Diabetologie und Stoffwechsel 2015; 10 - P121
DOI: 10.1055/s-0035-1549627

Identification of novel susceptibility genes for diabetes- and obesity-related traits in a backcross of obese NZO with lean C3 H mice

T Schallschmidt 1, S Osthold 1, Y Schulte 1, M Damen 1, T Stermann 1, A Chadt 1, H Al-Hasani 1
  • 1German Diabetes Center (DDZ), Leibniz-Center for Diabetes Research at the Heinrich-Heine-University Düsseldorf, Institute for Clinical Biochemistry and Pathobiochemistry, Düsseldorf, Germany

Background and aims: Type 2 diabetes (T2D) in humans is influenced by a combination of hundreds of adipogenic and diabetogenic alleles. In outcross experiments of obese and lean mouse strains, several QTL (Quantitative Trait Loci) for obesity and hyperglycaemia were separated. Mouse models could therefore help to identify several key obesity and diabetes modifier genes. In order to find further disease genes we performed a new crossbreeding approach and subsequent QTL analysis with obese New Zealand Obese (NZO) and lean C3HeB/FeJ mice.

Methods: We measured phenotypic traits associated with obesity and T2D in 310 N2 females and 330 males, fed a high-fat-diet (45% fat/cal.). Body weight, body composition, plasma glucose and -insulin concentrations during fasted and fed states were measured. At 21 weeks mice were sacrificed and tissues were harvested for analysis of metabolic regulators. We genotyped the N2 population via a genome-wide high-density SNP panel. Linkage analysis was performed by calculation of phenotype-genotype associations.

Results: Genetic linkage analysis revealed three highly significant QTLs on chromosomes 4 (32 cM, LOD 8.4), 7 (12 cM, LOD 14.0) and 15 (13 cM, LOD 7.5) for metabolic traits. The largest effects were contributed by Chromosome 7, where peaks of logarithm of odds (LOD) overlapped for blood glucose, body weight, lean mass, final plasma insulin and BMI.

Conclusion: We could successfully identify novel QTLs associated with obesity and T2D through a mouse genetic approach. Positional cloning and gene expression studies will help to narrow down the candidate regions until causal genes will be found.