Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the fi

Endotoxin Exposure In Sewage Treatment Workers: Investigation Of Exposure Variability And Comparison Of Analytical Techniques

Introduction: Objectives were to give an overview of endotoxin exposure and its determinants in sewage treatment workers, and to study exposure to culturable and non-culturable microorganisms and the applicability of the LAL assay in this work environment. Material and methods: In 43 Dutch sewage treatment plants 470 full-shift, 123 task-based personal and 54 stationary inhalable dust samples were collected. Endotoxin concentration was determined with the LAL-assay. Mixed effects models were used to investigate possible determinants of exposure. Simultaneous parallel filter Samples, impinger samples and viable total bacteria and Gram-negative bacterial samples were taken to compare analytical techniques. Filter and impinger samples were analyzed with the LAL-assay, gas chromatography-mass spectrometry (GC-MS) and fluorescence microscopy. Results: Endotoxin exposure levels were moderate to low (geometric mean personal exposure 27 EU/m(3), stationary 33 EU/m(3), task-based 64 EU/m(3)), yet differences between jobs and sources and some determinants of exposure were identified. Exposure varied more from day to day than between workers. Concentrations in filter samples were higher and more consistent than in impinger samples. Fungi and Gram-positive bacteria were found in higher levels than Gram-negative bacteria. The LAL assay and GC-MS showed comparable endotoxin levels. Discussion and conclusion: Endotoxin exposure in Dutch sewage treatment workers was relatively low,. Comparison of sampling and analytical techniques suggests that the LAL-assay did not result in much exposure misclassification. It thus seems justified to perform filter measurements in combination with the LAL-assay to measure endotoxin exposure in sewage treatment plants

Sex-specific and age-specific incidence of ischaemic heart disease, atrial fibrillation and heart failure in community patients with chronic obstructive pulmonary disease

OBJECTIVE: To estimate the incidence of ischaemic heart disease, atrial fibrillation and heart failure in community patients with or without chronic obstructive pulmonary disease (COPD). METHODS: For this population-based study, we used primary care data of the Julius General Practitioners' Network. Eligible participants were aged 40-80 years old and contributed data between January 2014 and February 2019. Participants were divided into groups according to COPD status and were followed up for new ischaemic heart disease, atrial fibrillation and/or heart failure. Age-specific and sex-specific incidence and incidence rate ratios were calculated for patients with and without COPD. RESULTS: Mean follow-up was 3.9 years, 6223 patients were included in the COPD group, and 137 028 individuals in the background group without COPD. Incidence rates of all three heart diseases increased with age and were higher in males, independent of presence of COPD. Incidence rate ratios for patients with COPD, adjusted for age and sex, were 1.69 (95% CI 1.49 to 1.92) for ischaemic heart disease, 1.56 (95% CI 1.38 to 1.77) for atrial fibrillation and 2.96 (95% CI 2.58 to 3.40) for heart failure. CONCLUSION: The incidence of all major cardiovascular diseases is higher in patients with COPD, with the highest incidence rate ratio observed for heart failure

'4D Biology for health and disease' workshop report

The "4D Biology Workshop for Health and Disease", held on 16-17th of March 2010 in Brussels, aimed at finding the best organising principles for large-scale proteomics, interactomics and structural genomics/biology initiatives, and setting the vision for future high-throughput research and large-scale data gathering in biological and medical science. Major conclusions of the workshop include the following. (i) Development of new technologies and approaches to data analysis is crucial. Biophysical methods should be developed that span a broad range of time/spatial resolution and characterise structures and kinetics of interactions. Mathematics, physics, computational and engineering tools need to be used more in biology and new tools need to be developed. (ii) Database efforts need to focus on improved definitions of ontologies and standards so that system-scale data and associated metadata can be understood and shared efficiently. (iii) Research infrastructures should play a key role in fostering multidisciplinary research, maximising knowledge exchange between disciplines and facilitating access to diverse technologies. (iv) Understanding disease on a molecular level is crucial. System approaches may represent a new paradigm in the search for biomarkers and new targets in human disease. (v) Appropriate education and training should be provided to help efficient exchange of knowledge between theoreticians, experimental biologists and clinicians. These conclusions provide a strong basis for creating major possibilities in advancing research and clinical applications towards personalised medicine

The impact of low-frequency and rare variants on lipid levels

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated

The impact of low-frequency and rare variants on lipid levels

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing

The impact of low-frequency and rare variants on lipid levels.

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing