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Am J Pathol. 2002 Feb;160(2):721-30.

Quantitative trait loci influence renal disease progression in a mouse model of Alport syndrome.

Author information

1
Renal Division, Department of Internal Medicine, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, Missouri 63110, USA.

Abstract

Alport syndrome is a human hereditary glomerulonephritis which results in end-stage renal failure (ESRF) in most cases. It is caused by mutations in any one of the collagen alpha3(IV), alpha4(IV), or alpha5(IV) chain genes (COL4A3-COL4A5). Patients carrying identical mutations can exhibit very different disease courses, suggesting that other genes or the environment influence disease progression. We previously generated a knockout mouse model of Alport syndrome by mutating Col4a3. Here, we show that genetic background strongly influences the timing of onset of disease and rate of progression to ESRF in these mice. On the 129X1/SvJ background, Col4a3 -/- mice reached ESRF at approximately 66 days of age, while on the C57BL/6J background, the mean age at ESRF was 194 days of age. This suggests the existence of modifier genes that influence disease progression. A detailed histopathological analysis revealed that glomerular basement membrane lesions typical of Alport syndrome were significantly more frequent in homozygotes on the 129X1/SvJ background than on the C57BL/6J background as early as two weeks of age, suggesting that modifier genes act by influencing glomerular basement membrane structure. Additional data indicated that differential physiological responses to basement membrane splitting also underlie the differences in disease progression. We attempted to map the modifier genes as quantitative trait loci (QTLs) using age at ESRF as the quantitative trait. Genome scans were performed on mice at the two extremes in a cohort of mutant F1 x C57BL/6J backcross mice. Analysis with Map Manager QT revealed QTLs linked to markers on chromosomes 9 and 16. A more detailed understanding of how these QTLs act could lead to new approaches for therapy in diverse renal diseases.

PMID:
11839593
PMCID:
PMC1850644
DOI:
10.1016/S0002-9440(10)64892-4
[Indexed for MEDLINE]
Free PMC Article

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