Sj. Rozzo et al., EFFECT OF GENETIC BACKGROUND ON THE CONTRIBUTION OF NEW-ZEALAND BLACKLOCI TO AUTOIMMUNE LUPUS NEPHRITIS, Proceedings of the National Academy of Sciences of the United Statesof America, 93(26), 1996, pp. 15164-15168
Autoimmune diseases such as systemic lupus erythematosus are complex g
enetic traits with contributions from major histocompatibility complex
(MHC) genes and multiple unknown non-MHC genes. Studies of animal mod
els of lupus have provided important insight into the immunopathogenes
is of disease, and genetic analyses of these models overcome certain o
bstacles encountered when studying human patients, Genome-wide scans o
f different genetic crosses have been used to map several disease-link
ed loci in New Zealand hybrid mice. Although some consensus exists amo
ng studies mapping the New Zealand Black (NZB) and New Zealand White (
NZW) loci that contribute to lupus-like disease, considerable variabil
ity is also apparent. A variable in these studies is (he genetic backg
round of the nonautoimmune strain, which could influence genetic contr
ibutions from the affected strain, A direct examination of this questi
on was undertaken in the present study by mapping NZB nephritis-linked
loci in backcrosses involving different non-autoimmune backgrounds, I
n a backcross with MHC-congenic C57BL/6J mice, H2(z) appeared to be th
e strongest genetic determinant of severe lupus nephritis, whereas in
a backcross with congenic BALB/cJ mice, H2(z) showed no influence on d
isease expression, NZB loci on chromosomes 1, 4, 11, and 14 appeared t
o segregate with disease in the BALB/cJ cross, but only the influence
of the chromosome 1 locus spanned both crosses and showed linkage with
disease when all mice were considered, Thus, the results indicate tha
t contributions from disease-susceptibility Loci, including MHC, may v
ary markedly depending on the non-autoimmune strain used in a backcros
s analysis, These studies provide insight into variables that affect g
enetic heterogeneity and add an important dimension of complexity for
linkage analyses of human autoimmune disease.