title: Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes.
abstract: OBJECTIVE
  More than 40 regions of the human genome confer susceptibility for type 1 diabetes and could be used to establish population screening strategies. The aim of our study was to identify weighted sets of SNP combinations for type 1 diabetes prediction.
  
  
  METHODS
  We applied multivariable logistic regression and Bayesian feature selection to the Type 1 Diabetes Genetics Consortium (T1DGC) dataset with genotyping of HLA plus 40 SNPs within other type 1 diabetes-associated gene regions in 4,574 cases and 1,207 controls. We tested the weighted models in an independent validation set (765 cases, 423 controls), and assessed their performance in 1,772 prospectively followed children.
  
  
  RESULTS
  The inclusion of 40 non-HLA gene SNPs significantly improved the prediction of type 1 diabetes over that provided by HLA alone (p = 3.1 × 10(-25)), with a receiver operating characteristic AUC of 0.87 in the T1DGC set, and 0.84 in the validation set. Feature selection identified HLA plus nine SNPs from the PTPN22, INS, IL2RA, ERBB3, ORMDL3, BACH2, IL27, GLIS3 and RNLS genes that could achieve similar prediction accuracy as the total SNP set. Application of this ten SNP model to prospectively followed children was able to improve risk stratification over that achieved by HLA genotype alone.
  
  
  CONCLUSIONS
  We provided a weighted risk model with selected SNPs that could be considered for recruitment of infants into studies of early type 1 diabetes natural history or appropriately safe prevention.
authors.affiliation: Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany.
authors.forename: Christiane
authors.initials: C
authors.lastname: Winkler
authors.forename: Jan
authors.initials: J
authors.lastname: Krumsiek
authors.forename: Florian
authors.initials: F
authors.lastname: Buettner
authors.forename: Christof
authors.initials: C
authors.lastname: Angermüller
authors.forename: Eleni Z
authors.initials: EZ
authors.lastname: Giannopoulou
authors.forename: Fabian J
authors.initials: FJ
authors.lastname: Theis
authors.forename: Anette-Gabriele
authors.initials: AG
authors.lastname: Ziegler
authors.forename: Ezio
authors.initials: E
authors.lastname: Bonifacio
mesh_terms: D001499:Bayes Theorem; D030541:Databases, Genetic; D003922:Diabetes Mellitus, Type 1 / Q000175:diagnosis* / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing / Q000379:methods*; D005838:Genotype; D006801:Humans; D020641:Polymorphism, Single Nucleotide