347 research outputs found
Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits
No full text<p><strong>Introduction</strong></p>
<p>These are the <em>Summary Level-data</em> as presented in:</p>
<p>"Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits". Eur J Hum Genet. 2019 Jan 24. doi: 10.1038/s41431-018-0295-z.<em> [Epub ahead of print]</em></p>
<p>If you use these data please cite the corresponding manuscript, which can be downloaded here: <a href="http://em.rdcu.be/wf/click?upn=lMZy1lernSJ7apc5DgYM8eFz0euOx0-2B13Abimi4Sb0A-3D_2NNavOiAD9A7CPFnsa04dGla3sU002fLfkDtL-2FhGlad0GuoM-2B3OlDb0C5GiEhwIvtH7ba4KKF45ipTOFodx6CqvVvoP2GQ992sPGoV9ZPWIe04tUd8-2BGWey0In0TXPII5zK-2Bfp8Wk9TpEqEcSd-2BEmywqZc8o5TW4xGPXZqmchfUH8chy3P4SEtpzHXMG1LwsIYrKfwegqTXG85RAJPr-2B21Tk9SobtpvFs0frMkJ4ekKsl33ryoZfFPk1byjQunJYn4-2BB0iqMgGs6cXv0AOgAxg-3D-3D">https://rdcu.be/bh8mu</a>. When you have any questions or comments regarding this study or these files, please contact me via:</p>
<p>Jessica van Setten, PhD | <em>Department of Cardiology, University Medical Center Utrecht, Utrecht University</em> | j.vansetten [at] umcutrecht [dot] nl</p>
<p> </p>
<p><strong>Files and description</strong></p>
<p>There are four files available:</p>
<ol>
<li>RR_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for RR interval</li>
<li>PR_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for PR interval</li>
<li>QT_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for QT interval</li>
<li>QRS_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for QRS duration</li>
</ol>
<p>All these files have the same lay-out and are gzipped. The reference used for meta-analysis of GWAS was Genome of the Netherlands v4. </p>
<ul>
<li><em>SNP</em> - variantID (rsID), please note that few hundred variants do not have an rsID, but are NA instead. These can still be identified by chromosome and position.</li>
<li><em>CHR</em> - chromosome numbers [1-22 and X].</li>
<li><em>POS</em> - base pair position, hg19 / build37.</li>
<li><em>CODED_ALLELE</em> - coded allele, <em>i.e.</em> the effect allele, as represented (and harmonized) across cohorts. Note that this is not necessarily the minor allele.</li>
<li><em>NON_CODED_ALLELE</em> - the other allele, <em>i.e.</em> the non-effect allele.</li>
<li><em>CODED_ALLELE_FREQ</em> - coded allele frequency, <em>i.e.</em> the effect allele frequency. Note that this is not necessarily the minor allele frequency.</li>
<li><em>BETA</em> - beta from the fixed-effects model.</li>
<li><em>SE </em>- standard error from the fixed-effects model.</li>
<li><em>P </em>- P-value from the fixed-effects model.</li>
<li><em>NEAREST_GENE</em> - the gene closest to the respective variant.</li>
</ul>
<p> </p>
PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity
No full text<p><strong>Introduction</strong></p>
<p>These are the <em>Summary Level-data</em> as presented in:</p>
<p>"PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity". <em>Nature Communications </em>volume 9, Article number: 2904 (2018) doi: 10.1038/s41467-018-04766-9 </p>
<p>If you use these data please cite the corresponding manuscript, which can be downloaded here: https://www.nature.com/articles/s41467-018-04766-9. When you have any questions or comments regarding this study or these files, please contact me via:</p>
<p>Jessica van Setten, PhD | <em>Department of Cardiology, University Medical Center Utrecht, Utrecht University</em> | j.vansetten [at] umcutrecht [dot] nl</p>
<p> </p>
<p><strong>Files and description</strong></p>
<p>The file PR_interval_July2018_summary_results.txt is gzipped and contains the PR interval GWAS meta-analysis summary results of 92,000 European samples. The imputation reference panel used for most studies was HapMap2 (please note: hg18, build36). </p>
<ul>
<li><em>SNP</em> - variantID (rsID).</li>
<li><em>CHR</em> - chromosome numbers [1-22 and X].</li>
<li><em>POS</em> - base pair position, hg18 / build36.</li>
<li><em>CODED_ALLELE</em> - coded allele, <em>i.e.</em> the effect allele, as represented (and harmonized) across cohorts. Note that this is not necessarily the minor allele.</li>
<li><em>NON_CODED_ALLELE</em> - the other allele, <em>i.e.</em> the non-effect allele.</li>
<li><em>CODED_ALLELE_FREQ</em> - coded allele frequency, <em>i.e.</em> the effect allele frequency. Note that this is not necessarily the minor allele frequency.</li>
<li><em>BETA_FIXED</em> - beta from the fixed-effects model.</li>
<li><em>SE_FIXED </em>- standard error from the fixed-effects model.</li>
<li><em>P_FIXED </em>- P-value from the fixed-effects model.</li>
</ul>
Reflections on the ocular surface: Summary of the presentations at the 4th Coronis Foundation Ophthalmic Symposium Debate: “A multifactorial approach to ocular surface disorders” (August 31 2021)
No full textThe author (van Setten) thanks the Karin Sandqvists Foundation (Karin Sandqvists Stiftelse) Stockholm, Sweden, the Eye Foundation (Ögonfonden), Stockholm, Sweden and the Crown Princess Margaretas Foundation Working committee for the visually impaired KMA (Stiftelsen Kronprinsessan Margaretas Arbetsnämnd för synskadade KMA) Stockholm, Sweden, for the funding received forming the base for the presented model of dry eye disease.Peer reviewe
Integrating omics for an improved understanding of cardiac diseases
No full textAtrial fibrillation (AF) and heart failure (HF) are diseases affecting approximately 60 million people worldwide each. AF patients suffer from an irregular heartbeat and HF patients experience a loss of pump function. Pharmacological treatments of AF, HF, and related heart muscle diseases (cardiomyopathies) focus predominantly on symptom relief and a more favourable prognosis, while prevention and treatment of underlying causes should be targeted. We searched for genes, proteins, and metabolites related to AF, HF, and cardiomyopathies, because perturbations in genes and proteins contribute to cardiac diseases and dysfunctional energy metabolism fails to meet the high energy demands of the heart to provide the body with blood, which weakens the heart. Indeed, we identified new and confirmed known associations. The findings not only deepen our understanding of cardiac diseases but also provide actionable leads for drug development and personalised therapeutics by pinpointing which drugs target these genes and proteins. Additionally, we evaluated pathogenic genetic variants in the general population, observing many healthy participants carry these variants associated with the inherited cardiomyopathies. Clustering HF patients using proteins, resulted in three subgroups with different rates of progression, which help identify patients in need of timely intervention. These studies show that the integration of data on genes, proteins, and metabolites reflects a promising trend in cardiovascular research, paving the way for more targeted therapeutics. As technology advances and datasets expand, knowledge on pathogenicity can be reevaluated and future studies will elucidate even more mechanisms contributing to cardiac disease, ultimately leading to improved clinical care
The genetics of carotid atherosclerosis: Associations with clinical outcome and histological plaque characteristics
No full textThroughout this Thesis we explored the potential mechanisms of common cardiovascular disease susceptibility genetic variants (loci). We studied their impact, individually or in aggregate on histological plaque characteristics, gene expression, DNA methylation, and circulating biomarkers in deeply phenotyped biobank studies. We show that the coronary artery disease (CAD) susceptibility locus on chromosome 7q22 associates with less fat in atherosclerotic plaques and reduced LDL levels in the circulation. Through wet-lab circularized chromosome conformation capture sequencing and in silico experiments we prioritized the regional genes. Overall, the analyses confirm that cardiovascular susceptibility loci play a role in atherosclerotic plaque progression. We also describe the presumed role of genes (ALOX5, ALOX5AP and LTA4h) in the arachidonic acid pathway on stroke risk. Through a genetic analysis of all the variants in and around these genes, we found no evidence for a causal role of the arachidonic acid signaling pathway in atherosclerotic plaque progression leading to disease. In another chapter we show that the atherosclerotic stroke risk conferring allele of rs2107595 (A>G) near HDAC9 increases expression of HDAC9 in circulating cells, and apoE-/- mice lacking a functional Hdac9 gene show marked reduction in atherosclerotic lesion size. The same risk-allele did not associate with histological plaque characteristics. Furthermore, we systematically searched literature for putative atherosclerotic genes identified in experimental animal models. First, we mapped these genes to their human orthologue. Then we used summary statistics from large genome-wide association studies (GWAS) on CAD and large artery ischemic stroke (LAS) to calculate per-gene empirical p-values. Very few of the putative atherosclerotic genes were associated with human cardiovascular disease or a plaque characteristic. Epidemiological evidence shows that carotid IMT is a biomarker for cardiovascular disease in general. GWAS have discovered 6 loci associated with cIMT and carotid plaque presence. We tested these loci for association with cIMT and assessed their impact on other vascular beds in a cohort of secondary prevention. We replicated the association with cIMT, and associated a variant near EDNRA with CAD. This analysis added to the evidence for a role of the EDNRA locus in cardiovascular disease, as earlier work showed it also associates with blood pressure. In the last chapter we test the putative causal role of cystatin C on cardiovascular disease through a meta-analysis of data from over 250,000 individuals, including more than 63,000 cases with cardiovascular disease. We replicated the strong correlation of a genetic locus near the CST3 gene (which encodes for cystatin C) with circulating levels of cystatin C and estimated glomerular filtration rate based on cystatin C. We also replicated earlier observational reports showing increasing risk for CVD with increasing cystatin C levels. Utilizing the Mendelian randomization method, we could not found evidence for a causal role of cystatin C in cardiovascular disease
Development of a Liquid Catalyst for Diesel Soot Oxidation - From powder to prototype
No full textApplied Science
Multikriteria-methoden voor ruimtelijk evaluatieonderzoek
No full textVerslag van het onderzoek EVAPLAN uitgevoerd in opdracht van de Rijksplanologische Dienst.Delft University of Technolog
Pipeline construction for the automated text retrieval, editing, and deletion in comic illustrations
No full textWith the increasing demand for high- quality data in the field of Machine Learning and AI, the availability of such data has become a major bottleneck for further advancements. This paper proposes a novel approach to extract valuable data from comic illustrations, aiming to address the scarcity of labeled datasets. By leveraging popular comic series such as Dilbert, which contain thousands of comic strips with multiple panels, text boxes, characters, and settings, we aim to create a pipeline for data labeling and manipulation. This pipeline will enable experiments in various areas, including generative comics, humor detection, translation, and more. The paper focuses on two key research questions: 1) How accurately can we get current OCR models to extract text from the comics, and 2) How can we create the ability to edit and delete existing text boxes. By accurately segmenting the panels and text boxes within the comics, we expect to improve OCR performance by reducing noise and addressing unique text formats. Object detection models will be employed to zoom into text boxes, further enhancing OCR text extraction accuracy. Evaluation metrics such as Latent Dirichlet allocation (LDA), Character Error Rate (CER), and Word Error Rate (WER) will be used to measure the effectiveness of the proposed techniques. In the end, utilizing a dataset of 500 labelled comic panels, we achieve accuracies of 94.07% for CER (up 9.86% from 84.21% baseline), 88.35% for WER (up 8.35% from 80.0% baseline), and 98.0% for LDA (up 3.77% from 94.23% baseline). Similarly, editing and deleting of text boxes inside the comic panels prove to be successful in a vast majority of instances. We believe these results are more than adequate for select use cases.CSE3000 Research ProjectComputer Science and Engineerin
Integrative Bioinformatics in Post-GWAS cardiovascular genomics
No full textCardiovascular diseases (CVDs) are the leading cause of death in the world. Genome-wide association (GWAS) studies have identified many genetic loci robustly associated to CVDs. Because most CVD-associated loci are non-coding, one of the main challenges in the post-GWAS era is interpretation of these statistical signals. This thesis presents bioinformatics applications that integrate genome, regulome and transcriptome information to address this challenge. Integrative approaches such as the ones presented in this thesis can help expand our knowledge of the biological mechanisms involved in CVDs, which in turn can be translated into better prevention and treatment
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