Interactions within the MHC contribute to the genetic architecture of celiac disease.
Interactions within the MHC contribute to the genetic architecture of celiac disease.
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DOI：
10.1371/journal.pone.0172826
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Inouye M
中科院分区：
文献类型：
--
作者：
Goudey B;Abraham G;Kikianty E;Wang Q;Rawlinson D;Shi F;Haviv I;Stern L;Kowalczyk A;Inouye M
GWAS的相互作用分析可以检测到单变异分析会忽略的信号，但在人类中很少检测到稳健的相互作用。最近的工作强调了MHC区域中已知的HLA风险单倍型之间的相互作用，用于各种自身免疫性疾病。为了更好地了解乳糜泻（CD）的遗传相互作用，我们在五项独立的CD病例对照研究中对成对相互作用进行了详尽的全基因组扫描，使用快速无模型方法检查了总计超过5000亿个SNP对。我们在MHC区域内发现了14个独立的相互作用信号，这些信号在多项研究中达到了严格的复制标准，并且独立于已知的CD风险HLA单倍型。最强的独立CD相互作用信号对应于HLA III类区域中的基因，特别是PRRC 2A和GPANK 1/C6 orf 47，已知其含有非霍奇金淋巴瘤和早期绝经、乳糜泻的共病的变体。没有观察到MHC外统计学相互作用的可复制证据。在欧洲人群内部和之间，我们观察到惊人的一致性，两个位点的模型和模型分布。在英国人口中，CD模型的基础上的相互作用和添加剂单SNP效应增加了解释CD方差约1%的单SNP。在五个队列中检测到的相互作用信号表明在MHC区域中存在使用加性模型无法检测到的新关联。我们的研究结果对确定遗传结构具有重要意义，并通过扩展，使用人类遗传学来验证治疗靶点。
Interaction analysis of GWAS can detect signal that would be ignored by single variant analysis, yet few robust interactions in humans have been detected. Recent work has highlighted interactions in the MHC region between known HLA risk haplotypes for various autoimmune diseases. To better understand the genetic interactions underlying celiac disease (CD), we have conducted exhaustive genome-wide scans for pairwise interactions in five independent CD case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 14 independent interaction signals within the MHC region that achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD interaction signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for statistical interaction outside the MHC was not observed. Both within and between European populations, we observed striking consistency of two-locus models and model distribution. Within the UK population, models of CD based on both interactions and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. The interactions signal detected across the five cohorts indicates the presence of novel associations in the MHC region that cannot be detected using additive models. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.