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  • Title: Genetic association meta-analysis: a new classification to assess ethnicity using the association of MCP-1 -2518 polymorphism and tuberculosis susceptibility as a model.
    Author: Vásquez-Loarte T, Trubnykova M, Guio H.
    Journal: BMC Genet; 2015 Oct 30; 16():128. PubMed ID: 26518714.
    Abstract:
    BACKGROUND: In meta-analyses of genetic association studies, ancestry and ethnicity are not accurately investigated. Ethnicity is usually classified using conventional race/ethnic categories or continental groupings even though they could introduce bias increasing heterogeneity between and within studies; thus decreasing the external validity of the results. In this study, we performed a meta-analysis using a novel ethnic classification system to test the association between MCP-1 -2518 polymorphism and pulmonary tuberculosis. Our new classification considers genetic distance, migration and linguistic origins, which will increase homogeneity within ethnic groups. METHODS: We included thirteen studies from three continents (Asia, Africa and Latin America) and considered seven ethnic groups (West Africa, South Africa, Saharan Africa, East Asia, South Asia, Persia and Latin America). RESULTS: The results were compared to the continental group classification. We found a significant association between MCP-1 -2518 polymorphism and TB susceptibility only in the East Asian and Latin American groups (OR 3.47, P = 0.08; OR 2.73, P = 0.02). This association is not observed in other ethnic groups that are usually considered in the Asian group, such as India and Persia, or in the African group. CONCLUSIONS: There is an association between MCP-1 -2518 polymorphism and TB susceptibility only in the East Asian and Latin American groups. We suggest the use of our new ethnic classification in future meta-analysis of genetic association studies when ancestry markers are not available. This new classification increases homogeneity for certain ethnic groups compared to the continental classification. We recommend considering previous data about migration, linguistics and genetic distance when classifying ethnicity in further studies.
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