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Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.

Nature genetics | Apr 30, 2009

A principal task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription and phenotypic information. Here we have validated our method through the characterization of transgenic and knockout mouse models of genes predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being newly confirmed, resulted in significant changes in obesity-related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F(2) intercross studies allows high-confidence prediction of causal genes and identification of pathways and networks involved.

Pubmed ID: 19270708 RIS Download

Mesh terms: Abdomen | Adipose Tissue | Animals | Carrier Proteins | Disease Models, Animal | Female | Gene Expression Profiling | Genetic Variation | Glutathione Peroxidase | Glycoproteins | Humans | Liver | Male | Mice | Mice, Knockout | Mice, Transgenic | Muscle, Skeletal | Nerve Tissue Proteins | Obesity | Phenotype | Reproducibility of Results | Transcription, Genetic

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Associated grants

  • Agency: NHLBI NIH HHS, Id: HL28481
  • Agency: NHLBI NIH HHS, Id: P01 HL028481
  • Agency: NIDDK NIH HHS, Id: R01 DK072206-04
  • Agency: NHLBI NIH HHS, Id: HL30568
  • Agency: NHLBI NIH HHS, Id: P01 HL030568
  • Agency: NIDDK NIH HHS, Id: DK072206
  • Agency: NIDDK NIH HHS, Id: R01 DK072206

Mouse Genome Informatics (Data, Gene Annotation)

Comparative Toxicogenomics Database (Data, Disease Annotation)

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