Age-related DNA Methylation Changes Research Articles

Aging drives a program of DNA methylation decay in plant organs.

How organisms age is a question with broad implications for human health. In mammals, DNA methylation is a biomarker for biological age, which may predict age more accurately than date of birth. However, limitations in mammalian models make it difficult to identify mechanisms underpinning age-related DNA methylation changes. Here, we show that the short-lived model plant Arabidopsis thaliana exhibits a loss of epigenetic integrity during aging, causing heterochromatin DNA methylation decay and the expression of transposable elements. We show that the rate of epigenetic aging can be manipulated by extending or curtailing lifespan, and that shoot apical meristems are protected from this aging process. We demonstrate that a program of transcriptional repression suppresses DNA methylation maintenance pathways during aging, and that mutants of this mechanism display a complete absence of epigenetic decay. This presents a new paradigm in which a gene regulatory program sets the rate of epigenomic information loss during aging.

Skin Rejuvenation by Modulation of DNA Methylation.

Skin aging is driven by a complex set of cellular pathways. Among these, epigenetic mechanisms have garnered particular attention, because of their sensitivity to environmental and lifestyle factors. DNA methylation represents the longest known and best understood epigenetic mechanism. We explain how DNA methylation might function as an interface between the environment and the genome of human skin. Exposures to different environmental factors and lifestyles are known to modulate age-related methylation patterns, as illustrated by their effect on DNA methylation clocks. Human skin provides a particularly well-suited tissue for understanding age-related methylation changes and it has been shown recently that modulation of DNA methylation can induce skin rejuvenation. We explain how the use of mildly demethylating agents can be safeguarded to ensure the specific removal of age-related DNA methylation changes. We also identify important areas of future research, leading to a deeper understanding of the mechanisms that drive epigenetic aging and to the development of further refined intervention strategies.

DNA methylation correlates of chronological age in diverse human tissue types

BackgroundWhile the association of chronological age with DNA methylation (DNAm) in whole blood has been extensively studied, the tissue-specificity of age-related DNAm changes remains an active area of research. Studies investigating the association of age with DNAm in tissues such as brain, skin, immune cells, fat, and liver have identified tissue-specific and non-specific effects, thus, motivating additional studies of diverse human tissue and cell types.ResultsHere, we performed an epigenome-wide association study, leveraging DNAm data (Illumina EPIC array) from 961 tissue samples representing 9 tissue types (breast, lung, colon, ovary, prostate, skeletal muscle, testis, whole blood, and kidney) from the Genotype-Tissue Expression (GTEx) project. We identified age-associated CpG sites (false discovery rate < 0.05) in 8 tissues (all except skeletal muscle, n = 47). This included 162,002 unique hypermethylated and 90,626 hypomethylated CpG sites across all tissue types, with 130,137 (80%) hypermethylated CpGs and 74,703 (82%) hypomethylated CpG sites observed in a single tissue type. While the majority of age-associated CpG sites appeared tissue-specific, the patterns of enrichment among genomic features, such as chromatin states and CpG islands, were similar across most tissues, suggesting common mechanisms underlying cellular aging. Consistent with previous findings, we observed that hypermethylated CpG sites are enriched in regions with repressed polycomb signatures and CpG islands, while hypomethylated CpG sites preferentially occurred in non-CpG islands and enhancers. To gain insights into the functional effects of age-related DNAm changes, we assessed the correlation between DNAm and local gene expression changes to identify age-related expression quantitative trait methylation (age-eQTMs). We identified several age-eQTMs present in multiple tissue-types, including in the CDKN2A, HENMT1, and VCWE regions.ConclusionOverall, our findings will aid future efforts to develop biomarkers of aging and understand mechanisms of aging in diverse human tissue types.

Epigenetics in Alzheimer's Disease: A Critical Overview.

Epigenetic modifications have been implicated in a number of complex diseases as well as being a hallmark of organismal aging. Several reports have indicated an involvement of these changes in Alzheimer's disease (AD) risk and progression, most likely contributing to the dysregulation of AD-related gene expression measured by DNA methylation studies. Given that DNA methylation is tissue-specific and that AD is a brain disorder, the limitation of these studies is the ability to identify clinically useful biomarkers in a proxy tissue, reflective of the tissue of interest, that would be less invasive, more cost-effective, and easily obtainable. The age-related DNA methylation changes have also been used to develop different generations of epigenetic clocks devoted to measuring the aging in different tissues that sometimes suggests an age acceleration in AD patients. This review critically discusses epigenetic changes and aging measures as potential biomarkers for AD detection, prognosis, and progression. Given that epigenetic alterations are chemically reversible, treatments aiming at reversing these modifications will be also discussed as promising therapeutic strategies for AD.

Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging.

Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

Nature of epigenetic aging from a single-cell perspective.

Age-related changes in DNA methylation (DNAm) form the basis of the most robust predictors of age-epigenetic clocks-but a clear mechanistic understanding of exactly which aspects of aging are quantified by these clocks is lacking. Here, to clarify the nature of epigenetic aging, we juxtapose the dynamics of tissue and single-cell DNAm in mice. We compare these changes during early development with those observed during adult aging in mice, and corroborate our analyses with a single-cell RNA sequencing analysis within the same multiomics dataset. We show that epigenetic aging involves co-regulated changes as well as a major stochastic component, and this is consistent with transcriptional patterns. We further support the finding of stochastic epigenetic aging by direct tissue and single-cell DNAm analyses and modeling of aging DNAm trajectories with a stochastic process akin to radiocarbon decay. Finally, we describe a single-cell algorithm for the identification of co-regulated and stochastic CpG clusters showing consistent transcriptomic coordination patterns. Together, our analyses increase our understanding of the basis of epigenetic clocks and highlight potential opportunities for targeting aging and evaluating longevity interventions.

DNA methylation clocks for estimating biological age in Chinese cohorts.

Epigenetic clocks are accurate predictors of human chronological age based on the analysis of DNA methylation (DNAm) at specific CpG sites. However, a systematic comparison between DNA methylation data and other omics datasets has not yet been performed. Moreover, available DNAm age predictors are based on datasets with limited ethnic representation. To address these knowledge gaps, we generated and analyzed DNA methylation datasets from two independent Chinese cohorts, revealing age-related DNAm changes. Additionally, a DNA methylation aging clock (iCAS-DNAmAge) and a group of DNAm-based multi-modal clocks for Chinese individuals were developed, with most of them demonstrating strong predictive capabilities for chronological age. The clocks were further employed to predict factors influencing aging rates. The DNAm aging clock, derived from multi-modal aging features (compositeAge-DNAmAge), exhibited a close association with multi-omics changes, lifestyles, and disease status, underscoring its robust potential for precise biological age assessment. Our findings offer novel insights into the regulatory mechanism of age-related DNAm changes and extend the application of the DNAm clock for measuring biological age and aging pace, providing the basis for evaluating aging intervention strategies.

ATAC-clock: An aging clock based on chromatin accessibility

The establishment of aging clocks highlighted the strong link between changes in DNA methylation and aging. Yet, it is not known if other epigenetic features could be used to predict age accurately. Furthermore, previous studies have observed a lack of effect of age-related changes in DNA methylation on gene expression, putting the interpretability of DNA methylation-based aging clocks into question. In this study, we explore the use of chromatin accessibility to construct aging clocks. We collected blood from 159 human donors and generated chromatin accessibility, transcriptomic, and cell composition data. We investigated how chromatin accessibility changes during aging and constructed a novel aging clock with a median absolute error of 5.27 years. The changes in chromatin accessibility used by the clock were strongly related to transcriptomic alterations, aiding clock interpretation. We additionally show that our chromatin accessibility clock performs significantly better than a transcriptomic clock trained on matched samples. In conclusion, we demonstrate that the clock relies on cell-intrinsic chromatin accessibility alterations rather than changes in cell composition. Further, we present a new approach to construct epigenetic aging clocks based on chromatin accessibility, which bear a direct link to age-related transcriptional alterations, but which allow for more accurate age predictions than transcriptomic clocks.

Age-related changes in sperm DNA methylation and their forensic and clinical implications.

As a link between a stable genome and a dynamic environment, epigenetics is a promising tool for mapping age-related changes in human DNA. Methylated cytosine changes at specific loci are generally less studied in sperm DNA than in somatic cell DNA. Age-related methylation changes can be connected to various reproductive health problems and multiple disorders in offspring. In addition, they can be helpful in forensic fields, where testing of specific loci in semen samples found at sexual assault crime scenes can predict a perpetrator's age and narrow down the police investigation. This review focuses on age-related methylation changes in sperm. It covers the biological role of methylation, methylation testing techniques and the implications of methylation changes in forensics and clinical practice.

DNA methylation as a biomarker for cardiometabolic disease risk

Abstract Funding Acknowledgements Type of funding sources: None. Cardiovascular disease (CVD) is the leading cause of death in most countries [1]. Risk factors known to predispose to the development of CVD include increasing age, male gender, diabetes mellitus, high blood cholesterol, tobacco smoking, high blood pressure (hypertension), obesity, physical inactivity, and family history [2]. Elevated plasma homocysteine is also an independent risk factor for CVD [2,3]. The mechanism by which elevated homocysteine contributes to CVD risk is not well understood, but it is well-established that dietary folate and vitamin B supplementation can reduce serum homocysteine levels by facilitating remethylation of homocysteine to methionine [4]. DNA methylation can modulate gene expression in response to exposure to various substances, such as nutrients, smoking, and environmental chemicals.Variation in healthy aging and lifespan is ascribed more to various non-genetic factors than to inherited genetic determinants, and a major goal in aging research is to reveal the epigenetic basis of aging. The remethylation cycle is essential for the systemic methyl donor supply, which is used for important biological processes, such as cytosine-5 methylation of genomic DNA, an epigenetic modification that plays an important role in maintaining genomic stability, chromatin structure, and in controlling transcriptional capacity [2,4]. Methodology/Principal Findings In this prospective study, we examined both gender patients, aged 40-50 years. Relationship between prevalence of Cardiometabolic risk factors (metabolic syndrome, oxidative stress and arterial hypertension) or its predisposing conditions (hypertrigliceridemia, dislipedimia, inusline resistance, D vitamin hipovitaminosis)) and DNA hydroximethylation was investigated. Hydroxymethylation measurement was done using a gold standard technique (liquid chromatography + mass spectrometry), the biological age equivalent was calculated by LC-MS in laboratories Reunis, to verify the potential value of DNA methylation as a CVD biomarker. Results Generally, 296 both gender patients were analyzed regarding metabolic syndrome and oxidative stress, age group 40-50 years (Me=47,1). MethylAge (DNA-hydroxymethylation) in analyzed group has average age 40,1 years old. DNA Hydroxymethylation is higher in those individuals, who has increased waist circumference, as well as, statistically significant correlation was observed between MethylAge waist circumference, metabolic syndrome and hypertriglyceridemia (p&amp;lt;0,05). Conclusion The evidence that the age-related changes in DNA methylation play a role in aging comes from studies of anti-aging interventions (e.g., caloric restriction, iron deficiency, dyslipidemia). Our data showed a link between premature biological ageing and waist circumference, hypertrigliceridimia. Hydroxymethylation of DNA is a good epigenetic marker for aging and risk assessment, especially in alliance with AGEs and oxidative stress research.

Time to relapse in chronic lymphocytic leukemia and DNA-methylation-based biological age

Chronic lymphocytic leukemia (CLL) is a mature B cell neoplasm with a predilection for older individuals. While previous studies have identified epigenetic signatures associated with CLL, whether age-related DNA methylation changes modulate CLL relapse remains elusive. In this study, we examined the association between epigenetic age acceleration and time to CLL relapse in a publicly available dataset. DNA methylation profiling of 35 CLL patients prior to initiating chemoimmunotherapy was performed using the Infinium HumanMethylation450 BeadChip. Four epigenetic age acceleration metrics (intrinsic epigenetic age acceleration [IEAA], extrinsic epigenetic age acceleration [EEAA], PhenoAge acceleration [PhenoAA], and GrimAge acceleration [GrimAA]) were estimated from blood DNA methylation levels. Linear, quantile, and logistic regression and receiver operating characteristic curve analyses were conducted to assess the association between each epigenetic age metric and time to CLL relapse. EEAA (p = 0.011) and PhenoAA (p = 0.046) were negatively and GrimAA (p = 0.040) was positively associated with time to CLL relapse. Simultaneous assessment of EEAA and GrimAA in male patients distinguished patients who relapsed early from patients who relapsed later (p = 0.039). No associations were observed with IEAA. These findings suggest epigenetic age acceleration prior to chemoimmunotherapy initiation is associated with time to CLL relapse. Our results provide novel insight into the association between age-related DNA methylation changes and CLL relapse and may serve has biomarkers for treatment relapse, and potentially, treatment selection.

Age-related methylation changes in the human sperm epigenome.

Advanced paternal age is associated with increased risks for reproductive and offspring medical problems. Accumulating evidence suggests age-related changes in the sperm epigenome as one underlying mechanism. Using reduced representation bisulfite sequencing on 73 sperm samples of males attending a fertility center, we identified 1,162 (74%) regions which were significantly (FDR-adjusted) hypomethylated and 403 regions (26%) being hypermethylated with age. There were no significant correlations with paternal BMI, semen quality, or ART outcome. The majority (1,152 of 1,565; 74%) of age-related differentially methylated regions (ageDMRs) were located within genic regions, including 1,002 genes with symbols. Hypomethylated ageDMRs were closer to transcription start sites than hypermethylated DMRs, half of which reside in gene-distal regions. In this and conceptually related genome-wide studies, so far 2,355 genes have been reported with significant sperm ageDMRs, however most (90%) of them in only one study. The 241 genes which have been replicated at least once showed significant functional enrichments in 41 biological processes associated with development and the nervous system and in 10 cellular components associated with synapses and neurons. This supports the hypothesis that paternal age effects on the sperm methylome affect offspring behaviour and neurodevelopment. It is interesting to note that sperm ageDMRs were not randomly distributed throughout the human genome; chromosome 19 showed a highly significant twofold enrichment with sperm ageDMRs. Although the high gene density and CpG content have been conserved, the orthologous marmoset chromosome 22 did not appear to exhibit an increased regulatory potential by age-related DNA methylation changes.

Is adiposity related to repeat measures of blood leukocyte DNA methylation across childhood and adolescence?

Epigenetic modifications such as DNA methylation may influence gene expression and phenotypes, including obesity in childhood. The directionality of this relationship is nevertheless unclear, and some evidence suggests that adiposity modifies the epigenome, rather than the other way around. In this pilot study, we utilize data from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) study to examine whether measures of adiposity in childhood and early adolescence are associated with repeated measures of blood leukocyte DNA methylation at LINE-1 repetitive elements and two genes implicated in growth and adiposity: H19 and HSD11B2. Longitudinal epigenetic data were generated from cord blood and blood from follow-up visits in early and late adolescence. We assessed interactions between age and measures of body mass index (BMI) at 5 years of age and weight, BMI and waist circumference in early adolescence to infer whether adiposity deflects age-related DNA methylation changes throughout childhood. Applying linear mixed-effects models, we found an inverse association between measures of childhood BMI (kg/m2 ) and early-teen weight (kg) with repeat measures of H19 DNA methylation. We did not observe any statistically significant associations (p-value <.05) between any anthropometric measures and DNA methylation at LINE-1 or HSD11B2. We did not demonstrate statistically significant evidence in support of deflection of age-related DNA methylation trajectories by adiposity-related measures (age by adiposity interaction term). Given the pilot nature of this study, the relationships between repeat measures of DNA methylation and adiposity-measures across childhood merit further exploration in larger study populations.

Hippocampal DNA Methylation, Epigenetic Age, and Spatial Memory Performance in Young and Old Rats.

In humans and rats, aging is associated with a progressive deterioration of spatial learning and memory. These functional alterations are correlated with morphological and molecular changes in the hippocampus. Here, we assessed age-related changes in DNA methylation (DNAm) landscape in the rat hippocampus and the correlation of spatial memory with hippocampal DNAm age in 2.6- and 26.6-month-old rats. Spatial memory performance was assessed with the Barnes maze test. To evaluate learning ability and spatial memory retention, we assessed the time spent by animals in goal sector 1 (GS1) and 3 (GS3) when the escape box was removed. The rat pan-tissue clock was applied to DNAm data from hippocampal tissue. An enrichment pathway analysis revealed that neuron fate commitment, brain development, and central nervous system development were processes whose underlying genes were enriched in hypermethylated CpGs in the old rats. In the old rat hippocampi, the methylation levels of CpG proximal to transcription factors associated with genes Pax5, Lbx1, Nr2f2, Hnf1b, Zic1, Zic4, Hoxd9; Hoxd10, Gli3, Gsx1 and Lmx1b, and Nipbl showed a significant regression with spatial memory performance. Regression analysis of different memory performance indices with hippocampal DNAm age was significant. These results suggest that age-related hypermethylation of transcription factors related to certain gene families, such as Zic and Gli, may play a causal role in the decline in spatial memory in old rats. Hippocampal DNAm age seems to be a reliable index of spatial memory performance in young and old rats.

Making sense of the ageing methylome.

Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.

Dietary Restriction and Rapamycin Affect Brain Aging in Mice by Attenuating Age-Related DNA Methylation Changes.

The fact that dietary restriction (DR) and long-term rapamycin treatment (RALL) can ameliorate the aging process has been reported by many researchers. As the interface between external and genetic factors, epigenetic modification such as DNA methylation may have latent effects on the aging rate at the molecular level. To understand the mechanism behind the impacts of dietary restriction and rapamycin on aging, DNA methylation and gene expression changes were measured in the hippocampi of different-aged mice. Examining the single-base resolution of DNA methylation, we discovered that both dietary restriction and rapamycin treatment can maintain DNA methylation in a younger state compared to normal-aged mice. Through functional enrichment analysis of genes in which DNA methylation or gene expression can be affected by DR/RALL, we found that DR/RALL may retard aging through a relationship in which DNA methylation and gene expression work together not only in the same gene but also in the same biological process. This study is instructive for understanding the maintenance of DNA methylation by DR/RALL in the aging process, as well as the role of DR and RALL in the amelioration of aging.

Premature aging in mice with error-prone protein synthesis.

The main source of error in gene expression is messenger RNA decoding by the ribosome. Translational accuracy has been suggested on a purely correlative basis to positively coincide with maximum possible life span among different rodent species, but causal evidence that translation errors accelerate aging in vivo and limit life span is lacking. We have now addressed this question experimentally by creating heterozygous knock-in mice that express the ribosomal ambiguity mutation RPS9 D95N, resulting in genome-wide error-prone translation. Here, we show that Rps9 D95N knock-in mice exhibit reduced life span and a premature onset of numerous aging-related phenotypes, such as reduced weight, chest deformation, hunchback posture, poor fur condition, and urinary syndrome, together with lymphopenia, increased levels of reactive oxygen species–inflicted damage, accelerated age-related changes in DNA methylation, and telomere attrition. Our results provide an experimental link between translational accuracy, life span, and aging-related phenotypes in mammals.

Role of Age-Related Changes in DNA Methylation in the Disproportionate Susceptibility and Worse Outcomes of Sepsis in Older Adults.

Sepsis, a complex multisystem disorder, is among the top causes of hospitalization and mortality in older adults. However, the mechanisms underlying the disproportionate susceptibility to sepsis and worse outcomes in the elderly are not well understood. Recently, changes in DNA methylation have been shown to be linked to aging processes and age-related diseases. Thus, we postulated that age-related changes in DNA methylation may play a role in the onset and prognosis of sepsis in elderly patients. Here, we performed genome-wide methylation profiling of peripheral blood from patients with sepsis and controls. Among the CpG sites whose methylation changes may contribute to an increase in sepsis susceptibility or mortality, 241 sites that possessed age-related changes in DNA methylation in controls may partly explain the increased risk of sepsis in older adults, and 161 sites whose methylation significantly correlated with age in sepsis group may be the potential mechanisms underlying the worse outcomes of elderly septic patients. Finally, an independent cohort was used to validate our findings. Together, our study demonstrates that age-related changes in DNA methylation may explain in part the disproportionate susceptibility and worse outcomes of sepsis in older adults.

Age-related DNA methylation on Y chromosome and their associations with total mortality among Chinese males.

In view of the sex differences in aging‐related diseases, sex chromosomes may play a critical role during aging process. This study aimed to identify age‐related DNA methylation changes on Y chromosome (ChrY). A two‐stage study design was conducted in this study. The discovery stage contained 419 Chinese males, including 205 from the Wuhan‐Zhuhai cohort panel, 107 from the coke oven workers panel, and 107 from the Shiyan panel. The validation stage contained 587 Chinese males from the Dongfeng‐Tongji sub‐cohort. We used the Illumina HumanMethylation BeadChip to determine genome‐wide DNA methylation in peripheral blood of the study participants. The associations between age and methylation levels of ChrY CpGs were investigated by using linear regression models with adjustment for potential confounders. Further, associations of age‐related ChrY CpGs with all‐cause mortality were tested in the validation stage. We identified the significant associations of 41 ChrY CpGs with age at false discovery rate (FDR) <0.05 in the discovery stage, and 18 of them were validated in the validation stage (p < 0.05). Meta‐analysis of both stages confirmed the robust positive associations of 14 CpGs and negative associations of 4 CpGs with age (FDR<0.05). Among them, cg03441493 and cg17816615 were significantly associated with all‐cause mortality risk [HR(95% CI) = 1.37 (1.04, 1.79) and 0.70 (0.54, 0.93), respectively]. Our results highlighted the importance of ChrY CpGs on male aging.

Mammalian Co-methylation Network Analysis of Species Characteristics

Age and disease prevalence are the two biggest risk factors for COVID-19 symptom severity and death. We therefore hypothesized that increased biological age, beyond chronological age, may be driving disease-related trends in COVID-19 severity. Using the UK Biobank England data, we tested whether a biological age estimate (PhenoAge) measured more than a decade prior to the COVID-19 pandemic was predictive of two COVID-19 severity outcomes (inpatient test positivity and COVID-19 related mortality with inpatient test-confirmed COVID-19). Logistic regression models were used with adjustment for age at the pandemic, sex, ethnicity, baseline assessment centers, and pre-existing diseases/conditions. 613 participants tested positive at inpatient settings between March 16 and April 27, 2020, 154 of whom succumbed to COVID-19. PhenoAge was associated with increased risks of inpatient test positivity and COVID-19 related mortality (ORMortality=1.63 per 5 years, 95% CI: 1.43-1.86, p=4.7x10E-13) adjusting for demographics including age at the pandemic. Further adjustment for pre-existing disease s/conditions at baseline (OR_M=1.50, 95% CI: 1.30-1.73 per 5 years, p=3.1x10E-8) and at the early pandemic (OR_M=1.21, 95% CI: 1.04-1.40 per 5 years, p=0.011) decreased the association. PhenoAge measured in 2006-2010 was associated with COVID-19 severity outcomes more than 10 years later. These associations were partly accounted for by prevalent chronic diseases proximate to COVID-19 infection. Overall, our results suggest that aging biomarkers, like PhenoAge may capture long-term vulnerability to diseases like COVID-19, even before the accumulation of age-related comorbid conditions.