28 research outputs found

    A Co-expression Analysis of the Placental Transcriptome in Association With Maternal Pre-pregnancy BMI and Newborn Birth Weight

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    Maternal body mass index (BMI) before pregnancy is known to affect both fetal growth and later-life health of the newborn, yet the implicated molecular mechanisms remain largely unknown. As the master regulator of the fetal environment, the placenta is a valuable resource for the investigation of processes involved in the developmental programming of metabolic health. We conducted a genome-wide placental transcriptome study aiming at the identification of functional pathways representing the molecular link between maternal BMI and fetal growth. We used RNA microarray (Agilent 8 × 60 K), medical records, and questionnaire data from 183 mother-newborn pairs from the ENVIRONAGE birth cohort study (Flanders, Belgium). Using a weighted gene co-expression network analysis, we identified 17 correlated gene modules. Three of these modules were associated with both maternal pre-pregnancy BMI and newborn birth weight. A gene cluster enriched for genes involved in immune response and myeloid cell differentiation was positively associated with maternal BMI and negatively with low birth weight. Two other gene modules, upregulated in association with maternal BMI as well as birth weight, were involved in processes related to organ and tissue development, with blood vessel morphogenesis and extracellular matrix structure as top Gene Ontology terms. In line with this, erythrocyte-, angiogenesis-, and extracellular matrix-related genes were among the identified hub genes. The association between maternal BMI and newborn weight was significantly mediated by gene expression for 5 of the hub genes (FZD4, COL15A1, GPR124, COL6A1, and COL1A1). As some of the identified hub genes have been linked to obesity in adults, our observation in placental tissue suggests that biological processes may be affected from prenatal life onwards, thereby identifying new molecular processes linking maternal BMI and fetal metabolic programming

    Sex-specific associations between particulate matter exposure and gene expression in independent discovery and validation cohorts of middle-aged men and women

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    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 PM(10) 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 PM(2.5) and PM(10) 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 PM(10) was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m(3) in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM(10) and the expression of individual genes differed by sex. In the validation cohort, long-term PM(10) 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 PM(10) 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 PM(10) 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 PM(10) 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/EHP37

    Genome-wide microRNA expression analysis in human placenta reveals sex-specific patterns:an ENVIRONAGE birth cohort study

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    There is an increasing interest in microRNAs (miRNAs) as they are of utmost importance in gene regulation at the posttranscriptional level. Sex-related susceptibility for non-communicable diseases later in life could originate in early life. Until now, no data on sex-specific miRNA expression are available for the placenta. Therefore, we investigated the difference by sex of newborn's miRNA expression in human placental tissue. Within the ENVIRONAGE birth cohort, miRNA and mRNA expression profiling was performed in 60 placentae (50% boys) using Agilent (8 x 60 K) microarrays. The distribution of chromosome locations was studied and pathway analysis of the identified sex-specific miRNAs in the placenta was carried out. Of the total 2558 miRNAs on the array, 597 miRNAs were expressed in over 70% of the samples and were included for further analyses. A total of 142 miRNAs were significantly (FD

    Genome-wide microRNA expression analysis in human placenta reveals sex-specific patterns: an ENVIR ON

    No full text
    There is an increasing interest in microRNAs (miRNAs) as they are of utmost importance in gene regulation at the posttranscriptional level. Sex-related susceptibility for non-communicable diseases later in life could originate in early life. Until now, no data on sex-specific miRNA expression are available for the placenta. Therefore, we investigated the difference by sex of newborn's miRNA expression in human placental tissue. Within the ENVIRONAGE birth cohort, miRNA and mRNA expression profiling was performed in 60 placentae (50% boys) using Agilent (8 x 60 K) microarrays. The distribution of chromosome locations was studied and pathway analysis of the identified sex-specific miRNAs in the placenta was carried out. Of the total 2558 miRNAs on the array, 597 miRNAs were expressed in over 70% of the samples and were included for further analyses. A total of 142 miRNAs were significantly (FD

    A Co-expression Analysis of the Placental Transcriptome in Association With Maternal Pre-pregnancy BMI and Newborn Birth Weight

    No full text
    Maternal body mass index (BMI) before pregnancy is known to affect both fetal growth and later-life health of the newborn, yet the implicated molecular mechanisms remain largely unknown. As the master regulator of the fetal environment, the placenta is a valuable resource for the investigation of processes involved in the developmental programming of metabolic health. We conducted a genome-wide placental transcriptome study aiming at the identification of functional pathways representing the molecular link between maternal BMI and fetal growth. We used RNA microarray (Agilent 8 × 60 K), medical records, and questionnaire data from 183 mother-newborn pairs from the ENVIRONAGE birth cohort study (Flanders, Belgium). Using a weighted gene co-expression network analysis, we identified 17 correlated gene modules. Three of these modules were associated with both maternal pre-pregnancy BMI and newborn birth weight. A gene cluster enriched for genes involved in immune response and myeloid cell differentiation was positively associated with maternal BMI and negatively with low birth weight. Two other gene modules, upregulated in association with maternal BMI as well as birth weight, were involved in processes related to organ and tissue development, with blood vessel morphogenesis and extracellular matrix structure as top Gene Ontology terms. In line with this, erythrocyte-, angiogenesis-, and extracellular matrix-related genes were among the identified hub genes. The association between maternal BMI and newborn weight was significantly mediated by gene expression for 5 of the hub genes (FZD4, COL15A1, GPR124, COL6A1, and COL1A1). As some of the identified hub genes have been linked to obesity in adults, our observation in placental tissue suggests that biological processes may be affected from prenatal life onwards, thereby identifying new molecular processes linking maternal BMI and fetal metabolic programming.status: publishe

    In vitro data combined with human disease data to improve toxicological hazard assessment: the ASAT Knowledge Base

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    In line with the Assuring Safety Without Animal Testing (ASAT) principle, risk assessment may ultimately become feasible without the use of animals (Fentem et al., 2004). ASAT assumes that activation of human disease mechanisms in in vitro models can be used for toxicological assessment. Therefore, goal of the present research was to demonstrate the integration of public data from the human disease domain with in vitro toxicology. Two diseases, associated with chemical exposure, were concerned: hepatocellular carcinoma and allergic contact dermatitis (ACD). Data were retrieved from online sources (e.g., GEO, CTD) and expert knowledge. A Knowledge Base for curation, storage and modelling of the data was developed. Using the Knowledge Base for ACD, it was possible to discern sensitizing from non-sensitizing chemicals, as defined by enrichment of disease gene sets in in vitro toxicogenomics datasets. Interestingly, the strongest sensitizers most profoundly activated these gene sets. The ongoing incorporation of (reverse) PBPK models in the Knowledge Base to judge the relevance of in vitro concentrations, in relation to realistic in vivo exposure scenarios, will be presented. Finally, the expansion with models towards other disease areas (cholestasis) will be discussed
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