ArticleJournal of the American Heart Association2013
Genetic-genomic replication to identify candidate mouse atherosclerosis modifier genes.
Article in Journal of the American Heart Association, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 20 citations in OpenAlex.
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- Optimized Method to Generate Well-Characterized Macrophages from Induced Pluripotent Stem Cells.Biomedicines · 2025Article
- Fine Mapping of the MouseGenes · 2021Article
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- Quantitative trait locus mapping identifies the Gpnmb gene as a modifier of mouse macrophage lysosome function.Scientific reports · 2021Article
- Hepatic transcriptional profile reveals the role of diet and genetic backgrounds on metabolic traits in female progenitor strains of the Collaborative Cross.Physiological genomics · 2021Article
- Confirmation of Ath26 locus on chromosome 17 and identification of Cyp4f13 as an atherosclerosis modifying gene.Atherosclerosis · 2019Article
- CD6 expression has no effect on atherosclerosis in apolipoprotein E-deficient mice.BMC research notes · 2018Article
- Quantitative Trait Locus Mapping of Macrophage Cholesterol Metabolism and CRISPR/Cas9 Editing Implicate an ACAT1 Truncation as a Causal Modifier Variant.Arteriosclerosis, thrombosis, and vascular biology · 2018Article
- Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study.PLoS genetics · 2017Article
- Applications and Limitations of Mouse Models for Understanding Human Atherosclerosis.Cell metabolism · 2017Review
- Human Macrophage Genetic Engineering.Arteriosclerosis, thrombosis, and vascular biology · 2016Article
- Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains.PLoS genetics · 2015Article
- Genetic determinants of atherosclerosis, obesity, and energy balance in consomic mice.Mammalian genome : official journal of the International Mammalian Genome Society · 2014Article
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Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveGenetics plays a large role in atherosclerosis susceptibility in humans and mice. We attempted to confirm previously determined mouse atherosclerosis-associated loci and use bioinformatics and transcriptomics to create a catalog of candidate atherosclerosis modifier genes at these loci. METHODS AND
resultsA strain intercross was performed between AKR and DBA/2 mice on the apoE(-/-) background generating 166 F2 progeny. Using the phenotype log10 of the aortic root lesion area, we identified 3 suggestive atherosclerosis quantitative trait loci (Ath QTLs). When combined with our prior strain intercross, we confirmed 3 significant Ath QTLs on chromosomes 2, 15, and 17, with combined logarithm of odds scores of 5.9, 5.3, and 5.6, respectively, which each met the genome-wide 5% false discovery rate threshold. We identified all of the protein coding differences between these 2 mouse strains within the Ath QTL intervals. Microarray gene expression profiling was performed on macrophages and endothelial cells from this intercross to identify expression QTLs (eQTLs), the loci that are associated with variation in the expression levels of specific transcripts. Cross tissue eQTLs and macrophage eQTLs that replicated from a prior strain intercross were identified. These bioinformatic and eQTL analyses produced a comprehensive list of candidate genes that may be responsible for the Ath QTLs.
conclusionsReplication studies for clinical traits as well as gene expression traits are worthwhile in identifying true versus false genetic associations. We have replicated 3 loci on mouse chromosomes 2, 15, and 17 that are associated with atherosclerosis. We have also identified protein coding differences and multiple replicated eQTLs, which may be useful in the identification of atherosclerosis modifier genes.
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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.