Genetic epidemiology of homocysteine and related diseases.

Abstract

Homocysteine is a sulphur-containing intermediate in one-carbon metabolism. Plasma total homocysteine (tHcy) concentration is associated to common diseases including venous thrombosis and neural tube defects (NTD). Identification of genetic determinants of plasma tHcy concentration can contribute to clarification of the underlying pathogenic processes. In the last 13 years, a focus on single locus association studies of functional variants has resulted in establishment of the MTHFR677C>T polymorphism as a genetic determinant of plasma tHcy concentrations. In this thesis, we looked beyond the single locus effects of evident candidate DNA variants and beyond the traditional genetic epidemiological study designs. The first part of the thesis describes a linkage study for plasma tHcy and four candidate-gene association studies for plasma tHcy, related metabolites, recurrent venous thrombosis (RVT), and NTD. The genome wide-linkage analysis revealed three regions that might harbour genetic determinants for plasma tHcy. Extensive association studies for over 40 one-carbon metabolism-related genes led to identification of novel candidates and known DNA variants that each had small contributions in plasma tHcy variation (<<2%); these studies also underlined the relative importance of MTHFR677C>T and CBS variants. Using multi-locus analysis we found a strongly associated five-locus interacting genotype that explained 17% of plasma tHcy variation in our population. Simultaneous analysis of candidate genes for plasma tHcy and folate and methionine concentrations indicated heterogeneity in genetic determinants for the three metabolites. The UCP2 45bp del was found to influence recurrent venous thrombosis risk and variants in CUBN and TRDMT1 were associated with NTD but not via plasma tHcy concentration. In the second part of the thesis, a new hybrid design is proposed which is shown to allow a powerful and flexible identification of both maternal and offspring genetic effects compared to alternative designs. Finally, four different methods to analyse gene-gene interactions are evaluated using simulated data.