Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 358

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium

Open access
Ganesh, Santhi K, Zakai, Neil A, van Rooij, Frank J A, Soranzo, Nicole, Smith, Albert V, Nalls, Michael A, Chen, Ming-Huei, Kottgen, Anna, Glazer, Nicole L, Dehghan, Abbas, Kuhnel, Brigitte, Aspelund, Thor, Yang, Qiong, Tanaka, Toshiko, Jaffe, Andrew, Bis, Joshua C M, Verwoert, Germaine C, Teumer, Alexander, Fox, Caroline S, Guralnik, Jack M, Ehret, Georg B, Rice, Kenneth, Felix, Janine F, Rendon, Augusto, Eiriksdottir, Gudny, Levy, Daniel, Patel, Kushang V, Boerwinkle, Eric, Rotter, Jerome I, Hofman, Albert, Sambrook, Jennifer G, Hernandez, Dena G, Zheng, Gang, Bandinelli, Stefania, Singleton, Andrew B, Coresh, Josef, Lumley, Thomas, Uitterlinden, André G, vanGils, Janine M, Launer, Lenore J, Cupples, L Adrienne, Oostra, Ben A, Zwaginga, Jaap-Jan, Ouwehand, Willem H, Thein, Swee-Lay, Meisinger, Christa, Deloukas, Panos, Nauck, Matthias, Spector, Tim D, Gieger, Christian, Gudnason, Vilmundur, van Duijn, Cornelia M, Psaty, Bruce M, Ferrucci, Luigi, Chakravarti, Aravinda, Greinacher, Andreas, O'Donnell, Christopher J, Witteman, Jacqueline C M, Furth, Susan, Cushman, Mary, Harris, Tamara B, Lin, Jing-Ping·2009·Nature Genetics

Abstract

Measurements of erythrocytes within the blood are important clinical traits and can indicate various hematological disorders. We report here genome-wide association studies (GWAS) for six erythrocyte traits, including hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and red blood cell count (RBC). We performed an initial GWAS in cohorts of the CHARGE Consortium totaling 24,167 individuals of European ancestry and replication in additional independent cohorts of the HaemGen Consortium totaling 9,456 individuals. We identified 23 loci significantly associated with these traits in a meta-analysis of the discovery and replication cohorts (combined P values ranging from 5 × 10−8 to 7 × 10−86). Our findings include loci previously associated with these traits (HBS1L-MYB, HFE, TMPRSS6, TFR2, SPTA1) as well as new associations (EPO, TFRC, SH2B3 and 15 other loci). This study has identified new determinants of erythrocyte traits, offering insight into common variants underlying variation in erythrocyte measures.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/ng.466

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 11 references

Research works printed but not linked: 55

  1. Havlik, R.J. et al. Evidence for additional blood pressure correlates in adults 20–56 years old. Circulation 61, 710–715 (1980). · DOI
  2. Tell, G.S. et al. Correlates of blood pressure in community-dwelling older adults. The Cardiovascular Health Study. Cardiovascular Health Study (CHS) Collaborative Research Group. Hypertension 23, 59–67 (1994). · DOI
  3. Zakai, N.A. et al. A prospective study of anemia status, hemoglobin concentration, and mortality in an elderly cohort: the Cardiovascular Health Study. Arch. Intern. Med. 165, 2214–2220 (2005). · DOI · Paper page
  4. Whitfield, J.B. & Martin, N.G. Genetic and environmental influences on the size and number of cells in the blood. Genet. Epidemiol. 2, 133–144 (1985). · doi:10.1002/gepi.1370020204
  5. Evans, D.M., Frazer, I.H. & Martin, N.G. Genetic and environmental causes of variation in basal levels of blood cells. Twin Res. 2, 250–257 (1999). · doi:10.1375/twin.2.4.250
  6. Lin, J.P. et al. Evidence for linkage of red blood cell size and count: genome-wide scans in the Framingham Heart Study. Am. J. Hematol. 82, 605–610 (2007). · DOI
  7. McLaren, C.E. et al. Determinants and characteristics of mean corpuscular volume and hemoglobin concentration in white HFE C282Y homozygotes in the hemochromatosis and iron overload screening study. Am. J. Hematol. 82, 898–905 (2007). · DOI
  8. Zeng, S.M., Yankowitz, J., Widness, J.A. & Strauss, R.G. Etiology of differences in hematocrit between males and females: sequence-based polymorphisms in erythropoietin and its receptor. J. Gend. Specif. Med. 4, 35–40 (2001).
  9. Zeng, S.M., Yankowitz, J., Widness, J.A. & Strauss, R.G. Sequence-based polymorphisms in members of the apoptosis Bcl-2 gene family and their association with hematocrit level. J. Gend. Specif. Med. 6, 36–42 (2003).
  10. Menzel, S. et al. The HBS1L-MYB intergenic region on chromosome 6q23.3 influences erythrocyte, platelet, and monocyte counts in humans. Blood 110, 3624–3626 (2007). · DOI
  11. Iliadou, A. et al. Genomewide scans of red cell indices suggest linkage on chromosome 6q23. J. Med. Genet. 44, 24–30 (2007). · doi:10.1136/jmg.2006.043521
  12. Yang, Q., Kathiresan, S., Lin, J.P., Tofler, G.H. & O'Donnell, C.J. Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study. BMC Med. Genet. 8 (Suppl. 1), S12 (2007). · DOI
  13. Lin, J.P., O'Donnell, C.J., Levy, D. & Cupples, L.A. Evidence for a gene influencing haematocrit on chromosome 6q23–24: genomewide scan in the Framingham Heart Study. J. Med. Genet. 42, 75–79 (2005). · doi:10.1136/jmg.2004.021097
  14. Psaty, B.M. et al. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: design of prospective meta-analyses of genome-wide association studies from five cohorts. Circ. Cardiovasc. Genet. 2, 73–80 (2009). · DOI · Paper page
  15. Agre, P., Casella, J.F., Zinkham, W.H., McMillan, C. & Bennett, V. Partial deficiency of erythrocyte spectrin in hereditary spherocytosis. Nature 314, 380–383 (1985). · DOI
  16. Marchesi, S.L. et al. Mutant forms of spectrin alpha-subunits in hereditary elliptocytosis. J. Clin. Invest. 80, 191–198 (1987). · doi:10.1172/jci113047
  17. Roest, M. et al. Heterozygosity for a hereditary hemochromatosis gene is associated with cardiovascular death in women. Circulation 100, 1268–1273 (1999). · DOI
  18. Tuomainen, T.P. et al. Increased risk of acute myocardial infarction in carriers of the hemochromatosis gene Cys282Tyr mutation: a prospective cohort study in men in eastern Finland. Circulation 100, 1274–1279 (1999). · DOI · Paper page
  19. Swinkels, D.W. & Wetzels, J.F. Hepcidin: a new tool in the management of anaemia in patients with chronic kidney disease? Nephrol. Dial. Transplant. 23, 2450–2453 (2008). · DOI
  20. Finberg, K.E. et al. Mutations in TMPRSS6 cause iron-refractory iron deficiency anemia (IRIDA). Nat. Genet. 40, 569–571 (2008). · DOI · Paper page
  21. Kerenyi, M.A. et al. Stat5 regulates cellular iron uptake of erythroid cells via IRP-2 and TfR-1. Blood 112, 3878–3888 (2008). · DOI
  22. Roetto, A. et al. Hemochromatosis due to mutations in transferrin receptor 2. Blood Cells Mol. Dis. 29, 465–470 (2002). · DOI
  23. Bea, S. et al. Diffuse large B-cell lymphoma subgroups have distinct genetic profiles that influence tumor biology and improve gene-expression-based survival prediction. Blood 106, 3183–3190 (2005). · DOI · Paper page
  24. Sankaran, V.G. et al. Human fetal hemoglobin expression is regulated by the developmental stage-specific repressor BCL11A. Science 322, 1839–1842 (2008). · DOI · Paper page
  25. Higgs, D.R. & Wood, W.G. Genetic complexity in sickle cell disease. Proc. Natl. Acad. Sci. USA 105, 11595–11596 (2008). · DOI
  26. Sandberg, M.L. et al. c-Myb and p300 regulate hematopoietic stem cell proliferation and differentiation. Dev. Cell 8, 153–166 (2005). · DOI · Paper page
  27. Emambokus, N. et al. Progression through key stages of haemopoiesis is dependent on distinct threshold levels of c-Myb. EMBO J. 22, 4478–4488 (2003). · DOI · Paper page
  28. Gudbjartsson, D.F. et al. Sequence variants affecting eosinophil numbers associate with asthma and myocardial infarction. Nat. Genet. 41, 342–347 (2009). · DOI · Paper page
  29. Newton-Cheh, C. et al. Genome-wide association study identifies eight loci associated with blood pressure. Nat. Genet. 41, 666–676 (2009). · DOI · Paper page
  30. Hunt, K.A. et al. Newly identified genetic risk variants for celiac disease related to the immune response. Nat. Genet. 40, 395–402 (2008). · DOI · Paper page
  31. Smyth, D.J. et al. Shared and distinct genetic variants in type 1 diabetes and celiac disease. N. Engl. J. Med. 359, 2767–2777 (2008). · DOI · Paper page
  32. Velazquez, L. et al. Cytokine signaling and hematopoietic homeostasis are disrupted in Lnk-deficient mice. J. Exp. Med. 195, 1599–1611 (2002). · DOI · Paper page
  33. Saxton, T.M. et al. Abnormal mesoderm patterning in mouse embryos mutant for the SH2 tyrosine phosphatase Shp-2. EMBO J. 16, 2352–2364 (1997). · DOI · Paper page
  34. Jongmans, M. et al. Genotypic and phenotypic characterization of Noonan syndrome: new data and review of the literature. Am. J. Med. Genet. A. 134A, 165–170 (2005). · DOI
  35. Kalidas, K. et al. Genetic heterogeneity in LEOPARD syndrome: two families with no mutations in PTPN11. J. Hum. Genet. 50, 21–25 (2005). · DOI
  36. Tartaglia, M. et al. Somatic mutations in PTPN11 in juvenile myelomonocytic leukemia, myelodysplastic syndromes and acute myeloid leukemia. Nat. Genet. 34, 148–150 (2003). · DOI · Paper page
  37. Tong, Z. et al. Promoter polymorphism of the erythropoietin gene in severe diabetic eye and kidney complications. Proc. Natl. Acad. Sci. USA 105, 6998–7003 (2008). · DOI · Paper page
  38. Wannamethee, G. & Shaper, A.G. Haematocrit: relationships with blood lipids, blood pressure and other cardiovascular risk factors. Thromb. Haemost. 72, 58–64 (1994). · doi:10.1055/s-0038-1648811
  39. Gagnon, D.R., Zhang, T.J., Brand, F.N. & Kannel, W.B. Hematocrit and the risk of cardiovascular disease—the Framingham study: a 34-year follow-up. Am. Heart J. 127, 674–682 (1994). · DOI · Paper page
  40. Elwood, P.C., Waters, W.E., Benjamin, I.T. & Sweetnam, P.M. Mortality and anaemia in women. Lancet 1, 891–894 (1974). · DOI
  41. Sarnak, M.J. et al. Anemia as a risk factor for cardiovascular disease in The Atherosclerosis Risk in Communities (ARIC) study. J. Am. Coll. Cardiol. 40, 27–33 (2002). · DOI · Paper page
  42. de Simone, G. et al. Association of blood pressure with blood viscosity in american indians: the Strong Heart Study. Hypertension 45, 625–630 (2005). · DOI
  43. Letcher, R.L., Chien, S., Pickering, T.G. & Laragh, J.H. Elevated blood viscosity in patients with borderline essential hypertension. Hypertension 5, 757–762 (1983). · DOI
  44. Sharp, D.S. et al. Mean red cell volume as a correlate of blood pressure. Circulation 93, 1677–1684 (1996). · doi:10.1161/01.cir.93.9.1677
  45. Wells, R.E. Jr. & Merrill, E.W. Influence of flow properties of blood upon viscosity-hematocrit relationships. J. Clin. Invest. 41, 1591–1598 (1962). · DOI · Paper page
  46. Ott, E.O., Lechner, H. & Aranibar, A. High blood viscosity syndrome in cerebral infarction. Stroke 5, 330–333 (1974). · doi:10.1161/01.str.5.3.330
  47. Gollob, M.H. et al. Identification of a gene responsible for familial Wolff-Parkinson-White syndrome. N. Engl. J. Med. 344, 1823–1831 (2001). · DOI · Paper page
  48. Gollob, M.H. et al. Novel PRKAG2 mutation responsible for the genetic syndrome of ventricular preexcitation and conduction system disease with childhood onset and absence of cardiac hypertrophy. Circulation 104, 3030–3033 (2001). · DOI · Paper page
  49. Beutler, E. & Waalen, J. The definition of anemia: what is the lower limit of normal of the blood hemoglobin concentration? Blood 107, 1747–1750 (2006). · DOI · Paper page
  50. Servin, B. & Stephens, M. Imputation-based analysis of association studies: candidate regions and quantitative traits. PLoS Genet. 3, e114 (2007). · DOI · Paper page
  51. Watkins, N.A. et al. A HaemAtlas: characterizing gene expression in differentiated human blood cells. Blood 113, e1–e9 (2009). · DOI · Paper page
  52. da Costa Martins, P. et al. P-selectin glycoprotein ligand-1 is expressed on endothelial cells and mediates monocyte adhesion to activated endothelium. Arterioscler. Thromb. Vasc. Biol. 27, 1023–1029 (2007). · DOI
  53. Du, P., Kibbe, W.A. & Lin, S.M. lumi: a pipeline for processing Illumina microarray. Bioinformatics 24, 1547–1548 (2008). · DOI · Paper page
  54. Hamosh, A (ed.). Online Mendelian Inheritance in Man (McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University (Baltimore, Maryland, USA) and National Center for Biotechnology Information, National Library of Medicine (Bethesda, Maryland, USA)). <http://www.ncbi.nlm.nih.gov/omim> .
  55. Becker, K.G., Barnes, K.C., Bright, T.J. & Wang, S.A. The genetic association database. Nat. Genet. 36, 431–432 (2004). · DOI · Paper page

Cited by

See all 358

Metadata

Authors
Ganesh, S. K., Zakai, N. A., van Rooij, F. J. A., Soranzo, N., Smith, A. V., Nalls, M. A., Chen, M.-H., Kottgen, A., Glazer, N. L., Dehghan, A., Kuhnel, B., Aspelund, T., Yang, Q., Tanaka, T., Jaffe, A., Bis, J. C. M., Verwoert, G. C., Teumer, A., Fox, C. S., Guralnik, J. M., Ehret, G. B., Rice, K., Felix, J. F., Rendon, A., Eiriksdottir, G., Levy, D., Patel, K. V., Boerwinkle, E., Rotter, J. I., Hofman, A., Sambrook, J. G., Hernandez, D. G., Zheng, G., Bandinelli, S., Singleton, A. B., Coresh, J., Lumley, T., Uitterlinden, A. G., vanGils, J. M., Launer, L. J., Cupples, L. A., Oostra, B. A., Zwaginga, J.-J., Ouwehand, W. H., Thein, S.-L., Meisinger, C., Deloukas, P., Nauck, M., Spector, T. D., Gieger, C., Gudnason, V., van Duijn, C. M., Psaty, B. M., Ferrucci, L., Chakravarti, A., Greinacher, A., O'Donnell, C. J., Witteman, J. C. M., Furth, S., Cushman, M., Harris, T. B., & Lin, J.-P.
Venue
Nature Genetics
Published
2009-10-11
Volume
41
Issue
11
Pages
1191-1198
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
OpenAlex
W1971476169
Cited by
358
References
11
FWCI
19.96
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium. https://app.cochat.ai/papers/10.1038/ng.466
The paper
Ganesh, S. K., Zakai, N. A., van Rooij, F. J. A., Soranzo, N., Smith, A. V., Nalls, M. A., Chen, M.-H., Kottgen, A., Glazer, N. L., Dehghan, A., Kuhnel, B., Aspelund, T., Yang, Q., Tanaka, T., Jaffe, A., Bis, J. C. M., Verwoert, G. C., Teumer, A., Fox, C. S., . . . Lin, J.-P. (2009). Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium. Nature Genetics. https://doi.org/10.1038/ng.466

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.