7 research outputs found

    Forest plot of Wald ratios and 95% CIs generated from clumped SNPs associated with BMI.

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    <p>Odds ratios for individual SNPs are listed according to magnitude of effect in the instrumental variable analysis and are presented with pooled effects using the IVW method and MR–Egger regression. The most recent meta-analysis of observational studies is also plotted (Wang et al. [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002314#pmed.1002314.ref013" target="_blank">13</a>]). Squares represent the point estimate, and the bars are the 95% confidence intervals. There was weak evidence of heterogeneity (<i>Q</i> statistic = 95.5; <i>I</i><sup>2</sup> = 20.4%; <i>p</i> = 0.065). IVW, inverse-variance weighted; MR, Mendelian randomisation.</p

    Frailty analysis.

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    <p>We obtained effect estimates from two sources: (1) analysis of the causal influence of BMI on PD using real data and (2) simulations where BMI had no effect on PD, and any apparent effect was due to survival bias alone. This figure shows the comparison of the estimates from these two sources using three different approaches—MR IVW analysis, MR–Egger regression, and observational associations. For the true effect estimates, the horizontal lines denote the 95% confidence intervals; for the results from simulations, the horizontal lines denote 95% confidence intervals obtained from 1,000 simulations. BMI, body mass index; IVW, inverse-variance weighted; MR, Mendelian randomisation; PD, Parkinson disease.</p

    Directed acyclic graph of instrumental variable analysis using genetic variants as proxies for environmental exposures (adapted from Lawlor et al. [14]).

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    <p>Genetic variants (<i>Z</i>) associated with an exposure such as BMI (<i>X</i>) can be used as proxies to determine the effect of the exposure (<i>X</i>) on the outcome (<i>Y</i>). The three IV assumptions are indicated by arrows or the absence of arrows: (1) the IV in this schematic (<i>FTO</i> gene variant) is robustly associated with the exposure; (2) the IV is not associated with confounding factors (<i>C</i>); and (3) there is no alternative way that the IV affects the outcome other than via the exposure. BMI, body mass index; IV, instrumental variable; PD, Parkinson disease.</p

    Genome-wide association results and detailed peak association regions.

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    <p>(<b>A</b>) Manhattan plot of the meta-analysis performed on early-onset bipolar patients and controls from France and Germany. Physical position is shown along the <i>x</i> axis and –log10(<i>P</i>-value) is shown along the <i>y</i> axis. (<b>B</b>) Detail of the two most associated regions on chromosomes 5p13 and 12p12. Allele frequency differences are represented by –log10(<i>P</i>-values) for the French (open grey circles), the German (open grey squares) and the meta- (open red diamonds) analyses. Grey crosses represent –log10(<i>P</i>-value) for imputed ungenotyped SNPs. The most associated SNP for each region is shown with orange circle. On chromosome 12p12, the lowest <i>P</i>-value (<i>P</i> = 2.1×10<sup>−7</sup>) was observed for an imputed SNP (<i>rs10743315</i>). On chromosome 5p13, the lowest <i>P</i>-value (<i>P</i> = 2.6×10<sup>−7</sup>) was observed for a three-SNPs window haplotype (light blue line) located downstream to <i>OXCT1</i> and upstream to <i>PLCXD3</i> (<i>rs624097-rs316762-rs10512793</i>). The genome-wide significant threshold (<i>P</i> = 5×10<sup>−8</sup>) is indicated by the blue dash line and the dot black line shows a threshold at <i>P</i> = 5×10<sup>−5</sup>. The largest differences in allele frequencies are represented with filled diamonds. Gene position and annotation (<a href="http://genome.ucsc.edu/" target="_blank">http://genome.ucsc.edu/</a>) are symbolised by green arrows. Linkage disequilibrium (r<sup>2</sup>) estimated according to HapMap CEU population SNPs (release 3) is symbolised in the bottom part of each figure. Darker red indicates higher values.</p
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