The GWAS analysis was performed by each study applying a standardized phenotype transformation to WC or WHR, respectively. Subjects were stratified by gender and the gender-specific rank of either the raw phenotype data or the residuals of a linear regression of the raw phenotype on age and age2 were inverse-normal transformed to yield normally distributed phenotypes. In case-control studies, cases and controls were analyzed separately. The additive genetic effect for each genotyped or imputed SNP was estimated using a linear regression model. For studies where the inverse-normal transformation was performed on raw phenotypes rather than residuals of the phenotype, age and age2 covariates were included in these tests. Some studies used association testing which takes genotype and imputation uncertainty into account using a missing data likelihood test implemented using SNPTEST [34] (http://www.stats.ox.ac.uk/~marchini/software) or by using allele dosages as the independent variable in the linear regression model in MACH2QTL [33] (http://www.sph.umich.edu/csg/abecasis/MACH/download/). To account for the clear gender dimorphism in these traits, analyses were performed in men and women separately, apart from the SardiNIA and deCODE studies for which, due to family
