Current genetic data do not improve the prediction of type 2 diabetes mellitus: the CoLaus study

J Clin Endocrinol Metab. 2012 Jul;97(7):E1338-41. doi: 10.1210/jc.2011-3412. Epub 2012 Apr 24.

Abstract

Context: Several genetic risk scores to identify asymptomatic subjects at high risk of developing type 2 diabetes mellitus (T2DM) have been proposed, but it is unclear whether they add extra information to risk scores based on clinical and biological data.

Objective: The objective of the study was to assess the extra clinical value of genetic risk scores in predicting the occurrence of T2DM.

Design: This was a prospective study, with a mean follow-up time of 5 yr.

Setting and subjects: The study included 2824 nondiabetic participants (1548 women, 52 ± 10 yr).

Main outcome measure: Six genetic risk scores for T2DM were tested. Four were derived from the literature and two were created combining all (n = 24) or shared (n = 9) single-nucleotide polymorphisms of the previous scores. A previously validated clinic + biological risk score for T2DM was used as reference.

Results: Two hundred seven participants (7.3%) developed T2DM during follow-up. On bivariate analysis, no differences were found for all but one genetic score between nondiabetic and diabetic participants. After adjusting for the validated clinic + biological risk score, none of the genetic scores improved discrimination, as assessed by changes in the area under the receiver-operating characteristic curve (range -0.4 to -0.1%), sensitivity (-2.9 to -1.0%), specificity (0.0-0.1%), and positive (-6.6 to +0.7%) and negative (-0.2 to 0.0%) predictive values. Similarly, no improvement in T2DM risk prediction was found: net reclassification index ranging from -5.3 to -1.6% and nonsignificant (P ≥ 0.49) integrated discrimination improvement.

Conclusions: In this study, adding genetic information to a previously validated clinic + biological score does not seem to improve the prediction of T2DM.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Data Interpretation, Statistical
  • Databases, Genetic / statistics & numerical data
  • Databases, Genetic / trends
  • Diabetes Mellitus, Type 2 / diagnosis*
  • Diabetes Mellitus, Type 2 / epidemiology
  • Diabetes Mellitus, Type 2 / etiology
  • Diabetes Mellitus, Type 2 / genetics*
  • Female
  • Follow-Up Studies
  • Genetic Predisposition to Disease*
  • Genetics, Population* / statistics & numerical data
  • Genetics, Population* / trends
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • Research Design
  • Risk Factors
  • Validation Studies as Topic