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. 2011 Oct 15;20(20):4082-92.
doi: 10.1093/hmg/ddr328. Epub 2011 Jul 28.

Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association

Andrew R Wood  1 , Dena G Hernandez, Michael A Nalls, Hanieh Yaghootkar, J Raphael Gibbs, Lorna W Harries, Sean Chong, Matthew Moore, Michael N Weedon, Jack M Guralnik, Stefania Bandinelli, Anna Murray, Luigi Ferrucci, Andrew B Singleton, David Melzer, Timothy M Frayling
Affiliations

Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association

Andrew R Wood et al. Hum Mol Genet. .

Abstract

The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.

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Figures

Figure 1.
Figure 1.
Effects of including two associated cis-eQTL SNPs in multivariable analyses. Plots show position of SNPs on the X-axis and –log10 P-values for association with cis gene expression on the Y-axis. The red diamonds represent the individual (univariable) statistics for the Index HapMap SNP and the second HapMap SNP. The two green diamonds represent the associations of the same two SNPs when accounting for the correlation between the two SNPs using a multivariable model. Estimated haplotype effects are shown underneath each plot, where ‘2’ represents an allele associated with increased gene expression, and ‘1’ represents an allele associated with reduced gene expression. Alleles on haplotypes are ordered by chromosomal position. (A and B) Examples of ‘jumpers’, pairs of SNPs that both increase in significance in the multivariable compared with univariable models at the FN3KRP and STAT6 loci, respectively. (C and D) Examples of ‘stickers’, pairs of SNPs that remain very similar in significance in the multivariable compared with univariable models at the GNLY and CPVL loci, respectively. (E and F) Examples of ‘fallers’, pairs of SNPs that both reduce in significance in multivariable compared with univariable models at the C17ORF97 and TIMM10 loci, respectively.
Figure 2.
Figure 2.
The correlation between how pairs of SNPs change in significance between univariable (single SNP) and multivariable (two SNP) models and the LD between them.
Figure 3.
Figure 3.
Effects of including three associated cis-eQTL SNPs in multivariable analyses. Bars represent association with cis gene expression for three SNPs per locus—from left to right: the Index HapMap SNP; the Second HapMap SNP; and the 1000G SNP. Black bars represent the association of the SNP with cis gene expression without taking into account correlation (due to LD) with any other SNPs (univariable analysis). The remaining bars represent the association of the SNP with cis gene expression while taking into account any correlation with the other two SNPs, both separately in two SNP models and as a single model with all three SNPs (multivariable analyses). (A–D) cis-eQTL with strongest evidence of allelic heterogeneity. (E–H) cis-eQTL loci where two apparently independent signals could represent a single association signal. Estimated haplotype effects are shown underneath each plot, where ‘2’ represents an allele associated with increased gene expression, and ‘1’ represents an allele associated with reduced gene expression. Alleles on haplotypes are ordered by the Index HapMap SNP, the second HapMap SNP and the 1000G SNP.
Figure 3.
Figure 3.
Effects of including three associated cis-eQTL SNPs in multivariable analyses. Bars represent association with cis gene expression for three SNPs per locus—from left to right: the Index HapMap SNP; the Second HapMap SNP; and the 1000G SNP. Black bars represent the association of the SNP with cis gene expression without taking into account correlation (due to LD) with any other SNPs (univariable analysis). The remaining bars represent the association of the SNP with cis gene expression while taking into account any correlation with the other two SNPs, both separately in two SNP models and as a single model with all three SNPs (multivariable analyses). (A–D) cis-eQTL with strongest evidence of allelic heterogeneity. (E–H) cis-eQTL loci where two apparently independent signals could represent a single association signal. Estimated haplotype effects are shown underneath each plot, where ‘2’ represents an allele associated with increased gene expression, and ‘1’ represents an allele associated with reduced gene expression. Alleles on haplotypes are ordered by the Index HapMap SNP, the second HapMap SNP and the 1000G SNP.
Figure 4.
Figure 4.
Effects of including three associated cis-eQTL SNPs in multivariable analyses shown as regional plots. Plots show position of SNPs on the X-axis and –log10 P-value for association with cis gene expression on the Y-axis. The red diamonds represent the individual (univariable) statistics. The green diamonds represent the associations of the same SNPs when accounting for the correlation between each other using a multivariable model. Arrows emphasize the directional change of significance; (A) examples of two loci where inclusion of the 1000G SNP does not reduce the evidence for two independent signals; (B) examples of two loci where a single 1000G SNP appears to account for two apparently independent HapMap cis-eQTL SNP associations.
Figure 4.
Figure 4.
Effects of including three associated cis-eQTL SNPs in multivariable analyses shown as regional plots. Plots show position of SNPs on the X-axis and –log10 P-value for association with cis gene expression on the Y-axis. The red diamonds represent the individual (univariable) statistics. The green diamonds represent the associations of the same SNPs when accounting for the correlation between each other using a multivariable model. Arrows emphasize the directional change of significance; (A) examples of two loci where inclusion of the 1000G SNP does not reduce the evidence for two independent signals; (B) examples of two loci where a single 1000G SNP appears to account for two apparently independent HapMap cis-eQTL SNP associations.
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