Evaluating diagnostic accuracy of genetic profiles in affected offspring families

Abstract

Diagnostic accuracy of a genetic test involving multiple disease genes is evaluated using sensitivity and specificity. For estimation, data from both affected and unaffected subjects are required. For early onset diseases, such as autism spectrum disorder (ASD), only data from families with affected offspring are available. To enable estimation of specificity when no data for unaffected offspring are available (single affected offspring, SAO, data), we combine the pseudocontrol method of Cordell and Clayton (Am. J. Hum. Genet. 2002; 70:124-141) with the approach of DeLong et al. (Biometrics 1985; 41:947-958) in a logistic regression model for disease outcome with a risk score (RS) constructed from genotype information as prognostic variable. The area under the receiver operating characteristic curve (AUC) is then computed using the non-parametric Mann-Whitney method. Extensive simulation studies show that, analogous to other approaches utilizing pseudocontrols, the resulting estimates of AUC using SAO data are slightly conservative when compared with the estimates computed using the full population-based data. The method is illustrated using data from a study of ASD.

Figure 1

Receiver operating characteristic associated with the risk score. Specificity was estimated using sensitivity and the odds ratio. The estimated area under the curve (AUC) was 0.61 (95% CI: 0.59 – 0.64).