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논문 기본 정보

자료유형
학술저널
저자정보
Hong Xu (JiangXi Medical College of Nanchang University) Chengxin Gong (JiangXi Medical College of Nanchang University) Yonghu Xu (Jiangxi Medical College of Nanchang University) Yongfang Fan (Jiangxi Medical College of Nanchang University) Xingzi Liu (Jiangxi Medical College of Nanchang University) Chaopeng Xiong (Fuzhou Medical College of Nanchang University) Luling He (JiangXi Medical College of Nanchang University) Changle Liu (JiangXi Medical College of Nanchang University) Shenqiang Rao (JiangXi Medical College of Nanchang University) Wen Xiao (Jiangxi Medical College of Nanchang University) Lu Ding (Jiangxi Medical College of Nanchang University) Lan Tang (Jiangxi Medical College of Nanchang University) Fangfang Hu (Jiangxi Medical College of Nanchang University) Mengqi Xiong (Jiangxi Medical College of Nanchang University) Mei Yang (JiangXi Medical College of Nanchang University) Shangdong Liang (JiangXi Medical College of Nanchang University)
저널정보
한국유전학회 Genes & Genomics Genes & Genomics Vol.38 No.7
발행연도
2016.1
수록면
595 - 600 (6page)

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Diabetic nephropathy (DN) is one of the major complications of diabetes. A tremendous amount of genetic variations have been identified to be associated with DN. However, most of them only generate from statistical associations at the DNA level, generally without direct functional evidence regarding their association mechanisms underlying DN. Based on the publicly available datasets and resources, this study performed integrative analyses (expression quantitative trait loci analysis, differential gene expression analysis and functional prediction analysis) to detect the molecular functional mechanisms underlying the associations for DN. Among 150 selected (P\E-4) genetic associations that were archived in the public databases, two single nucleotide polymorphisms (SNPs) (rs3135377 and rs9469220) have been found to act as cis-effect regulators of the ‘‘identified’’ gene (HLADRA and HLA-DRB1). These eQTL genes have differential expression signals in the DN-associated cell groups. These SNPs were predicted as regulatory sites by utilizing online prediction tools. Our data suggest potential mechanistic links underlying the association between DN and two identified SNPs. These results could help us to have a deeper understanding of the functional relevance of genetic variants with susceptibility to DN, which is useful for pursuit of in-depth validation studies to dissect their involvements and molecular functional mechanisms in DN.

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