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Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components from CpG-level data as input for biological age prediction. Our retrained principal-component versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or prior knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of principal component-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies, and clinical trials of aging interventions.

While chronological age is the single biggest risk factor for cancer, it is less clear whether frailty, an age-related state of physiological decline, may also predict cancer incidence. We assessed the associations of frailty index (FI) and frailty phenotype (FP) scores with the incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, melanoma) in 453,144 UK Biobank (UKB) and 36,888 Screening Across the Lifespan Twin study (SALT) participants, who aged 38–73 years and had no cancer diagnosis at baseline. During a median follow-up of 10.9 and 10.7 years, 53,049 (11.7%) and 4,362 (11.8%) incident cancers were documented in UKB and SALT, respectively. Using multivariable-adjusted Cox models, we found a higher risk of any cancer in frail vs. non-frail UKB participants, when defined by both FI (hazard ratio [HR] = 1.22; 95% confidence interval [CI] = 1.17–1.28) and FP (HR = 1.16; 95% CI = 1.11–1.21). The FI in SALT similarly predicted risk of any cancer (HR = 1.31; 95% CI = 1.15–1.49). Moreover, frailty was predictive of lung cancer in UKB, although this association was not observed in SALT. Adding frailty scores to models including age, sex, and traditional cancer risk factors resulted in little improvement in C-statistics for most cancers. In a within-twin-pair analysis in SALT, the association between FI and any cancer was attenuated within monozygotic but not dizygotic twins, indicating that it may partly be explained by genetic factors. Our findings suggest that frailty scores are associated with the incidence of any cancer and lung cancer, although their clinical utility for predicting cancers may be limited.

Apolipoprotein E (APOE) ε4, the strongest genetic risk factor for late onset Alzheimer's disease (LOAD), has been associated with cognitive decline independent from AD pathology, but the role for other LOAD risk genes in normal cognitive aging is less studied. We examined the effect of APOE ε4 and several different polygenic risk scores (PRS) for LOAD on cognitive level and decline in aging, using longitudinal data from the UK Biobank. While PRS-LOAD including all variants (except APOE) predicted cognitive level, APOE ε4 and PRS-LOAD based on 17 non-APOE gene variants with strong association to AD (p < 5e-8) predicted age-related decline in verbal numeric reasoning. The effect on decline were partly driven by 4 variants involved in the immune system. Those variants also predicted serum levels of the inflammatory marker C-reactive protein (CRP), but CRP did not mediate the effect on decline. Those findings suggest genetic variations in immune functions play a role in aspects of cognitive aging that may be independent of LOAD pathology as well as systemic inflammation measured by CRP.

While midlife adiposity is a risk factor for dementia, adiposity in late-life appears to be associated with lower risk. What drives the associations is poorly understood, especially the inverse association in late-life. Using results from genome-wide association studies, we identified inflammation and lipid metabolism as biological pathways involved in both adiposity and dementia. To test if these factors mediate the effect of midlife and/or late-life adiposity on dementia, we then used cohort data from the Swedish Twin Registry, with measures of adiposity and potential mediators taken in midlife (age 40–64, n = 5999) or late-life (age 65–90, n = 7257). Associations between body-mass index (BMI), waist-hip ratio (WHR), C-reactive protein (CRP), lipid levels, and dementia were tested in survival and mediation analyses. Age was used as the underlying time scale, and sex and education included as covariates in all models. Fasting status was included as a covariate in models of lipids. One standard deviation (SD) higher WHR in midlife was associated with 25% (95% CI 2–52%) higher dementia risk, with slight attenuation when adjusting for BMI. No evidence of mediation through CRP or lipid levels was present. After age 65, one SD higher BMI, but not WHR, was associated with 8% (95% CI 1–14%) lower dementia risk. The association was partly mediated by higher CRP, and suppressed when high-density lipoprotein levels were low. In conclusion, the negative effects of midlife adiposity on dementia risk were driven directly by factors associated with body fat distribution, with no evidence of mediation through inflammation or lipid levels. There was an inverse association between late-life adiposity and dementia risk, especially where the body’s inflammatory response and lipid homeostasis is intact. CC BY 4.0Published: 03 October 2022© 2022, The Author(s)© 2022 Springer Nature Switzerland AG. Part of Springer Nature.Ida K. Karlsson ida.karlsson@ki.seThis work was supported by the Strategic Research Program in Epidemiology at Karolinska Institutet; the Swedish Research Council for Health, Working Life and Welfare (2018-01201); the Swedish Research Council (2016-03081); and the National Institutes of Health (R01 AG060470).Open access funding provided by Karolinska Institute. We acknowledge the Swedish Twin Registry for access to data. The Swedish Twin Registry is managed by Karolinska Institutet and receives funding through the Swedish Research Council under the Grant No. 2017-00641. The STR substudies were supported by the National Institutes of Health (Grants R01 AG10175, R01 AG08724, R01 AG08861, R01 AG028555, and U01 DK066134), the MacArthur Foundation Research Network on Successful Aging, the Axel and Margaret Ax:son Johnsons Foundation, the Swedish Research Council, the Swedish Foundation for Health Care Sciences and Allergy Research, and the Swedish Council for Working Life and Social Research (2013-2292).

Background: Observational studies have suggested that fatty acids such as higher levels of n-3 polyunsaturated fatty acids (PUFAs) may prevent frailty. By using Mendelian randomization analysis, we examined the relationship between fatty acids and frailty. Methods: We used summary statistics data for single-nucleotide polymorphisms associated with plasma levels of saturated fatty acids (palmitic acid, stearic acid), mono-unsaturated fatty acids (MUFAs) (palmitoleic acid, oleic acid), n-6 PUFAs (linoleic acid, arachidonic acid), and n-3 PUFAs (alpha-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid, docosahexaenoic acid), and the corresponding data for frailty index (FI) in 356,432 individuals in the UK Biobank. Results: Although there were no robust associations on the MUFAs or the PUFAs, genetically predicted higher plasma stearic acid level (one of saturated fatty acids) was statistically significantly associated with higher FI (β = 0.178, 95% confidence interval = −0.050 to 0.307, p = 0.007). Such a relationship was also observed in a multivariate MR (β = 0.361, 95% confidence interval = 0.155 to 0.567, p = 0.001). Genetically predicted higher palmitic acid was also significantly associated with higher FI (β = 0.288, 95% confidence interval = 0.128 to 0.447, p &lt, 0.001) in the multivariate MR analysis. Conclusions: The present MR study implies that saturated fatty acids, especially stearic acid, is a risk factor of frailty.

Background Frailty has been identified as a risk factor for cognitive impairment and dementia. However, it is not known whether familial factors, such as genetics and shared environmental factors, underlie this association. We analyzed the association between frailty and the risk of dementia in a large twin cohort and examined the role of familial factors in the association. Methods The Rockwood frailty index (FI) based on 44 health deficits was used to assess frailty. The population-level association between FI and the risk of all-cause dementia was analyzed in 41,550 participants of the Screening Across the Lifespan Twin (SALT) study (full sample, aged 41–97 years at baseline), using Cox and competing risk models. A subsample of 10,487 SALT participants aged 65 and older who received a cognitive assessment (cognitive sample) was used in a sensitivity analysis to assess the effect of baseline cognitive level on the FI-dementia association. To analyze the influence of familial effects on the FI-dementia association, a within-pair analysis was performed. The within-pair model was also used to assess whether the risk conferred by frailty varies by age at FI assessment. Results A total of 3183 individuals were diagnosed with dementia during the 19-year follow-up. A 10% increase in FI was associated with an increased risk of dementia (hazard ratio [HR] 1.17 (95% confidence interval [CI] 1.07, 1.18)) in the full sample adjusted for age, sex, education, and tobacco use. A significant association was likewise found in the cognitive sample, with an HR of 1.13 (95% CI 1.09, 1.20), adjusted for age, sex, and cognitive level at baseline. The associations were not attenuated when adjusted for APOE ɛ4 carrier status or considering the competing risk of death. After adjusting for familial effects, we found no evidence for statistically significant attenuation of the effect. The risk conferred by higher FI on dementia was constant after age 50 until very old age. Conclusions A higher level of frailty predicts the risk of dementia and the association appears independent of familial factors. Targeting frailty might thus contribute to preventing or delaying dementia.

Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Background Biomarker-disease relationships are extensively investigated. However, associations between common clinical biomarkers and healthspan, the disease-free lifespan, are largely unknown. We aimed to explore the predictive values of ten biomarkers on healthspan and lifespan, and to identify putative causal mechanisms. Methods Using data from 12,098 Swedish individuals aged 47–94 years, we examined both serum concentrations and genetically predicted levels of ten glycemic, lipid-, inflammatory, and hematological biomarkers. During a follow-up period of up to 16 years, 3681 incident cases of any chronic disease (i.e., end of healthspan) and 2674 deaths (i.e., end of lifespan) were documented. Cox regression models were applied to estimate the associations of a one standard deviation increase in biomarkers with healthspan and lifespan. Findings Seven out of ten serum biomarkers were significantly associated with risks of any chronic disease and death; elevated glycemic biomarkers and high-density lipoprotein-related biomarkers showed the strongest detrimental (hazard ratio [HR] 1·29 [95% CI 1·24–1·34]) and protective effects (HR 0·92 [95% CI 0·89–0·96]), respectively. Genetic predisposition to elevated fasting blood glucose (FBG) was associated with increased risks of any chronic disease (HR 1·05 [95% CI 1·02–1·09]); genetically determined higher C-reactive protein correlated with lower death risks (HR 0·91 [95% CI 0·87–0·95]). Notably, the genetically proxied FBG-healthspan association was largely explained by serum FBG concentration. Interpretation Circulating concentrations of glycemic, lipid-, and inflammatory biomarkers are predictive of healthspan and lifespan. Glucose control is a putative causal mechanism and a potential intervention target for healthspan maintenance. Funding This study was supported by the Swedish Research Council (2015–03,255, 2018–02,077), FORTE (2013–2292), the Loo & Hans Osterman Foundation, the Foundation for Geriatric Diseases, the Magnus Bergwall Foundation, the Strategic Research Program in Epidemiology at Karolinska Institutet (SH, JJ), the China Scholarship Council, and the Swedish National Graduate School for Competitive Science on Ageing and Health. The Swedish Twin Registry is managed by Karolinska Institutet and receives funding as an infrastructure through the Swedish Research Council, 2017–00,641.

BACKGROUND: frailty shows an upward trajectory with age, and higher levels increase the risk of mortality. However, it is less known whether the shape of frailty trajectories differs by age at death or whether the rate of change in frailty is associated with mortality. OBJECTIVES: to assess population frailty trajectories by age at death and to analyse whether the current level of the frailty index (FI) i.e. the most recent measurement or the person-specific rate of change is more predictive of mortality. METHODS: 3,689 individuals from three population-based cohorts with up to 15 repeated measurements of the Rockwood frailty index were analysed. The FI trajectories were assessed by stratifying the sample into four age-at-death groups: 90 years. Generalised survival models were used in the survival analysis. RESULTS: the FI trajectories by age at death showed that those who died at CC BY-NC-ND 4.0© The Author(s) 2021. Published by Oxford University Press on behalf of the British Geriatrics SocietyAddress correspondence to: Juulia Jylhävä. Tel: 358-505351712. Email: juulia.jylhava@ki.seDeclaration of Sources of Funding: National Institutesof Health (grant numbers R01 AG04563, AG10175,AG028555, AG08861-09); the MacArthur Foundation Research Network on Successful Aging; the Swedish Council for Working Life and Social Research (FAS/FORTE) (grant numbers 97:0147:1B to N.L.P., 2009-0795 toN.L.P.); the Swedish Research Council (grant numbers 825-2007-7460, 825-2009-6141, 521-2013-8689, 2015-03255, 2018-02077 to J.J., 2016-03081, 2019-01272 to S.H.); JPND/Swedish Research Council (2015-06796 to N.L.P.); FORTE (2013-2292 to N.L.P.); the Loo & Hans Osterman Foundation to S.H. and J.J.; the Foundation for Geriatric Diseases to S.H.; the Magnus Bergwall Foundation to S.H.; the Strategic Research Program in Epidemiology at Karolinska Institutet to S.H. and J.J. and the King Gustaf V’s and Queen Victoria’s Freemason Foundation to S.H. and China Scholarship Council to G.B. and X.L. The financial sponsors had no role in the design, execution, analysis andinterpretation of data, or writing of the study.

Background: Epigenetic mechanisms are important in aging and may be involved in late-life changes in cognitive abilities. We conducted an epigenome-wide association study of leukocyte DNA methylation in relation to level and change in cognitive abilities, from midlife through late life in 535 Swedish twins. Results: Methylation levels were measured with the Infinium Human Methylation 450 K or Infinium MethylationEPIC array, and all sites passing quality control on both arrays were selected for analysis (n = 250,816). Empirical Bayes estimates of individual intercept (age 65), linear, and quadratic change were obtained from latent growth curve models of cognitive traits and used as outcomes in linear regression models. Significant sites (p < 2.4 × 10–7) were followed up in between-within twin pair models adjusting for familial confounding and full-growth modeling. We identified six significant associations between DNA methylation and level of cognitive abilities at age 65: cg18064256 (PPP1R13L) with processing speed and spatial ability; cg04549090 (NRXN3) with spatial ability; cg09988380 (POGZ), cg25651129 (-), and cg08011941 (ENTPD8) with working memory. The genes are involved in neuroinflammation, neuropsychiatric disorders, and ATP metabolism. Within-pair associations were approximately half that of between-pair associations across all sites. In full-growth curve models, associations between DNA methylation and cognitive level at age 65 were of small effect sizes, and associations between DNA methylation and longitudinal change in cognitive abilities of very small effect sizes. Conclusions: Leukocyte DNA methylation was associated with level, but not change in cognitive abilities. The associations were substantially attenuated in within-pair analyses, indicating they are influenced in part by genetic factors. CC BY 4.0© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, whichpermits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit lineto the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutoryregulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Correspondence: ida.karlsson@ki.se Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

Background This study aims to investigate if DNA methylation of the apolipoprotein E (APOE) locus affects the risks of dementia, Alzheimeŕs disease (AD) or cardiovascular disease (CVD). Methods DNA methylation across theAPOE gene has previously been categorized into three distinct regions: a hypermethylated region in the promoter, a hypomethylated region in the first two introns and exons and a hypermethylated region in the 3′exon that also harbours theAPOE ε2 and ε4 alleles. DNA methylation levels in leukocytes were measured using the Illumina 450K array in 447 Swedish twins (mean age 78.1 years). We used logistic regression to investigate whether methylation levels in those regions affect the odds of disease. Results We found that methylation levels in the promoter region were associated with dementia and AD after adjusting for sex, age at blood draw, education, smoking and relatedness among twins [odds ratio (OR) 1.32 per standard deviation increase in methylation levels, 95% confidence interval (CI) 1.08–1.62 for dementia; OR 1.38, 95% CI 1.07–1.78 for AD). We did not detect any difference in methylation levels between CVD cases and controls. Results were similar when comparing within discordant twin pairs, and did not differ as a function ofAPOE genotype. Conclusions We found that higher DNA methylation levels in the promoter region ofAPOE increase the odds of dementia and AD, but not CVD. The effect was independent ofAPOE genotype, indicating that allelic variation and methylation variation inAPOE may act independently to increase the risk of dementia.

Epigenetic clocks are widely used aging biomarkers, but they are calculated from methylation data for individual CpGs that can be surprisingly unreliable. We report that technical noise causes six major epigenetic clocks to deviate by 3 to 9 years between replicates. We present a novel computational solution: we perform principal component analysis followed by biological age prediction using principal components, extracting shared age-related changes across CpGs while ignoring noise from individual CpGs. Our novel principal-component versions of six clocks show agreement between most technical replicates within 1 year, and increased stability in short- and long-term longitudinal studies. This requires only one additional step compared to traditional clocks, does not require prior knowledge of CpG reliabilities, and can improve the reliability of any existing or future epigenetic biomarker. The extremely high reliability of principal component epigenetic clocks makes them particularly useful for personalized medicine and clinical trials evaluating novel aging interventions.

DNA methylation outlier burden has been suggested as a potential marker of biological age. An outlier is typically defined as DNA methylation levels at any one CpG site that are three times beyond the inter-quartile range from the 25th or 75th percentiles compared to the rest of the population. DNA methylation outlier burden (the number of such outlier sites per individual) increases exponentially with age. However, these findings have been observed in small samples. Here, we showed an association between age and log10-transformed DNA methylation outlier burden in a large cross-sectional cohort, the Generation Scotland Family Health Study (N=7,010, β=0.0091, p−16), and in two longitudinal cohort studies, the Lothian Birth Cohorts of 1921 (N=430, β=0.033, p=7.9×10−4) and 1936 (N=898, β=7.9×10−3, p=0.074). Significant confounders of both cross-sectional and longitudinal associations between outlier burden and age included white blood cell proportions, BMI, smoking, and batch effects. In Generation Scotland, the increase in epigenetic outlier burden with age was not purely an artefact of an increase in DNA methylation level variability with age (epigenetic drift). Log10-transformed DNA methylation outlier burden in Generation Scotland was not related to self-reported, or family history of, age-related diseases and it was not heritable (SNP-based heritability of 4.4%, p=0.18). Finally, DNA methylation outlier burden was not significantly related to survival in either of the Lothian Birth Cohorts individually but it was in a meta-analysis (HRmeta=1.12; 95%CImeta=[1.02; 1.21]; pmeta=0.021). These findings suggest that, while it does not associate with ageing-related health outcomes, DNA methylation outlier burden does track chronological ageing and may also relate to survival. DNA methylation outlier burden may thus be useful as a marker of biological ageing.

SummaryAging is associated with progressive and site-specific changes in DNA methylation (DNAm). These global changes are captured by DNAm clocks that accurately predict chronological age in humans but relatively little is known about how clocks perform in vitro. Here we culture primary human fibroblasts across the cellular lifespan (∼6 months) and use four different DNAm clocks to show that age-related DNAm signatures are conserved and accelerated in vitro. The Skin & Blood clock shows the best linear correlation with chronological time (r=0.90), including during replicative senescence. Although similar in nature, the rate of epigenetic aging is approximately 62x times faster in cultured cells than in the human body. Consistent with in vivo data, cells aged under hyperglycemic conditions exhibit an approximately three years elevation in baseline DNAm age. Moreover, candidate gene-based analyses further corroborate the conserved but accelerated biological aging process in cultured fibroblasts. Fibroblasts mirror the established DNAm topology of the age-related ELOVL2 gene in human blood and the rapid hypermethylation of its promoter cg16867657, which correlates with a linear decrease in ELOVL2 mRNA levels across the lifespan. Using generalized additive modeling on twelve timepoints across the lifespan, we also show how single CpGs exhibit loci-specific, linear and nonlinear trajectories that reach rates up to −47% (hypomethylation) to +23% (hypermethylation) per month. Together, these high temporal resolution global, gene-specific, and single CpG data highlight the conserved and accelerated nature of epigenetic aging in cultured fibroblasts, which may constitute a system to evaluate age-modifying interventions across the lifespan.Graphical Abstract

Several studies have linked DNA methylation at individual CpG sites to aging and various diseases. Recent studies have also identified single CpGs whose methylation levels are associated with all-cause mortality. In this study, we perform an epigenome-wide study of the association between CpG methylation and mortality in a population of 435 monozygotic twin pairs from three Danish twin studies. The participants were aged 55–90 at the time of blood sampling and were followed for up to 20 years. We validated our results by comparison with results from a British and a Swedish cohort, as well as results from the literature. We identified 2806 CpG sites associated with mortality (false discovery rate ( FDR ) < 0.05 ), of which 24 had an association p-value below 10 − 7 . This was confirmed by intra-pair comparison controlling for confounding effects. Eight of the 24 top sites could be validated in independent datasets or confirmed by previous studies. For all these eight sites, hypomethylation was associated with poor survival prognosis, and seven showed monozygotic correlations above 35%, indicating a potential moderate to strong heritability, but leaving room for substantial shared or unique environmental effects. We also set up a predictor for mortality using least absolute shrinkage and selection operator (LASSO) regression. The predictor showed good performance on the Danish data under cross-validation, but did not perform very well in independent samples.

Age-related changes in DNA methylation have been observed in many cross-sectional studies, but longitudinal evidence is still very limited. Here, we aimed to characterize longitudinal age-related methylation patterns (Illumina HumanMethylation450 array) using 1011 blood samples collected from 385 old Swedish twins (mean age of 69 at baseline) up to five times over 20 years. We identified 1316 age-associated methylation sites (p−7) using a longitudinal epigenome-wide association study design. We measured how estimated cellular compositions changed with age and how much they confounded the age effect. We validated the results in two independent longitudinal cohorts, where 118 CpGs were replicated in PIVUS (p−5) and 594 were replicated in LBC (p−5). Functional annotation of age-associated CpGs showed enrichment in CCCTC-binding factor (CTCF) and other unannotated transcription factor binding sites. We further investigated genetic influences on methylation (methylation quantitative trait loci) and found no interaction between age and genetic effects in the 1316 age-associated CpGs. Moreover, in the same CpGs, methylation differences within twin pairs increased over time, where monozygotic twins had smaller intra-pair differences than dizygotic twins. We show that age-related methylation changes persist in a longitudinal perspective, and are fairly stable across cohorts. Moreover, the changes are under genetic influence, although this effect is independent of age. In addition, inter-individual methylation variations increase over time, especially in age-associated CpGs, indicating the increase of environmental contributions on DNA methylation with age.

The epigenome has been shown to be influenced by biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption, and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here, we provide evidence on the associations between epigenetic modifications—in our case, CpG methylation—and educational attainment (EA), a biologically distal environmental factor that is arguably among of the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10,767 individuals. While we find that 9 CpG probes are significantly associated with EA, only two remain associated when we restrict the sample to never-smokers. These two are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, their effect sizes on EA are far smaller than the known associations between CpG probes and biologically proximal environmental factors. Two analyses that combine the effects of many probes—polygenic methylation score and epigenetic-clock analyses—both suggest small associations with EA. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.

Interindividual variability of DNA methylation is a mechanism of the epigenetic drift in aging. Studies on cross-sectional data have discovered a change in methylation variability in association with age. However, thus far, no method explored DNA methylation variability in longitudinal data, which was the aim of this study. First, we performed a simulation study to explore methods for estimating methylation variability in longitudinal data. Second, an epigenome-wide association study (EWAS) on 1011 longitudinal samples (385 individuals followed up to 18 years) was performed to identify age-varying methylation sites using these methods. Following Breusch–Pagan test of heteroscedasticity, we showed that a linear regression model, where the residuals were used in a mixed effect model with a random intercept, properly estimated the change of interindividual variability over time. Our EWAS identified 570 CpG sites where methylation variability was significantly associated with age (P