title: Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score--the CoLaus Study.
abstract: OBJECTIVE
  Several susceptibility genes for type 2 diabetes have been discovered recently. Individually, these genes increase the disease risk only minimally. The goals of the present study were to determine, at the population level, the risk of diabetes in individuals who carry risk alleles within several susceptibility genes for the disease and the added value of this genetic information over the clinical predictors.
  
  
  METHODS
  We constructed an additive genetic score using the most replicated single-nucleotide polymorphisms (SNPs) within 15 type 2 diabetes-susceptibility genes, weighting each SNP with its reported effect. We tested this score in the extensively phenotyped population-based cross-sectional CoLaus Study in Lausanne, Switzerland (n = 5,360), involving 356 diabetic individuals.
  
  
  RESULTS
  The clinical predictors of prevalent diabetes were age, BMI, family history of diabetes, WHR, and triacylglycerol/HDL-cholesterol ratio. After adjustment for these variables, the risk of diabetes was 2.7 (95% CI 1.8-4.0, p = 0.000006) for individuals with a genetic score within the top quintile, compared with the bottom quintile. Adding the genetic score to the clinical covariates improved the area under the receiver operating characteristic curve slightly (from 0.86 to 0.87), yet significantly (p = 0.002). BMI was similar in these two extreme quintiles.
  
  
  CONCLUSIONS
  In this population, a simple weighted 15 SNP-based genetic score provides additional information over clinical predictors of prevalent diabetes. At this stage, however, the clinical benefit of this genetic information is limited.
authors.affiliation: Discovery Analytics, GlaxoSmithKline, Collegeville, PA, USA.
authors.forename: X
authors.initials: X
authors.lastname: Lin
authors.forename: K
authors.initials: K
authors.lastname: Song
authors.forename: N
authors.initials: N
authors.lastname: Lim
authors.forename: X
authors.initials: X
authors.lastname: Yuan
authors.forename: T
authors.initials: T
authors.lastname: Johnson
authors.forename: A
authors.initials: A
authors.lastname: Abderrahmani
authors.forename: P
authors.initials: P
authors.lastname: Vollenweider
authors.forename: H
authors.initials: H
authors.lastname: Stirnadel
authors.forename: S S
authors.initials: SS
authors.lastname: Sundseth
authors.forename: E
authors.initials: E
authors.lastname: Lai
authors.forename: D K
authors.initials: DK
authors.lastname: Burns
authors.forename: L T
authors.initials: LT
authors.lastname: Middleton
authors.forename: A D
authors.initials: AD
authors.lastname: Roses
authors.forename: P M
authors.initials: PM
authors.lastname: Matthews
authors.forename: G
authors.initials: G
authors.lastname: Waeber
authors.forename: L
authors.initials: L
authors.lastname: Cardon
authors.forename: D M
authors.initials: DM
authors.lastname: Waterworth
authors.forename: V
authors.initials: V
authors.lastname: Mooser
mesh_terms: D000328:Adult; D000368:Aged; D001794:Blood Pressure; D015992:Body Mass Index; D003920:Diabetes Mellitus / Q000453:epidemiology* / Q000235:genetics*; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology / Q000235:genetics; D005260:Female; D005787:Gene Frequency; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006801:Humans; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D015995:Prevalence; D013557:Switzerland / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data
chemical_list: D005819:Genetic Markers