Revisiting the Clinical Validity of Multiplex Genetic Testing in Complex Diseases

Janssens, A. Cecile J.W.; Pardo, M. C.; Steyerberg, Ewout W.; Duijn, Cornelia M. van

doi:10.1086/382052

Cited by 74 publications

(50 citation statements)

References 6 publications

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“…We have proposed earlier that the usefulness of a genomic profile associated with a binary outcome should be evaluated by the area under the ROC curve. 14,15 In medicine, ROC analysis has been extensively used in the evaluation of diagnostic tests. We show that the 54-loci genomic profile had a relatively low discriminative accuracy (AUC ¼ 65% for a person falling into 5% tallest).…”

Section: Discussionmentioning

confidence: 99%

Predicting human height by Victorian and genomic methods

et al. 2009

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In the Victorian era, Sir Francis Galton showed that 'when dealing with the transmission of stature from parents to children, the average height of the two parents, y is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4-6% of the sex-and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex-and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified.

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Section: Discussionmentioning

confidence: 99%

Predicting human height by Victorian and genomic methods

et al. 2009

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“…5 We have proposed that the usefulness of genetic profiling should be evaluated by the area under the receiver-operating characteristic (ROC) curve. 5 The ROC curve presents the combinations of sensitivity and specificity for each possible cut-off value of the continuous test result that can be considered to define positive and negative test outcomes. The magnitude of the area under the receiver-operating characteristic curve (AUC) indicates whether a test is useful to identify individuals who are at increased risk of disease (screening; e.g., AUC ϳ 0.80) or to diagnose a disease before the onset of symptoms (presymptomatic diagnosis; e.g., AUC Ͼ 0.99).…”

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confidence: 99%

Predictive testing for complex diseases using multiple genes: Fact or fiction?

Janssens

Aulchenko²,

Elefante³

et al. 2006

Genetics in Medicine

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Purpose: There is ongoing debate about whether testing low-risk genes at multiple loci will be useful in clinical care and public health. We investigated the usefulness of multiple genetic testing using simulated data. Methods:Usefulness was evaluated by the area under the receiver-operating characteristic curve (AUC), which indicates the accuracy of genetic profiling in discriminating between future patients and nonpatients. The AUC was investigated in relation to the number of genes assumed to be involved, the risk allele frequency, the odds ratio of the risk genotypes, and to the proportion of variance explained by genetic factors as an approximation of the heritability of the disease. Results: We demonstrated that a high (AUC Ͼ 0.80) to excellent discriminative accuracy (AUC Ͼ 0.95) can be obtained by simultaneously testing multiple susceptibility genes. A higher discriminative accuracy is obtained when genetic factors play a larger role in the disease, as indicated by the proportion of explained variance.The maximum discriminative accuracy of future genetic profiling can be estimated at present from the heritability and prevalence of disease. Conclusions: Genetic profiling may have the potential to identify individuals at higher risk of disease depending on the prevalence and heritability of the disease. Genet Med 2006:8(7):395-400.

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“…161 Nevertheless, it is true to say that if a large number of high-risk genes are present in combination, a small group of individuals may be faced with a very high risk of a certain condition. 162 These can include serious conditions for which no treatment (or no proper treatment) is available, such as Alzheimer's disease. If integrated risk profiling is performed, a process which often tests for a large number of conditions at the same time, it is conceivable that people will not be sufficiently prepared for such an outcome.…”

Section: Genetic Screeningmentioning

confidence: 99%