Genome-wide differential gene expression in children exposed to air pollution in the Czech Republic

Occupational exposure to potentially toxic elements alters gene expression profiles in formal and informal Brazilian workers

Chemical elements, such as toxic metals, have previously demonstrated their ability to alter gene expression in humans and other species. In this study, microarray analysis was used to compare the gene expression profiles of different occupational exposure populations: a) informal workers who perform soldering of jewelry inside their houses (n = 22) in São Paulo (SP) State; and b) formal workers from a steel company (n = 10) in Rio de Janeiro (RJ) state, Brazil. Control participants were recruited from the same neighborhoods without occupational chemical exposure (n = 19 in SP and n = 8 in RJ). A total of 68 blood samples were collected and RNA was extracted and hybridized using an Agilent microarray platform. Data pre-processing, statistical and pathway analysis were performed using GeneSpring software. Different expression was detected by fold-change analysis resulting in 16 up- and 33 down-regulated genes in informal workers compared to the control group. Pathway analysis revealed genes enriched in MAPK, Toll-like receptor, and NF-kappa B signaling pathways, involved in inflammatory and immune responses. In formal workers, 20 up- and 50 down-regulated genes were found related to antimicrobial peptides, defensins, neutrophil degranulation, Fc-gamma receptor-dependent phagocytosis, and pathways associated with atherosclerosis development, which is one of the main factors involved in the progression of cardiovascular diseases. The gene IFI27 was the only one commonly differentially expressed between informal and formal workers and is known to be associated with various types of cancer. In conclusion, differences in gene expression related to occupational exposure are mainly associated with inflammation and immune response. Previous research has identified a link between inflammation and immune responses and the development of chronic diseases, suggesting that prolonged occupational exposures to potentially toxic elements in Brazilian metal workers could lead to negative health outcomes. Further analysis should be carried out to investigate its direct effects and to validate causal associations.

Associating Air Pollution with Cytokinesis-Block Micronucleus Assay Parameters in Lymphocytes of the General Population in Zagreb (Croatia)

Air pollution is recognized as one of the most serious public health issues worldwide and was declared to be a leading environmental cause of cancer deaths. At the same time, the cytokinesis-block micronucleus (CBMN) assay serves as a cancer predictive method that is extensively used in human biomonitoring for populations exposed to environmental contamination. The objective of this cross-sectional study is two-fold: to evaluate genomic instability in a sample (N = 130) of healthy, general population residents from Zagreb (Croatia), chronically exposed to different levels of air pollution, and to relate them to air pollution levels in the period from 2011 to 2015. Measured frequencies of CBMN assay parameters were in agreement with the baseline data for the general population of Croatia. Air pollution exposure was based on four factors obtained from a factor analysis of all exposure data obtained for the examined period. Based on the statistical results, we did not observe a significant positive association between any of the CBMN assay parameters tested and measured air pollution parameters for designated time windows, except for benzo(a)pyrene (B[a]P) that showed significant negative association. Our results show that measured air pollution parameters are largely below the regulatory limits, except for B[a]P, and as such, they do not affect CBMN assay parameters’ frequency. Nevertheless, as air pollution is identified as a major health threat, it is necessary to conduct prospective studies investigating the effect of air pollution on genome integrity and human health.

Integrative analysis to explore the biological association between environmental skin diseases and ambient particulate matter

Although numerous experimental studies have suggested a significant association between ambient particulate matter (PM) and respiratory damage, the etiological relationship between ambient PM and environmental skin diseases is not clearly understood. Here, we aimed to explore the association between PM and skin diseases through biological big data analysis. Differential gene expression profiles associated with PM and environmental skin diseases were retrieved from public genome databases. The co-expression among them was analyzed using a text-mining-based network analysis software. Activation/inhibition patterns from RNA-sequencing data performed with PM_2.5-treated normal human epidermal keratinocytes (NHEK) were overlapped to select key regulators of the analyzed pathways. We explored the adverse effects of PM on the skin and attempted to elucidate their relationships using public genome data. We found that changes in upstream regulators and inflammatory signaling networks mediated by MMP-1, MMP-9, PLAU, S100A9, IL-6, and S100A8 were predicted as the key pathways underlying PM-induced skin diseases. Our integrative approach using a literature-based co-expression analysis and experimental validation not only improves the reliability of prediction but also provides assistance to clarify underlying mechanisms of ambient PM-induced dermal toxicity that can be applied to screen the relationship between other chemicals and adverse effects.

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.

Candidate gene expression in response to low-level air pollution

BACKGROUND

Epidemiological studies have linked air pollutant to adverse health effects even at low exposure levels, but limited evidence is available on its associations with gene expression levels.

AIM

To investigate associations between air pollutants and gene expression levels.

METHODS

We collected data from Brisbane System Genetics Study (BSGS) - a family-based system genetics study. Expression levels of candidate genes were obtained for whole blood from 266 pairs of twins (192 monozygotic and 74 dizygotic pairs) and 165 parents. Data on individual phenotypes were also obtained, including age, sex, Body Mass Index and exposure to smoke. Daily data on mean temperature and air pollutants, including particulate matter with aerodynamic diameter ≤2.5 μm (PM_2.5), ozone (O₃), nitrogen dioxide (NO₂) and sulfur dioxide (SO₂), were collected from seven monitoring stations for the day when the blood samples were collected. The association between each air pollutant and expression level of each gene was analyzed by using generalized linear models with adjustment for temperature and individual phenotypes, and its difference between monozygotic and dizygotic twins was investigated.

RESULTS

The mean value for daily concentration of air pollutants were 5.9 µg/m³ for PM_2.5, 16.3 ppb for O₃, 6.5 ppb for NO₂, and 1.4 ppb for SO₂, respectively. All air pollutants' levels in Brisbane during our study period were well under the National Air Quality Standard Air pollutant levels. We observed positive associations (false discovery rate [FDR]<0.1) among twins between PM_2.5 and expression levels of HSPA8 and SOD1 and also between SO₂ and AHR expression level. Negative associations were observed between SO₂ and 11 genes among twins, including AHR, DUSP1, GEMIN4, GPX1, KLF2, PTGS2, TLR4, TNF, TNFRSF1B, TXNRD1, and XBP1, with most of them found at lag 0-7 days (FDR < 0.1). Furthermore, the association between SO₂ and DUSP1 expression level was stronger among monozygotic twins than dizygotic twins (FDR < 0.1). We did not find strong evidence linking air pollutants to gene expression levels among parents.

CONCLUSION

Our findings require confirmation but suggest potential associations of expression levels at several genes with air pollutants at low exposure level and an individual's genetic background modifies the association between SO₂ and DUSP1 gene, which may help bridge the gap of epidemiological studies with both in vivo and in vitro toxicological experiments and provide some insights into the role of nature-nurture of an individual in gene expression response to air pollutants.

Diesel exhaust particles dysregulate multiple immunological pathways in murine macrophages: Lessons from microarray and scRNA-seq technologies

Exposure to ambient particulate matter has been shown to promote a variety of disorders, including cardiovascular diseases predominantly of ischemic etiology. However, the mechanisms linking inhaled particulates with systemic vascular effects, resulting in worsened atherosclerosis, are not well defined. We assessed the potential role of macrophages in translating these effects by analyzing gene expression patterns in response to diesel exhaust particles (DEP) at the average cell level, using Affymetrix microarrays in peritoneal macrophages in culture (in vitro), and at the individual cell level, using single-cell RNA sequencing (scRNA-seq) in alveolar macrophages collected from exposed mice (in vivo). Peritoneal macrophages were harvested from C57BL/6J mice and treated with 25 μg/mL of a DEP methanol extract (DEPe). These cells exhibited significant (FDR < 0.05) differential expression of a large number of genes and enrichment in pathways, especially engaged in immune responses and antioxidant defense. DEPe led to marked upregulation of heme oxygenase 1 (Hmox1), the most significantly upregulated gene (FDR = 1.75E-06), and several other antioxidant genes. For the in vivo work, C57BL/6J mice were subjected to oropharyngeal aspiration of 200 μg of whole DEP. The gene expression profiles of the alveolar macrophages harvested from these mice were analyzed at the single-cell level using scRNA-seq, which showed significant dysregulation of a broad number of genes enriched in immune system pathways as well, but with a large heterogeneity in how individual alveolar macrophages responded to DEP exposures. Altogether, DEP pollutants dysregulated immunological pathways in macrophages that may mediate the development of pulmonary and systemic vascular effects.

The human circulating miRNome reflects multiple organ disease risks in association with short-term exposure to traffic-related air pollution

Traffic-related air pollution is a complex mixture of particulate matter (PM) and gaseous pollutants, such as nitrogen dioxide (NO2). PM exposure contributes to the pathogenesis of many diseases including several types of cancer, as well as pulmonary, cardiovascular and neurodegenerative diseases. Also exposure to NO2 has been related to increased cardiovascular mortality. In search of an early diagnostic biomarker for improved air pollution-associated health risk assessment, recent human studies have shown that certain circulating miRNAs are altered upon exposure to traffic-related air pollutants. Here, we present for the first time a global analysis of the circulating miRNA genome in an experimental cross-over study of a human population exposed to traffic-related air pollution. By utilizing next-generation sequencing technology and detailed real-time exposure measurements we identified 54 circulating miRNAs to be dose- and pollutant species-dependently associated with PM10, PM2.5, black carbon, ultrafine particles and NO2 already after 2 h of exposure. Bioinformatics analysis suggests that these circulating miRNAs actually reflect the adverse consequences of traffic pollution-induced toxicity in target tissues including the lung, heart, kidney and brain. This study shows the strong potential of circulating miRNAs as novel biomarkers for environmental health risk assessment.

The exposome in practice: Design of the EXPOsOMICS project

EXPOsOMICS is a European Union funded project that aims to develop a novel approach to the assessment of exposure to high priority environmental pollutants, by characterizing the external and the internal components of the exposome. It focuses on air and water contaminants during critical periods of life. To this end, the project centres on 1) exposure assessment at the personal and population levels within existing European short and long-term population studies, exploiting available tools and methods which have been developed for personal exposure monitoring (PEM); and 2) multiple "omic" technologies for the analysis of biological samples (internal markers of external exposures). The search for the relationships between external exposures and global profiles of molecular features in the same individuals constitutes a novel advancement towards the development of "next generation exposure assessment" for environmental chemicals and their mixtures. The linkage with disease risks opens the way to what are defined here as 'exposome-wide association studies' (EWAS).

Nrf2-related gene expression and exposure to traffic-related air pollution in elderly subjects with cardiovascular disease: An exploratory panel study

Gene expression changes are linked to air pollutant exposures in in vitro and animal experiments. However, limited data are available on how these outcomes relate to ambient air pollutant exposures in humans. We performed an exploratory analysis testing whether gene expression levels were associated with air pollution exposures in a Los Angeles area cohort of elderly subjects with coronary artery disease. Candidate genes (35) were selected from published studies of gene expression-pollutant associations. Expression levels were measured weekly in 43 subjects (≤ 12 weeks) using quantitative PCR. Exposures included gaseous pollutants O3, nitrogen oxides (NOx), and CO; particulate matter (PM) pollutants elemental and black carbon (EC, BC); and size-fractionated PM mass. We measured organic compounds from PM filter extracts, including polycyclic aromatic hydrocarbons (PAHs), and determined the in vitro oxidative potential of particle extracts. Associations between exposures and gene expression levels were analyzed using mixed-effects regression models. We found positive associations of traffic-related pollutants (EC, BC, primary organic carbon, PM 0.25-2.5 PAH and/or PM 0.25 PAH, and NOx) with NFE2L2, Nrf2-mediated genes (HMOX1, NQO1, and SOD2), CYP1B1, IL1B, and SELP. Findings suggest that NFE2L2 gene expression links associations of traffic-related air pollution with phase I and II enzyme genes at the promoter transcription level.

Development and regulatory application of microRNA biomarkers

MicroRNAs, a class of regulatory small non-coding RNAs, are emerging as promising biomarkers for different health outcomes. Due to their tissue specificity, stability in extracellular space and high conservation between preclinical test species, applications of novel miRNA-based biomarkers for drug safety testing regarding hepatotoxicity and cardiotoxicity are investigated. Furthermore, miRNA expression is altered by environmental exposure such as cigarette smoke or polychlorinated biphenyls. As a consequence, miRNAs potentially influence tumor suppressor genes and oncogenes and may influence carcinogenesis. This has raised the interest in the use of miRNA profiles for health risk assessment. This review summarizes the recent developments in miRNA research with focus on biomarkers for drug safety testing and biomarkers for health outcomes related to environmental exposures.

Reduced gene expression levels after chronic exposure to high concentrations of air pollutants

We analyzed the ability of particulate matter (PM) and chemicals adsorbed onto it to induce diverse gene expression profiles in subjects living in two regions of the Czech Republic differing in levels and sources of the air pollution. A total of 312 samples from polluted Ostrava region and 154 control samples from Prague were collected in winter 2009, summer 2009 and winter 2010. The highest concentrations of air pollutants were detected in winter 2010 when the subjects were exposed to: PM of aerodynamic diameter <2.5μm (PM2.5) (70 vs. 44.9μg/m(3)); benzo[a]pyrene (9.02 vs. 2.56ng/m(3)) and benzene (10.2 vs. 5.5μg/m(3)) in Ostrava and Prague, respectively. Global gene expression analysis of total RNA extracted from leukocytes was performed using Illumina Expression BeadChips microarrays. The expression of selected genes was verified by quantitative real-time PCR (qRT-PCR). Gene expression profiles differed by locations and seasons. Despite lower concentrations of air pollutants a higher number of differentially expressed genes and affected KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways was found in subjects from Prague. In both locations immune response pathways were affected, in Prague also neurodegenerative diseases-related pathways. Over-representation of the latter pathways was associated with the exposure to PM2.5. The qRT-PCR analysis showed a significant decrease in expression of APEX, ATM, FAS, GSTM1, IL1B and RAD21 in subjects from Ostrava, in a comparison of winter 2010 and summer 2009. In Prague, an increase in gene expression was observed for GADD45A and PTGS2. In conclusion, high concentrations of pollutants in Ostrava were not associated with higher number of differentially expressed genes, affected KEGG pathways and expression levels of selected genes. This observation suggests that chronic exposure to air pollution may result in reduced gene expression response with possible negative health consequences.

Characterization of the peripheral blood transcriptome in a repeated measures design using a panel of healthy individuals

A repeated measures microarray design with 22 healthy, non-smoking volunteers (aging 32±5years) was set up to study transcriptome profiles in whole blood samples. The results indicate that repeatable data can be obtained with high within-subject correlation. Probes that could discriminate between individuals are associated with immune and inflammatory functions. When investigating possible time trends in the microarray data, we have found no differential expression within a sampling period (within-season effect). Differential expression was observed between sampling seasons and the data suggest a weak response of genes related to immune system functioning. Finally, a high number of probes showed significant season-specific expression variability within subjects. Expression variability increased in springtime and there was an association of the probe list with immune system functioning. Our study suggests that the blood transcriptome of healthy individuals is reproducible over a time period of several months.

Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes

Background

Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven manner. However, significant challenges exist with regard to how to segregate individuals into suitable subtypes of the disease and understand the distinct biological mechanisms of each when the goal is to maximize the discovery potential of these data sets.

Results

A multi-step decision tree-based method is described for defining endotypes based on gene expression, clinical covariates, and disease indicators using childhood asthma as a case study. We attempted to use alternative approaches such as the Student’s t-test, single data domain clustering and the Modk-prototypes algorithm, which incorporates multiple data domains into a single analysis and none performed as well as the novel multi-step decision tree method. This new method gave the best segregation of asthmatics and non-asthmatics, and it provides easy access to all genes and clinical covariates that distinguish the groups.

Conclusions

The multi-step decision tree method described here will lead to better understanding of complex disease in general by allowing purely data-driven disease endotypes to facilitate the discovery of new mechanisms underlying these diseases. This application should be considered a complement to ongoing efforts to better define and diagnose known endotypes. When coupled with existing methods developed to determine the genetics of gene expression, these methods provide a mechanism for linking genetics and exposomics data and thereby accounting for both major determinants of disease.

Gender-specific transcriptomic response to environmental exposure in Flemish adults

Flanders, Belgium, is one of the most densely populated areas in Europe. The Flemish Environment and Health Survey (2002-2006) aimed at determining exposure to pollutants of neonates, adolescents, and older adults and to assess associated biological and health effects. This study investigated genome wide gene expression changes associated with a range of environmental pollutants, including cadmium, lead, PCBs, dioxin, hexachlorobenzene, p,p'-DDE, benzene, and PAHs. Gene expression levels were measured in peripheral blood cells of 20 adults with relatively high and 20 adults with relatively low combined internal exposure levels, all non-smokers aged 50-65. Pearson correlation was used to analyze associations between pollutants and gene expression levels, separately for both genders. Pollutant- and gender-specific correlation analysis results were obtained. For organochlorine pollutants, analysis within genders revealed that genes were predominantly regulated in opposite directions in males and females. Significantly modulated pathways were found to be associated with each of the exposure biomarkers measured. Pathways and/or genes related to estrogen and STAT5 signaling were correlated to organochlorine exposures in both genders. Our work demonstrates that gene expression in peripheral blood is influenced by environmental pollutants. In particular, gender-specific changes are associated with organochlorine pollutants, including gender-specific modulation of endocrine related pathways and genes. These pathways and genes have previously been linked to endocrine disruption related disorders, which in turn have been associated with organochlorine exposure. Based on our results, we recommend that males and females be considered separately when analyzing gene expression changes associated with exposures that may include chemicals with endocrine disrupting properties.

Making sense of OMICS data in population-based environmental health studies

Although experience from the application of OMICS technologies in population-based environmental health studies is still relatively limited, the accumulated evidence shows that it can allow the identification of features (genes, proteins, and metabolites), or sets of such features, which are targeted by particular exposures or correlate with disease risk. Such features or profiles can therefore serve as biomarkers of exposure or disease risk. Blood-based OMIC profiles appear to reflect to some extent events occurring in target tissues and are associated with toxicity or disease and therefore have the potential to facilitate the elucidation of exposure-disease relationships. Further progress in this direction requires better understanding of the significance of exposure-induced network perturbations for disease initiation and progression and the development of a framework that combines agnostic searches with the utilization of prior knowledge, taking account of particular elements which characterize the structure and evolution of complex systems and brings in principles of systems biology.

Factors affecting the 27K DNA methylation pattern in asthmatic and healthy children from locations with various environments

Gene expression levels are significantly regulated by DNA methylation. Differences in gene expression profiles in the populations from various locations with different environmental conditions were repeatedly observed. In this study we compare the methylation profiles in 200 blood samples of children (aged 7-15 years) with and without bronchial asthma from two regions in the Czech Republic with different levels of air pollution (a highly polluted Ostrava region and a control Prachatice region). Samples were collected in March 2010 when the mean concentrations of benzo[a]pyrene (B[a]P) measured by stationary monitoring were 10.1±2.4ng/m(3) in Ostrava Bartovice (5.6 times higher than in the control region). Significantly higher concentrations of other pollutants (benzene, NO2, respirable air particles and metals) were also found in Ostrava. We applied the Infinium Methylation Assay, using the Human Methylation 27K BeadChip with 27,578 CpG loci for identification of the DNA methylation pattern in studied groups. Results demonstrate a significant impact of different environmental conditions on the DNA methylation patterns of children from the two regions. We found 9916 CpG sites with significantly different methylation (beta value) between children from Ostrava vs. Prachatice from which 58 CpG sites had differences >10%. The methylation of all these 58 CpG sites was lower in children from polluted Ostrava, which indicates a higher gene expression in comparison with the control Prachatice region. We did not find a difference in DNA methylation patterns between children with and without bronchial asthma in individual locations, but patterns in both asthmatics and healthy children differed between Ostrava and Prachatice. Further, we show differences in DNA methylation pattern depending on gender and urinary cotinine levels. Other factors including length of gestation, birth weight and length of full breastfeeding are suggested as possible factors that can impact the DNA methylation pattern in future life.

Health impact of air pollution to children

Health impact of air pollution to children was studied over the last twenty years in heavily polluted parts of the Czech Republic during. The research program (Teplice Program) analyzed these effects in the polluted district Teplice (North Bohemia) and control district Prachatice (Southern Bohemia). Study of pregnancy outcomes for newborns delivered between 1994 and 1998 demonstrated that increase in intrauterine growth retardation (IUGR) was associated with PM10 and c-PAHs exposure (carcinogenic polycyclic aromatic hydrocarbons) in the first month of gestation. Morbidity was followed in the cohort of newborns (N=1492) up to the age of 10years. Coal combustion in homes was associated with increased incidence of lower respiratory track illness and impaired early childhood skeletal growth up to the age of 3years. In preschool children, we observed the effect of increased concentrations of PM2.5 and PAHs on development of bronchitis. The Northern Moravia Region (Silesia) is characterized by high concentrations of c-PAHs due to industrial air pollution. Exposure to B[a]P (benzo[a]pyrene) in Ostrava-Radvanice is the highest in the EU. Children from this part of the city of Ostrava suffered higher incidence of acute respiratory diseases in the first year of life. Gene expression profiles in leukocytes of asthmatic children compared to children without asthma were evaluated in groups from Ostrava-Radvanice and Prachatice. The results suggest the distinct molecular phenotype of asthma bronchiale in children living in polluted Ostrava region compared to children living in Prachatice. The effect of exposure to air pollution to biomarkers in newborns was analyzed in Prague vs. Ceske Budejovice, two locations with different levels of pollution in winter season. B[a]P concentrations were higher in Ceske Budejovice. DNA adducts and micronuclei were also elevated in cord blood in Ceske Budejovice in comparison to Prague. Study of gene expression profiles in the cord blood showed differential expression of 104 genes. Specifically, biological processes related to immune and defense response were down-regulated in Ceske Budejovice. Our studies demonstrate that air pollution significantly affect child health. Especially noticeable is the increase of respiratory morbidity. With the development of molecular epidemiology, we can further evaluate the health risk of air pollution using biomarkers.

Transcriptomic network analysis of micronuclei-related genes: a case study

Mechanistically relevant information on responses of humans to xenobiotic exposure in relation to chemically induced biological effects, such as micronuclei (MN) formation can be obtained through large-scale transcriptomics studies. Network analysis may enhance the analysis and visualisation of such data. Therefore, this study aimed to develop a 'MN formation' network based on a priori knowledge, by using the pathway tool MetaCore. The gene network contained 27 genes and three gene complexes that are related to processes involved in MN formation, e.g. spindle assembly checkpoint, cell cycle checkpoint and aneuploidy. The MN-related gene network was tested against a transcriptomics case study associated with MN measurements. In this case study, transcriptomic data from children and adults differentially exposed to ambient air pollution in the Czech Republic were analysed and visualised on the network. Six genes from the network, i.e. BAX, DMNT1, PCNA, HIC1, p21 and CDC20, were retrieved. Based on these six genes and in combination with p53 and IL-6, a dedicated network was created. This dedicated network is possibly suited for the development of a reporter gene assay that could be used to screen populations complementary to the current MN test assay. In conclusion, we have shown that network analysis of transcriptomics data in relation to the formation of MN is possible and provides a novel mechanistic hypothesis by indicating which genes are regulated and influence others.

Toxicogenomic profiling of chemically exposed humans in risk assessment

Gene-environment interactions contribute to complex disease development. The environmental contribution, in particular low-level and prevalent environmental exposures, may constitute much of the risk and contribute substantially to disease. Systematic risk evaluation of the majority of human chemical exposures, has not been conducted and is a goal of regulatory agencies in the U.S. and worldwide. With the recent recognition that toxicological approaches more predictive of effects in humans are required for risk assessment, in vitro human cell line data as well as animal data are being used to identify toxicity mechanisms that can be translated into biomarkers relevant to human exposure studies. In this review, we discuss how data from toxicogenomic studies of exposed human populations can inform risk assessment, by generating biomarkers of exposure, early effect, and/or susceptibility, elucidating mechanisms of action underlying exposure-related disease, and detecting response at low doses. Good experimental design incorporating precise, individual exposure measurements, phenotypic anchors (pre-disease or traditional toxicological markers), and a range of relevant exposure levels, is necessary. Further, toxicogenomic studies need to be designed with sufficient power to detect true effects of the exposure. As more studies are performed and incorporated into databases such as the Comparative Toxicogenomics Database (CTD) and Chemical Effects in Biological Systems (CEBS), data can be mined for classification of newly tested chemicals (hazard identification), and, for investigating the dose-response, and inter-relationship among genes, environment and disease in a systems biology approach (risk characterization).

Gender-related differences in response to mutagens and carcinogens

The incidences of many cancers can be very different in men and women. Besides differences in exposures to putative causative agents, it is plausible that both genetic and epigenetic effects play roles in these differences. In addition, gender-specific lifestyle and behavioural factors may modulate the effects of exposure to genotoxins. This commentary focuses on several aspects of gender-related differences in responses to mutagens and carcinogens, including sensitivity to chromosome damage, the contribution of genotypic variation and the role of DNA methylation. It is concluded that the reasons for gender differences in cancer susceptibility remain largely unknown in many cases, and the subject deserves more attention and study.

Environmental exposure measurement in cancer epidemiology

Environmental exposures, used in the broadest sense of lifestyle, infections, radiation, natural and man-made chemicals and occupation, are a major cause of human cancer. However, the precise contribution of specific risk factors and their interaction, both with each other and with genotype, continues to be difficult to elucidate. This is partially due to limitations in accurately measuring exposure with the subsequent risk of misclassification. One of the primary challenges of molecular cancer epidemiology therefore is to improve exposure assessment. Progress has been made with biomarkers such as carcinogens and their metabolites, DNA and protein adducts and mutations measured in various tissues and body fluids. Nevertheless, much remains to be accomplished in order to establish aetiology and provide the evidence base for public health decisions. This review considers some of the principles behind the application of exposure biomarkers in cancer epidemiology. It also demonstrates how the same biomarkers can contribute both to establishing the biological plausibility of associations between exposure and disease and be valuable endpoints in intervention studies. The potential of new technologies such as transcriptomics, proteomics and metabonomics to provide a step change in environmental exposure assessment is discussed. An increasing recognition of the role of epigenetic changes in carcinogenesis presents a fresh challenge as alterations in DNA methylation, histone modification and microRNA in response to environmental exposures demand a new generation of exposure biomarker. The overall importance of this area of research is brought into sharp relief by the large prospective cohort studies (e.g. UK Biobank) which need accurate exposure measurement in order to shed light on the complex gene:environment interactions underlying common chronic disorders including cancer. It is suggested that a concerted effort is now required, with appropriate funding, to develop and validate the required exposure assessment methodology before these cohorts come to maturity.

Transcriptome analysis in peripheral blood of humans exposed to environmental carcinogens: a promising new biomarker in environmental health studies

BACKGROUND

Human carcinogenesis is known to be initiated and/or promoted by exposure to chemicals that occur in the environment. Molecular cancer epidemiology is used to identify human environmental cancer risks by applying a range of effect biomarkers, which tend to be nonspecific and do not generate insights into underlying modes of action. Toxicogenomic technologies may improve on this by providing the opportunity to identify molecular biomarkers consisting of altered gene expression profiles.

OBJECTIVES

The aim of the present study was to monitor the expression of selected genes in a random sample of adults in Flanders selected from specific regions with (presumably) different environmental burdens. Furthermore, associations of gene expression with blood and urinary measures of biomarkers of exposure, early phenotypic effects, and tumor markers were investigated.

RESULTS

Individual gene expression of cytochrome p450 1B1, activating transcription factor 4, mitogen-activated protein kinase 14, superoxide dismutase 2 (Mn), chemokine (C-X-C motif) lig-and 1 (melanoma growth stimulating activity, alpha), diacylglycerol O-acyltransferase homolog 2 (mouse), tigger transposable element derived 3, and PTEN-induced putative kinase1 were measured by means of quantitative polymerase chain reaction in peripheral blood cells of 398 individuals. After correction for the confounding effect of tobacco smoking, inhabitants of the Olen region showed the highest differences in gene expression levels compared with inhabitants from the Gent and fruit cultivation regions. Importantly, we observed multiple significant correlations of particular gene expressions with blood and urinary measures of various environmental carcinogens.

CONCLUSIONS

Considering the observed significant differences between gene expression levels in inhabitants of various regions in Flanders and the associations of gene expression with blood or urinary measures of environmental carcinogens, we conclude that gene expression profiling appears promising as a tool for biological monitoring in relation to environmental exposures in humans.

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

Background

In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions.

Results

In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability.

Conclusion

CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that resulted in a selection of genes with a potential impact in the regulation of complex pathways.

Genetic susceptibility of newborn daughters to oxidative stress

A central question in risk assessment is whether newborns' susceptibility to mutagens is different from that of adults. Therefore we investigated whether genotype and/or the DNA strand break repair phenotype in combination with the MN assay would allow estimation of the relative sensitivity of a newborn as compared to his mother for oxidative DNA damage. We compared the in vitro genetic susceptibility for H2O2 in PBMC of 17 mother-newborn daughter pairs taking into account genotypes for relevant DNA repair (hOGG1, XRCC1, XRCC3, XPD) and folate metabolism (MTHFR) polymorphisms. After in vitro challenge with H2O2 the repair capacity was assessed by the Comet assay and chromosome/genome mutations by the cytokinesis-block MN assay. No statistically significant differences were found between mothers and their newborn daughters either for initial DNA damage or for residual DNA damage. Mothers showed higher background frequencies of MN as compared to their newborn daughters, due to the age factor. This was confirmed by significantly higher frequencies of MN observed in mothers versus newborn daughters for several genotypes. No genotype with a significant effect on DNA repair capacity in newborns was identified. Concerning MN frequencies, however, newborns carrying the variant XRCC3(241) genotype might be at higher risk for the induction of MN by oxidative stress. Multivariate analysis revealed a significant protective effect of maternal antioxidant supplementation during pregnancy against oxidative DNA damage in newborns in terms of MN frequencies. However, these conclusions might not be extrapolable to other types of DNA damage and need confirmation in a study on a larger population.

Biomarkers of intermediate endpoints in environmental and occupational health

The use of biomarkers in environmental and occupational health is increasing due to increasing demands on information about health risks from unfavourable exposures. Biomarkers provide information about individual loads. Biomarkers of intermediate endpoints benefit in comparison with biomarkers of exposure from the fact that they are closer to the adverse outcome in the pathway from exposure to health effects and may provide powerful information for intervention. Some biomarkers are specific, e.g., DNA and protein adducts, while others are unspecific like the cytogenetic biomarkers of chromosomal aberrations (CA), sister chromatid exchanges and micronuclei (MN). The validation of biomarkers includes measurements of sensitivity and specificity of biomarkers and round robin tests to ensure reproducible protocols within different laboratories. The predictive value of biomarkers with respect to adverse health effect from the result of the measurement has been performed for the cytogenetic biomarkers showing a predictive value of high levels of CA and increased risk of cancer. The use of CA in future studies is, however, limited by the laborious and sensitive procedure of the test and lack of trained cytogeneticists. Less time consuming, but robust biomarkers, sensitive to environmental exposures are suggested. From the selection of developed biomarkers, the comet assay is highly sensitive to lifestyle exposures, often confounding the output, while MN in lymphocytes seem promising with respect to laboratory and health effect (cancer) validity. Also, new biomarkers exploiting the new 'omics' technologies are being developed. A number of ethical issues arise from the use of biomarkers with a predictive value aiming at respecting the autonomy of the study person in participation (only upon written informed consent and with obligations of withdrawal at any time), access to personal information (right to know and right not to know the study result) and securing proper data management (data protection to avoid misuse in employment, insurance, loaning and learning opportunities).

Usefulness of biomarkers in population studies: from exposure to susceptibility and to prediction of cancer

From a review of decades of intensive biomarker research and prospective validation studies, it becomes clear that only a limited number of biomarkers can be used to provide reliable documentation of excessive exposure to environmental mutagenic agents, expression of detrimental biological effects from the exposure and increased risk for cancer. These studies also demonstrate that expression of each biomarker represents an integrated response to the exposure that is influenced by susceptibility factors, and an integral component of the complex carcinogenic pathway. A current interest is in the use of phenotypic functional assays to improve and complement the assessment of cancer risk. A recommended approach includes assays that indicate DNA repair deficiency, i.e. host-cell-mediated reporter gene and challenge (mutagen-sensitivity) assays. The usefulness and limitations in biomarker investigations will be discussed. The review emphasizes the need for carefully designed investigations that involve adequate sample sizes and a combination of appropriate biomarkers to generate reproducible results that can be translated into more reliable cancer risk assessment. The assessment can be used to drive the implementation of disease prevention and intervention activities. Such an approach is consistent with the current priority in translating basic science knowledge into health applications.