20 research outputs found

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

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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 (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

    Impact of donor lung quality on post-transplant recipient outcome in the Lung Allocation Score era in Eurotransplant - a historical prospective study

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    The aim of this study was to investigate whether there is an impact of donation rates on the quality of lungs used for transplantation and whether donor lung quality affects post-transplant outcome in the current LAS era. All consecutive adult LTx performed in Eurotransplant (ET) between January 2012 and December 2016 were included (N=3053). Donors used for LTx in countries with high donation rate were younger (42% vs. 33% ≤ 45 years, p<0.0001), were less often smokers (35% vs. 46%, p<0.0001), had more often clear chest X-rays (82% vs. 72%, p<0.0001), had better donor oxygenation ratio's (20% vs. 26% with PaO /FiO ≤ 300 mmHg, p<0.0001) and had better lung donor score values (LDS) (28% vs. 17% with LDS=6, p<0.0001) compared to donors used for LTx in countries with low donation rate. Survival rates for the groups LDS =6 and ≥7 at 5 years were 69.7% and 60.9% (p=0.007). Lung donor quality significantly impacts on long-term patient survival. Countries with a low donation rate are more oriented to using donor lungs with a lesser quality compared to countries with a high donation rate. Instead of further stretching donor eligibility criteria, the full potential of the donor pool should be realized

    Impact of donor lung quality on post-transplant recipient outcome in the Lung Allocation Score era in Eurotransplant – a historical prospective study

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    The aim of this study was to investigate whether there is an impact of donation rates on the quality of lungs used for transplantation and whether donor lung quality affects post-transplant outcome in the current Lung Allocation Score era. All consecutive adult LTx performed in Eurotransplant (ET) between January 2012 and December 2016 were included (N = 3053). Donors used for LTx in countries with high donation rate were younger (42% vs. 33% ≤45 years, P < 0.0001), were less often smokers (35% vs. 46%, P < 0.0001), had more often clear chest X-rays (82% vs. 72%, P < 0.0001), had better donor oxygenation ratios (20% vs. 26% with PaO2/FiO2 ≤ 300 mmHg, P < 0.0001), and had better lung donor score values (LDS; 28% vs. 17% with LDS = 6, P < 0.0001) compared with donors used for LTx in countries with low donation rate. Survival rates for the groups LDS = 6 and ≥7 at 5 years were 69.7% and 60.9% (P = 0.007). Lung donor quality significantly impacts on long-term patient survival. Countries with a low donation rate are more oriented to using donor lungs with a lesser quality compared to countries with a high donation rate. Instead of further stretching donor eligibility criteria, the full potential of the donor pool should be realized

    Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

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    Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits

    Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

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    Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

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    Background: DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes that affect DNA methylation patterns in blood using large-scale population genomics data. Results: By employing genetic instruments as causal anchors, we establish directed associations between gene expression and distant DNA methylation levels, while ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. The identified genes are enriched for transcription factors, of which many consistently increased or decreased DNA methylation levels at multiple CpG sites. In addition, we show that a substantial number of transcription factors affected DNA methylation at their experimentally determined binding sites. We also observe genes encoding proteins with heterogenous functions that have widespread effects on DNA methylation, e.g., NFKBIE, CDCA7(L), and NLRC5, and for several examples, we suggest plausible mechanisms underlying their effect on DNA methylation. Conclusion: We report hundreds of genes that affect DNA methylation and provide key insights in the principles underlying epigenetic regulation
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