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Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

Abstract

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure–associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein–protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure–associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

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Figure 1: Overall study design.
Figure 2: NPR1 gene: low-frequency and rare variants associated in aggregate with mean arterial pressure.
Figure 3: DBH gene: rare variants associated in aggregate with mean arterial pressure.

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Acknowledgements

We thank the two anonymous reviewers and editors for their helpful comments. Study-specific funding sources and acknowledgments are reported in the Supplementary Note.

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Study design: A.T.K., C.L., N.F., G.B.E., C.N.-C., J.I.R., B.M.P., D.L., D.I.C. Phenotyping: E.B., V.G., B.M.P., D.L., D.R.W., A. Correa, A. Chakravarti, W.P., M.D., R.R., W.H.-H.S., P.M.R., A.P.R., J.E.R., C.K., N.F., K.L., C.B., Y.-D.I.C., A.T.K., M.G.L., L.J.R., E.P.B., O.G., H.V., W.-J.L., J.I.R., O.H.F., R.S.V., R.J.F.L., A. Correa, A. Chakravarti, T.L.E., I.-T.L., L.W.M., G.J.P. Genotyping: E.B., D.L., A.P.R., C.K., Y.-D.I.C., M.F., C.J.O'D., S.L.R.K., U.V., D.I.C., C.N.-C., J.A.B., J.C.B., E.W.D., K.D.T., C.L., J.A.S., W.Z., J.D.F., Y.-D.I.C., S.W., E.K., A.G.U., A.Y.C., J.I.R., B.M.P., D.R.V.E., Y. Liu, C.M.v.D., I.B.B., R.J.F.L., L.J.L., T.B.H., T.L.E., S.B.F., F.G., P.L.A., M.L.G. Quality control: A.P.R., D.I.C., C.N.-C., J.A.B., J.C.B., E.W.D., K.D.T., C.L., S.-J.H., J.A.S., W.Z., J.D.F., S.W., A.Y.C., F.G., P.L.A., M.L.G., M.D., H.V., G.B.E., A.C.M., J.J., A.V.S., L. Lin. Software development: J.A.B., C.L., A.Y.C., F.G., P.L.A., A.T.K., K.R., A.V., H.C., D.I.C. Statistical analysis: A.P.R., D.I.C., C.N.-C., G.K., J.A.B., J.C.B., C.L., Y. Lu, J.A.S., W.Z., J.D.F., S.W., A.Y.C., F.G., P.L.A., G.B.E., A.C.M., J.J., A.V.S., L. Lin, J.M.S., N.A., K.S.T., T.H., A.G., C.K., N.F., A.T.K., M.G.L., S.G., E.S., K.R., H.M., X.G., J.Y., P.S., F.D., J.P.C., S.K., N.O.S., H.S., P.D., N.S., C.F., M.G., M.L., C.P. Manuscript writing: C.L., A.T.K., J.A.S., N.F., J.C.B., Y. Lu, W.P., L.W.M., M.G.L., K.R., T.L.E., M.F., G.B.E., J.I.R., C.N.-C., D.L., D.I.C.

Corresponding authors

Correspondence to Chunyu Liu, Daniel Levy or Daniel I Chasman.

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Competing interests

B.M.P. serves on the DSMB for a clinical trial funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. The other authors declare no competing financial interests.

Additional information

A list of members and affiliations appears in the Supplementary Note

A list of members and affiliations appears in the Supplementary Note

A list of members and affiliations appears in the Supplementary Note

A list of members and affiliations appears in the Supplementary Note

A list of members and affiliations appears in the Supplementary Note

A list of members and affiliations appears in the Supplementary Note

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3, Supplementary Tables 7–20 and Supplementary Note. (PDF 3709 kb)

Supplementary Table 1

CHARGE+ Exome Chip BP Consortium: experiment-wide significant associations in meta-analysis. (XLSX 15 kb)

Supplementary Table 2

CHARGE+ Exome Chip BP Consortium: associations with P < 1 × 10−4 in samples of all ancestries. (XLSX 76 kb)

Supplementary Table 3

CHARGE+ Exome Chip BP Consortium: previously identified GWAS loci with P < 0.001 for any blood pressure trait. (XLSX 23 kb)

Supplementary Table 4

Meta-analysis of the discovery and follow-up samples of European ancestry: associations with P < 3.4 × 10−7. (XLSX 20 kb)

Supplementary Table 5

Meta-analysis of the discovery and follow-up samples of all ancestries: associations with P < 3.4 × 10−7. (XLSX 21 kb)

Supplementary Table 6

CHARGE+ Exome Chip BP Consortium: effects of the coded alleles on the five blood pressure traits in all ancestries. (XLSX 23 kb)

Supplementary Table 21

Exome Chip genotyping, data cleaning, and quality control. (XLSX 13 kb)

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Liu, C., Kraja, A., Smith, J. et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet 48, 1162–1170 (2016). https://doi.org/10.1038/ng.3660

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