Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation

Abstract

Longitudinal electronic health records on 99,785 Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort individuals provided 1,342,814 systolic and diastolic blood pressure measurements for a genome-wide association study on long-term average systolic, diastolic, and pulse pressure. We identified 39 new loci among 75 genome-wide significant loci (P ≤ 5 × 10^-8), with most replicating in the combined International Consortium for Blood Pressure (ICBP; n = 69,396) and UK Biobank (UKB; n = 152,081) studies. Combining GERA with ICBP yielded 36 additional new loci, with most replicating in UKB. Combining all three studies (n = 321,262) yielded 241 additional genome-wide significant loci, although no replication sample was available for these. All associated loci explained 2.9%, 2.5%, and 3.1% of variation in systolic, diastolic, and pulse pressure, respectively, in GERA non-Hispanic whites. Using multiple blood pressure measurements in GERA doubled the variance explained. A normalized risk score was associated with time to onset of hypertension (hazards ratio = 1.18, P = 8.2 × 10^-45). Expression quantitative trait locus analysis of blood pressure loci showed enrichment in aorta and tibial artery.

Figure 1

Project workflow. (a) EHR phenotype extraction for the GERA cohort. (b) GWAS analysis approaches.

Figure 2

Empirical cumulative distribution functions of BP measures (mmHg), stratified by GERA race/ethnicity group and normalized to a 61 year old male with BMI 27kg/m² for reference, indicated by the vertical dashed line. There were 80,792 non-Hispanic whites, 8,231 Latinos, 7,243 East Asians, 3,058 African Americans, and 461 South Asians.

Figure 3

Novel BP loci detected in GERA and tested for replication in the ICBP+UKB meta-analysis. The two SNPs rs76217164 and rs143118162 failed to impute in ICBP (owing to low allele frequency), and rs141216986 was on the X chromosome and not available in ICBP or UK. We used an additive model. The effect allele is the allele to the left (e.g., A in A/G). Effect sizes are indicated in mmHg. Each line represents the effect size and 95% confidence interval for each group, with the text on top of each line representing the group tested: G, GERA (n=99,785); IU, meta-analysis of the ICBP and UKB (n=221,477); and GIU, meta-analysis of GERA, ICBP, and the UKB (n=321,262). The color of each line indicates the statistical significance of the test: red, P≤10⁻⁹; orange, 10⁻⁹<P≤5×10⁻⁸; green, 5×10⁻⁸<P≤0.00067 (Bonferroni correction for 39+36=75 SNPs); blue, 0.00066<P≤0.05; black, P>0.05.

Figure 4

Novel BP loci identified in the GERA+ICBP meta-analysis, and tested for replication in the UKB. We used an additive model. The effect allele is the allele to the left (e.g., A in A/G). Effect sizes are indicated in mmHg. Each line represents the effect size and 95% confidence interval for each group, with the text on top of each line representing the group tested: GI, meta-analysis of GERA and ICBP (n=169,181); U, UK Biobank (n=152,081); and GIU, meta-analysis of GERA, ICBP, and the UKB (n=321,262). The color of each line indicates the statistical significance of the test: red, P≤10⁻⁹; orange, 10⁻⁹<P≤5×10⁻⁸; green, 5×10⁻⁸<P≤0.00067 (Bonferroni correction for 39+36=75 SNPs); blue, 0.00066<P≤0.05; black, P>0.05.

Figure 5

Tissue specific expression quantitative trait loci (eQTL) analysis of 51 tissues. The two outlier tissues, accounting for total eQTL count, are labeled. Tissue total eQTL counts vs P-values at (a) the locus and (b) the sentinel variant.