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Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension

Abstract

High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to 192,763 individuals and used 155,063 samples for independent replication. We identified 30 new blood pressure– or hypertension-associated genetic regions in the general population, including 3 rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5 mm Hg/allele) than common variants. Multiple rare nonsense and missense variant associations were found in A2ML1, and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention.

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Figure 1: Study design and workflow diagram for single-variant discovery analyses.
Figure 2: Overlap of the 30 new blood pressure–associated loci across SBP, DBP, PP and HTN.
Figure 3: Study design for conditional analyses and rare variant gene-based discovery analyses.
Figure 4: Locus plot for A2ML1 and secondary amino acid structure of the gene product.

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Acknowledgements

Full acknowledgments appear in the Supplementary Note.

Author information

Authors and Affiliations

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Contributions

Supervision and management of the project: J.M.H.H. and P.B.M. The following authors contributed to the drafting of the manuscript: J.M.M.H., P.B.M. P. Surendran, H.W., A.S.B., F.D., J.P.C., D.R.B., K.W., M. Tomaszewski, F.W.A., L.V.W., N.J.S., J.D., A.K.M., H.Y., C.M.L., N.G., X.S., T. Tukiainen, D.F.F., O.G., T.F. and V.T. All authors critically reviewed and approved the final version of the manuscript. Statistical analysis review: J.M.M.H., P. Surendran, F.D., H.W., J.P.C., R.Y., N.M., P.B.M., L.V.W., H.Y., T.F., E. Mihailov, A.D.M., A. Mahajan, A. Moayyeri, E.E., A.S.B., F.W.A., M.J.C., C.F., T.F., S.E.H., A.S.H., J.E.H., J.L., G.M., J.M., N.M., A.P.M., A. Poveda, N.J.S., R.A.S., L.S., K.E.S., M. Tomaszewski, V.T., T.V.V., N.V., K.W., A.M.Y., W. Zhang, N.G., C.M.L., A.K.M., X.S. and T. Tuomi. Central data quality control: J.M.M.H., A.S.B., P. Surendran, R.Y., F.D., H.W., J.P.C., T.F., L.V.W., P.B.M., E. Mihailov, N.M., C.M.L., N.G., X.S. and A.K.M. Central data analysis: J.M.M.H., P. Surendran, F.D., H.W., J.P.C., N.G., C.M.L., A.K.M. and X.S. Pathway analysis and literature review: J.M.M.H., D.R.B., P.B.M., M. Tomaszewski, K.W., V.T., O.G., A.T. and F.W.A. GWAS lookups, eQTL analysis, GRS analysis, variant annotation and enrichment analyses: J.M.M.H., A.S.B., D.R.B., J.R.S., D.F.F., F.D., M. Harakalova, P.B.M., F.W.A., T. Tuomi, C.M.L., A.K.M. and S. Burgess. Study investigators in alphabetical order by consortium (CHD Exome+, ExomeBP and GoT2D): D.S.A., P.A., E.D.A., D.A., A.S.B., R.C., J.D., J.F., I.F., P.F., J.W.J., F. Kee, A.S.M., S.F.N., B.G.N., D.S., N. Sattar, J.V., F.W.A., P.I.W.d.B., M.J.B., M.J.C., J.C.C., J.M.C., I.J.D., G.D., A.F.D., P.E., T.E., P.W.F., G.G., P.v.d.H., C.H., K.H., E.I., M.-R.J., F. Karpe, S.K., J.S.K., L. Lind, M.I.M., O.M., A. Metspalu, A.D.M., A.P.M., P.B.M., M.E.N., S.P., C.N.A.P., O. Polasek, D.J.P., S.R., O.R., I.R., V.S., N.J.S., P. Sever, T.D.S., J.M.S., N.J.W., C.J.W., E.Z., M.B., I.B., F.S.C., L.G., T.H., E.K.-H., P.J., J. Kuusisto, M.L., T.A.L., A.L., K.L.M., H.O., O. Pedersen, R.R., J.T., M.U. M.U.-N., A. Malarstig, D.F.R., M. Hoek, T.F.V. Study phenotyping in alphabetical order by consortium (CHD Exome+, ExomeBP and GoT2D): P.A., D.A., S. Blankenberg, M.C., J.F., J.W.J., F. Kee, K.K., S.F.N., B.G.N., C.J.P., A.R., M.S., N. Sattar, J.V., W. Zhao, R.A.d.B., M.J.B., M.J.C., J.C.C., J.M.C., A.F.D., A.S.F.D., L.A.D., T.E., A.-E.F., G.G., G.H., P.v.d.H., A.S.H., O.L.H., M. Hassinen, E.I., M.-R.J., F. Karpe, J.S.K., L. Lind, L. Lannfelt, G.M., A. Matchan, P.v.d.M., A. Metspalu, R. Mägi, M.J.N., M.E.N., O. Polasek, N.P., F.R., V.S., N.J.S., T.D.S., A.V.S., J.M.S., M. Tomaszewski, A.-C.V., N.V., N.J.W., T. Tuomi, C.C., L.L.H., A.T.K., P.K., J.L., S.M., E.R.B.P., A.S., T.S., H.M.S., B.T. Study data quality control and analysis in alphabetical order by consortium (CHD Exome+, ExomeBP and GoT2D): A.S.B., A.J.M.d.C., K.-H.H., J.M.M.H., A.K., J. Kontto, C. Langenberg, S.F.N., B.G.N., M.M.-N., S.P., M.P., P. Surendran, S.T., G.V., S.M.W., R.Y., F.W.A., J.P.C., F.D., A.-E.F., T.F., C.H., A. Matchan, A. Mahajan, A.P.M., P.B.M., C.N.A.P., N.W.R., F.R., N.J.S., M. Tomaszewski, V.T., H.W., H.Y., N.G., A.K.M., X.S. Exome chip data quality control in alphabetical order by consortium (CHD Exome+, ExomeBP and GoT2D): A.S.B., K.-H.H., J.M.M.H., A.K., C. Langenberg, S.F.N., B.G.N., P. Surendran, R.Y., F.W.A., P.I.W.d.B., A.I.F.B., J.C.C., J.P.C., P.D., L.A.D., F.D., E.E., C.F., T.F., S.E.H., P.v.d.H., S.S.-H., K.H., J.E.H., E.K., A. Mahajan, G.M., J.M., N.M., E. Mihailov, A. Moayyeri, A.P.M., P.B.M., C.P.N., M.J.N., C.N.A.P., A. Poveda, N.W.R., N.R.R., R.A.S., N. Soranzo, L.S., K.E.S., M.D.T., V.T., T.V.V., N.V., H.W., H.Y., A.M.Y., E.Z., W. Zhang, N.G., C.M.L., A.K.M., X.S. Exome chip data analysis in alphabetical order by consortium (CHD Exome+, ExomeBP and GoT2D): J.M.M.H., P. Surendran, R.Y., F.W.A., P.I.W.d.B., A.I.F.B., R.A.d.B., M.J.C., J.C.C., J.P.C., P.D., L.A.D., P.E., E.E., C.F., T.F., P.W.F., S.F., C.J.G., S.E.H., P.v.d.H., A.S.H., C.H., O.L.H., J.E.H., E.I., M.-R.J., F. Karpe, J.S.K., D.C.M.L., L. Lind, J.L., G.M., R. Marioni, J.M., N.M., M.I.M., P.v.d.M., O.M., C.M., E. Mihailov, A. Moayyeri, A.P.M., R. Mägi, P.B.M., C.P.N., M.J.N., T.O., A. Palotie, A. Poveda, N.W.R., N.R.R., N.J.S., R.A.S., N. Soranzo, L.S., T.D.S., K.E.S., M.D.T., E.T., V.T., T.V.V., N.V., L.V.W., N.J.W., H.W., H.Y., A.M.Y., E.Z., H.Z., W. Zhang, L.L.B., A.P.G., N.G., J.R.H., A.U.J., J.B.-J., C.M.L., A.K.M., N.N., X.S., A.S., A.J.S. GRS lookups: A.E.J., E. Marouli, H.S.M., H.L., H.M.H., J.F.F., M. Traylor, R.S.V., W.L. CHARGE EXOME-BP lookups: Study design. A.T.K., C. Liu, C.N.-C. Analysis. A.T.K., C. Liu.

Corresponding authors

Correspondence to Joanna M M Howson or Patricia B Munroe.

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Competing interests

N.P. has received financial support from several pharmaceutical companies that manufacture either blood pressure -lowering or lipid-lowering agents, or both, and consultancy fees. S.K. has received research grants from Merck, Bayer and Aegerion, is on the SAB of Catabasis, Regeneron Genetics Center, Merck and Celera, has equity in San Therapeutics and Catabasis, and performs consulting for Novartis, Aegerion, Bristol Myers Squibb, Sanofi, AstraZeneca and Alnylam. P. Sever has received research awards from Pfizer. A. Malarstig and M.U.-N. are full-time employees of Pfizer. D.F.R. and M. Hoek are full-time employees of Merck. M.J.C. is Chief Scientist for Genomics England, a UK government company. The authors declare no other competing financial interests.

Additional information

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

A full list of members and affiliations appears in the Supplementary Note

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Surendran, P., Drenos, F., Young, R. et al. Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension. Nat Genet 48, 1151–1161 (2016). https://doi.org/10.1038/ng.3654

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