Gene expression network analyses in response to air pollution exposures in the trucking industry

Conceptual frameworks for the integration of genetic and social epidemiology in complex diseases

Uncovering the root causes of complex diseases requires complex approaches, yet many studies continue to isolate the effects of genetic and social determinants of disease. Epidemiologic efforts that under-utilize genetic epidemiology methods and findings may lead to incomplete understanding of disease. Meanwhile, genetic epidemiology studies are often conducted without consideration of social and environmental context, limiting the public health impact of genomic discoveries. This divide endures despite shared goals and increases in interdisciplinary data due to a lack of shared theoretical frameworks and differing language. Here, we demonstrate that bridging epidemiological divides does not require entirely new ways of thinking. Existing social epidemiology frameworks including Ecosocial theory and Fundamental Cause Theory, can both be extended to incorporate principles from genetic epidemiology. We show that genetic epidemiology can strengthen, rather than detract from, efforts to understand the impact of social determinants of health. In addition to presenting theoretical synergies, we offer practical examples of how genetics can improve the public health impact of epidemiology studies across the field. Ultimately, we aim to provide a guiding framework for trainees and established epidemiologists to think about diseases and complex systems and foster more fruitful collaboration between genetic and traditional epidemiological disciplines.

Particulate matter-induced gene expression patterns in human-derived cells based on 11 public gene expression datasets

BACKGROUND

Exposure to particulate matter (PM) and house dust mite (HDM) can change the expression patterns of inflammation-, oxidative stress-, and cell death-related genes. We investigated the changes in gene expression patterns owing to PM exposure.

OBJECTIVE

This study examined the changes in gene expression patterns following PM exposure.

METHODS

We searched for differentially expressed genes (DEGs) following PM exposure using five cell line-based RNA-seq or microarray datasets and six human-derived datasets. The enrichment terms of the DEGs were assessed.

RESULTS

DEG analysis yielded two gene sets. Thus, enrichment analysis was performed for each gene set, and the enrichment terms related to respiratory diseases were presented. The intersection of six human-derived datasets and two gene sets was obtained, and the expression patterns following PM exposure were observed.

CONCLUSIONS

Two gene sets were obtained for cells treated with PM and their expression patterns were presented following verification in human-derived cells. Our findings suggest that exposure to PM2.5 and HDM may reveal changes in genes that are associated with diseases, such as allergies, highlighting the importance of mitigating PM2.5 and HDM exposure for disease prevention.

Characterization of risks and pathogenesis of respiratory diseases caused by rural atmospheric PM2.5

Forty-six percent of the world's population resides in rural areas, the majority of whom belong to vulnerable groups. They mainly use cheap solid fuels for cooking and heating, which release a large amount of PM2.5 and cause adverse effects to human health. PM2.5 exhibits urban-rural differences in its health risk to the respiratory system. However, the majority of research on this issue has focused on respiratory diseases induced by atmospheric PM2.5 in urban areas, while rural areas have been ignored for a long time, especially the pathogenesis of respiratory diseases. This is not helpful for promoting environmental equity to aid vulnerable groups under PM2.5 pollution. Thus, this study focuses on rural atmospheric PM2.5 in terms of its chemical components, toxicological effects, respiratory disease types, and pathogenesis, represented by PM2.5 from rural areas in the Sichuan Basin, China (Rural SC-PM2.5). In this study, organic carbon is the most significant component of Rural SC-PM2.5. Rural SC-PM2.5 significantly induces cytotoxicity, oxidative stress, and inflammatory response. Based on multiomics, bioinformatics, and molecular biology, Rural SC-PM2.5 inhibits ribonucleotide reductase regulatory subunit M2 (RRM2) to disrupt the cell cycle, impede DNA replication, and ultimately inhibit lung cell proliferation. Furthermore, this study supplements and supports the epidemic investigation. Through an analysis of the transcriptome and human disease database, it is found that Rural SC-PM2.5 may mainly involve pulmonary hypertension, sarcoidosis, and interstitial lung diseases; in particular, congenital diseases may be ignored by epidemiological surveys in rural areas, including tracheoesophageal fistula, submucous cleft of the hard palate, and congenital hypoplasia of the lung. This study contributes to a greater scientific understanding of the health risks posed by rural PM2.5, elucidates the pathogenesis of respiratory diseases, clarifies the types of respiratory diseases, and promotes environmental equity.

Biological effects of negative air ions on human health and integrated multiomics to identify biomarkers: a literature review

Environmental pollution seriously affects human health. The concentration of negative air ions (NAIs), which were discovered at the end of the nineteenth century, is one of the factors used to evaluate air quality. Additionally, NAIs have been widely considered markers by scholars due to their unique biological function. The aim of this study was to summarize existing research and propose future research on the generation and temporal and spatial dynamic patterns of NAIs concentrations as well as the relationship between NAIs and human health. We identified 187 studies (published January 2013-January 2023) that met our inclusion criteria. Fourteen English studies evaluated the effects of NAIs on depression, the cardiovascular system, the respiratory system, reproduction and development, cognition, and sports muscle injury. Only two studies reported the associations of NAIs exposure with metabolic omics. NAIs concentrations vary temporally with solar radiation, air temperature, and relative humidity, while the temporal dynamic patterns of NAIs are affected by season, time, meteorological factors, air quality index, geographical location, forest vegetation, and other factors. Researchers have shown that exposure to NAIs may benefit our health by changing amino acid metabolism, which mainly manifests as increased anti-inflammation and reduced inflammation and antioxidation. Furthermore, exposure to NAIs promotes energy production, affects the expression of c-fos, and regulates 5-HT levels. There has been considerable interest in the potential effects of NAIs on human health and well-being, but the conclusions have been inconsistent and the mechanisms remain unclear. The use of omics to elucidate the biological mechanism of NAIs is relatively new and has some advantages.

Gene Expression Profile of Uterine Leiomyoma from Women Exposed to Different Air Pollution Levels in Metropolitan Cities of Sao Paulo, Brazil

Leiomyomas (LMs) are the most frequent uterine benign tumors, representing the leading cause of hysterectomy indications worldwide. They are highly associated with women's reproductive complications, and endocrine disruptors may influence their etiology. In this sense, air pollution represents a relevant hormonal disruptor that acts on key signaling pathways, resulting in tumor development and infertility. Our goal was to evaluate submucosal LM samples from patients living in the metropolitan and Sao Paulo city regions, focusing on genes involved in tumor development and infertility features. Twenty-four patients were selected based on their region of residence and clinical information availability. Several genes were differentially expressed between women living in metropolitan areas and Sao Paulo city. Significant associations were observed between BCL-2, DVL1, FGFR3, and WNT5b downregulation and contraceptive use in the samples from women living in Sao Paulo city. ESR1 and HHAT downregulation was associated with ethnicity. WNT5b and GREM were associated with LM treatment and related pathologies, respectively. In the samples from women living in other cities of the metropolitan region, abortion occurrence was associated with BMP4 upregulation. Although further studies may be necessary, our results showed that air pollution exposure influences the expression of genes related to LM development and female reproductive features.

Transcriptional Response of Blood Mononuclear Cells from Patients with Inflammatory and Autoimmune Disorders Exposed to "Krakow Smog"

Despite the general awareness of the need to reduce air pollution, the efforts were undertaken in Poland to eliminate the pollutants and their harmful effect on human health seem to be insufficient. Moreover, the latest data indicate that the city of Krakow is at the forefront of the most polluted cities worldwide. Hence, in this report, we investigated the impact of particulate matter isolated from the air of Krakow (PM KRK) on the gene expression profile of peripheral blood mononuclear cells (PBMCs) in healthy donors (HD) and patients with atherosclerosis (AS), rheumatoid arthritis (RA) and multiple sclerosis (MS), after in vitro exposure. Blood samples were collected in two seasons, differing in the concentration of PM in the air (below or above a daily limit of 50 µg/m³ for PM 10). Data show that PBMCs exposed in vitro to PM KRK upregulated the expression of genes involved, among others, in pro-inflammatory response, cell motility, and regulation of cell metabolism. The transcriptional effects were observed predominantly in the group of patients with AS and MS. The observed changes seem to be dependent on the seasonal concentration of PM in the air of Krakow and may suggest their important role in the progression of AS, MS, and RA in the residents of Krakow.

Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry

Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010, and analyzed using untargeted high-resolution metabolomics to characterize metabolite associations with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM2.5). Metabolic associations with EC, OC and PM2.5 were evaluated for biochemical processes known to be associated with disease risk. Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and transcriptomic changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution.

Differences in transcriptome response to air pollution exposure between adult residents with and without chronic obstructive pulmonary disease in Beijing: A panel study

Ambient air pollution is a major risk factor for the prevalence and exacerbation of chronic obstructive pulmonary disease (COPD). Based on the COPDB (COPD in Beijing) panel study, whole-blood transcriptomes were repeatedly measured in 48 COPD patients and 62 healthy participants. Ambient mass concentrations of fine particulate matter (PM_2.5), temperature, and relative humidity were continuously monitored at a monitoring station. The linear mixed-effects models were applied to estimate the associations between logarithmically transformed transcript levels and 1-day (d), 7-d, and 14-d average concentrations of PM_2.5 before the start of follow-up visits. MetaCore™ was used to conduct the pathway enrichment analyses. Exposure to 1-, 7-, and 14-d average concentrations of PM_2.5 was significantly associated with the transcriptome responses in both groups. The top 10, top 100, and top 1000 PM_2.5-associated transcripts differed greatly between the two groups. Among COPD patients, role of alpha-6/beta-4 integrins in carcinoma progression, Notch signaling in breast cancer, and ubiquinone metabolism were the most significantly enriched PM_2.5-associated biological pathways in the three time windows, respectively. In healthy participants, pro-opiomelanocortin processing was the most significant PM_2.5-associated biological pathway in all three time windows. Our findings provide novel insights into the adverse health effects of air pollution exposure.

Revealing consensus gene pathways associated with respiratory functions and disrupted by PM2.5 nitrate exposure at bulk tissue and single cell resolution

BACKGROUND

Nitrate is a major pollutant component in ambient PM_2.5. It is known that chronic exposure to PM_2.5 NO₃^- damages respiratory functions. We aim to explore the underlying toxicological mechanism at single cell resolution.

METHODS

We systematically conducted exposure experiments on forty C57BL/6 mice, assessed respiratory functions, and profiled lung transcriptome. . Afterward, we estimated the cell type compositions from RNA-seq data using deconvolution analysis. The genes and pathways associated with respiratory function and dysregulated by to PM_2.5 NO₃^- exposure were characterized at bulk-tissue and single-cell resolution.

RESULTS

PM_2.5 NO₃^- exposure did not significantly modify the cell type composition in lung, but profoundly altered the gene expression within each cell type. At ambient concentration (22 μg/m³), exposure significantly (FDR<10%) altered 95 genes' expression. Among the genes associated with respiratory functions, a large fraction (74.6-91.7%) were significantly perturbed by PM_2.5 NO₃^- exposure. For example, among the 764 genes associated with peak expiratory flow (PEF), 608 (79.6%) were affected by exposure (p = 1.92e-345). Pathways known to play role in lung disease pathogenesis, including circadian rhythms, sphingolipid metabolism, immune response and lysosome, were found significantly associated with respiratory functions and disrupted by PM_2.5 NO₃^- exposure.

CONCLUSIONS

This study extended our knowledge of PM_2.5 NO₃^- exposure's effect to the levels of lung gene expression, pathways, lung cell type composition and cell specific transcriptome. At single cell resolution, we provided insights in toxicological mechanism of PM_2.5 NO₃^- exposure and subsequent pulmonary disease risks.

The Influence of Air Pollution on the Development of Allergic Inflammation in the Airways in Krakow's Atopic and Non-Atopic Residents

Until now, the simultaneous influence of air pollution assessed by measuring the objective marker of exposition (1-hydroxypirene, 1-OHP) and atopy on the development of allergic airway diseases has not been studied. The aim of this study was to determine the pathomechanism of the allergic response to PM2.5 in atopic and non-atopic patients. We investigated the changes in peripheral blood basophil activity of patients after stimulation with the birch pollen allergen alone, the allergen combined with PM2.5 (BP), PM2.5 alone, a concentration of 1-OHP in urine, and a distance of residence from the main road in 30 persons. Activation by dust alone was positive for all concentrations in 83% of atopic and 75% of non-atopic assays. In the group of people with atopy, the simultaneous activation of BP gave a higher percentage of active basophils compared to the sum of activation with dust and birch pollen alone (B + P) for all concentrations. The difference between BP and B + P was 117.5 (p = 0.02) at a PM concentration of 100 μg. Such a relationship was not observed in the control group. The correlation coefficient between the distance of residence from major roads and urinary 1-OHP was 0.62. A Pearson correlation analysis of quantitative variables was performed, and positive correlation results were obtained in the atopy group between BP and 1-OH-P. Exposure to birch pollen and PM2.5 has a synergistic effect in sensitized individuals. The higher the exposure to pollutants, the higher the synergistic basophil response to the allergen and PM in atopic patients.

Application of high-resolution metabolomics to identify biological pathways perturbed by traffic-related air pollution

BACKGROUND

Substantial research has investigated the adverse effects of traffic-related air pollutants (TRAP) on human health. Convincing associations between TRAP and respiratory and cardiovascular diseases are known, but the underlying biological mechanisms are not well established. High-resolution metabolomics (HRM) is a promising platform for untargeted characterization of molecular mechanisms between TRAP and health indexes.

OBJECTIVES

We examined metabolic perturbations associated with short-term exposures to TRAP, including carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), fine particulate matter (PM2.5), organic carbon (OC), and elemental carbon (EC) among 180 participants of the Center for Health Discovery and Well-Being (CHDWB), a cohort of Emory University-affiliated employees.

METHODS

A cross-sectional study was conducted on baseline visits of 180 CHDWB participants enrolled during 2008-2012, in whom HRM profiling was determined in plasma samples using liquid chromatography-high-resolution mass spectrometry with positive and negative electrospray ionization (ESI) modes. Ambient pollution concentrations were measured at an ambient monitor near downtown Atlanta. Metabolic perturbations associated with TRAP exposures were assessed following an untargeted metabolome-wide association study (MWAS) framework using feature-specific Tobit regression models, followed by enriched pathway analysis and chemical annotation.

RESULTS

Subjects were predominantly white (76.1%) and non-smokers (95.6%), and all had at least a high school education. In total, 7821 and 4123 metabolic features were extracted from the plasma samples by the negative and positive ESI runs, respectively. There are 3421 features significantly associated with at least one air pollutant by negative ion mode, and 1691 features by positive ion mode. Biological pathways enriched by features associated with the pollutants are primarily involved in nucleic acids damage/repair (e.g., pyrimidine metabolism), nutrient metabolism (e.g., fatty acid metabolism), and acute inflammation (e.g., histidine metabolism and tyrosine metabolism). NO2 and EC were associated most consistently with these pathways. We confirmed the chemical identity of 8 metabolic features in negative ESI and 2 features in positive ESI, including metabolites closely linked to oxidative stress and inflammation, such as histamine, tyrosine, tryptophan, and proline.

CONCLUSIONS

We identified a range of ambient pollutants, including components of TRAP, associated with differences in the metabolic phenotype among the cohort of 180 subjects. We found Tobit models to be a robust approach to handle missing data among the metabolic features. The results were encouraging of further use of HRM and MWAS approaches for characterizing molecular mechanisms underlying exposure to TRAP.

Integration of gene expression and DNA methylation identifies epigenetically controlled modules related to PM2.5 exposure

Air pollution has been associated with adverse health effects across the life-course. Although underlying mechanisms are unclear, several studies suggested pollutant-induced changes in transcriptomic profiles. In this meta-analysis of transcriptome-wide association studies of 656 children and adolescents from three European cohorts participating in the MeDALL Consortium, we found two differentially expressed transcript clusters (FDR p < 0.05) associated with exposure to particulate matter < 2.5 µm in diameter (PM_2.5) at birth, one of them mapping to the MIR1296 gene. Further, by integrating gene expression with DNA methylation using Functional Epigenetic Modules algorithms, we identified 9 and 6 modules in relation to PM_2.5 exposure at birth and at current address, respectively (including NR1I2, MAPK6, TAF8 and SCARA3). In conclusion, PM_2.5 exposure at birth was linked to differential gene expression in children and adolescents. Importantly, we identified several significant interactome hotspots of gene modules of relevance for complex diseases in relation to PM_2.5 exposure.

Airborne particulate matter (PM2.5) triggers cornea inflammation and pyroptosis via NLRP3 activation

Although studies have demonstrated that fine particulate matter (PM_2.5) induces ocular surface damage, PM2.5 exposure causes cornea toxicity is not entirely clear. The aim of this study is to investigate the role of the nod-like receptor family pyrin domain containing three (NLRP3) inflammasome-mediated pyroptosis in PM_2.5-related corneal toxicity. Human corneal epithelial cells (HCECs) were exposed to different concentrations of PM_2.5, and the cell viability, expressions of NLRP3 inflammasome mediated pyroptosis axis molecules and intracellular reactive oxygen species (ROS) formation were measured in HCECs. Animal experiments were undertaken to topically apply PM_2.5 suspension to mouse eyes for three months and the pyroptosis related molecules in the mouse corneas were measured. RESULTS: Our results showed a dose-dependent decrease of HCEC viability in the PM_2.5-treated cells. NLRP3 inflammasome-mediated pyroptosis axis (NLRP3, ASC, GSDMD, caspase-1, IL-1β, and IL-18) were activated in the PM_2.5-treated HCECs, accompanied by increased ROS formation. Further in vivo study confirmed the activation of this pathway in the mouse corneas exposed to PM_2.5. In conclusion, this study provids novel evidence that PM_2.5 induces corneal toxicity by triggering cell pyroptosis.

Bile Acids and GPBAR-1: Dynamic Interaction Involving Genes, Environment and Gut Microbiome

Bile acids (BA) are amphiphilic molecules synthesized in the liver from cholesterol. BA undergo continuous enterohepatic recycling through intestinal biotransformation by gut microbiome and reabsorption into the portal tract for uptake by hepatocytes. BA are detergent molecules aiding the digestion and absorption of dietary fat and fat-soluble vitamins, but also act as important signaling molecules via the nuclear receptor, farnesoid X receptor (FXR), and the membrane-associated G protein-coupled bile acid receptor 1 (GPBAR-1) in the distal intestine, liver and extra hepatic tissues. The hydrophilic-hydrophobic balance of the BA pool is finely regulated to prevent BA overload and liver injury. By contrast, hydrophilic BA can be hepatoprotective. The ultimate effects of BA-mediated activation of GPBAR-1 is poorly understood, but this receptor may play a role in protecting the remnant liver and in maintaining biliary homeostasis. In addition, GPBAR-1 acts on pathways involved in inflammation, biliary epithelial barrier permeability, BA pool hydrophobicity, and sinusoidal blood flow. Recent evidence suggests that environmental factors influence GPBAR-1 gene expression. Thus, targeting GPBAR-1 might improve liver protection, facilitating beneficial metabolic effects through primary prevention measures. Here, we discuss the complex pathways linked to BA effects, signaling properties of the GPBAR-1, mechanisms of liver damage, gene-environment interactions, and therapeutic aspects.

Cardiovascular adaptations to particle inhalation exposure: molecular mechanisms of the toxicology

Ambient air, occupational settings, and the use and distribution of consumer products all serve as conduits for toxicant exposure through inhalation. While the pulmonary system remains a primary target following inhalation exposure, cardiovascular implications are exceptionally culpable for increased morbidity and mortality. The epidemiological evidence for cardiovascular dysfunction resulting from acute or chronic inhalation exposure to particulate matter has been well documented, but the mechanisms driving the resulting disturbances remain elusive. In the current review, we aim to summarize the cellular and molecular mechanisms that are directly linked to cardiovascular health following exposure to a variety of inhaled toxicants. The purpose of this review is to provide a comprehensive overview of the biochemical changes in the cardiovascular system following particle inhalation exposure and to highlight potential biomarkers that exist across multiple exposure paradigms. We attempt to integrate these molecular signatures in an effort to provide direction for future investigations. This review also characterizes how molecular responses are modified in at-risk populations, specifically the impact of environmental exposure during critical windows of development. Maternal exposure to particulate matter during gestation can lead to fetal epigenetic reprogramming, resulting in long-term deficits to the cardiovascular system. In both direct and indirect (gestational) exposures, connecting the biochemical mechanisms with functional deficits outlines pathways that can be targeted for future therapeutic intervention. Ultimately, future investigations integrating "omics"-based approaches will better elucidate the mechanisms that are altered by xenobiotic inhalation exposure, identify biomarkers, and guide in clinical decision making.

Involvement of fine particulate matter exposure with gene expression pathways in breast tumor and adjacent-normal breast tissue

BACKGROUND

Fine particulate matter (PM_2.5) has been associated with breast cancer specific mortality, particularly for women with Stage I cancer. We examined the biological pathways that are perturbed by PM_2.5 exposures by analyzing gene expression measurements from breast tissue specimens.

METHODS

The Nurses' Health Studies (NHS and NHSII) are prospective cohorts with archival breast tissue specimens from breast cancer cases. Global gene expression data were ascertained with the Affymetrix Glue Human Transcriptome Array 3.0. PM_2.5 was estimated using spatio-temporal models linked to participants' home addresses. All analyses were performed separately in tumor (n = 591) and adjacent-normal (n = 497) samples, and stratified by estrogen receptor (ER) status and stage. We used multivariable linear regression, gene-set enrichment analyses (GSEA), and the least squares kernel machine (LSKM) to assess whether 3-year cumulative average pre-diagnosis PM_2.5 exposure was associated with breast-tissue gene expression pathways among predominately Stage I and II women (90.7%) and postmenopausal (81.2%) women. Replication samples (tumor, n = 245; adjacent-normal, n = 165) were measured on Affymetrix Human Transcriptome Array (HTA 2.0).

RESULTS

Overall, no pathways in the tumor area were significantly associated with PM_2.5 exposure. Among 272 adjacent-normal samples from Stage I ER-positive women, PM_2.5 was associated with perturbations in the oxidative phosphorylation, protein secretion, and mTORC1 signaling pathways (GSEA and LSKM p-values <0.05); however, results were not replicated in a small set of replication samples (n = 80).

CONCLUSIONS

PM_2.5 was generally not associated with breast tissue gene expression though was suggested to perturb oxidative phosphorylation and regulation of proteins and cellular signaling in adjacent-normal breast tissue. More research is needed on the biological role of PM_2.5 that influences breast tumor progression.

Metabolomic assessment of exposure to near-highway ultrafine particles

Exposure to traffic-related air pollutants has been associated with increased risk of adverse cardiopulmonary outcomes and mortality; however, the biochemical pathways linking exposure to disease are not known. To delineate biological response mechanisms associated with exposure to near-highway ultrafine particles (UFP), we used untargeted high-resolution metabolomics to profile plasma from 59 participants enrolled in the Community Assessment of Freeway Exposure and Health (CAFEH) study. Metabolic variations associated with UFP exposure were assessed using a cross-sectional study design based upon low (mean 16,000 particles/cm3) and high (mean 24,000 particles/cm3) annual average UFP exposures. In comparing quantified metabolites, we identified five metabolites that were differentially expressed between low and high exposures, including arginine, aspartic acid, glutamine, cystine and methionine sulfoxide. Analysis of the metabolome identified 316 m/z features associated with UFP, which were consistent with increased lipid peroxidation, endogenous inhibitors of nitric oxide and vehicle exhaust exposure biomarkers. Network correlation analysis and metabolic pathway enrichment identified 38 pathways and included variations related to inflammation, endothelial function and mitochondrial bioenergetics. Taken together, these results suggest UFP exposure is associated with a complex series of metabolic variations related to antioxidant pathways, in vivo generation of reactive oxygen species and processes critical to endothelial function.

The Exposome: Molecules to Populations

Derived from the term exposure, the exposome is an omic-scale characterization of the nongenetic drivers of health and disease. With the genome, it defines the phenome of an individual. The measurement of complex environmental factors that exert pressure on our health has not kept pace with genomics and historically has not provided a similar level of resolution. Emerging technologies make it possible to obtain detailed information on drugs, toxicants, pollutants, nutrients, and physical and psychological stressors on an omic scale. These forces can also be assessed at systems and network levels, providing a framework for advances in pharmacology and toxicology. The exposome paradigm can improve the analysis of drug interactions and detection of adverse effects of drugs and toxicants and provide data on biological responses to exposures. The comprehensive model can provide data at the individual level for precision medicine, group level for clinical trials, and population level for public health.

Ambient Pollution-related Reprogramming of the Human Small Airway Epithelial Transcriptome

RATIONALE

Epidemiologic studies have demonstrated that exposure to particulate matter ambient pollution has adverse effects on lung health, exacerbated by cigarette smoking. Particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM2.5) is among the most harmful urban pollutants and is closely linked to respiratory disease.

OBJECTIVES

Based on the knowledge that the small airway epithelium (SAE) plays a central role in the pathogenesis of smoking-related lung disease, we hypothesized that elevated PM2.5 levels are associated with dysregulation of SAE gene expression, which may contribute to the development of respiratory disease.

METHODS

From 2009 to 2012, healthy nonsmoker (n = 29) and smoker (n = 129) residents of New York City underwent bronchoscopy with SAE brushing (2.6 ± 1.3 samples/subject; total of 405 samples). SAE gene expression was assessed by Affymetrix HG-U133 Plus 2.0 microarray. New York City PM2.5 levels (Environmental Protection Agency data) were averaged for the 30 days before bronchoscopy. A linear mixed model was used to assess PM2.5-related gene dysregulation accounting for multiple clinical and methodologic variables.

MEASUREMENTS AND MAIN RESULTS

Thirty-day mean PM2.5 levels varied from 6.2 to 18 μg/m3. In nonsmokers, there was no dysregulation of SAE gene expression associated with ambient PM2.5 levels. In marked contrast, n = 219 genes were significantly dysregulated in association with PM2.5 levels in the SAE of smokers. Many of these genes relate to cell growth and transcription regulation. Interestingly, 11% of genes were mitochondria associated.

CONCLUSIONS

PM2.5 exposure contributes to significant dysregulation of the SAE transcriptome of smokers, linking pollution and airway epithelial biology in the risk of development of respiratory disease in susceptible individuals.

Prediction of microRNA and gene target from an integrated network in chronic obstructive pulmonary disease based on canonical correlation analysis

BACKGROUND:

Chronic obstructive pulmonary disease (COPD) is a complex disorder with a high mortality. The pathophysiology of COPD has not been characterized till date.

OBJECTIVE:

To identify COPD-related biomarkers by a bioinformatics analysis.

METHODS:

Here, we conducted the canonical correlation analysis to extract the potential COPD-related miRNAs and mRNAs based on the miRNA-mRNA dual expression profiling data. After identifying miRNAs and mRNAs related to COPD, we constructed an interaction network by integrating three validated miRNA-target sources. Then we expanded the network by adding miRNA-mRNA pairs, which were identified by Spearman rank correlation test. For miRNAs involved in the network, we further performed the Gene Ontology (GO) functional enrichment analysis of their targets. To validate COPD-related mRNAs involved in the network, we performed receiver operating characteristic (ROC) curve analysis and Support Vector Machine (SVM) classification on only those mRNAs that overlapped with COPD-related mRNAs of Online Mendelian Inheritance in Man (OMIM) database.

RESULTS:

The results indicate that some identified miRNAs and their targets in the constructed network might be potential biomarkers of COPD.

CONCLUSIONS:

Our study helps us to predict the potential risk biomarkers of COPD, and it can certainly help in further elucidating the genetic etiology of COPD.

Mechanisms and Measurement of Changes in Gene Expression

Research on gene expression (GE) provides insights into the physiology of a cell or group of cells at a given point in time. Studies of changes in GE can be used to identify patients at higher risk for various medical conditions, a higher symptom burden, and/or the adverse consequences associated with various treatments. The aims of this article are as follows: (1) to describe the different types of RNA transcripts, (2) to describe the processes involved in GE (i.e., RNA transcription, epigenetics, and posttranscriptional modifications), (3) to describe common sources of variation in GE, (4) to describe the most common methods used to measure GE, and (5) to discuss factors to consider when choosing tissue for a GE study. This article begins with an overview of the mechanisms involved in GE. Then, the factors that can influence the findings from GE experiments (e.g., tissue specificity, host age, host gender, and time of sample collection) are described and potential solutions are presented. This article concludes with a discussion of how the types of tissue used in GE studies can affect study findings. Given that the costs associated with the measurement of changes in GE are decreasing and the methods to analyze GE data are becoming easier to use, nurse scientists need to understand the basic principles that underlie any GE study.

Changes in gene expression in chronic allergy mouse model exposed to natural environmental PM2.5-rich ambient air pollution

Particulate matter (PM) air pollution has been associated with an increase in the incidence of chronic allergic diseases; however, the mechanisms underlying the effect of exposure to natural ambient air pollution in chronic allergic diseases have not been fully elucidated. In the present study, we aimed to investigate the cellular responses induced by exposure to natural ambient air pollution, employing a mouse model of chronic allergy. The results indicated that exposure to ambient air pollution significantly increased the number of eosinophils in the nasal mucosa. The modulation of gene expression profile identified a set of regulated genes, and the Triggering Receptor Expressed on Myeloid cells1(TREM1) signaling canonical pathway was increased after exposure to ambient air pollution. In vitro, PM2.5 increased Nucleotide-binding oligomerization domain-containing protein 1 (Nod1) and nuclear factor (NF)-κB signaling pathway activation in A549 and HEK293 cell cultures. These results suggest a novel mechanism by which, PM2.5 in ambient air pollution may stimulate the innate immune system through the PM2.5-Nod1-NF-κB axis in chronic allergic disease.

Predictive and Prognostic Biomarkers of Respiratory Diseases due to Particulate Matter Exposure

Air pollution is getting severe and concerns about its toxicity effects on airway and lung disease are also increasing. Particulate matter (PM) is major component of air pollutant. It causes respiratory diseases, such as asthma, chronic obstructive pulmonary disease, lung cancer, and so on. PM particles enter the airway and lung by inhalation, causing damages to them. Especially, PM_2.5 can penetrate into the alveolus and pass to the systemic circulation. It can affect the cardiopulmonary system and cause cardiopulmonary disorders. In this review, we focused on PM-inducing toxicity mechanisms in the framework of oxidative stress, inflammation, and epigenetic changes. We also reviewed its correlation with respiratory diseases. In addition, we reviewed biomarkers related to PM-induced respiratory diseases. These biomarkers might be used for disease prediction and early diagnosis. With recent trend of using genomic analysis tools in the field of toxicogenomics, respiratory disease biomarkers associated with PM will be continuously investigated. Effective biomarkers derived from earlier studies and further studies might be utilized to reduce respiratory diseases.