251 research outputs found

    Internship workplace preferences of final-year medical students at Zagreb University Medical School, Croatia: all roads lead to Zagreb

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    BACKGROUND: Human resources management in health often encounters problems related to workforce geographical distribution. The aim of this study was to investigate the internship workplace preferences of final-year medical students and the reasons associated with their choices. METHOD: A total of 204 out of 240 final-year medical students at Zagreb University Medical School, Croatia, were surveyed a few months before graduation. We collected data on each student's background, workplace preference, academic performance and emigration preferences. Logistic regression was used to analyse the factors underlying internship workplace preference, classified into two categories: Zagreb versus other areas. RESULTS: Only 39 respondents (19.1%) wanted to obtain internships outside Zagreb, the Croatian capital. Gender and age were not significantly associated with internship workplace preference. A single predictor variable significantly contributed to the logistic regression model: students who believed they would not get the desired specialty more often chose Zagreb as a preferred internship workplace (odds ratio 0.32, 95% CI 0.12–0.86). CONCLUSION: A strong preference for Zagreb as an internship workplace was recorded. Uncertainty about getting the desired specialty was associated with choosing Zagreb as a workplace, possibly due to more extensive and diverse job opportunities

    Informing epidemic (research) responses in a timely fashion by knowledge management - a Zika virus use case

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    The response of pathophysiological research to emerging epidemics often occurs after the epidemic and, as a consequence, has little to no impact on improving patient outcomes or on developing high-quality evidence to inform clinical management strategies during the epidemic. Rapid and informed guidance of epidemic (research) responses to severe infectious disease outbreaks requires quick compilation and integration of existing pathophysiological knowledge. As a case study we chose the Zika virus (ZIKV) outbreak that started in 2015 to develop a proof-of-concept knowledge repository. To extract data from available sources and build a computationally tractable and comprehensive molecular interaction map we applied generic knowledge management software for literature mining, expert knowledge curation, data integration, reporting and visualization. A multi-disciplinary team of experts, including clinicians, virologists, bioinformaticians and knowledge management specialists, followed a pre-defined workflow for rapid integration and evaluation of available evidence. While conventional approaches usually require months to comb through the existing literature, the initial ZIKV KnowledgeBase (ZIKA KB) was completed within a few weeks. Recently we updated the ZIKA KB with additional curated data from the large amount of literature published since 2016 and made it publicly available through a web interface together with a step-by-step guide to ensure reproducibility of the described use case. In addition, a detailed online user manual is provided to enable the ZIKV research community to generate hypotheses, share knowledge, identify knowledge gaps, and interactively explore and interpret data. A workflow for rapid response during outbreaks was generated, validated and refined and is also made available. The process described here can be used for timely structuring of pathophysiological knowledge for future threats. The resulting structured biological knowledge is a helpful tool for computational data analysis and generation of predictive models and opens new avenues for infectious disease research. ZIKV Knowledgebase is available at www.zikaknowledgebase.eu

    A meta-analysis of genome-wide data from five European isolates reveals an association of COL22A1, SYT1, and GABRR2 with serum creatinine level

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    <p>Abstract</p> <p>Background</p> <p>Serum creatinine (S<sub>CR</sub>) is the most important biomarker for a quick and non-invasive assessment of kidney function in population-based surveys. A substantial proportion of the inter-individual variability in S<sub>CR </sub>level is explicable by genetic factors.</p> <p>Methods</p> <p>We performed a meta-analysis of genome-wide association studies of S<sub>CR </sub>undertaken in five population isolates ('discovery cohorts'), all of which are part of the European Special Population Network (EUROSPAN) project. Genes showing the strongest evidence for an association with S<sub>CR </sub>(candidate loci) were replicated in two additional population-based samples ('replication cohorts').</p> <p>Results</p> <p>After the discovery meta-analysis, 29 loci were selected for replication. Association between S<sub>CR </sub>level and polymorphisms in the collagen type XXII alpha 1 (<it>COL22A1</it>) gene, on chromosome 8, and in the synaptotagmin-1 (<it>SYT1</it>) gene, on chromosome 12, were successfully replicated in the replication cohorts (p value = 1.0 × 10<sup>-6 </sup>and 1.7 × 10<sup>-4</sup>, respectively). Evidence of association was also found for polymorphisms in a locus including the gamma-aminobutyric acid receptor rho-2 (<it>GABRR2</it>) gene and the ubiquitin-conjugating enzyme E2-J1 (<it>UBE2J1</it>) gene (replication p value = 3.6 × 10<sup>-3</sup>). Previously reported findings, associating glomerular filtration rate with SNPs in the uromodulin (<it>UMOD</it>) gene and in the schroom family member 3 (<it>SCHROOM3</it>) gene were also replicated.</p> <p>Conclusions</p> <p>While confirming earlier results, our study provides new insights in the understanding of the genetic basis of serum creatinine regulatory processes. In particular, the association with the genes <it>SYT1 </it>and <it>GABRR2 </it>corroborate previous findings that highlighted a possible role of the neurotransmitters GABA<sub>A </sub>receptors in the regulation of the glomerular basement membrane and a possible interaction between GABA<sub>A</sub>receptors and synaptotagmin-I at the podocyte level.</p

    Genome-wide meta-analysis of myopia and hyperopia provides evidence for replication of 11 loci

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    Refractive error (RE) is a complex, multifactorial disorder characterized by a mismatch between the optical power of the eye and its axial length that causes object images to be focused off the retina. The two major subtypes of RE are myopia (nearsightedness) and hyperopia (farsightedness), which represent opposite ends of the distribution of the quantitative measure of spherical refraction. We performed a fixed effects meta-analysis of genome-wide association results of myopia and hyperopia from 9 studies of European-derived populations: AREDS, KORA, FES, OGP-Talana, MESA, RSI, RSII, RSIII and ERF. One genome-wide significant region was observed for myopia, corresponding to a previously identified myopia locus on 8q12 (p = 1.25610-8), which has been reported by Kiefer et al. as significantly associated with myopia age at onset and Verhoeven et al. as significantly associated to mean spherical-equivalent (MSE) refractive error. We observed two genomewide significant association

    Automated workflow-based exploitation of pathway databases provides new insights into genetic associations of metabolite profiles

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    Background: Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets. Results: Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression. Conclusions: We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWAS datasets of metabolomic phenotypes. We report novel loci and potential biochemical mechanisms that contribute to our understanding of the genetic basis of metabolic variation and its relationship to disease development and progression

    Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain

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    Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of ch

    Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

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    So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels

    Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6.

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    BACKGROUND: Genome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear. RESULTS: Here, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction. CONCLUSIONS: Our approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes.BH

    Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

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    Background So far, more than 170 loci have been associated with circulating lipid levels through genomewide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ~60 000 individuals in the discovery stage and ~90 000 samples in the replication stage. Results Our study resu
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