Chen Han, Choi Seung Hoan, Hong Jaeyoung, Lu Chen, Milton Jacqueline N, Allard Catherine, Lacey Sean M, Lin Honghuang, Dupuis Josée
Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, USA.
Département de Mathématiques, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC J1K 2R1, Canada.
BMC Proc. 2014 Jun 17;8(Suppl 1):S35. doi: 10.1186/1753-6561-8-S1-S35. eCollection 2014.
The genetic variants associated with blood pressure identified so far explain only a small proportion of the total heritability of this trait. With recent advances in sequencing technology and statistical methodology, it becomes feasible to study the association between blood pressure and rare genetic variants. Using real baseline phenotype data and imputed dosage data from Genetic Analysis Workshop 18, we performed a candidate gene association analysis. We focused on 8 genes shown to be associated with either systolic or diastolic blood pressure to identify the association with both common and rare genetic variants, and then did a genome-wide rare-variant analysis on blood pressure. We performed association analysis for rare coding and splicing variants within each gene region and all rare variants in each sliding window, using either burden tests or sequence kernel association tests accounting for familial correlation. With a sample size of only 747, we failed to find any novel associated genetic loci. Consequently, we performed analyses on simulated data, with knowledge of the underlying simulating model, to evaluate the type I error rate and power for the methods used in real data analysis.
目前已确定的与血压相关的基因变异仅解释了该性状总遗传力的一小部分。随着测序技术和统计方法的最新进展,研究血压与罕见基因变异之间的关联变得可行。利用遗传分析研讨会18的真实基线表型数据和估算剂量数据,我们进行了候选基因关联分析。我们聚焦于8个已显示与收缩压或舒张压相关的基因,以确定与常见和罕见基因变异的关联,然后对血压进行全基因组罕见变异分析。我们使用考虑家族相关性的负担检验或序列核关联检验,对每个基因区域内的罕见编码和剪接变异以及每个滑动窗口中的所有罕见变异进行关联分析。由于样本量仅为747,我们未能发现任何新的相关基因位点。因此,我们在了解潜在模拟模型的情况下对模拟数据进行分析,以评估实际数据分析中所用方法的I型错误率和检验效能。