Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA.
Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA.
Hypertension. 2022 Aug;79(8):1656-1667. doi: 10.1161/HYPERTENSIONAHA.122.19324. Epub 2022 Jun 2.
The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure.
We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants.
Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (<5×10). Among them, a rare intergenic variant at novel locus, , was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; =4.99×10) but not stage-2 analysis (=0.11). Furthermore, a novel common variant at the known locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; =4.18×10) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; =7.28×10). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (<1×10 and <1×10, respectively).
We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
全基因组测序数据在大型研究中的可用性使得人们能够评估编码和非编码变异在等位基因频率谱范围内与血压的关联。
我们对 51456 名参与跨组学精准医学和常见疾病基因组中心计划的参与者(阶段 1)的血压进行了多祖先全基因组测序分析。在阶段 2 分析中,我们利用了来自英国生物库(N=383145)、百万退伍军人计划(N=318891)和地理和种族差异中风原因(N=10643)参与者的数组数据,以及英国生物库(N=199631)参与者的全外显子组测序数据。
在阶段 1 和阶段 2 单变体发现的荟萃分析中,有两个血压信号达到了全基因组显著水平(<5×10)。其中,在新发现的基因间位置的罕见变异与阶段 1 中的收缩压降低有关(beta [SE]=-32.6 [6.0];=4.99×10),但在阶段 2 分析中没有关系(=0.11)。此外,在已知的 位置的一个新的常见变异与阶段 1 中的舒张压呈提示性关联(beta [SE]=-0.36 [0.07];=4.18×10),并在阶段 2 中达到全基因组显著水平(beta [SE]=-0.29 [0.03];=7.28×10)。在单变体和聚合稀有变体发现的荟萃分析中,还有 19 个信号提示与血压有关(<1×10 和 <1×10,分别)。
我们报告了一个有希望但未经证实的与血压有关的罕见变异,更重要的是,为未来的血压测序研究提供了见解。我们的发现表明,聚合分析有希望补充单变体分析策略,需要更大、更多样化的样本和家族研究,以实现稳健的罕见变异识别。