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Chunk #40 — Online methods — GWAS analysis and covariate adjustment

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Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation.
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We first analyzed each of the five race/ethnicity groups separately. Data from each SNP were modeled using additive dosages accounting for imputation uncertainty53. For each quantitative trait (treatment adjusted SBP, DBP, and PP), for computational efficiency, we first ran a mixed model of the BP measurement adjusted for age, age2, BMI, and sex using all BP measurements for each individual. We then constructed a long-term average residual for each individual as the dependent variable in a linear mixed model using estimated kinship matrices with leave-one-chromosome-out (LOCO) to account for population substructure and cryptic relatedness with Bolt-LMM54. Finally, we undertook a fixed-effects meta-analysis to combine the results of the five groups using Metasoft v2.055. We considered as novel loci that were at a physical distance >0.5Mb from any previously-described locus (and visual inspection for longer LD stretches, see below).