Novel loci for glycaemic and obesity-related traits achieving genome-wide significance (<i>p</i><5x10^-8).

<p>Novel loci for glycaemic and obesity-related traits achieving genome-wide significance (<i>p</i><5x10^-8).</p

Regional plots of multiple distinct signals at WHR_adjBMI locus <i>RSPO3</i> (A), FG loci <i>G6PC2</i> (B) and <i>GCK</i> (C).

<p>Regional plots for each locus are displayed from: the unconditional meta-analysis (left); the exact conditional meta-analysis for the primary signal after adjustment for the index variant for the secondary signal (middle); and the exact conditional meta-analysis for the secondary signal after adjustment for the index variant for the primary signal (right). The sample sizes vary due to the availability of the well imputed index SNPs of the primary and secondary signals. Directly genotyped or imputed SNPs are plotted with their association <i>P</i> values (on a -log₁₀ scale) as a function of genomic position (NCBI Build 37). Estimated recombination rates are plotted to reflect the local LD structure around the associated SNPs and their correlated proxies (according to a blue to red scale from <i>r</i>^<i>2</i> = 0 to 1, based on pairwise EUR <i>r</i>^<i>2</i> values from the 1000 Genomes June 2011 release). SNP annotations are as follows: circles, no annotation; downward triangles, nonsynonymous; squares, coding or 3′ UTR; asterisks, TFBScons (in a conserved region predicted to be a transcription factor binding site); squares with an X, MCS44 placental (in a region highly conserved in placental mammals).</p

Loci with multiple distinct signals of association with glycaemic and obesity-related traits achieving “locus-wide” significance in conditional analysis (<i>p</i>_COND<10⁻⁵).

<p>Loci with multiple distinct signals of association with glycaemic and obesity-related traits achieving “locus-wide” significance in conditional analysis (<i>p</i>_COND<10⁻⁵).</p

Broad category functional annotation (A) and cell-type specific annotation (B) of credible set variants.

<p>On the x-axis is each category of broad functional annotation (A) or cell-type specific annotation (B). The fraction of credible set variants that overlap with each category is shown on y-axis. The overlapping variants are further broken down into either variants that exist in both the 1000 Genomes and HapMap reference panel (green) or those that exist only in the 1000 Genomes reference panel (red). TFBS, transcription factor binding site; ncRNA, non-coding RNA; UTR, untranslated regions; GM12878, lymphoblastoid cell line from European ancestry female; hESC, H1 human embryonic stem cells; hASC(t1), human pre-adipocytes; hASC(t4), mature human adipocytes; HepG2, liver carcinoma cell-line; HMEC, human mammary epithelial cells; HSMM, human skeletal muscle myoblasts; HUVEC, human umbilical vein endothelial cells; K562, human myelogenous leukemia cell-line; NHEK, normal human epidermal keratinocytes; NHLF, normal human lung fibroblasts.</p

Association signals for glycaemic and obesity-related traits for which the 99% credible sets contain no more than 20 variants.

<p>Association signals for glycaemic and obesity-related traits for which the 99% credible sets contain no more than 20 variants.</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

Interaction QQ plots.

<p>Quantile-Quantile plots showing P-Values for age-difference (<i>P</i>_{<i>agediff</i>}, green), sex-difference (<i>P</i>_{<i>sexdiff</i>}, blue) and age- and sex-difference (<i>P</i>_{<i>agesexdiff</i>}, purple). For BMI the P-Values are depicted for all SNPs genome-wide (A) as well as for a limited subset of SNPs that survived pre-filtering on the overall association with BMI, <i>P</i>_{<i>Overall</i>} < 1x10^-5 (B). For WHR_adjBMI the P-Values are depicted for all SNPs genome-wide (C) as well as for a limited subset of SNPs that survived pre-filtering on the overall association with WHR_adjBMI, <i>P</i>_{<i>Overall</i>} < 1x10^-5 (D).</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

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

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