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Open Access Research article

Effects of interacting networks of cardiovascular risk genes on the risk of type 2 diabetes mellitus (the CODAM study)

Marleen MJ van Greevenbroek1*, Jian Zhang2*, Carla JH van der Kallen1, Paul MH Schiffers3, Edith JM Feskens4 and Tjerk WA de Bruin1

Author Affiliations

1 Laboratory for Metabolism and Vascular Medicine, Department of Internal Medicine/Cardiovascular Research Institute (CARIM), Maastricht University, Maastricht, The Netherlands.

2 Institute of Mathematics, Statistics and Actuarial Sciences, University of Kent, Canterbury, UK.

3 Department of Pharmacology and Toxicology, Maastricht University, Maastricht, The Netherlands.

4 Division of Human Nutrition, Section Nutrition and Epidemiology, Wageningen University, Wageningen, The Netherlands.

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BMC Medical Genetics 2008, 9:36  doi:10.1186/1471-2350-9-36

Published: 24 April 2008

Abstract

Background:

Genetic dissection of complex diseases requires innovative approaches for identification of disease-predisposing genes. A well-known example of a human complex disease with a strong genetic component is Type 2 Diabetes Mellitus (T2DM).

Methods:

We genotyped normal-glucose-tolerant subjects (NGT; n = 54), subjects with an impaired glucose metabolism (IGM; n = 111) and T2DM (n = 142) subjects, in an assay (designed by Roche Molecular Systems) for detection of 68 polymorphisms in 36 cardiovascular risk genes. Using the single-locus logistic regression and the so-called haplotype entropy, we explored the possibility that (1) common pathways underlie development of T2DM and cardiovascular disease -which would imply enrichment of cardiovascular risk polymorphisms in "pre-diabetic" (IGM) and diabetic (T2DM) populations- and (2) that gene-gene interactions are relevant for the effects of risk polymorphisms.

Results:

In single-locus analyses, we showed suggestive association with disturbed glucose metabolism (i.e. subjects who were either IGM or had T2DM), or with T2DM only. Moreover, in the haplotype entropy analysis, we identified a total of 14 pairs of polymorphisms (with a false discovery rate of 0.125) that may confer risk of disturbed glucose metabolism, or T2DM only, as members of interacting networks of genes. We substantiated gene-gene interactions by showing that these interacting networks can indeed identify potential "disease-predisposing allele-combinations".

Conclusion:

Gene-gene interactions of cardiovascular risk polymorphisms can be detected in prediabetes and T2DM, supporting the hypothesis that common pathways may underlie development of T2DM and cardiovascular disease. Thus, a specific set of risk polymorphisms, when simultaneously present, increases the risk of disease and hence is indeed relevant in the transfer of risk.