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Review
. 2013;75(2-4):98-105.
doi: 10.1159/000353180. Epub 2013 Sep 27.

Genetic admixture and obesity: recent perspectives and future applications

Affiliations
Review

Genetic admixture and obesity: recent perspectives and future applications

José R Fernández et al. Hum Hered. 2013.

Abstract

The process of the colonization of the New World that occurred centuries ago served as a natural experiment, creating unique combinations of genetic material in newly formed admixed populations. Through a genetic admixture approach, the identification and genotyping of ancestry informative markers have allowed for the estimation of proportions of ancestral parental populations among individuals in a sample. These admixture estimates have been used in different ways to understand the genetic contributions to individual variation in obesity and body composition parameters, particularly among diverse admixed groups known to differ in obesity prevalence within the United States. Although progress has been made through the use of genetic admixture approaches, further investigations are needed in order to explore the interaction of environmental factors with the degree of genetic ancestry in individuals. A challenge to confront at this time would be to further stratify and define environments in progressively more granular terms, including nutrients, muscle biology, stress responses at the cellular level, and the social and built environments.

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Figures

Figure 1
Figure 1
Association of BMI and the interaction of PUFA intake and Amerindian admixture in a multiethnic sample of children. Predicted BMI calculated from multiple variable linear regression model including Amerindian admixture, PUFA intake, interaction of Amerindian admixture and PUFA intake controlled for age, sex, ethnicity, tanner stage, total energy intake, and socioeconomic status. PUFA intake and Amerindian admixture interaction was significant (p = 0.0471). Symbols represent the following levels of Amerindian admixture formula image (0%), formula image (25%), formula image (50%), formula image (75%) and + (100%).

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