| First Author | Rodriguez-Gil JL | Year | 2020 |
| Journal | Dis Model Mech | PubMed ID | 31996359 |
| Mgi Jnum | J:286285 | Mgi Id | MGI:6401229 |
| Doi | 10.1242/dmm.042614 | Citation | Rodriguez-Gil JL, et al. (2020) Genetic background modifies phenotypic severity and longevity in a mouse model of Niemann-Pick disease type C1. Dis Model Mech :dmm042614 |
| abstractText | Niemann-Pick disease type C1 (NPC1) is a rare, fatal neurodegenerative disorder characterized by lysosomal accumulation of unesterified cholesterol and glycosphingolipids. These subcellular pathologies lead to phenotypes of hepatosplenomegaly, neurological degeneration, and premature death. NPC1 is extremely heterogeneous in the timing of clinical presentation and is associated with a wide spectrum of causative NPC1 mutations. To study the genetic architecture of NPC1, including the clinical and genetic heterogeneity seen in this patient population, we have generated a new NPC1 mouse model, Npc1 (em1Pav) Npc1 (em1Pav/em1Pav) mutants showed notably reduced NPC1 protein compared to controls and displayed the pathological and biochemical hallmarks of NPC1. Interestingly, Npc1 (em1Pav/em1Pav) mutants on a C57BL/6J genetic background showed more severe visceral pathology, quantified by the presence of CD68(+) foam cells, compared to Npc1 (em1Pav/em1Pav) mutants on a BALB/cJ background. Furthermore, C57BL/6J mutants exhibited a significantly shorter lifespan (mean=70 days) than Npc1 (em1Pav/em1Pav) mutants on a BALB/cJ genetic background (mean=84 days), suggesting strain-specific modifiers contribute to disease severity and survival. QTL analysis for lifespan of 202 backcross N2 mutants on a mixed C57BL/6J and BALB/cJ background detected significant linkage to markers on chromosomes 1 (LOD=5.57) and 7 (LOD=8.91). The discovery of these modifier regions demonstrates that mouse models are powerful tools for analyzing the genetics underlying rare human disease, which can be used to improve understanding of the variability in NPC1 phenotypes and advance options for patient diagnosis and therapy. |
