Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks
Open accessAbstract
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.
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If genetic data, such as GWAS loci for disease or eQTLs for genes, are available, it may be possible to infer causality using DNA as an anchor.
“If genetic data, such as GWAS loci for disease or eQTLs for genes, are available it may be possible to infer causality using DNA as an anchor [75–77].”
From Multi-omics approaches to disease (2017) · cites this paper as [77]
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- Authors
- Yang, X., Deignan, J. L., Qi, H., Zhu, J., Qian, S., Zhong, J., Torosyan, G., Majid, S., Falkard, B., Kleinhanz, R. R., Karlsson, J., Castellani, L. W., Mumick, S., Wang, K., Xie, T., Coon, M., Zhang, C., Estrada-Smith, D., Farber, C. R., Wang, S. S., van Nas, A., Ghazalpour, A., Zhang, B., MacNeil, D. J., Lamb, J. R., Dipple, K. M., Reitman, M. L., Mehrabian, M., Lum, P. Y., Schadt, E. E., Lusis, A. J., & Drake, T. A.
- Affiliations
- University of California, Los Angeles (US)
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- Corresponding author
- Drake, Thomas A
- ORCID
- Venue
- Nature Genetics
- Published
- 2009-03-08
- Volume
- 41
- Issue
- 4
- Pages
- 415-423
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC2837947
- OpenAlex
- W2168312688
- Cited by
- 288
- References
- 49
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 5 · 2023: 7 · 2022: 9 · 2021: 23 · 2020: 16 · 2019: 7 · 2018: 7 · 2017: 15 · 2016: 14 · 2015: 21 · 2014: 26 · 2013: 27 · 2012: 27
- FWCI
- 13.81
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (HL3 0568, HL28481, P01HL030568, P01HL028481)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK072206, DK-072206)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- obesity, abdominal obesity, knockout mouse models, transgenic mouse model, GAS7, ME1, glutathione peroxidase 3, metabolic pathways, metabolic networks, hepatic gene expression, gene expression data integration, complex trait genetics
- MeSH terms
- Abdomen, Adipose Tissue, Animals, Carrier Proteins, Disease Models, Animal, Female, Glutathione Peroxidase, Glycoproteins, Humans, Liver, Male, Mice, Transgenic, Nerve Tissue Proteins, Obesity, Phenotype, Transcription, Genetic, Genetic Variation, Reproducibility of Results, Mice, Knockout, Muscle, Skeletal, Gene Expression Profiling, Vesicular Transport Proteins, Mice
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