Are Interactions between cis-Regulatory Variants Evidence for Biological Epistasis or Statistical Artifacts?

Abstract

The importance of epistasis-or statistical interactions between genetic variants-to the development of complex disease in humans has been controversial. Genome-wide association studies of statistical interactions influencing human traits have recently become computationally feasible and have identified many putative interactions. However, statistical models used to detect interactions can be confounded, which makes it difficult to be certain that observed statistical interactions are evidence for true molecular epistasis. In this study, we investigate whether there is evidence for epistatic interactions between genetic variants within the cis-regulatory region that influence gene expression after accounting for technical, statistical, and biological confounding factors. We identified 1,119 (FDR = 5%) interactions that appear to regulate gene expression in human lymphoblastoid cell lines, a tightly controlled, largely genetically determined phenotype. Many of these interactions replicated in an independent dataset (90 of 803 tested, Bonferroni threshold). We then performed an exhaustive analysis of both known and novel confounders, including ceiling/floor effects, missing genotype combinations, haplotype effects, single variants tagged through linkage disequilibrium, and population stratification. Every interaction could be explained by at least one of these confounders, and replication in independent datasets did not protect against some confounders. Assuming that the confounding factors provide a more parsimonious explanation for each interaction, we find it unlikely that cis-regulatory interactions contribute strongly to human gene expression, which calls into question the relevance of cis-regulatory interactions for other human phenotypes. We additionally propose several best practices for epistasis testing to protect future studies from confounding.

Figure 1

Workflow Used to Identify and Group ieQTL In the discovery analysis, nominally significant cis-eQTL (denoted by triangles) were paired together and tested for interactions significantly associated with gene expression levels (denoted by arcs). The within-pair LD was then calculated (Figure S1), and interactions composed of variants in modest LD (r² > 0.6) with one another were removed from the remainder of the analysis. Some of the remaining interactions represented the same pair of interacting genomic loci (Figure S2) and were partitioned into distinct groups (denoted by the arc color). For two interactions to be grouped together, each SNP within one significant ieQTL model had to be in high LD (r² ≥ 0.9) with a SNP within the second ieQTL model, and vice versa.

Figure 2

The Interaction between rs1783165 and rs1673426 Associated with the Expression of PKHD1L1 May Be a Ceiling Effect The ceiling effect, caused by limitations in the detectable range of gene expression, has a hallmark pattern—both variants have main effects with concordant direction of effect, and the interaction term has a discordant direction. (A and B) The minor allele of rs1673426 (A) increases the expression of PKHD1L1. The minor allele of rs1783165 (B) also increases the expression of PKHD1L1, meaning both variants have a concordant direction of effect. (C) The interaction plot depicts the mean gene expression for all individuals with the specified genotype combination, with each line representing the number of minor alleles at rs1673426. When there is only one minor allele at rs1673426, the mean gene expression increases for each minor allele at rs1783165; however, when there are two minor alleles at rs1673426, the increase in gene expression due to minor alleles at rs1783165 reaches a “maximum” at one minor allele. There is no additional increase in expression for having two minor alleles at rs1783165. This is denoted by the flat line connecting the two genotype combinations. Given that each minor allele at rs1783165 increases gene expression on the background of one minor allele at rs1673426, and that the maximum reached on the background of two minor alleles at rs1673426 is very close to the maximum gene expression levels possible to observe, we consider this an example of the ceiling effect.

Figure 3

Interactions Impacting the Expression of CPEB4 May Represent Haplotype Effects (A) A significant interaction between rs6864691 and rs969518 regulating the expression of CPEB4 was identified. The cis-eQTL rs72812817 mediated this interaction in the conditional analysis; however, none of these variants were within putative regulatory elements in GM12878 assayed by the ENCODE Project. (B) However, a D′ heatmap of the region (the numbers correspond to SNP labels in A) illustrated that an indel, rs144869372, always occurred on the background of the cis-eQTL (D′ = 1). (C) This occurs despite modest r² values, as shown in the r² heatmap of the region. There is evidence from ENCODE (A) suggesting the indel may be functional, as it occurs within both a ChromHMM strong enhancer (yellow) and a CTCF binding peak in GM12878. (D) Notably, the indel is predicted to alter the binding of CTCF by HaploReg, by altering the last three nucleotides in the binding motif. Given the functional genomics evidence, the indel may be the causal variant and is detected by interactions that tag the haplotype carrying the indel.

Figure 4

The Interacting SNPs Regulating ACCS Are Probably Tagging a Single-Variant cis-eQTL through Linkage Disequilibrium The interaction between rs178501 and rs7121151 is mediated by the cis-eQTL rs2074038 in the conditional analysis (interaction p value > 0.05). (A) While the interacting variants are in low LD with the cis-eQTL based on r², their high D′ indicates they often occur on the same haplotype. (B) The interacting variants are not located within DNase hypersensitivity sites, predicted chromatin states with a regulatory function (GM12878 Combined), or any of the uniform binding peaks identified for all transcription factors tested in GM12878 by ENCODE; however, the cis-eQTL is located within the canonical promoter for ACCS, a DNase hypersensitivity site, and numerous transcription factor binding peaks identified in GM12878 by ENCODE. (C) Notably, the cis-eQTL occurs within a binding peak for both ELF1 and SPI1 in GM12878 and also alters the binding motifs of these transcription factors at the position highlighted in orange. Thus, the cis-eQTL rs2074038 is probably the causal variant, and the interaction is simply capturing its effect through LD.

Figure 5

Population-Specific eQTLs May Underlie ieQTL Regulating C12orf54 The interaction between rs2731091 and rs4760707 regulating C12orf54 replicated but was not nominally significant (p < 0.05) in any population in the stratified analysis. (A) Due to the population normalization procedure, there are not systematic differences in the expression of C12orf54 between populations; however, we found that each variant was a population-specific cis-eQTL. (B) rs4760707 was a cis-eQTL in CHB+JPT (p = 7.25 × 10⁻⁶) but not in YRI (p = 0.17) or CEU (p = 0.96). (C) rs2731091 significantly regulated gene expression as a cis-eQTL in YRI (p = 7.28 × 10⁻⁶) but not CEU (p = 0.14) or CHB+JPT (p = 0.84). (D) There were clear population differences in the frequency of two-locus genotypes between populations; in combination, it appears the population differences in two-locus genotypes and population-specific cis-eQTL produced a nuanced form of population stratification.

Figure 6

Despite Consistent Replication, the Interaction Regulating MYRFL Is Attributable to cis-eQTL (A–E) In each interaction plot, all individuals are categorized according to their two-locus genotype at rs1262808 and rs11615099. The mean expression of MYRFL for all individuals with each of the nine possible two-locus genotypes is shown here for the (A) discovery, (B) replication, (C) Mayo, cerebellum, (D) Mayo, cortex, (E) GTEx, whole blood datasets. The interaction plot illustrates a consistent trend across all datasets, this interaction is mediated by cis-eQTL. (F) Conditional cis-eQTL analyses were conducted in the discovery (CEU only, yellow); GTEx (purple); Mayo, cerebellum (teal); and Mayo, temporal cortex (orange). For each conditional analysis, the conditional LRT p value is plotted by the genomic position of the cis-eQTL conditioned on. The p value peak observed in this region illustrates that cis-eQTL completely attenuate the interaction when they are conditioned on.