Interrogating the major histocompatibility complex with high-throughput genomics

被引:75
作者
de Bakker, Paul I. W. [1 ,2 ,3 ,5 ]
Raychaudhuri, Soumya [3 ,4 ,5 ,6 ,7 ]
机构
[1] Univ Med Ctr Utrecht, Dept Med Genet, NL-3508 GA Utrecht, Netherlands
[2] Univ Med Ctr Utrecht, Dept Epidemiol, NL-3508 GA Utrecht, Netherlands
[3] Harvard Univ, Brigham & Womens Hosp, Sch Med, Div Genet, Boston, MA 02115 USA
[4] Harvard Univ, Brigham & Womens Hosp, Sch Med, Div Rheumatol, Boston, MA 02115 USA
[5] Broad Inst Harvard & MIT, Program Med & Populat Genet, Cambridge, MA USA
[6] Partners HealthCare Ctr Personalized Genet Med, Boston, MA USA
[7] Univ Manchester, Fac Med & Human Sci, Manchester, Lancs, England
基金
美国国家卫生研究院;
关键词
PEPTIDE-BINDING POCKET; CLASSICAL HLA ALLELES; HIGH-RESOLUTION HLA; EXTENDED HUMAN MHC; DISEASE ASSOCIATION; MULTIPLE-SCLEROSIS; WIDE ASSOCIATION; RHEUMATOID-ARTHRITIS; CELIAC-DISEASE; GRAVES-DISEASE;
D O I
10.1093/hmg/dds384
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
070307 [化学生物学]; 071010 [生物化学与分子生物学];
摘要
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.
引用
收藏
页码:R29 / R36
页数:8
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