Mammalian Genome

, Volume 18, Issue 5, pp 361–372 | Cite as

Quantitative trait loci for peripheral blood cell counts: a study in baboons

  • Angéline BertinEmail author
  • Michael C. Mahaney
  • Laura A. Cox
  • Jeffrey Rogers
  • John L. VandeBerg
  • Carlo Brugnara
  • Orah S. Platt


Increasingly, baseline peripheral blood cell counts are implicated as risk factors for common complex diseases. While genetic influences on these hematologic parameters are firmly established, the genetic architecture of the blood counts is still poorly understood. In this article we used data from 582 healthy pedigreed baboons and variance components methods to localize quantitative trait loci (QTLs) influencing complete blood count variables. Besides performing genome-wide linkage scans for each trait individually, we conducted bivariate linkage analyses for all pairwise trait combinations to also identify pleiotropic QTLs influencing several blood counts. While significant and suggestive QTLs were localized throughout the genome (LOD range: 1.5–3.5), chromosomal regions associated with the expression of various hematologic parameters stand out. In particular, our results provide significant and consistent evidence for a QTL on the orthologous human chromosome 1p that is shared by several blood counts, mainly erythrocyte parameters. In addition, multiple suggestive evidence of linkage was detected on the orthologous human chromosomes 10 (near the q-terminus) and 19 (centromeric section). Future studies should help identify the genes responsible for these QTL and elucidate their role on baseline variation in hematologic indicators of health and disease.


Genetic Correlation Mean Platelet Volume Mean Corpuscular Volume Additive Genetic Effect Inverse Gaussian Normalization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank D. Winnier and two anonymous reviewers for constructive comments on an earlier version of the manuscript and D. Newman for outstanding technical assistance. This work was supported by grants from the National Institutes of Health (NIH): R01 HL068922 (OSP), R01 HL054141 (MCM), P01 HL028972 (JLV, MCM, JR), P51 RR013086 (JLV, MCM, JR), and R01 RR08781 (JR). This investigation was conducted in facilities constructed with support from Research Facilities Improvement Program Grant Number C06 RR13556 from the National Center for Research Resources, National Institutes of Health.


  1. Allison DB, Neale MC, Zannolli R, Schork NJ, Amos CI, et al. (1999) Testing the robustness of the likelihood-ratio test in a variance-component quantitative-trait loci-mapping procedure. Am J Hum Genet 65:531–544PubMedCrossRefGoogle Scholar
  2. Almasy L, Blangero J (1998) Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 62:1198–1211PubMedCrossRefGoogle Scholar
  3. Almasy L, Dyer TD, Blangero J (1997) Bivariate quantitative trait linkage analysis: Pleiotropy versus co-incident linkages. Genet Epidemiol 14:953–958PubMedCrossRefGoogle Scholar
  4. Amos CI (1994) Robust variance-components approach for assessing genetic-linkage in pedigrees. Am J Hum Genet 54:535–543PubMedGoogle Scholar
  5. Amos CI, de Andrade M, Zhu DK (2001) Comparison of multivariate tests for genetic linkage. Hum Hered 51:133–144PubMedCrossRefGoogle Scholar
  6. Bain BJ (1996) Ethnic and sex differences in the total and differential white cell count and platelet count. J Clin Pathol 49:664–666PubMedCrossRefGoogle Scholar
  7. Bath P, Algert C, Chapman N, Neal B (2004) Association of mean platelet volume with risk of stroke among 3134 individuals with history of cerebrovascular disease. Stroke 35:622–626PubMedCrossRefGoogle Scholar
  8. Blangero J, Williams JT, Almasy L (2000) Quantitative trait locus mapping using human pedigrees. Hum Biol 72:35–62PubMedGoogle Scholar
  9. Blangero J, Williams JT, Almasy L (2001) Variance component methods for detecting complex trait loci. Adv Genet 42:151–181 PubMedGoogle Scholar
  10. Camp NJ, Farnham JM (2001) Correcting for multiple analyses in genomewide linkage studies. Ann Hum Genet 65:577–582PubMedCrossRefGoogle Scholar
  11. Cheung CC, Martin ICA, Zenger KR, Donald JA, Thomson PC, et al. (2004) Quantitative trait loci for steady-state platelet count in mice. Mamm Genome 15:784–797PubMedCrossRefGoogle Scholar
  12. Cox LA, Mahaney MC, VandeBerg JF, Rogers J (2006) A second-generation genetic linkage map of the baboon (Papio hamadryas) genome. Genomics 88:274–281PubMedCrossRefGoogle Scholar
  13. Curtis D, Sham PC (1994) Using risk calculation to implement an extended relative pair analysis. Ann Hum Genet 58:151–162PubMedGoogle Scholar
  14. Delaunay J (2002) Molecular basis of red cell membrane disorders. Acta Haematol 108:210–218PubMedCrossRefGoogle Scholar
  15. DelValle G, Taniguchi N (1995) Genetic variation of some physiological traits of clonal ayu (Plecoglossus altivelis) under stressed and non-stressed conditions. Aquaculture 137:193–202CrossRefGoogle Scholar
  16. Edwards A (1992) Likelihood (Baltimore: Johns Hopkins University Press)Google Scholar
  17. Evans DM (2002) The power of multivariate quantitative-trait loci linkage analysis is influenced by the correlation between variables. Am J Hum Genet 70:1599–1602PubMedCrossRefGoogle Scholar
  18. Evans DM, Frazer IH, Martin NG (1999) Genetic and environmental causes of variation in basal levels of blood cells. Twin Res 2:250–257PubMedCrossRefGoogle Scholar
  19. Evans DM, Zhu G, Duffy DL, Montgomery GW, Frazer IH, Martin NG (2004) Multivariate QTL linkage analysis suggests a QTL for platelet count on chromosome 19q. Eur J Hum Genet 12:835–842PubMedCrossRefGoogle Scholar
  20. Feingold E, Brown PO, Siegmund D (1993) Gaussian models for genetic-linkage analysis using complete high-resolution maps of identity by descent. Am J Hum Genet 53:234–251PubMedGoogle Scholar
  21. Garner C, Tatu T, Reittie JE, Littlewood T, Darley J, et al. (2000) Genetic influences on F cells and other hematologic variables: a twin heritability study. Blood 95:342–346PubMedGoogle Scholar
  22. Gregg D, Goldschmidt-Clermont PJ (2003) Platelets and cardiovascular disease. Circulation 108:E88–E90PubMedCrossRefGoogle Scholar
  23. Haltmayer M, Mueller T, Luft C, Poelz W, Haidinger D (2002) Erythrocyte mean corpuscular volume associated with severity of peripheral arterial disease: An angiographic evaluation. Ann Vasc Surg 16:474–479PubMedCrossRefGoogle Scholar
  24. Hampton JW, Matthews C (1966) Similarities between baboon and human blood clotting. J Appl Physiol 21:1713 PubMedGoogle Scholar
  25. Hanson SR, Harker LA (1987) Baboon models of acute arterial thrombosis. Thromb Haemost 58:801–805PubMedGoogle Scholar
  26. Heath SC (1997) Markov chain Monte Carlo segregation and linkage analysis for oligogenic models. Am J Hum Genet 61:748–760PubMedGoogle Scholar
  27. Heath SC, Snow GL, Thompson EA, Tseng C, Wijsman EM (1997) MCMC segregation and linkage analysis. Genet Epidemiol 14:1011–1016PubMedCrossRefGoogle Scholar
  28. Herodin F, Thullier P, Garin D, Drouet M (2005) Nonhuman primates are relevant models for research in hematology, immunology and virology. Eur Cytokine Netw 16:104–116PubMedGoogle Scholar
  29. Hoffman M, Blum A, Baruch R, Kaplan E, Benjamin M (2004) Leukocytes and coronary heart disease. Atherosclerosis 172:1–6PubMedCrossRefGoogle Scholar
  30. Kato K, Kanaji T, Russell S, Kunicki TJ, Furihata K, et al. (2003) The contribution of glycoprotein VI to stable platelet adhesion and thrombus formation illustrated by targeted gene deletion. Blood 102:1701–1707PubMedCrossRefGoogle Scholar
  31. Kilicli-Camur N, Demirtunc R, Konuralp C, Eskiser A, Basaran Y (2005) Could mean platelet volume be a predictive marker for acute myocardial infarction? Med Sci Monitor 11:CR387–CR392Google Scholar
  32. Kobayashi T, Miyoshi Y, Yamaoka K, Yano E (2001) Relationship between hematological parameters and incidence of ischemic heart diseases among Japanese white-collar male workers. J Occup Health 43:85–89Google Scholar
  33. KristalBoneh E, Froom P, Harari G, Ribak J (1997) Seasonal differences in blood cell parameters and the association with cigarette smoking. Clin Lab Haematol 19:177–181CrossRefGoogle Scholar
  34. Lander E, Kruglyak L (1995) Genetic dissection of complex traits – guidelines for interpreting and reporting linkage results. Nat Genet 11:241–247PubMedCrossRefGoogle Scholar
  35. Lin JP, O’Donnell CJ, Levy D, Cupples LA (2005) Evidence for a gene influencing haematocrit on chromosome 6q23–24: genomewide scan in the Framingham Heart Study. J Med Genet 42:75–79PubMedCrossRefGoogle Scholar
  36. Madjid M, Awan I, Willerson JT, Casscells SW (2004) Leukocyte count and coronary heart disease – Implications for risk assessment. J Am Coll Cardiol 44:1945–1956PubMedCrossRefGoogle Scholar
  37. Mahaney MC, Jaquish CE, Comuzzie AG (1995) Statistical genetics of normal variation in family data for oligogenic diseases. Genet Epidemiol 12:783–787PubMedCrossRefGoogle Scholar
  38. Mahaney MC, Brugnara C, Lease LR, Platt OS (2005) Genetic influences on peripheral blood cell counts: a study in baboons. Blood 106:1210–1214PubMedCrossRefGoogle Scholar
  39. Mueller T, Haidinger D, Luft C, Horvath W, Poelz W, et al. (2001) Association between erythrocyte mean corpuscular volume and peripheral arterial disease in male subjects – A case control study. Angiology 52:605–613PubMedCrossRefGoogle Scholar
  40. Mueller T, Luft C, Haidinger D, Poelz W, Haltmayer M (2002) Erythrocyte mean corpuscular volume associated with the anatomical distribution in peripheral arterial disease. Vasa 31:81–85PubMedCrossRefGoogle Scholar
  41. National Research Council (1996) Guide for Care and Use of Laboratory Animals, National Academy of Sciences, ed. (Washington, DC: National Academy Press)Google Scholar
  42. Ott J (1988) Analysis of human genetic linkage (Baltimore: Johns Hopkins University Press)Google Scholar
  43. Peters LL, Lambert AJ, Zhang WD, Churchill GA, Brugnara C, et al. (2006) Quantitative trait loci for baseline erythroid traits. Mamm Genome 17:298–309PubMedCrossRefGoogle Scholar
  44. Peters LL, Zhang WD, Lambert AJ, Brugnara C, Churchill GA, et al. (2005) Quantitative trait loci for baseline white blood cell count, platelet count, and mean platelet volume. Mamm Genome 16:749–763PubMedCrossRefGoogle Scholar
  45. Puddu PE, Lanti M, Menotti A, Mancini M, Zanchetti A, et al. (2002) Red blood cell count in short-term prediction of cardiovascular disease incidence in the Gubbio Population Study. Acta Cardiol 57:177–185PubMedCrossRefGoogle Scholar
  46. Rogers J, Mahaney MC, Witte SM, Nair S, Newman D, et al. (2000) A genetic linkage map of the baboon (Papio hamadryas) genome based on human microsatellite polymorphisms. Genomics 67:237–247PubMedCrossRefGoogle Scholar
  47. Self SG, Liang KY (1987) Asymptotic properties of maximum-likelihood estimators and likelihood ratio tests under nonstandard conditions. J Am Stat Assoc 82:605–610CrossRefGoogle Scholar
  48. Smith JD, Bhasin JM, Baglione J, Settle M, Xu YM, et al. (2006) Atherosclerosis susceptibility loci identified from a strain intercross of apolipoprotein E-deficient mice via a high-density genome scan. Arterioscler Thromb Vasc Biol 26:597–603PubMedCrossRefGoogle Scholar
  49. Wattrang E, Almqvist M, Johansson A, Fossum C, Wallgren P, et al. (2005) Confirmation of QTL on porcine chromosomes 1 and 8 influencing leukocyte numbers, haematological parameters and leukocyte function. Anim Genet 36:337–345PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Angéline Bertin
    • 1
    Email author
  • Michael C. Mahaney
    • 1
    • 2
  • Laura A. Cox
    • 1
    • 2
  • Jeffrey Rogers
    • 1
    • 2
  • John L. VandeBerg
    • 1
    • 2
  • Carlo Brugnara
    • 3
  • Orah S. Platt
    • 3
  1. 1.Department of GeneticsSouthwest Foundation for Biomedical ResearchSan AntonioUSA
  2. 2.Southwest National Primate Research CenterSouthwest Foundation for Biomedical ResearchSan AntonioUSA
  3. 3.Children’s Hospital BostonHarvard Medical SchoolBostonUSA

Personalised recommendations