Genetic‐Genomic Replication to Identify Candidate Mouse Atherosclerosis Modifier Genes. Issue 1 (23rd January 2013)

• Record Type: Journal Article
• Authors: Hsu, Jeffrey; Smith, Jonathan D.
• Is Part Of: Journal of the American Heart Association. Volume 2:Issue 1(2013:Feb.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-01-23
• Subjects: atherosclerosis -- genetics -- transcriptomics; Heart -- Diseases -- Periodicals; Cardiovascular system -- Diseases -- Periodicals; Cerebrovascular disease -- Periodicals; Cardiology -- Periodicals; 616.1
• DOI: 10.1161/JAHA.112.005421
• Languages: English
• ISSNs: 2047-9980

Abstract

Abstract : Objective: Genetics 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 Results: A 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. Conclusions: Replication 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.