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


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.

SUBMITTER: Lv WQ 

PROVIDER: S-EPMC5812278 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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

Lv Wan-Qiang WQ   Zhang Xue X   Zhang Qiang Q   He Jing-Yang JY   Liu Hui-Min HM   Xia Xin X   Fan Kun K   Zhao Qi Q   Shi Xue-Zhong XZ   Zhang Wei-Dong WD   Sun Chang-Qing CQ   Deng Hong-Wen HW  

Journal of molecular and cellular cardiology 20170824


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 as  ...[more]

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