期刊论文详细信息
Genetics and Molecular Biology
Polymorphisms associated with the risk of lung cancer in a healthy Mexican Mestizo population: application of the additive model for cancer
Rebeca Pérez-morales2  Ignacio Méndez-ramírez1  Clementina Castro-hernández2  Ollin C. Martínez-ramírez2  María Eugenia Gonsebatt2  Julieta Rubio2 
[1] ,Universidad Nacional Autónoma de México Instituto de Investigaciones Biomédicas Departamento de Medicina Genómica y Toxicología AmbientalMexico City,México
关键词: additive model;    genetic polymorphism;    lung cancer;    Mexicans;    molecular epidemiology;   
DOI  :  10.1590/S1415-47572011005000053
来源: SciELO
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【 摘 要 】

Lung cancer is the leading cause of cancer mortality in Mexico and worldwide. In the past decade, there has been an increase in the number of lung cancer cases in young people, which suggests an important role for genetic background in the etiology of this disease. In this study, we genetically characterized 16 polymorphisms in 12 low penetrance genes (AhR, CYP1A1, CYP2E1, EPHX1, GSTM1, GSTT1, GSTPI, XRCC1, ERCC2, MGMT, CCND1 and TP53) in 382 healthy Mexican Mestizos as the first step in elucidating the genetic structure of this population and identifying high risk individuals. All of the genotypes analyzed were in Hardy-Weinberg equilibrium, but different degrees of linkage were observed for polymorphisms in the CYP1A1 and EPHX1 genes. The genetic variability of this population was distributed in six clusters that were defined based on their genetic characteristics. The use of a polygenic model to assess the additive effect of low penetrance risk alleles identified combinations of risk genotypes that could be useful in predicting a predisposition to lung cancer. Estimation of the level of genetic susceptibility showed that the individual calculated risk value (iCRV) ranged from 1 to 16, with a higher iCRV indicating a greater genetic susceptibility to lung cancer.

【 授权许可】

CC BY   
 All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License

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