Biological Age Predictors

Underlying Mechanisms of the Protective Effects of Lifestyle Factors in the Prevention of Age-Related Diseases

The rise in life expectancy has significantly increased the occurrence of age-related chronic diseases, leading to escalating expenses for both society and individuals. Among the main factors influencing health and lifespan, lifestyle takes a forefront position. Specifically, nutrition, mental activity, and physical exercise influence the molecular and functional mechanisms that contribute to the prevention of major age-related diseases. Gaining deeper insights into the mechanisms that drive the positive effects of healthy lifestyles is valuable for creating interventions to prevent or postpone the development of chronic degenerative diseases. This review summarizes the main mechanisms that underlie the positive effect of lifestyle factors in counteracting the major age-related diseases involving brain health, musculoskeletal function, cancer, frailty, and cardiovascular diseases, among others. This knowledge will help to identify high-risk populations for targeted intervention trials and discover new biomarkers associated with healthy aging.

Effect of Modifiable Lifestyle Factors on Biological Aging

Biological age is a concept that uses bio-physiological parameters to account for individual heterogeneity in the biological processes driving aging and aims to enhance the prediction of age-related clinical conditions compared to chronological age. Although engaging in healthy lifestyle behaviors has been linked to a lower mortality risk and a reduced incidence of chronic diseases, it remains unclear to what extent these health benefits result from slowing the pace of the biological aging process. This short review summarized how modifiable lifestyle factors - including diet, physical activity, smoking, alcohol consumption, and the aggregate of multiple healthy behaviors - were associated with established estimates of biological age based on clinical or cellular/molecular markers, including Klemera-Doubal Method biological age, homeostatic dysregulation, phenotypic age, DNA methylation age, and telomere length. In brief, the available studies tend to show a consistent association of lifestyle factors with physiological measures of biological age, while findings regarding molecular-based metrics vary. The limited evidence highlights the need for further research in this field, particularly with a life-course approach.

Effects from medications on functional biomarkers of aging in three longitudinal studies of aging in Sweden

Antihypertensive, lipid-lowering, and blood glucose-lowering drugs have slowed down the aging process in animal models. In humans, studies are limited, have short follow-up times, and show mixed results. Therefore, this study aimed to estimate the effects of commonly used medications on functional aging, cognitive function, and frailty. We included information on individuals from three Swedish longitudinal population-based studies collected between 1986 and 2014. Our exposures were the 21 most used groups of medications among individuals aged 65 years and older in the Swedish population in 2022. Functional aging index (n = 1191), cognitive function (n = 1094), and frailty index (n = 1361) were the outcomes of interest. To estimate the medication effects, we used a self-controlled analysis, where each individual is his/her own control, thereby adjusting for all time-stable confounders. The analysis was additionally adjusted for time-varying confounders (chronological age, Charlson Comorbidity Index, smoking, body mass index, and the number of drugs). The participants were 65.5-82.8 years at the first in-person assessment. Adrenergics/inhalants (effect size = 0.089) and lipid-modifying agents/plain (effect size = 0.082) were associated with higher values of cognitive function (improvement), and selective calcium channel blockers with mainly vascular effects (effect size = -0.129) were associated with lower values of the functional aging index (improvement). No beneficial effects were found on the frailty index. Adrenergics/inhalants, lipid-modifying agents/plain, and selective calcium channel blockers with mainly vascular effects may benefit functional biomarkers of aging. More research is needed to investigate their clinical value in preventing adverse aging outcomes.

The prognostic value of serum α-klotho in age-related diseases among the US population: A prospective population-based cohort study

Objective

α-Klotho is a potential biological marker of aging with satisfactory clinical applicability. However, its prognostic significance in age-related diseases has largely been undermined. Therefore, we aimed to report the prognostic value of serum α-klotho levels in age-related diseases.

Methods

Participants with available serum α-klotho data from the National Health and Nutrition Examination Survey (2007-2016) were included. Their survival status was collected at 7.62 ± 2.99 years after serum α-klotho data was collected, and the endpoint was all-cause and cardiovascular mortality. A Cox regression model was established to examine the association between serum α-klotho levels and all-cause and cardiovascular mortality.

Results

The present study included 13,746 U.S. adults with a survey-weighted mean age of 56.19 ± 10.42 years old. Of these, 52.2 % were female and 72.9 % were non-Hispanic whites. The optimal cutoff value of serum α-klotho for predicting all-cause mortality risk in the general population was 603.5 pg/ml. Individuals with low serum α-klotho (<603.5 pg/ml) had a significantly higher risk of all-cause (adjusted HR: 1.34(1.18-1.52), P < 0.001) and cardiovascular mortality (adjusted HR: 1.63(1.27-2.10), P < 0.001). Subgroup analysis showed that low serum α-klotho level was an independent risk factor for all-cause and cardiovascular mortality in people with hypertension, congestive heart failure, diabetes mellitus, and emphysema, while it was an independent risk factor for all-cause mortality in patients with renal insufficiency.

Conclusion

A low serum α-klotho concentration (<603.5 pg/ml) could serve as a marker of all-cause and cardiovascular mortality in the general population and in people with age-related diseases, including hypertension, congestive heart failure, diabetes mellitus, and emphysema.

An epigenetic toolbox for conservation biologists

Ongoing climatic shifts and increasing anthropogenic pressures demand an efficient delineation of conservation units and accurate predictions of populations' resilience and adaptive potential. Molecular tools involving DNA sequencing are nowadays routinely used for these purposes. Yet, most of the existing tools focusing on sequence-level information have shortcomings in detecting signals of short-term ecological relevance. Epigenetic modifications carry valuable information to better link individuals, populations, and species to their environment. Here, we discuss a series of epigenetic monitoring tools that can be directly applied to various conservation contexts, complementing already existing molecular monitoring frameworks. Focusing on DNA sequence-based methods (e.g. DNA methylation, for which the applications are readily available), we demonstrate how (a) the identification of epi-biomarkers associated with age or infection can facilitate the determination of an individual's health status in wild populations; (b) whole epigenome analyses can identify signatures of selection linked to environmental conditions and facilitate estimating the adaptive potential of populations; and (c) epi-eDNA (epigenetic environmental DNA), an epigenetic-based conservation tool, presents a non-invasive sampling method to monitor biological information beyond the mere presence of individuals. Overall, our framework refines conservation strategies, ensuring a comprehensive understanding of species' adaptive potential and persistence on ecologically relevant timescales.

Retirement Makes You Old? Causal Effect of Retirement on Biological Age

Retirement is a critical life event for older people. Health scholars have scrutinized the health effects of retirement, but its consequences on age-related diseases and mortality are unclear. We extend this body of research by integrating measurements of biological age, representing the physiological decline preceding disease onset. Using data from the UK Biobank and a fuzzy regression discontinuity design, we estimated the effects of retirement on two biomarker-based biological age measures. Results showed that retirement significantly increases biological age for those induced to retire by the State Pension eligibility by 0.871-2.503 years, depending on sex and specific biological age measurement. Given the emerging scientific discussion about direct interventions to biological age to achieve additional improvements in population health, the positive effect of retirement on biological age has important implications for an increase in the State Pension eligibility age and its potential consequences on population health, public health care policy, and older people's labor force participation. Overall, this study provides novel empirical evidence contributing to the question of what social factors make people old.

Systems Age: A single blood methylation test to quantify aging heterogeneity across 11 physiological systems

Individuals, organs, tissues, and cells age in diverse ways throughout the lifespan. Epigenetic clocks attempt to quantify differential aging between individuals, but they typically summarize aging as a single measure, ignoring within-person heterogeneity. Our aim was to develop novel systems-based methylation clocks that, when assessed in blood, capture aging in distinct physiological systems. We combined supervised and unsupervised machine learning methods to link DNA methylation, system-specific clinical chemistry and functional measures, and mortality risk. This yielded a panel of 11 system-specific scores- Heart, Lung, Kidney, Liver, Brain, Immune, Inflammatory, Blood, Musculoskeletal, Hormone, and Metabolic. Each system score predicted a wide variety of outcomes, aging phenotypes, and conditions specific to the respective system. We also combined the system scores into a composite Systems Age clock that is predictive of aging across physiological systems in an unbiased manner. Finally, we showed that the system scores clustered individuals into unique aging subtypes that had different patterns of age-related disease and decline. Overall, our biological systems based epigenetic framework captures aging in multiple physiological systems using a single blood draw and assay and may inform the development of more personalized clinical approaches for improving age-related quality of life.

Self-rated health, epigenetic ageing, and long-term mortality in older Australians

Self-rated health (SRH) is a subjective indicator of overall health based on a single questionnaire item. Previous evidence found that it is a strong predictor of mortality, although the underlying mechanism is poorly understood. Epigenetic age is an objective, emerging biomarker of health, estimated using DNA methylation data at hundreds of sites across the genome. This study aimed to assess the overlap and interaction between SRH and epigenetic ageing in predicting mortality risk. We used DNA methylation data from 1059 participants in the Melbourne Collaborative Cohort Study (mean age: 69 years) to calculate three age-adjusted measures of epigenetic ageing: GrimAge, PhenoAge, and DunedinPACE. SRH was assessed using a five-category questionnaire item ("excellent, very good, good, fair, poor"). Cox models were used to assess the associations of SRH, epigenetic ageing, and their interaction, with all-cause mortality over up to 17 years of follow-up (Ndeaths = 345). The association of SRH with mortality per category increase was HR = 1.29; 95%CI: 1.14-1.46. The association was slightly attenuated after adjusting for all three epigenetic ageing measures (HR = 1.25, 95%CI: 1.10-1.41). A strong gradient was observed in the association of GrimAge (Pinteraction = 0.006) and DunedinPACE (Pinteraction = 0.002) with mortality across worsening SRH strata. For example, the association between DunedinPACE and mortality in participants with "excellent" SRH was HR = 1.02, 95%CI: 0.73-1.43 and for "fair/poor" HR = 1.72, 95%CI: 1.35-2.20. SRH and epigenetic ageing were synergistic risk factors of mortality in our study. These findings suggest that consideration of subjective and objective factors may improve general health assessment, which has implications for the ongoing development of molecular markers of ageing.

Interplay Between Skeletal and Hematopoietic Cells in the Bone Marrow Microenvironment in Homeostasis and Aging

PURPOSE OF THE REVIEW

In this review, we discuss the most recent scientific advances on the reciprocal regulatory interactions between the skeletal and hematopoietic stem cell niche, focusing on immunomodulation and its interplay with the cell's mitochondrial function, and how this impacts osteoimmune health during aging and disease.

RECENT FINDINGS

Osteoimmunology investigates interactions between cells that make up the skeletal stem cell niche and immune system. Much work has investigated the complexity of the bone marrow microenvironment with respect to the skeletal and hematopoietic stem cells that regulate skeletal formation and immune health respectively. It has now become clear that these cellular components cooperate to maintain homeostasis and that dysfunction in their interaction can lead to aging and disease. Having a deeper, mechanistic appreciation for osteoimmune regulation will lead to better research perspective and therapeutics with the potential to improve the aging process, skeletal and hematologic regeneration, and disease targeting.

Childhood adversity, accelerated GrimAge, and associated health consequences

Childhood adversity is linked to psychological, behavioral, and physical health problems, including obesity and cardiometabolic disease. Epigenetic alterations are one pathway through which the effects of early life stress and adversity might persist into adulthood. Epigenetic mechanisms have also been proposed to explain why cardiometabolic health can vary greatly between individuals with similar Body Mass Index (BMIs). We evaluated two independent cross-sectional cohorts of adults without known medical illness, one of which explicitly recruited individuals with early life stress (ELS) and control participants (n = 195), and the other a general community sample (n = 477). In these cohorts, we examine associations between childhood adversity, epigenetic aging, and metabolic health. Childhood adversity was associated with increased GrimAge Acceleration (GAA) in both cohorts, both utilizing a dichotomous yes/no classification (both p < 0.01) as well as a continuous measure using the Childhood Trauma Questionnaire (CTQ) (both p < 0.05). Further investigation demonstrated that CTQ subscales for physical and sexual abuse (both p < 0.05) were associated with increased GAA in both cohorts, whereas physical and emotional neglect were not. In both cohorts, higher CTQ was also associated with higher BMI and increased insulin resistance (both p < 0.05). Finally, we demonstrate a moderating effect of BMI on the relationship between GAA and insulin resistance where GAA correlated with insulin resistance specifically at higher BMIs. These results, which were largely replicated between two independent cohorts, suggest that interactions between epigenetics, obesity, and metabolic health may be important mechanisms through which childhood adversity contributes to long-term physical and metabolic health effects.

Breaking down causes, consequences, and mediating effects of telomere length variation on human health

BACKGROUND

Telomeres form repeated DNA sequences at the ends of chromosomes, which shorten with each cell division. Yet, factors modulating telomere attrition and the health consequences thereof are not fully understood. To address this, we leveraged data from 326,363 unrelated UK Biobank participants of European ancestry.

RESULTS

Using linear regression and bidirectional univariable and multivariable Mendelian randomization (MR), we elucidate the relationships between leukocyte telomere length (LTL) and 142 complex traits, including diseases, biomarkers, and lifestyle factors. We confirm that telomeres shorten with age and show a stronger decline in males than in females, with these factors contributing to the majority of the 5.4% of LTL variance explained by the phenome. MR reveals 23 traits modulating LTL. Smoking cessation and high educational attainment associate with longer LTL, while weekly alcohol intake, body mass index, urate levels, and female reproductive events, such as childbirth, associate with shorter LTL. We also identify 24 traits affected by LTL, with risk for cardiovascular, pulmonary, and some autoimmune diseases being increased by short LTL, while longer LTL increased risk for other autoimmune conditions and cancers. Through multivariable MR, we show that LTL may partially mediate the impact of educational attainment, body mass index, and female age at childbirth on proxied lifespan.

CONCLUSIONS

Our study sheds light on the modulators, consequences, and the mediatory role of telomeres, portraying an intricate relationship between LTL, diseases, lifestyle, and socio-economic factors.

Severe drought exposure in utero associates to children's epigenetic age acceleration in a global climate change hot spot

The goal of this study is to examine the association between in utero drought exposure and epigenetic age acceleration (EAA) in a global climate change hot spot. Calculations of EAA in adults using DNA methylation have been found to accurately predict chronic disease and longevity. However, fewer studies have examined EAA in children, and drought exposure in utero has not been investigated. Additionally, studies of EAA in low-income countries with diverse populations are rare. We assess EAA using epigenetic clocks and two DNAm-based pace-of-aging measurements from whole saliva samples in 104 drought-exposed children and 109 same-sex sibling controls in northern Kenya. We find a positive association between in utero drought exposure and EAA in two epigenetic clocks (Hannum's and GrimAge) and a negative association in the DNAm based telomere length (DNAmTL) clock. The combined impact of drought's multiple deleterious stressors may reduce overall life expectancy through accelerated epigenetic aging.

Conditional independence as a statistical assessment of evidence integration processes

Intuitively, combining multiple sources of evidence should lead to more accurate decisions than considering single sources of evidence individually. In practice, however, the proper computation may be difficult, or may require additional data that are inaccessible. Here, based on the concept of conditional independence, we consider expressions that can serve either as recipes for integrating evidence based on limited data, or as statistical benchmarks for characterizing evidence integration processes. Consider three events, A, B, and C. We find that, if A and B are conditionally independent with respect to C, then the probability that C occurs given that both A and B are known, P(C|A, B), can be easily calculated without the need to measure the full three-way dependency between A, B, and C. This simplified approach can be used in two general ways: to generate predictions by combining multiple (conditionally independent) sources of evidence, or to test whether separate sources of evidence are functionally independent of each other. These applications are demonstrated with four computer-simulated examples, which include detecting a disease based on repeated diagnostic testing, inferring biological age based on multiple biomarkers of aging, discriminating two spatial locations based on multiple cue stimuli (multisensory integration), and examining how behavioral performance in a visual search task depends on selection histories. Besides providing a sound prescription for predicting outcomes, this methodology may be useful for analyzing experimental data of many types.

Inflammatory age and its impact on age-related health in older Chinese adults

INTRODUCTION

A standardized measure for inflammaging is lacking. We introduced the inflammatory age (iAge) as a quantification method and explored its associations with age-related traits and diseases in an older Chinese cohort.

METHODS

Inflammatory markers including white blood cell count (WBC), neutrophils, lymphocytes, monocytes, C-reactive protein, platelets and albumin were measured. Quantitative real-time polymerase chain reaction was used to measure telomere length. Traditional multivariable linear, partial least squares, and logistic regression were used.

RESULTS

iAge was constructed based on WBC, neutrophils, monocytes and albumin, which were associated with telomere length independently. A higher iAge indicated a heavier aging-related inflammation burden. Per 1-year increase in iAge was associated with higher body mass index (β 0.86 (95 % CI 0.67, 1.05) kg/m2), waist circumference (β 2.37 (95 % CI 1.85, 2.90) cm), glycosylated hemoglobin A1c (β 0.06 (95 % CI 0.02, 0.10) %), systolic blood pressure (β 1.06 (95 % CI 0.10, 2.03) mmHg), triglycerides (β 0.05 (95 % CI 0.01, 0.08) mmol/L), 10-year cardiovascular diseases risk (β 0.05 (95 % CI 0.02, 0.08) %), diabetes (OR 1.22 (95 % CI 1.02, 1.46)), hypertension (OR 1.21 (95 % CI 1.04, 1.42)) and metabolic syndrome risks (OR 1.25 (95 % CI 1.04, 1.51)), and lower fasting plasma glucose (β -0.016 (95 % CI -0.024, -0.007) mmol/L), total cholesterol (β -0.06 (95 % CI -0.12, -0.01) mmol/L) and high-density lipoprotein cholesterol (β -0.05 (95 % CI -0.07, -0.03) mmol/L).

CONCLUSION

The newly introduced iAge, derived from inflammatory markers and telomere length, aligns with various metabolic dysfunctions and age-related disease risks, underscoring its potential ability in identifying aging-related phenotypes.

Early-life exposure to tobacco, genetic susceptibility, and accelerated biological aging in adulthood

Early-life tobacco exposure serves as a non-negligible risk factor for aging-related diseases. To understand the underlying mechanisms, we explored the associations of early-life tobacco exposure with accelerated biological aging and further assessed the joint effects of tobacco exposure and genetic susceptibility. Compared with those without in utero exposure, participants with in utero tobacco exposure had an increase in Klemera-Doubal biological age (KDM-BA) and PhenoAge acceleration of 0.26 and 0.49 years, respectively, but a decrease in telomere length of 5.34% among 276,259 participants. We also found significant dose-response associations between the age of smoking initiation and accelerated biological aging. Furthermore, the joint effects revealed that high-polygenic risk score participants with in utero exposure and smoking initiation in childhood had the highest accelerated biological aging. There were interactions between early-life tobacco exposure and age, sex, deprivation, and diet on KDM-BA and PhenoAge acceleration. These findings highlight the importance of reducing early-life tobacco exposure to improve healthy aging.

Association between biological aging and periodontitis using NHANES 2009-2014 and mendelian randomization

Aging is a recognized risk factor for periodontitis, while biological aging could provide more accurate insights into an individual's functional status. This study aimed to investigate the potential association between biological aging and periodontitis. Epidemiological data from 9803 participants in the 2009-2014 National Health and Nutrition Examination Survey were analyzed at a cross-sectional level to assess this link. Three biological ages [Klemera-Doubal method (KDM), PhenoAge, and homeostatic dysregulation (HD)] and two measures of accelerated biological aging (BioAgeAccel and PhenoAgeAccel) were set as primary exposure and were calculated. Logistic regression and restricted cubic spline regression were employed to examine the relationship between biological aging and periodontitis. Additionally, Mendelian randomization analysis was conducted to explore the causal connection between accelerated biological aging and periodontitis. After adjusting for age, gender, race, educational level, marital status, ratio of family income, and disease conditions, this study, found a significant association between subjects with older higher biological ages, accelerated biological aging, and periodontitis. Specifically, for a per year increase in the three biological ages (HD, KDM, and PhenoAge), the risk of periodontitis increases by 15%, 3%, and 4% respectively. Individuals who had positive BioAgeAccel or PhenoAgeAccel were 20% or 37% more likely to develop periodontitis compared with those who had negative BioAgeAccel or PhenoAgeAccel. Furthermore, a significant non-linear positive relationship was observed between the three biological ages, accelerated biological aging, and periodontitis. However, the Mendelian randomization analysis indicated no causal effect of accelerated biological aging on periodontitis. Our findings suggest that biological aging may contribute to the risk of periodontitis, highlighting the potential utility of preventive strategies targeting aging-related pathways in reducing periodontitis risk among older adults.

Mixed-Methods Study of Disability Self-Management in Mexican Americans With Osteoarthritis

BACKGROUND

Health disparities in osteoarthritis (OA) outcomes exist both in the occurrence and treatment of functional limitation and disability for Mexican Americans. Although the effect of self-management of chronic illness is well established, studies demonstrate little attention to self-management of function or disability, despite the strong potential effect on both and, consequently, on patients' lives.

OBJECTIVE

The purpose of this study pilot was to develop and test key variable relationships for a measure of disability self-management among Mexican Americans.

METHODS

In this sequential, two-phased, mixed-methods, biobehavioral pilot study of Mexican American women and men with OA, a culturally tailored measure of disability self-management was created, and initial relationships among key variables were explored.

RESULTS

First, a qualitative study of 19 adults of Mexican American descent born in Texas (United States) or Mexico was conducted. The Mexican American Disability Self-Management Scale was created using a descriptive content analysis of interview data. The scale was tested and refined, resulting in 18 items and a descriptive frequency of therapeutic management efforts. Second, correlations between study variables were estimated: Disability and function were negatively correlated. Disability correlated positively with social support and activity effort. Disability correlated negatively with disability self-management, pain, and C-reactive protein. Function was positively correlated with age, pain, and depression. Liver enzymes (alanine transaminase) correlated positively with pain and anxiety.

DISCUSSION

This mixed-methods study indicates directions for further testing and interventions for disability outcomes among Mexican Americans.

Metabolomic age and risk of 50 chronic diseases in community-dwelling adults: A prospective cohort study

It is unclear how metabolomic age is associated with the risk of a wide range of chronic diseases. Our analysis included 110,692 participants (training: n = 27,673; testing: n = 27,673; validating: n = 55,346) aged 39-71 years at baseline (2006-2010) from the UK Biobank. Incident chronic diseases were identified using inpatient records, or death registers until January 2021. Predicted metabolomic age was trained and tested based on 168 metabolomics. Metabolomic age was linked to the risk of 50 diseases in the validation dataset. The median follow-up duration for individual diseases ranged from 11.2 years to 11.9 years. After controlling for false discovery rate, chronological age-adjusted age gap (CAAG) was significantly associated with the incidence of 25 out of 50 chronic diseases. After adjustment for full covariates, associations with 15 chronic diseases remained significant. Greater CAAG was associated with increased risk of eight cardiometabolic disorders (including cardiovascular diseases and diabetes), some cancers, alcohol use disorder, chronic obstructive pulmonary disease, chronic kidney disease, chronic liver disease and age-related macular degeneration. The association between CAAG and risk of peripheral vascular disease, other cardiac diseases, fracture, cataract and thyroid disorder was stronger among individuals with unhealthy diet than in those with healthy diet. The association between CAAG and risk of some conditions was stronger in younger individuals, those with metabolic disorders or low education. Metabolomic age plays an important role in the development of multiple chronic diseases. Healthy diet and high education may mitigate the risk for some chronic diseases due to metabolomic age acceleration.

Joint association of biological aging and lifestyle with risks of cancer incidence and mortality: A cohort study in the UK Biobank

BACKGROUND

Aging is a risk factor for cancer incidence and mortality. Biological aging can reflect the aging degree of the body better than chronological age and can be aggravated by unhealthy lifestyle factors. We aimed to assess the joint effect of biological aging and lifestyle with risks of cancer incidence and mortality.

METHODS

This study included a total of 281,889 participants aged 37 to 73 from the UK Biobank database. Biological age was derived from chronological age and 9 clinical blood indicators, and lifestyle score was constructed by body mass index, smoking status, alcohol consumption, physical activity, and diet. Multivariate Cox hazard proportional regression model was used to analyze the independent and joint association of biological aging and lifestyle with risks of cancer incidence and mortality, respectively.

RESULTS

Over a median follow-up period of 12.3 years, we found that older biological age was associated with increased risks of overall cancer, digestive system cancers, lung, breast and renal cancers incidence and mortality (HRs: 1.12-2.25). In the joint analysis of biological aging and lifestyle with risks of cancer incidence and mortality, compared with unhealthy lifestyle and younger biological age, individuals with healthy lifestyle and older biological age had decreased risks of incidence (8% ∼ 60%) and mortality (20% ∼ 63%) for overall, esophageal, colorectal, pancreatic and lung cancers.

CONCLUSIONS

Biological aging may be an important risk factor for cancer morbidity and mortality. A healthier lifestyle is more likely to mitigate the adverse effects of biological aging on overall cancer and some site-specific cancers.

Strategies to deal with genetic analyzer-specific DNA methylation measurements

Targeted bisulfite sequencing using single-base extension (SBE) can be used to measure DNA methylation via capillary electrophoresis on genetic analyzers in forensic labs. Several accurate age prediction models have been reported using this method. However, using different genetic analyzers with different software settings can generate different methylation values, leading to significant errors in age prediction. To address this issue, the study proposes and compares four methods as follows: (1) adjusting methylation values using numerous actual body fluid DNA samples, (2) adjusting methylation values using control DNAs with varying methylation ratios, (3) constructing new age prediction models for each genetic analyzer type, and (4) constructing new age prediction models that could be applied to all types of genetic analyzers. To test the methods for adjusting values using actual body fluid DNA samples, previously reported adjusting equations were used for blood/saliva DNA age prediction markers (ELOVL2, FHL2, KLF14, MIR29B2CHG/C1orf132, and TRIM59). New equations were generated for semen DNA age prediction markers (TTC7B, LOC401324/cg12837463, and LOC729960/NOX4) by drawing polynomial regression lines between the results of the three types of genetic analyzers (3130, 3500, and SeqStudio). The same method was applied to obtain adjustment equations using 11 control DNA samples. To develop new age prediction models for each genetic analyzer type, linear regression analysis was conducted using DNA methylation data from 150 blood, 150 saliva, and 62 semen samples. For the genetic analyzer-independent models, control DNAs were used to formulate equations for calibrating the bias of the data from each genetic analyzer, and linear regression analysis was performed using calibrated body fluid DNA data. In the comparison results, the genetic analyzer-specific models showed the highest accuracy. However, genetic analyzer-independent models through bias adjustment also provided accurate age prediction results, suggesting its use as an alternative in situations with multiple constraints.

Blood-Based Epigenetic Age Acceleration and Incident Colorectal Cancer Risk: Findings from a Population-Based Case-Control Study

This study investigates the association between epigenetic age acceleration (EAA) derived from DNA methylation and the risk of incident colorectal cancer (CRC). We utilized data from a random population sample of 9,360 individuals (men and women, aged 45-69) from the HAPIEE Study who had been followed up for 16 years. A nested case-control design yielded 35 incident CRC cases and 354 matched controls. Six baseline epigenetic age (EA) measures (Horvath, Hannum, PhenoAge, Skin and Blood (SB), BLUP, and Elastic Net (EN)) were calculated along with their respective EAAs. After adjustment, the odds ratios (ORs) for CRC risk per decile increase in EAA ranged from 1.20 (95% CI: 1.04-1.39) to 1.44 (95% CI: 1.21-1.76) for the Horvath, Hannum, PhenoAge, and BLUP measures. Conversely, the SB and EN EAA measures showed borderline inverse associations with ORs of 0.86-0.87 (95% CI: 0.76-0.99). Tertile analysis reinforced a positive association between CRC risk and four EAA measures (Horvath, Hannum, PhenoAge, and BLUP) and a modest inverse relationship with EN EAA. Our findings from a prospective population-based-case-control study indicate a direct association between incident CRC and four markers of accelerated baseline epigenetic age. In contrast, two markers showed a negative association or no association. These results warrant further exploration in larger cohorts and may have implications for CRC risk assessment and prevention.

Alcohol consumption and accelerated biological ageing in middle-aged and older people: A longitudinal study from two cohorts

BACKGROUND AND AIMS

The relationship between alcohol consumption and age-related diseases is inconsistent. Biological age (BA) serves as both a precursor and a predictor of age-related diseases; however, longitudinal associations between alcohol consumption and BA in middle-aged and older people remain unclear. We measured whether there was a longitudinal association between drinking frequency and pure alcohol intake with BA among middle-aged and older people.

DESIGN AND SETTING AND PARTICIPANTS

This study involved two prospective cohort studies, set in Southwestern China and the United Kingdom. A total of 8046 participants from the China Multi-Ethnic Cohort study (CMEC) and 5412 participants from the UK Biobank (UKB), aged 30-79 years, took part, with complete data from two waves of clinical biomarkers.

MEASUREMENTS

BA was calculated by the Klemera Doubal's method. Accelerated BA equalled BA minus chronological age. Drinking frequency and pure alcohol intake were obtained through self-reported questionnaires. Drinking frequency in the past year was classified as current non-drinking, occasional (monthly drinking) and regular (weekly drinking).

FINDINGS

Compared with consistent current non-drinkers, more frequent drinkers [CMEC: β = 0.46, 95% confidence interval (CI) = 0.13-0.80; UKB: β = 0.65, 95% CI = 0.01-1.29)], less frequent drinkers (CMEC: β = 0.62, 95% CI = 0.37-0.87; UKB: β = 0.54, 95% CI = -0.01-1.09), consistent occasional drinkers (CMEC: β = 0.51, 95% CI = 0.23-0.79; UKB: β = 0.63, 95% CI = 0.13-1.13) and consistent regular drinkers (CMEC: β = 0.56, 95% CI = 0.17-0.95; UKB: β = 0.46, 95% CI = 0.00-0.91) exhibited increased accelerated BA. A non-linear relationship between pure alcohol intake and accelerated BA was observed among consistent regular drinkers.

CONCLUSIONS

In middle-aged and older people, any change in drinking frequency and any amount of pure alcohol intake seem to be positively associated with acceleration of biological ageing, compared with maintaining abstinence.

The Evolution of Risk Assessment in Spine Surgery: A Narrative Review

BACKGROUND

Risk assessment is critically important in elective and high-risk interventions, particularly spine surgery. This narrative review describes the evolution of risk assessment from the earliest instruments focused on general surgical risk stratification, to more accurate and spine-specific risk calculators that quantified risk, to the current era of big data.

METHODS

The PubMed and SCOPUS databases were queried on October 11, 2023 using search terms to identify risk assessment tools (RATs) in spine surgery. A total of 108 manuscripts were included after screening with full-text review using the following inclusion criteria: 1) study population of adult spine surgical patients, 2) studies describing validation and subsequent performance of preoperative RATs, and 3) studies published in English.

RESULTS

Early RATs provided stratified patients into broad categories and allowed for improved communication between physicians. Subsequent risk calculators attempted to quantify risk by estimating general outcomes such as mortality, but then evolved to estimate spine-specific surgical complications. The integration of novel concepts such as invasiveness, frailty, genetic biomarkers, and sarcopenia led to the development of more sophisticated predictive models that estimate the risk of spine-specific complications and long-term outcomes.

CONCLUSIONS

RATs have undergone a transformative shift from generalized risk stratification to quantitative predictive models. The next generation of tools will likely involve integration of radiographic and genetic biomarkers, machine learning, and artificial intelligence to improve the accuracy of these models and better inform patients, surgeons, and payers.

Association between epigenetic age and type 2 diabetes mellitus or glycemic traits: A longitudinal twin study

Epigenetic clocks based on DNA methylation have been known as biomarkers of aging, including principal component (PC) clocks representing the degree of aging and DunedinPACE representing the pace of aging. Prior studies have shown the associations between epigenetic aging and T2DM, but the results vary by epigenetic age metrics and people. This study explored the associations between epigenetic age metrics and T2DM or glycemic traits, based on 1070 twins (535 twin pairs) from the Chinese National Twin Registry. It also explored the temporal relationships of epigenetic age metrics and glycemic traits in 314 twins (157 twin pairs) who participated in baseline and follow-up visits after a mean of 4.6 years. DNA methylation data were used to calculate epigenetic age metrics, including PCGrimAge acceleration (PCGrimAA), PCPhenoAge acceleration (PCPhenoAA), DunedinPACE, and the longitudinal change rate of PCGrimAge/PCPhenoAge. Mixed-effects and cross-lagged modelling assessed the cross-sectional and temporal relationships between epigenetic age metrics and T2DM or glycemic traits, respectively. In the cross-sectional analysis, positive associations were identified between DunedinPACE and glycemic traits, as well as between PCPhenoAA and fasting plasma glucose, which may be not confounded by shared genetic factors. Cross-lagged models revealed that glycemic traits (fasting plasma glucose, HbA1c, and TyG index) preceded DunedinPACE increases, and TyG index preceded PCGrimAA increases. Glycemic traits are positively associated with epigenetic age metrics, especially DunedinPACE. Glycemic traits preceded the increases in DunedinPACE and PCGrimAA. Lowering the levels of glycemic traits may reduce DunedinPACE and PCGrimAA, thereby mitigating age-related comorbidities.

Developmental epigenomic effects of maternal financial problems

Early-life adversity as neglect or low socioeconomic status is associated with negative physical/mental health outcomes and plays an important role in health trajectories through life. The early-life environment has been shown to be encoded as changes in epigenetic markers that are retained for many years.We investigated the effect of maternal major financial problems (MFP) and material deprivation (MD) on their children's epigenome in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Epigenetic aging, measured with epigenetic clocks, was weakly accelerated with increased MFP. In subsequent EWAS, MFP, and MD showed strong, independent programing effects on children's genomes. MFP in the period from birth to age seven was associated with genome-wide epigenetic modifications on children's genome visible at age 7 and partially remaining at age 15.These results support the hypothesis that physiological processes at least partially explain associations between early-life adversity and health problems later in life. Both maternal stressors (MFP/MD) had similar effects on biological pathways, providing preliminary evidence for the mechanisms underlying the effects of low socioeconomic status in early life and disease outcomes later in life. Understanding these associations is essential to explain disease susceptibility, overall life trajectories and the transition from health to disease.

Echocardiographic heart ageing patterns predict cardiovascular and non-cardiovascular events and reflect biological age: the SardiNIA study

AIMS

Age is a crucial risk factor for cardiovascular (CV) and non-CV diseases. As people age at different rates, the concept of biological age has been introduced as a personalized measure of functional deterioration. Associations of age with echocardiographic quantitative traits were analysed to assess different heart ageing rates and their ability to predict outcomes and reflect biological age.

METHODS AND RESULTS

Associations of age with left ventricular mass, geometry, diastolic function, left atrial volume, and aortic root size were measured in 2614 healthy subjects. Based on the 95% two-sided tolerance intervals of each correlation, three discrete ageing trajectories were identified and categorized as 'slow', 'normal', and 'accelerated' heart ageing patterns. The primary endpoint included fatal and non-fatal CV events, and the secondary endpoint was a composite of CV and non-CV events and all-cause death. The phenotypic age of the heart (HeartPhAge) was estimated as a proxy of biological age. The slow ageing pattern was found in 8.7% of healthy participants, the normal pattern in 76.9%, and the accelerated pattern in 14.4%. Kaplan-Meier curves of the heart ageing patterns diverged significantly (P = 0.0001) for both primary and secondary endpoints, with the event rate being lowest in the slow, intermediate in the normal, and highest in the accelerated pattern. In the Cox proportional hazards model, heart ageing patterns predicted both primary (P = 0.01) and secondary (P = 0.03 to <0.0001) endpoints, independent of chronological age and risk factors. Compared with chronological age, HeartPhAge was 9 years younger in slow, 4 years older in accelerated (both P < 0.0001), and overlapping in normal ageing patterns.

CONCLUSION

Standard Doppler echocardiography detects slow, normal, and accelerated heart ageing patterns. They predict CV and non-CV events, reflect biological age, and provide a new tool to calibrate prevention timing and intensity.

Clinical biomarker-based biological ageing and future risk of neurological disorders in the UK Biobank

BACKGROUND

Many common neurological disorders are associated with advancing chronological age, but their association with biological age (BA) remains poorly understood.

METHODS

We studied 325 870 participants in the UK Biobank without a diagnosed neurological condition at baseline and generated three previously-described measures of BA based on 18 routinely measured clinical biomarkers (PhenoAge, Klemera-Doubal method age (KDMAge), homeostatic dysregulation age). Using survival models, we assessed the effect of advanced BA on incident neurological diagnoses, including all-cause and cause-specific dementia, ischaemic stroke, Parkinson's disease and motor neuron disease.

RESULTS

During a mean follow-up of 9.0 years, there were 1397 incident cases of dementia and 2515 of ischaemic stroke, with smaller case numbers of other diagnoses. The strongest associations with a 1 SD in BA residual were seen for all-cause dementia (KDMAge HR=1.19, 95% CI=1.11 to 1.26), vascular dementia (1.41, 1.25 to 1.60) and ischaemic stroke (1.39, 1.34 to 1.46). Weaker associations were seen for Alzheimer's disease and motor neuron disease, while, in contrast, HRs for Parkinson's disease tended to be <1. Results were largely consistent after adjustment for disease-specific covariates including common cardiometabolic risk factors.

CONCLUSIONS

Advanced BA calculated from routine clinical biomarker results increases the risk of subsequent neurological diagnoses including all-cause dementia and ischaemic stroke.

Loss of the Y Chromosome: A Review of Molecular Mechanisms, Age Inference, and Implications for Men's Health

Until a few years ago, it was believed that the gradual mosaic loss of the Y chromosome (mLOY) was a normal age-related process. However, it is now known that mLOY is associated with a wide variety of pathologies in men, such as cardiovascular diseases, neurodegenerative disorders, and many types of cancer. Nevertheless, the mechanisms that generate mLOY in men have not been studied so far. This task is of great importance because it will allow focusing on possible methods of prophylaxis or therapy for diseases associated with mLOY. On the other hand, it would allow better understanding of mLOY as a possible marker for inferring the age of male samples in cases of human identification. Due to the above, in this work, a comprehensive review of the literature was conducted, presenting the most relevant information on the possible molecular mechanisms by which mLOY is generated, as well as its implications for men's health and its possible use as a marker to infer age.

The AccelerAge framework: a new statistical approach to predict biological age based on time-to-event data

Aging is a multifaceted and intricate physiological process characterized by a gradual decline in functional capacity, leading to increased susceptibility to diseases and mortality. While chronological age serves as a strong risk factor for age-related health conditions, considerable heterogeneity exists in the aging trajectories of individuals, suggesting that biological age may provide a more nuanced understanding of the aging process. However, the concept of biological age lacks a clear operationalization, leading to the development of various biological age predictors without a solid statistical foundation. This paper addresses these limitations by proposing a comprehensive operationalization of biological age, introducing the "AccelerAge" framework for predicting biological age, and introducing previously underutilized evaluation measures for assessing the performance of biological age predictors. The AccelerAge framework, based on Accelerated Failure Time (AFT) models, directly models the effect of candidate predictors of aging on an individual's survival time, aligning with the prevalent metaphor of aging as a clock. We compare predictors based on the AccelerAge framework to a predictor based on the GrimAge predictor, which is considered one of the best-performing biological age predictors, using simulated data as well as data from the UK Biobank and the Leiden Longevity Study. Our approach seeks to establish a robust statistical foundation for biological age clocks, enabling a more accurate and interpretable assessment of an individual's aging status.

Signs of aging in midlife: physical function and sex differences in microbiota

Microbiota composition has been linked to physical activity, health measures, and biological age, but a shared profile has yet to be shown. The aim of this study was to examine the associations between microbiota composition and measures of function, such as a composite measure of physical capacity, and biological age in midlife, prior to onset of age-related diseases. Seventy healthy midlife individuals (age 44.58 ± 0.18) were examined cross-sectionally, and their gut-microbiota profile was characterized from stool samples using 16SrRNA gene sequencing. Biological age was measured using the Klemera-Doubal method and a composition of blood and physiological biomarkers. Physical capacity was calculated based on sex-standardized functional tests. We demonstrate that the women had significantly richer microbiota, p = 0.025; however, microbiota diversity was not linked with chronological age, biological age, or physical capacity for either women or men. Men had slightly greater β-diversity; however, β-diversity was positively associated with biological age and with physical capacity for women only (p = 0.01 and p = 0.04; respectively). For women, an increase in abundance of Roseburia faecis and Collinsella aerofaciens, as well as genus Ruminococcus and Dorea, was significantly associated with higher biological age and lower physical capacity; an increase in abundance of Akkermansia muciniphila and genera Bacteroides and Alistipes was associated with younger biological age and increased physical capacity. Differentially abundant taxa were also associated with non-communicable diseases. These findings suggest that microbiota composition is a potential mechanism linking physical capacity and health status; personalized probiotics may serve as a new means to support health-promoting interventions in midlife. Investigating additional factors underlying this link may facilitate the development of a more accurate method to estimate the rate of aging.

A growth chart of brain function from infancy to adolescence based on EEG

BACKGROUND

In children, objective, quantitative tools that determine functional neurodevelopment are scarce and rarely scalable for clinical use. Direct recordings of cortical activity using routinely acquired electroencephalography (EEG) offer reliable measures of brain function.

METHODS

We developed and validated a measure of functional brain age (FBA) using a residual neural network-based interpretation of the paediatric EEG. In this cross-sectional study, we included 1056 children with typical development ranging in age from 1 month to 18 years. We analysed a 10- to 15-min segment of 18-channel EEG recorded during light sleep (N1 and N2 states).

FINDINGS

The FBA had a weighted mean absolute error (wMAE) of 0.85 years (95% CI: 0.69-1.02; n = 1056). A two-channel version of the FBA had a wMAE of 1.51 years (95% CI: 1.30-1.73; n = 1056) and was validated on an independent set of EEG recordings (wMAE = 2.27 years, 95% CI: 1.90-2.65; n = 723). Group-level maturational delays were also detected in a small cohort of children with Trisomy 21 (Cohen's d = 0.36, p = 0.028).

INTERPRETATION

A FBA, based on EEG, is an accurate, practical and scalable automated tool to track brain function maturation throughout childhood with accuracy comparable to widely used physical growth charts.

FUNDING

This research was supported by the National Health and Medical Research Council, Australia, Helsinki University Diagnostic Center Research Funds, Finnish Academy, Finnish Paediatric Foundation, and Sigrid Juselius Foundation.

Assessing Biological Age: The Potential of ECG Evaluation Using Artificial Intelligence: JACC Family Series

Biological age may be a more valuable predictor of morbidity and mortality than a person's chronological age. Mathematical models have been used for decades to predict biological age, but recent developments in artificial intelligence (AI) have led to new capabilities in age estimation. Using deep learning methods to train AI models on hundreds of thousands of electrocardiograms (ECGs) to predict age results in a good, but imperfect, age prediction. The error predicting age using ECG, or the difference between AI-ECG-derived age and chronological age (delta age), may be a surrogate measurement of biological age, as the delta age relates to survival, even after adjusting for chronological age and other covariates associated with total and cardiovascular mortality. The relative affordability, noninvasiveness, and ubiquity of ECGs, combined with ease of access and potential to be integrated with smartphone or wearable technology, presents a potential paradigm shift in assessment of biological age.

Towards personalized nicotinamide mononucleotide (NMN) supplementation: Nicotinamide adenine dinucleotide (NAD) concentration

Nicotinamide mononucleotide (NMN) is a precursor of nicotinamide adenine dinucleotide (NAD), which declines with age. Supplementation of NMN has been shown to improve blood NAD concentration. However, the optimal NMN dose remains unclear. This is a post-hoc analysis of a double-blinded clinical trial involving 80 generally healthy adults aged 40-65 years. The participants received a placebo or daily 300 mg, 600 mg, or 900 mg NMN for 60 days. Blood NAD concentration, blood biological age, homeostatic model assessment for insulin resistance, 6-minute walk test, and 36-item short-form survey (SF-36) were measured at baseline and after supplement. A significant dose-dependent increase in NAD concentration change (NADΔ) was observed following NMN supplementation, with a large coefficient of variation (29.2-113.3%) within group. The increase in NADΔ was associated with an improvement in the walking distance of 6-minute walk test and the SF-36 score. The median effect dose of NADΔ for the 6-minute walk test and SF-36 score was 15.7 nmol/L (95% CI: 10.9-20.5 nmol/L) and 13.5 nmol/L (95% CI; 10.5-16.5 nmol/L), respectively. Because of the high interindividual variability of the NADΔ after NMN supplementation, monitoring NAD concentration can provide valuable insights for tailoring personalized dosage regimens and optimizing NMN utilization.

Interplay of body mass index and metabolic syndrome: association with physiological age from midlife to late-life

Obesity and metabolic syndrome (MetS) share common pathophysiological characteristics with aging. To better understand their interplay, we examined how body mass index (BMI) and MetS jointly associate with physiological age, and if the associations changed from midlife to late-life. We used longitudinal data from 1,825 Swedish twins. Physiological age was measured as frailty index (FI) and functional aging index (FAI) and modeled independently in linear mixed-effects models adjusted for chronological age, sex, education, and smoking. We assessed curvilinear associations of BMI and chronological age with physiological age, and interactions between BMI, MetS, and chronological age. We found a significant three-way interaction between BMI, MetS, and chronological age on FI (p-interaction = 0·006), not FAI. Consequently, we stratified FI analyses by age: < 65, 65-85, and ≥ 85 years, and modeled FAI across ages. Except for FI at ages ≥ 85, BMI had U-shaped associations with FI and FAI, where BMI around 26-28 kg/m2 was associated with the lowest physiological age. MetS was associated with higher FI and FAI, except for FI at ages < 65, and modified the BMI-FI association at ages 65-85 (p-interaction = 0·02), whereby the association between higher BMI levels and FI was stronger in individuals with MetS. Age modified the MetS-FI association in ages ≥ 85, such that it was stronger at higher ages (p-interaction = 0·01). Low BMI, high BMI, and metabolic syndrome were associated with higher physiological age, contributing to overall health status among older individuals and potentially accelerating aging.

Exposure to ambient temperature and heat index in relation to DNA methylation age: A population-based study in Taiwan

BACKGROUND

Climate change caused an increase in ambient temperature in the past decades. Exposure to high ambient temperature could result in biological aging, but relevant studies in a warm environment were lacking. We aimed to study the exposure effects of ambient temperature and heat index (HI) in relation to age acceleration in Taiwan, a subtropical island in Asia.

METHODS

The study included 2,084 participants from Taiwan Biobank. Daily temperature and relative humidity data were collected from weather monitoring stations. Individual residential exposure was estimated by ordinary kriging. Moving averages of ambient temperature and HI from 1 to 180 days prior to enrollment were calculated to estimate the exposure effects in multiple time periods. Age acceleration was defined as the difference between DNA methylation age and chronological age. DNA methylation age was calculated by the Horvath's, Hannum's, Weidner's, ELOVL2, FHL2, phenotypic (Pheno), Skin & blood, and GrimAge2 (Grim2) DNA methylation age algorithms. Multivariable linear regression models, generalized additive models (GAMs), and distributed lag non-linear models (DLNMs) were conducted to estimate the effects of ambient temperature and HI exposures in relation to age acceleration.

RESULTS

Exposure to high ambient temperature and HI were associated with increased age acceleration, and the associations were stronger in prolonged exposure. The heat stress days with maximum HI in caution (80-90°F), extreme caution (90-103°F), danger (103-124°F), and extreme danger (>124°F) were also associated with increased age acceleration, especially in the extreme danger days. Each extreme danger day was associated with 571.38 (95 % CI: 42.63-1100.13), 528.02 (95 % CI: 36.16-1019.87), 43.9 (95 % CI: 0.28-87.52), 16.82 (95 % CI: 2.36-31.28) and 15.52 (95 % CI: 2.17-28.88) days increase in the Horvath's, Hannum's, Weidner's, Pheno, and Skin & blood age acceleration, respectively.

CONCLUSION

High ambient temperature and HI may accelerate biological aging.

Crystalline lens nuclear age prediction as a new biomarker of nucleus degeneration

BACKGROUND

The crystalline lens is a transparent structure of the eye to focus light on the retina. It becomes muddy, hard and dense with increasing age, which makes the crystalline lens gradually lose its function. We aim to develop a nuclear age predictor to reflect the degeneration of the crystalline lens nucleus.

METHODS

First we trained and internally validated the nuclear age predictor with a deep-learning algorithm, using 12 904 anterior segment optical coherence tomography (AS-OCT) images from four diverse Asian and American cohorts: Zhongshan Ophthalmic Center with Machine0 (ZOM0), Tomey Corporation (TOMEY), University of California San Francisco and the Chinese University of Hong Kong. External testing was done on three independent datasets: Tokyo University (TU), ZOM1 and Shenzhen People's Hospital (SPH). We also demonstrate the possibility of detecting nuclear cataracts (NCs) from the nuclear age gap.

FINDINGS

In the internal validation dataset, the nuclear age could be predicted with a mean absolute error (MAE) of 2.570 years (95% CI 1.886 to 2.863). Across the three external testing datasets, the algorithm achieved MAEs of 4.261 years (95% CI 3.391 to 5.094) in TU, 3.920 years (95% CI 3.332 to 4.637) in ZOM1-NonCata and 4.380 years (95% CI 3.730 to 5.061) in SPH-NonCata. The MAEs for NC eyes were 8.490 years (95% CI 7.219 to 9.766) in ZOM1-NC and 9.998 years (95% CI 5.673 to 14.642) in SPH-NC. The nuclear age gap outperformed both ophthalmologists in detecting NCs, with areas under the receiver operating characteristic curves of 0.853 years (95% CI 0.787 to 0.917) in ZOM1 and 0.909 years (95% CI 0.828 to 0.978) in SPH.

INTERPRETATION

The nuclear age predictor shows good performance, validating the feasibility of using AS-OCT images as an effective screening tool for nucleus degeneration. Our work also demonstrates the potential use of the nuclear age gap to detect NCs.

Inverted U-shaped relationship between sleep duration and phenotypic age in US adults: a population-based study

Sleep is a modifiable behavior that can be targeted in interventions aimed at promoting healthy aging. This study aims to (i) identify the sleep duration trend in US adults; (ii) investigate the relationship between sleep duration and phenotypic age; and (iii) explore the role of exercise in this relationship. Phenotypic age as a novel index was calculated according to biomarkers collected from US adults based on the National Health and Nutrition Examination Survey (NHANES). Sleep information was self-reported by participants and discerned through individual interviews. The principal analytical method employed was weighted multivariable linear regression modeling, which accommodated for the complex multi-stage sampling design. The potential non-linear relationship was explored using a restricted cubic spline (RCS) model. Furthermore, subgroup analyses evaluated the potential effects of sociodemographic and lifestyle factors on the primary study outcomes. A total of 13,569 participants were finally included in, thereby resulting in a weighted population of 78,880,615. An examination of the temporal trends in sleep duration revealed a declining proportion of individuals with insufficient and markedly deficient sleep time since the 2015-2016 cycle. Taken normal sleep group as a reference, participants with extreme short sleep [β (95% CI) 0.582 (0.018, 1.146), p = 0.044] and long sleep [β (95% CI) 0.694 (0.186, 1.203), p = 0.010] were both positively associated with phenotypic age using the fully adjusted model. According to the dose-response relationship between sleep duration and phenotypic age, long sleep duration can benefit from regular exercise activity, whereas short sleep duration with more exercise tended to have higher phenotypic age. There is an inverted U-shaped relationship between short and long sleep durations and phenotypic age. This study represents an important step forward in our understanding of the complex relationship between sleep and healthy aging. By shedding light on this topic and providing practical exercise recommendations for promoting healthy sleep habits, researchers can help individuals live longer, healthier, and more fulfilling lives.

Epigenetic age acceleration and risk of aortic valve stenosis: a bidirectional Mendelian randomization study

BACKGROUND

Aortic valve stenosis (AVS) is the most prevalent cardiac valve lesion in developed countries, and pathogenesis is closely related to aging. DNA methylation-based epigenetic clock is now recognized as highly accurate predictor of the aging process and associated health outcomes. This study aimed to explore the causal relationship between epigenetic clock and AVS by conducting a bidirectional Mendelian randomization (MR) analysis.

METHODS

Summary genome-wide association study statistics of epigenetic clocks (HannumAge, HorvathAge, PhenoAge, and GrimAge) and AVS were obtained and assessed for significant instrumental variables from Edinburgh DataShare (n = 34,710) and FinnGen biobank (cases = 9870 and controls = 402,311). The causal association between epigenetic clock and AVS was evaluated using inverse variance weighted (IVW), weighted median (WM), and MR-Egger methods. Multiple analyses (heterogeneity analysis, pleiotropy analysis, and sensitivity analysis) were performed for quality control assessment.

RESULTS

The MR analysis showed that the epigenetic age acceleration of HorvathAge and PhenoAge was associated with an increased risk of AVS (HorvathAge: OR = 1.043, P = 0.016 by IVW, OR = 1.058, P = 0.018 by WM; PhenoAge: OR = 1.058, P = 0.005 by IVW, OR = 1.053, P = 0.039 by WM). Quality control assessment proved our findings were reliable and robust. However, there was a lack of evidence supporting a causal link from AVS to epigenetic aging.

CONCLUSION

The present MR analysis unveiled a causal association between epigenetic clocks, especially HorvathAge and PhenoAge, with AVS. Further research is required to elucidate the underlying mechanisms and develop strategies for potential interventions.

Causal association of obesity with epigenetic aging and telomere length: a bidirectional mendelian randomization study

BACKGROUND

In observational studies, there exists an association between obesity and epigenetic age as well as telomere length. However, varying and partially conflicting outcomes have notably arisen from distinct studies on this topic. In the present study, two-way Mendelian randomization was used to identify potential causal associations between obesity and epigenetic age and telomeres.

METHODS

A genome-wide association study was conducted using data from individuals of European ancestry to investigate bidirectional Mendelian randomization (MR) regarding the causal relationships between obesity, as indicated by three obesity indicators (body mass index or BMI, waist circumference adjusted for BMI or WCadjBMI, and waist-to-hip ratio adjusted for BMI or WHRadjBMI), and four epigenetic age measures (HannumAge, HorvathAge, GrimAge, PhenoAge), as well as telomere length. To assess these causal associations, various statistical methods were employed, including Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Weighted Mode, and Simple Mode. To address the issue of multiple testing, we applied the Bonferroni correction. These methods were used to determine whether there is a causal link between obesity and epigenetic age, as well as telomere length, and to explore potential bidirectional relationships. Forest plots and scatter plots were generated to show causal associations between exposures and outcomes. For a comprehensive visualization of the results, leave-one-out sensitivity analysis plots, individual SNP-based forest plots for MR analysis, and funnel plots were included in the presentation of the results.

RESULTS

A strong causal association was identified between obesity and accelerated HannumAge, GrimAge, PhenoAge and telomere length shrinkage. The causal relationship between WCadjBMI and PhenoAge acceleration (OR: 2.099, 95%CI: 1.248-3.531, p = 0.005) was the strongest among them. However, only the p-values for the causal associations of obesity with GrimAge, PhenoAge, and telomere length met the criteria after correction using the Bonferroni multiple test. In the reverse MR analysis, there were statistically significant causal associations between HorvathAge, PhenoAge and GrimAge and BMI, but these associations exhibited lower effect sizes, as indicated by their Odds Ratios (ORs). Notably, sensitivity analysis revealed the robustness of the study results.

CONCLUSIONS

The present findings reveal a causal relationship between obesity and the acceleration of epigenetic aging as well as the reduction of telomere length, offering valuable insights for further scientific investigations aimed at developing strategies to mitigate the aging process in humans.

Clarifying the biological and statistical assumptions of cross-sectional biological age predictors: an elaborate illustration using synthetic and real data

BACKGROUND

There is divergence in the rate at which people age. The concept of biological age is postulated to capture this variability, and hence to better represent an individual's true global physiological state than chronological age. Biological age predictors are often generated based on cross-sectional data, using biochemical or molecular markers as predictor variables. It is assumed that the difference between chronological and predicted biological age is informative of one's chronological age-independent aging divergence ∆.

METHODS

We investigated the statistical assumptions underlying the most popular cross-sectional biological age predictors, based on multiple linear regression, the Klemera-Doubal method or principal component analysis. We used synthetic and real data to illustrate the consequences if this assumption does not hold.

RESULTS

The most popular cross-sectional biological age predictors all use the same strong underlying assumption, namely that a candidate marker of aging's association with chronological age is directly informative of its association with the aging rate ∆. We called this the identical-association assumption and proved that it is untestable in a cross-sectional setting. If this assumption does not hold, weights assigned to candidate markers of aging are uninformative, and no more signal may be captured than if markers would have been assigned weights at random.

CONCLUSIONS

Cross-sectional methods for predicting biological age commonly use the untestable identical-association assumption, which previous literature in the field had never explicitly acknowledged. These methods have inherent limitations and may provide uninformative results, highlighting the importance of researchers exercising caution in the development and interpretation of cross-sectional biological age predictors.

Mitigating cellular aging and enhancing cognitive functionality: visual arts-mediated Cognitive Activation Therapy in neurocognitive disorders

The growing phenomenon of population aging is redefining demographic dynamics, intensifying age-related conditions, especially dementia, projected to triple by 2050 with an enormous global economic burden. This study investigates visual arts-mediated Cognitive Activation Therapy (CAT) as a non-pharmacological CAT intervention targets both biological aging [leukocyte telomere length (LTL), DNA methylation age (DNAmAge)] and cognitive functionality. Aligning with a broader trend of integrating non-pharmacological approaches into dementia care. The longitudinal study involved 20 patients with mild to moderate neurocognitive disorders. Cognitive and functional assessments, and biological aging markers -i.e., LTL and DNAmAge- were analyzed before and after CAT intervention. Change in LTL was positively correlated with days of treatment (p =0.0518). LTL significantly elongated after intervention (p =0.0269), especially in men (p =0.0142), correlating with younger age (p =0.0357), and higher education (p =0.0008). DNAmAge remained instead stable post-treatment. Cognitive and functional improvements were observed for Copy of complex geometric figure, Progressive Silhouettes, Position Discrimination, Communication Activities of Daily Living-Second edition, Direct Functional Status (p < 0.0001) and Object decision (p =0.0594), but no correlations were found between LTL and cognitive gains. Visual arts-mediated CAT effectively mitigates cellular aging, especially in men, by elongating LTL. These findings underscore the potential of non-pharmacological interventions in enhancing cognitive and functional status and general well-being in dementia care. Further research with larger and longer-term studies is essential for validation.

Causal relationship between telomere length and sepsis: a bidirectional Mendelian randomization study

Numerous observational studies have elucidated a connection between leukocyte telomere length (LTL) and sepsis, yet its fundamental cause remains enigmatic. Thus, the current study's objective is to employ a bidirectional Mendelian randomization (MR) approach to scrutinize the causality between LTL and sepsis. We selected single nucleotide polymorphisms (SNPs) associated with LTL (n = 472,174) and sepsis from a genome-wide association study (GWAS), including Sepsis (n = 486,484, ncase = 11,643), Sepsis (28 day death in critical care) (n = 431,365, ncase = 347), Sepsis (under 75) (n = 462,869, ncase = 11,568), Sepsis (28 day death) (n = 486,484, ncase = 1896), and Sepsis (critical care) (n = 431,365, ncase = 1380), as instrumental variables (IVs). The inverse variance weighted (IVW) MR method was employed as the primary approach, and various sensitivity analyses were conducted to assess the validity of this instrument and potential pleiotropy. Using the IVW method, we uncovered a potential causal relationship between genetically predicted LTL reduction and increased susceptibility to sepsis, with an odds ratio (OR) of 1.161 [95% confidence interval (CI) 1.039-1.297, p = 0.008]. However, reverse MR analysis did not indicate any impact of sepsis on LTL. Our forward MR study highlights a potential causal relationship between LTL as an exposure and increased susceptibility to sepsis. Specifically, our findings suggest that individuals with genetically determined shorter LTL may be at an increased risk of developing sepsis. This may contribute to the development of novel diagnostic and therapeutic strategies for the prevention, diagnosis, and treatment of sepsis.

Decreased telomere length in a subgroup of young individuals with bipolar disorders: replication in the FACE-BD cohort and association with the shelterin component POT1

Bipolar disorder (BD) has been associated with premature cellular aging with shortened telomere length (TL) as compared to the general population. We recently identified a subgroup of young individuals with prematurely shortened TL. The aims of the present study were to replicate this observation in a larger sample and analyze the expression levels of genes associated with age or TL in a subsample of these individuals. TL was measured on peripheral blood DNA using quantitative polymerase chain reaction in a sample of 542 individuals with BD and clustering analyses were performed. Gene expression level of 29 genes, associated with aging or with telomere maintenance, was analyzed in RNA samples from a subsample of 129 individuals. Clustering analyses identified a group of young individuals (mean age 29.64 years), with shorter TL. None of the tested clinical variables were significantly associated with this subgroup. Gene expression level analyses showed significant downregulation of MYC, POT1, and CD27 in the prematurely aged young individuals compared to the young individuals with longer TL. After adjustment only POT1 remained significantly differentially expressed between the two groups of young individuals. This study confirms the existence of a subgroup of young individuals with BD with shortened TL. The observed decrease of POT1 expression level suggests a newly described cellular mechanism in individuals with BD, that may contribute to telomere shortening.

The causal relationship between autoimmune thyroid disorders and telomere length: A Mendelian randomization and colocalization study

This study aimed to evaluate whether there is a causal relationship between autoimmune thyroid disorders (AITDs) and telomere length (TL) in the European population and whether there is reverse causality. In this study, Mendelian randomization (MR) and colocalization analysis were conducted to assess the potential causal relationship between AITDs and TL using summary statistics from large-scale genome-wide association studies, followed by analysis of the relationship between TL and thyroid stimulating hormone and free thyroxine (FT4) to help interpret the findings. The inverse variance weighted (IVW) method was used to estimate the causal estimates. The weighted median, MR-Egger and leave-one-out methods were used as sensitivity analyses. The IVW method results showed a significant causal relationship between autoimmune hyperthyroidism and TL (β = -1.93 × 10-2 ; p = 4.54 × 10-5 ). There was no causal relationship between autoimmune hypothyroidism and TL (β = -3.99 × 10-3 ; p = 0.324). The results of the reverse MR analysis showed that genetically TL had a significant causal relationship on autoimmune hyperthyroidism (IVW: odds ratio (OR) = 0.49; p = 2.83 × 10-4 ) and autoimmune hypothyroidism (IVW: OR = 0.86; p = 7.46 × 10-3 ). Both horizontal pleiotropy and heterogeneity tests indicated the validity of our bidirectional MR study. Finally, colocalization analysis suggested that there were shared causal variants between autoimmune hyperthyroidism and TL, further highlighting the robustness of the results. In conclusion, autoimmune hyperthyroidism may accelerate telomere attrition, and telomere attrition is a causal factor for AITDs.

Consequences of heterogeneity in aging: parental age at death predicts midlife all-cause mortality and hospitalization in a Swedish national birth cohort

BACKGROUND

The processes that underlie aging may advance at different rates in different individuals and an advanced biological age, relative to the chronological age, is associated with increased risk of disease and death. Here we set out to quantify the extent to which heterogeneous aging shapes health outcomes in midlife by following a Swedish birth-cohort and using parental age at death as a proxy for biological age in the offspring.

METHODS

We followed a nationwide Swedish birth cohort (N = 89,688) between the ages of 39 and 66 years with respect to hospitalizations and death. Cox regressions were used to quantify the association, in the offspring, between parental age at death and all-cause mortality, as well as hospitalization for conditions belonging to the 10 most common ICD-10 chapters.

RESULTS

Longer parental lifespan was consistently associated with reduced risks of hospitalization and all-cause mortality. Differences in risk were mostly evident from before the age of 50 and persisted throughout the follow-up. Each additional decade of parental survival decreased the risk of offspring all-cause mortality by 22% and risks of hospitalizations by 9 to 20% across the 10 diseases categories considered. The number of deaths and hospitalizations attributable to having parents not living until old age were 1500 (22%) and 11,000 (11%) respectively.

CONCLUSIONS

Our findings highlight that increased parental lifespan is consistently associated with health benefits in the offspring across multiple outcomes and suggests that heterogeneous aging processes have clinical implications already in midlife.

Association between modifiable lifestyle factors and telomere length: a univariable and multivariable Mendelian randomization study

BACKGROUND

Telomere length has long been recognized as a valuable biomarker of aging and is inversely correlated with chronological age. Various lifestyle factors have been implicated in telomere shortening or preservation; however, the association between lifestyle factors and telomere length remains controversial. To address this issue, we conducted a Mendelian randomization (MR) analysis to investigate the potential causal associations between multiple lifestyle factors and telomere length.

METHODS

Independent genetic variants strongly associated with lifestyle factors (tobacco smoking, sleep duration, insomnia, and physical activity) were selected as instrumental variables from corresponding genome-wide association studies (GWASs). Summary-level data for telomere length was obtained from a GWAS comprising 472,174 European ancestries. Univariable and multivariable MR analyses were performed to assess the relationships.

RESULTS

The genetic liability to lifetime smoking was robustly associated with shorter telomere length (odd ratio [OR]: 0.882; 95% confidence interval [CI]: 0.847-0.918). Genetically predicted insomnia was also linked to shorter telomere length (OR: 0.972; 95% CI: 0.959-0.985), while no significant association was observed between sleep duration and telomere length. Furthermore, a suggestive association was found between moderate-to-vigorous physical activity and longer telomere length (OR: 1.680; 95% CI: 1.115-2.531). In multivariable MR analyses, adjusting for potential mediators such as body mass index, type 2 diabetes, alcohol consumption, and alcohol use disorder, the associations of lifetime smoking and insomnia with telomere length remained robust.

CONCLUSION

Our findings suggest that smoking and insomnia may contribute to telomere shortening, while physical activity may play a role in telomere length maintenance. These findings underscore the importance of managing positive risk factors and adopting a healthy lifestyle to promote telomere health.

A Review: Multi-Omics Approach to Studying the Association between Ionizing Radiation Effects on Biological Aging

Multi-omics studies have emerged as powerful tools for tailoring individualized responses to various conditions, capitalizing on genome sequencing technologies' increasing affordability and efficiency. This paper delves into the potential of multi-omics in deepening our understanding of biological age, examining the techniques available in light of evolving technology and computational models. The primary objective is to review the relationship between ionizing radiation and biological age, exploring a wide array of functional, physiological, and psychological parameters. This comprehensive review draws upon an extensive range of sources, including peer-reviewed journal articles, government documents, and reputable websites. The literature review spans from fundamental insights into radiation effects to the latest developments in aging research. Ionizing radiation exerts its influence through direct mechanisms, notably single- and double-strand DNA breaks and cross links, along with other critical cellular events. The cumulative impact of DNA damage forms the foundation for the intricate process of natural aging, intersecting with numerous diseases and pivotal biomarkers. Furthermore, there is a resurgence of interest in ionizing radiation research from various organizations and countries, reinvigorating its importance as a key contributor to the study of biological age. Biological age serves as a vital reference point for the monitoring and mitigation of the effects of various stressors, including ionizing radiation. Ionizing radiation emerges as a potent candidate for modeling the separation of biological age from chronological age, offering a promising avenue for tailoring protocols across diverse fields, including the rigorous demands of space exploration.

Association of a Blood-Based Aging Biomarker Index With Death and Chronic Disease: Cardiovascular Health Study

BACKGROUND

A goal of gerontology is to discover phenotypes that reflect biological aging distinct from disease pathogenesis. Biomarkers that are strongly associated with mortality could be used to define such a phenotype. However, the relation of such an index with multiple chronic conditions warrants further exploration.

METHODS

A biomarker index (BI) was constructed in the Cardiovascular Health Study (N = 3 197), with a mean age of 74 years. The BI incorporated circulating levels of new biomarkers, including insulin-like growth factor-1, interleukin-6, amino-terminal pro-B-type natriuretic peptide, cystatin-C, C-reactive protein, tumor necrosis factor-alpha soluble receptor 1, fasting insulin, and fasting glucose, and was built based on their relationships with mortality. Cox proportional hazards models predicting a composite of death and chronic disease involving cardiovascular disease, dementia, and cancer were calculated with 6 years of follow-up.

RESULTS

The hazard ratio (HR, 95% CI) for the composite outcome of death or chronic disease per category of BI was 1.65 (1.52, 1.80) and 1.75 (1.58, 1.94) in women and men, respectively. The HR (95% CI) per 5 years of age was 1.57 (1.48, 1.67) and 1.55 (1.44, 1.67) in women and men, respectively. Moreover, BI could attenuate the effect of age on the composite outcome by 16.7% and 22.0% in women and men, respectively.

CONCLUSIONS

Biomarker index was significantly and independently associated with a composite outcome of death and chronic disease, and attenuated the effect of age. The BI that is composed of plasma biomarkers may be a practical intermediate phenotype for interventions aiming to modify the course of aging.

Associations of healthy aging index and all-cause and cause-specific mortality: a prospective cohort study of UK Biobank participants

The healthy aging index (HAI) has been recently developed as a surrogate measure of biological age. However, to what extent the HAI is associated with all-cause and cause-specific mortality and whether this association differs in younger and older adults remains unknown. We aimed to quantify the association between the HAI and mortality in a population of UK adults. In the prospective cohort study, data are obtained from the UK Biobank. Five HAI components (systolic blood pressure, reaction time, cystatin C, serum glucose, forced vital capacity) were scored 0 (healthiest), 1, and 2 (unhealthiest) according to sex-specific tertiles or clinically relevant cut-points and summed to construct the HAI (range 0-10). Cox proportional hazard regression models were used to estimate the associations of the HAI with the risk of all-cause and cause-specific mortality. 387,794 middle-aged and older participants were followed up for a median of 8.9 years (IQR 8.3-9.5). A total of 14,112 all-cause deaths were documented. After adjustments, each 1-point increase in the HAI was related to a higher risk of all-cause mortality (hazards ratio [HR], 1.17; 95%CI, 1.15-1.18). Such association was stronger among adults younger than 60 years (1.19, 1.17-1.21) than that among those 60 years and older (1.15, 1.14-1.17) (P interaction < 0.001). For each unit increment of the HAI, the multivariate-adjusted HRs for risk of death were 1.28 (1.25-1.31) for cardiovascular diseases, 1.09 (1.07-1.10) for cancer, 1.36 (1.29-1.44) for digestive disease, 1.42 (1.35-1.48) for respiratory disease, 1.42 (1.33-1.51) for infectious diseases, and 1.15 (1.09-1.21) for neurodegenerative disease, respectively. Our findings indicate that the HAI is positively associated with all-cause and cause-specific mortality independent of chronological age. Our results further underscore the importance of effective early-life interventions to slow aging and prevent premature death.