Interrogating the major histocompatibility complex with high-throughput genomics

Abstract

The major histocompatibility complex (MHC) region on the short arm of chromosome 6 harbors the largest number of replicated associations across the human genome for a wide range of diseases, but the functional basis for these associations is still poorly understood. One fundamental challenge in fine-mapping associations to functional alleles is the enormous sequence diversity and broad linkage disequilibrium of the MHC, both of which hamper the cost-effective interrogation in large patient samples and the identification of causal variants. In this review, we argue that there is now a valuable opportunity to leverage existing genome-wide association study (GWAS) datasets for in-depth investigation to identify independent effects in the MHC. Application of imputation to GWAS data facilitates comprehensive interrogation of the classical human leukocyte antigen (HLA) loci. These datasets are, in many cases, sufficiently large to give investigators the ability to disentangle effects at different loci. We also explain how querying variation at individual amino acid positions for association can be powerful and expand traditional analyses that focus only on the classical HLA types.

Figure 1.

Overview of the MHC region with validated GWAS associations from the NHGRI GWAS catalog (http://www.genome.gov/gwastudies/) plotted as a function of position along chromosome 6 (hg18). Strongest SNP associations are annotated by trait or disease. Classical HLA-A, -B, -C, -DP, -DQ and -DR genes are highlighted (red vertical ticks) among the many hundreds of genes across the region.

Figure 2.

Illustration of HLA-DRB1 variation at two-, four- and six-digit resolution. Here we show a subset of the HLA-DRB1 cDNA sequences, using HLA-DRB1*01:01:01 as a reference. Yellow indicates reference alleles within a sequence, and black represents the presence of a non-reference allele. At the two-digit level, allelic differences cluster in specific regions that may influence binding of serological reagents. At the four-digit level, additional non-synonymous polymorphisms are present, so that each four-digit allele defines a unique amino acid sequence. At the six-digit level, synonymous polymorphisms are taken into account.

Figure 3.

Three-dimensional model of the HLA-B protein based on the Protein Data Bank entry 2bvp. Amino acid position 97 is highlighted in the peptide-binding groove, as is the backbone of a peptide bound to the HLA molecule. Variations at position 97 are strongly associated with durable host control of HIV-1 replication, and can explain the observed effects of classical HLA-B alleles, including B*57 and B*27.