One-carbon metabolism is an important contributor to aging-related diseases; nevertheless, relationships of one-carbon metabolites with novel DNA methylation-based measures of biological aging remain poorly characterized. We examined relationships of one-carbon metabolites with three DNA methylation-based measures of biological aging: DNAmAge, GrimAge, and PhenoAge. We measured plasma levels of four common one-carbon metabolites (vitamin B6, vitamin B12, folate, and homocysteine) in 715 VA Normative Aging Study participants with at least one visit between 1999 and 2008 (observations = 1153). DNA methylation age metrics were calculated using the HumanMethylation450 BeadChip. We utilized Bayesian Kernel Machine Regression (BKMR) models adjusted for chronological age, lifestyle factors, age-related diseases, and study visits to determine metabolites important to the aging outcomes. BKMR models allowed for the estimation of the relationships of single metabolites and the cumulative metabolite mixture with methylation age. Log vitamin B6 was selected as important to PhenoAge (beta = -1.62-years, 95%CI: -2.28, -0.96). Log folate was selected as important to GrimAge (beta = 0.75-years, 95%CI: 0.41, 1.09) and PhenoAge (beta = 1.62-years, 95%CI: 0.95, 2.29). Compared to a model where each metabolite in the mixture is set to its 50 th percentile, the log cumulative mixture with each metabolite at its 30 th (beta = -0.13-years, 95%CI: -0.26, -0.005) and 40 th percentile (beta = -0.06-years, 95%CI: -0.11, -0.005) was associated with decreased GrimAge. Our results provide novel characterizations of the relationships between one-carbon metabolites and DNA methylation age in a human population study. Further research is required to confirm these findings and establish their generalizability.

{BACKGROUND: Globally, toxic metal exposures are a well-recognized risk factor for many adverse health outcomes. DNA methylation-based measures of biological aging are predictive of disease, but have poorly understood relationships with metal exposures. OBJECTIVE: We performed a pilot study examining the relationships of 24-h urine metal concentrations with three novel DNA methylation-based measures of biological aging: DNAmAge, GrimAge, and PhenoAge. METHODS: We utilized a previously established urine panel of five common metals [arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg)] found in a subset of the elderly US Veterans Affairs Normative Aging Study cohort (N = 48). The measures of DNA methylation-based biological age were calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. Bayesian Kernel Machine Regression (BKMR) was used to determine metals most important to the aging outcomes and the relationship of the cumulative metal mixture with the outcomes. Individual relationships of important metals with the biological aging outcomes were modeled using fully-adjusted linear models controlling for chronological age, renal function, and lifestyle/environmental factors. RESULTS: Mn was selected as important to PhenoAge. A 1 ng/mL increase in urine Mn was associated with a 9.93-year increase in PhenoAge (95%CI: 1.24, 18.61

OBJECTIVE: To investigate the role of epigenetics in statins' diabetogenic effect comparing DNA methylation (DNAm) between statin users and nonusers in an epigenome-wide association study in blood. RESEARCH DESIGN AND METHODS: Five cohort studies' participants (n = 8,270) were classified as statin users when they were on statin therapy at the time of DNAm assessment with Illumina 450K or EPIC array or noncurrent users otherwise. Associations of DNAm with various outcomes like incident type 2 diabetes, plasma glucose, insulin, and insulin resistance (HOMA of insulin resistance [HOMA-IR]) as well as with gene expression were investigated. RESULTS: Discovery (n = 6,820) and replication (n = 1,450) phases associated five DNAm sites with statin use: cg17901584 (1.12 x 10(-25) [DHCR24]), cg10177197 (3.94 x 10(-08) [DHCR24]), cg06500161 (2.67 x 10(-23) [ABCG1]), cg27243685 (6.01 x 10(-09) [ABCG1]), and cg05119988 (7.26 x 10(-12) [SC4MOL]). Two sites were associated with at least one glycemic trait or type 2 diabetes. Higher cg06500161 methylation was associated with higher fasting glucose, insulin, HOMA-IR, and type 2 diabetes (odds ratio 1.34 [95% CI 1.22, 1.47]). Mediation analyses suggested that ABCG1 methylation partially mediates the effect of statins on high insulin and HOMA-IR. Gene expression analyses showed that statin exposure and ABCG1 methylation were associated with ABCG1 downregulation, suggesting epigenetic regulation of ABCG1 expression. Further, outcomes insulin and HOMA-IR were significantly associated with ABCG1 expression. CONCLUSIONS: This study sheds light on potential mechanisms linking statins with type 2 diabetes risk, providing evidence on DNAm partially mediating statins' effects on insulin traits. Further efforts shall disentangle the molecular mechanisms through which statins may induce DNAm changes, potentially leading to ABCG1 epigenetic regulation.

Current studies indicate that long-term exposure to ambient fine particulate matter (PM2.5) is related with global mortality, yet no studies have explored relationships of PM2.5 and its species with DNAm PhenoAge acceleration (DNAmPhenoAccel), a new epigenetic biomarker of phenotypic age. We identified which PM2.5 species had association with DNAmPhenoAccel in a one-year exposure window in a longitudinal cohort. We collected whole blood samples from 683 elderly men in the Normative Aging Study between 1999 and 2013 (n = 1254 visits). DNAm PhenoAge was calculated using 513 CpGs retrieved from the Illumina Infinium HumanMethylation450 BeadChip. Daily concentrations of PM2.5 species were measured at a fixed air-quality monitoring site and one-year moving averages were computed. Linear mixed-effect (LME) regression and Bayesian kernel machine (BKM) regression were used to estimate the associations. The covariates included chronological age, body mass index (BMI), cigarette pack years, smoking status, estimated cell types, batch effects etc. Benjamini-Hochberg false discovery rate at a 5% false positive threshold was used to adjust for multiple comparison. During the study period, the mean DNAm PhenoAge and chronological age in our subjects were 68 and 73 years old, respectively. Using LME model, only lead and calcium were significantly associated with DNAmPhenoAccel. For example, an interquartile range (IQR, 0.0011 mug/m(3)) increase in lead was associated with a 1.29-year [95% confidence interval (CI): 0.47, 2.11] increase in DNAmPhenoAccel. Using BKM model, we selected PM2.5, lead, and silicon to be predictors for DNAmPhenoAccel. A subsequent LME model showed that only lead had significant effect on DNAmPhenoAccel: 1.45-year (95% CI: 0.46, 2.46) increase in DNAmPhenoAccel following an IQR increase in one-year lead. This is the first study that investigates long-term effects of PM2.5 components on DNAmPhenoAccel. The results demonstrate that lead and calcium contained in PM2.5 was robustly associated with DNAmPhenoAccel.

BACKGROUND: DNA methylation (DNAm) may play a role in age-related outcomes. It is not yet known which DNAm-based biomarkers of age acceleration (BoAA) has the strongest association with age-related endpoints. METHODS: We collected the blood samples from two independent cohorts: the Normative Ageing Study, and the Cooperative Health Research in the Region of Augsburg cohort. We measured epigenome-wide DNAm level, and generated five DNAm BoAA at baseline. We used Cox proportional hazards model to analyze the relationships between BoAA and all-cause death. We applied the Fine and Gray competing risk model to estimate the risk of BoAA on myocardial infarction (MI), stroke, and cancer, accounting for death of other reasons as the competing risks. We used random-effects meta-analyses to pool the individual results, with adjustment for multiple testing. FINDINGS: The mean chronological ages in the two cohorts were 74, and 61, respectively. Baseline GrimAgeAccel, and DNAm-related mortality risk score (DNAmRS) both had strong associations with all-cause death, MI, and stroke, independent from chronological age. For example, a one standard deviation (SD) increment in GrimAgeAccel was significantly associated with increased risk of all-cause death [hazard ratio (HR): 2.01; 95% confidence interval (CI), 1.15, 3.50], higher risk of MI (HR: 1.44; 95% CI, 1.16, 1.79), and elevated risk of stroke (HR: 1.42; 95% CI, 1.06, 1.91). There were no associations between any BoAA and cancer. INTERPRETATION: From the public health perspective, GrimAgeAccel is the most useful tool for identifying at-risk elderly, and evaluating the efficacy of anti-aging interventions. FUNDING: National Institute of Environmental Health Sciences of U.S., Harvard Chan-NIEHS Center for Environmental Health, German Federal Ministry of Education and Research, and the State of Bavaria in Germany.

Importance: Chronic obstructive pulmonary disease (COPD) is a critical public health burden. The neutrophil to lymphocyte ratio (NLR), an inflammation biomarker, has been associated with COPD morbidity and mortality; however, its associations with lung function decline and COPD development are poorly understood. Objective: To explore the associations of NLR with lung function decline and COPD risks. Design, Setting, and Participants: This longitudinal cohort study included white male veterans in the US with more than 30 years of follow-up to investigate the associations of NLR with lung function, COPD, and hypomethylation of cg05575921, the top DNA methylation marker of lung function changes in response to tobacco smoking. This study included 7466 visits from 1549 participants, each examined up to 13 times between 1982 and 2018. A subgroup of 1411 participants without COPD at baseline were selected to analyze the association of NLR with incident COPD. Data were analyzed from September 2019 to January 2020. Exposures: The primary exposure was NLR, which was estimated using automated whole blood cell counts based on a blood sample collected at each visit. The methylation level of cg05575921 was measured in blood DNA from a subgroup of 1228 visits. Main Outcomes and Measures: The outcomes of interest were lung function, measured as forced respiratory volume in the first second (FEV1) in liters, forced vital capacity (FVC) in liters, percentage of FVC exhaled in the first second (FEV1/FVC), and maximal midexpiratory flow rate (MMEF) in liters per minute and COPD status, defined as meeting the Global Initiative for Chronic Obstructive Lung Diseases stage II (or higher) criteria. Both outcomes were measured as each visit. Results: Among 1549 included men (mean [SD] age, 68.3 [9.3] years) with 7466 visits from 1982 to 2018, a 1-unit increase in NLR was associated with statistically significant mean (SE) decreases of 0.021 (0.004) L in FEV1, 0.016 (0.005) L in FVC, 0.290% (0.005) L in FVC, 0.290% (0.065%) in FEV1/FVC, and 3.65 (0.916) L/min MMEF. Changes in NLR up to approximately 10 years were associated with corresponding longitudinal changes in lung function. Furthermore, this increase in NLR was associated with 9% higher odds of COPD (odds ratio, 1.09 [95% CI, 1.03-1.15]) for all visits and 27% higher risk of incident COPD (odds ratio, 1.07 [95% CI, 1.07-1.51]) for participants without COPD at baseline. Additionally, a 1-unit increase in NLR was associated with a mean (SE) decrease of 0.0048 (0.0021 in cg05575921 hypomethylation, which may mediate the adverse association of NLR-related inflammation on lung function. Conclusions and Relevance: These findings suggest that NLR may be a clinically relevant biomarker associated with high risk of lung function impairment and COPD alone or in combination with DNA methylation profiles.

Biological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood-DNA-methylation measure that is sensitive to variation in pace of biological aging among individuals born the same year. We first modeled change-over-time in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in n = 954 members of the Dunedin Study born in 1972-1973. Rates of change in each biomarker over ages 26-38 years were composited to form a measure of aging-related decline, termed Pace-of-Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace-of-Aging, called DunedinPoAm for Dunedin(P)ace(o)f(A)ging(m)ethylation. Validation analysis in cohort studies and the CALERIE trial provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person's pace of biological aging. People's bodies age at different rates. Age-related biological changes that increase the risk of disease and disability progress rapidly in some people. In others, these processes occur at a slower pace, allowing those individuals to live longer, healthier lives. This observation has led scientists to try to develop therapies that slow aging. The hope is that such treatments could prevent or delay diseases like heart disease or dementia, for which older age is the leading risk factor. Studies in animals have identified treatments that extend the creatures' lives and slow age-related disease. But testing these treatments in humans is challenging. Our lives are much longer than the worms, flies or mice used in the experiments. Scientists would have to follow human study participants for decades to detect delays in disease onset or an extension of their lives. An alternative approach is to try to develop a test that measures the pace of aging, or essentially "a speedometer for aging". This would allow scientists to more quickly determine if treatments slow the aging process. Now, Belsky et al. show a blood test designed to measure the pace of aging predicts which people are at increased risk of poor health, chronic disease and an earlier death. First, data about chemical changes to an individual's DNA, called DNA methylation, were analyzed from white blood cell samples collected from 954 people in a long-term health study known as "The Dunedin Study". Using the data, Belsky et al. then developed an algorithm - named "DunedinPoAm" - that identified people with an accelerated or slowed pace of aging based on a single blood test. Next, they used the algorithm on samples from participants in three other long-term studies. This verified that those people the algorithm identified as aging faster had a greater risk of poor health, developing chronic diseases or dying earlier. Similarly, those identified as aging more slowly performed better on tests of balance, strength, walking speed and mental ability, and they also looked younger to trained raters. Additionally, Belsky et al. used the test on participants in a randomized trial testing whether restricting calories had potential to extend healthy lifespan. The results suggested that the calorie restriction could counter the effects of an accelerated pace of aging. The test developed by Belsky et al. may provide an alternate way of measuring whether age-slowing treatments work. This would allow faster testing of treatments that can extend the healthy lifespan of humans. The test may also help identify individuals with accelerated aging. This might help public health officials test whether policies or programs can help people lead longer, healthier lives. eng

Chronic obstructive pulmonary disease (COPD) is a frequent diagnosis in older individuals and contributor to global morbidity and mortality. Given the link between lung disease and aging, we need to understand how molecular indicators of aging relate to lung function and disease. Using data from the population-based KORA (Cooperative Health Research in the Region of Augsburg) surveys, we associated baseline epigenetic (DNA methylation) age acceleration with incident COPD and lung function. Models were adjusted for age, sex, smoking, height, weight, and baseline lung disease as appropriate. Associations were replicated in the Normative Aging Study. Of 770 KORA participants, 131 developed incident COPD over 7 years. Baseline accelerated epigenetic aging was significantly associated with incident COPD. The change in age acceleration (follow-up - baseline) was more strongly associated with COPD than baseline aging alone. The association between the change in age acceleration between baseline and follow-up and incident COPD replicated in the Normative Aging Study. Associations with spirometric lung function parameters were weaker than those with COPD, but a meta-analysis of both cohorts provide suggestive evidence of associations. Accelerated epigenetic aging, both baseline measures and changes over time, may be a risk factor for COPD and reduced lung function.

DNA methylation has fundamental roles in gene programming and aging that may help predict mortality. However, no large-scale study has investigated whether site-specific DNA methylation predicts all-cause mortality. We used the Illumina-HumanMethylation450-BeadChip to identify blood DNA methylation sites associated with all-cause mortality for 12, 300 participants in 12 Cohorts of the Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium. Over an average 10-year follow-up, there were 2,561 deaths across the cohorts. Nine sites mapping to three intergenic and six gene-specific regions were associated with mortality (P < 9.3x10(-7)) independently of age and other mortality predictors. Six sites (cg14866069, cg23666362, cg20045320, cg07839457, cg07677157, cg09615688)-mapping respectively to BMPR1B, MIR1973, IFITM3, NLRC5, and two intergenic regions-were associated with reduced mortality risk. The remaining three sites (cg17086398, cg12619262, cg18424841)-mapping respectively to SERINC2, CHST12, and an intergenic region-were associated with increased mortality risk. DNA methylation at each site predicted 5%-15% of all deaths. We also assessed the causal association of those sites to age-related chronic diseases by using Mendelian randomization, identifying weak causal relationship between cg18424841 and cg09615688 with coronary heart disease. Of the nine sites, three (cg20045320, cg07839457, cg07677157) were associated with lower incidence of heart disease risk and two (cg20045320, cg07839457) with smoking and inflammation in prior CHARGE analyses. Methylation of cg20045320, cg07839457, and cg17086398 was associated with decreased expression of nearby genes (IFITM3, IRF, NLRC5, MT1, MT2, MARCKSL1) linked to immune responses and cardiometabolic diseases. These sites may serve as useful clinical tools for mortality risk assessment and preventative care.