Correlação estatística entre os dados de freqüências genéticas e dados de prevalência de doença podem complementar os estudos de caso-controle para identificar loci susceptibilidade em estudos de associação genética

Abstract

Disease-gene association studies reported a relation between the TPH2 and depression in different populations, however some studies have produced contradictory results, being the tryptophan hydroxylase-2 (TPH2) a limiting enzyme in the rate of synthetic route of serotonin in the brain, many studies reported the polymorphisms of the TPH2 enzyme. Two big projects, HapMap and 1000 genomes, organized the major part of these polymorphisms from the study of several populations becoming these data available. This work is aimed to develop a system to obtain possible predisposition markers of a disease from the correlation between epidemiological data and population frequencies of polymorphism, based in the hypothesis that if in a population there is more frequency of a certain kind of pathology genetically determined, the variables involved should be more frequent and vice-versa. The model used was the involvement of variables of the TPH2 gene in the predisposition of depression. The data obtained with positive correlation in one of homozygous genotypes and in the allele of this homozygous suggested the presence of 10 polymorphisms (total 14,49%) possibly related to the development of depression. These data were compared to literature data involving case control studies. In these work were studied 20 from 69 polymorphisms described to the TPH2 gene. With the exception of only one polymorphism, all the data obtained through the strategy proposed in this work have been equals to the literature data, including the allele that is determinant to the predisposition of depression when it is demonstrated the association. Therefore, it is proposed this strategy as an alternative to realize this kind of Genome-Wide Association studies without the necessity of a case control study, only using the epidemiological data from the disease, decreasing the time and the cost of this study.