Air pollution, particulate matter composition and methylation-based biologic age

The Challenge by Multiple Environmental and Biological Factors Induce Inflammation in Aging: Their Role in the Promotion of Chronic Disease

The aging process is driven by multiple mechanisms that lead to changes in energy production, oxidative stress, homeostatic dysregulation and eventually to loss of functionality and increased disease susceptibility. Most aged individuals develop chronic low-grade inflammation, which is an important risk factor for morbidity, physical and cognitive impairment, frailty, and death. At any age, chronic inflammatory diseases are major causes of morbimortality, affecting up to 5-8% of the population of industrialized countries. Several environmental factors can play an important role for modifying the inflammatory state. Genetics accounts for only a small fraction of chronic-inflammatory diseases, whereas environmental factors appear to participate, either with a causative or a promotional role in 50% to 75% of patients. Several of those changes depend on epigenetic changes that will further modify the individual response to additional stimuli. The interaction between inflammation and the environment offers important insights on aging and health. These conditions, often depending on the individual's sex, appear to lead to decreased longevity and physical and cognitive decline. In addition to biological factors, the environment is also involved in the generation of psychological and social context leading to stress. Poor psychological environments and other sources of stress also result in increased inflammation. However, the mechanisms underlying the role of environmental and psychosocial factors and nutrition on the regulation of inflammation, and how the response elicited for those factors interact among them, are poorly understood. Whereas certain deleterious environmental factors result in the generation of oxidative stress driven by an increased production of reactive oxygen and nitrogen species, endoplasmic reticulum stress, and inflammation, other factors, including nutrition (polyunsaturated fatty acids) and behavioral factors (exercise) confer protection against inflammation, oxidative and endoplasmic reticulum stress, and thus ameliorate their deleterious effect. Here, we discuss processes and mechanisms of inflammation associated with environmental factors and behavior, their links to sex and gender, and their overall impact on aging.

Epigenetic clocks may come out of rhythm-implications for the estimation of chronological age in forensic casework

There is a growing perception that DNA methylation may be influenced by exogenous and endogenous parameters. Knowledge of these factors is of great relevance for the interpretation of DNA-methylation data for the estimation of chronological age in forensic casework. We performed a literature review to identify parameters, which might be of relevance for the prediction of chronological age based on DNA methylation. The quality of age predictions might particularly be influenced by lifetime adversities (chronic stress, trauma/post-traumatic stress disorder (PTSD), violence, low socioeconomic status/education), cancer, obesity and related diseases, infectious diseases (especially HIV and Cytomegalovirus (CMV) infections), sex, ethnicity and exposure to toxins (alcohol, smoking, air pollution, pesticides). Such factors may alter the DNA methylation pattern and may explain the partly high deviations between epigenetic age and chronological age in single cases (despite of low mean absolute deviations) that can also be observed with “epigenetic clocks” comprising a high number of CpG sites. So far, only few publications dealing with forensic age estimation address these confounding factors. Future research should focus on the identification of further relevant confounding factors and the development of models that are “robust” against the influence of such biological factors by systematic investigations under targeted inclusion of diverse and defined cohorts.

Serum dioxin levels and sperm DNA methylation age: Findings in Vietnam war veterans exposed to Agent Orange

Exposure to dioxin, a known endocrine disruptor and carcinogen, is associated with poor reproductive outcomes. Yet, few studies have explored the role of DNA methylation in these relationships. Utilizing a publicly available dataset from 37 male Air Force Health Study participants exposed to dioxin-contaminated Agent Orange during the Vietnam war, we cross-sectionally examined the relationship of serum dioxin levels with a novel DNA methylation-based measure of sperm age (DNAm-agesperm). DNAm-agesperm was calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. We estimated associations of dioxin levels with DNAm-agesperm using linear regression models adjusted for chronological age, body mass index, and smoking status. Chronological age was highly correlated with DNAmagesperm (r = 0.80). In fully-adjusted linear models, a one percent increase in serum dioxin levels was significantly associated with a 0.0126-year (i.e. 4.6-day) increase in DNAm-agesperm (95%CI: 0.003, 0.022, p = 0.01). Further analyses demonstrated significant negative associations of dioxin levels (β = -0.0005, 95%CI: -0.0010, 0.00004, P = 0.03) and DNAm-agesperm (β = -0.02, 95%CI: -0.04, -0.001, P = 0.03) with methylation levels of FOXK2 - a gene previously reported to be hypomethylated in infertile men. In sum, we demonstrate associations of dioxin with increased methylation aging of sperm. DNAm-agesperm may provide utility for understanding how dioxin levels impact sperm health and potentially male reproductive capacity in human population studies. Moreover, our pilot study contributes further evidence that some environmental toxicants are associated with methylation aging. Additional studies are necessary to confirm these findings, and better characterize dioxin and sperm methylation relationships with male reproductive health.

EWAS Data Hub: a resource of DNA methylation array data and metadata

Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

Effects of particulate matter exposure on semen quality: A retrospective cohort study

BACKGROUND

Particulate matter (PM) exposure is closely associated with male infertility. Even though an association between poor semen quality and PM exposure has been widely accepted, which and when the semen parameter could be affected are still controversial. The purpose of this study is to estimate the effects of PM exposure on semen quality in Huai'an, China.

OBJECTIVES AND METHODS

The study included 1955 men with 2073 semen samples between 2015 and 2017 with moderate to high exposure to air pollution in Huai'an, China. Three multivariable linear regression models were used to conduct exposure-response analyses for PM exposure and semen quality and to estimate the influence during different exposure periods by every 15 days period before ejaculation in all participants group and normal semen quality participants group.

RESULTS

The average age of the observations was 28.9 ± 5.4 old years and the average abstinence period was 4.2 ± 1.5 days. The results showed high correlations between both PM_2.5 and PM₁₀ exposures throughout entire spermatogenesis and the declines of sperm count (β: -0.93, p < 2 × 10^-16 and β: -1.00, p < 2 × 10^-16), and sperm concentration (β: -1.00, p < 2 × 10^-16 and β: -1.06, p < 2 × 10^-16), and PM₁₀ exposure decreased sperm total motility (β: -0.60, p = 2.56 × 10^-7), but not sperm progressive motility. Furthermore, PM_2.5 exposure decreased sperm count and concentration during 15-75 lag days, and PM₁₀ exposure showed significant association with sperm count and concentration during 0-75 lag days. PM_2.5 and PM₁₀ exposures during 45-59 lag days were both inversely associated with sperm total motility (all p value < 0.05).

CONCLUSION

The present study revealed that ambient PM exposure throughout spermatogenesis during a long period, especially at early and middle stage were adversely associated with semen quality, sperm count and sperm concentration in particular.

Associations of annual ambient PM2.5 components with DNAm PhenoAge acceleration in elderly men: The Normative Aging Study

Current studies indicate that long-term exposure to ambient fine particulate matter (PM_2.5) is related with global mortality, yet no studies have explored relationships of PM_2.5 and its species with DNAm PhenoAge acceleration (DNAmPhenoAccel), a new epigenetic biomarker of phenotypic age. We identified which PM_2.5 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 PM_2.5 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 μg/m³) 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 PM_2.5, 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 PM_2.5 components on DNAmPhenoAccel. The results demonstrate that lead and calcium contained in PM_2.5 was robustly associated with DNAmPhenoAccel.

Epigenetic mortality predictors and incidence of breast cancer

Measures derived using blood DNA methylation are increasingly under investigation as indicators of disease and mortality risk. Three existing epigenetic age measures or “epigenetic clocks” appear associated with breast cancer. Two newly-developed epigenetic mortality predictors may be related to all-cancer incidence, but associations with specific cancers have not been examined in large studies. Using HumanMethylation450 BeadChips to measure blood DNA methylation in 2,773 cancer-free women enrolled in the Sister Study, we calculated two epigenetic mortality predictors: ‘GrimAgeAccel’ and the ‘mortality score’ (MS). Using Cox proportional hazard models, neither GrimAgeAccel nor the MS were associated with overall breast cancer incidence (GrimAgeAccel hazard ratio [HR]: 1.06, 95% confidence interval [CI]: 0.98-1.14, P=0.17; MS HR: 0.99, 95% CI: 0.92-1.07, P=0.85); however, a weak, positive association was observed for GrimAgeAccel and invasive breast cancer (HR: 1.08, 95% CI: 0.99-1.17, P=0.08). Stratification of invasive cancers by menopause status at diagnoses revealed the association was predominantly observed for postmenopausal breast cancer (HR: 1.10, 95% CI: 1.01, 1.20, P=0.04). Although the MS was unrelated to breast cancer risk, we find evidence that GrimAgeAccel may be weakly associated with invasive breast cancer, particularly for women diagnosed after menopause.

Air Pollution, Clustering of Particulate Matter Components, and Breast Cancer in the Sister Study: A U.S.-Wide Cohort

BACKGROUND

Particulate matter (PM) is a complex mixture. Geographic variations in PM may explain the lack of consistent associations with breast cancer.

OBJECTIVE

We aimed to evaluate the relationship between air pollution, PM components, and breast cancer risk in a United States-wide prospective cohort.

METHODS

We estimated annual average ambient residential levels of particulate matter <2.5 μm and <10 μm in aerodynamic diameter (PM2.5 and PM10, respectively) and nitrogen dioxide (NO2) using land-use regression for 47,433 Sister Study participants (breast cancer-free women with a sister with breast cancer) living in the contiguous United States. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk associated with an interquartile range (IQR) increase in pollutants. Predictive k-means were used to assign participants to clusters derived from PM2.5 component profiles to evaluate the impact of heterogeneity in the PM2.5 mixture. For PM2.5, we investigated effect measure modification by component cluster membership and by geographic region without regard to air pollution mixture.

RESULTS

During follow-up (mean=8.4 y), 2,225 invasive and 623 ductal carcinoma in situ (DCIS) cases were identified. PM2.5 and NO2 were associated with breast cancer overall [HR=1.05 (95% CI:0.99, 1.11) and 1.06 (95% CI:1.02, 1.11), respectively] and with DCIS but not with invasive cancer. Invasive breast cancer was associated with PM2.5 only in the Western United States [HR=1.14 (95% CI:1.02, 1.27)] and NO2 only in the Southern United States [HR=1.16 (95% CI:1.01, 1.33)]. PM2.5 was associated with a higher risk of invasive breast cancer among two of seven identified composition-based clusters. A higher risk was observed [HR=1.25 (95% CI: 0.97, 1.60)] in a California-based cluster characterized by low S and high Na and nitrate (NO3-) fractions and for another Western United States cluster [HR=1.60 (95% CI: 0.90, 2.85)], characterized by high fractions of Si, Ca, K, and Al.

CONCLUSION

Air pollution measures were related to both invasive breast cancer and DCIS within certain geographic regions and PM component clusters. https://doi.org/10.1289/EHP5131.