Mammalian Genome

, Volume 25, Issue 11, pp 549–563

Genetic determinants of atherosclerosis, obesity, and energy balance in consomic mice

  • Sabrina H. Spiezio
  • Lynn M. Amon
  • Timothy S. McMillen
  • Cynthia M. Vick
  • Barbara A. Houston
  • Mark Caldwell
  • Kayoko Ogimoto
  • Gregory J. Morton
  • Elizabeth A. Kirk
  • Michael W. Schwartz
  • Joseph H. Nadeau
  • Renée C. LeBoeuf
Article

DOI: 10.1007/s00335-014-9530-2

Cite this article as:
Spiezio, S.H., Amon, L.M., McMillen, T.S. et al. Mamm Genome (2014) 25: 549. doi:10.1007/s00335-014-9530-2

Abstract

Metabolic diseases such as obesity and atherosclerosis result from complex interactions between environmental factors and genetic variants. A panel of chromosome substitution strains (CSSs) was developed to characterize genetic and dietary factors contributing to metabolic diseases and other biological traits and biomedical conditions. Our goal here was to identify quantitative trait loci (QTLs) contributing to obesity, energy expenditure, and atherosclerosis. Parental strains C57BL/6 and A/J together with a panel of 21 CSSs derived from these progenitors were subjected to chronic feeding of rodent chow and atherosclerotic (females) or diabetogenic (males) test diets, and evaluated for a variety of metabolic phenotypes including several traits unique to this report, namely fat pad weights, energy balance, and atherosclerosis. A total of 297 QTLs across 35 traits were discovered, two of which provided significant protection from atherosclerosis, and several dozen QTLs modulated body weight, body composition, and circulating lipid levels in females and males. While several QTLs confirmed previous reports, most QTLs were novel. Finally, we applied the CSS quantitative genetic approach to energy balance, and identified three novel QTLs controlling energy expenditure and one QTL modulating food intake. Overall, we identified many new QTLs and phenotyped several novel traits in this mouse model of diet-induced metabolic diseases.

Supplementary material

335_2014_9530_MOESM1_ESM.pdf (222 kb)
Supplementary material 1 (PDF 222 kb)
335_2014_9530_MOESM2_ESM.pdf (214 kb)
Supplementary material 2 (PDF 214 kb)
335_2014_9530_MOESM3_ESM.pdf (248 kb)
Supplementary material 3 (PDF 247 kb)
335_2014_9530_MOESM4_ESM.pdf (247 kb)
Supplementary material 4 (PDF 247 kb)

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Sabrina H. Spiezio
    • 1
  • Lynn M. Amon
    • 2
  • Timothy S. McMillen
    • 3
  • Cynthia M. Vick
    • 3
  • Barbara A. Houston
    • 3
  • Mark Caldwell
    • 3
  • Kayoko Ogimoto
    • 3
  • Gregory J. Morton
    • 3
  • Elizabeth A. Kirk
    • 4
  • Michael W. Schwartz
    • 3
  • Joseph H. Nadeau
    • 5
  • Renée C. LeBoeuf
    • 3
    • 6
  1. 1.Institute for Systems BiologySeattleUSA
  2. 2.Seattle Biomedical Research InstituteSeattleUSA
  3. 3.Division of Metabolism, Endocrinology, Nutrition, and Diabetes and Obesity Center of Excellence, Department of MedicineUniversity of WashingtonSeattleUSA
  4. 4.Bastyr UniversityKenmoreUSA
  5. 5.Pacific Northwest Research InstituteSeattleUSA
  6. 6.Department of MedicineUniversity of WashingtonSeattleUSA