Progress in biological age research

Depressive symptoms partially mediate the relationship between psychosocial factors and epigenetic age acceleration in a multi-racial/ethnic sample of older adults

Psychosocial factors, including cumulative psychosocial stress and loneliness, have been linked to epigenetic aging in older adults. Further, depressive symptoms have established relationships with both psychosocial factors and epigenetic aging. However, it is not known whether depressive symptoms mediate the association between psychosocial factors and epigenetic aging.We conducted linear regression models to examine associations between psychosocial stress, loneliness, and depressive symptoms and five epigenetic age acceleration (AA) measures estimated by DNA methylation in a multi-racial/ethnic sample of 2681 older adults from the Health and Retirement Study (mean age: 70.4 years). For all identified associations, we tested for effect modification by sex and educational attainment and performed mediation analysis to characterize the role of depressive symptoms on these associations.Psychosocial stress, loneliness, and depressive symptoms were each associated with at least one measure of epigenetic AA (FDR q < 0.05). Further, we observed interactions between loneliness, psychosocial stress, and sex on DunedinPACE, as well as loneliness and educational attainment on GrimAA, PhenoAA, and DunedinPACE, with females and individuals without a college degree appearing more sensitive to the psychosocial effects on epigenetic aging. Depressive symptoms mediated between 24 % and 35 % of the relationships between psychosocial stress and HannumAA, GrimAA, and DunedinPACE, as well as 40 % and 37 % of the relationships between loneliness and both GrimAA and DunedinPACE, respectively.

Results

from this study may help elucidate the relationship between psychosocial factors and epigenetic aging, which is critical in understanding the biological mechanisms through which psychosocial factors may contribute to age-related disease.

Multivariate analysis of immunosenescence data in healthy humans and diverse diseases

Introduction

Immunosenescence is a dynamic process, where both genetic and environmental factors account for the substantial inter-individual variability. This paper integrates all the data on immunosenescence markers generated in our laboratory and describes the differences and/or similarities between individuals based on their biological conditions (immunosenescence markers) and their associations with chronological age and health status.

Materials and Methods

The dataset consisted of immunological data from healthy donors, centenarians, patients diagnosed with chronic kidney disease, COVID-19 and non-small cell lung cancer (NSCLC), treatment-naïve or treated with platinum-based chemotherapy. To determine whether there are groups of immunologically different individuals despite their age or clinical condition, cluster analysis was performed. Canonical discriminant analysis was performed to determine which variables characterize each cluster.

Results

There are differences in the expression of immunosenescence markers between healthy subjects and patients diagnosed with different pathological conditions, regardless of their age. Meanwhile, the distribution of the clusters indicates the presence of two separate groups of healthy participants, one of them characterized by a high frequency of naïve lymphocytes, and the other with high expression of terminally differentiated lymphocyte subsets. Advanced NSCLC treatment-naïve patients were in the same cluster as a group of healthy subjects. Additionally, centenarians belong to a different cluster than healthy subjects, suggesting they might have a unique immune signature.

Conclusion

The distribution of clusters appears to be more appropriate than univariate associations of single markers for health and disease research. The present work reveals which immune markers are relevant in different physiological and pathological contexts and indicates the need for deeper studies on the biological age of the immune system.

A Sex-Specific Minimal CpG-Based Model for Biological Aging Using ELOVL2 Methylation Analysis

Significant deviations between chronological and biological age can signal the early risk of chronic diseases, driving the need for tools that accurately determine biological age. While DNA methylation-based clocks have demonstrated strong predictive power for biological aging determination, their clinical application is limited by several barriers including high costs, the need to analyze hundreds of methylation sites using sophisticated platforms and the lack of standardized measurement tools and protocols. In this study, we developed a multivariate linear model using the analysis of eight CpGs within the promoter region of the very long chain fatty acid elongase 2 gene (ELOVL2). The model generated predicts biological age with a mean absolute error (MAE) of 5.04, providing a simplified, cost-effective alternative to more complex methylation-based clocks. Additionally, we identified sex-specific biological clocks, achieving MAEs of 4.37 for males and 5.38 for females, highlighting sex-related molecular differences in the methylation of this gene during aging. Our minimal CpG-based clock offers a practical solution for estimating biological age, with potential applications in clinical practice for assessing age-related disease risks and providing personalized healthcare interventions.

Biological age model using explainable automated CT-based cardiometabolic biomarkers for phenotypic prediction of longevity

We derive and test a CT-based biological age model for predicting longevity, using an automated pipeline of explainable AI algorithms that quantifies skeletal muscle, abdominal fat, aortic calcification, bone density, and solid abdominal organs. We apply these AI tools to abdominal CT scans from 123,281 adults (mean age, 53.6 years; 47% women; median follow-up, 5.3 years). The final weighted CT biomarker selection was based on the index of prediction accuracy. The CT model significantly outperforms standard demographic data for predicting longevity (IPA = 29.2 vs. 21.7; 10-year AUC = 0.880 vs. 0.779; p < 0.001). Age- and sex-corrected survival hazard ratio for the highest-vs-lowest risk quartile was 8.73 (95% CI,8.14-9.36) for the CT biological age model, and increased to 24.79 after excluding cancer diagnoses within 5 years of CT. Muscle density, aortic plaque burden, visceral fat density, and bone density contributed the most. Here we show a personalized phenotypic CT biological age model that can be opportunistically-derived, regardless of clinical indication, to better inform risk assessment.

Age-related features of the pattern of oral fluid patients with non-alcoholic fatty liver disease

INTRODUCTION

In recent years, non-invasive screening methods for diagnosing various human conditions, including those corresponding to biological age, have attracted great interest, one of the sources for non-invasive research of which is oral fluid.

A prospective study of associations between accelerated biological aging and twenty musculoskeletal disorders

BACKGROUND

Musculoskeletal disorders pose major public health challenges, and accelerated biological aging may increase their risk. This study investigates the association between biological aging and musculoskeletal disorders, with a focus on sex-related differences.

METHODS

We analyzed data from 172,332 UK Biobank participants (mean age of 56.03 ± 8.10 years). Biological age was calculated using the KDM-BA and PhenoAge algorithms based on blood biomarkers. Musculoskeletal disorders were diagnosed using the ICD-10 criteria, with sample sizes ranging from 1,182 to 23,668. Logistic regression assessed cross-sectional associations between age acceleration (AA) metrics and musculoskeletal disorders. Accelerated Failure Time (AFT) model was used for survival analysis to evaluate the relationships between AAs and musculoskeletal disorders onset. Models were adjusted for demographic, lifestyle, and socio-economic covariates. The threshold of P-values were set by the Holm-Bonferroni correction.

RESULTS

Cross-sectional analyses reveal significant associations between AAs and fourteen musculoskeletal disorders. Survival analyses indicate that AAs significantly accelerate the onset of nine musculoskeletal disorders, including inflammatory polyarthropathies (RTKDM-BA = 0.993; RTPhenoAge = 0.983), systemic connective tissue disorders (RTKDM-BA = 0.987; RTPhenoAge = 0.980), spondylopathies (RTPhenoAge= 0.994), disorders of bone density and structure (RTPhenoAge= 0.991), gout (RTPhenoAge= 0.968), arthritis (RTPhenoAge= 0.991), pain in joint (RTPhenoAge= 0.989), low back pain (RTPhenoAge= 0.986), and osteoporosis (RTPhenoAge= 0.994). Sensitivity analyses are consistent with the primary findings. Sex-specific variations are observed, with AAs accelerating spondylopathies, arthritis, and low back pain in females, while osteoporosis is accelerated in males.

CONCLUSION

Accelerated biological aging is significantly associated with the incidence of several musculoskeletal disorders. These insights highlight the importance of biological age assessments in gauging musculoskeletal disorder risk, aiding early detection, prevention, and management.

Radiomic-based biomarkers: Transforming age and body composition metrics into personalized age-informed indices

Chronological age has been the standard for quantifying the aging process. While it is simple to quantify it cannot fully discern the biological variability of aging between individuals. The growing body of interest in this variability of human aging has led to the introduction of new biomarkers to operationalize biological age. The inclusion of body composition may provide additional value to biological aging as a prediction and estimation factor of individual health outcomes. Diagnostic images based on radiomic techniques such as Computed Tomography contain an untapped wealth of patient-specific data that remain inaccessible to healthcare providers. These images are beneficial for collecting information from body composition that adds precision and granularity when compared to traditional measures. This information can subsequently be aggregated to construct models for changes in the human body associated with aging. In addition, aging leads to a natural decline in the best parameter of drug dosing in older adults, glomerular filtration rate. Since the conventional models of kidney function are correlated with age and body composition, the radiomic biomarkers representing age-related changes in body composition may also serve as potential new imaging biomarkers of kidney function for personalized dosing. Our review introduces potential radiomic biomarkers as measures of body composition change targeting the aging processes. As a functional example, we have hypothesized an age-related model of radiomics as a covariate of kidney function to improve personalized dosing. Future research focusing on evaluating this hypothesis in human subject studies is acknowledged.

Climbing the longevity pyramid: overview of evidence-driven healthcare prevention strategies for human longevity

Longevity medicine is an emerging and iterative healthcare discipline focusing on early detection, preventive measures, and personalized approaches that aim to extend healthy lifespan and promote healthy aging. This comprehensive review introduces the innovative concept of the "Longevity Pyramid." This conceptual framework delineates progressive intervention levels, providing a structured approach to understanding the diverse strategies available in longevity medicine. At the base of the Longevity Pyramid lies the level of prevention, emphasizing early detection strategies and advanced diagnostics or timely identification of potential health issues. Moving upwards, the next step involves lifestyle modifications, health-promoting behaviors, and proactive measures to delay the onset of age-related conditions. The Longevity Pyramid further explores the vast range of personalized interventions, highlighting the importance of tailoring medical approaches based on genetic predispositions, lifestyle factors, and unique health profiles, thereby optimizing interventions for maximal efficacy. These interventions aim to extend lifespan and reduce the impact and severity of age-related conditions, ensuring that additional years are characterized by vitality and wellbeing. By outlining these progressive levels of intervention, this review offers valuable insights into the evolving field of longevity medicine. This structured framework guides researchers and practitioners toward a nuanced strategic approach to advancing the science and practice of healthy aging.

Metabolic Aging as an Increased Risk for Chronic Obstructive Pulmonary Disease

BACKGROUND/OBJECTIVES

Both aging and chronic obstructive pulmonary disease (COPD) are strongly associated with changes in the metabolome; however, it is unknown whether there are common aging/COPD metabolomic signatures and if accelerated aging is associated with COPD.

METHODS

Plasma from 5704 subjects from the Genetic Epidemiology of COPD study (COPDGene) and 2449 subjects from Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) were profiled using the Metabolon global metabolomics platform (1013 annotated metabolites). Post-bronchodilator spirometry measures of airflow obstruction (forced expiratory volume at one second (FEV1)/forced vital capacity (FVC) < 0.7) were used to define COPD. Elastic net regression was trained on never and former smokers with normal spirometry and no emphysema to create a metabolomic age score which was validated in SPIROMICS subjects.

RESULTS

Our metabolic age score was strongly associated with chronic age in the validation cohort (correlation coefficient = 0.8). COPD subjects with accelerated aging (>7 years difference between metabolic and actual age) had more severe disease compared with those who had decelerated aging (<-7 years difference between metabolic and actual age). COPD and aging metabolites were shared more than expected (p < 0.001), with amino acid and glutathione metabolism among pathways overrepresented.

CONCLUSIONS

These findings suggest a common mechanism between aging and COPD and that COPD is associated with accelerated metabolic aging.

Association between biological ageing and periodontitis: Evidence from a cross-sectional survey and multi-omics Mendelian randomization analysis

AIM

To investigate the relationship and potential causality between biological ageing and periodontitis.

MATERIALS AND METHODS

We obtained the National Health and Nutrition Examination Survey (NHANES) and genome-wide association study (GWAS) summary statistics as well as single-cell sequencing data. Multivariate regression analysis based on cross-sectional data, Mendelian randomization (MR) and multi-omics integration analysis were employed to explore the causal association and potential molecular mechanisms between biological ageing and periodontitis. Additionally, two-step MR mediation analysis explored the risk factors in biological ageing-mediated periodontitis.

RESULTS

We analysed data from 3189 participants in the NHANES data and found that higher biological age was associated with increased risk of periodontitis. MR analyses revealed causal associations between biological age measures and periodontitis risk. Frailty (odds ratio [OR] = 2.08, 95% confidence interval [CI]: 1.04-4.18, p = .039) and GrimAge acceleration (OR = 1.16, 95% CI: 1.01-1.32, p = .033) were causally associated with periodontitis risk, and these results were validated in a large-scale meta-periodontitis GWAS dataset. Additionally, the risk effects of body mass index, waist circumference and lifetime smoking on periodontitis were partially mediated by frailty and GrimAge acceleration.

CONCLUSIONS

Evidence from cross-sectional survey and MR analysis suggests that biological ageing increases the risk of periodontitis. Additionally, improving the associated risk factors can help prevent both ageing and periodontitis.

A study on the development of a fitness age prediction model: the national fitness award cohort study 2017-2021

BACKGROUND

Physical fitness is considered an important indicator of the health of the general public. In particular, the physical fitness of the older adults is an important requirement for determining the possibility of independent living. Therefore, the purpose of this study was to examine the association between chronological age and physical fitness variables in the National Fitness Award Cohort study data and to develop multiple linear regression analyses to predict fitness age using dependent variables.

METHODS

Data from 501,774 (359,303 adults, 142,471 older adults) individuals who participated in the Korea National Fitness Award Cohort Study from 2017 to 2021 were used. The physical fitness tests consisted of 5 candidate markers for adults and 6 candidate markers for the older adults to measure muscle strength, muscle endurance, cardiopulmonary endurance, flexibility, balance, and agility. Pearson's correlation and stepwise regression analyses were used to analyze the data.

RESULTS

We obtained a predicted individual fitness age values from physical fitness indicators for adults and older adults individuals, and the mean explanatory power of the fitness age for adults was [100.882 - (0.029 × VO2max) - (1.171 × Relative Grip Strength) - (0.032 × Sit-up) + (0.032 × Sit and reach) + (0.769 × Sex male = 1; female = 2)] was 93.6% (adjusted R2); additionally, the fitness age for older adults individuals was [79.807 - (0.017 × 2-min step test) - (0.203 × Grip Strength) - (0.031 × 30-s chair stand) - (0.052 × Sit and reach) + (0.985 × TUG) - (3.468 × Sex male = 1; female = 2) was 24.3% (adjusted R2).

CONCLUSIONS

We suggest the use of fitness age as a valid indicator of fitness in adults and older adults as well as a useful motivational tool for undertaking exercise prescription programs along with exercise recommendations at the national level.

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.

Age is just a number: can proteomic analysis provide insight into the aging body?

Recent proteomic studies have increased our understanding of the molecular process of aging, potentially enabling age-related diseases to be treated before the appearance of symptoms. [Formula: see text].

Progress in the study of aging marker criteria in human populations

The use of human aging markers, which are physiological, biochemical and molecular indicators of structural or functional degeneration associated with aging, is the fundamental basis of individualized aging assessments. Identifying methods for selecting markers has become a primary and vital aspect of aging research. However, there is no clear consensus or uniform principle on the criteria for screening aging markers. Therefore, we combine previous research from our center and summarize the criteria for screening aging markers in previous population studies, which are discussed in three aspects: functional perspective, operational implementation perspective and methodological perspective. Finally, an evaluation framework has been established, and the criteria are categorized into three levels based on their importance, which can help assess the extent to which a candidate biomarker may be feasible, valid, and useful for a specific use context.

Sex and gender correlates of sexually polymorphic cognition

BACKGROUND

Sexually polymorphic cognition (SPC) results from the interaction between biological (birth-assigned sex (BAS), sex hormones) and socio-cultural (gender identity, gender roles, sexual orientation) factors. The literature remains quite mixed regarding the magnitude of the effects of these variables. This project used a battery of classic cognitive tests designed to assess the influence of sex hormones on cognitive performance. At the same time, we aimed to assess the inter-related and respective effects that BAS, sex hormones, and gender-related factors have on SPC.

METHODS

We recruited 222 adults who completed eight cognitive tasks that assessed a variety of cognitive domains during a 150-min session. Subgroups were separated based on gender identity and sexual orientation and recruited as follows: cisgender heterosexual men (n = 46), cisgender non-heterosexual men (n = 36), cisgender heterosexual women (n = 36), cisgender non-heterosexual women (n = 38), gender diverse (n = 66). Saliva samples were collected before, during, and after the test to assess testosterone, estradiol, progesterone, cortisol, and dehydroepiandrosterone. Psychosocial variables were derived from self-report questionnaires.

RESULTS

Cognitive performance reflects sex and gender differences that are partially consistent with the literature. Interestingly, biological factors seem to better explain differences in male-typed cognitive tasks (i.e., spatial), while psychosocial factors seem to better explain differences in female-typed cognitive tasks (i.e., verbal).

CONCLUSION

Our results establish a better comprehension of SPC over and above the effects of BAS as a binary variable. We highlight the importance of treating sex as a biological factor and gender as a socio-cultural factor together since they collectively influence SPC.

Associations between the New DNA-Methylation-Based Telomere Length Estimator, the Mediterranean Diet and Genetics in a Spanish Population at High Cardiovascular Risk

Biological aging is a relevant risk factor for chronic diseases, and several indicators for measuring this factor have been proposed, with telomere length (TL) among the most studied. Oxidative stress may regulate telomere shortening, which is implicated in the increased risk. Using a novel estimator for TL, we examined whether adherence to the Mediterranean diet (MedDiet), a highly antioxidant-rich dietary pattern, is associated with longer TL. We determined TL using DNA methylation algorithms (DNAmTL) in 414 subjects at high cardiovascular risk from Spain. Adherence to the MedDiet was assessed by a validated score, and genetic variants in candidate genes and at the genome-wide level were analyzed. We observed several significant associations (p < 0.05) between DNAmTL and candidate genes (TERT, TERF2, RTEL1, and DCAF4), contributing to the validity of DNAmTL as a biomarker in this population. Higher adherence to the MedDiet was associated with lower odds of having a shorter TL in the whole sample (OR = 0.93; 95% CI: 0.85-0.99; p = 0.049 after fully multivariate adjustment). Nevertheless, this association was stronger in women than in men. Likewise, in women, we observed a direct association between adherence to the MedDiet score and DNAmTL as a continuous variable (beta = 0.015; SE: 0.005; p = 0.003), indicating that a one-point increase in adherence was related to an average increase of 0.015 ± 0.005 kb in TL. Upon examination of specific dietary items within the global score, we found that fruits, fish, "sofrito", and whole grains exhibited the strongest associations in women. The novel score combining these items was significantly associated in the whole population. In the genome-wide association study (GWAS), we identified ten polymorphisms at the suggestive level of significance (p < 1 × 10-5) for DNAmTL (intergenics, in the IQSEC1, NCAPG2, and ABI3BP genes) and detected some gene-MedDiet modulations on DNAmTL. As this is the first study analyzing the DNAmTL estimator, genetics, and modulation by the MedDiet, more studies are needed to confirm these findings.

A framework of biomarkers for vascular aging: a consensus statement by the Aging Biomarker Consortium

Aging of the vasculature, which is integral to the functioning of literally all human organs, serves as a fundamental physiological basis for age-related alterations as well as a shared etiological mechanism for various chronic diseases prevalent in the elderly population. China, home to the world's largest aging population, faces an escalating challenge in addressing the prevention and management of these age-related conditions. To meet this challenge, the Aging Biomarker Consortium of China has developed an expert consensus on biomarkers of vascular aging (VA) by synthesizing literature and insights from scientists and clinicians. This consensus provides a comprehensive assessment of biomarkers associated with VA and presents a systemic framework to classify them into three dimensions: functional, structural, and humoral. Within each dimension, the expert panel recommends the most clinically relevant VA biomarkers. For the functional domain, biomarkers reflecting vascular stiffness and endothelial function are highlighted. The structural dimension encompasses metrics for vascular structure, microvascular structure, and distribution. Additionally, proinflammatory factors are emphasized as biomarkers with the humoral dimension. The aim of this expert consensus is to establish a foundation for assessing the extent of VA and conducting research related to VA, with the ultimate goal of improving the vascular health of the elderly in China and globally.