ArticleMammalian genome : official journal of the International Mammalian Genome Society2003
Microarray analysis of hepatic gene expression in gallstone-susceptible and gallstone-resistant mice.
Article in Mammalian genome : official journal of the International Mammalian Genome Society, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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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3 citing papers in PubMed, 16 citations in OpenAlex.
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- Gallstone Disease and Microbiome.Microorganisms · 2020Review
- Article
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4 authors at 1 institution in 1 country.
Funding
Abstract
Cholesterol gallstone disease affects 40 million Americans, and evidence indicates that there is a genetic component to human gallstone disease. In a mouse model of gallstone formation, where mice are fed a lithogenic diet, QTL analysis has been employed to identify the Lith 1 locus on Chromosome (Chr) 2. In order to identify genes in which the difference in expression is independent of factors other than strain-specific genotype, we employed microarray analysis of hepatic gene expression in gallstone-susceptible (C57L/J) and gallstone-resistant (AKR/J) mice. We observed 57 genes with consistent differential expression between C57L/J and AKR/J mice, including many cytochrome, antioxidant, and lipid peroxidation genes. Analysis of differentially expressed genes identified numerous genes involved in fatty acid metabolism. Northern analysis of selected lipid metabolic genes further confirmed the strain-specific differential expression. Literature searches of common regulatory elements within antioxidant systems identified the nuclear transcription factor Nrf2, which maps to the Lith 1 loci. Hepatic Nrf2 gene and protein expression is also increased in strain AKR/J, compared with C57L/J mice, identifying Nrf2 as a putative Lith 1 gallstone gene. These data indicate that microarray analysis may complement QTL analysis to identify systems of regulation and genotypic differences responsible for polygenic diseases.
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Registered trials
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