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Locus and gene-based GWAS meta-analysis identifies new diabetic nephropathy genes

机译:基于基于遗迹和基因的GWAS Meta分析鉴定了新的糖尿病肾病基因

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摘要

Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due to a paucity of genes identified despite several GWAS. OASIS was applied to three DN dbGAP GWAS datasets (4725 subjects; 1.06 million SNPs). OASIS identified 19 DN genes which were verified using single variant replication in a standard association study and gene-based analysis using GATES. CARS and FRMD3 were confirmed as DN genes, and five known diabetes-associated genes, viz. NLRP3, INPPL1, PIK3C2G, NRXN3, and TBC1D4, not previously identified using these datasets were discovered. Furthermore, three additional novel DN genes were found which replicated in two sets of analysis, viz. NTN1, EBF2, and DNAH11. Hence, composite analysis with OASIS, gene-based, and single variant association testing can be universally applied to existing GWAS datasets for the identification of new genes.
机译:客观同化SNPs在同步(OASIS)中相互作用的是最近描述的基于基于轨迹的聚类算法,其可能在基因组 - 宽协会研究(GWAS)的复杂疾病中来解决误报和否定。由于尽管几个GWAS所鉴定的基因缺乏,糖尿病肾病(DN)被不完全理解。 OASIS应用于三个DN DBGAP GWAS数据集(4725个受试者; 1,06百万个SNP)。 OASIS确定了19dN基因,在标准关联研究和基于基因的基于基因分析中使用单一变体复制进行验证。汽车和FRMD3被证实为DN基因,以及五种已知的糖尿病相关基因,VIZ。发现NLRP3,INPPL1,PIK3C2G,NRXN3和TBC1D4未以前未使用这些数据集识别。此外,发现了三种额外的新型DN基因,其在两组分析中复制,VIZ。 NTN1,EBF2和DNAH11。因此,具有绿洲,基因和单变种关联测试的复合分析可以普遍应用于现有的GWAS数据集以识别新基因。

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