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Sökning: WFRF:(Randall Joshua C.) > Karolinska Institutet

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1.
  • Lindgren, Cecilia M, et al. (författare)
  • Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.
  • 2009
  • Ingår i: PLoS genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 5:6, s. e1000508-
  • Tidskriftsartikel (refereegranskat)abstract
    • To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
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2.
  • Winkler, Thomas W., et al. (författare)
  • Quality control and conduct of genome-wide association meta-analyses
  • 2014
  • Ingår i: Nature Protocols. - : Springer Science and Business Media LLC. - 1754-2189 .- 1750-2799. ; 9:5, s. 1192-1212
  • Tidskriftsartikel (refereegranskat)abstract
    • Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta- level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.
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