An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene interactions on risk of myocardial infarction: The importance of model validation

被引:106
作者
Coffey, CS [1 ]
Hebert, PR
Ritchie, MD
Krumholz, HM
Gaziano, JM
Ridker, PM
Brown, NJ
Vaughan, DE
Moore, JH
机构
[1] Univ Alabama Birmingham, Dept Biostat, Birmingham, AL 35294 USA
[2] Yale Univ, Sch Med, Dept Med, Sect Cardiovasc Med, New Haven, CT 06510 USA
[3] Vanderbilt Univ, Sch Med, Dept Mol Physiol & Biophys, Ctr Human Genet Res, Nashville, TN 37232 USA
[4] Yale Univ, Sch Med, Dept Epidemiol & Publ Hlth, Sect Hlth Policy & Adm, New Haven, CT 06510 USA
[5] Yale Univ, Sch Med, Robert Wood Johnson Clin Scholars Program, New Haven, CT 06510 USA
[6] Yale New Haven Med Ctr, Ctr Outcomes Res & Evaluat, New Haven, CT 06510 USA
[7] Harvard Univ, Sch Med, Brigham & Womens Hosp, Div Prevent Med, Boston, MA 02215 USA
[8] Harvard Univ, Sch Med, Brigham & Womens Hosp, Ctr Cardiovasc Dis Prevent, Boston, MA 02215 USA
[9] Vanderbilt Univ, Sch Med, Dept Med, Nashville, TN 37232 USA
[10] Vanderbilt Univ, Sch Med, Dept Pharmacol, Nashville, TN 37232 USA
关键词
D O I
10.1186/1471-2105-5-49
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: To examine interactions among the angiotensin converting enzyme (ACE) insertion/deletion, plasminogen activator inhibitor-1 (PAI-1) 4G/5G, and tissue plasminogen activator (t-PA) insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR) method. One advantage of the MDR method is that it provides an internal prediction error for validation. We summarize our use of this internal prediction error for model validation. Results: The overall results for the two methods were consistent, with both suggesting an interaction between the ACE I/D and PAI-1 4G/5G polymorphisms. However, using ten-fold cross validation, the 46% prediction error for the final MDR model was not significantly lower than that expected by chance. Conclusions: The significant interaction initially observed does not validate and may represent a type I error. As data-driven analytic methods continue to be developed and used to examine complex genetic interactions, it will become increasingly important to stress model validation in order to ensure that significant effects represent true relationships rather than chance findings.
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页数:10
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