Li Man, Carey Jacob, Cristiano Stephen, Susztak Katalin, Coresh Josef, Boerwinkle Eric, Kao Wen Hong L, Beaty Terri H, Köttgen Anna, Scharpf Robert B
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America.
PLoS One. 2017 Jan 30;12(1):e0170815. doi: 10.1371/journal.pone.0170815. eCollection 2017.
Genome-wide association studies (GWAS) using single nucleotide polymorphisms (SNPs) have identified more than 50 loci associated with estimated glomerular filtration rate (eGFR), a measure of kidney function. However, significant SNPs account for a small proportion of eGFR variability. Other forms of genetic variation have not been comprehensively evaluated for association with eGFR. In this study, we assess whether changes in germline DNA copy number are associated with GFR estimated from serum creatinine, eGFRcrea. We used hidden Markov models (HMMs) to identify copy number polymorphic regions (CNPs) from high-throughput SNP arrays for 2,514 African (AA) and 8,645 European ancestry (EA) participants in the Atherosclerosis Risk in Communities (ARIC) study. Separately for the EA and AA cohorts, we used Bayesian Gaussian mixture models to estimate copy number at regions identified by the HMM or previously reported in the HapMap Project. We identified 312 and 464 autosomal CNPs among individuals of EA and AA, respectively. Multivariate models adjusted for SNP-derived covariates of population structure identified one CNP in the EA cohort near genome-wide statistical significance (Bonferroni-adjusted p = 0.067) located on chromosome 5 (876-880kb). Overall, our findings suggest a limited role of CNPs in explaining eGFR variability.
利用单核苷酸多态性（SNP）进行的全基因组关联研究（GWAS）已经确定了50多个与估算肾小球滤过率（eGFR，一种肾功能指标）相关的基因座。然而，显著的SNP仅占eGFR变异性的一小部分。其他形式的遗传变异尚未被全面评估与eGFR的关联。在本研究中，我们评估种系DNA拷贝数的变化是否与根据血清肌酐估算的肾小球滤过率（eGFRcrea）相关。我们使用隐马尔可夫模型（HMM）从社区动脉粥样硬化风险（ARIC）研究中2514名非洲裔（AA）和8645名欧洲裔（EA）参与者的高通量SNP阵列中识别拷贝数多态性区域（CNP）。分别针对EA和AA队列，我们使用贝叶斯高斯混合模型来估计由HMM识别或先前在HapMap计划中报道的区域的拷贝数。我们在EA和AA个体中分别鉴定出312个和464个常染色体CNP。针对群体结构的SNP衍生协变量进行调整的多变量模型在EA队列中位于5号染色体（876 - 880kb）上的一个CNP附近发现了接近全基因组统计显著性（Bonferroni校正p = 0.067）。总体而言，我们的研究结果表明CNP在解释eGFR变异性方面作用有限。
