One and two QTL genome scans for liver fibrosis in inbred mice

Aims: Recently we identified genetic loci that determine susceptibility to liver fibrosis in experimental crosses between fibrosis-susceptible and resistant inbred strains of mice (Hillebrandt et al. Gastroenterology 2002;123: 2041–2051 and Nat Genet 2005;37: 835–43). For these analyses, we modelled the effects of single QTLs only. Our aim now was to assess the effects of gender and multiple (additive or interacting) QTLs on liver fibrosis.

Methods: We intercrossed F1 hybrids of the fibrosis-susceptible strain BALB/cJ and the resistant strain FVB/NJ and generated 294 F2 progeny. To induce liver fibrosis, we challenged all mice with CCl4 (2mg/kg/wk i.p. for 6 wks). For phenotypic characterization, we determined the histological stage of liver fibrosis and measured hepatic collagen contents via the specific amino acid hydroxyproline. We performed a one QTL genome scan with microsatellite markers (average distance 14 cM) in all backcross progeny, followed by scans of all pair wise interactions, as implemented in R/qtl (two QTL genome scans). LOD thresholds were determined by permutation tests.

Results: The 294 intercross progeny show a normal distribution of collagen concentrations, consistent with polygenic inheritance of fibrosis susceptibility in our model (mean fibrosis stage 1.8±0.5; mean collagen content 319±113,15 μg hydroxyproline/g liver). In extension of our previously described fibrogenic QTLs (Hfib1 and Hfib2) on mouse chromosomes 2 and 15, one QTL genome scans observed peak linkage for fibrosis stages and collagen accumulation on mouse chromosomes 1 and 16. In the two QTL genome scans, we identified gene-gene interaction of several QTLs. When analyzing gene-gender interaction, we observed significantly higher LOD scores in female F2 progeny but no linkage to chromosome X.

Conclusions: This genome analysis demonstrates single susceptibility loci, gene-gene epistasis and gene-gender interactions during liver fibrogenesis and provides a basic experimental framework to model biological networks during chronic liver injury.