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Revista chilena de cardiología

On-line version ISSN 0718-8560

Abstract

GUZMAN, Neftalí  and  SALAZAR, Luis A. Association of functional variants in homocysteine metabolism genes, deep venous thrombosis risk and hyperhomocysteinemia in Southern Chilean subjects. Rev Chil Cardiol [online]. 2011, vol.30, n.1, pp.28-32. ISSN 0718-8560.  http://dx.doi.org/10.4067/S0718-85602011000100004.

Background: Deep Venous Thrombosis (DVT) is an important health problem in modern society. Recent evidence suggests an association between functional variants in homocysteine metabolism genes and DVT. However, findings in different populations have been contradictory. In this work, we evaluated the potential association between the presence of polymorphisms in homocysteine metabolism genes, DVT susceptibility and hyperhomocysteinemia in Chilean subjects. Methods: A total of 231 individuals, 77 patients with diagnosis of DVT and 154 controls were included in this study. Common variants in Metylenete-trahydrofolate reductase (MTHFR) and Cistationine p-synthetase (CBS) genes were genotyped by PCR-RFLP. Basal homocysteine was quantified by Fluorescence Polarization Immunoassay. Results: Genotype distribution and allelic frequencies of MTHFR C677T polymorphism were significantly different between patients and controls. Odds Ratio for DVT associated to homozygous status was 3.68 (95%C.I., 1.628-8.337, p<0.01). On the other hand, the genotype distribution of the CBS 844ins68 variant was similar in both groups (OR 1.82, 95%C.I.: 0.636-5.234, p=0.257). In addition, the individuals carrying the MTHFR 677TT homozygous genotype exhibited higher levels of homocysteine. Conclusion: The MTHFR C677T polymorphism constituted a molecular biomarker of DVT in Chilean population, and related to higher levels of homocysteine in homozygote subjects. The results suggest that the molecular detection of this polymorphism should be included in the basic screening for thrombophilia in our population.

Keywords : Deep venous thrombosis; Risk factors; Molecular biomarkers.

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