Multiomic Signatures of Traffic-Related Air Pollution in London Reveal Potential Short-Term Perturbations in Gut Microbiome-Related Pathways.

This randomized crossover study investigated the metabolic and mRNA alterations associated with exposure to high and low traffic-related air pollution (TRAP) in 50 participants who were either healthy or were diagnosed with chronic pulmonary obstructive disease (COPD) or ischemic heart disease (IHD). For the first time, this study combined transcriptomics and serum metabolomics measured in the same participants over multiple time points (2 h before, and 2 and 24 h after exposure) and over two contrasted exposure regimes to identify potential multiomic modifications linked to TRAP exposure. With a multivariate normal model, we identified 78 metabolic features and 53 mRNA features associated with at least one TRAP exposure. Nitrogen dioxide (NO2) emerged as the dominant pollutant, with 67 unique associated metabolomic features. Pathway analysis and annotation of metabolic features consistently indicated perturbations in the tryptophan metabolism associated with NO2 exposure, particularly in the gut-microbiome-associated indole pathway. Conditional multiomics networks revealed complex and intricate mechanisms associated with TRAP exposure, with some effects persisting 24 h after exposure. Our findings indicate that exposure to TRAP can alter important physiological mechanisms even after a short-term exposure of a 2 h walk. We describe for the first time a potential link between NO2 exposure and perturbation of the microbiome-related pathways.

A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data.

Given the association of disturbances in non-esterified fatty acid (NEFA) metabolism with the development of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models of glucose-insulin dynamics have been extended to account for the interplay with NEFA. In this study, we use arteriovenous measurement across the subcutaneous adipose tissue during a mixed meal challenge test to evaluate the performance and underlying assumptions of three existing models of adipose tissue metabolism and construct a new, refined model of adipose tissue metabolism. Our model introduces new terms, explicitly accounting for the conversion of glucose to glyceraldehye-3-phosphate, the postprandial influx of glycerol into the adipose tissue, and several physiologically relevant delays in insulin signalling in order to better describe the measured adipose tissues fluxes. We then applied our refined model to human adipose tissue flux data collected before and after a diet intervention as part of the Yoyo study, to quantify the effects of caloric restriction on postprandial adipose tissue metabolism. Significant increases were observed in the model parameters describing the rate of uptake and release of both glycerol and NEFA. Additionally, decreases in the model's delay in insulin signalling parameters indicates there is an improvement in adipose tissue insulin sensitivity following caloric restriction.

The application of omics-based human liver platforms for investigating the mechanism of drug-induced hepatotoxicity in vitro.

Drug-induced liver injury (DILI) complicates safety assessment for new drugs and poses major threats to both patient health and drug development in the pharmaceutical industry. A number of human liver cell-based in vitro models combined with toxicogenomics methods have been developed as an alternative to animal testing for studying human DILI mechanisms. In this review, we discuss the in vitro human liver systems and their applications in omics-based drug-induced hepatotoxicity studies. We furthermore present bioinformatic approaches that are useful for analyzing toxicogenomic data generated from these models and discuss their current and potential contributions to the understanding of mechanisms of DILI. Human pluripotent stem cells, carrying donor-specific genetic information, hold great potential for advancing the study of individual-specific toxicological responses. When co-cultured with other liver-derived non-parenchymal cells in a microfluidic device, the resulting dynamic platform enables us to study immune-mediated drug hypersensitivity and accelerates personalized drug toxicology studies. A flexible microfluidic platform would also support the assembly of a more advanced organs-on-a-chip device, further bridging gap between in vitro and in vivo conditions. The standard transcriptomic analysis of these cell systems can be complemented with causality-inferring approaches to improve the understanding of DILI mechanisms. These approaches involve statistical techniques capable of elucidating regulatory interactions in parts of these mechanisms. The use of more elaborated human liver models, in harmony with causality-inferring bioinformatic approaches will pave the way for establishing a powerful methodology to systematically assess DILI mechanisms across a wide range of conditions.

Consumption of Nitrate-Rich Beetroot Juice with or without Vitamin C Supplementation Increases the Excretion of Urinary Nitrate, Nitrite, and N-nitroso Compounds in Humans.

Consumption of nitrate-rich beetroot juice (BRJ) by athletes induces a number of beneficial physiological health effects, which are linked to the formation of nitric oxide (NO) from nitrate. However, following a secondary pathway, NO may also lead to the formation of N-nitroso compounds (NOCs), which are known to be carcinogenic in 39 animal species. The extent of the formation of NOCs is modulated by various other dietary factors, such as vitamin C. The present study investigates the endogenous formation of NOCs after BRJ intake and the impact of vitamin C on urinary NOC excretion. In a randomized, controlled trial, 29 healthy recreationally active volunteers ingested BRJ with or without additional vitamin C supplements for one week. A significant increase of urinary apparent total N-nitroso Compounds (ATNC) was found after one dose (5 to 47 nmol/mmol: p < 0.0001) and a further increase was found after seven consecutive doses of BRJ (104 nmol/mmol: p < 0.0001). Vitamin C supplementation inhibited ATNC increase after one dose (16 compared to 72 nmol/mmol, p < 0.01), but not after seven daily doses. This is the first study that shows that BRJ supplementation leads to an increase in formation of potentially carcinogenic NOCs. In order to protect athlete's health, it is therefore important to be cautious with chronic use of BRJ to enhance sports performances.

Pre-diagnostic blood immune markers, incidence and progression of B-cell lymphoma and multiple myeloma: Univariate and functionally informed multivariate analyses.

Recent prospective studies have shown that dysregulation of the immune system may precede the development of B-cell lymphomas (BCL) in immunocompetent individuals. However, to date, the studies were restricted to a few immune markers, which were considered separately. Using a nested case-control study within two European prospective cohorts, we measured plasma levels of 28 immune markers in samples collected a median of 6 years before diagnosis (range 2.01-15.97) in 268 incident cases of BCL (including multiple myeloma [MM]) and matched controls. Linear mixed models and partial least square analyses were used to analyze the association between levels of immune marker and the incidence of BCL and its main histological subtypes and to investigate potential biomarkers predictive of the time to diagnosis. Linear mixed model analyses identified associations linking lower levels of fibroblast growth factor-2 (FGF-2 p = 7.2 × 10-4 ) and transforming growth factor alpha (TGF-α, p = 6.5 × 10-5 ) and BCL incidence. Analyses stratified by histological subtypes identified inverse associations for MM subtype including FGF-2 (p = 7.8 × 10-7 ), TGF-α (p = 4.08 × 10-5 ), fractalkine (p = 1.12 × 10-3 ), monocyte chemotactic protein-3 (p = 1.36 × 10-4 ), macrophage inflammatory protein 1-alpha (p = 4.6 × 10-4 ) and vascular endothelial growth factor (p = 4.23 × 10-5 ). Our results also provided marginal support for already reported associations between chemokines and diffuse large BCL (DLBCL) and cytokines and chronic lymphocytic leukemia (CLL). Case-only analyses showed that Granulocyte-macrophage colony stimulating factor levels were consistently higher closer to diagnosis, which provides further evidence of its role in tumor progression. In conclusion, our study suggests a role of growth-factors in the incidence of MM and of chemokine and cytokine regulation in DLBCL and CLL.

Epigenome-wide association study of adiposity and future risk of obesity-related diseases.

BACKGROUND: Obesity is an established risk factor for several common chronic diseases such as breast and colorectal cancer, metabolic and cardiovascular diseases; however, the biological basis for these relationships is not fully understood. To explore the association of obesity with these conditions, we investigated peripheral blood leucocyte (PBL) DNA methylation markers for adiposity and their contribution to risk of incident breast and colorectal cancer and myocardial infarction. METHODS: DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population. RESULTS: We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P = 9.07×10-8 to 3.27×10-18) and lower transcriptional activity of the full-length isoform of ABCG1 (P = 6.00×10-7), higher triglyceride levels (P = 5.37×10-9) and higher triglycerides-to-HDL cholesterol ratio (P = 1.03×10-10). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P < 1.6×10-3) and one intergenic locus on chromosome 1 was inversely associated with myocardial infarction (P < 1.25×10-3), independently of obesity and established risk factors. CONCLUSION: Our results suggest that epigenetic changes, in particular altered DNA methylation patterns, may be an intermediate biomarker at the intersection of obesity and obesity-related diseases, and could offer clues as to underlying biological mechanisms.

Exploring the nature of prediagnostic blood transcriptome markers of chronic lymphocytic leukemia by assessing their overlap with the transcriptome at the clinical stage.

BACKGROUND: We recently identified 700 genes whose expression levels were predictive of chronic lymphocytic leukemia (CLL) in a genome-wide gene expression analysis of prediagnostic blood from future cases and matched controls. We hypothesized that a large fraction of these markers were likely related to early disease manifestations. Here we aim to gain a better understanding of the natural history of the identified markers by comparing results from our prediagnostic analysis, the only prediagnostic analysis to date, to results obtained from a meta-analysis of a series of publically available transcriptomics profiles obtained in incident CLL cases and controls. RESULTS: We observed considerable overlap between the results from our prediagnostic study and the clinical CLL signals (p-value for overlap Bonferroni significant markers 0.01; p-value for overlap nominal significant markers < 2.20e-16). We observed similar patterns with time to diagnosis and similar functional annotations for the markers that were identified in both settings compared to the markers that were only identified in the prediagnostic study. These results suggest that both gene sets operate in similar pathways. CONCLUSION: An overlap exists between expression levels of genes predictive of CLL identified in prediagnostic blood and expression levels of genes associated to CLL at the clinical stage. Our analysis provides insight in a set of genes for which expression levels can be used to follow the time-course of the disease; providing an opportunity to study CLL progression in more detail in future studies.

Evolving DNA methylation and gene expression markers of B-cell chronic lymphocytic leukemia are present in pre-diagnostic blood samples more than 10 years prior to diagnosis.

BACKGROUND: B-cell chronic lymphocytic leukemia (CLL) is a common type of adult leukemia. It often follows an indolent course and is preceded by monoclonal B-cell lymphocytosis, an asymptomatic condition, however it is not known what causes subjects with this condition to progress to CLL. Hence the discovery of prediagnostic markers has the potential to improve the identification of subjects likely to develop CLL and may also provide insights into the pathogenesis of the disease of potential clinical relevance. RESULTS: We employed peripheral blood buffy coats of 347 apparently healthy subjects, of whom 28 were diagnosed with CLL 2.0-15.7 years after enrollment, to derive for the first time genome-wide DNA methylation, as well as gene and miRNA expression, profiles associated with the risk of future disease. After adjustment for white blood cell composition, we identified 722 differentially methylated CpG sites and 15 differentially expressed genes (Bonferroni-corrected p < 0.05) as well as 2 miRNAs (FDR < 0.05) which were associated with the risk of future CLL. The majority of these signals have also been observed in clinical CLL, suggesting the presence in prediagnostic blood of CLL-like cells. Future CLL cases who, at enrollment, had a relatively low B-cell fraction (<10%), and were therefore less likely to have been suffering from undiagnosed CLL or a precursor condition, showed profiles involving smaller numbers of the same differential signals with intensities, after adjusting for B-cell content, generally smaller than those observed in the full set of cases. A similar picture was obtained when the differential profiles of cases with time-to-diagnosis above the overall median period of 7.4 years were compared with those with shorted time-to-disease. Differentially methylated genes of major functional significance include numerous genes that encode for transcription factors, especially members of the homeobox family, while differentially expressed genes include, among others, multiple genes related to WNT signaling as well as the miRNAs miR-150-5p and miR-155-5p. CONCLUSIONS: Our findings demonstrate the presence in prediagnostic blood of future CLL patients, more than 10 years before diagnosis, of CLL-like cells which evolve as preclinical disease progresses, and point to early molecular alterations with a pathogenetic potential.

Nuclear and Mitochondrial DNA Methylation Patterns Induced by Valproic Acid in Human Hepatocytes.

Valproic acid (VPA) is one of the most widely prescribed antiepileptic drugs in the world. Despite its pharmacological importance, it may cause liver toxicity and steatosis through mitochondrial dysfunction. The aim of this study is to further investigate VPA-induced mechanisms of steatosis by analyzing changes in patterns of methylation in nuclear DNA (nDNA) and mitochondrial DNA (mtDNA). Therefore, primary human hepatocytes (PHHs) were exposed to an incubation concentration of VPA that was shown to cause steatosis without inducing overt cytotoxicity. VPA was administered daily for 5 days, and this was followed by a 3 day washout (WO). Methylated DNA regions (DMRs) were identified by using the methylated DNA immunoprecipitation-sequencing (MeDIP-seq) method. The nDNA DMRs after VPA treatment could indeed be classified into oxidative stress- and steatosis-related pathways. In particular, networks of the steatosis-related gene EP300 provided novel insight into the mechanisms of toxicity induced by VPA treatment. Furthermore, we suggest that VPA induces a crosstalk between nDNA hypermethylation and mtDNA hypomethylation that plays a role in oxidative stress and steatosis development. Although most VPA-induced methylation patterns appeared reversible upon terminating VPA treatment, 31 nDNA DMRs (including 5 zinc finger protein genes) remained persistent after the WO period. Overall, we have shown that MeDIP-seq analysis is highly informative in disclosing novel mechanisms of VPA-induced toxicity in PHHs. Our results thus provide a prototype for the novel generation of interesting methylation biomarkers for repeated dose liver toxicity in vitro.

Integrative "-Omics" Analysis in Primary Human Hepatocytes Unravels Persistent Mechanisms of Cyclosporine A-Induced Cholestasis.

Cyclosporine A (CsA) is an undecapeptide with strong immunosuppressant activities and is used a lot after organ transplantation. Furthermore, it may induce cholestasis in the liver. In general, the drug-induced cholestasis (DIC) pathway includes genes involved in the uptake, synthesis, conjugation, and secretion of bile acids. However, whether CsA-induced changes in the cholestasis pathway in vitro are persistent for repeated dose toxicity has not yet been investigated. To explore this, primary human hepatocytes (PHH) were exposed to a subcytotoxic dose of 30 µM CsA daily for 3 and 5 days. To investigate the persistence of induced changes upon terminating CsA exposure after 5 days, a subset of PHH was subjected to a washout period (WO-period) of 3 days. Multiple -omics analyses, comprising whole genome analysis of DNA methylation, gene expression, and microRNA expression, were performed. The CsA-treatment resulted after 3 and 5 days, respectively, in 476 and 20 differentially methylated genes (DMGs), 1353 and 1481 differentially expressed genes (DEGs), and in 22 and 29 differentially expressed microRNAs (DE-miRs). Cholestasis-related pathways appeared induced during CsA-treatment. Interestingly, 828 persistent DEGs and 6 persistent DE-miRs but no persistent DMGs were found after the WO-period. These persistent DEGs and DE-miRs showed concordance for 22 genes. Furthermore, 29 persistent DEGs changed into the same direction as observed in livers from cholestasis patients. None of those 29 DEGs which among others relate to oxidative stress and lipid metabolism are yet present in the DIC pathway or cholestasis adverse outcome pathway (AOP) thus presenting novel findings. In summary, we have demonstrated for the first time a persistent impact of repeated dose administration of CsA on genes and microRNAs related to DIC in the gold standard human liver in vitro model with PHH.

Distinct genotype-dependent differences in transcriptome responses in humans exposed to environmental carcinogens.

Considering genetic variability in population studies focusing on the health risk assessment of exposure to environmental carcinogens may provide improved insights in individual environmental cancer risks. Therefore, the current study aims to determine the impact of genetic polymorphisms on the relationship between exposure and gene expression, by identifying exposure-dependently coregulated genes and genetic pathways. Statistical analysis based on mixed models, was performed to relate gene expression data from 134 subjects to exposure measurements of multiple carcinogens, 28 polymorphisms, age, sex and biomarkers of cancer risk. We evaluated the combined exposure to cadmium, lead, polychlorinated biphenyls, p,p'-dichlorodiphenyldichloroethylene, hexachlorobenzene and 1-OH-pyrene, and the outcome was biologically interpreted by using ConsensusPathDB, thereby focusing on carcinogenesis-related pathways. We found generic and carcinogenesis-related pathways deregulated in both sexes, but males showed a stronger transcriptome response than females. We highlighted NOTCH1, CBR1, ITGB3, ITGA4, ADI1, HES1, NCOA2 and SMARCA2 in view of their direct link with cancer development. Two of these, NOTCH1 and ITGB3, are also known to respond to PCBs and cadmium chloride exposure in rodents and to lead in humans. Subjects carrying a high number of risk alleles appear more responsive to combined carcinogen exposure with respect to the induced expression of some of these cancer-related genes, which may be indicative of increased cancer risk as a consequence of environmental factors.

The exposome concept in a human nutrigenomics study: evaluating the impact of exposure to a complex mixture of phytochemicals using transcriptomics signatures.

The application of transcriptome analyses in molecular epidemiology studies has become a promising tool in order to evaluate the impact of environmental exposures. These analyses have a great value in establishing the exposome, the totality of human exposures, both by identifying the chemical nature of the exposures and the induced molecular responses. Transcriptomic signatures can be regarded as biomarker of exposure as well as markers of effect which reflect the interaction between individual genetic background and exposure levels. However, the biological interpretation of modulated gene expression profiles is a challenging task and translating affected molecular pathways into risk assessment, for instance in terms of cancer promoting or disease preventing responses, is a far from standardised process. Here, we describe the in-depth analyses of the gene expression responses in a human dietary intervention in which the interaction between genotype and exposure to a blueberry-apple juice containing a complex mixture of phytochemicals is investigated. We also describe how data on differences in genetic background combined with different effect markers can provide a better understanding of gene-environment interactions. Pathway analyses of differentially expressed genes in combination with gene were used to identify complex but strong changes in several biological processes like immune response, cell adhesion, lipid metabolism and apoptosis. These observed changes may lead to upgraded growth control, induced immunity, reduced platelet aggregation and activation, diminished production of reactive oxidative species by platelets, blood glucose homeostasis, regulation of blood lipid levels and increased apoptosis. Our findings demonstrate that applying transcriptomics to well-controlled human dietary intervention studies can provide insight into mechanistic pathways involved in disease prevention by dietary factors.

Epigenetic mechanisms underlying arsenic-associated lung carcinogenesis.

Arsenic is an established human carcinogen, but the mechanisms through which it contributes to for instance lung cancer development are still unclear. As arsenic is methylated during its metabolism, it may interfere with the DNA methylation process, and is therefore considered to be an epigenetic carcinogen. In the present study, we hypothesize that arsenic is able to induce DNA methylation changes, which lead to changes in specific gene expression, in pathways associated with lung cancer promotion and progression. A549 human adenocarcinoma lung cells were exposed to a low (0.08 µM), intermediate (0.4 µM) and high (2 µM) concentration of sodium arsenite for 1, 2 and 8 weeks. DNA was isolated for whole-genome DNA methylation analyses using NimbleGen 2.1 M deluxe promoter arrays. In addition, RNA was isolated for whole-genome transcriptomic analysis using Affymetrix microarrays. Arsenic modulated DNA methylation and expression levels of hundreds of genes in a dose-dependent and time-dependent manner. By combining whole-genome DNA methylation and gene expression data with possibly involved transcription factors, a large molecular interaction network was created based on transcription factor-target gene pairs, consisting of 216 genes. A tumor protein p53 (TP53) subnetwork was identified, showing the interactions of TP53 with other genes affected by arsenic. Furthermore, multiple other new genes were discovered showing altered DNA methylation and gene expression. In particular, arsenic modulated genes which function as transcription factor, thereby affecting target genes which are known to play a role in lung cancer promotion and progression.

Dietary acrylamide intake and the risk of colorectal cancer with specific mutations in KRAS and APC.

Acrylamide, a probable human carcinogen, is present in heat-treated carbohydrate-rich foods. Epidemiological studies have not shown a clear association between acrylamide intake and colorectal cancer (CRC) risk. This may be due to the molecular heterogeneity in colorectal tumors, which was not taken into consideration before. Since the acrylamide metabolite glycidamide induces specific DNA mutations in rodents, we investigated whether acrylamide is associated with CRC risk characterized by mutations in Kirsten-ras (KRAS) and adenomatous polyposis coli (APC); key genes in colorectal carcinogenesis. This case-cohort analysis, within the Netherlands Cohort Study on diet and cancer, was based on 7.3 years of follow-up. Acrylamide intake was assessed with a food frequency questionnaire. Mutation analysis of codons 1286-1520 in exon 15 in APC and codons 12 and 13 in exon 1 in KRAS was performed on tumor tissue of 733 cases. Hazard ratios (HR) were calculated using Cox proportional hazards analysis. Among men, acrylamide intake was statistically significantly associated with an increased risk of particularly tumors with an activating KRAS mutation {HR fourth versus first quartile: 2.12 [95% confidence interval (CI): 1.16-3.87], P trend: 0.01}. Among women, acrylamide intake was statistically significantly associated with a decreased risk of particularly tumors with a truncating APC mutation (fourth versus first quartile: 0.47 (95% CI: 0.23-0.94), P trend: 0.02), but only in the highest quartile of intake. This is the first study to show that acrylamide might be associated with CRC with specific somatic mutations, differentially in men and women. More research is needed to corroborate or refute these findings.

Analysis of cell-specific transcriptional responses in human colon tissue using CIBERSORTx.

Diet is an important determinant of overall health, and has been linked to the risk of various cancers. To understand the mechanisms involved, transcriptomic responses from human intervention studies are very informative. However, gene expression analysis of human biopsy material only represents the average profile of a mixture of cell types that can mask more subtle, but relevant cell-specific changes. Here, we use the CIBERSORTx algorithm to generate single-cell gene expression from human multicellular colon tissue. We applied the CIBERSORTx to microarray data from the PHYTOME study, which investigated the effects of different types of meat on transcriptional and biomarker changes relevant to colorectal cancer (CRC) risk. First, we used single-cell mRNA sequencing data from healthy colon tissue to generate a novel signature matrix in CIBERSORTx, then we determined the proportions and gene expression of each separate cell type. After comparison, cell proportion analysis showed a continuous upward trend in the abundance of goblet cells and stem cells, and a continuous downward trend in transit amplifying cells after the addition of phytochemicals in red meat products. The dietary intervention influenced the expression of genes involved in the growth and division of stem cells, the metabolism and detoxification of enterocytes, the translation and glycosylation of goblet cells, and the inflammatory response of innate lymphoid cells. These results show that our approach offers novel insights into the heterogeneous gene expression responses of different cell types in colon tissue during a dietary intervention.

Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data.

The liver is the primary site for the metabolism and detoxification of many compounds, including pharmaceuticals. Consequently, it is also the primary location for many adverse reactions. As the liver is not readily accessible for sampling in humans; rodent or cell line models are often used to evaluate potential toxic effects of a novel compound or candidate drug. However, relating the results of animal and in vitro studies to relevant clinical outcomes for the human in vivo situation still proves challenging. In this study, we incorporate principles of transfer learning within a deep artificial neural network allowing us to leverage the relative abundance of rat in vitro and in vivo exposure data from the Open TG-GATEs data set to train a model to predict the expected pattern of human in vivo gene expression following an exposure given measured human in vitro gene expression. We show that domain adaptation has been successfully achieved, with the rat and human in vitro data no longer being separable in the common latent space generated by the network. The network produces physiologically plausible predictions of human in vivo gene expression pattern following an exposure to a previously unseen compound. Moreover, we show the integration of the human in vitro data in the training of the domain adaptation network significantly improves the temporal accuracy of the predicted rat in vivo gene expression pattern following an exposure to a previously unseen compound. In this way, we demonstrate the improvements in prediction accuracy that can be achieved by combining data from distinct domains.

Whole-genome gene expression modifications associated with nitrosamine exposure and micronucleus frequency in human blood cells.

N-nitroso compounds (NOCs) are suspected human carcinogens and relevant in human exposure. NOCs also induce micronuclei (MN) formation in vivo. Since lymphocytic MN represent a validated biomarker of human cancer risk, establishing a link between NOC exposure and MN frequency in humans and concurrently investigating associated transcriptomic responses may provide crucial information on underlying molecular mechanisms that predispose to carcinogenicity. We used lymphocytes, from adult females participating in the pan-European biomarker research project NewGeneris, as a surrogate tissue for analysing such potentially carcinogenic gene expression and MN formation events in target organs. To assess NOC exposure, urine samples were analysed for marker nitrosamines. NOC excretion levels and MN frequency were subsequently linked to peripheral blood transcriptomics. We demonstrated a significant association between MN frequency and urinary NOCs (r = 0.41, P = 0.025) and identified modifications in among others cytoskeleton remodeling, cell cycle, apoptosis and survival, signal transduction, immune response, G-protein signaling and development pathways, which indicate a response to NOC-induced genotoxicity. Moreover, we established a network of genes, the most important ones of which include FBXW7, BUB3, Caspase 2, Caspase 8, SMAD3, Huntingtin and MGMT, which are involved in processes relevant in carcinogenesis. The modified genetic processes and genes found in this study may be of interest for future investigations into the potential carcinogenic risk associated with NOC exposure in humans.

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of gene expression measured following an exposure in rodents to humans, circumventing the current reliance on orthologs, and also from in vitro to in vivo experimental designs. Of the applied deep learning architectures applied in this study the convolutional neural network (CNN) and a deep artificial neural network with bottleneck architecture significantly outperform classical machine learning techniques in predicting the time series of gene expression in primary human hepatocytes given a measured time series of gene expression from primary rat hepatocytes following exposure in vitro to a previously unseen compound across multiple toxicologically relevant gene sets. With a reduction in average mean absolute error across 76 genes that have been shown to be predictive for identifying carcinogenicity from 0.0172 for a random regression forest to 0.0166 for the CNN model (p < 0.05). These deep learning architecture also perform well when applied to predict time series of in vivo gene expression given measured time series of in vitro gene expression for rats.

Identification of Sex-Specific Transcriptome Responses to Polychlorinated Biphenyls (PCBs).

PCBs are classified as xenoestrogens and carcinogens and their health risks may be sex-specific. To identify potential sex-specific responses to PCB-exposure we established gene expression profiles in a population study subdivided into females and males. Gene expression profiles were determined in a study population consisting of 512 subjects from the EnviroGenomarkers project, 217 subjects who developed lymphoma and 295 controls were selected in later life. We ran linear mixed models in order to find associations between gene expression and exposure to PCBs, while correcting for confounders, in particular distribution of white blood cells (WBC), as well as random effects. The analysis was subdivided according to sex and development of lymphoma in later life. The changes in gene expression as a result of exposure to the six studied PCB congeners were sex- and WBC type specific. The relatively large number of genes that are significantly associated with PCB-exposure in the female subpopulation already indicates different biological response mechanisms to PCBs between the two sexes. The interaction analysis between different PCBs and WBCs provides only a small overlap between sexes. In males, cancer-related pathways and in females immune system-related pathways are identified in association with PCBs and WBCs. Future lymphoma cases and controls for both sexes show different responses to the interaction of PCBs with WBCs, suggesting a role of the immune system in PCB-related cancer development.