Genome-wide association of copy-number variation reveals an association between short stature and the presence of low-frequency genomic deletions

Abstract

Height is a model polygenic trait that is highly heritable. Genome-wide association studies have identified hundreds of single-nucleotide polymorphisms associated with stature, but the role of structural variation in determining height is largely unknown. We performed a genome-wide association study of copy-number variation and stature in a clinical cohort of children who had undergone comparative genomic hybridization (CGH) microarray analysis for clinical indications. We found that subjects with short stature had a greater global burden of copy-number variants (CNVs) and a greater average CNV length than did controls (p < 0.002). These associations were present for lower-frequency (<5%) and rare (<1%) deletions, but there were no significant associations seen for duplications. Known gene-deletion syndromes did not account for our findings, and we saw no significant associations with tall stature. We then extended our findings into a population-based cohort and found that, in agreement with the clinical cohort study, an increased burden of lower-frequency deletions was associated with shorter stature (p = 0.015). Our results suggest that in individuals undergoing copy-number analysis for clinical indications, short stature increases the odds that a low-frequency deletion will be found. Additionally, copy-number variation might contribute to genetic variation in stature in the general population.

Figure 1

Height Distribution of 4,411 Subjects in the Clinical Cohort

Figure 2

Quantile-Quantile Plot of p Values for Regional-CNV Association Analysis Quantile-quantile plots for deletion and duplication CNVs are plotted separately. The x axis represents the negative log p value for the expected distribution of p values, and the y axis represents the negative log p value for the observed p values. The circles forming a horizontal line at a negative log p value of ∼5 on the y axis represent regions where there are no simulations with summed Z scores more extreme than our observed data. These areas represent regions with CNVs whose associations with stature have experiment-wide significance.