Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Abstract

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

Figure 1

Q-Q plot of the −log₁₀ p-values for the difference between the observed association for the tails of BMI and expected association based on the overall BMI distribution.

Figure 2. Variance in extreme obesity explained by common genetic variants

The phenotypic variance explained is higher when SNPs with lower degrees of significance are included in the polygenetic prediction model. The y-axis represents the proportion of variance explained (Nagelkerke R²) of extreme obesity in six studies not included in the discovery meta-analysis. In panel A, the prediction model was based on the results from the stage I meta-analysis of tails of BMI. The thicker lines represent the weighted average; 95% confidence intervals are reported as double-headed arrows. In panel B, the prediction model was based on BMI from the full distribution (modified version of the previous GIANT meta-analysis by Speliotes et al). * Essen Obesity Study was not adjusted by age.