The association of genetic markers for type 2 diabetes with prediabetic status beyond nutrition and anthropometry
Information on the impact of multiple gene loci as to the risk for prediabetes is limited. This research uses random forest analysis to identify genetic markers that may add to the information of anthropometric data, inflammatory markers and lifestyle factors regarding the risk for developing prediabetes.
Cross-sectional data of 129 men and 157 women of the Delay of Impaired Glucose Tolerance by a Healthy Lifestyle Trial (DELIGHT). Besides established risk factors including dietary factors, physical activity, central adiposity and inflammatory markers, 41 single nucleotide polymorphisms (SNPs) that have previously been found to be associated with type 2 diabetes were analyzed. As a nonparametric test a random forest approach was used that allows to process a large number of predictors. Variables with the highest impact were entered into a multivariate logistic regression model.
Individuals with prediabetes were characterized by a slightly, but significantly higher number of type 2 diabetes risk alleles (42.5 ± 4.1 vs. 41.3 ± 4.1, p = 0.013). A random forest analysis did not show a major impact of dietary and lifestyle factors as to risk of prediabetes. After adjustment for age, waist circumference and leptin,of 6 SNPs with the highest impact 5 were positively associated with prediabetes statusin a logistic regression model (odds ratio for prediabetes: 1.57 per allele (95% Cl 1.21-2.10, p=0.001)).
This explorative analysis of data of DELIGHT demonstrates that at least 5 out of 41 genetic variants characteristic of individuals with type 2 diabetes indicate risk of prediabetes beyond nutrition, physical activity and anthropometry. Accumulation of these risk alleles may markedly increase the risk for prediabetes. However, prospective studies are required to corroborate these findings and to demonstrate the predictive value of these genetic variants for the risk to develop prediabetes.