Class II HLA interactions modulate genetic risk for multiple sclerosis

Abstract

Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01-HLA-DRB1*15:01 and HLA-DQB1*03:01-HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles.

Figure 1

Overview of genetic effects in the HLA region influencing risk for multiple sclerosis. The relative locations of the classical HLA loci are shown (central bar) along with forest plots for each of the major effects identified. Each forest plot shows the estimated odds ratio from the cohort-specific logistic model and the 95% confidence interval, with point size proportional to sample size and the cohorts ordered by size (Supplementary Table 1). The bottom point for each locus and the corresponding red dashed line show the result from fixed-effect meta-analysis (META). Plot background indicates the nature of the effect: none, main effect; blue, departure from additivity; pink, interaction. The lead allele for each signal is indicated. The solid black line represents OR = 1 for additive effects and the expected homozygote effect for departures from additivity. Curly brackets represent an indicator function that combines heterozygotes and homozygotes into a single category. HOM, homozygote.

Figure 2

Evidence for interactions with associated HLA alleles. Results are shown here for HLA-DRB1*15:01 (top row), HLA-A*02:01 (middle row) and HLA-DQB1*03:02 (bottom row). Results for the other associated HLA alleles are shown in Supplementary Figures 3–5. (a) Quantile-quantile plot showing the distribution of P values for the interaction terms between the indicated multiple sclerosis–associated allele and all 152 other classical HLA alleles analyzed. (b) Quantile-quantile plot showing the distribution of P values for the interaction terms with the 98 previously identified non-HLA multiple sclerosis–associated alleles. In each plot in a and b, the red line represents the expected relationship, and dashed lines represent the 95% confidence interval. (c) The effect of the indicated allele among individuals stratified in quartiles by a combined non-HLA risk score. The point estimate and 95% confidence interval for effect size are estimated independently for each quartile of non-HLA genetic risk. For each plot, the dashed and dotted lines represent the combined point estimate and 95% confidence interval, respectively. All analyses are for the UK cohort only. Interaction analyses included all non-epistatic effects within the model of Figure 1, including non-additive effects of the indicated allele.

Figure 3

Estimates of polygenic epistasis influencing the effects of major HLA loci on multiple sclerosis. Point estimates (X’s) and 95% confidence intervals (lines; floored to zero) are shown for the ratio of the standard deviation in effect induced by genome-wide polygenic epistasis to the absolute magnitude of the average effect size for classical HLA alleles influencing risk of multiple sclerosis. Results are shown from fixed-effect meta-analysis across cohorts. Under a simple model (Supplementary Note), this factor can be estimated by comparing the difference in apparent heritability for major alleles between cases and controls. The dashed lines at 0 and 1 indicate, respectively, the case with no epistasis and the case where the standard deviation in the epistatically induced effect equals the average main effect.

Figure 4

HLA effects on age at onset. The point estimate and 95% confidence interval are shown for each cohort (with the area of each square proportional to sample size) along with the meta-analysis estimate (META; brown dashed line). (a) Forest plots showing fixed-effect meta-analysis of the effect of combined HLA risk score (Online Methods) on age at onset of multiple sclerosis. (b,c) Meta-analysis of the effects of the HLA-DRB1*15:01 (b) and HLA-DRB1*01:01 (c) alleles on age at onset (results for HLA-DQB1*06:02 and HLA-DQA1*01:01 are shown in Supplementary Fig. 7).