Resumen

LEON, Francisco Javier et al. Analysis of population genetic structure from Bucaramanga (Colombia) based on gene polymorphisms associated with regulation of blood pressure. Colomb. Med. [online]. 2012, vol.43, n.2, pp.154-161. ISSN 1657-9534.

Introduction: In spite nearly 40% of the variability in blood pressure can be explained by genetic factors, the identification of genes associated to essential high blood pressure is difficult in populations where individuals have different genetic precedents; in these circumstances it is necessary to determinate whether the population is sub-structured because this can bias studies associated with this disease. Objectives: To determine the genetic structure of the population in Bucaramanga from genetic polymorphisms asso-Received in revised form 25 november 2011 ciated with the regulation of blood pressure: 448G>T, 679C>T y 1711C>T from the gene kinase 4 of the dopaminergic receptor linked to the protein G and Glu298Asp, -786T>C and the VNTR of the intron 4 of the gene of endothelial nitric oxide. Methodology: A sample of 552 unrelated individuals was studied through analysis of Restriction fragment length polymorphism. The allelic, haplotypic and genotypic frequencies were calculated, the Hardy-Weinberg equilibrium was determined and a molecular analysis of variance was performed to determine the genetic structure. Results: 38 Haplotypes were identified, with GCCTG4b as the most frequent (21.2%). The most diverse polymorphism was 448G>T with a frequency of 49.9% for heterozygous. The six polymorphisms were found in genetic equilibrium and genetic structure of populations was not evidenced (F_ST = 0,0038). Conclusion: The population studied does not present a genetic sub-structure and the polymorphisms analyzed were found in genetic equilibrium, this indicates that the population mixes randomly and there are no sub-groups capable of affecting the results of the association studies.

Palabras clave : High blood pressure essence; Complex disease; GRK4; eNOS; Polymorphisms; Populations genetics.

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