SNPs and other features as they predispose to complex disease: Genome-wide predictive analysis of a quantitative phenotype for hypertension

PLoS ONE

Volumn 6, Issue 11, 2011, Pages

  Won, Joong Ho ^a,b   Ehret, Georg ^c,d   Chakravarti, Aravinda ^c,e   Olshen, Richard A ^b  

^a VA Cooperative Studies Program   (United States)

^b STANFORD UNIVERSITY   (United States)

^c JOHNS HOPKINS UNIVERSITY   (United States)

^d GENEVA UNIVERSITY HOSPITALS   (Switzerland)

^e JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CONTROLLED STUDY; FEMALE; GENETIC ASSOCIATION; GENETIC PREDISPOSITION; GENETIC VARIABILITY; GENOTYPE; HUMAN; HYPERTENSION; MAJOR CLINICAL STUDY; MATHEMATICAL MODEL; MEAN ARTERIAL PRESSURE; PREDICTION; QUANTITATIVE ANALYSIS; REGRESSION ANALYSIS; RISK FACTOR; SINGLE NUCLEOTIDE POLYMORPHISM;

EID: 82355181996     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0027891     Document Type: Article

References (31)

1. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, et al. (2008) Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Reviews Genetics 9: 356-369.
2. Goldstein DB, (2009) Common Genetic Variation and Human Traits. N Engl J Med 360: 1696-1698.
3. Hirschhorn JN, (2009) Genomewide Association Studies - Illuminating Biologic Pathways. N Engl J Med 360: 1699-1701.
4. Kraft P, Hunter DJ, (2009) Genetic Risk Prediction - Are We There Yet? N Engl J Med 360: 1701-1703.
5. The ARIC Investigators (1989) The Atherosclerosis Risk In Communities (ARIC) Study: Design and Objectives. Am J Epidemiol 129: 687-702.
6. Franklin SS, Lopez VA, Wong ND, Mitchell GF, Larson MG, et al. (2009) Single versus combined blood pressure components and risk for cardiovascular disease: the Framingham Heart Study. Circulation 119: 243-250.
7. Strandberg TE, Salomaa VV, Vanhanen HT, Pitkälä K, Miettinen TA, (2002) Isolated diastolic hypertension, pulse pressure, and mean arterial pressure as predictors of mortality during a follow-up of up to 32 years. Journal of Hypertension 20: 399-404.
8. Levy D, Ehret GB, Rice K, Verwoert GC, Launer LJ, et al. (2009) Genome-wide association study of blood pressure and hypertension. Nat Genet 41: 677-687.
9. Hirschhorn JN, Lohmueller K, Byrne E, Hirschhorn K, (2002) A comprehensive review of genetic association studies. Genetics in Medicine: Official Journal of the American College of Medical Genetics 4: 45-61.
10. Koivukoski L, Fisher SA, Kanninen T, Lewis CM, von Wowern F, et al. (2004) Meta-analysis of genome-wide scans for hypertension and blood pressure in Caucasians shows evidence of susceptibility regions on chromosomes 2 and 3. Hum Mol Genet 13: 2325-2332.
11. Chang Y, Liu X, Kim J, Ikeda M, Layton M, et al. (2007) Multiple Genes for Essential-Hypertension Susceptibility on Chromosome 1q. The American Journal of Human Genetics 80: 253-264.
12. Efron B, Tibshirani R, Storey JD, Tusher V, (2001) Empirical Bayes Analysis of a Microarray Experiment. Journal of the American Statistical Association 96: 1151-1160.
13. Efron B, (2010) Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction. Cambridge University Press.
14. Jakobsdottir J, Gorin MB, Conley YP, Ferrell RE, Weeks DE, (2009) Interpretation of Genetic Association Studies: Markers with Replicated Highly Significant Odds Ratios May Be Poor Classifiers. PLoS Genetics 5: e1000337 Available: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2629574/. Accessed 2011 Nov 7.
15. Lee SH, van der Werf JHJ, Hayes BJ, Goddard ME, Visscher PM, (2008) Predicting Unobserved Phenotypes for Complex Traits from Whole-Genome SNP Data. PLoS Genetics 4: e1000231 Available: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2565502/. Accessed 2011 Nov 7.
16. Huang J, Lin A, Narasimhan B, Quertermous T, Hsiung CA, et al. (2004) Tree-structured supervised learning and the genetics of hypertension. Proceedings of the National Academy of Sciences of the United States of America 101: 10529-10534.
17. de Andrade M, Amos CI, Thiel TJ, (1999) Methods to estimate genetic components of variance for quantitative traits in family studies. Genetic Epidemiology 17: 64-76.
18. Morgan JN, Sonquist JA, (1963) Problems in the Analysis of Survey Data, and a Proposal. Journal of the American Statistical Association 58: 415-434.
19. Chen X, Liu C-T, Zhang M, Zhang H, (2007) A forest-based approach to identifying gene and gene gene interactions. Proceedings of the National Academy of Sciences of the United States of America 104: 19199-19203.
20. Wang M, Zhang M, Chen X, Zhang H, (2009) Detecting Genes and Gene-gene Interactions for Age-related Macular Degeneration with a Forest-based Approach. Statistics in biopharmaceutical research 1: 424-430.
21. Breiman L, Friedman JH, Olshen RA, Stone C, (1984) Classification and regression trees Cole, Pacific Grove, California, USA Chapman & Hall/CRC.
22. Park MY, Hastie T, (2008) Penalized logistic regression for detecting gene interactions. Biostat 9: 30-50.
23. Benjamini Y, Hochberg Y, (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B (Methodological) 57: 289-300.
24. Sun W, Cai TT, (2007) Oracle and adaptive compound decision rules for false discovery rate control. Journal of the American Statistical Association 102: 901-912.
25. Tobin MD, Sheehan NA, Scurrah KJ, Burton PR, (2005) Adjusting for treatment effects in studies of quantitative traits: antihypertensive therapy and systolic blood pressure. Statistics in Medicine 24: 2911-2935.
26. Wei Z, Wang K, Qu H-Q, Zhang H, Bradfield J, et al. (2009) From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes. PLoS Genetics 5: e1000678 Available: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2748686/. Accessed 2011 Nov 7.
27. Evans DM, Visscher PM, Wray NR, (2009) Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk. Hum Mol Genet 18: 3525-3531.
28. Pandey JP, (2010) Candidate Gene Approach's Missing Link. Science 329: 1148.
29. Janssens ACJW, van Duijn CM, (2008) Genome-based prediction of common diseases: advances and prospects. Hum Mol Genet 17: R166-R173.
30. Mitchell GF, DeStefano AL, Larson MG, Benjamin EJ, Chen M-H, et al. (2005) Heritability and a genome-wide linkage scan for arterial stiffness, wave reflection, and mean arterial pressure: the Framingham Heart Study. Circulation 112: 194-199.
31. Zhang H, Singer BH, (2010) Recursive partitioning and applications Springer Verlag.