ArticleNature genetics2009
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
Article in Nature genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 175 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
175 citing papers in PubMed, 281 citations in OpenAlex.
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- Fiber type-specific expression of LACTB leverages a function in oxidative metabolism.Histochemistry and cell biology · 2026Article
- Effects of aging and anti-aging dietary restriction on regulators of the [NADPH]/[NADPFree radical biology & medicine · 2025Review
- Metabolites are not genes - avoiding the misuse of pathway analysis in metabolomics.Nature metabolism · 2025Article
- Integrated hepatic transcriptomics and metabolomics identify Pck1 as a key factor in the broad dysregulation induced by vehicle pollutants.Particle and fibre toxicology · 2024Article
- Identification of potential key lipid metabolism-related genes involved in tubular injury in diabetic kidney disease by bioinformatics analysis.Acta diabetologica · 2024Article
- The Roles of White Adipose Tissue and Liver NADPH in Dietary Restriction-Induced Longevity.Antioxidants (Basel, Switzerland) · 2024Review
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- Malic enzyme 1 knockout has no deleterious phenotype and is favored in the male germline under standard laboratory conditions.PloS one · 2024Article
- A multi-layered network model identifies Akt1 as a common modulator of neurodegeneration.Molecular systems biology · 2023Article
- Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease.Communications biology · 2023Article
- Malic Enzyme 1 (ME1) Promotes Adiposity and Hepatic Steatosis and Induces Circulating Insulin and Leptin in Obese Female Mice.International journal of molecular sciences · 2023Article
- Multi-omic integration reveals cell-type-specific regulatory networks of insulin resistance in distinct ancestry populations.Cell systems · 2023Article
- The structure of the human LACTB filament reveals the mechanisms of assembly and membrane binding.PLoS biology · 2022Article
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- Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2022Article
- Unveiling the Function of the Mitochondrial Filament-Forming Protein LACTB in Lipid Metabolism and Cancer.Cells · 2022Review
- Intermittent prednisone treatment in mice promotes exercise tolerance in obesity through adiponectin.The Journal of experimental medicine · 2022Article
115 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
32 authors at 2 institutions in 1 country.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.