The ConsensusPathDB interaction database: 2013 update

Knowledge of the various interactions between molecules in the cell is crucial for understanding cellular processes in health and disease. Currently available interaction databases, being largely complementary to each other, must be integrated to obtain a comprehensive global map of the different types of interactions. We have previously reported the development of an integrative interaction database called ConsensusPathDB (http://ConsensusPathDB.org) that aims to fulfill this task. In this update article, we report its significant progress in terms of interaction content and web interface tools. ConsensusPathDB has grown mainly due to the integration of 12 further databases; it now contains 215 541 unique interactions and 4601 pathways from overall 30 databases. Binary protein interactions are scored with our confidence assessment tool, IntScore. The ConsensusPathDB web interface allows users to take advantage of these integrated interaction and pathway data in different contexts. Recent developments include pathway analysis of metabolite lists, visualization of functional gene/metabolite sets as overlap graphs, gene set analysis based on protein complexes and induced network modules analysis that connects a list of genes through various interaction types. To facilitate the interactive, visual interpretation of interaction and pathway data, we have re-implemented the graph visualization feature of ConsensusPathDB using the Cytoscape.js library

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 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

Epigenome-Wide Meta-Analysis of Methylation in Children Related to Prenatal NO2 Air Pollution Exposure

BACKGROUND: Prenatal exposure to air pollution is considered to be associated with adverse effects on child health. This may partly be mediated by mechanisms related to DNA methylation. OBJECTIVES: We investigated associations between exposure to air pollution, using nitrogen dioxide (NO2) as marker, and epigenome-wide cord blood DNA methylation. METHODS: We meta-analyzed the associations between NO2 exposure at residential addresses during pregnancy and cord blood DNA methylation (Illumina 450K) in four European and North American studies (n = 1,508) with subsequent look-up analyses in children ages 4 (n = 733) and 8 (n = 786) years. Additionally, we applied a literature-based candidate approach for antioxidant and anti-inflammatory genes. To assess influence of exposure at the transcriptomics level, we related mRNA expression in blood cells to NO2 exposure in 4- (n = 111) and 16-year-olds (n = 239). RESULTS: We found epigenome-wide significant associations [false discovery rate (FDR) p < 0.05] between maternal NO2 exposure during pregnancy and DNA methylation in newborns for 3 CpG sites in mitochondria-related genes: cg12283362 (LONP1), cg24172570 (3.8 kbp upstream of HIBADH), and cg08973675 (SLC25A28). The associations with cg08973675 methylation were also significant in the older children. Further analysis of antioxidant and anti-inflammatory genes revealed differentially methylated CpGs in CAT and TPO in newborns (FDR p < 0.05). NO2 exposure at the time of biosampling in childhood had a significant impact on CAT and TPO expression. CONCLUSIONS: NO2 exposure during pregnancy was associated with differential offspring DNA methylation in mitochondria-related genes. Exposure to NO2 was also linked to differential methylation as well as expression of genes involved in antioxidant defense pathways. Citation: Gruzieva O, Xu CJ, Breton CV, Annesi-Maesano I, Antó JM, Auffray C, Ballereau S, Bellander T, Bousquet J, Bustamante M, Charles MA, de Kluizenaar Y, den Dekker HT, Duijts L, Felix JF, Gehring U, Guxens M, Jaddoe VV, Jankipersadsing SA, Merid SK, Kere J, Kumar A, Lemonnier N, Lepeule J, Nystad W, Page CM, Panasevich S, Postma D, Slama R, Sunyer J, Söderhäll C, Yao J, London SJ, Pershagen G, Koppelman GH, Melén E. 2017. Epigenome-wide meta-analysis of methylation in children related to prenatal NO2 air pollution exposure. Environ Health Perspect 125:104-110; http://dx.doi.org/10.1289/EHP36