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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.

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Figure 1: Project workflow.
Figure 2: Empirical cumulative distribution functions (cdf) of blood pressure measures (in mm Hg).
Figure 3: New blood pressure loci detected in GERA and tested for replication in ICBP + UKB meta-analysis.
Figure 4: New blood pressure loci identified in the GERA + ICBP meta-analysis and tested for replication in UKB.
Figure 5: Tissue-specific eQTL analysis of 51 tissues.

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Acknowledgements

We are grateful to the Kaiser Permanente Northern California members who have generously agreed to participate in the Kaiser Permanente Research Program on Genes, Environment, and Health. Support for participant enrollment, survey completion, and biospecimen collection for the RPGEH was provided by the Robert Wood Johnson Foundation, the Wayne and Gladys Valley Foundation, the Ellison Medical Foundation, and Kaiser Permanente Community Benefit Programs. Genotyping of the GERA cohort was funded by a grant from the National Institute on Aging, National Institute of Mental Health, and National Institute of Health Common Fund (RC2 AG036607 to C.S. and N.R.). This research has been conducted using the UK Biobank Resource. This research has also been conducted using access-controlled ICBP data from dbGaP. We thank our colleagues for making these data available. Data analyses were facilitated by National Heart, Lung, and Blood Institute grant R01 HL128782 (to A.C. and N.R.). G.B.E. receives support from Geneva University Hospitals and the Foundation of Medical Researchers, Geneva. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

T.J.H., G.B.E., C.I., A.C., and N.R. conceived and designed the study. P.-Y.K. supervised the creation of genotype data. D.R., in collaboration with C.I., C.S., T.J.H., and N.R., extracted phenotype data from EHRs. T.J.H., P.N., D.R., and N.R. performed statistical analyses. T.J.H., G.B.E., P.N., C.I., A.C., and N.R. interpreted the results of analyses. All authors contributed to the drafting and critical review of the manuscript.

Corresponding authors

Correspondence to Thomas J Hoffmann or Neil Risch.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3 and 5–9, and Supplementary Tables 1, 2 and 7. (PDF 22310 kb)

Supplementary Figure 4

Zoomed-in plots of each genetic locus. (PDF 24625 kb)

Supplementary Table 3

Full novel blood pressure results found in the GERA meta-analysis and the meta-analysis of GERA and ICBP together. (XLSX 451 kb)

Supplementary Table 4

SNP annotation. (XLSX 32 kb)

Supplementary Table 5

Joint and univariate fits of conditional/stepwise regression models to test for additional independent SNPs of SBP at previously identified and novel loci. (XLSX 17 kb)

Supplementary Table 6

GERA results for previously identified blood pressure loci. (XLSX 451 kb)

Supplementary Table 8

Sex heterogeneity tests in the GERA cohort using SNPs that were previously identified (P), GERA (G), the meta-analysis of GERA and ICBP (GI), or the meta-analysis of GERA, ICBP, and UKB (GIU). (XLSX 102 kb)

Supplementary Table 9

Testing for equality of normalized SBP and normalized DBP in SNPs that were previously identified (P), GERA (G), the meta-analysis of GERA and ICBP (GI), or the meta-analysis of GERA, ICBP, and UKB (GIU). (XLSX 34 kb)

Supplementary Table 10

DAVID enrichment analysis. (XLSX 11 kb)

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Hoffmann, T., Ehret, G., Nandakumar, P. et al. Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation. Nat Genet 49, 54–64 (2017). https://doi.org/10.1038/ng.3715

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