Polymorphism in the P-selectin and interleukin-4
genes as determinants of stroke: a
population-based, prospective genetic analysis
Robert Y.L. Zee1,*, Nancy R. Cook1, Suzanne Cheng2, Rebecca Reynolds2,
Henry A. Erlich2, Klaus Lindpaintner3and Paul M. Ridker1
1Center for Cardiovascular Disease Prevention and LeDucq Center for Molecular and Genetic Epidemiology,
Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA,2Department of Human Genetics,
Roche Molecular Systems, Alameda, CA, USA and3Roche Center for Medical Genomics, Basel, Switzerland
Received September 25, 2003; Revised and Accepted December 9, 2003
Candidate gene polymorphisms related to inflammation, thrombosis and lipid metabolism have been
implicated in the development of ischemic stroke. Using DNA samples collected at baseline in a prospective
cohort of 14916 initially healthy American men, we genotyped 92 polymorphisms from 56 candidate genes
among 319 individuals who subsequently developed ischemic stroke and among 2092 individuals who
remained free of reported cardiovascular disease over a mean follow-up period of 13.2 years to prospectively
determine whether candidate gene polymorphisms contribute to stroke risk. After adjustment for multiple
comparisons and age, smoking, body mass index, hypertension, hyperlipidemia and diabetes, two related
to inflammation [a val640leu polymorphism in the P-selectin gene (OR¼1.63, 95% CI 1.22–2.17, P¼0.001) and
a C582T polymorphism in the interleukin-4 gene (OR¼1.40, 95% CI 1.13–1.73, P¼0.003)] were found to be
independent predictors of thrombo-embolic stroke. In bootstrap replications, the inclusion of genetic
information from these two polymorphisms improved prediction models for stroke based upon traditional
risk factors alone (ROC 0.67 versus 0.64). Two polymorphisms related to thrombosis (an arg353gln
polymorphism in the factor VII gene and a T11053G polymorphism in the plasminogen activator inhibitor
type-1 gene) and one related to lipid metabolism [a C(-482)T polymorphism in the apolipoprotein CIII gene]
achieved nominal significance, but were not found to be independent predictors after multiple comparison
adjustment. Two inflammatory candidate gene polymorphisms were identified which were independently
associated with incident stroke. These population-based data demonstrate the ability of prospective,
epidemiological studies to test candidate gene associations for athero-thrombotic disease.
Completion of the initial sequencing of the human genome
project brings substantial promise to clinical medicine, includ-
ing the potential to develop genetic panels for the assessment
of disease risk (1). One approach to this issue is the evaluation
of selected polymorphisms in genes, which are suspected of
being associated with disease, either because they are known
to encode for specific proteins related to the disease process
or because they lie within chromosomal regions identified in
linkage studies. Although retrospective case–control studies
are frequently used to assess relationships between candi-
date markers and disease endpoints, a preferred setting for such
analyses is large prospective population cohorts where an
adequate number of individuals can be evaluated to ensure
stable estimates of the background allele and genotype
frequencies, and where the number of incident events is
sufficient to provide both informative null data as well as
narrow estimates for any observed positive effects. If the
population under study derives from a homogeneous prospec-
tivecohort of initially healthy individuals such that case status is
defined solely by the subsequent development of disease,
inadvertent epidemiological bias arising from case selection
criteria or from population stratification can be minimized (2,3).
With regard to occlusive cardiovascular events, candidate
genes of interest include those associated with lipid metabolism,
*To whom correspondence should be addressed at: Center for Cardiovascular Disease Prevention, Brigham and Women’s Hospital, 900 Commonwealth
Avenue East, Boston, MA 02215, USA. Tel: þ1 6177328175; Fax: þ1 6177839212; Email: firstname.lastname@example.org
Human Molecular Genetics, 2004, Vol. 13, No. 4
Advance Access published on December 17, 2003
Human Molecular Genetics, Vol. 13, No. 4 # Oxford University Press 2004; all rights reserved
by guest on June 4, 2013
18. Lane, A., Green, F., Scarabin, P.Y., Nicaud, V., Bara, L., Humphries, S.,
Evans, A., Luc, G., Cambou, J.P., Arveiler, D. and Cambien, F. (1996)
Factor VII arg/gln353 polymorphism determines factor VII coagulant
activity in patients with myocardial infarction (MI) and control subjects in
Belfast and in France but is not a strong indicator of MI risk in the ECTIM
study. Atherosclerosis, 119, 119–127.
19. Iacoviello, L., Di Casstelnuova, A., de Knijff, P., D’Orazio, A., Amore, C.,
Arboretti, R., Kluft, C. and Benedetta Donati, M. (1998) Polymorphisms in
the coagulation factor VII gene and the risk of myocardial infarction. New
Engl. J. Med., 338, 79–85.
20. Girelli, D., Russo, C., Ferraresi, P., Olivieri, O., Pinotti, M., Friso, S.,
Manzato, F., Mazzucco, A., Bernardi, F. and Corrocher, R. (2000)
Polymorphisms in the factor VII gene and the risk of myocardial
infarction in patients with coronary artery disease. New Engl. J. Med.,
21. Doggen, C.J.M., Cats, V.M., Bertina, R.M., Reitsma, P.H.,
Vandenbroucke, J.P. and Rosendaal, F.R. (1998) A genetic propensity to
high factor VII is not associated with the risk of myocardial infarction in
men. Thromb. Haemost., 80, 281–285.
22. Hamsten, A., Wiman, B., Defaire, U. and Blomback, M. (1985) Increased
plasma level of a rapid inhibitor of tissue plasminogen activator in young
survivors of myocardial infarction. New Engl. J. Med., 313, 1557–1563.
24. Steering Committee of the Physicians’ Health Study Research Group
(1989) Final report of the aspirin component of the ongoing Physicians’
Health Study. New Engl. J. Med., 321, 129–135.
25. Ridker, P.M., Hennekens, C.H., Lindpaintner, K., Stampfer, M.J.,
Eisenberg, P.R. and Miletich, J.P. (1995) Mutation in the gene coding for
thrombosis in apparently healthy men. New. Engl. J. Med., 332, 912–917.
26. Lindpaintner, K., Pfeffer, M.A., Kreutz, R., Stampfer, M.J., Grodstein, F.,
LaMotte, F., Buring, J. and Hennekens, C.H. (1993) A prospective
evaluation of an angiotensin-converting-enzyme gene polymorphism and
the risk of ischemic heart disease. New Engl. J. Med., 332, 706–711.
27. Cheng, S., Pallaud, C., Grow, M., Scharf, S.J., Erlich, H.A., Klitz, W.,
Pullinger, C.R., Malloy, M.J., Kane, J.P., Siest, G. and Visvikis, S.
(1998) A multilocus genotyping assay for cardiovascular disease. Clin.
Chem. Lab. Med., 36, 561–566.
28. Cheng, S., Grow, M.A., Pallaud, C., Klitz, W., Erlich, H.A., Visvikis, S.,
Chen, J.J., Pullinger, C.R., Malloy, M.J., Siest, G. and Kane, J.P. (1999) A
multilocus genotyping assay for candidate markers of cardiovascular
disease risk. Genome Res., 9, 936–949.
29. Ridker, P.M., Hennekens, C.H. and Miletich, J.P. (1999) G20210A
mutation in the prothrombin gene and the risk of myocardial infarction,
stroke, and venous thrombosis in a large cohort of US men. Circulation,
30. Zee, R.Y.L., Lindpaintner, K., Struk, B., Hennekens, C.H. and Ridker, P.M.
(2001) A prospective evaluation of the CD14 C(-260)T gene polymorphism
and the risk of myocardial infarction. Atherosclerosis, 154, 699–702.
31. Weir, B.S. (1996) Genetic Data Analysis II: Methods for discrete
population genetic data. Sinauer Associates, Sunderland, MA.
32. Schwartz, G. (1978) Estimating the dimension of a model. Ann. Stat., 6,
33. Westfall, P.H. and Young, S.S. (1989) P value adjustments for
multiple tests in multivariable binomial models. J. Am. Stat. Assoc.,
34. Mosig, M.O., Lipkin, E., Khutoreskaya, G., Tchourzyna, E., Soller, M. and
Friedman, A. (2001) A whole genome scan for quantitative trait loci
affecting milk protein percentage in Israeli-Holstein cattle, by means of
selective DNA pooling in a daughter design, using an adjusted false
discovery rate criterion. Genetics, 157, 1683–1698.
35. Hanley, J.A. and McNeil, B.J. (1982) The meaning and use of the
area under a receiver operating characteristic (ROC) curve. Radiology,
36. Efron, B. and Tibshirani, R. (1993) An Introduction of the Bootstrap.
Monographs on Statistics and Applied Probability. Chapman and Hall,
37. Steyerberg, E.W., Harrell, F.E., Borsboom, G.J.M., Eijkemans, M.J.C.,
Vergouwe, Y. and Habbena, J.D.F. (2000) Internal validation of predictive
models: efficiency of some procedures for logistic regression analysis.
J. Clin. Epidemiol., 54, 774–781.
38. Devlin, B. and Roeder, K. (1999) Genomic control for association studies.
Biometrics, 55, 997–1004.
39. Bacanu, S.A., Devlin, B. and Roeder, K. (2000) The power of genomic
control. Am. J. Hum. Genet., 66, 1933–1944.
396 Human Molecular Genetics, 2004, Vol. 13, No. 4
by guest on June 4, 2013