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Rare and low-frequency coding variants in CXCR2 and other genes are associated with hematological traits

Nature Genetics volume 46, pages 629–634 (2014)Cite this article

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Abstract

Hematological traits are important clinical parameters. To test the effects of rare and low-frequency coding variants on hematological traits, we analyzed hemoglobin concentration, hematocrit levels, white blood cell (WBC) counts and platelet counts in 31,340 individuals genotyped on an exome array. We identified several missense variants in CXCR2 associated with reduced WBC count (gene-based P = 2.6 × 10−13). In a separate family-based resequencing study, we identified a CXCR2 frameshift mutation in a pedigree with congenital neutropenia that abolished ligand-induced CXCR2 signal transduction and chemotaxis. We also identified missense or splice-site variants in key hematopoiesis regulators (EPO, TFR2, HBB, TUBB1 and SH2B3) associated with blood cell traits. Finally, we were able to detect associations between a rare somatic JAK2 mutation (encoding p.Val617Phe) and platelet count (P = 3.9 × 10−22) as well as hemoglobin concentration (P = 0.002), hematocrit levels (P = 9.5 × 10−7) and WBC count (P = 3.1 × 10−5). In conclusion, exome arrays complement genome-wide association studies in identifying new variants that contribute to complex human traits.

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Figure 1: Association results in the meta-analysis of the MHI and WHI cohorts (n = 24,814) for hematocrit levels at the TFR2-EPO locus on chromosome 7 and for platelet count at the SH2B3 locus on chromosome 12.
Figure 2: Rare and low-frequency missense variants in CXCR2 are associated with lower WBC count.
Figure 3: Functional characterization of the CXCR2fs mutant receptor.

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Acknowledgements

We thank all participants and staff of the MHI Biobank and acknowledge the technical support of the Beaulieu-Saucier MHI Pharmacogenomic Center. This work was supported by the Centre of Excellence in Personalized Medicine (CEPMed), Fonds de Recherche du Québec–Santé (FRQS), the Canada Research Chair program and the MHI Foundation. The WHI program is funded by the National Heart, Lung, and Blood Institute, the US National Institutes of Health and the US Department of Health and Human Services (HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C and HHSN271201100004C). Exome chip data and analysis were supported through the Exome Sequencing Project (NHLBI RC2 HL-102924, RC2 HL-102925 and RC2 HL-102926), the Genetics and Epidemiology of Colorectal Cancer Consortium (NCI CA137088), the Genomics and Randomized Trials Network (NHGRI U01-HG005152) and a National Cancer Institute training grant (R25CA094880). The authors thank the WHI investigators and staff for their dedication and the study participants for making the program possible. SHIP is part of the Community Medicine Research network of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs, as well as the Social Ministry of the Federal State of Mecklenburg–West Pomerania, and the network Greifswald Approach to Individualized Medicine (GANI_MED) funded by the Federal Ministry of Education and Research (grant 03IS2061A). Generation of ExomeChip data has been supported by the Federal Ministry of Education and Research (grant 03Z1CN22) and the Federal State of Mecklenburg–West Pomerania. The University of Greifswald is a member of the Center of Knowledge Interchange program of Siemens AG and the Caché Campus program of InterSystems. G.A.D. acknowledges support from US National Institutes of Health award P01AI061093.

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Author notes

  1. George A Diaz, Alexander P Reiner and Guillaume Lettre: These authors jointly directed this work.

Authors and Affiliations

  1. School of Public Health, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin, USA

    Paul L Auer

  2. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

    Paul L Auer, Ursula Schick, Chris Carlson, Jeff Haessler, Charles Kooperberg, Ulrike Peters, Li Hsu & Alexander P Reiner

  3. Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany

    Alexander Teumer, Frank Schmidt & Uwe Völker

  4. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    Andrew O'Shaughnessy & George A Diaz

  5. Montreal Heart Institute, Montreal, Quebec, Canada

    Ken Sin Lo, Nathalie Chami, Simon de Denus, Marie-Pierre Dubé, Louis-Philippe Lemieux Perreault, John D Rioux, Valérie Turcot, Jean-Claude Tardif & Guillaume Lettre

  6. Faculty of Medicine, Université de Montréal, Montreal, Québec, Canada

    Simon de Denus, Marie-Pierre Dubé, John D Rioux, Jean-Claude Tardif & Guillaume Lettre

  7. Faculty of Pharmacy, Université de Montréal, Montreal, Québec, Canada

    Simon de Denus, Marie-Pierre Dubé, John D Rioux, Jean-Claude Tardif & Guillaume Lettre

  8. Division of Endocrinology, Diabetes and Metabolism, Ohio State University, Columbus, Ohio, USA

    Rebecca D Jackson

  9. Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany

    Matthias Nauck

  10. Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA

    Ulrike Peters & Alexander P Reiner

  11. Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany

    Henry Völzke

  12. Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Greifswald, Germany

    Andreas Greinacher

  13. Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    George A Diaz

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  1. Paul L Auer
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  2. Alexander Teumer
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Contributions

P.L.A., G.A.D., A.P.R. and G.L. conceived and designed the experiments. P.L.A., A.T., U.S., A.O., K.S.L., G.A.D., A.P.R. and G.L. performed the experiments. P.L.A., A.T., U.S., A.O., K.S.L., G.A.D., A.P.R. and G.L. analyzed the data. All authors contributed reagents and materials. P.L.A., G.A.D., A.P.R. and G.L. wrote the manuscript with contributions from all authors.

Corresponding authors

Correspondence to George A Diaz, Alexander P Reiner or Guillaume Lettre.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Quantile-quantile plots of single-variant association results.

(a) Hematocrit. (b) Hemoglobin. (c) White blood cell count. (d) Platelet count.

Supplementary Figure 2 Quantile-quantile plots of gene-based burden T1 results.

(a) Hematocrit. (b) Hemoglobin. (c) White blood cell count. (d) Platelet count. For each gene, we only considered missense, nonsense and splice-site variants with a minor allele frequency of <1%.

Supplementary Figure 3 Quantile-quantile plots of gene-based SKAT results.

(a) Hematocrit. (b) Hemoglobin. (c) White blood cell count. (d) Platelet count. For each gene, we only considered missense, nonsense and splice-site variants with a minor allele frequency of <5%.

Supplementary Figure 4 Impact of the mutation p.Asp70Asn in EPO.

(a) Crystal structure of erythropoietin (EPO, yellow) with two erythropoietin receptor subunits (EPOR, green and red)24. The white circle indicates the interface between EPO and EPOR magnified in (b) and (c). In (b) and (c), the white circles highlight residue 70 (43 after cleavage of the propeptide). Replacing Asp70 (b) by Asn70 (c) may destabilize the EPO loop that interacts with EPOR because it disrupts a hydrogen bond between Asp70 and Thr71.

Supplementary Figure 5 Intensity plots for JAK2 p.Val617Phe in the Montreal Heart Institute (MHI; left) and the Study of Health in Pomerania (SHIP; right) genotyped on the Illumina HumanExome BeadChip.

Density plots for the Women's Health Initiative were not available.

Supplementary Figure 6 Mutations in SH2B3 may interfere with JAK2 binding.

Crystal structure of the SH2-B SH2 domain (beige) with JAK2 phosphotyrosine peptide (pTyr813, yellow)25. JAK2 pTyr813 interacts with arginine residues in the SH2-B BC loop. The glutamate residues identified in our association study (Glu395 and Glu400, green) correspond to Glu558 and Glu563 in the SH2-B sequence. They are directly in the BC loop that interacts with JAK2. Glu563 interacts with Arg578.

Supplementary Figure 7 UCSC ENCODE tracks for the rs1465788 variant near ZFP36L1.

The rs1465788 variant appears to be in a K562 FAIRE nucleosome depletion peak. rs1465788 is also in high LD with rs2236263 (r2 = 0.91 in CEU), rs3742887 (r2 = 0.99 in CEU) and rs6573857 (r2 = 1 in CEU), which all lie in an active promoter for ZFP36L1.

Supplementary Figure 8 Crystal structure of CXCR1 in a phospholipid bilayer.

CXCR2, like CXCR1 and CXCR4, is a protein with seven transmembrane (TM) domains. In purple are the CXCR1 residues that correspond to the missense mutations identified in CXCR2 (two CXCR2 residues, Met6 and Ala37, do not have their CXCR1 equivalent on this structure). In parentheses are the corresponding CXCR2 residues. CXCR2 Arg289 and Arg294 are in TM domains. The remaining four CXCR2 residues (Arg144, Arg236, Arg248, His332) are in intracellular loops.

Supplementary Figure 9 Analysis of CXCR2 in a myelokathexis pedigree.

(a) A myelokathexis pedigree with two affected (filled) and two unaffected (open) daughters is shown at left. The CXCR2 sequence trace shows a single-base deletion corresponding to coding sequence position 968 in individual I-2 (unaffected) compared to an unrelated control (arrow). (b) An NcoI recognition site (CCATGG) that gives a 325-bp fragment when a wild-type amplicon is digested is destroyed by the c.968delA mutation so that the 375-bp undigested amplicon persists. Affected siblings II-2 and II-4 are homozygous for the deletion mutation, parents and sibling II-1 are heterozygous for the mutation, and sibling II-3 is homozygous for the wild-type allele. White blood cell (WBC) counts for each family member are shown below. (c) A structural model of CXCR2 with the conserved GPCR motifs (purple, intracellular loop 2; dark blue, DRY; green, NPXXY), the mutant frameshift peptide (orange) and the truncated wild-type tail (red) indicated. The frameshift is located in helix 8, which is predicted to be parallel to the plasma membrane. Amino acid sequences from the wild-type and mutant CXCR2 constructs are shown. The CXCR2fs construct contains a six-amino-acid frameshift peptide (LDSSRF). Amino acid colors correspond to those used in the structure model. The black bar over the primary sequence indicates the location of a highly conserved LLKIL dileucine motif that is critical for receptor-mediated chemotaxis27.

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Auer, P., Teumer, A., Schick, U. et al. Rare and low-frequency coding variants in CXCR2 and other genes are associated with hematological traits. Nat Genet 46, 629–634 (2014). https://doi.org/10.1038/ng.2962

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