Improved Detection of Common Variants Associated with Schizophrenia by Leveraging Pleiotropy with Cardiovascular-Disease Risk Factors
Improved Detection of Common Variants Associated with Schizophrenia by Leveraging Pleiotropy with Cardiovascular-Disease Risk Factors
复制标题
DOI：
10.1016/j.ajhg.2013.01.001
复制
发表时间：
2013-02-07
影响因子：
9.8
通讯作者：
Dale, Anders M.
中科院分区：
文献类型：
--
作者：
Andreassen, Ole A.;Djurovic, Srdjan;Dale, Anders M.
一些证据表明，全基因组关联研究（GWAS）有可能解释更多常见复杂表型的“缺失遗传力”。然而，目前缺乏用于鉴定更大比例的SNP的可靠方法。在这里，我们提出了一个遗传多效性知情的方法，提高基因发现与GWAS汇总统计数据的使用。我们应用这种方法来确定与精神分裂症（SCZ），一个高度遗传性疾病与显着缺失的遗传性相关的其他基因座。流行病学和临床研究表明，SCZ和心血管疾病（CVD）的危险因素，包括收缩压，甘油三酯，低密度脂蛋白和高密度脂蛋白，体重指数，腰臀比和2型糖尿病之间的共病。使用分层分位数-分位数图，我们显示了与SCZ相关的SNPs的富集作为与几个CVD危险因素相关的函数，以及相应的错误发现率（FDR）的降低。我们通过在独立的SCZ子研究中证明复制率增加来验证这种“多效性富集”。应用分层FDR方法，我们确定了25个位点与SCZ在条件FDR水平为0.01。其中，10个位点与SCZ和CVD风险因素相关，主要是甘油三酯和低密度和高密度脂蛋白，但也与腰臀比，收缩压和体重指数相关。总之，这些研究结果表明，使用遗传多效性知情的方法来改善SCZ中的基因发现并确定与各种CVD风险因素的潜在机制关系是可行的。
Several lines of evidence suggest that genome-wide association studies (GWASs) have the potential to explain more of the "missing heritability" of common complex phenotypes. However, reliable methods for identifying a larger proportion of SNPs are currently lacking. Here, we present a genetic-pleiotropy-informed method for improving gene discovery with the use of GWAS summary-statistics data. We applied this methodology to identify additional loci associated with schizophrenia (SCZ), a highly heritable disorder with significant missing heritability. Epidemiological and clinical studies suggest comorbidity between SCZ and cardiovascular-disease (CVD) risk factors, including systolic blood pressure, triglycerides, low- and high-density lipoprotein, body mass index, waist-to-hip ratio, and type 2 diabetes. Using stratified quantile-quantile plots, we show enrichment of SNPs associated with SCZ as a function of the association with several CVD risk factors and a corresponding reduction in false discovery rate (FDR). We validate this "pleiotropic enrichment" by demonstrating increased replication rate across independent SCZ substudies. Applying the stratified FDR method, we identified 25 loci associated with SCZ at a conditional FDR level of 0.01. Of these, ten loci are associated with both SCZ and CVD risk factors, mainly triglycerides and low- and high-density lipoproteins but also waist-to-hip ratio, systolic blood pressure, and body mass index. Together, these findings suggest the feasibility of using genetic-pleiotropy-informed methods for improving gene discovery in SCZ and identifying potential mechanistic relationships with various CVD risk factors.