Sickle cell anemia (SCA) is a paradigmatic single gene disorder caused by homozygosity with respect to a unique mutation at the β-globin locus. SCA is phenotypically complex, with different clinical courses ranging from early childhood mortality to a virtually unrecognized condition. Overt stroke is a severe complication affecting 6–8% of individuals with SCA. Modifier genes might interact to determine the susceptibility to stroke, but such genes have not yet been identified. Using Bayesian networks, we analyzed 108 SNPs in 39 candidate genes in 1,398 individuals with SCA. We found that 31 SNPs in 12 genes interact with fetal hemoglobin to modulate the risk of stroke. This network of interactions includes three genes in the TGF-β pathway and SELP, which is associated with stroke in the general population. We validated this model in a different population by predicting the occurrence of stroke in 114 individuals with 98.2% accuracy.
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Adams, R.J. et al. Stroke and conversion to high risk in children screened with transcranial Doppler ultrasound during the STOP study. Blood 103, 3689–3694 (2004).
Steinberg, M.H., Forget, B.G., Higgs, D.R. & Nagel, R.L. Disorders of Hemoglobin: Genetics, Pathophysiology, and Clinical Management (Cambridge University Press, Cambridge, 2001).
Ware, R.E., Zimmerman, S.A. & Schultz, W.H. Hydroxyurea as an alternative to blood transfusions for the prevention of recurrent stroke in children with sickle cell disease. Blood 94, 3022–3026 (1999).
Adams, R.J. et al. Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial Doppler ultrasonography. N. Engl. J. Med. 339, 5–11 (1998).
Taylor, J.G.t. et al. Variants in the VCAM1 gene and risk for symptomatic stroke in sickle cell disease. Blood 100, 4303–4309 (2002).
Hoppe, C. et al. Gene interactions and stroke risk in children with sickle cell anemia. Blood 103, 2391–2396 (2004).
Adams, R.J. et al. Alpha thalassemia and stroke risk in sickle cell anemia. Am. J. Hematol. 45, 279–282 (1994).
Platt, O.S. et al. Mortality in sickle cell disease. Life expectancy and risk factors for early death. N. Engl. J. Med. 330, 1639–1644 (1994).
Gaston, M. et al. Recruitment in the Cooperative Study of Sickle Cell Disease (CSSCD). Control Clin. Trials 8, 131S–140S (1987).
Gabriel, S.B. et al. Segregation at three loci explains familial and population risk in Hirschsprung disease. Nat. Genet. 31, 89–93 (2002).
Collins, F.S., Green, E.D., Guttmacher, A.E. & Guyer, M.S. A vision for the future of genomics research. Nature 422, 835–847 (2003).
Carlson, C.S., Eberle, M.A., Kruglyak, L. & Nickerson, D.A. Mapping complex disease loci in whole-genome association studies. Nature 429, 446–452 (2004).
Friedman, N. Inferring cellular networks using probabilistic graphical models. Science 303, 799–805 (2004).
Jansen, R. et al. A Bayesian networks approach for predicting protein-protein interactions from genomic data. Science 302, 449–453 (2003).
Lauritzen, S.L. & Sheehan, N.A. Graphical models for genetic analysis. Statist. Sci. 18, 489–514 (2004).
Cowell, R.G., Dawid, A.P., Lauritzen, S.L. & Spiegelhalter, D.J. Probabilistic Networks and Expert Systems (Springer, New York, 1999).
Chakravarti, A. Population genetics–making sense out of sequence. Nat. Genet. 21, 56–60 (1999).
Hoh, J. & Ott, J. Mathematical multi-locus approaches to localizing complex human trait genes. Nat. Rev. Genet. 4, 701–709 (2003).
Hand, D.J., Mannila, H. & Smyth, P. Principles of Data Mining (MIT Press, Cambridge, Massachusetts, 2001).
Ling, Q. et al. Annexin II regulates fibrin homeostasis and neoangiogenesis in vivo. J. Clin. Invest. 113, 38–48 (2004).
Angerio, A.D. & Lee, N.D. Sickle cell crisis and endothelin antagonists. Crit. Care Nurs. Q. 26, 225–229 (2003).
Brown, C.B., Boyer, A.S., Runyan, R.B. & Barnett, J.V. Requirement of type III TGF-beta receptor for endocardial cell transformation in the heart. Science 283, 2080–2082 (1999).
Zee, R.Y. et al. Polymorphism in the P-selectin and interleukin-4 genes as determinants of stroke: a population-based, prospective genetic analysis. Hum. Mol. Genet. 13, 389–396 (2004).
Alexander, N., Higgs, D., Dover, G. & Serjeant, G.R. Are there clinical phenotypes of homozygous sickle cell disease? Br. J. Haematol. 126, 606–611 (2004).
Steinberg, M.H. et al. Association of polymorphisms in genes of the transforming growth factor-beta pathway with sickle cell osteonecrosis. Blood 102, 262A–263A (2003).
Botstein, D. & Risch, N. Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat. Genet. 33 Suppl: 228–237 (2003).
Beaumont, M.A. & Rannala, B. The Bayesian revolution in genetics. Nat. Rev. Genet. 5, 251–261 (2004).
Ohene-Frempong, K. et al. Cerebrovascular accidents in sickle cell disease: rates and risk factors. Blood 91, 288–294 (1998).
Chiu, N.H. et al. Mass spectrometry of single-stranded restriction fragments captured by an undigested complementary sequence. Nucleic Acids Res. 28, E31 (2000).
Cooper, G.F. & Herskovitz, G.F. A Bayesian method for the induction of probabilistic networks from data. Mach. Learn. 9, 309–347 (1992).
We thank R. Adams, A. Anderson and R. Iyer for providing the blood samples of the individuals with stroke in the independent validation set. This work was supported by National Science Foundation and the National Heart, Lung and Blood Institute of the National Institutes of Health.
P.S. and M.F.R. have financial interests in the company that produces one of the software programs used to analyze data reported in this paper.
Box plot of the predictive probability of stroke (risk in 5 years) in an independent set of 7 stroke patients and 107 non-stroke patients obtained through logistic regression. (PDF 18 kb)
Correspondence table between SNPs in the network in Figure 2 and their RS number. (PDF 18 kb)
Results of the predictive validation. (PDF 29 kb)
Epidemiological statistics of the patient population. (PDF 10 kb)
Conditional probability distributions quantifying the network in Figure 2. (PDF 12 kb)
Summary statistics of the logistic regression model. (PDF 12 kb)
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Sebastiani, P., Ramoni, M., Nolan, V. et al. Genetic dissection and prognostic modeling of overt stroke in sickle cell anemia. Nat Genet 37, 435–440 (2005). https://doi.org/10.1038/ng1533
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