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Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

An Author Correction to this article was published on 02 November 2018

This article has been updated

Abstract

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

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Figure 1: Study design.
Figure 2: Allelic spectrum of cardiometabolic trait variants.
Figure 3: GARFIELD functional enrichment analyses.
Figure 4: Fine-mapping experiments.
Figure 5: Summary of variant consequences for fine-mapped variants.

Change history

  • 02 November 2018

    In the version of the article published, the surname of author Aaron Isaacs is misspelled as Issacs.

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Acknowledgements

This study makes use of data generated by the UK10K Consortium, derived from samples from the ALSPAC and TwinsUK data sets. A full list of the investigators who contributed to the generation of the data is available from http://www.UK10K.org/. Funding for UK10K was provided by the Wellcome Trust under award WT091310. The research of N.S. is supported by the Wellcome Trust (grants WT098051 and WT091310), the European Union Framework Programme 7 (EPIGENESYS grant 257082 and BLUEPRINT grant HEALTH-F5-2011-282510) and the National Institute for Health Research Blood and Transplant Research Unit (NIHR BTRU) in Donor Health and Genomics at the University of Cambridge in partnership with NHS Blood and Transplant (NHSBT). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or NHSBT. P.L.A. was supported by NHLBI R21 HL121422-02. A full list of grant support and acknowledgements can be found in the Supplementary Note and ref. 14.

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Contributions

Designed and/or managed individual studies and contributed data: A.B., A.D., A.G.U., A. Hamsten, A. Hofman, A.P.R., C.L., C.K., C.M.v.D., D.M., D.T., E.Z., G.G., H.W., J.C.C., J.S.K., L.F., M.A.S., M. Franberg, M. Frontini, N.J.T., N.S., P.G., P.L.A., R.A.S., R.P., W.M. Generated and/or performed quality control of data: A.-E.F., A. Hamsten, A. Hofman, A.I., A.M., B.S., C.S.F., E.M.v.L., F.R., G.L., G.M., G.Z., H.E., I.N., J.H., J.L., J.L.M., J.R.B.P., K.P., K.W., L.C., L.S., M.C., M.E.K., M.S.-L., M.T., N.A., O.H.F., S.-Y.-S., T.J., T.R.G., W.A., Y.M. Analyzed the data and provided critical interpretation of results: A.-E.F., A. Hamsten, A. Hofman, C.B., C.S.F., D.J., F.v.D., H.E., J.A.M., J.H., J.L.M., J.R.B.P., K.P., K.W., L.C., M.C., M.T.M., P.D., P.L.A., S.-Y.S., T.J., T.R.G., V.I., W.A., W.Z., Y.M. Provided tools or materials: A.P.R., E.Z., F.v.D., G.D., M.T.M., N.J.T., N.S., P.D. Wrote the manuscript: A.P.R., C.B., D.J., J.A.M., J.H., J.L.M., K.W., L.C., L.F., M.A.S., N.J.T., N.S., P.L.A., V.I. Evaluated the manuscript: A.B., A.D., A.-E.F., A.G.U., A. Hamsten, A. Hofman, A.I., A.M., A.P.R., B.S., C.B., C.L., C.K., C.S.F., C.M.v.D., D.J., D.M., D.T., E.M.v.L., E.Z., F.R., F.v.D., G.D., G.G., G.L., G.M., G.Z., H.E., H.W., I.N., J.A.M., J.C.C., J.H., J.L., J.L.M., J.R.B.P., J.S.K., K.P., K.W., L.C., L.F., L.S., M.A.S., M.C., M.E.K., M. Franberg, M. Frontini, M.S.-L., M.T., M.T.M., N.A., N.J.T., N.S., O.H.F., P.D., P.G., P.L.A., R.A.S., R.P., S.-Y.S., T.J., T.R.G., V.I., W.A., W.M., W.Z., Y.M. Designed and/or managed the project: A.P.R., N.J.T., N.S., P.L.A.

Corresponding authors

Correspondence to Alexander P Reiner or Paul L Auer or Nicole Soranzo.

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Competing interests

The authors declare no competing financial interests.

Additional information

A list of consortium members and affiliations can be found at http://www.uk10k.org/.

Supplementary information

Supplementary Text and Figures

Supplementary Note and Supplementary Figures 1–4. (PDF 8534 kb)

Supplementary Table 1

Study descriptives. (XLSX 117 kb)

Supplementary Table 2

Phenotype preparation protocols. (XLSX 73 kb)

Supplementary Table 3

Association statistics for new loci in discovery and replication. (XLSX 131 kb)

Supplementary Table 4

GENCODE, ENCODE and Roadmap Epigenomics annotations used for enrichment analysis with software GARFIELD. (XLSX 106 kb)

Supplementary Table 5

Enrichment of cardiometabolic traits in 1,005 GENCODE, ENCODE and Roadmap Epigenomics annotations at 1 × 10−5 and 1 × 10−8 GWAS significance thresholds. (XLSX 202 kb)

Supplementary Table 6

Fine-mapping results. (XLSX 231 kb)

Supplementary Table 7

FINEMAP analysis with a relaxed assumption of multiple causal variants per locus. (XLSX 41 kb)

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Iotchkova, V., Huang, J., Morris, J. et al. Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps. Nat Genet 48, 1303–1312 (2016). https://doi.org/10.1038/ng.3668

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