Abstract 5519: High Resolution Genetic Mapping Strategies for Metabolic Disease in Mice: Towards Association Based Studies
Background: Common complex diseases, such as atherosclerosis, diabetes and obesity, are the result of genetic, environmental and gene/environmental interactions. Genetic studies using mice have relied on linkage studies where two mouse strains with different disease phenotypes are crossed to identify a genetic loci conferring susceptibility or resistance to the disease. One limitation with such an approach is that linkage areas are many megabases in size and thus gene resolution is low. Recently, several whole genome association studies in large human cohorts have reported single nucleotide polymorphisms (SNPs) associated with common forms of disease. We have begun similar association based approaches to common diseases using mice. One important advantage of murine association studies is that association results can be validated biologically with knockout or transgenic approaches.
Methods and Results: Our initial studies have focused on the metabolic syndrome and we have collected traits related to diabetes, adiposity and cholesterol metabolism. We have phenotyped 100 strains of mice including a panel of classic inbred mice and several panels of recombinant inbred mice (BxH, AxB, BxA and BxD). We report here our initial strategy for association in mice, power calculations and describe strain selection along with initial phenotypes and associations. Our laboratory has previously identified linkage peaks on chromosome 1 for HDL and Total Cholesterol. Studies from our laboratory and others have identified apolipoprotein A2 as a major determinate of circulating lipoproteins in mice. As a proof of principle we have focused on associations of total cholesterol and HDL cholesterol at the A2 locus on chromosome 1 and demonstrate the increased resolution of this approach. We also report loci contributing to HDL and total cholesterol levels from independent F2 crosses and coincident lipoprotein associations in the mouse diversity panel.
Conclusion: Association based studies in mice have high resolution can successfully identify previously validated genes. Studies are currently ongoing to validate novel SNPs associated with other metabolic phenotypes.
This research has received full or partial funding support from the American Heart Association, AHA National Center.