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Sökning: WFRF:(Foy R)

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  • Tang, Wenbo, et al. (författare)
  • Large-Scale Genome-Wide Association Studies and Meta-Analyses of Longitudinal Change in Adult Lung Function
  • 2014
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:7, s. e100776-
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function. Methods: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis. Results: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P = 5.71 x 10(-7)). In addition, meta-analysis using the five cohorts with >= 3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P = 2.18 x 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively. Conclusions: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function.
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  • Shekelle, PG, et al. (författare)
  • Advancing the science of patient safety
  • 2011
  • Ingår i: Annals of internal medicine. - : American College of Physicians. - 1539-3704 .- 0003-4819. ; 154:10, s. 693-696
  • Tidskriftsartikel (refereegranskat)
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  • de Foy, B., et al. (författare)
  • Modelling constraints on the emission inventory and on vertical dispersion for CO and SO2 in the Mexico City Metropolitan Area using Solar FTIR and zenith sky UV spectroscopy
  • 2007
  • Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 7, s. 781-801
  • Tidskriftsartikel (refereegranskat)abstract
    • Emissions of air pollutants in and around urban areas lead to negative health impacts on the population. To estimate these impacts, it is important to know the sources and transport mechanisms of the pollutants accurately. Mexico City has a large urban fleet in a topographically constrained basin leading to high levels of carbon monoxide ( CO). Large point sources of sulfur dioxide (SO2) surrounding the basin lead to episodes with high concentrations. An Eulerian grid model (CAMx) and a particle trajectory model ( FLEXPART) are used to evaluate the estimates of CO and SO2 in the current emission inventory using mesoscale meteorological simulations from MM5. Vertical column measurements of CO are used to constrain the total amount of emitted CO in the model and to identify the most appropriate vertical dispersion scheme. Zenith sky UV spectroscopy is used to estimate the emissions of SO2 from a large power plant and the Popocatepetl volcano. Results suggest that the models are able to identify correctly large point sources and that both the power plant and the volcano impact the MCMA. Modelled concentrations of CO based on the current emission inventory match observations suggesting that the current total emissions estimate is correct. Possible adjustments to the spatial and temporal distribution can be inferred from model results. Accurate source and dispersion modelling provides feedback for development of the emission inventory, verification of transport processes in air quality models and guidance for policy decisions.
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