Journal
AMERICAN JOURNAL OF HUMAN GENETICS
Volume 82, Issue 3, Pages 641-651Publisher
CELL PRESS
DOI: 10.1016/j.ajhg.2007.12.025
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Funding
- NCRR NIH HHS [P41 RR003655, RR03655] Funding Source: Medline
- NIGMS NIH HHS [GM28356, R01 GM028356, R37 GM028356] Funding Source: Medline
- PHS HHS [P30CAD43703] Funding Source: Medline
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Current extensive genetic research into common complex diseases, especially with the completion of genome-wide association studies, is bringing to light many novel genetic risk loci. These new discoveries, along with previously known genetic risk variants, offer an important opportunity for researchers to improve health care. We describe a method of quick evaluation of these new findings for potential clinical practice by designing a new predictive genetic test, estimating its classification accuracy, and determining the sample size required for the verification of this accuracy. The proposed predictive test is asymptotically more powerful than tests built on any other existing method and can be extended to scenarios where loci are linked or interact. We illustrate the approach for the case of type 2 diabetes. We incorporate recently discovered risk factors into the proposed test and find a potentially better predictive genetic test. The area under the receiver operating characteristic (ROC) curve (AUC) of the proposed test is estimated to be higher (AUC = 0.671) than for the existing test (AUC = 0.580).
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