Genetics of human obesity
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Updated: Aug 17, 2026

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
Published on: April 4, 2012
1Inserm Avenir, Paris, EA3502 and Paris 6 University, Nutrition Department, Hôtel-Dieu Hospital, France. karine.clement@htd.ap-hop-paris.fr
Abstract:
The rapid development of new concepts and tools has led to a change in the way in which researchers carry out nutrition-related research. Obesity is determined by the interaction between predisposing genetic and environmental aspects, but at present the gene-gene and gene-environment interactions contributing to the development of this complex disease cannot be analysed in detail. The purpose of the present paper is to provide some examples of the knowledge that is available in the field of obesity genetics, and also the new strategies being developed that are aimed at studying the relative contribution of numerous genes to obesity and their responses to environmental changes. In the rare cases of monogenic obesities in which a major gene is the cause the molecular approach has proved extremely powerful in the identification of the genes responsible and in defining new syndromes. However, in the common forms of obesity (polygenic obesity) most studies have analysed genotype-phenotype associations without sometimes taking into account the influence of environmental factors (diet, sedentary lifestyle). Among the aspects limiting this integrated approach to obesity are the difficulty of having large enough samples and the expansion of biocomputing tools developed for accessing the question of multiple interactions with no a priori hypotheses. This picture is rapidly changing. Large databases of clinical data and DNA and biological sample banks with more precise environmental information and patient phenotypes are being compiled. The capacity for studying multiple genes simultaneously at the DNA or RNA levels is also possible. Finally, the tremendous progress in biocomputing will allow the integration of these different types of data (relating to environment, phenotype, genotype, gene expression) and will improve the ability to deal with this complex disease.
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