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Interpretation of genetic association studies: Markers with replicated highly significant odds ratios may be poor classifiers

Jakobsdottir, J and Gorin, MB and Conley, YP and Ferrell, RE and Weeks, DE (2009) Interpretation of genetic association studies: Markers with replicated highly significant odds ratios may be poor classifiers. PLoS Genetics, 5 (2). ISSN 1553-7390

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Abstract

Recent successful discoveries of potentially causal single nucleotide polymorphisms (SNPs) for complex diseases hold great promise, and commercialization of genomics in personalized medicine has already begun. The hope is that genetic testing will benefit patients and their families, and encourage positive lifestyle changes and guide clinical decisions. However, for many complex diseases, it is arguable whether the era of genomics in personalized medicine is here yet. We focus on the clinical validity of genetic testing with an emphasis on two popular statistical methods for evaluating markers. The two methods, logistic regression and receiver operating characteristic (ROC) curve analysis, are applied to our age-related macular degeneration dataset. By using an additive model of the CFH, LOC387715, and C2 variants, the odds ratios are 2.9, 3.4, and 0.4, with p-values of 10 -13, 10-13, and 10-3, respectively. The area under the ROC curve (AUC) is 0.79, but assuming prevalences of 15%, 5.5%, and 1.5% (which are realistic for age groups 80 y, 65 y, and 40 y and older, respectively), only 30%, 12%, and 3% of the group classified as high risk are cases. Additionally, we present examples for four other diseases for which strongly associated variants have been discovered. In type 2 diabetes, our classification model of 12 SNPs has an AUC of only 0.64, and two SNPs achieve an AUC of only 0.56 for prostate cancer. Nine SNPs were not sufficient to improve the discrimination power over that of nongenetic predictors for risk of cardiovascular events. Finally, in Crohn's disease, a model of five SNPs, one with a quite low odds ratio of 0.26, has an AUC of only 0.66. Our analyses and examples show that strong association, although very valuable for establishing etiological hypotheses, does not guarantee effective discrimination between cases and controls. The scientific community should be cautious to avoid overstating the value of association findings in terms of personalized medicine before their time. © 2009 Jakobsdottir et al.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Jakobsdottir, J
Gorin, MB
Conley, YPyconley@pitt.eduYCONLEY
Ferrell, RErferrell@pitt.eduRFERRELL
Weeks, DEweeks@pitt.eduWEEKS0000-0001-9410-7228
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorAbecasis, Goncalo R.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date: 1 February 2009
Date Type: Publication
Journal or Publication Title: PLoS Genetics
Volume: 5
Number: 2
DOI or Unique Handle: 10.1371/journal.pgen.1000337
Schools and Programs: School of Public Health > Biostatistics
School of Public Health > Human Genetics
School of Nursing > Nursing
Refereed: Yes
ISSN: 1553-7390
PubMed Central ID: PMC2629574
PubMed ID: 19197355
Date Deposited: 24 Jul 2012 18:56
Last Modified: 22 Jun 2021 15:55
URI: http://d-scholarship.pitt.edu/id/eprint/13100

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