Novel Common Variants Associated With Body Mass Index And Coronary Artery Disease Detected Using A Pleiotropic CFDR Method

Genome-wide association studies(GWAS)have been successful in detecting single nucleotide polymorphisms(SNPs)which are associated with many phenotypes and diseases.Until now,at existing GWAS sample sizes,these variants explain only part of the estimated heritability,no more than 10%.Leverage of GWAS results from related phenotypes may improve detection without increasing recruitments of additional study subjects.The conditional false discovery rate(c FDR)constitutes an upper bound on the expected false discovery rate(FDR)across a set of SNPs whose p values for two diseases are both less than two disease-specific thresholds.Calculation of the c FDR requires only summary statistics and have several advantages over traditional GWAS analysis.Objectives Here,we applied a genetic pleiotropic conditional false discovery rate method that combines summary statistic p values from different multi-center GWAS data of body mass index(BMI)and coronary artery disease(CAD),to detect common genetic variants associated with these two traits.Methods 1.The conditional Q-Q plot was applied to assess the enrichment of SNPs which are associated with obesity and CAD.2.The common variants were identified for obesity and CAD by calculating the c FDR value across a set of SNPs.3.Manhattan plots were conducted to illustrate the SNPs' genomic locations based on the conditional and conjunction FDR values of SNPs.4.The GO term enrichment analysis may provide further insight into the mechanism why individuals with a high BMI may suffer from CAD simultaneously.Results 1.The conditional Q-Q plot for CAD conditioned on BMI showed much enrichment across different levels of significance thresholds,and vice versa 2.Applying the c FDR method at the significance level of 0.05,7 variants were identified to be associated with CAD,5 variants had been reported to be associated with CAD according to the Pub Med and 2 variants were novel.34 variants were associated with BMI,23 variants were associated with BMI earlier and 11 were novel.3.Applying the conjunction FDR method at the significance level of 0.05,three variants were associated with both CAD and BMI.Moreover,one variant was associated with both CAD and BMI earlier,and 2 were novel.The SNP rs653178(ATXN2)is noteworthy as this variant was replicated in an independent analysis.4.Several functional terms were identified to be enriched in the development of BMI or CAD or both.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.Conclusions The c FDR method can improve SNP detection in GWAS by re-analysing existing data,2 and 11 novel SNPs were found to be associated with obesity and CAD,respectively.Two novel SNPs were found to be associated with both obesity and CAD.