Abstract
Genome-wide association studies have identified more than 150 susceptibility loci for coronary artery disease (CAD); however, there is still a large proportion of missing heritability remaining to be investigated. This study sought to identify population-based genetic variation associated with acute coronary syndromes (ACS) in individuals of Chinese Han descent. We proposed a novel strategy integrating a well-developed risk prediction model into control selection in order to lower the potential misclassification bias and increase the statistical power. An exome-wide association analysis was performed for 1,669 ACS patients and 1,935 healthy controls. Promising variants were further replicated using the existing in silico dataset. Additionally, we performed gene- and pathway-based analyses to investigate the aggregate effect of multiple variants within the same genes or pathways. Although none of the association signals were consistent across studies after Bonferroni correction, one promising variant, rs10409124 at STRN4, showed potential impact on ACS in both European and East Asian populations. Gene-based analysis explored four genes (ANXA7, ZNF655, ZNF347, and ZNF750) that showed evidence for association with ACS after multiple test correction, and identification of ZNF655 was successfully replicated by another dataset. Pathway-based analysis revealed that 32 potential pathways might be involved in the pathogenesis of ACS. Our study identified several candidate genes and pathways associated with ACS. Future studies are needed to further validate these findings and explore these genes and pathways as potential therapeutic targets in ACS.
Highlights
Coronary artery disease (CAD) is the leading cause of death worldwide (Naghavi et al, 2017)
Statistics of the discovery-stage is available from the Supplementary Material (Supplementary Data Sheet S1)
Other datasets analyzed during this study were derived from the following public domain resources: Summary statistics of the replication stage is available from CARDIoGRAMplusC4D Consortium and gene expression datasets is available from GEO Profiles
Summary
Coronary artery disease (CAD) is the leading cause of death worldwide (Naghavi et al, 2017). During the past 10 years, several large-scale genome-wide association studies (GWAS) have successfully identified more than 150 loci with robust links to the risk of CAD (Erdmann et al, 2018; van der Harst and Verweij, 2018; Musunuru and Kathiresan, 2019). These variants only explained ∼20% of the observed disease variation, revealing the problem of “missing heritability”. Using exome chip and wholegenome/exome sequencing techniques, several additional lowfrequency coding variants associated with CAD have been detected, e.g., low density lipoprotein cholesterin-related genes (PSCK9, LDLR, and NPC1L1) and triglyceride-related genes (APOA5, APCO3, LPL, and ANGPTL4) (Khera and Kathiresan, 2017). Owing to the differences in LD structure and MAF among different races and ethnicities, it is of great importance to conduct association analyses in nonEuropean populations so as to detect novel loci associated with the risk of CAD
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