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

Non-homologous end-joining pathway associated with occurrence of myocardial infarction: gene set analysis of genome-wide association study data

<p>Purpose: DNA repair deficiencies have been postulated to play a role in the development and progression of cardiovascular disease (CVD). The hypothesis is that DNA damage accumulating with age may induce cell death, which promotes formation of unstable plaques. Defects in DNA repair mechanisms may therefore increase the risk of CVD events. We examined whether the joints effect of common genetic variants in 5 DNA repair pathways may influence the risk of CVD events.</p> <p>Methods: The PLINK set-based test was used to examine the association to myocardial infarction (MI) of the DNA repair pathway in GWAS data of 866 subjects of the GENetic DEterminants of Restenosis (GENDER) study and 5,244 subjects of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) study. We included the main DNA repair pathways (base excision repair, nucleotide excision repair, mismatch repair, homologous recombination and non-homologous end-joining (NHEJ)) in the analysis.</p> <p>Results: The NHEJ pathway was associated with the occurrence of MI in both GENDER (P = 0.0083) and PROSPER (P = 0.014). This association was mainly driven by genetic variation in the MRE11A gene (PGENDER = 0.0001 and PPROSPER = 0.002). The homologous recombination pathway was associated with MI in GENDER only (P = 0.011), for the other pathways no associations were observed.</p> <p>Conclusion: This is the first study analyzing the joint effect of common genetic variation in DNA repair pathways and the risk of CVD events, demonstrating an association between the NHEJ pathway and MI in 2 different cohorts.</p&gt

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

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

Attributable mortality of antibiotic resistance in Gram-negative infections in the Netherlands: a parallel matched cohort study

Objectives: Antibiotic resistance in Gram-negative bacteria has been associated with increased mortality. This was demonstrated mostly for third-generation cephalosporin-resistant (3GC-R) Enterobacterales bacteraemia in international studies. Yet, the burden of resistance specifically in the Netherlands and created by all types of Gram-negative infection has not been quantified. We therefore investigated the attributable mortality of antibiotic resistance in Gram-negative infections in the Netherlands. Methods: In eight hospitals, a sample of Gram-negative infections was identified between 2013 and 2016, and separated into resistant and susceptible infection cohorts. Both cohorts were matched 1:1 to non-infected control patients on hospital, length of stay at infection onset, and age. In this parallel matched cohort set-up, 30-day mortality was compared between infected and non-infected patients. The impact of resistance was then assessed by dividing the two separate risk ratios (RRs) for mortality attributable to Gram-negative infection. Results: We identified 1954 Gram-negative infections, of which 1190 (61%) involved Escherichia coli, 210 (11%) Pseudomonas aeruginosa, and 758 (39%) bacteraemia. Resistant Gram-negatives caused 243 infections (12%; 189 (78%) 3GC-R Enterobacterales, nine (4%) multidrug-resistant P. aeruginosa, no carbapenemase-producing Enterobacterales). Subsequently, we matched 1941 non-infected controls. After adjustment, point estimates for RRs comparing mortality between infections and controls were similarly higher than 1 in case of resistant infections and susceptible infections (1.42 (95% confidence interval 0.66–3.09) and 1.32 (1.06–1.65), respectively). By dividing these, the RR reflecting attributable mortality of resistance was calculated as 1.08 (0.48–2.41). Conclusions: In the Netherlands, antibiotic resistance did not increase 30-day mortality in Gram-negative infections

Short-course aminoglycosides as adjunctive empirical therapy in patients with Gram-negative bloodstream infection, a cohort study

Objective: Short-course aminoglycosides as adjunctive empirical therapy to β-lactams in patients with a clinical suspicion of sepsis are used to broaden antibiotic susceptibility coverage and to enhance bacterial killing. We quantified the impact of this approach on 30-day mortality in a subset of sepsis patients with a Gram-negative bloodstream infection. Methods: From a prospective cohort study conducted in seven hospitals in the Netherlands between June 2013 and November 2015, we selected all patients with Gram-negative bloodstream infection (GN-BSI). Short-course aminoglycoside therapy was defined as tobramycin, gentamicin or amikacin initiated within a 48-hour time window around blood-culture obtainment, and prescribed for a maximum of 2 days. The outcome of interest was 30-day all-cause mortality. Confounders were selected a priori for adjustment using a propensity score analysis with inverse probability weighting. Results: A total of 626 individuals with GN-BSI who received β-lactams were included; 156 (24.9%) also received aminoglycosides for a median of 1 day. Patients receiving aminoglycosides more often had septic shock (31/156, 19.9% versus 34/470, 7.2%) and had an eight-fold lower risk of inappropriate treatment (3/156, 1.9% versus 69/470, 14.7%). Thirty-day mortality was 17.3% (27/156) and 13.6% (64/470) for patients receiving and not receiving aminoglycosides, respectively; yielding crude and adjusted odds ratios for 30-day mortality for patients treated with aminoglycosides of 1.33 (95% CI 0.80–2.15) and 1.57 (0.84–2.93), respectively. Conclusions: Short-course adjunctive aminoglycoside treatment as part of empirical therapy with β-lactam antibiotics in patients with GN-BSI did not result in improved outcomes, despite better antibiotic coverage of pathogens

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

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

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes