Mouse genetic model for clinical and immunological heterogeneity of leishmaniasis
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
- MeSH
- cytokiny krev MeSH
- druhová specificita MeSH
- genetická predispozice k nemoci MeSH
- genetická variace MeSH
- imunoglobulin E krev MeSH
- kinetika MeSH
- Leishmania major MeSH
- leishmanióza genetika imunologie patologie MeSH
- modely genetické MeSH
- modely nemocí na zvířatech * MeSH
- myši inbrední BALB C MeSH
- myši kongenní genetika imunologie MeSH
- myši MeSH
- zvířata MeSH
- Check Tag
- myši MeSH
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- cytokiny MeSH
- imunoglobulin E MeSH
Systematic assessment of the role of host genes in clinico-pathological and immunological manifestations of Leishmania major-induced disease in mice was performed using 20 recombinant congenic (RC) strains. As the RC strains are homozygous and each carries a different, random set of 12.5% genes from the resistant strain, STS/A, and 87.5% genes from the susceptible strain, BALB/cHeA, they allowed us to study the pathological and immunological characteristics of infected hosts in 20 fixed different random combinations of BALB/c and STS genes. The 20 RC strains differ widely in expression of different symptoms of disease and in immunological characteristics. Disease or healing in different strains occurred in association with different components of immune response -- with the exception of a frequently occurring correlation between the disease and IgE levels. Moreover, some parameters of the immune response were highly correlated in some strains but not at all in others. This shows that several patterns of the immune response may be associated with the same clinical outcome, depending on the host genotype. Our data also suggest that despite the complexity of regulation, when a sufficient number of controlling loci is known, the prediction of a phenotype is possible. Combining functional and clinical information with multilocus genotyping may improve our ability to predict the progression of the disease and to optimize the treatment.
Citace poskytuje Crossref.org
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