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Sökning: WFRF:(Davis A. Darlene)

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1.
  • Weinstein, John N., et al. (författare)
  • The cancer genome atlas pan-cancer analysis project
  • 2013
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:10, s. 1113-1120
  • Forskningsöversikt (refereegranskat)abstract
    • The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile. © 2013 Nature America, Inc. All rights reserved.
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2.
  • Nead, Kevin T., et al. (författare)
  • Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity : a systematic review and meta-analysis with evidence from up to 331 175 individuals
  • 2015
  • Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 24:12, s. 3582-3594
  • Tidskriftsartikel (refereegranskat)abstract
    • Polymorphisms rs6232 and rs6234/rs6235 in PCSK1 have been associated with extreme obesity [e.g. body mass index (BMI) a parts per thousand yen 40 kg/m(2)], but their contribution to common obesity (BMI a parts per thousand yen 30 kg/m(2)) and BMI variation in a multi-ethnic context is unclear. To fill this gap, we collected phenotypic and genetic data in up to 331 175 individuals from diverse ethnic groups. This process involved a systematic review of the literature in PubMed, Web of Science, Embase and the NIH GWAS catalog complemented by data extraction from pre-existing GWAS or custom-arrays in consortia and single studies. We employed recently developed global meta-analytic random-effects methods to calculate summary odds ratios (OR) and 95% confidence intervals (CIs) or beta estimates and standard errors (SE) for the obesity status and BMI analyses, respectively. Significant associations were found with binary obesity status for rs6232 (OR = 1.15, 95% CI 1.06-1.24, P = 6.08 x 10(-6)) and rs6234/rs6235 (OR = 1.07, 95% CI 1.04-1.10, P = 3.00 x 10(-7)). Similarly, significant associations were found with continuous BMI for rs6232 (beta = 0.03, 95% CI 0.00-0.07; P = 0.047) and rs6234/rs6235 (beta = 0.02, 95% CI 0.00-0.03; P = 5.57 x 10(-4)). Ethnicity, age and study ascertainment significantly modulated the association of PCSK1 polymorphisms with obesity. In summary, we demonstrate evidence that common gene variation in PCSK1 contributes to BMI variation and susceptibility to common obesity in the largest known meta-analysis published to date in genetic epidemiology.
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