63 research outputs found
Over de vroeg beginnende gasvorming in kaas
The early production of gas in cheese, called 'blowing' was caused chiefly by some coli-aerogenes bacteria of the aerogenes-cloacae type and intermediate types. These bacteria produced gas in a combined fermentation-curdling test both on milk and on cheese; they were called blowing-positive strains.A second group of coli-aerogenes bacteria, although forming acid and gas from lactose in a synthetic lactose medium, did not produce gas in the combined fermentation-curdling test. This was apparently due to the presence of citric acid in the combined test since this acid prevented blowing-negative coliaerogenes strains producing gas from lactose; the citric acid was reduced to succinic acid. As a result these blowing-negative types decomposed the sugar present in the medium without forming gas. Excess of citric acid, however, may be fermented with production of gas. Citric acid always increased gas production by blowing-positive strains through its fermentation. Blowing caused by blowing-positive strains decreased when negative strains were also present.It was found that KN0 3 , KNO 2 , and KClO 3 , prevented gas production from lactose by blowing-positive strains. These compounds seemed to be reduced, thus inhibiting gas production from lactose, while intermediate products occurred which prevented the development of the coli-aerogenes bacteria. KClO 3 appeared to be the most efficient inhibitor. Under practical conditions addition of 1 g per 100 litres milk may be sufficient. Lactic acid fermentation was not influenced by adding this amount of KClO 3
Implicit stigmatization-related biases in individuals with skin conditions and their significant others
FSW - Self-regulation models for health behavior and psychopathology - ou
An association study of germline variants in bladder cancer-related genes with the prognosis of on-Muscle Invasive Bladder Cancer
BACKGROUND:
Various germline genetic variants are associated with the prognosis of non-muscle invasive bladder cancer (NMIBC). Germline variants in genes frequently somatically mutated in bladder cancer have not been studied thoroughly in relation to risk of recurrence or progression in NMIBC.
OBJECTIVE:
To identify germline DNA variants in bladder carcinogenesis-related genes associated with recurrence or progression in NMIBC.
METHODS:
We analysed associations between single-nucleotide polymorphisms (SNPs) and NMIBC recurrence and progression using data from the Nijmegen Bladder Cancer Study (NBCS, 1,443 patients). We included 5,053 SNPs within 46 genes known to have mutation, overexpression or amplification in bladder cancer. We included all recurrences in the statistical analysis and performed both single variant analysis and gene-based analysis. SNPs and genes that showed significant or suggestive association (false discovery rate P value < 20%) were followed-up in independent cohorts for replication analysis, through eQTL analysis and tests for association of tumour expression levels with NMIBC recurrence and progression.
RESULTS:
Single variant analysis showed no statistically significant associations with recurrence or progression. In gene-based analysis, the aggregate effect of the 25 SNPs in the Cyclin D1 gene (CCND1) was statistically significantly associated with NMIBC recurrence (Punadj = 0.001, PFDR = 0.046), but not with progression (Punadj = 0.17, PFDR = 0.54). Validation analysis in independent cohorts did not confirm the association of CCND1 with NMIBC recurrence.
CONCLUSIONS:
We could not identify reproducible associations between common germline variants in bladder carcinogenesis-related genes and NMIBC recurrence or progression
Genome-wide meta-analysis identifies novel genes associated with recurrence and progression in non–muscle-invasive bladder cancer
Background
Non–muscle-invasive bladder cancer (NMIBC) is characterized by frequent recurrences and a risk of progression in stage and grade. Increased knowledge of underlying biological mechanisms is needed.
Objective
To identify single nucleotide polymorphisms (SNPs) associated with recurrence-free (RFS) and progression-free (PFS) survival in NMIBC.
Design, setting, and participants
We analyzed outcome data from 3400 newly diagnosed NMIBC patients from the Netherlands, the UK, Canada, and Spain. We generated genome-wide germline SNP data using Illumina OmniExpress and Infinium Global Screening Array in combination with genotype imputation.
Outcome measurements and statistical analysis
Cohort-specific genome-wide association studies (GWASs) for RFS and PFS were performed using a Cox proportional hazard model. Results were combined in a fixed-effect inverse-variance weighted meta-analysis. Candidate genes for the identified SNP associations were prioritized using functional annotation, gene-based analysis, expression quantitative trait locus analysis, and transcription factor binding site databases. Tumor expression levels of prioritized genes were tested for association with RFS and PFS in an independent NMIBC cohort.
Results and limitations
This meta-analysis revealed a genome-wide significant locus for RFS on chromosome 14 (lead SNP rs12885353, hazard ratio [HR] C vs T allele 1.55, 95% confidence interval [CI] 1.33–1.82, p = 4.0 × 10–8), containing genes G2E3 and SCFD1. Higher expression of SCFD1 was associated with increased RFS (HR 0.70, 95% CI 0.59–0.84, pFDR = 0.003). Twelve other loci were suggestively associated with RFS (p < 10–5), pointing toward 18 additional candidate genes. For PFS, ten loci showed suggestive evidence of association, indicating 36 candidate genes. Expression levels of ten of these genes were statistically significantly associated with PFS, of which four (IFT140, UBE2I, FAHD1, and NME3) showed directional consistency with our meta-analysis results and published literature.
Conclusions
In this first prognostic GWAS in NMIBC, we identified several novel candidate loci and five genes that showed convincing associations with recurrence or progression.
Patient summary
In this study, we searched for inherited DNA changes that affect the outcome of non–muscle-invasive bladder cancer (NMIBC). We identified several genes that are associated with disease recurrence and progression. The roles and mechanisms of these genes in NMIBC prognosis should be investigated in future studies
Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity
Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents' survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan
Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.
Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets
Genetic insights into resting heart rate and its role in cardiovascular disease.
Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development
The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape : A Large-Scale Genome-Wide Interaction Study
Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age-and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to similar to 2.8M SNPs with BMI and WHRadjBMI in four strata (men 50y, women 50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR= 50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may providefurther insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.Peer reviewe
Hepcidin: population-based studies into genetic determinants and effects on atherosclerosis
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134180.pdf (publisher's version ) (Open Access)Radboud Universiteit Nijmegen, 9 januari 2015Promotores : Swinkels, D.W., Kiemeney, L.A.L.M.
Co-promotor : Vermeulen, S.H
A comparison of multivariate genome-wide association methods
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137652.pdf (publisher's version ) (Open Access)Joint association analysis of multiple traits in a genome-wide association study (GWAS), i.e. a multivariate GWAS, offers several advantages over analyzing each trait in a separate GWAS. In this study we directly compared a number of multivariate GWAS methods using simulated data. We focused on six methods that are implemented in the software packages PLINK, SNPTEST, MultiPhen, BIMBAM, PCHAT and TATES, and also compared them to standard univariate GWAS, analysis of the first principal component of the traits, and meta-analysis of univariate results. We simulated data (N = 1000) for three quantitative traits and one bi-allelic quantitative trait locus (QTL), and varied the number of traits associated with the QTL (explained variance 0.1%), minor allele frequency of the QTL, residual correlation between the traits, and the sign of the correlation induced by the QTL relative to the residual correlation. We compared the power of the methods using empirically fixed significance thresholds (alpha = 0.05). Our results showed that the multivariate methods implemented in PLINK, SNPTEST, MultiPhen and BIMBAM performed best for the majority of the tested scenarios, with a notable increase in power for scenarios with an opposite sign of genetic and residual correlation. All multivariate analyses resulted in a higher power than univariate analyses, even when only one of the traits was associated with the QTL. Hence, use of multivariate GWAS methods can be recommended, even when genetic correlations between traits are weak
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