Comparison of Genotypic and Phenotypic Correlations: Cheverud's Conjecture in Humans

Abstract

Accurate estimation of genetic correlation requires large sample sizes and access to genetically informative data, which are not always available. Accordingly, phenotypic correlations are often assumed to reflect genotypic correlations in evolutionary biology. Cheverud's conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations is appropriate. Empirical evidence of the conjecture has been found across plant and animal species, with results suggesting that there is indeed a robust relationship between the two. Here, we investigate the conjecture in human populations, an analysis made possible by recent developments in availability of human genomic data and computing resources. A sample of 108,035 British European individuals from the UK Biobank was split equally into discovery and replication datasets. Seventeen traits were selected based on sample size, distribution, and heritability. Genetic correlations were calculated using linkage disequilibrium score regression applied to the genome-wide association summary statistics of pairs of traits, and compared within and across datasets. Strong and significant correlations were found for the between-dataset comparison, suggesting that the genetic correlations from one independent sample were able to predict the phenotypic correlations from another independent sample within the same population. Designating the selected traits as morphological or nonmorphological indicated little difference in correlation. The results of this study support the existence of a relationship between genetic and phenotypic correlations in humans. This finding is of specific interest in anthropological studies, which use measured phenotypic correlations to make inferences about the genetics of ancient human populations.

Keywords: UK Biobank; genetic correlation; genetic proxy; linkage disequilibrium score regression; morphological nonmorphological traits.

Figure 1

Schematic diagram of statistical analyses performed. 108,035 British European individuals were evenly divided into discovery and replication datasets. Genetic and phenotypic correlations were calculated within group for 17 traits. Black arrows show the comparisons performed. Empty gray arrows indicate comparisons similar to the equivalent gray arrow (i.e., the within-replication, between-trait comparison is the same as the within-discovery, between-trait comparison). * Figure 3, Table 2, and † Table 3.

Figure 2

Boxplots of the distribution of estimated SNP-heritabilities for all traits (combined, 17 traits), morphological traits (10 traits), and nonmorphological traits (seven traits). Quantitative traits were selected from the UK Biobank and SNP-heritabilities estimated through LD score regression. Sample sizes used to calculate SNP-heritabilities range from 31,174 to 53,942 individuals.

Figure 3

Plots of genetic correlation vs. phenotypic correlation for the between-dataset comparison. 108,035 British European individuals were distributed into discovery (n = 54,017) and replication (n = 54,018) datasets. Genetic and phenotypic correlations were calculated within group for 17 traits. (A) Genetic correlations from the discovery dataset and phenotypic correlations from the replication dataset. (B) Genetic correlations from the replication dataset and phenotypic correlations from the discovery dataset. The between-trait comparison refers to the correlations between morphological (M) and nonmorphological traits (N).