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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 (2×)) 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.

Insights into individual differences in gene expression and its heritability (h2) can help in understanding pathways from DNA to phenotype. We estimated the heritability of gene expression of 52,844 genes measured in whole blood in the largest twin RNA-Seq sample to date (1497 individuals including 459 monozygotic twin pairs and 150 dizygotic twin pairs) from classical twin modeling and identity-by-state-based approaches. We estimated for each gene h2total, composed of cis-heritability (h2cis, the variance explained by single nucleotide polymorphisms in the cis-window of the gene), and trans-heritability (h2res, the residual variance explained by all other genome-wide variants). Mean h2total was 0.26, which was significantly higher than heritability estimates earlier found in a microarray-based study using largely overlapping (>60%) RNA samples (mean h2 = 0.14, p = 6.15 × 10−258). Mean h2cis was 0.06 and strongly correlated with beta of the top cis expression quantitative loci (eQTL, ρ = 0.76, p −308) and with estimates from earlier RNA-Seq-based studies. Mean h2res was 0.20 and correlated with the beta of the corresponding trans-eQTL (ρ = 0.04, p −3) and was significantly higher for genes involved in cytokine-cytokine interactions (p = 4.22 × 10−15), many other immune system pathways, and genes identified in genome-wide association studies for various traits including behavioral disorders and cancer. This study provides a thorough characterization of cis- and trans-h2 estimates of gene expression, which is of value for interpretation of GWAS and gene expression studies.

Background Cells can be primed by external stimuli to obtain a long-term epigenetic memory. We hypothesize that long-term exposure to elevated blood lipids can prime circulating immune cells through changes in DNA methylation, a process that may contribute to the development of atherosclerosis. To interrogate the causal relationship between triglyceride, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol levels and genome-wide DNA methylation while excluding confounding and pleiotropy, we perform a stepwise Mendelian randomization analysis in whole blood of 3296 individuals. Results This analysis shows that differential methylation is the consequence of inter-individual variation in blood lipid levels and not vice versa. Specifically, we observe an effect of triglycerides on DNA methylation at three CpGs, of LDL cholesterol at one CpG, and of HDL cholesterol at two CpGs using multivariable Mendelian randomization. Using RNA-seq data available for a large subset of individuals (N = 2044), DNA methylation of these six CpGs is associated with the expression of CPT1A and SREBF1 (for triglycerides), DHCR24 (for LDL cholesterol) and ABCG1 (for HDL cholesterol), which are all key regulators of lipid metabolism. Conclusions Our analysis suggests a role for epigenetic priming in end-product feedback control of lipid metabolism and highlights Mendelian randomization as an effective tool to infer causal relationships in integrative genomics data. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1000-6) contains supplementary material, which is available to authorized users.

Aggressive behavior is highly heritable, while environmental influences, particularly early in life, are also important. Epigenetic mechanisms, such as DNA methylation, regulate gene expression throughout development and adulthood, and may mediate genetic and environmental effects on complex traits. We performed an epigenome-wide association study (EWAS) to identify regions in the genome where DNA methylation level is associated with aggressive behavior. Subjects took part in longitudinal survey studies from the Netherlands Twin Register (NTR) and participated in the NTR biobank project between 2004 and 2011 (N = 2,029, mean age at blood sampling = 36.4 years, SD = 12.4, females = 69.2%). Aggressive behavior was rated with the ASEBA Adult Self-Report (ASR). DNA methylation was measured in whole blood by the Illumina HM450k array. The association between aggressive behavior and DNA methylation level at 411,169 autosomal sites was tested. Association analyses in the entire cohort showed top sites at cg01792876 (chr8; 116,684,801, nearest gene = TRPS1, p = 7.6 × 10−7, False discovery rate (FDR) = 0.18) and cg06092953 (chr18; 77,905,699, nearest gene = PARD6G-AS1, p = 9.0 ×10−7, FDR = 0.18). Next, we compared methylation levels in 20 pairs of monozygotic (MZ) twins highly discordant for aggression. Here the top sites were cg21557159 (chr 11; 107,795,699, nearest gene = RAB39, p = 5.7 × 10−6, FDR = 0.99), cg08648367 (chr 19; 51,925,472, nearest gene = SIGLEC10, p = 7.6 × 10−6, FDR = 0.99), and cg14212412 (chr 6; 105,918,992, nearest gene = PREP, p = 8.0 × 10−6, FDR = 0.99). The two top hits based on the entire cohort showed the same direction of effect in discordant MZ pairs (cg01792876, Pdiscordant twins = 0.09 and cg06092953, Pdiscordant twins = 0.24). The other way around, two of the three most significant sites in discordant MZ pairs showed the same direction of effect in the entire cohort (cg08648367, Pentire EWAS = 0.59 and cg14212412, Pentire EWAS = 3.1 × 10−3). Gene ontology analysis highlighted significant enrichment of various central nervous system categories among higher-ranking methylation sites. Higher-ranking methylation sites also showed enrichment for DNase I hypersensitive sites and promoter regions, showing that DNA methylation in peripheral tissues is likely to be associated with aggressive behavior.

Background— Estimates of the heritability of plasma fibrinogen concentration, an established predictor of cardiovascular disease, range from 34% to 50%. Genetic variants so far identified by genome-wide association studies explain only a small proportion ( Methods and Results— We conducted a meta-analysis of 28 genome-wide association studies including >90 000 subjects of European ancestry, the first genome-wide association meta-analysis of fibrinogen levels in 7 studies in blacks totaling 8289 samples, and a genome-wide association study in Hispanics totaling 1366 samples. Evaluation for association of single-nucleotide polymorphisms with clinical outcomes included a total of 40 695 cases and 85 582 controls for coronary artery disease, 4752 cases and 24 030 controls for stroke, and 3208 cases and 46 167 controls for venous thromboembolism. Overall, we identified 24 genome-wide significant ( P −8 ) independent signals in 23 loci, including 15 novel associations, together accounting for 3.7% of plasma fibrinogen variation. Gene-set enrichment analysis highlighted key roles in fibrinogen regulation for the 3 structural fibrinogen genes and pathways related to inflammation, adipocytokines, and thyrotrophin-releasing hormone signaling. Whereas lead single-nucleotide polymorphisms in a few loci were significantly associated with coronary artery disease, the combined effect of all 24 fibrinogen-associated lead single-nucleotide polymorphisms was not significant for coronary artery disease, stroke, or venous thromboembolism. Conclusions— We identify 23 robustly associated fibrinogen loci, 15 of which are new. Clinical outcome analysis of these loci does not support a causal relationship between circulating levels of fibrinogen and coronary artery disease, stroke, or venous thromboembolism.