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Meta-analysis of rare and common exome chip variants identifies S1PR4 and other loci influencing blood cell traits | Nature Genetics
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Meta-analysis of rare and common exome chip variants identifies S1PR4 and other loci influencing blood cell traits

Abstract

Hematologic measures such as hematocrit and white blood cell (WBC) count are heritable and clinically relevant. We analyzed erythrocyte and WBC phenotypes in 52,531 individuals (37,775 of European ancestry, 11,589 African Americans, and 3,167 Hispanic Americans) from 16 population-based cohorts with Illumina HumanExome BeadChip genotypes. We then performed replication analyses of new discoveries in 18,018 European-American women and 5,261 Han Chinese. We identified and replicated four new erythrocyte trait–locus associations (CEP89, SHROOM3, FADS2, and APOE) and six new WBC loci for neutrophil count (S1PR4), monocyte count (BTBD8, NLRP12, and IL17RA), eosinophil count (IRF1), and total WBC count (MYB). The association of a rare missense variant in S1PR4 supports the role of sphingosine-1-phosphate signaling in leukocyte trafficking and circulating neutrophil counts. Loss-of-function experiments for S1pr4 in mouse and s1pr4 in zebrafish demonstrated phenotypes consistent with the association observed in humans and altered kinetics of neutrophil recruitment and resolution in response to tissue injury.

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Figure 1: Forest plots of the S1PR4 variant encoding p.Arg365Leu for total WBC count.
Figure 2
Figure 3: Blood neutrophils in S1pr4−/− mice.
Figure 4: Reduction in neutrophil counts in zebrafish embryos with decreased s1pr4 expression by morpholino-mediated knockdown with two independent morpholino oligonucleotides.
Figure 5: Neutrophil migration in response to injury is altered in zebrafish embryos with low s1pr4 gene expression.

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Acknowledgements

We thank the staff and participants of all studies for their important contributions. A complete list of acknowledgments for each study is available in the Supplementary Note.

This work was supported by the following grants and contracts: US National Institutes of Health contracts (N01AG12100, HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, HHSN268201100012C, HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC25195, N02HL64278, N01AG62101, N01AG62103, N01AG62106, HHSN268200782096C, HHSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, HHSN268201300050C, N01HC95159, N01HC95160, N01HC95161, N01HC95162, N01HC95163, N01HC95164, N01HC95165, N01HC95166, N01HC95167, N01HC95168, N01HC95169, RR024156, N02HL64278, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSN271201100004C, RC2HL102924, and CA137088); US National Institutes of Health grants (5RC2HL102419, HL080295, HL087652, HL103612, HL105756, HL120393, AG023629, DK063491, R01DK089256, R01HL087700, R01HL088215, R01HL117078, 1R01AG032098-01A1, U01-HG005152, R25CA094880, R01HL122684, R01HL04880, R01HL32262, R01DK49216, R01HL10001, R01DK092760, and R01OD017870); a Clinical and Translational Science Institute grant (UL1TR000124); a Danish Heart Foundation grant (07-10-R61-A1754-B838-22392F); a Biobanking and BioMolecular resources Research Infrastructure–The Netherlands (BBMRI-NL) grant (NWO 184.021.007); a Health Insurance Foundation grant (2012B233); and Academy of Finland grants (134309, 126925, 121584, 124282, 129378, 117787, and 41071).

This work was supported in part by the NIDDK Division of Intramural Research.

The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute, the National Institutes of Health, or the US Department of Health and Human Services.

This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute.

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N.P., Y. Zhou, Y. Zhang, E.P.B., I.J.D., O.H.F., M.E.G., V.G., T.H., T.B.H., A.H., L.J.L., A.L., O.P., J.M.S., A.D., Y.H., C.J.O'D., A.P.R., and S.K.G. designed the study. Y. Zhang, I.B.B., E.P.B., M.C., I.J.D., L.D., M.F.F., M.E.G., V.G., T.B.H., A.H., R.D.J., J.J., M.K., T.L., A.L., M.E.N., B.M.P., O.T.R., S.S.R., J.M.S., B.H.T., R.P.T., Jiansong Wang, and C.J.O'D. recruited and assessed participants. P.L.A., J.B.-J., N.G., L.-P.L., Y. Zhang, F.W.A., E.B., I.B.B., E.P.B., P.I.W.d.B., M.F.F., M.L.G., T.L., D.C.L., Y. Liu, S.S.R., F.R., J.I.R., K.D.T., and A.G.U. generated genotyping data. Y. Zhou, M.L.A., V.C., E.J.H., B.H., K.H., X.Z., V.M.N., A.M.R.D.S., R.L.P., and L.I.Z. performed functional experiments. N.P., U.M.S., T.S.A., M.L.A., P.L.A., J.B.-J., N.G., B.H., Y. Lu, M.A.N., R.P., A.V.S., Y. Zhang, J.S.F., N.F., M.L.G., R.J.F.L., B.M.P., A.D., L.A.C., J.G.W., R.L.P., L.I.Z., C.J.O'D., A.P.R., and S.K.G. analyzed and interpreted data. N.P., U.M.S., W.Z., T.S.A., J.B.-J., J.A.B., M.-H.C., J.D.E., N.G., A.D.J., M.L., Y. Lu, L.-P.L., A.M., R.E.M., M.A.N., R.P., A.V.S., F.J.A.v.R., M.-L.Y., Judy Wang, and A.P.R. performed statistical analysis. N.P., U.M.S., Y. Zhou, A.P.R., and S.K.G. wrote the manuscript. All authors were given the opportunity to comment and provide revisions to the manuscript text.

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Correspondence to Nathan Pankratz or Santhi K Ganesh.

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the CHARGE Consortium Hematology Working Group. Meta-analysis of rare and common exome chip variants identifies S1PR4 and other loci influencing blood cell traits. Nat Genet 48, 867–876 (2016). https://doi.org/10.1038/ng.3607

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