Evaluating DNA methylation age on the Illumina MethylationEPIC Bead Chip.
ABSTRACT: DNA methylation age (DNAm age) has become a widely utilized epigenetic biomarker for the aging process. The Horvath method for determining DNAm age is perhaps the most widely utilized and validated DNA methylation age assessment measure. Horvath DNAm age is calculated based on methylation measurements at 353 loci, present on Illumina's 450k and 27k DNA methylation microarrays. With increasing use of the more recently developed Illumina MethylationEPIC (850k) microarray, it is worth revisiting this aging measure to evaluate estimation differences due to array design. Of the requisite 353 loci, 17 are missing from the 850k microarray. Similarly, an alternate, 71 loci DNA methylation age assessment measure created by Hannum et al. is missing 6 requisite loci. Using 17 datasets with 27k, 450k, and/or 850k methylation data, we compared each sample's epigenetic age estimated from all 353 loci required by the Horvath DNAm age calculator, and using only the 336 loci available on the 850k array. In 450k/27k data, removing loci not on the 850k array resulted in underestimation of Horvath's DNAm age. Underestimation of Horvath DNAm age increased from ages 0 to ~20, remaining stable thereafter (mean deviation = -3.46 y, SD = 1.13 for individuals ?20 years). Underestimation of Horvath's DNAm age by the reduced 450k/27k data was similar to the underestimation observed in the 850k data indicating it is driven by missing probes. In analogous examination of Hannum's DNAm age, the magnitude and direction of epigenetic age misestimation varied with chronological age. In conclusion, inter-array deviations in DNAm age estimations may be largely driven by missing probes between arrays, despite default probe imputation procedures. Though correlations and associations based on Horvath's DNAm age may be unaffected, researchers should exercise caution when interpreting results based on absolute differences in DNAm age or when mixing samples assayed on different arrays.
Project description:There is high mortality among patients with bipolar disorder (BD). Studies have reported accelerated biological aging in patients with BD. Recently, Horvath and Hannum et al. independently developed DNA methylation (DNAm) profiles as "epigenetic clocks," which are the most accurate biological age estimate. This led to the development of two accomplished measures of epigenetic age acceleration (EAA) using blood samples, namely, intrinsic and extrinsic EAA (IEAA and EEAA, respectively). IEAA, which is based on Horvath's clock, is independent of blood cell counts and indicates cell-intrinsic aging. On the other hand, EEAA, which is based on Hannum's clock, is associated with age-dependent changes in blood cell counts and indicates immune system aging. Further, Lu et al. developed the "GrimAge" clock, which can strongly predict the mortality risk, and DNAm-based telomere length (DNAmTL). We used a DNAm dataset from whole blood samples obtained from 30 patients with BD and 30 healthy controls. We investigated Horvath EAA, IEAA, Hannum EAA, EEAA, Grim EAA, DNAmTL, and DNAm-based blood cell composition. Compared with controls, there was a decrease in Horvath EAA and IEAA in patients with BD. Further, there was a significant decrease in Horvath EAA and IEAA in patients with BD taking medication combinations of mood stabilizers (including lithium carbonate, sodium valproate, and carbamazepine) than in those taking no medication/monotherapy. This study provides novel evidence indicating decelerated epigenetic aging associated with mood stabilizers in patients with BD.
Project description:DNA methylation (DNAm) has been found to show robust and widespread age-related changes across the genome. DNAm profiles from whole blood can be used to predict human aging rates with great accuracy. We sought to test whether DNAm-based predictions of age are related to phenotypes associated with type 2 diabetes (T2D), with the goal of identifying risk factors potentially mediated by DNAm. Our participants were 43 women enrolled in the Women's Health Initiative. We obtained methylation data via the Illumina 450K Methylation array on whole blood samples from participants at three timepoints, covering on average 16 years per participant. We employed the method and software of Horvath, which uses DNAm at 353 CpGs to form a DNAm-based estimate of chronological age. We then calculated the epigenetic age acceleration, or ?age, at each timepoint. We fit linear mixed models to characterize how ?age contributed to a longitudinal model of aging and diabetes-related phenotypes and risk factors. For most participants, ?age remained constant, indicating that age acceleration is generally stable over time. We found that ?age associated with body mass index (p = 0.0012), waist circumference (p = 0.033), and fasting glucose (p = 0.0073), with the relationship with BMI maintaining significance after correction for multiple testing. Replication in a larger cohort of 157 WHI participants spanning 3 years was unsuccessful, possibly due to the shorter time frame covered. Our results suggest that DNAm has the potential to act as a mediator between aging and diabetes-related phenotypes, or alternatively, may serve as a biomarker of these phenotypes.
Project description:BACKGROUND:Long-term PM2.5 exposure and aging have been implicated in multiple shared diseases; studying their relationship is a promising strategy to further understand the adverse impact of PM2.5 on human health. OBJECTIVE:We assessed the relationship of major PM2.5 component species (ammonium, elemental carbon, organic carbon, nitrate, and sulfate) with Horvath and Hannum DNA methylation (DNAm) age, two DNA methylation-based predictors of chronological age. METHODS:This analysis included 552 participants from the Normative Aging Study with multiple visits between 2000 and 2011 (n=940 visits). We estimated 1-year PM2.5 species levels at participants' addresses using the GEOS-chem transport model. Blood DNAm-age was calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. We fit linear mixed-effects models, controlling for PM2.5 mass and lifestyle/environmental factors as fixed effects, with the adaptive LASSO penalty to identify PM2.5 species associated with DNAm-age. RESULTS:Sulfate and ammonium were selected by the LASSO in the Horvath DNAm-age models. In a fully-adjusted multiple-species model, interquartile range increases in both 1-year sulfate (95%CI: 0.28, 0.74, P<0.0001) and ammonium (95%CI: 0.02, 0.70, P=0.04) levels were associated with at least a 0.36-year increase in Horvath DNAm-age. No PM2.5 species were selected by the LASSO in the Hannum DNAm-age models. Our findings persisted in sensitivity analyses including only visits with 1-year PM2.5 levels within US EPA national ambient air quality standards. CONCLUSION:Our results demonstrate that sulfate and ammonium were most associated with Horvath DNAm-age and suggest that DNAm-age measures differ in their sensitivity to ambient particle exposures and potentially disease.
Project description:BACKGROUND:Many CpGs become hyper or hypo-methylated with age. Multiple methods have been developed by Horvath et al. to estimate DNA methylation (DNAm) age including Pan-tissue, Skin & Blood, PhenoAge, and GrimAge. Pan-tissue and Skin & Blood try to estimate chronological age in the normal population whereas PhenoAge and GrimAge use surrogate markers associated with mortality to estimate biological age and its departure from chronological age. Here, we applied Horvath's four methods to calculate and compare DNAm age in 499 subjects with type 1 diabetes (T1D) from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study using DNAm data measured by Illumina EPIC array in the whole blood. Association of the four DNAm ages with development of diabetic complications including cardiovascular diseases (CVD), nephropathy, retinopathy, and neuropathy, and their risk factors were investigated. RESULTS:Pan-tissue and GrimAge were higher whereas Skin & Blood and PhenoAge were lower than chronological age (p < 0.0001). DNAm age was not associated with the risk of CVD or retinopathy over 18-20?years after DNAm measurement. However, higher PhenoAge (? = 0.023, p = 0.007) and GrimAge (? = 0.029, p = 0.002) were associated with higher albumin excretion rate (AER), an indicator of diabetic renal disease, measured over time. GrimAge was also associated with development of both diabetic peripheral neuropathy (OR = 1.07, p = 9.24E-3) and cardiovascular autonomic neuropathy (OR = 1.06, p = 0.011). Both HbA1c (? = 0.38, p = 0.026) and T1D duration (? = 0.01, p = 0.043) were associated with higher PhenoAge. Employment (? = - 1.99, p = 0.045) and leisure time (? = - 0.81, p = 0.022) physical activity were associated with lower Pan-tissue and Skin & Blood, respectively. BMI (? = 0.09, p = 0.048) and current smoking (? = 7.13, p = 9.03E-50) were positively associated with Skin & Blood and GrimAge, respectively. Blood pressure, lipid levels, pulse rate, and alcohol consumption were not associated with DNAm age regardless of the method used. CONCLUSIONS:Various methods of measuring DNAm age are sub-optimal in detecting people at higher risk of developing diabetic complications although some work better than the others.
Project description:DNA methylation (DNAm) algorithms of biological age provide a robust estimate of an individual's chronological age and can predict their risk of age-related disease and mortality. This study reviewed the evidence that environmental, lifestyle and health factors are associated with the Horvath and Hannum epigenetic clocks. A systematic search identified 61 studies. Chronological age was correlated with DNAm age in blood (median .83, range .13-.99). In a meta-analysis body mass index (BMI) was associated with increased DNAm age (Hannum ?: 0.07, 95% CI 0.04 to 0.10; Horvath ?: 0.06, 95% CI 0.02 to 0.10), but there was no association with smoking (Hannum ?: 0.12, 95% CI -0.50 to 0.73; Horvath ?:0.18, 95% CI -0.10 to 0.46). DNAm age was positively associated with frailty (three studies, n = 3,093), and education was negatively associated with the Hannum estimate of DNAm age specifically (four studies, n = 13,955). For most other exposures, findings were too inconsistent to draw conclusions. In conclusion, BMI was positively associated with biological aging measured using DNAm, with some evidence that frailty also increased aging. More research is needed to provide conclusive evidence regarding other exposures. This field of research has the potential to provide further insights into how to promote slower biological aging and ultimately prolong healthy life.
Project description:DNA methylation is the best known epigenetic mark. Cancer and other pathologies show an altered DNA methylome. However, delivering complete DNA methylation maps is compromised by the price and labor-intensive interpretation of single nucleotide methods.Following the success of the HumanMethylation450 BeadChip (Infinium) methylation microarray (450K), we report the technical and biological validation of the newly developed MethylationEPIC BeadChip (Infinium) microarray that covers over 850,000 CpG methylation sites (850K). The 850K microarray contains >90% of the 450K sites, but adds 333,265 CpGs located in enhancer regions identified by the ENCODE and FANTOM5 projects.The 850K array demonstrates high reproducibility at the 450K CpG sites, is consistent among technical replicates, is reliable in the matched study of fresh frozen versus formalin-fixed paraffin-embeded samples and is also useful for 5-hydroxymethylcytosine. These results highlight the value of the MethylationEPIC BeadChip as a useful tool for the analysis of the DNA methylation profile of the human genome.
Project description:Background & Aims:A DNA methylation (DNAm) signature derived from 353 CpG sites (the Horvath clock) has been proposed as an epigenetic measure of chronological and biological age. This epigenetic signature is accelerated in diverse tissue types in various disorders, including non-alcoholic steatohepatitis, and is associated with mortality. Here, we assayed whole blood DNAm to explore age acceleration in patients with primary sclerosing cholangitis (PSC). Methods:Using the MethylationEPIC BeadChip (850K) array, DNAm signatures in whole blood were analyzed in 36 patients with PSC enrolled in a 96-week trial of simtuzumab (Ishak F0-1, n = 13; F5-6, n = 23). Age acceleration was calculated as the difference between DNAm age and chronological age. Comparisons between patients with high and low age acceleration (? vs. < the median) were made and Cox regression evaluated the association between age acceleration and PSC-related clinical events (e.g. decompensation, cholangitis, transplantation). Results:Age acceleration was significantly higher in patients with PSC compared to a healthy reference cohort (median, 11.1 years, p <2.2 × 10-16). In PSC, demographics, presence of inflammatory bowel disease, and ursodeoxycholic acid use were similar between patients with low and high age acceleration. However, patients with high age acceleration had increased serum alkaline phosphatase, gamma glutamyltransferase, alanine aminotransferase, enhanced liver fibrosis test scores, and greater hepatic collagen and ?-smooth muscle actin expression on liver biopsy (all p <0.05). Moreover, patients with high age acceleration had an increased prevalence of cirrhosis (89% vs. 39%; p = 0.006) and greater likelihood of PSC-related events (hazard ratio 4.19; 95% CI 1.15-15.24). Conclusion:This analysis of blood DNAm profiles suggests that compared with healthy controls, patients with PSC - particularly those with cirrhosis - exhibit significant acceleration of epigenetic age. Future studies are required to evaluate the prognostic implications and effect of therapies on global methylation patterns and age acceleration in PSC. Lay summary:An epigenetic clock based on DNA methylation has been proposed as a marker of age. In liver diseases such as non-alcoholic steatohepatitis, age acceleration based on this epigenetic clock has been observed. Herein, we show that patients with primary sclerosing cholangitis have marked age acceleration, which is further accentuated by worsening fibrosis. This measure of age acceleration could be a useful marker for prognostication or risk stratification in primary sclerosing cholangitis.
Project description:Accumulating evidence suggests that posttraumatic stress disorder (PTSD) may accelerate cellular aging and lead to premature morbidity and neurocognitive decline.This study evaluated associations between PTSD and DNA methylation (DNAm) age using recently developed algorithms of cellular age by Horvath (2013) and Hannum et al. (2013). These estimates reflect accelerated aging when they exceed chronological age. We also examined if accelerated cellular age manifested in degraded neural integrity, indexed via diffusion tensor imaging.Among 281 male and female veterans of the conflicts in Iraq and Afghanistan, DNAm age was strongly related to chronological age (rs ?.88). Lifetime PTSD severity was associated with Hannum DNAm age estimates residualized for chronological age (?=.13, p=.032). Advanced DNAm age was associated with reduced integrity in the genu of the corpus callosum (?=-.17, p=.009) and indirectly linked to poorer working memory performance via this region (indirect ?=-.05, p=.029). Horvath DNAm age estimates were not associated with PTSD or neural integrity.Results provide novel support for PTSD-related accelerated aging in DNAm and extend the evidence base of known DNAm age correlates to the domains of neural integrity and cognition.
Project description:A DNA methylation (DNAm) signature (the "Horvath clock") has been proposed as a measure of human chronological and biological age. We determined peripheral blood DNAm in patients with nonalcoholic steatohepatitis (NASH) and assessed whether accelerated aging occurs in these patients. DNAm signatures were obtained in patients with biopsy-proven NASH and stage 2-3 fibrosis. The DNAm profile from one test and two validation cohorts served as controls. Age acceleration was calculated as the difference between DNAm age and the predicted age based on the linear model derived from controls. Hepatic collagen content was assessed by quantitative morphometry. The Horvath clock accurately predicts the chronological age of the entire cohort. Age acceleration was observed among NASH subjects compared with control data sets and our test controls. Age acceleration in NASH subjects did not differ by fibrosis stage but correlated with hepatic collagen content. A set of 152 differentially methylated CpG islands between NASH subjects and controls identified gene set enrichment for transcription factors and developmental pathways. Patients with NASH exhibit epigenetic age acceleration that correlates with hepatic collagen content.
Project description:Epigenetic age estimations based on DNA methylation (DNAm) can predict human chronological age with a high level of accuracy. These DNAm age algorithms can also be used to index advanced cellular age, when estimated DNAm age exceeds chronological age. Advanced DNAm age has been associated with several diseases and metabolic and inflammatory pathology, but the causal direction of this association is unclear. The goal of this study was to examine potential bidirectional associations between advanced epigenetic age and metabolic and inflammatory markers over time in a longitudinal cohort of 179 veterans with a high prevalence of posttraumatic stress disorder (PTSD) who were assessed over the course of two years. Analyses focused on two commonly investigated metrics of advanced DNAm age derived from the Horvath (developed across multiple tissue types) and Hannum (developed in whole blood) DNAm age algorithms. Results of cross-lagged panel models revealed that advanced Hannum DNAm age at Time 1 (T1) was associated with increased (i.e., accounting for T1 levels) metabolic syndrome (MetS) severity at Time 2 (T2; p = < 0.001). This association was specific to worsening lipid panels and indicators of abdominal obesity (p = 0.001). In contrast, no baseline measures of inflammation or metabolic pathology were associated with changes in advanced epigenetic age over time. No associations emerged between advanced Horvath DNAm age and any of the examined biological parameters. Results suggest that advanced epigenetic age, when measured using an algorithm developed in whole blood, may be a prognostic marker of pathological metabolic processes. This carries implications for understanding pathways linking advanced epigenetic age to morbidity and mortality.