Comparative validation of three DNA methylation algorithms of ageing and a frailty index in relation to mortality: results from the ESTHER cohort study

Frailty, polypharmacy, malnutrition, chronic conditions, and quality of life in the elderly: Large population-based study

BACKGROUND

Aging, a significant public health issue, is associated with multiple concurrent chronic diseases and aging-related conditions (geriatric syndromes).

OBJECTIVE

To investigate the impact of age and chronic conditions on geriatric syndromes and the intercorrelations between multiple geriatric syndromes and quality of life (QoL) in the elderly (≥65 years) at the population level.

METHODS

A large representative sample was randomly selected from a county with 17 towns and 811,867 residents, with multiple chronic conditions, geriatric syndromes (frailty, polypharmacy, and malnutrition), and QoL assesses and compared between geriatric and nongeriatric populations and among subgroups of the elderly. Associations of demographic information and chronic conditions with geriatric conditions and QoL in the elderly were assessed using multivariable-adjusted logistic regression. Intercorrelations between age, multiple geriatric syndromes, and QoL were investigated using both correlation analysis and restricted cubic splines (RCS)-based multivariable-adjusted dose-response analysis.

RESULTS

Elderly people comprised 43.4% of the whole population, and prevalence of frailty, (pre-)malnutrition, polypharmacy, and impaired QoL among the elderly (median age, 73 years; male proportion, 51.0%) was 8.3%, 15.6%, 3.2%, and 10.8%, respectively. Prevalence of geriatric syndromes mostly did not significantly differ among different age subgroups of the elderly (except that frailty occurred more often with older age) or by gender. (Pre-)malnutrition was significantly associated with less often obesity and more frequent constipation, polypharmacy with more often diabetes and constipation, frailty with more frequent constipation and hernia, and impaired QoL with more often hypertension, diabetes, physical disability, and constipation. MNA-SF, GFI, and EQ-5D-5L scores and number of drugs used mostly significantly predicted the other geriatric syndromes and QoL. Impaired QoL was significantly associated with more often frailty, (pre-)malnutrition, and polypharmacy, and frailty with more frequent (pre-)malnutrition and polypharmacy. At 1.5-year follow-up, impaired QoL was significantly linked to polypharmacy and frailty at baseline; (pre-)malnutrition was significantly associated with frailty at baseline; polypharmacy was significantly linked to frailty at baseline; frailty was significantly linked to both (pre-)malnutrition and polypharmacy at baseline. Causal mediation analyses showed that frailty mediated the linkage between polypharmacy and worse QoL, and also that polypharmacy mediated the linkage between frailty and worse QoL.

CONCLUSIONS

In this large population-based study of the elderly with prospective follow-up, multiple chronic conditions were associated with one or more of the investigated geriatric syndromes. Geriatric syndromes were mostly significantly intercorrelated with and well predictive of each other and QoL, and there existed causal relationships between geriatric syndromes and QoL with other geriatric syndromes being mediators. The findings might be subject to some bias due to residual confounding factors not available in the dataset. It would be important to perform personalized geriatric syndromes stratified by chronic conditions, and active prevention or intervention of any syndrome might help to reduce the others and improve QoL.

CLINICALTRIAL

Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

Value of combining biological age with assessment of individual frailty to optimize management of cancer treated with targeted therapies: model of chronic myeloid leukemia treated with tyrosine kinase inhibitors (BIO-TIMER trial)

BACKGROUND

In the era of targeted therapies, the influence of aging on cancer management varies from one patient to another. Assessing individual frailty using geriatric tools has its limitations, and is not appropriate for all patients especially the youngest one. Thus, assessing the complementary value of a potential biomarker of individual aging is a promising field of investigation. The chronic myeloid leukemia model allows us to address this question with obvious advantages: longest experience in the use of tyrosine kinase inhibitors, standardization of therapeutic management and response with minimal residual disease and no effect on age-related diseases. Therefore, the aim of the BIO-TIMER study is to assess the biological age of chronic myeloid leukemia or non-malignant cells in patients treated with tyrosine kinase inhibitors and to determine its relevance, in association or not with individual frailty to optimize the personalised management of each patient.

METHODS

The BIO-TIMER study is a multi-center, prospective, longitudinal study aiming to evaluate the value of combining biological age determination by DNA methylation profile with individual frailty assessment to personalize the management of chronic myeloid leukemia patients treated with tyrosine kinase inhibitors. Blood samples will be collected at diagnosis, 3 months and 12 months after treatment initiation. Individual frailty and quality of life will be assess at diagnosis, 6 months after treatment initiation, and then annually for 3 years. Tolerance to tyrosine kinase inhibitors will also be assessed during the 3-year follow-up. The study plans to recruit 321 patients and recruitment started in November 2023.

DISCUSSION

The assessment of individual frailty should make it possible to personalize the treatment and care of patients. The BIO-TIMER study will provide new data on the role of aging in the management of chronic myeloid leukemia patients treated with tyrosine kinase inhibitors, which could influence clinical decision-making.

TRIAL REGISTRATION

ClinicalTrials.gov , ID NCT06130787; registered on November 14, 2023.

Deficit Accumulation Index and Biological Markers of Aging in Survivors of Childhood Cancer

Importance

Survivors of childhood cancer experience premature aging compared with community controls. The deficit accumulation index (DAI) uses readily available clinical data to measure physiological age in survivors; however, little data exist on how well deficit accumulation represents underlying biological aging among survivors of cancer.

Objective

To examine the associations between the DAI and epigenetic age acceleration (EAA) and mean leukocyte telomere length (LTL).

Design, Setting, and Participants

This cross-sectional study analyzed data from the St Jude Lifetime Cohort, an assessment of survivors of childhood cancer who were treated at St Jude Children's Research Hospital in Memphis, Tennessee. Data were collected between 2007 and 2016, assayed between 2014 and 2019, and analyzed between 2022 and 2023. Participants were adult survivors who were diagnosed between 1962 and 2012 and who survived 5 years or more from time of diagnosis. The analyses were restricted to survivors with European ancestry, as there were too few survivors with non-European ancestry.

Exposures

The DAI included 44 aging-related items, such as chronic health conditions and functional, psychosocial, and mental well-being. Item responses were summed and divided by the total number of items, resulting in a ratio ranging from 0 to 1. These DAI results were categorized based on reported associations with hospitalization and mortality: low, defined as a DAI less than 0.2; medium, defined as a DAI of 0.2 to less than 0.35; and high, defined as a DAI of 0.35 or higher.

Main Outcomes and Measures

Genome-wide DNA methylation was generated from peripheral blood mononuclear cell-derived DNA. The EAA was calculated as the residuals from regressing the Levine epigenetic age on chronological age. The mean LTL was estimated using whole-genome sequencing data.

Results

This study included 2101 survivors of childhood cancer (1122 males [53.4%]; mean [SD] age, 33.9 [9.1] years; median [IQR] time since diagnosis, 25.1 [18.7-31.9] years) with European ancestry. Compared with survivors in the low DAI group, those in the high DAI group experienced 3.7 more years of EAA (β = 3.66; 95% CI, 2.47-4.85; P < .001), whereas those in the medium DAI group experienced 1.8 more years of EAA (β = 1.77; 95% CI, 0.84-2.69; P < .001), independent of treatment exposures. The EAA and DAI association was consistent across 3 common diagnoses (acute lymphoblastic leukemia, Hodgkin lymphoma, and central nervous system tumors) and across chronological age groups. For example, among acute lymphoblastic leukemia survivors, those in the medium DAI group (β = 2.27; 95% CI, 0.78-3.76; P = .001) experienced greater EAA vs those in the low DAI group. Similarly, among survivors younger than 30 years, the high DAI group experienced 4.9 more years of EAA vs the low DAI group (β = 4.95; 95% CI, 2.14-7.75; P < .001). There were no associations between mean LTL residual and the DAI.

Conclusions and Relevance

This cross-sectional study of survivors of childhood cancer showed that the DAI was associated with EAA, suggesting an underlying biological process to the accumulation of deficits. Both the DAI and EAA were effective at identifying aging phenotypes, and either may be used to measure aging and response to interventions targeting aging pathways.

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.

The lipidomic correlates of epigenetic aging across the adult lifespan: A population-based study

Lipid signaling is involved in longevity regulation, but which specific lipid molecular species affect human biological aging remains largely unknown. We investigated the relation between complex lipids and DNA methylation-based metrics of biological aging among 4181 participants (mean age 55.1 years (range 30.0-95.0)) from the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany. The absolute concentration of 14 lipid classes, covering 964 molecular species and 267 fatty acid composites, was measured by Metabolon Complex Lipid Panel. DNA methylation-based metrics of biological aging (AgeAccelPheno and AgeAccelGrim) were calculated based on published algorithms. Epigenome-wide association analyses (EWAS) of biological aging-associated lipids and pathway analysis were performed to gain biological insights into the mechanisms underlying the effects of lipidomics on biological aging. We found that higher levels of molecular species belonging to neutral lipids, phosphatidylethanolamines, phosphatidylinositols, and dihydroceramides were associated with faster biological aging, whereas higher levels of lysophosphatidylcholine, hexosylceramide, and lactosylceramide species were associated with slower biological aging. Ceramide, phosphatidylcholine, and lysophosphatidylethanolamine species with odd-numbered fatty acid tail lengths were associated with slower biological aging, whereas those with even-numbered chain lengths were associated with faster biological aging. EWAS combined with functional pathway analysis revealed several complex lipids associated with biological aging as important regulators of known longevity and aging-related pathways.

An emerging role of astrocytes in aging/neuroinflammation and gut-brain axis with consequences on sleep and sleep disorders

Understanding the role of astrocytes in the central nervous system has changed dramatically over the last decade. The accumulating findings indicate that glial cells are involved not only in the maintenance of metabolic and ionic homeostasis and in the implementation of trophic functions but also in cognitive functions and information processing in the brain. Currently, there are some controversies regarding the role of astrocytes in complex processes such as aging of the nervous system and the pathogenesis of age-related neurodegenerative diseases. Many findings confirm the important functional role of astrocytes in age-related brain changes, including sleep disturbance and the development of neurodegenerative diseases and particularly Alzheimer's disease. Until recent years, neurobiological research has focused mainly on neuron-glial interactions, in which individual astrocytes locally modulate neuronal activity and communication between neurons. The review considers the role of astrocytes in the physiology of sleep and as an important "player" in the development of neurodegenerative diseases. In addition, the features of the astrocytic network reorganization during aging are discussed.

Derivation and validation of an epigenetic frailty risk score in population-based cohorts of older adults

DNA methylation (DNAm) patterns in peripheral blood have been shown to be associated with aging related health outcomes. We perform an epigenome-wide screening to identify CpGs related to frailty, defined by a frailty index (FI), in a large population-based cohort of older adults from Germany, the ESTHER study. Sixty-five CpGs are identified as frailty related methylation loci. Using LASSO regression, 20 CpGs are selected to derive a DNAm based algorithm for predicting frailty, the epigenetic frailty risk score (eFRS). The eFRS exhibits strong associations with frailty at baseline and after up to five-years of follow-up independently of established frailty risk factors. These associations are confirmed in another independent population-based cohort study, the KORA-Age study, conducted in older adults. In conclusion, we identify 65 CpGs as frailty-related loci, of which 20 CpGs are used to calculate the eFRS with predictive performance for frailty over long-term follow-up.

Associations of DNA methylation algorithms of aging and cancer risk: Results from a prospective cohort study

Background

Previous studies have shown that three DNA methylation (DNAm) based algorithms of aging, DNAm PhenoAge acceleration (AgeAccelPheno), DNAm GrimAge acceleration (AgeAccelGrim), and mortality risk score (MRscore), to be strong predictors of mortality and aging related outcomes. We aimed to investigate if and to what extent these algorithms predict cancer.

Methods

In four subsets (n = 727, 1003, 910, and 412) of a population-based cohort from Germany, DNA methylation in whole blood was measured using the Infinium Methylation EPIC BeadChip kit or the Infinium HumanMethylation450K BeadChip Assay (Illumina.Inc, San Diego, CA, USA). AgeAccelPheno, AgeAccelGrim, and a revised MRscore based on 8 CpGs only (MRscore-8CpGs), were calculated. Hazard ratios (HRs) were calculated to assess associations of the three DNAm algorithms with total cancer risk and risk of invasive breast, lung, prostate, and colorectal cancer incidence.

Findings

During 17 years of follow-up, a total of 697 malignant tumors (thereof breast cancer = 75, lung cancer = 146, prostate cancer = 114, colorectal cancer = 155) were observed. All three algorithms showed strong positive associations with lung cancer risk in a dose response manner, with adjusted HRs per SD increase in AgeAccelPheno, AgeAccelGrim, and MRscore-8CpGs, of 1·37 (1·03-1·82), 1·74 (1·11-2·73), and 2·06 (1·39-3·06), respectively. By contrast, strong inverse associations were seen with breast cancer risk [adjusted HRs 0·65 (0·49-0·86), 0·45 (0·25-0·80), and 0·42 (0·25-0·70), respectively]. Weak positive associations of MRscore-8CpGs were seen with total cancer risk.

Interpretation

The DNAm algorithms, particularly the MRscore-8CpGs, have potential to contribute to site-specific cancer risk prediction.

Funding

The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany). The work of Xiangwei Li was supported by a grant from Fondazione Cariplo (Bando Ricerca Malattie invecchiamento, #2017-0653).