Abstract

Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.

Highlights

  • Height is a classic complex trait, which is influenced by both genetic and non-genetic factors

  • This study explores whether a different type of genetic variant might be important

  • We investigate the role of recessive genetic variants, where two identical copies of a variant are required to have an effect

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Summary

Introduction

Height is a classic complex trait, which is influenced by both genetic and non-genetic factors. Within any one population at one point in time, 80–90% of the variation in height is explained by genetic factors [3,4,5,6,7,8] These characteristics, plus the fact that height is cheaply and accurately measurable and has been assessed in many thousands of study subjects, make it an attractive model for investigating the genetic architecture of quantitative traits generally [9,10]. Because height is associated with a range of complex diseases, including cancer, [12,13,14,15] and because pleiotropic effects have been observed between disease-associated and heightassociated genetic variants [16,17,18], a better understanding of the genetic mechanisms influencing height may provide biological insights into disease mechanisms

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