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Sökning: WFRF:(de Faire Ulf) > Naturvetenskap

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1.
  • Beelen, Rob, et al. (författare)
  • Natural-Cause Mortality and Long-Term Exposure to Particle Components : An Analysis of 19 European Cohorts within the Multi-Center ESCAPE Project
  • 2015
  • Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 123:6, s. 525-533
  • Forskningsöversikt (refereegranskat)abstract
    • Background: Studies have shown associations between mortality and long-term exposure to particulate matter air pollution. Few cohort studies have estimated the effects of the elemental composition of particulate matter on mortality. Objectives: Our aim was to study the association between natural-cause mortality and long-term exposure to elemental components of particulate matter. Methods: Mortality and confounder data from 19 European cohort studies were used. Residential exposure to eight a priori-selected components of particulate matter ( PM) was characterized following a strictly standardized protocol. Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM size fractions <= 2.5 mu m (PM2.5) and <= 10 mu m (PM10) were estimated using land-use regression models. Cohort-specific statistical analyses of the associations between mortality and air pollution were conducted using Cox proportional hazards models using a common protocol followed by meta-analysis. Results: The total study population consisted of 291,816 participants, of whom 25,466 died from a natural cause during follow-up (average time of follow-up, 14.3 years). Hazard ratios were positive for almost all elements and statistically significant for PM2.5 sulfur (1.14; 95% CI: 1.06, 1.23 per 200ng/m(3)). In a two-pollutant model, the association with PM2.5 sulfur was robust to adjustment for PM2.5 mass, whereas the association with PM2.5 mass was reduced. Conclusions: Long-term exposure to PM2.5 sulfur was associated with natural-cause mortality. This association was robust to adjustment for other pollutants and PM2.5.
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2.
  • Fuks, Kateryna B., et al. (författare)
  • Arterial blood pressure and long-term exposure to traffic-related air pollution : an analysis in the European Study of Cohorts for Air Pollution Effects (ESCAPE)
  • 2014
  • Ingår i: Journal of Environmental Health Perspectives. - : National Institute of Environmental Health Sciences (NIEHS). - 0091-6765 .- 1552-9924. ; 122:9, s. 896-905
  • Forskningsöversikt (refereegranskat)abstract
    • BACKGROUND: Long-term exposure to air pollution is hypothesized to elevate arterial blood pressure (BP). The existing evidence is scarce and country-specific. OBJECTIVES: We investigated the cross-sectional association of long-term traffic-related air pollution with BP and prevalent hypertension in European populations. METHODS: Fifteen population-based cohorts, participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE), were analysed. Residential exposure to particulate matter and nitrogen oxides was modelled with land use regression using a uniform protocol. Traffic exposure was assessed with traffic indicator variables. We analysed systolic and diastolic BP in participants medicated and non-medicated with BP lowering medication (BPLM) separately, adjusting for personal and area-level risk factors and environmental noise. Prevalent hypertension was defined as ≥ 140 mmHg systolic, or ≥ 90 mmHg diastolic BP, or intake of BPLM. We combined cohort-specific results using random-effects meta-analysis. RESULTS: In the main meta-analysis of 113,926 participants, traffic load on major roads within 100 m of the residence was associated with increased systolic and diastolic BP in non-medicated participants (0.35 mmHg [95% CI: 0.02-0.68] and 0.22 mmHg [95% CI: 0.04-0.40] per 4,000,000 vehicles × m/day, respectively). The estimated odds ratio for prevalent hypertension was 1.05 [95% CI: 0.99-1.11] per 4,000,000 vehicles × m/day. Modelled air pollutants and BP were not clearly associated. CONCLUSIONS: In this first comprehensive meta-analysis of European population-based cohorts we observed a weak positive association of high residential traffic exposure with BP in non-medicated participants, and an elevated OR for prevalent hypertension. The relationship of modelled air pollutants with BP was inconsistent.
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3.
  • Weinmayr, Gudrun, et al. (författare)
  • Particulate matter air pollution components and incidence of cancers of the stomach and the upper aerodigestive tract in the European Study of Cohorts of Air Pollution Effects (ESCAPE)
  • 2018
  • Ingår i: Environment International. - : Elsevier BV. - 0160-4120 .- 1873-6750. ; 120, s. 163-171
  • Tidskriftsartikel (refereegranskat)abstract
    • Introduction: Previous analysis from the large European multicentre ESCAPE study showed an association of ambient particulate matter < 2.5 mu m (PM2.5) air pollution exposure at residence with the incidence of gastric cancer. It is unclear which components of PM are most relevant for gastric and also upper aerodigestive tract (UADT) cancer and some of them may not be strongly correlated with PM mass. We evaluated the association between long-term exposure to elemental components of PM2.5 and PM10 and gastric and UADT cancer incidence in European adults.Methods: Baseline addresses of individuals were geocoded and exposure was assessed by land-use regression models for copper (Cu), iron (Fe) and zinc (Zn) representing non-tailpipe traffic emissions; sulphur (S) indicating long-range transport; nickel (Ni) and vanadium (V) for mixed oil-burning and industry; silicon (Si) for crustal material and potassium (K) for biomass burning. Cox regression models with adjustment for potential confounders were used for cohort-specific analyses. Combined estimates were determined with random effects meta-analyses.Results: Ten cohorts in six countries contributed data on 227,044 individuals with an average follow-up of 14.9 years with 633 incident cases of gastric cancer and 763 of UADT cancer. The combined hazard ratio (HR) for an increase of 200 ng/m(3) of PM2.5_S was 1.92 (95%-confidence interval (95%-CI) 1.13; 3.27) for gastric cancer, with no indication of heterogeneity between cohorts (I-2= 0%), and 1.63 (95%-CI 0.88; 3.01) for PM2.5_Zn (I-2= 70%). For the other elements in PM2.5 and all elements in PM10 including PM10_S, non-significant HRs between 0.78 and 1.21 with mostly wide CIs were seen. No association was found between any of the elements and UADT cancer. The HR for PM2.5_S and gastric cancer was robust to adjustment for additional factors, including diet, and restriction to study participants with stable addresses over follow-up resulted in slightly higher effect estimates with a decrease in precision. In a two-pollutant model, the effect estimate for total PM2.5 decreased whereas that for PM2.5_S was robust.Conclusion: This large multicentre cohort study shows a robust association between gastric cancer and long-term exposure to PM2.5 S but not PM10 S, suggesting that S in PM2.5 or correlated air pollutants may contribute to the risk of gastric cancer.
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4.
  • Berndt, Sonja I., et al. (författare)
  • Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
  • 2013
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
  • Tidskriftsartikel (refereegranskat)abstract
    • Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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5.
  • Gaulton, Kyle J, et al. (författare)
  • Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.
  • 2015
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 47:12, s. 1415-1415
  • Tidskriftsartikel (refereegranskat)abstract
    • We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
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6.
  • Scott, Robert A., et al. (författare)
  • Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways
  • 2012
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 44:9, s. 991-1005
  • Tidskriftsartikel (refereegranskat)abstract
    • Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.
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7.
  • Frånberg, Mattias, 1985-, et al. (författare)
  • Fast and general tests of genetic interaction for genome-wide association studies
  • 2017
  • Ingår i: PloS Computational Biology. - : PUBLIC LIBRARY SCIENCE. - 1553-734X .- 1553-7358. ; 13:6
  • Tidskriftsartikel (refereegranskat)abstract
    • A complex disease has, by definition, multiple genetic causes. In theory, these causes could be identified individually, but their identification will likely benefit from informed use of anticipated interactions between causes. In addition, characterizing and understanding interactions must be considered key to revealing the etiology of any complex disease. Large-scale collaborative efforts are now paving the way for comprehensive studies of interaction. As a consequence, there is a need for methods with a computational efficiency sufficient for modern data sets as well as for improvements of statistical accuracy and power. Another issue is that, currently, the relation between different methods for interaction inference is in many cases not transparent, complicating the comparison and interpretation of results between different interaction studies. In this paper we present computationally efficient tests of interaction for the complete family of generalized linear models (GLMs). The tests can be applied for inference of single or multiple interaction parameters, but we show, by simulation, that jointly testing the full set of interaction parameters yields superior power and control of false positive rate. Based on these tests we also describe how to combine results from multiple independent studies of interaction in a meta-analysis. We investigate the impact of several assumptions commonly made when modeling interactions. We also show that, across the important class of models with a full set of interaction parameters, jointly testing the interaction parameters yields identical results. Further, we apply our method to genetic data for cardiovascular disease. This allowed us to identify a putative interaction involved in Lp(a) plasma levels between two 'tag' variants in the LPA locus (p = 2.42 . 10(-09)) as well as replicate the interaction (p = 6.97 . 10(-07)). Finally, our meta-analysis method is used in a small (N = 16,181) study of interactions in myocardial infarction.
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8.
  • Quell, Jan D., et al. (författare)
  • Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies
  • 2017
  • Ingår i: Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences. - : Elsevier BV. - 1570-0232 .- 1873-376X. ; 1071, s. 58-67
  • Tidskriftsartikel (refereegranskat)abstract
    • Identification of metabolites in non-targeted metabolomics continues to be a bottleneck in metabolomics studies in large human cohorts. Unidentified metabolites frequently emerge in the results of association studies linking metabolite levels to, for example, clinical phenotypes. For further analyses these unknown metabolites must be identified. Current approaches utilize chemical information, such as spectral details and fragmentation characteristics to determine components of unknown metabolites. Here, we propose a systems biology model exploiting the internal correlation structure of metabolite levels in combination with existing biochemical and genetic information to characterize properties of unknown molecules.Levels of 758 metabolites (439 known, 319 unknown) in human blood samples of 2279 subjects were measured using a non-targeted metabolomics platform (LC-MS and GC-MS). We reconstructed the structure of biochemical pathways that are imprinted in these metabolomics data by building an empirical network model based on 1040 significant partial correlations between metabolites. We further added associations of these metabolites to 134 genes from genome-wide association studies as well as reactions and functional relations to genes from the public database Recon 2 to the network model. From the local neighborhood in the network, we were able to predict the pathway annotation of 180 unknown metabolites. Furthermore, we classified 100 pairs of known and unknown and 45 pairs of unknown metabolites to 21 types of reactions based on their mass differences. As a proof of concept, we then looked further into the special case of predicted dehydrogenation reactions leading us to the selection of 39 candidate molecules for 5 unknown metabolites. Finally, we could verify 2 of those candidates by applying LC-MS analyses of commercially available candidate substances. The formerly unknown metabolites X-13891 and X-13069 were shown to be 2-dodecendioic acid and 9-tetradecenoic acid, respectively.Our data-driven approach based on measured metabolite levels and genetic associations as well as information from public resources can be used alone or together with methods utilizing spectral patterns as a complementary, automated and powerful method to characterize unknown metabolites.
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9.
  • Persson, Jonas, et al. (författare)
  • Sex-Specific Effects of Adiponectin on Carotid Intima-Media Thickness and Incident Cardiovascular Disease
  • 2015
  • Ingår i: Journal of the American Heart Association. - : WILEY-BLACKWELL. - 2047-9980 .- 2047-9980. ; 4:8
  • Tidskriftsartikel (refereegranskat)abstract
    • Background-Plasma adiponectin levels have previously been inversely associated with carotid intima-media thickness (IMT), a marker of subclinical atherosclerosis. In this study, we used a sex-stratified Mendelian randomization approach to investigate whether adiponectin has a causal protective influence on IMT. Methods and Results-Baseline plasma adiponectin concentrationwas tested for association with baseline IMT, IMT progression over 30 months, and occurrence of cardiovascular events within 3 years in 3430 participants (women, n=1777; men, n=1653) with high cardiovascular risk but no prevalent disease. Plasma adiponectin levels were inversely associated with baseline mean bifurcation IMT after adjustment for established risk factors (beta=-0.018, P<0.001) in men but not in women (beta=-0.006, P=0.185; P for interaction=0.061). Adiponectin levels were inversely associated with progression of mean common carotid IMT in men (beta=-0.0022, P=0.047), whereas no association was seen in women (0.0007, P=0.475; P for interaction=0.018). Moreover, we observed that adiponectin levels were inversely associated with coronary events in women (hazard ratio 0.57, 95% CI 0.37 to 0.87) but not in men (hazard ratio 0.82,95% CI0.54 to 1.25). Agenescore of adiponectin-raisingalleles in6loci, reported recently inalarge multi-ethnic metaanalysis, was inversely associated with baseline mean bifurcation IMT in men (beta=-0.0008, P=0.004) but not in women (beta=-0.0003, P=0.522; P for interaction=0.007). Conclusions-This report provides some evidence for adiponectin protecting against atherosclerosis, with effects being confined to men; however, compared with established cardiovascular risk factors, the effect of plasma adiponectin was modest. Further investigation involving mechanistic studies is warranted.
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10.
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