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利用多效性 cFDR 方法检测到与体重指数和冠状动脉疾病相关的新型常见变异。

Novel common variants associated with body mass index and coronary artery disease detected using a pleiotropic cFDR method.

机构信息

College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China.

Department of Geriatrics, Renmin Hospital of Wuhan University, Hubei Zhang Road (Formerly Ziyang Road), Wuchang District No. 99 Jiefang Road 238, Wuhan 430060, People's Republic of China.

出版信息

J Mol Cell Cardiol. 2017 Nov;112:1-7. doi: 10.1016/j.yjmcc.2017.08.011. Epub 2017 Aug 24.

Abstract

Genome-wide association studies (GWAS) have been successfully applied in identifying single nucleotide polymorphisms (SNPs) associated with body mass index (BMI) and coronary heart disease (CAD). However, the SNPs to date can only explain a small percentage of the genetic variances of traits. Here, we applied a genetic pleiotropic conditional false discovery rate (cFDR) method that combines summary statistic p values from different multi-center GWAS datasets, to detect common genetic variants associated with these two traits. The enrichment of SNPs associated with BMI and CAD was assessed by conditional Q-Q plots and the common variants were identified by the cFDR method. By applying the cFDR level of 0.05, 7 variants were identified to be associated with CAD (2 variants being novel), 34 variants associated with BMI (11 variants being novel), and 3 variants associated with both BMI and CAD (2 variants being novel). The SNP rs653178 (ATXN2) is noteworthy as this variant was replicated in an independent analysis. SNP rs12411886 (CNNM2) and rs794356 (HIP1) were of note as the annotated genes may be associated with processes that are functionally important in lipid metabolism. In conclusion, the cFDR method identified novel variants associated with BMI and/or CAD by effectively incorporating different GWAS datasets.

摘要

全基因组关联研究(GWAS)已成功应用于鉴定与体重指数(BMI)和冠心病(CAD)相关的单核苷酸多态性(SNP)。然而,迄今为止,SNP 只能解释特征遗传变异的一小部分。在这里,我们应用了一种遗传多效性条件假发现率(cFDR)方法,该方法结合了来自不同多中心 GWAS 数据集的汇总统计 p 值,以检测与这两种特征相关的常见遗传变异。通过条件 Q-Q 图评估与 BMI 和 CAD 相关的 SNP 的富集,通过 cFDR 方法鉴定常见变异。通过应用 cFDR 水平为 0.05,鉴定出 7 个与 CAD 相关的变体(2 个是新的),34 个与 BMI 相关的变体(11 个是新的),以及 3 个与 BMI 和 CAD 相关的变体(2 个是新的)。SNP rs653178(ATXN2)值得注意,因为该变体在独立分析中得到了复制。SNP rs12411886(CNNM2)和 rs794356(HIP1)值得注意,因为注释基因可能与脂质代谢过程中的功能重要性有关。总之,cFDR 方法通过有效整合不同的 GWAS 数据集,鉴定出与 BMI 和/或 CAD 相关的新变体。

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