Human Genetics

, Volume 131, Issue 4, pp 639–652

Genetic variants associated with the white blood cell count in 13,923 subjects in the eMERGE Network

  • David R. Crosslin
  • Andrew McDavid
  • Noah Weston
  • Sarah C. Nelson
  • Xiuwen Zheng
  • Eugene Hart
  • Mariza de Andrade
  • Iftikhar J. Kullo
  • Catherine A. McCarty
  • Kimberly F. Doheny
  • Elizabeth Pugh
  • Abel Kho
  • M. Geoffrey Hayes
  • Stephanie Pretel
  • Alexander Saip
  • Marylyn D. Ritchie
  • Dana C. Crawford
  • Paul K. Crane
  • Katherine Newton
  • Rongling Li
  • Daniel B. Mirel
  • Andrew Crenshaw
  • Eric B. Larson
  • Chris S. Carlson
  • Gail P. Jarvik
  • The electronic Medical Records and Genomics (eMERGE) Network
Original Investigation

Abstract

White blood cell count (WBC) is unique among identified inflammatory predictors of chronic disease in that it is routinely measured in asymptomatic patients in the course of routine patient care. We led a genome-wide association analysis to identify variants associated with WBC levels in 13,923 subjects in the electronic Medical Records and Genomics (eMERGE) Network. We identified two regions of interest that were each unique to subjects of genetically determined ancestry to the African continent (AA) or to the European continent (EA). WBC varies among different ancestry groups. Despite being ancestry specific, these regions were identifiable in the combined analysis. In AA subjects, the region surrounding the Duffy antigen/chemokine receptor gene (DARC) on 1q21 exhibited significant association (p value = 6.71e−55). These results validate the previously reported association between WBC and of the regulatory variant rs2814778 in the promoter region, which causes the Duffy negative phenotype (Fy−/−). A second missense variant (rs12075) is responsible for the two principal antigens, Fya and Fyb of the Duffy blood group system. The two variants, consisting of four alleles, act in concert to produce five antigens and subsequent phenotypes. We were able to identify the marginal and novel interaction effects of these two variants on WBC. In the EA subjects, we identified significantly associated SNPs tagging three separate genes in the 17q21 region: (1) GSDMA, (2) MED24, and (3) PSMD3. Variants in this region have been reported to be associated with WBC, neutrophil count, and inflammatory diseases including asthma and Crohn’s disease.

Supplementary material

439_2011_1103_MOESM1_ESM.pdf (622 kb)
Supplementary material 1 (PDF 622 kb)

References

  1. Altshuler D, Gibbs R, Peltonen L, Dermitzakis E, Schaffner S, Yu F, Bonnen P, de Bakker P, Deloukas P, Gabriel S, Gwilliam R, Hunt S, Inouye M, Jia X, Palotie A, Parkin M, Whittaker P, Chang K, Hawes A, Lewis L, Ren Y, Wheeler D, Muzny D, Barnes C, Darvishi K, Hurles M, Korn J, Kristiansson K, Lee C, McCarrol S, Nemesh J, Keinan A, Montgomery S, Pollack S, Price A, Soranzo N, Gonzaga-Jauregui C, Anttila V, Brodeur W, Daly M, Leslie S, McVean G, Moutsianas L, Nguyen H, Zhang Q, Ghori M, McGinnis R, McLaren W, Takeuchi F, Grossman S, Shlyakhter I, Hostetter E, Sabeti P, Adebamowo C, Foster M, Gordon D, Licinio J, Manca M, Marshall P, Matsuda I, Ngare D, Wang V, Reddy D, Rotimi C, Royal C, Sharp R, Zeng C, Brooks L, McEwen J, Consortium IH (2010) Integrating common and rare genetic variation in diverse human populations. Nature 467:52–58. doi:10.1038/nature09298 PubMedCrossRefGoogle Scholar
  2. Bach JF (2002) The effect of infections on susceptibility to autoimmune and allergic diseases. N Engl J Med 347:911–920. doi:10.1056/NEJMra020100 PubMedCrossRefGoogle Scholar
  3. Barrett JC, Hansoul S, Nicolae DL, Cho JH, Duerr RH, Rioux JD, Brant SR, Silverberg MS, Taylor KD, Barmada MM, Bitton A, Dassopoulos T, Datta LW, Green T, Griffiths AM, Kistner EO, Murtha MT, Regueiro MD, Rotter JI, Schumm LP, Steinhart AH, Targan SR, Xavier RJ, Libioulle C, Sandor C, Lathrop M, Belaiche J, Dewit O, Gut I, Heath S, Laukens D, Mni M, Rutgeerts P, Van Gossum A, Zelenika D, Franchimont D, Hugot JP, de Vos M, Vermeire S, Louis E, Cardon LR, Anderson CA, Drummond H, Nimmo E, Ahmad T, Prescott NJ, Onnie CM, Fisher SA, Marchini J, Ghori J, Bumpstead S, Gwilliam R, Tremelling M, Deloukas P, Mansfield J, Jewell D, Satsangi J, Mathew CG, Parkes M, Georges M, Daly MJ (2008) Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nat Genet 40:955–962. doi:10.1038/ng.175 PubMedCrossRefGoogle Scholar
  4. Barrett JC, Clayton DG, Concannon P, Akolkar B, Cooper JD, Erlich HA, Julier C, Morahan G, Nerup J, Nierras C, Plagnol V, Pociot F, Schuilenburg H, Smyth DJ, Stevens H, Todd JA, Walker NM, Rich SS (2009) Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nat Genet 41:703–707. doi:10.1038/ng.381 PubMedCrossRefGoogle Scholar
  5. Breslow DK, Collins SR, Bodenmiller B, Aebersold R, Simons K, Shevchenko A, Ejsing CS, Weissman JS (2010) Orm family proteins mediate sphingolipid homeostasis. Nature 463:1048–1053. doi:10.1038/nature08787 PubMedCrossRefGoogle Scholar
  6. Browning B, Browning S (2009) A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet 84:210–223. doi:10.1016/j.ajhg.2009.01.005 PubMedCrossRefGoogle Scholar
  7. Dean L (2005) Blood groups and red cell antigensGoogle Scholar
  8. Gudbjartsson DF, Bjornsdottir US, Halapi E, Helgadottir A, Sulem P, Jonsdottir GM, Thorleifsson G, Helgadottir H, Steinthorsdottir V, Stefansson H, Williams C, Hui J, Beilby J, Warrington NM, James A, Palmer LJ, Koppelman GH, Heinzmann A, Krueger M, Boezen HM, Wheatley A, Altmuller J, Shin HD, Uh ST, Cheong HS, Jonsdottir B, Gislason D, Park CS, Rasmussen LM, Porsbjerg C, Hansen JW, Backer V, Werge T, Janson C, Jonsson UB, Ng MC, Chan J, So WY, Ma R, Shah SH, Granger CB, Quyyumi AA, Levey AI, Vaccarino V, Reilly MP, Rader DJ, Williams MJ, van Rij AM, Jones GT, Trabetti E, Malerba G, Pignatti PF, Boner A, Pescollderungg L, Girelli D, Olivieri O, Martinelli N, Ludviksson BR, Ludviksdottir D, Eyjolfsson GI, Arnar D, Thorgeirsson G, Deichmann K, Thompson PJ, Wjst M, Hall IP, Postma DS, Gislason T, Gulcher J, Kong A, Jonsdottir I, Thorsteinsdottir U, Stefansson K (2009) Sequence variants affecting eosinophil numbers associate with asthma and myocardial infarction. Nat Genet 41:342–347. doi:10.1038/ng.323 PubMedCrossRefGoogle Scholar
  9. Halapi E, Gudbjartsson DF, Jonsdottir GM, Bjornsdottir US, Thorleifsson G, Helgadottir H, Williams C, Koppelman GH, Heinzmann A, Boezen HM, Jonasdottir A, Blondal T, Gudjonsson SA, Thorlacius T, Henry AP, Altmueller J, Krueger M, Shin HD, Uh ST, Cheong HS, Jonsdottir B, Ludviksson BR, Ludviksdottir D, Gislason D, Park CS, Deichmann K, Thompson PJ, Wjst M, Hall IP, Postma DS, Gislason T, Kong A, Jonsdottir I, Thorsteinsdottir U, Stefansson K (2010) A sequence variant on 17q21 is associated with age at onset and severity of asthma. Eur J Hum Genet 18:902–908. doi:10.1038/ejhg.2010.38 PubMedCrossRefGoogle Scholar
  10. Harrell FE (2004) Statistical tables and plots using S and LaTeXGoogle Scholar
  11. Hollard D, Berthier R, Douady F (1975) Granulopoiesis and its regulation. Sem Hop 51:643–651PubMedGoogle Scholar
  12. Kabesch M (2010) Novel asthma-associated genes from genome-wide association studies: what is their significance? Chest 137:909–915. doi:10.1378/chest.09-1554 PubMedCrossRefGoogle Scholar
  13. Kamatani Y, Matsuda K, Okada Y, Kubo M, Hosono N, Daigo Y, Nakamura Y, Kamatani N (2010) Genome-wide association study of hematological and biochemical traits in a Japanese population. Nat Genet 42:210–215. doi:10.1038/ng.531 PubMedCrossRefGoogle Scholar
  14. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler D (2002) The human genome browser at UCSC. Genome Res 12:996–1006. doi:10.1101/gr.229102 (Article published online before print in May 2002)PubMedGoogle Scholar
  15. Laurie CC, Doheny KF, Mirel DB, Pugh EW, Bierut LJ, Bhangale T, Boehm F, Caporaso NE, Cornelis MC, Edenberg HJ, Gabriel SB, Harris EL, Hu FB, Jacobs KB, Kraft P, Landi MT, Lumley T, Manolio TA, McHugh C, Painter I, Paschall J, Rice JP, Rice KM, Zheng X, Weir BS (2010) Quality control and quality assurance in genotypic data for genome-wide association studies. Genet Epidemiol 34:591–602. doi:10.1002/gepi.20516 PubMedCrossRefGoogle Scholar
  16. Madjid M, Awan I, Willerson JT, Casscells SW (2004) Leukocyte count and coronary heart disease: implications for risk assessment. J Am Coll Cardiol 44:1945–1956. doi:10.1016/j.jacc.2004.07.056 PubMedCrossRefGoogle Scholar
  17. McCarty CA, Chisholm RL, Chute CG, Kullo IJ, Jarvik GP, Larson EB, Li R, Masys DR, Ritchie MD, Roden DM, Struewing JP, Wolf WA (2011) The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC Med Genomics 4:13. doi:10.1186/1755-8794-4-13 PubMedCrossRefGoogle Scholar
  18. Moffatt MF, Kabesch M, Liang L, Dixon AL, Strachan D, Heath S, Depner M, von Berg A, Bufe A, Rietschel E, Heinzmann A, Simma B, Frischer T, Willis-Owen SA, Wong KC, Illig T, Vogelberg C, Weiland SK, von Mutius E, Abecasis GR, Farrall M, Gut IG, Lathrop GM, Cookson WO (2007) Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma. Nature 448:470–473. doi:10.1038/nature06014 PubMedCrossRefGoogle Scholar
  19. Moffatt MF, Gut IG, Demenais F, Strachan DP, Bouzigon E, Heath S, von Mutius E, Farrall M, Lathrop M, Cookson WO (2010) A large-scale, consortium-based genomewide association study of asthma. N Engl J Med 363:1211–1221. doi:10.1056/NEJMoa0906312 PubMedCrossRefGoogle Scholar
  20. Nalls MA, Wilson JG, Patterson NJ, Tandon A, Zmuda JM, Huntsman S, Garcia M, Hu D, Li R, Beamer BA, Patel KV, Akylbekova EL, Files JC, Hardy CL, Buxbaum SG, Taylor HA, Reich D, Harris TB, Ziv E (2008) Admixture mapping of white cell count: genetic locus responsible for lower white blood cell count in the Health ABC and Jackson Heart studies. Am J Hum Genet 82:81–87. doi:10.1016/j.ajhg.2007.09.003 PubMedCrossRefGoogle Scholar
  21. Okada Y, Kamatani Y, Takahashi A, Matsuda K, Hosono N, Ohmiya H, Daigo Y, Yamamoto K, Kubo M, Nakamura Y, Kamatani N (2010) Common variations in PSMD3-CSF3 and PLCB4 are associated with neutrophil count. Hum Mol Genet 19:2079–2085. doi:10.1093/hmg/ddq080 PubMedCrossRefGoogle Scholar
  22. Patterson N, Price AL, Reich D (2006) Population structure and eigenanalysis. Plos Genetics 2:e190. doi:10.1371/journal.pgen.0020190 PubMedCrossRefGoogle Scholar
  23. Phillips C, Salas A, Sanchez JJ, Fondevila M, Gomez-Tato A, Alvarez-Dios J, Calaza M, de Cal MC, Ballard D, Lareu MV, Carracedo A (2007) Inferring ancestral origin using a single multiplex assay of ancestry-informative marker SNPs. Forensic Sci Int Genet 1:273–280. doi:10.1016/j.fsigen.2007.06.008 PubMedCrossRefGoogle Scholar
  24. Pruenster M, Rot A (2006) Throwing light on DARC. Biochem Soc Trans 34:1005–1008. doi:10.1042/BST0341005 PubMedCrossRefGoogle Scholar
  25. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575. doi:10.1086/519795 PubMedCrossRefGoogle Scholar
  26. Reich D, Nalls MA, Kao WH, Akylbekova EL, Tandon A, Patterson N, Mullikin J, Hsueh WC, Cheng CY, Coresh J, Boerwinkle E, Li M, Waliszewska A, Neubauer J, Li R, Leak TS, Ekunwe L, Files JC, Hardy CL, Zmuda JM, Taylor HA, Ziv E, Harris TB, Wilson JG (2009) Reduced neutrophil count in people of African descent is due to a regulatory variant in the Duffy antigen receptor for chemokines gene. Plos Genetics 5:e1000360. doi:10.1371/journal.pgen.1000360 PubMedCrossRefGoogle Scholar
  27. Roden DM, Pulley JM, Basford MA, Bernard GR, Clayton EW, Balser JR, Masys DR (2008) Development of a large-scale de-identified DNA biobank to enable personalized medicine. Clin Pharmacol Ther 84:362–369. doi:10.1038/clpt.2008.89 PubMedCrossRefGoogle Scholar
  28. Schnabel RB, Baumert J, Barbalic M, Dupuis J, Ellinor PT, Durda P, Dehghan A, Bis JC, Illig T, Morrison AC, Jenny NS, Keaney JF Jr, Gieger C, Tilley C, Yamamoto JF, Khuseyinova N, Heiss G, Doyle M, Blankenberg S, Herder C, Walston JD, Zhu Y, Vasan RS, Klopp N, Boerwinkle E, Larson MG, Psaty BM, Peters A, Ballantyne CM, Witteman JC, Hoogeveen RC, Benjamin EJ, Koenig W, Tracy RP (2010) Duffy antigen receptor for chemokines (Darc) polymorphism regulates circulating concentrations of monocyte chemoattractant protein-1 and other inflammatory mediators. Blood 115:5289–5299. doi:10.1182/blood-2009-05-221382 PubMedCrossRefGoogle Scholar
  29. Shankar A, Mitchell P, Rochtchina E, Tan J, Wang JJ (2007) Association between circulating white blood cell count and long-term incidence of age-related macular degeneration: the Blue Mountains Eye Study. Am J Epidemiol 165:375–382. doi:10.1093/aje/kwk022 PubMedCrossRefGoogle Scholar
  30. Skol AD, Scott LJ, Abecasis GR, Boehnke M (2006) Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet 38:209–213. doi:10.1038/ng1706 PubMedCrossRefGoogle Scholar
  31. Soranzo N, Spector TD, Mangino M, Kuhnel B, Rendon A, Teumer A, Willenborg C, Wright B, Chen L, Li M, Salo P, Voight BF, Burns P, Laskowski RA, Xue Y, Menzel S, Altshuler D, Bradley JR, Bumpstead S, Burnett MS, Devaney J, Doring A, Elosua R, Epstein SE, Erber W, Falchi M, Garner SF, Ghori MJ, Goodall AH, Gwilliam R, Hakonarson HH, Hall AS, Hammond N, Hengstenberg C, Illig T, Konig IR, Knouff CW, McPherson R, Melander O, Mooser V, Nauck M, Nieminen MS, O’Donnell CJ, Peltonen L, Potter SC, Prokisch H, Rader DJ, Rice CM, Roberts R, Salomaa V, Sambrook J, Schreiber S, Schunkert H, Schwartz SM, Serbanovic-Canic J, Sinisalo J, Siscovick DS, Stark K, Surakka I, Stephens J, Thompson JR, Volker U, Volzke H, Watkins NA, Wells GA, Wichmann HE, Van Heel DA, Tyler-Smith C, Thein SL, Kathiresan S, Perola M, Reilly MP, Stewart AF, Erdmann J, Samani NJ, Meisinger C, Greinacher A, Deloukas P, Ouwehand WH, Gieger C (2009) A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nat Genet 41:1182–1190. doi:10.1038/ng.467 PubMedCrossRefGoogle Scholar
  32. Turner S, Armstrong LL, Bradford Y, Carlson CS, Crawford DC, Crenshaw AT, de Andrade M, Doheny KF, Haines JL, Hayes G, Jarvik G, Jiang L, Kullo IJ, Li R, Ling H, Manolio TA, Matsumoto M, McCarty CA, McDavid AN, Mirel DB, Paschall JE, Pugh EW, Rasmussen LV, Wilke RA, Zuvich RL, Ritchie MD (2011) Quality control procedures for genome-wide association studies. Curr Protoc Hum Genet Chapter 1: Unit1 19. doi: 10.1002/0471142905.hg0119s68
  33. Verlaan DJ, Berlivet S, Hunninghake GM, Madore AM, Lariviere M, Moussette S, Grundberg E, Kwan T, Ouimet M, Ge B, Hoberman R, Swiatek M, Dias J, Lam KC, Koka V, Harmsen E, Soto-Quiros M, Avila L, Celedon JC, Weiss ST, Dewar K, Sinnett D, Laprise C, Raby BA, Pastinen T, Naumova AK (2009) Allele-specific chromatin remodeling in the ZPBP2/GSDMB/ORMDL3 locus associated with the risk of asthma and autoimmune disease. Am J Hum Genet 85:377–393. doi:10.1016/j.ajhg.2009.08.007 PubMedCrossRefGoogle Scholar
  34. Weijenberg MP, Feskens EJ, Kromhout D (1996) White blood cell count and the risk of coronary heart disease and all-cause mortality in elderly men. Arterioscler Thromb Vasc Biol 16:499–503PubMedCrossRefGoogle Scholar
  35. Zody MC, Jiang Z, Fung HC, Antonacci F, Hillier LW, Cardone MF, Graves TA, Kidd JM, Cheng Z, Abouelleil A, Chen L, Wallis J, Glasscock J, Wilson RK, Reily AD, Duckworth J, Ventura M, Hardy J, Warren WC, Eichler EE (2008) Evolutionary toggling of the MAPT 17q21.31 inversion region. Nat Genet 40(9):1076–1083. doi:10.1038/ng.193 PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • David R. Crosslin
    • 1
    • 4
  • Andrew McDavid
    • 3
  • Noah Weston
    • 2
  • Sarah C. Nelson
    • 4
  • Xiuwen Zheng
    • 4
  • Eugene Hart
    • 2
  • Mariza de Andrade
    • 5
  • Iftikhar J. Kullo
    • 6
  • Catherine A. McCarty
    • 7
  • Kimberly F. Doheny
    • 8
  • Elizabeth Pugh
    • 8
  • Abel Kho
    • 9
  • M. Geoffrey Hayes
    • 10
  • Stephanie Pretel
    • 11
  • Alexander Saip
    • 13
  • Marylyn D. Ritchie
    • 14
  • Dana C. Crawford
    • 12
    • 15
  • Paul K. Crane
    • 16
  • Katherine Newton
    • 2
  • Rongling Li
    • 17
  • Daniel B. Mirel
    • 18
  • Andrew Crenshaw
    • 18
  • Eric B. Larson
    • 2
  • Chris S. Carlson
    • 3
  • Gail P. Jarvik
    • 1
  • The electronic Medical Records and Genomics (eMERGE) Network
  1. 1.Department of Medicine, Division of Medical GeneticsUniversity of WashingtonSeattleUSA
  2. 2.Group Health Research InstituteSeattleUSA
  3. 3.Public Health Sciences DivisionFred Hutchinson Cancer Research CenterSeattleUSA
  4. 4.Department of BiostatisticsUniversity of WashingtonSeattleUSA
  5. 5.Division of Biomedical Statistics and InformaticsMayo ClinicRochesterUSA
  6. 6.Division of Cardiovascular DiseasesMayo ClinicRochesterUSA
  7. 7.Essentia Institute of Rural HealthDuluthUSA
  8. 8.Center for Inherited Disease ResearchJohns Hopkins UniversityBaltimoreUSA
  9. 9.Divisions of General Internal Medicine and Health and Biomedical InformaticsNorthwestern UniversityChicagoUSA
  10. 10.Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of MedicineNorthwestern UniversityChicagoUSA
  11. 11.National Center for Biotechnology InformationNational Library of Medicine, National Institutes of HealthBethesdaUSA
  12. 12.Department of Molecular Physiology and BiophysicsVanderbilt UniversityNashvilleUSA
  13. 13.Vanderbilt Institute for Clinical and Translational ResearchVanderbilt UniversityNashvilleUSA
  14. 14.Department of Biochemistry and Molecular BiologyThe Pennsylvania State UniversityUniversity ParkUSA
  15. 15.Center for Human Genetics ResearchVanderbilt UniversityNashvilleUSA
  16. 16.Department of Medicine, Division of General Internal MedicineUniversity of WashingtonSeattleUSA
  17. 17.Office of Population GenomicsNational Human Genome Research Institute, National Institutes of HealthBethesdaUSA
  18. 18.Program in Medical and Population GeneticsBroad Institute of Harvard and MITCambridgeUSA

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