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基于通路的全基因组关联研究表明,Rac1通路与血浆脂联素水平相关。

Pathway-Based Genome-wide Association Studies Reveal That the Rac1 Pathway Is Associated with Plasma Adiponectin Levels.

作者信息

Li Wei-Dong, Jiao Hongxiao, Wang Kai, Yang Fuhua, Grant Struan F A, Hakonarson Hakon, Ahima Rexford, Arlen Price R

机构信息

Research Center of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.

Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.

出版信息

Sci Rep. 2015 Aug 24;5:13422. doi: 10.1038/srep13422.

Abstract

Pathway-based analysis as an alternative and effective approach to identify disease-related genes or loci has been verified. To decipher the genetic background of plasma adiponectin levels, we performed genome wide pathway-based association studies in extremely obese individuals and normal-weight controls. The modified Gene Set Enrichment Algorithm (GSEA) was used to perform the pathway-based analyses (the GenGen Program) in 746 European American females, which were collected from our previous GWAS in extremely obese (BMI > 35 kg/m(2)) and never-overweight (BMI<25 kg/m(2)) controls. Rac1 cell motility signaling pathway was associated with plasma adiponectin after false-discovery rate (FDR) correction (empirical P < 0.001, FDR = 0.008, family-wise error rate = 0.008). Other several Rac1-centered pathways, such as cdc42racPathway (empirical P < 0.001), hsa00603 (empirical P = 0.003) were among the top associations. The RAC1 pathway association was replicated by the ICSNPathway method, yielded a FDR = 0.002. Quantitative pathway analyses yielded similar results (empirical P = 0.001) for the Rac1 pathway, although it failed to pass the multiple test correction (FDR = 0.11). We further replicated our pathway associations in the ADIPOGen Consortium data by the GSA-SNP method. Our results suggest that Rac1 and related cell motility pathways might be associated with plasma adiponectin levels and biological functions of adiponectin.

摘要

基于通路的分析作为一种识别疾病相关基因或位点的替代且有效的方法已得到验证。为了解析血浆脂联素水平的遗传背景,我们在极度肥胖个体和正常体重对照中进行了全基因组基于通路的关联研究。使用改良的基因集富集算法(GSEA)对746名欧美女性进行基于通路的分析(GenGen程序),这些样本来自我们之前对极度肥胖(BMI>35kg/m²)和从未超重(BMI<25kg/m²)对照的全基因组关联研究。在错误发现率(FDR)校正后,Rac1细胞运动信号通路与血浆脂联素相关(经验P<0.001,FDR=0.008,家族wise错误率=0.008)。其他几个以Rac1为中心的通路,如cdc42rac通路(经验P<0.001)、hsa00603(经验P=0.003)也在顶级关联之中。RAC1通路关联通过ICSN通路方法得到重复,FDR=0.002。定量通路分析对Rac1通路产生了相似结果(经验P=0.001),尽管它未能通过多重检验校正(FDR=0.11)。我们通过GSA-SNP方法在ADIPOGen联盟数据中进一步重复了我们的通路关联。我们的结果表明,Rac1和相关细胞运动通路可能与血浆脂联素水平及脂联素的生物学功能相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a6e/4642532/0b0825bf6bd5/srep13422-f1.jpg

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