title: QTLs influencing IGF-1 levels in a LOU/CxFischer 344F2 rat population. Tracks towards the metabolic theory of Ageing.
abstract: OBJECTIVE
  Since a reduction of the insulin/IGF-1 signaling cascade extends life span in many species and IGF-1 signaling might partly mediate the effects of caloric restriction (CR), an experimental intervention for increasing longevity, the purpose of the present study was to use quantitative trait loci (QTL) analysis, an unbiased genetic approach, to identify particular regions of the genome influencing plasma IGF-1 levels in an F2 intercross between F344 and LOU/C rats; the latter being an inbred strain of Wistar origin, considered as a model of healthy aging since it resists to age (and diet)-induced obesity.
  
  
  METHODS
  F1 hybrids were obtained by crossbreeding LOU/C with F344 rats, and then F1 were bred inter se to obtain the F2 population, of which 93 males and 94 females were studied. Total plasma IGF-1 levels were determined by radioimmunoassay. A genome scan of the F2 population was made with 100 microsatellite markers) selected for their polymorphism between LOU/C and F344 strains (and by covering evenly the whole genome.
  
  
  RESULTS
  By simple interval mapping sex-dependent QTLs were found on chromosome 17 in males and on chromosome 18 in females. By multiple interval mapping, additional QTLs were found on chromosomes 1, 4, 5, 6, 12, 15 and 19 in males and on chromosomes 3, 5, 6, 12 and 17 in females. Only the markers D1Rat196 and D12Mgh5 were found in both males and females. The majority of QTLs corresponded to metabolic syndrome (cardiac function: n = 45 (30%), obesity/diabetes: n = 22 (15%), inflammation: n = 19 (13%) and only a limited number to body weight: n = 13 (9%), proliferation (n = 10 (7%) or ossification: n = 7 (5%). Ninety-six candidate genes were located on the different QTLs. A significant proportion of these genes are connected to IGF-1 production and receptor pathways (n = 18) or metabolic syndrome (n = 11).
  
  
  CONCLUSIONS
  Subsequent studies are necessary to determine whether the genetic networks underscored are also involved in age-associated obesity, diabetes and inflammation as well as cardiovascular impairments.
authors.affiliation: INRA, Laboratory of Nutrition and Integrative Neurobiology, UMR1286, 33076 Bordeaux Cedex, France; Univ. Bordeaux, Laboratory of Nutrition and Integrative Neurobiology, UMR1286, 33076 Bordeaux Cedex, France.
authors.forename: Nathalie
authors.initials: N
authors.lastname: Marissal-Arvy
authors.forename: Emmanuelle
authors.initials: E
authors.lastname: Duron
authors.forename: Frédéric
authors.initials: F
authors.lastname: Parmentier
authors.forename: Philippe
authors.initials: P
authors.lastname: Zizzari
authors.forename: Pierre
authors.initials: P
authors.lastname: Mormède
authors.forename: Jacques
authors.initials: J
authors.lastname: Epelbaum
mesh_terms: D000375:Aging / Q000502:physiology*; D000818:Animals; D003433:Crosses, Genetic; D005260:Female; D007334:Insulin-Like Growth Factor I / Q000378:metabolism*; D008126:Lod Score; D008297:Male; D053858:Metabolic Networks and Pathways; D010641:Phenotype; D040641:Quantitative Trait Loci; D011863:Radioimmunoassay; D051381:Rats; D011916:Rats, Inbred F344; D017208:Rats, Wistar
chemical_list: D007334:Insulin-Like Growth Factor I
keywords: Ageing; Energy metabolism; Inflammation; Metabolic syndrome