64 research outputs found

    Air Pollution and Pulmonary Tuberculosis: A Nested Case–Control Study among Members of a Northern California Health Plan

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    BACKGROUND: Ecologic analyses, case-case comparisons, and animal experiments suggest positive associations between air pollution and tuberculosis. OBJECTIVES: We evaluated this hypothesis in a large sample, which yielded results that are applicable to the general population. METHODS: We conducted a case-control study nested within a cohort of Kaiser Permanente of Northern California members. All active pulmonary tuberculosis (TB) cases newly diagnosed between 1996 and 2010 (n = 2,309) were matched to two controls (n = 4,604) by age, sex, and race/ethnicity on the index date corresponding with the case diagnosis date. Average individual-level concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5) and 10 μm (PM10) for 2 years before diagnosis/entry into the study were estimated using measurements from the California Air Resources Board monitor closest to the participant's residence. RESULTS: In single-pollutant adjusted conditional logistic regression models, the pulmonary TB odds ratios (95% confidence intervals) for the highest quintile (vs. lowest) were 1.50 (95% CI: 1.15, 1.95) for CO and 1.42 (95% CI: 1.10, 1.84) for NO2. Corresponding estimates were higher among never [1.68 (95% CI: 1.26, 2.24)] than ever [1.19 (95% CI: 0.74, 1.92)] smokers for CO. In contrast, for NO2, estimates were higher among ever [1.81 (95% CI: 1.13, 2.91)] than never [1.29 (95% CI: 0.97, 1.71)] smokers. O3 was inversely associated for smokers [0.66 (95% CI: 0.43, 1.02)] and never smokers [0.65 (95% CI: 0.52, 0.81)]. No other consistent patterns were observed. CONCLUSIONS: In this first, to our knowledge, U.S. nested case-control study on air pollution and pulmonary TB, we observed positive associations with ambient CO and NO2, which require confirmation. CITATION: Smith GS, Van Den Eeden SK, Garcia C, Shan J, Baxter R, Herring AH, Richardson DB, Van Rie A, Emch M, Gammon MD. 2016. Air pollution and pulmonary tuberculosis: a nested case-control study among members of a Northern California health plan. Environ Health Perspect 124:761-768; http://dx.doi.org/10.1289/ehp.1408166

    Unresolved issues with the assessment of multidecadal global land surface temperature trends

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    This paper documents various unresolved issues in using surface temperature trends as a metric for assessing global and regional climate change. A series of examples ranging from errors caused by temperature measurements at a monitoring station to the undocumented biases in the regionally and globally averaged time series are provided. The issues are poorly understood or documented and relate to micrometeorological impacts due to warm bias in nighttime minimum temperatures, poor siting of the instrumentation, effect of winds as well as surface atmospheric water vapor content on temperature trends, the quantification of uncertainties in the homogenization of surface temperature data, and the influence of land use/land cover (LULC) change on surface temperature trends. Because of the issues presented in this paper related to the analysis of multidecadal surface temperature we recommend that greater, more complete documentation and quantification of these issues be required for all observation stations that are intended to be used in such assessments. This is necessary for confidence in the actual observations of surface temperature variability and long-term trends

    Documentation of Uncertainties and Biases Associated with Surface Temperature Measurement Sites for Climate Change Assessment

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    © Copyright 2007 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act September 2010 Page 2 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (https://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected] objective of this research is to determine whether poorly sited long-term surface temperature monitoring sites have been adjusted in order to provide spatially representative independent data for use in regional and global surface temperature analyses. We present detailed analyses that demonstrate the lack of independence of the poorly sited data when they are adjusted using the homogenization procedures employed in past studies, as well as discuss the uncertainties associated with undocumented station moves. We use simulation and mathematics to determine the effect of trend on station adjustments and the associated effect of trend in the reference series on the trend of the adjusted station. We also compare data before and after adjustment to the reanalysis data, and we discuss the effect of land use changes on the uncertainty of measurement. A major conclusion of our analysis is that there are large uncertainties associated with the surface temperature trends from the poorly sited stations. Moreover, rather than providing additional independent information, the use of the data from poorly sited stations provides a false sense of confidence in the robustness of the surface temperature trend assessments.Department of Energy National Science Foundation National Aeronautics and Space Administration United States Geological Survey Mary K. Rice Foundatio

    Geobiology of the late Paleoproterozoic Duck Creek Formation, Western Australia

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    The ca. 1.8 Ga Duck Creek Formation, Western Australia, preserves 1000 m of carbonates and minor iron formation that accumulated along a late Paleoproterozoic ocean margin. Two upward-deepening stratigraphic packages are preserved, each characterized by peritidal precipitates at the base and iron formation and carbonate turbidites in its upper part. Consistent with recent studies of Neoarchean basins, carbon isotope ratios of Duck Creek carbonates show no evidence for a strong isotopic depth gradient, but carbonate minerals in iron formations can be markedly depleted in C-13. In contrast, oxygen isotopes covary strongly with depth; delta O-18 values as positive as 2%. VPDB in peritidal facies systematically decline to values of 6 to 16% in basinal rocks, reflecting, we posit, the timing of diagenetic closure. The Duck Creek Formation contains microfossils similar to those of the Gunflint Formation, Canada; they are restricted to early diagenetic cherts developed in basinal facies, strengthening the hypothesis that such fossils capture communities driven by iron metabolism. Indeed, X-ray diffraction data indicate that the Duck Creek basin was ferruginous throughout its history. The persistence of ferruginous waters and iron formation deposition in Western Australia for at least several tens of millions of years after the transition to sulfidic conditions in Laurentia suggests that the late Paleoproterozoic expansion of sulfidic subsurface waters was globally asynchronous

    Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

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    Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.BCAC is funded by Cancer Research UK (C1287/A10118, C1287/A12014) and by the European Community's Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS). Meetings of the BCAC have been funded by the European Union COST programme (BM0606). Genotyping on the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710, C8197/A16565), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer program and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combination of the GWAS data was supported in part by the US National Institutes of Health (NIH) Cancer Post-Cancer GWAS initiative, grant 1 U19 CA148065-01 (DRIVE, part of the GAME-ON initiative). For a full description of funding and acknowledgments, see the Supplementary Note.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.324

    Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

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    Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10−8) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Genetically Predicted Body Mass Index and Breast Cancer Risk : Mendelian Randomization Analyses of Data from 145,000 Women of European Descent

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    Background Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. Methods We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases = 46,325, controls = 42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. Results In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR] = 0.65 per 5 kg/m(2) increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 x 10(-10)). The associations were similar for both premenopausal (OR = 0.44, 95% CI: 0.31-0.62, p = 9.91x10(-8)) and postmenopausal breast cancer (OR = 0.57, 95% CI: 0.46-0.71, p = 1.88x10(-8)). This association was replicated in the data from the DRIVE consortium (OR = 0.72, 95% CI: 0.60-0.84, p = 1.64 x 10(-7)). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p <0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. Conclusions BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.Peer reviewe

    Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

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    Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (PPeer reviewe
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