Literature DB >> 28877428

What has GWAS done for HLA and disease associations?

A E Kennedy1, U Ozbek2,3, M T Dorak4.   

Abstract

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-eQTLs/meQTLs 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 SNPs. 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.
© 2017 John Wiley & Sons Ltd.

Entities:  

Keywords:  HLA complex; disease predisposition; genetic predisposition to disease; genetic variation; genome biology; genomewide association studies

Mesh:

Substances:

Year:  2017        PMID: 28877428     DOI: 10.1111/iji.12332

Source DB:  PubMed          Journal:  Int J Immunogenet        ISSN: 1744-3121            Impact factor:   1.466


  21 in total

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2.  Defining the genetic control of human blood plasma N-glycome using genome-wide association study.

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Journal:  Hum Mol Genet       Date:  2019-06-15       Impact factor: 6.150

3.  Genetic meta-analysis of cancer diagnosis following statin use identifies new associations and implicates human leukocyte antigen (HLA) in women.

Authors:  Jean-Claude Tardif; Marie-Pierre Dubé; Maxine Sun; Audrey Lemaçon; Marc-André Legault; Géraldine Asselin; Sylvie Provost; Hugues Aschard; Amina Barhdadi; Yassamin Feroz Zada; Diane Valois; Ian Mongrain
Journal:  Pharmacogenomics J       Date:  2021-03-01       Impact factor: 3.550

4.  Evaluation of the major histocompatibility complex (MHC) class II as a candidate for sudden acquired retinal degeneration syndrome (SARDS) in Dachshunds.

Authors:  Stephanie J Stromberg; Sara M Thomasy; Ariana D Marangakis; Soohyun Kim; Ann E Cooper; Emily A Brown; David J Maggs; Danika L Bannasch
Journal:  Vet Ophthalmol       Date:  2019-02-21       Impact factor: 1.644

5.  Interplay between genome-wide implicated genetic variants and environmental factors related to childhood antisocial behavior in the UK ALSPAC cohort.

Authors:  I Hyun Ruisch; Andrea Dietrich; Jeffrey C Glennon; Jan K Buitelaar; Pieter J Hoekstra
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2018-12-19       Impact factor: 5.270

6.  Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function.

Authors:  Maud Fagny; John Platig; Marieke Lydia Kuijjer; Xihong Lin; John Quackenbush
Journal:  Br J Cancer       Date:  2019-12-06       Impact factor: 7.640

7.  MHC Genomics and Disease: Looking Back to Go Forward.

Authors:  Roger L Dawkins; Sally S Lloyd
Journal:  Cells       Date:  2019-08-21       Impact factor: 6.600

8.  Type 1 Diabetes and the HLA Region: Genetic Association Besides Classical HLA Class II Genes.

Authors:  Jana Sticht; Miguel Álvaro-Benito; Stefan Konigorski
Journal:  Front Genet       Date:  2021-06-17       Impact factor: 4.599

9.  Ensuring HLA-matched platelet support requires an ethnic diverse donor population.

Authors:  Aukje L Kreuger; Geert W Haasnoot; Judith A E Somers; Bert Tomson; Johanna G van der Bon; Marian G J van Kraaij; Claudia M Weller
Journal:  Transfusion       Date:  2020-02-22       Impact factor: 3.157

Review 10.  HIV-1 and human genetic variation.

Authors:  Paul J McLaren; Jacques Fellay
Journal:  Nat Rev Genet       Date:  2021-06-24       Impact factor: 53.242

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