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What has GWAS done for HLA and disease associations?
Author(s) -
Kennedy A. E.,
Ozbek U.,
Dorak M. T.
Publication year - 2017
Publication title -
international journal of immunogenetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.41
H-Index - 47
eISSN - 1744-313X
pISSN - 1744-3121
DOI - 10.1111/iji.12332
Subject(s) - genetics , biology , major histocompatibility complex , human leukocyte antigen , single nucleotide polymorphism , pseudogene , genome wide association study , haplotype , linkage disequilibrium , gene , genetic association , genome , computational biology , allele , antigen , genotype
Summary The major histocompatibility complex ( MHC ) is located in chromosome 6p21 and contains crucial regulators of immune response, including human leucocyte antigen ( HLA ) genes, alongside other genes with nonimmunological roles. More recently, a repertoire of noncoding RNA genes, including expressed pseudogenes, has also been identified. The MHC is the most gene dense and most polymorphic part of the human genome. The region exhibits haplotype‐specific linkage disequilibrium patterns, contains the strongest cis‐ and trans‐ eQTL s/me QTL s in the genome and is known as a hot spot for disease associations. Another layer of complexity is provided to the region by the extreme structural variation and copy number variations. While the HLA ‐B gene has the highest number of alleles, the HLA ‐ DR / DQ subregion is structurally most variable and shows the highest number of disease associations. Reliance on a single reference sequence has complicated the design, execution and analysis of GWAS for the MHC region and not infrequently, the MHC region has even been excluded from the analysis of GWAS data. Here, we contrast features of the MHC region with the rest of the genome and highlight its complexities, including its functional polymorphisms beyond those determined by single nucleotide polymorphisms or single amino acid residues. One of the several issues with customary GWAS analysis is that it does not address this additional layer of polymorphisms unique to the MHC region. We highlight alternative approaches that may assist with the analysis of GWAS data from the MHC region and unravel associations with all functional polymorphisms beyond single SNP s. We suggest that despite already showing the highest number of disease associations, the true extent of the involvement of the MHC region in disease genetics may not have been uncovered.