Department of Genetic Epidemiology, University Regensburg, Regensburg, Germany.
Department of Nephrology, University Hospital Regensburg, Regensburg, Germany.
Sci Rep. 2017 Apr 28;7:45040. doi: 10.1038/srep45040.
HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples.
HapMap 全基因组关联研究（GWAS）已经揭示了超过 50 个常见变异体与肾功能相关的基因座，这些变异体的次要等位基因频率 >5%。使用更完整的参考集进行 imputation（如 1000 Genomes 项目中的参考集）的 GWAS 有望鉴定到以前的研究中遗漏的新基因座。为了研究这种更完整的变异目录的价值，我们使用 1000 个基因组 imputed 数据对 110517 名欧洲血统参与者的肾小球滤过率（eGFR）进行了基于估计的全基因组关联研究（GWAS）meta 分析。我们在之前基于 HapMap 的 GWAS 中鉴定出了 10 个新的基因座，这些基因座的 p 值 <5 × 10。其中 6 个基因座（HOXD8、ARL15、PIK3R1、EYA4、ASTN2 和 EPB41L3）由 1000 个基因组参考面板特有的常见 SNP 标记。通过通路分析，我们鉴定出了 39 个显著的（FDR <0.05）基因和 127 个显著富集的基因集，这些基因在我们之前的分析中被遗漏了。其中，鉴定出的 10 个新基因是肾脏发育、碳水化合物代谢、心脏中隔发育和葡萄糖代谢通路的一部分。这些结果突出了使用更密集的参考面板重新 imputation 的实用性，直到全基因组测序在大样本中变得可行。
