Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2x)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted

Comprehensive Gene-Expression Survey Identifies Wif1 as a Modulator of Cardiomyocyte Differentiation

During chicken cardiac development the proepicardium (PE) forms the epicardium (Epi), which contributes to several non-myocardial lineages within the heart. In contrast to Epi-explant cultures, PE explants can differentiate into a cardiomyocyte phenotype. By temporal microarray expression profiles of PE-explant cultures and maturing Epi cells, we identified genes specifically associated with differentiation towards either of these lineages and genes that are associated with the Epi-lineage restriction. We found a central role for Wnt signaling in the determination of the different cell lineages. Immunofluorescent staining after recombinant-protein incubation in PE-explant cultures indicated that the early upregulated Wnt inhibitory factor-1 (Wif1), stimulates cardiomyocyte differentiation in a similar manner as Wnt stimulation. Concordingly, in the mouse pluripotent embryogenic carcinoma cell line p19cl6, early and late Wif1 exposure enhances and attenuates differentiation, respectively. In ovo exposure of the HH12 chicken embryonic heart to Wif1 increases the Tbx18-positive cardiac progenitor pool. These data indicate that Wif1 enhances cardiomyogenesis

Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution

We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking

Refining Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Genetic Loci by Integrating Summary Data From Genome-wide Association, Gene Expression, and DNA Methylation Studies

Background: Recent genome-wide association studies (GWASs) identified the first genetic loci associated with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The next step is to use these results to increase our understanding of the biological mechanisms involved. Most of the identified variants likely influence gene regulation. The aim of the current study is to shed light on the mechanisms underlying the genetic signals and prioritize genes by integrating GWAS results with gene expression and DNA methylation (DNAm) levels. Methods: We applied summary-data–based Mendelian randomization to integrate ADHD and ASD GWAS data with fetal brain expression and methylation quantitative trait loci, given the early onset of these disorders. We also analyzed expression and methylation quantitative trait loci datasets of adult brain and blood, as these provide increased statistical power. We subsequently used summary-data–based Mendelian randomization to investigate if the same variant influences both DNAm and gene expression levels. Results: We identified multiple gene expression and DNAm levels in fetal brain at chromosomes 1 and 17 that were associated with ADHD and ASD, respectively, through pleiotropy at shared genetic variants. The analyses in brain and blood showed additional associated gene expression and DNAm levels at the same and additional loci, likely because of increased statistical power. Several of the associated genes have not been identified in ADHD and ASD GWASs before. Conclusions: Our findings identified the genetic variants associated with ADHD and ASD that likely act through gene regulation. This facilitates prioritization of candidate genes for functional follow-up studies

DNA methylation signatures of aggression and closely related constructs : A meta-analysis of epigenome-wide studies across the lifespan

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 x 10(-7); Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.Peer reviewe

Blood Transcriptome Profiling Links Immunity to Disease Severity in Myotonic Dystrophy Type 1 (DM1)

The blood transcriptome was examined in relation to disease severity in type I myotonic dystrophy (DM1) patients who participated in the Observational Prolonged Trial In DM1 to Improve QoL- Standards (OPTIMISTIC) study. This sought to (a) ascertain if transcriptome changes were associated with increasing disease severity, as measured by the muscle impairment rating scale (MIRS), and (b) establish if these changes in mRNA expression and associated biological pathways were also observed in the Dystrophia Myotonica Biomarker Discovery Initiative (DMBDI) microarray dataset in blood (with equivalent MIRS/DMPK repeat length). The changes in gene expression were compared using a number of complementary pathways, gene ontology and upstream regulator analyses, which suggested that symptom severity in DM1 was linked to transcriptomic alterations in innate and adaptive immunity associated with muscle-wasting. Future studies should explore the role of immunity in DM1 in more detail to assess its relevance to DM1

RD-Connect: An Integrated Platform Connecting Databases, Registries, Biobanks and Clinical Bioinformatics for Rare Disease Research

International audienceResearch into rare diseases is typically fragmented by data type and disease. Individual efforts often have poor interoperability and do not systematically connect data across clinical phenotype, genomic data, biomaterial availability, and research/trial data sets. Such data must be linked at both an individual-patient and whole-cohort level to enable researchers to gain a complete view of their disease and patient population of interest. Data access and authorization procedures are required to allow researchers in multiple institutions to securely compare results and gain new insights. Funded by the European Union's Seventh Framework Programme under the International Rare Diseases Research Consortium (IRDiRC), RD-Connect is a global infrastructure project initiated in November 2012 that links genomic data with registries, biobanks, and clinical bioinformatics tools to produce a central research resource for rare diseases

Selection of effective antisense oligodeoxynucleotides with a green fluorescent protein-based assay. Discovery of selective and potent inhibitors of glutathione S-transferase Mu expression

Antisense oligodeoxynucleotides (AS-ODNs) are frequently used for the down-regulation of protein expression. Because the majority of potential antisense sequences lacks effectiveness, fast screening methods for the selection of effective AS-ODNs are needed. We describe a new cellular screening assay for the evaluation of the potency and specificity of new antisense sequences. Fusion constructs of the gene of interest and the gene encoding the enhanced green fluorescent protein (EGFP) are cotransfected with AS-ODNs to COS-7 cells. Subsequently, cells are analysed for expression of the EGFP fusion protein by flow cytometry. With the assay, we tested the effectiveness of a set of 15 phosphorothioate ODNs against rat glutathione S-transferase Mu1 (GSTM1) and/or Mu2 (GSTM2). We found several AS-ODNs that demonstrated potent, sequence-specific, and concentration-dependent inhibition of fusion protein expression. At 0.5 microm, AS-6 and AS-8 inhibited EGFP-GSTM1 expression by 95 +/- 4% and 81 +/- 6%, respectively. AS-5 and AS-10 were selective for GSTM2 (82 +/- 4% and 85 +/- 0.4% decrease, respectively). AS-2 and AS-3, targeted at homologous regions in GSTM1 and GSTM2, inhibited both isoforms (77-95% decrease). Other AS-ODNs were not effective or displayed non-target-specific inhibition of protein expression. The observed decrease in EGFP expression was accompanied by a decrease in GSTM enzyme activity. As isoform-selective, chemical inhibitors of GSTM and GSTM knock-out mice are presently unavailable, the selected AS-ODNs constitute important tools for the study of the role of GSTM in detoxification of xenobiotics and protection against chemical-induced carcinogenesis

Blood Transcriptome Profiling Links Immunity to Disease Severity in Myotonic Dystrophy Type 1 (DM1)

The blood transcriptome was examined in relation to disease severity in type I myotonic dystrophy (DM1) patients who participated in the Observational Prolonged Trial In DM1 to Improve QoL- Standards (OPTIMISTIC) study. This sought to (a) ascertain if transcriptome changes were associated with increasing disease severity, as measured by the muscle impairment rating scale (MIRS), and (b) establish if these changes in mRNA expression and associated biological pathways were also observed in the Dystrophia Myotonica Biomarker Discovery Initiative (DMBDI) microarray dataset in blood (with equivalent MIRS/DMPK repeat length). The changes in gene expression were compared using a number of complementary pathways, gene ontology and upstream regulator analyses, which suggested that symptom severity in DM1 was linked to transcriptomic alterations in innate and adaptive immunity associated with muscle-wasting. Future studies should explore the role of immunity in DM1 in more detail to assess its relevance to DM1