34 research outputs found

    Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

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    Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P interaction  = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications

    Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population.

    Get PDF
    Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications

    Fault Prediction for Nonlinear System Using Sliding ARMA Combined with Online LS-SVR

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    A robust online fault prediction method which combines sliding autoregressive moving average (ARMA) modeling with online least squares support vector regression (LS-SVR) compensation is presented for unknown nonlinear system. At first, we design an online LS-SVR algorithm for nonlinear time series prediction. Based on this, a combined time series prediction method is developed for nonlinear system prediction. The sliding ARMA model is used to approximate the nonlinear time series; meanwhile, the online LS-SVR is added to compensate for the nonlinear modeling error with external disturbance. As a result, the one-step-ahead prediction of the nonlinear time series is achieved and it can be extended to n-step-ahead prediction. The result of the n-step-ahead prediction is then used to judge the fault based on an abnormity estimation algorithm only using normal data of system. Accordingly, the online fault prediction is implemented with less amount of calculation. Finally, the proposed method is applied to fault prediction of model-unknown fighter F-16. The experimental results show that the method can predict the fault of nonlinear system not only accurately but also quickly

    A New Perspective to Algebraic Characterization on Controllability of Multiagent Systems

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    Recently, algebraic characterization of multiagent controllability through its topology has been widely concerned by the systems and control community. The controllability of leader-follower networked multiagent systems under the framework of generic linear dynamics is firstly discussed via λ-matrix. Some new algebra-theoretic necessary and/or sufficient conditions of the controllability for generic linear multiagent systems are established. Moreover, the controllable conditions for multiagent networks with special topological graphs through λ-matrix are presented

    Description of a new horned toad of Megophrys Kuhl & Van Hasselt, 1822 (Anura, Megophryidae) from southwest China

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    A new species of the genus Megophrys is described from Guizhou Province, China. Molecular phylogenetic analyses supported the new species as an independent clade nested into the Megophrys. The new species could be distinguished from its congeners by a combination of the following characters: body size moderate (SVL 49.3–58.2 mm in males); vomerine ridges present distinctly, vomerine teeth present; tongue feebly notched behind; tympanum distinctly visible, oval; two metacarpal tubercles in hand; toes with one-third webbing and wide lateral fringes; heels overlapped when thighs are positioned at right angles to the body; tibiotarsal articulation reaching the level between tympanum and eye when leg stretched forward; an internal single subgular vocal sac present in male; in breeding male, the nuptial pads with large and sparse black nuptial spines present on the dorsal bases of the first two fingers

    The anti-HEV rates of the population in Guangdong province, China, according to age, gender, and pig-exposure status.

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    <p>a: OR, odds ratio; b: 95%CI, 95%confidence interval; c: X<sup>2</sup>, Chi-Square Test; d: ref, reference; UF, urban female; UM, urban male; FF, swine farm female; FM, swine farm male; **, significant difference; *, different.</p
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