Maria Tsamou

A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo

The lack of accurate in vitro assays for predicting in vivo toxicity of chemicals together with new legislations demanding replacement and reduction of animal testing has triggered the development of alternative methods. This study aimed at developing a transcriptomics-based in vitro prediction assay for in vivo genotoxicity. Transcriptomics changes induced in the human liver cell line HepG2 by 34 compounds after treatment for 12, 24, and 48 h were used for the selection of gene-sets that are capable of discriminating between in vivo genotoxins (GTX) and in vivo nongenotoxins (NGTX). By combining transcriptomics with publicly available results for these chemicals from standard in vitro genotoxicity studies, we developed several prediction models. These models were validated by using an additional set of 28 chemicals. The best prediction was achieved after stratification of chemicals according to results from the Ames bacterial gene mutation assay prior to transcriptomics evaluation after 24h of treatment. A total of 33 genes were selected for discriminating GTX from NGTX for Ames-positive chemicals and 22 for Ames-negative chemicals. Overall, this method resulted in 89% accuracy and 91% specificity, thereby clearly outperforming the standard in vitro test battery. Transcription factor network analysis revealed HNF3a, HNF4a, HNF6, androgen receptor, and SP1 as main factors regulating the expression of classifiers for Ames-positive chemicals. Thus, the classical bacterial gene mutation assay in combination with in vitro transcriptomics in HepG2 is proposed as an upgraded in vitro approach for predicting in vivo genotoxicity of chemicals holding a great promise for reducing animal experimentations on genotoxicity.

Assessing compound carcinogenicity in vitro using connectivity mapping

One of the main challenges of toxicology is the accurate prediction of compound carcinogenicity. The default test model for assessing chemical carcinogenicity, the 2 year rodent cancer bioassay, is currently criticized because of its limited specificity. With increased societal attention and new legislation against animal testing, toxicologists urgently need an alternative to the current rodent bioassays for chemical cancer risk assessment. Toxicogenomics approaches propose to use global high-throughput technologies (transcriptomics, proteomics and metabolomics) to study the toxic effect of compounds on a biological system. Here, we demonstrate the improvement of transcriptomics assay consisting of primary human hepatocytes to predict the putative liver carcinogenicity of several compounds by applying the connectivity map methodology. Our analyses underline that connectivity mapping is useful for predicting compound carcinogenicity by connecting in vivo expression profiles from human cancer tissue samples with in vitro toxicogenomics data sets. Furthermore, the importance of time and dose effect on carcinogenicity prediction is demonstrated, showing best prediction for low dose and 24 h exposure of potential carcinogens.

Performance of in vitro γH2AX assay in HepG2 cells to predict in vivo genotoxicity

The γH2AX assay has recently been suggested as a new in vitro assay for detecting genotoxic (GTX) properties of chemicals. This assay is based on the phosphorylation of H2AX histone in response to DNA damage [i.e. induction of double-strand breaks (DSBs)]. Quantification of γH2AX foci using flow cytometry can rapidly detect DNA damage induced by chemicals that cause DNA DSBs. Up to now, only few compounds have been tested with this assay. The main goal of this study was to compare the performance of this automated γH2AX assay with that of standard in vitro genotoxicity assays in predicting in vivo genotoxicity. HepG2 cells were exposed to 64 selected compounds with known GTX properties and subsequently analysed for induction of γH2AX foci. The results of this assay were compared with public data from standard in vitro genotoxicity tests. Accuracy, sensitivity and specificity in predicting in vivo genotoxicity, using the γH2AX assay alone or in combinations with conventional assays, were calculated. Both the γH2AX assay and the bacterial mutagenicity test (Ames) were highly specific for in vivo GTX, whereas chromosomal aberration/micronucleus test (CA/MN) resulted in highest sensitivity. The currently widely used in vitro genotoxicity test battery-Ames test, mouse lymphoma assay (MLA) and CA/MN test-resulted in low accuracy (55-65%) to predict in vivo genotoxicity. Interestingly, the inclusion of γH2AX assay in the standard battery, instead of MLA assay, resulted in higher accuracy (62-70%) compared with other combinations. Advantage of the γH2AX assay in HepG2 cells is its high sensitivity to detect DNA-reactive GTX compounds, although the reduced sensitivity for compounds that require metabolic activation needs to be improved. In conclusion, the automated γH2AX assay can be a useful, fast and cost-effective human cell-based tool for early screening of compounds for in vivo genotoxicity.

Air pollution-induced placental epigenetic alterations in early life: a candidate miRNA approach

ABSTRACT Particulate matter (PM) exposure during in utero life may entail adverse health outcomes in later-life. Air pollutions adverse effects are known to alter gene expression profiles, which can be regulated by microRNAs (miRNAs). We investigate the potential influence of air pollution exposure in prenatal life on placental miRNA expression. Within the framework of the ENVIRONAGE birth cohort, we measured the expression of six candidate miRNAs in placental tissue from 210 mother-newborn pairs by qRT-PCR. Trimester-specific PM2.5 exposure levels were estimated for each mothers home address using a spatiotemporal model. Multiple regression models were used to study miRNA expression and in utero exposure to PM2.5 over various time windows during pregnancy. The placental expression of miR-21 (−33.7%, 95% CI: −53.2 to −6.2, P = 0.022), miR-146a (−30.9%, 95% CI: −48.0 to −8.1, P = 0.012) and miR-222 (−25.4%, 95% CI: −43.0 to −2.4, P = 0.034) was inversely associated with PM2.5 exposure during the 2nd trimester of pregnancy, while placental expression of miR-20a and miR-21 was positively associated with 1st trimester exposure. Tumor suppressor phosphatase and tensin homolog (PTEN) was identified as a common target of the miRNAs significantly associated with PM exposure. Placental PTEN expression was strongly and positively associated (+59.6% per 5 µg/m³ increment, 95% CI: 26.9 to 100.7, P < 0.0001) with 3rd trimester PM2.5 exposure. Further research is required to establish the role these early miRNA and mRNA expression changes might play in PM-induced health effects. We provide molecular evidence showing that in utero PM2.5 exposure affects miRNAs expression as well as its downstream target PTEN.

Cohort Profile: The ENVIRonmental influence ON early AGEing (ENVIRONAGE): a birth cohort study

The ENVIRONAGE birth cohort is supported by the European Research Council [ERC-2012-StG.310898], and by funds of the Flemish Scientific Research council [FWO, G.0.733.15.N]. Bianca Cox, Janneke Hogervorst and Karen Vrijens have a postdoctoral fellowship from the Research Foundation - Flanders (FWO).

Sex-Specific Associations between Particulate Matter Exposure and Gene Expression in Independent Discovery and Validation Cohorts of Middle-Aged Men and Women.

Background: Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. Objectives: Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. Methods: Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM10 in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM2.5 and PM10 exposures over 2-years were estimated for each participant’s residential address using spatiotemporal interpolation in combination with a dispersion model. Results: Average long-term PM10 was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m3 in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM10 and the expression of individual genes differed by sex. In the validation cohort, long-term PM10 was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 (p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM10 in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM10 exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). Conclusions: Expression of the sex-specific candidate genes identified in the discovery population predicted PM10 exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects. Citation: Vrijens K, Winckelmans E, Tsamou M, Baeyens W, De Boever P, Jennen D, de Kok TM, Den Hond E, Lefebvre W, Plusquin M, Reynders H, Schoeters G, Van Larebeke N, Vanpoucke C, Kleinjans J, Nawrot TS. 2017. Sex-specific associations between particulate matter exposure and gene expression in independent discovery and validation cohorts of middle-aged men and women. Environ Health Perspect 125:660–669; http://dx.doi.org/10.1289/EHP370

Mother’s Pre-pregnancy BMI and Placental Candidate miRNAs: Findings from the ENVIR ON AGE Birth Cohort

There is increasing evidence that the predisposition for development of chronic diseases arises at the earliest times of life. In this context, maternal pre-pregnancy weight might modify fetal metabolism and the child’s predisposition to develop disease later in life. The aim of this study is to investigate the association between maternal pre-pregnancy body mass index (BMI) and miRNA alterations in placental tissue at birth. In 211 mother-newborn pairs from the ENVIRONAGE birth cohort, we assessed placental expression of seven miRNAs important in crucial cellular processes implicated in adipogenesis and/or obesity. Multiple linear regression models were used to address the associations between pre-pregnancy BMI and placental candidate miRNA expression. Maternal pre-pregnancy BMI averaged (±SD) 23.9 (±4.1) kg/m2. In newborn girls (not in boys) placental miR-20a, miR-34a and miR-222 expression was lower with higher maternal pre-pregnancy BMI. In addition, the association between maternal pre-pregnancy BMI and placental expression of these miRNAs in girls was modified by gestational weight gain. The lower expression of these miRNAs in placenta in association with pre-pregnancy BMI, was only evident in mothers with low weight gain (<14 kg). The placental expression of miR-20a, miR-34a, miR-146a, miR-210 and miR-222 may provide a sex-specific basis for epigenetic effects of pre-pregnancy BMI.

Author Correction: Mother’s Pre-pregnancy BMI and Placental Candidate miRNAs: Findings from the ENVIR ON AGE Birth Cohort

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Sex-specific associations between telomere length and candidate miRNA expression in placenta

BackgroundIn the early-life environment, proper development of the placenta is essential for both fetal and maternal health. Telomere length at birth has been related to life expectancy. MicroRNAs (miRNAs) as potential epigenetic determinants of telomere length at birth have not been identified. In this study, we investigate whether placental miRNA expression is associated with placental telomere length at birth.MethodsWe measured the expression of seven candidate miRNAs (miR-16-5p, -20a-5p, -21-5p, -34a-5p, 146a-5p, -210-3p and -222-3p) in placental tissue at birth in 203 mother-newborn (51.7% girls) pairs from the ENVIRONAGE birth cohort. We selected miRNAs known to be involved in crucial cellular processes such as inflammation, oxidative stress, cellular senescence related to aging. Placental miRNA expression and relative average placental telomere length were measured using RT-qPCR.ResultsBoth before and after adjustment for potential covariates including newborn’s ethnicity, gestational age, paternal age, maternal smoking status, maternal educational status, parity, date of delivery and outdoor temperature during the 3rd trimester of pregnancy, placental miR-34a, miR-146a, miR-210 and miR-222 expression were significantly (p ≤ 0.03) and positively associated with placental relative telomere length in newborn girls. In newborn boys, only higher expression of placental miR-21 was weakly (p = 0.08) associated with shorter placental telomere length. Significant miRNAs explain around 6–8% of the telomere length variance at birth.ConclusionsPlacental miR-21, miR-34a, miR-146a, miR-210 and miR-222 exhibit sex-specific associations with telomere length in placenta. Our results indicate miRNA expression in placental tissue could be an important determinant in the process of aging starting from early life onwards.

Placental miRNA expression in association with in utero particulate air pollution exposure

Background and aims Particulate matter exposure during in utero life may entail adverse health outcomes later in life. Epidemiological studies in adults have linked air pollution’s adverse effects to alterations in gene expression profiles, which can be regulated by epigenetic mechanisms, including microRNAs (miRNAs). MiRNAs have been implicated in diverse biological processes. We investigate the potential influence of air pollution exposure in early life on placental miRNA expression.