Predicting risk of type 2 diabetes mellitus in Korean adults aged 40-69 by integrating clinical and genetic factors

Prim Care Diabetes. 2019 Feb;13(1):3-10. doi: 10.1016/j.pcd.2018.07.004. Epub 2018 Nov 23.

Abstract

Aims: The purpose of our investigation was to identify the genetic and clinical risk factors of type 2 diabetes mellitus (T2DM) and to predict the incidence of T2DM in Korean adults aged 40-69 at follow-up intervals of 5, 7, and 10years.

Methods: Korean Genome and Epidemiology Study (KoGES) cohort data (n=10,030) were used to develop T2DM prediction models. Both clinical-only and integrated (clinical factors+genetic factors) models were derived using the Cox proportional hazards model. Internal validation was performed to evaluate the prediction capabilities of the clinical and integrated models.

Results: The clinical model included 10 selected clinical risk factors. The selected SNPs for the integrated model were rs9311835 in PTPRG, rs10975266 in RIC1, rs11057302 in TMED2, rs17154562 in ADAM12, and rs8038172 in CGNL1. For the clinical model, validated c-indices with time points of 5, 7, and 10 years were 0.744, 0.732, and 0.732, respectively. Slightly higher validated c-indices were observed for the integrated model at 0.747, 0.736, and 0.738, respectively. The p-values of the survival net reclassification improvement (NRI) for the SNP point-based score were statistically significant.

Conclusions: Clinical and integrated models can be effectively used to predict the incidence of T2DM in Koreans.

Keywords: Genetic risk score; Risk factor; Risk prediction; Single-nucleotide polymorphism.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Diabetes Mellitus, Type 2 / diagnosis
  • Diabetes Mellitus, Type 2 / epidemiology*
  • Diabetes Mellitus, Type 2 / genetics*
  • Female
  • Genetic Markers
  • Genetic Predisposition to Disease
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Models, Genetic
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • Prognosis
  • Republic of Korea / epidemiology
  • Risk Assessment
  • Risk Factors
  • Time Factors

Substances

  • Genetic Markers