVD risk were found and shown to be complementary to conventional risk factors.

Resilience to psychosocial stress and epigenetic aging in schizophrenia: findings from a pilot study.

Exposure to stress is known to affect biological aging as well as individuals' susceptibility to a wide variety of mental illnesses, such as schizophrenia. There is an established relationship between the onset of schizophrenia spectrum disorders (SSD) and biological aging. On the other hand, epigenetic modifications, such as DNA methylation (DNAm), are used as biomarkers for biological aging and were previously proven to be altered in schizophrenia. However, previous research did not consider the effect of psychosocial resilience to stress and its effect on aging in schizophrenia, which is what our study aims to address. For our pilot study, 65 schizophrenia patients were recruited and stress exposure and perception levels were assessed using the Social Readjustment Rating Scale (SRRS) and Perceived Stress Scale (PSS), respectively. Moreover, DNA was extracted from venous blood samples and 850,000 CpG loci were assessed for DNA methylation analysis. Average age of participants was 43.15 ± 13.32 years (55.4% male, 44.6% female). Linear regression plots showed significant correlation between SRRS and PSS scores as well as between biological and chronological ages (p < 0.05). The residuals from the two regression models were defined as the psychosocial resilience and DNAm age acceleration, respectively. Interestingly, DNAm age acceleration was inversely correlated with resilience to stress (p < 0.05). In conclusion, it appears that epigenetic age acceleration is associated with reduced resilience to stress in schizophrenia patients. Future studies should focus on establishing resilience effect on disease prognosis.

Frailty Trajectories Preceding Dementia in the US and UK.

An accessible marker of both biological age and dementia risk is crucial to advancing dementia prevention and treatment strategies. Although frailty is a candidate for that role, the nature of the relationship between frailty and dementia is not well understood. To clarify the temporal relationship between frailty and incident dementia by investigating frailty trajectories in the years preceding dementia onset. Participant data came from 4 prospective cohort studies: the English Longitudinal Study of Ageing, the Health and Retirement Study, the Rush Memory and Aging Project, and the National Alzheimer Coordinating Center. Data were collected between 1997 and 2024 and were analyzed from July 2023 to August 2024. The settings were retirement communities, national-level surveys, and a multiclinic-based cohort. Included individuals were 60 years or older and without cognitive impairment at baseline. Included individuals also had data on age, sex, education level, and ethnicity and a frailty index score calculated at baseline. Frailty was the main exposure, with participants' degrees of frailty quantified using retrospectively calculated frailty index scores. Incident all-cause dementia ascertained through physician-derived diagnoses, self- and informant-report, and estimated classifications based on combinations of cognitive tests. The participant number before exclusions was 87 737. After exclusions, data from 29 849 participants (mean [SD] age, 71.6 [7.7] years; 18 369 female [62%]; 257 963 person-years of follow-up; 3154 cases of incident dementia) were analyzed. Bayesian generalized linear mixed regression models revealed accelerations in frailty trajectories 4 to 9 years before incident dementia. Overall, frailty was positively associated with dementia risk (adjusted hazard ratios [aHRs] ranged from 1.18; 95% CI, 1.13-1.24 to 1.73; 95% CI, 1.57-1.92). This association held among participants whose time between frailty measurement and incident dementia exceeded the identified acceleration period (aHRs ranged from 1.18; 95% CI, 1.12-1.23 to 1.43; 95% CI, 1.14-1.80). These findings suggest that frailty measurements may be used to identify high-risk population groups for preferential enrolment into clinical trials for dementia prevention and treatment. Frailty itself may represent a useful upstream target for behavioral and societal approaches to dementia prevention.

Aspekte des Alter(n)s im Schwankzyklus Till Eulenspiegel

In society and in literature, age is often associated with positive (wisdom, life experience) or negative aspects (stubbornness, impatience). The article examines the extent to which the biological age influences social relationships, experiences and/or behaviour, and the reactions of the archetypal German prankster and his interaction partners.

Reproductive factors and biological aging: the association with all-cause and cause-specific premature mortality.

Are reproductive factors associated with biological aging, and does biological aging mediate the associations of reproductive factors with premature mortality? Multiple reproductive factors are related to phenotypic age acceleration (PhenoAge-Accel), while adherence to a healthy lifestyle mitigates these harmful effects; PhenoAge-Accel mediated the associations between reproductive factors and premature mortality. Accelerated aging is a key contributor to mortality, but knowledge about the effect of reproductive factors on aging is limited. This prospective cohort study included 223729 women aged 40-69years from the UK biobank in 2006-2010 and followed up until 12 November 2021. Reproductive factors were collected through a touchscreen questionnaire. Biological aging was assessed through PhenoAge-Accel. Multiple linear regression models were used to examine the relationships of reproductive factors with PhenoAge-Accel and estimate the modified effect of a healthy lifestyle. Furthermore, we applied mediation analysis to explore the mediating role of PhenoAge-Accel in the associations between reproductive factors and premature mortality. Early menarche (<12 years vs 13 years, β: 0.37, 95% CI: 0.30, 0.44), late menarche (≥15 years vs 13 years, β: 0.18, 95% CI: 0.11, 0.25), early menopause (<45 years vs 50-51 years, β: 0.62, 95% CI: 0.51, 0.72), short reproductive lifespan (<30 years vs 35-39 years, β: 0.81, 95% CI: 0.70, 0.92), nulliparity (vs two live births, β: 0.36, 95% CI: 0.30, 0.43), high parity (≥4 vs 2 live births, β: 0.49, 95% CI: 0.40, 0.59), early age at first live birth (<20 years vs 25-29 years, β: 0.66, 95% CI: 0.56, 0.75), and stillbirth (β: 0.51, 95% CI: 0.36, 0.65) were associated with increased PhenoAge-Accel. Furthermore, PhenoAge-Accel mediated 6.0%-29.7% of the associations between reproductive factors and premature mortality. Women with an unfavorable lifestyle and reproductive risk factors had the highest PhenoAge-Accel compared to those with a favorable lifestyle and without reproductive risk factors. The participants in the UK Biobank were predominantly of White ethnicity; thus, caution is warranted when generalizing these findings to other ethnic groups. Our findings reveal the harmful effects of multiple reproductive factors on biological aging and the mediating role of biological aging in the associations between reproductive factors and premature mortality. They highlight the significance of adhering to a healthy lifestyle to slow biological aging as a potential way to reduce premature mortality among women with reproductive risk factors. This study was funded by the National Natural Science Foundation of China (82003479, 82073660, 72204215), Hubei Provincial Natural Science Foundation of China (2023AFB663), Zhejiang Province Public Welfare Technology Application Research Project (GF22H269155), and China Postdoctoral Science Foundation (2019M662646, 2020T130220). The authors have no competing interests to disclose. N/A.

Exploring multi-omics and clinical characteristics linked to accelerated biological aging in Asian women of reproductive age: insights from the S-PRESTO study

BackgroundPhenotypic age (PhenoAge), a widely used marker of biological aging, has been shown to be a robust predictor of all-cause mortality and morbidity in different populations. Existing studies on biological aging have primarily focused on individual domains, resulting in a lack of a comprehensive understanding of the multi-systemic dysregulation that occurs in aging.MethodsPhenoAge was evaluated based on a linear combination of chronological age (CA) and 9 clinical biomarkers in 952 multi-ethnic Asian women of reproductive age. Phenotypic age acceleration (PhenoAgeAccel), an aging biomarker, represents PhenoAge after adjusting for CA. This study conducts an in-depth association analysis of PhenoAgeAccel with clinical, nutritional, lipidomic, gut microbiome, and genetic factors.ResultsHigher adiposity, glycaemia, plasma saturated fatty acids, kynurenine pathway metabolites, GlycA, riboflavin, nicotinamide, and insulin-like growth factor binding proteins were positively associated with PhenoAgeAccel. Conversely, a healthier diet and higher levels of pyridoxal phosphate, all-trans retinol, betaine, tryptophan, glutamine, histidine, apolipoprotein B, and insulin-like growth factors were inversely associated with PhenoAgeAccel. Lipidomic analysis found 132 lipid species linked to PhenoAgeAccel, with PC(O-36:0) showing the strongest positive association and CE(24:5) demonstrating the strongest inverse association. A genome-wide association study identified rs9864994 as the top genetic variant (P = 5.69E-07) from the ZDHHC19 gene. Gut microbiome analysis revealed that Erysipelotrichaceae UCG-003 and Bacteroides vulgatus were inversely associated with PhenoAgeAccel. Integrative network analysis of aging-related factors underscored the intricate links among clinical, nutritional and lipidomic variables, such as positive associations between kynurenine pathway metabolites, amino acids, adiposity, and insulin resistance. Furthermore, potential mediation effects of blood biomarkers related to inflammation, immune response, and nutritional and energy metabolism were observed in the associations of diet, adiposity, genetic variants, and gut microbial species with PhenoAgeAccel.ConclusionsOur findings provide a comprehensive analysis of aging-related factors across multiple platforms, delineating their complex interconnections. This study is the first to report novel signatures in lipidomics, gut microbiome and blood biomarkers specifically associated with PhenoAgeAccel. These insights are invaluable in understanding the molecular and metabolic mechanisms underlying biological aging and shed light on potential interventions to mitigate accelerated biological aging by targeting modifiable factors.