The Novel "Genomic Pathway Approach" to Complex Diseases A Reason for (Over-)Optimism?

LP Breitling, Ewout Steyerberg, H Brenner

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Background: Examination of the genetic structure of complex diseases by a "genomic pathway approach"-which applies stepwise model selection to sets of more than 1000 polymorphisms in studies of several hundred subjects-has recently been proposed. Models constructed through extensive selection procedures may yield misleading test statistics and measures of predictive performance; we aimed to quantify the extent Of Such problems inherent to stepwise regression on the genomic pathway scale. Methods: We performed permutation analyses and data-splitting approaches using one of the datasets examined in the paper that originally Suggested this approach (n = 536: 1195 SNPs in 22 genes) (Lesnick et al. PLoS Genet. 2007;3:e98). Results: The P values for the genetic effects produced by standard testing severely overestimated file significance, resulting in our example in a standard P value of 3.5 X 10(-69) and a permutation P of 0.003 (95% confidence interval = 0.001 to 0.009). Furthermore, the apparent validity as measured by the area Under the receiver operating characteristic Curve in 90%. training datasets (0.935 [interquartile range = 0.918-0.951]) was extremely overoptimistic when compared with the validity estimated from the excluded 10% validation subsets (0.564 [0.518-0.614]). This validated area under the receiver operating characteristic curve was lower than for models predicting case/control Status Solely from age and sex while excluding any genetic effects (median difference = -0.040 [95%, confidence interval = -0.049 to -0.031]). Conclusions: The application of stepwise model selection oil the genomic pathway scale-at least in the simple form Currently put forward-is prone to yield highly misleading results. We provide pointers to some promising, alternatives. (Epidemiology 2009;20: 500-507)
Original languageUndefined/Unknown
Pages (from-to)500-507
Number of pages8
Issue number4
Publication statusPublished - 2009

Research programs

  • EMC NIHES-02-65-01

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