%0 Journal Article
%T Genome-based prediction of common diseases: methodological considerations for future research
%A A Cecile JW Janssens
%A Cornelia M van Duijn
%J Genome Medicine
%D 2009
%I BioMed Central
%R 10.1186/gm20
%X The past decade has seen rapid developments in our understanding of the genetic etiology of various common multifactorial diseases, such as age-related macular degeneration (AMD), type 1 and type 2 diabetes, cardiovascular diseases, Crohn's disease and various cancers [1]. Further developments in genomic research, such as the growing number of genome-wide association studies, the large-scale consortia that are pooling data from various studies, and the advances in statistical genomics and genotype technology, are drastically improving the chances of identifying common low risk variants and rare high risk variants. It is beyond doubt that many more genetic susceptibility variants will be discovered in the next few years.Expectations are high that increasing knowledge of the genetic bases of disease will eventually lead to personalized medicine, that is, to preventive and therapeutic interventions for complex diseases that are tailored to individuals on the basis of their genetic profiles [2,3]. Genome-based personalized medicine already exists for monogenic disorders. For example, female carriers of BRCA1 or BRCA2 mutations are offered biannual mammography screening or provided the opportunity of preventive surgery. Potential applications of genetic profiling in multifactorial diseases include tailoring of prevention programs to at-risk individuals, determining the starting age of participation in screening programs [4] and, when profiles predict treatment success, tailoring treatment modalities and starting doses.As we have reviewed recently [5], the predictive value of genetic profiling is still limited at present, with a few promising exceptions. The area under the receiver operating characteristic curve (AUC) gives an assessment of the discriminative accuracy of a prediction model, that is, the degree to which the test results can discriminate between persons who will develop the disease and those who will not. AUC ranges from 0.50 (equal to tossing a coin) to 1.
%U http://genomemedicine.com/content/1/2/20