Novel linkage disequilibrium clustering algorithm identifies new lupus genes on meta-analysis of GWAS datasets.
Novel linkage disequilibrium clustering algorithm identifies new lupus genes on meta-analysis of GWAS datasets.
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DOI：
10.1007/s00251-017-0976-8
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发表时间：
2017-05
期刊：
影响因子：
3.2
通讯作者：
Saeed M
中科院分区：
文献类型：
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作者：
Saeed M
系统性红斑狼疮（SLE）是一种复杂的疾病。复杂疾病的遗传关联研究存在以下三个主要问题：表型异质性、假阳性（I型错误）和假阴性（II型错误）结果。因此，在标准分析中，特别是在统计校正之后，具有低至中等影响的基因被遗漏。OASIS是一种新型的连锁不平衡聚类算法，可以潜在地解决复杂疾病（如SLE）的全基因组关联研究（GWAS）中的假阳性和假阴性。OASIS应用于两个SLE dbGAP GWAS数据集（6077名受试者; 175万个单核苷酸多态性）。OASIS确定了三个已知的SLE基因，即IFIH 1，TNIP 1和CD 44，以前没有使用这些GWAS数据集报道。此外，还发现了22个新的SLE基因位点，并验证了先前使用这些数据集报道的5个SLE基因。使用GATES的单变异复制和基于基因的分析来验证OASIS方法。这导致了60%的OASIS位点的验证。OASIS鉴定并进一步验证的新SLE基因包括TNFAIP 6、DNAJB 3、TTF 1、GRIN 2B、MON 2、LATS 2、SNX 6、RBFOX 1、NCOA 3和CHAF 1B。这项研究提出了OASIS算法，软件，以及两个公开可用的SLE GWAS数据集的荟萃分析沿着新的SLE基因。因此，OASIS是一种新的连锁不平衡聚类方法，可以普遍应用于现有的GWAS数据集的新基因的识别。本文的在线版本（doi：10.1007/s 00251 -017-0976-8）包含补充材料，可供授权用户使用。
Systemic lupus erythematosus (SLE) is a complex disorder. Genetic association studies of complex disorders suffer from the following three major issues: phenotypic heterogeneity, false positive (type I error), and false negative (type II error) results. Hence, genes with low to moderate effects are missed in standard analyses, especially after statistical corrections. OASIS is a novel linkage disequilibrium clustering algorithm that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders such as SLE. OASIS was applied to two SLE dbGAP GWAS datasets (6077 subjects; ∼0.75 million single-nucleotide polymorphisms). OASIS identified three known SLE genes viz. IFIH1, TNIP1, and CD44, not previously reported using these GWAS datasets. In addition, 22 novel loci for SLE were identified and the 5 SLE genes previously reported using these datasets were verified. OASIS methodology was validated using single-variant replication and gene-based analysis with GATES. This led to the verification of 60% of OASIS loci. New SLE genes that OASIS identified and were further verified include TNFAIP6, DNAJB3, TTF1, GRIN2B, MON2, LATS2, SNX6, RBFOX1, NCOA3, and CHAF1B. This study presents the OASIS algorithm, software, and the meta-analyses of two publicly available SLE GWAS datasets along with the novel SLE genes. Hence, OASIS is a novel linkage disequilibrium clustering method that can be universally applied to existing GWAS datasets for the identification of new genes. The online version of this article (doi:10.1007/s00251-017-0976-8) contains supplementary material, which is available to authorized users.