...
首页> 外文期刊>PLoS Genetics >Fine Mapping of Five Loci Associated with Low-Density Lipoprotein Cholesterol Detects Variants That Double the Explained Heritability
【24h】

Fine Mapping of Five Loci Associated with Low-Density Lipoprotein Cholesterol Detects Variants That Double the Explained Heritability

机译:与低密度脂蛋白胆固醇相关的五个基因座的精细作图可检测到使遗传力加倍的变异

获取原文
           

摘要

Complex trait genome-wide association studies (GWAS) provide an efficient strategy for evaluating large numbers of common variants in large numbers of individuals and for identifying trait-associated variants. Nevertheless, GWAS often leave much of the trait heritability unexplained. We hypothesized that some of this unexplained heritability might be due to common and rare variants that reside in GWAS identified loci but lack appropriate proxies in modern genotyping arrays. To assess this hypothesis, we re-examined 7 genes (APOE, APOC1, APOC2, SORT1, LDLR, APOB, and PCSK9) in 5 loci associated with low-density lipoprotein cholesterol (LDL-C) in multiple GWAS. For each gene, we first catalogued genetic variation by re-sequencing 256 Sardinian individuals with extreme LDL-C values. Next, we genotyped variants identified by us and by the 1000 Genomes Project (totaling 3,277 SNPs) in 5,524 volunteers. We found that in one locus (PCSK9) the GWAS signal could be explained by a previously described low-frequency variant and that in three loci (PCSK9, APOE, and LDLR) there were additional variants independently associated with LDL-C, including a novel and rare LDLR variant that seems specific to Sardinians. Overall, this more detailed assessment of SNP variation in these loci increased estimates of the heritability of LDL-C accounted for by these genes from 3.1% to 6.5%. All association signals and the heritability estimates were successfully confirmed in a sample of ~10,000 Finnish and Norwegian individuals. Our results thus suggest that focusing on variants accessible via GWAS can lead to clear underestimates of the trait heritability explained by a set of loci. Further, our results suggest that, as prelude to large-scale sequencing efforts, targeted re-sequencing efforts paired with large-scale genotyping will increase estimates of complex trait heritability explained by known loci.
机译:复杂性状全基因组关联研究(GWAS)提供了一种有效的策略,用于评估大量个体中的大量常见变异并鉴定与特征相关的变异。然而,GWAS通常使很多特征遗传力无法解释。我们假设这种无法解释的遗传力可能是由于GWAS鉴定的基因座中存在常见且罕见的变异,但在现代基因分型阵列中缺少适当的代理。为了评估此假设,我们在多个GWAS中的5个低密度脂蛋白胆固醇(LDL-C)相关位点中重新检查了7个基因(APOE,APOC1,APOC2,SORT1,LDLR,APOB和PCSK9)。对于每个基因,我们首先通过对具有极端LDL-C值的256个撒丁岛个体进行重新排序来对遗传变异进行分类。接下来,我们对我们和1000个基因组计划(总计3277个SNP)在5,524名志愿者中鉴定出的变体进行了基因分型。我们发现,在一个基因座(PCSK9)中,GWAS信号可以用先前描述的低频变体来解释,而在三个基因座(PCSK9,APOE和LDLR)中,还有与LDL-C独立相关的其他变体,包括一个新的罕见的LDLR变种,似乎是撒丁岛人所特有的。总体而言,这些基因座中SNP变异的更详细评估将这些基因占LDL-C遗传力的估计值从3.1%提升至6.5%。在约10,000名芬兰和挪威人的样本中成功确认了所有关联信号和遗传力估计。因此,我们的结果表明,关注通过GWAS可访问的变体可能导致一组基因座所解释的性状遗传力的明显低估。此外,我们的结果表明,作为大规模测序工作的序幕,有针对性的重测序工作与大规模基因分型相结合将增加对已知基因座所解释的复杂性状遗传力的估计。

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号