Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. Issue 8 (2nd June 2022) - Kelly, Tanika N.; Sun, Xiao; He, Karen Y.; Brown, Michael R.; Taliun, Sarah A. Gagliano; Hellwege, Jacklyn N.; Irvin, Marguerite R.; Mi, Xuenan; Brody, Jennifer A.; Franceschini, Nora; Guo, Xiuqing; Hwang, Shih-Jen; et al.
Abstract : Background: 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. Methods: 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. Results: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings ( P <5×10 -8 ). Among them, a rare intergenic variant at novel locus, LOC100506274, was associated with lower systolic blood pressure in stage-1 (beta [SE]=−32.6 [6.0]; P =4.99×10 -8 ) but not stage-2 analysis ( P =0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=−0.36 [0.07]; P =4.18×10 -7 ) and attained genome-wide significance in stage-2 (beta [SE]=−0.29 [0.03]; P =7.28×10 -23 ). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings ( P <1×10 -6 and P <1×10 -4, respectively). Discussion: 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.