Editor's Highlight: Modifying Role of Endothelial Function Gene Variants on the Association of Long-Term PM2.5 Exposure With Blood DNA Methylation Age: The VA Normative Aging Study

Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.

Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.

Impact of Particles on Pulmonary Endothelial Cells

According to the WHO, air quality affects around 40 million people, contributing to around 21,000 premature deaths per year. Severe respiratory diseases, such as asthma and chronic obstructive pulmonary disorder, can be promoted by air pollution, which has already been documented; this is one of the reasons why air quality is a very relevant factor for human health and well-being. Aerosols are an aggregation of solid or liquid particles dispersed in the air and can be found in the form of dust or fumes. Aerosols can be easily inhaled or absorbed by the skin, which can lead to adverse health effects according to their sizes that range from the nanometre to the millimetre scale. Based on the PRISMA methodology and using the Rayyan QCRI platform, it was possible to assess more than four hundred research articles. This systematic review study aimed to understand the impact of particles on pulmonary endothelial cells, namely particulate matter in different sizes, cigarette smoke, diesel exhaust particles and carbon black. The main conclusions were that particles induce multiple health effects on endothelial cells, namely endothelial dysfunction, which can lead to apoptosis and necrosis, and it may also cause necroptosis in lung structure.

Association of Long-term Ambient Black Carbon Exposure and Oxidative Stress Allelic Variants With Intraocular Pressure in Older Men

Importance

Elevated intraocular pressure is a major risk factor for glaucoma, a leading cause of irreversible blindness worldwide. Environmental air pollution has been suggested as a potential contributor to elevated intraocular pressure; however, no studies have demonstrated such an association to date.

Objective

To investigate the association of long-term ambient black carbon exposure with intraocular pressure in community-dwelling older adults.

Design, Setting, and Participants

This population-based analysis, conducted from October 18, 2017, through March 22, 2018, used data from the all-male, New England-based Normative Aging Study of the US Department of Veterans Affairs. The analysis included 419 older men with a total of 911 follow-up study visits between January 1, 2000, and December 30, 2011. Intraocular pressure was measured by Goldmann applanation tonometry during the study visits. Validated spatiotemporal models were used to generate 1-year black carbon exposure levels at the addresses of the participants.

Main Outcomes and Measures

An independently developed genetic score approach was used to calculate allelic risk scores for 3 pathways associated with black carbon toxicity: endothelial function, oxidative stress, and metal processing. The associations among black carbon exposure, allelic risk scores, and intraocular pressure were explored using linear mixed-effects models.

Results

All 419 participants were men with a mean (SD) age of 75.3 (6.9) years. The mean (SD) 1-year black carbon exposure was 0.51 (0.18) μg/m3, and the mean (SD) intraocular pressure for the left eye was 14.1 (2.8) mm Hg and for the right eye was 14.1 (3.0) mm Hg. Of the 911 visits, 520 (57.1%) had a high endothelial function allelic risk score, 644 (70.7%) had a high metal-processing allelic risk score, and 623 (68.4%) had a high oxidative stress allelic risk score. In fully adjusted linear mixed-effects models, the association of black carbon with intraocular pressure was greater in individuals with a high oxidative stress allelic score (β = 0.36; 95% CI, 0.003-0.73) compared with individuals with a low score (β = -0.35; 95% CI, -0.86 to 0.15).

Conclusions and Relevance

Ambient black carbon exposure may be a risk factor for increased intraocular pressure in individuals susceptible to other biological oxidative stressors. If additional studies confirm these results, monitoring ambient black carbon exposure and physiological oxidative stress may prevent the development and progression of intraocular pressure-related disease.

Characteristics of cohort studies of long-term exposure to PM2.5: a systematic review

This study systematically reviewed all the cohort studies investigating the relationship between long-term exposure to PM_2.5 and any health outcome until February 2018. We searched ISI Web of Knowledge, Pubmed, and Scopus databases for peer-reviewed journal research articles published in English. We only extracted the results of the single-pollutant main analysis of each study, excluding the effect modifications and sensitivity analyses. Out of the initial 9523 articles, 203 articles were ultimately included for analysis. Based on the different characteristics of studies such as study design, outcome, exposure assessment method, and statistical model, we calculated the number and relative frequency of analyses with statistically significant and insignificant results. Most of the studies were prospective (84.8%), assessed both genders (66.5%), and focused on a specific age range (86.8%). Most of the articles (78.1%) had used modeling techniques for exposure assessment of cohorts' participants. Among the total of 317 health outcomes, the most investigated outcomes include mortality due to cardiovascular disease (6.19%), all causes (5.48%), lung cancer (4.00%), ischemic heart disease (3.50%), and non-accidental causes (3.50%). The percentage of analyses with statistically significant results were higher among studies that used prospective design, mortality as the outcome, fixed stations as exposure assessment method, hazard ratio as risk measure, and no covariate adjustment. We can somehow conclude that the choice of right characteristics for cohort studies can make a difference in their results.

Relationships of Long-Term Smoking and Moist Snuff Consumption With a DNA Methylation Age Relevant Smoking Index: An Analysis in Buccal Cells

INTRODUCTION

Currently, there is no widely accepted, non-self-report measure that simultaneously reflects smoking behaviors and is molecularly informative of general disease processes. Recently, researchers developed a smoking index (SI) using nucleated blood cells and a multi-tissue DNA methylation-based predictor of chronological age and disease (DNA methylation age [DNAm-age]). To better understand the utility of this novel SI in readily accessible cell types, we used buccal cell DNA methylation to examine SI relationships with long-term tobacco smoking and moist snuff consumption.

METHODS

We used a publicly available dataset composed of buccal cell DNA methylation values from 120 middle-aged men (40 long-term smokers, 40 moist snuff consumers, and 40 nonsmokers). DNAm-age (353-CpGs) and SI (66-CpGs) were calculated using CpG sites measured using the Illumina HumanMethylation450 BeadChip. We estimated associations of tobacco consumption habits with both SI and DNAm-age using linear regression models adjusted for chronological age, race, and methylation technical covariates.

RESULTS

In fully adjusted models with nonsmokers as the reference, smoking (β = 1.08, 95% CI = 0.82 to 1.33, p < .0001) but not snuff consumption (β = .06, 95% CI = -0.19 to 0.32, p = .63) was significantly associated with SI. SI was an excellent predictor of smoking versus nonsmoking (area under the curve = 0.92, 95% CI = 0.85 to 0.98). Four DNAm-age CpGs were differentially methylated between smokers and nonsmokers including cg14992253 [EIF3I], which has been previously shown to be differentially methylated with exposure to long-term fine-particle air pollution (PM2.5).

CONCLUSIONS

The 66-CpG SI appears to be a useful tool for measuring smoking-specific behaviors in buccal cells. Still, further research is needed to broadly confirm our findings and SI relationships with DNAm-age.

IMPLICATIONS

Our findings demonstrate that this 66-CpG blood-derived SI can reflect long-term tobacco smoking, but not long-term snuff consumption, in buccal cells. This evidence will be useful as the field works to identify an accurate non-self-report smoking biomarker that can be measured in an easily accessible tissue. Future research efforts should focus on (1) optimizing the relationship of the SI with DNAm-age so that the metric can maximize its utility as a tool for understanding general disease processes, and (2) determining normal values for the SI CpGs so that the measure is not as study sample specific.

DNA Methylation Age-Environmental Influences, Health Impacts, and Its Role in Environmental Epidemiology

PURPOSE OF REVIEW

DNA methylation-based aging biomarkers are valuable tools for evaluating the aging process from a molecular perspective. These epigenetic aging biomarkers can be evaluated across the lifespan and are tissue specific. This review examines the literature relating environmental exposures to DNA methylation-based aging biomarkers and also the literature evaluating these biomarkers as predictors of health outcomes.

RECENT FINDINGS

Multiple studies evaluated the association between air pollution and DNA methylation age and consistently observed that higher exposures are associated with elevated DNA methylation age. Psychosocial exposures, e.g., traumas and adolescent adversity, and infections are also associated with epigenetic aging. DNA methylation age has been repeatedly associated with mortality, cancer, and cognitive impairment. DNA methylation age is responsive to the environment and predictive of health outcomes. Studies are still needed to evaluate whether DNA methylation age acts as a mediator or modifier of environmental health effects and to understand the impact of factors such as race, gender, and genetics.

Multi-tissue DNA methylation age: Molecular relationships and perspectives for advancing biomarker utility

The multi-tissue DNA methylation estimator of chronological age (DNAm-age) has been associated with a wide range of exposures and health outcomes. Still, it is unclear how DNAm-age can have such broad relationships and how it can be best utilized as a biomarker. Understanding DNAm-age's molecular relationships is a promising approach to address this critical knowledge gap. In this review, we discuss the existing literature regarding DNAm-age's molecular relationships in six major categories: animal model systems, cancer processes, cellular aging processes, immune system processes, metabolic processes, and nucleic acid processes. We also present perspectives regarding the future of DNAm-age research, including the need to translate a greater number of ongoing research efforts to experimental and animal model systems.

miRNA processing gene polymorphisms, blood DNA methylation age and long-term ambient PM2.5 exposure in elderly men

AIM

We tested whether genetic variation in miRNA processing genes modified the association of PM2.5 with DNA methylation (DNAm) age.

PATIENTS & METHODS

We conducted a repeated measures study based on 552 participants from the Normative Aging Study with multiple visits between 2000 and 2011 (n = 940 visits). Address-level 1-year PM2.5 exposures were estimated using the GEOS-chem model. DNAm-age and a panel of 14 SNPs in miRNA processing genes were measured from participant blood samples.

RESULTS & CONCLUSION

In fully adjusted linear mixed-effects models, having at least one copy of the minor rs4961280 [AGO2] allele was associated with a lower DNAm-age (β = -1.13; 95% CI: -2.26 to -0.002). However, the association of PM2.5 with DNAm-age was significantly (Pinteraction  = 0.01) weaker in homozygous carriers of the major rs4961280 [AGO2] allele (β = 0.38; 95% CI: -0.20 to 0.96) when compared with all other participants (β = 1.58; 95% CI: 0.76 to 2.39). Our results suggest that miRNA processing impacts DNAm-age relationships. Graphical abstract: miRNA processing AGO2 polymorphism (rs4961280) modifies the association of long-term ambient fine particle exposure with blood DNA methylation age [Formula: see text] The graph depicts lines from a fully adjusted linear regression model with fine particle exposure levels ranging from the tenth to the ninetieth percentile, all other continuous variables held constant at their means, and all other categorical variables held at their most frequent level.

Air Pollution and the Epigenome: A Model Relationship for the Exploration of Toxicoepigenetics

The field of toxicoepigenetics is rapidly emerging to provide new insights into the relationship between environmental factors, the epigenome, and public health. Toxicoepigenetic data have the potential to revolutionize our understanding of environmental exposure effects and susceptibility. Studies in recent years have demonstrated that exposure to air pollution alters epigenetic modification states; however, continued advancement of the field is limited by the intrinsic complexity of the epigenome and inherent limitations of different types of studies (epidemiological, clinical, and in vitro) that are used in toxicoepigenetics. Overcoming these challenges will require a concerted and collaborative effort between molecular and cellular biologists, toxicologists, epidemiologists, and risk assessors to develop a thorough and practical understanding of the relationship between air pollution exposure, the epigenome, and health effects. Here we review the current state of air pollution epigenetics and discuss perspectives on the necessary steps to move the field forward to determine the role that the epigenome plays in air pollution exposure effects and susceptibility.