Association of variants in small GTPase genes with epithelial ovarian cancer risk (p-value<10⁻⁴) and functional annotation.

<p>Association of variants in small GTPase genes with epithelial ovarian cancer risk (p-value<10⁻⁴) and functional annotation.</p

Association of rs2256787 in the <i>ARHGEF10L</i> gene with invasive endometrioid EOC risk by study site and combined.

<p>Squares represent the estimated per-allele odds ratio (OR) and are proportional to sample size for each study; lines indicate its 95% confidence interval (CI); source indicates contributing study;[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197561#pone.0197561.ref011" target="_blank">11</a>] MAF, control minor allele frequency; PVal, per-allele p-value adjusted for age, site, and principal components to account for residual differences in European ancestry.</p

Top SNPs associated with SER EOC across racial groups.

<p>¹ MAF, minor allele and its frequency</p><p>² p-value <0.05 are in bold</p><p>³ Odds ratio, 95% confidence interval</p><p>Top SNPs associated with SER EOC across racial groups.</p

The most significant SNPs in the transport pathway genes and risk of EOC by histology, invasiveness, and race/ethnicity¹.

<p>¹ INV: all invasive EOC combined; LMP: low malignant potential / borderline tumors; SER: serous; CC: clear cell; End: endometrioid; Muc: mucinous. Statistically significant associations are indicated in bold (P<0.05). Data format is the following: OR (95% CI); p-value; FDR q-value (white-European women). Only significant FDRs (q<0.2) are shown (<i>HEPH</i>: INV and SER<i>; UGT1A</i>: End).</p><p>The most significant SNPs in the transport pathway genes and risk of EOC by histology, invasiveness, and race/ethnicity<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0128106#t001fn001" target="_blank">¹</a>.</p

Age-dependent BMI loci.

<p>Effect estimates (beta ±95CI) per standard deviation in BMI and risk allele for loci showing age-differences in men & women ≤50y compared to men & women >50y. Loci are ordered by greater magnitude of effect in men & women ≤50y compared to men & women >50y. (95%CI: 95% confidence interval; BMI: body mass index; SD: standard deviation, *Newly identified loci).</p

Forty-four WHR_adjBMI loci showing significant sex-differences.

<p>Chr: Chromosome; Pos: position; EAF: Effect Allele Frequency; EA: Effect allele; OA: Other allele</p><p>^a ‘Yes’ if the locus is mentioned as WHR_adjBMI locus for the first time</p><p>^b ‘Yes’ if the sex-difference in the effect on WHR_adjBMI is reported for the first time</p><p>^c Effect allele is according to the WHR_adjBMI increasing allele according to the associated sex.</p><p>The table shows the sex-specific (age-group combined) results, ordered by largest, positive effect in women to largest, negative effect in women. The age- and sex-specific results (four strata), more detailed information on the loci and on the screens for which they were detected are given in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005378#pgen.1005378.s021" target="_blank">S5 Table</a></b>.</p

Fifteen BMI loci showing significant age-differences in adults ≤50y compared to adults >50y.

<p>Chr: Chromosome; Pos: position; EAF: Effect Allele Frequency; EA: Effect allele; OA: Other allele</p><p>^a ‘Yes’ if the locus is mentioned as BMI locus for the first time</p><p>^b Effect allele is according to the BMI increasing allele according to the associated sex.</p><p>The table shows the age-group specific (sex-combined) results, ordered by largest to smallest effect in adults ≤50y. All loci were detected by the screen on age-difference that included the a-priori filter on <i>P</i>_{<i>Overall</i>} < 10⁻⁵. The age- and sex-specific results (four strata) and more detailed information on the loci are given in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005378#pgen.1005378.s020" target="_blank">S4 Table</a></b>.</p

Power heatplots.

<p>Power for the combination of screens and gain through a priori filtering for varying configurations of effect sizes across the 4 strata. The figures illustrate (A) the power to detect age-difference, sex-difference or age-sex-difference in at least one of our scans (on <i>P</i>_{<i>agediff</i>}, <i>P</i>_{<i>sexdiff</i>} and <i>P</i>_{<i>agesexdiff</i>}, with and without a priori filtering); and (B) a power comparison, comparing approaches with and without a priori filtering on <i>P</i>_{<i>Overall</i>} < 1x10^-5. We here assume four equally sized strata and a total sample size of N = 300,000 (comparable to the sample size in our BMI analyses). We set b_F≤50y = 0.033 (corresponding to a known and mean BMI effect in <i>MAP2K5</i> region with R² = 0.037%), b_M>50y = 0, and vary b_F>50y and b_M≤50 on the axes. This strategy allows us to cover the most interesting and plausible interaction effects: Two-way interactions, such as (i) pure age-difference (b_≤50y = 0.033, b_>50y = 0) and (ii) pure sex-difference (b_F = 0.033, b_M = 0); and three-way interactions, such as (iii) extreme three-way interaction with opposite direction across AGE and SEX, (iv) 1-strata interaction (b_F≤50y = 0.033, b_F>50y = b_M≤50y = b_M>50y = 0), and (v) 3-strata interaction (b_F≤50y = b_F>50y = b_M≤50y = 0.033, b_M>50y = 0).</p

Sex-dependent WHR_adjBMI loci.

<p>Effect estimates (beta ± 95CI) per standard deviation in WHR_adjBMI and risk allele for loci showing sex-differences in women compared to men. Loci are ordered by greater magnitude of effect in women compared to men. (95%CI: 95% confidence interval; SD: standard deviation. *Newly identified loci. † Newly identified sex-differences)</p

Enrichment analyses using look-up data for the 15 age-group specific BMI loci.

<p>^a One-sided binomial P-values that test for enrichment of nominal significant and directionally consistent association in the look-up data.</p><p>^b For the BMI increasing alleles of the 11 SNPs with stronger effect on BMI in ≤50y, we expect to see a nominal significant association with increased birth weight, increased risk for childhood obesity and increased BMI in the 16–25y age-group.</p><p>^c For the BMI increasing alleles of the 11 SNPs with stronger effect on BMI in ≤50y, we expect to see a nominal significant association with negative effect on weight change (weight loss), and for the BMI increasing alleles of the four SNPs with stronger effect on BMI in >50y, we expect to see a nominal significant association with positive effect on weight change (weight gain) (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005378#sec017" target="_blank">Methods</a> for details).</p><p>The look-up data is taken from the EGG consortium for birth weight and for childhood obesity, and from personal communication for weight change trajectories. More details including SNP specific effect sizes or odds ratios and association P-Values on the look-up trait can be found in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005378#pgen.1005378.s031" target="_blank">S15 Table</a></b> (for birth weight), <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005378#pgen.1005378.s032" target="_blank">S16 Table</a></b> (for childhood obesity) and <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005378#pgen.1005378.s034" target="_blank">S18 Table</a></b> (for weight change).</p