ArticleScientific reports2022
Correlation of age of onset and clinical severity in Niemann-Pick disease type C1 with lysosomal abnormalities and gene expression.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- 2025 Consensus Clinical Management Guidelines for Niemann-Pick Disease Type C.Journal of inherited metabolic disease · 2026Review
- Article
- A multi-omics-empowered framework for precision diagnosis and treatment of lysosomal diseases.Journal of pharmaceutical analysis · 2025Review
- Advances in mass spectrometry of lipids for the investigation of Niemann-pick type C disease.Lipids in health and disease · 2025Review
- Sterol O-Acyltransferase 1 (International journal of molecular sciences · 2024Article
- Differently increased volumes of multiple brain areas inFrontiers in neuroanatomy · 2024Article
- At a glance: the largest Niemann-Pick type C1 cohort with 602 patients diagnosed over 15 years.European journal of human genetics : EJHG · 2023Article
- Understanding the phenotypic variability in Niemann-Pick disease type C (NPC): a need for precision medicine.NPJ genomic medicine · 2023Review
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
Abstract
Niemann-Pick disease type C1 (NPC1) is a rare, prematurely fatal lysosomal storage disorder which exhibits highly variable severity and disease progression as well as a wide-ranging age of onset, from perinatal stages to adulthood. This heterogeneity has made it difficult to obtain prompt diagnosis and to predict disease course. In addition, small NPC1 patient sample sizes have been a limiting factor in acquiring genome-wide transcriptome data. In this study, primary fibroblasts from an extensive cohort of 41 NPC1 patients were used to validate our previous findings that the lysosomal quantitative probe LysoTracker can be used as a predictor for age of onset and disease severity. We also examined the correlation between these clinical parameters and RNA expression data from primary fibroblasts and identified a set of genes that were significantly associated with lysosomal defects or age of onset, in particular neurological symptom onset. Hierarchical clustering showed that these genes exhibited distinct expression patterns among patient subgroups. This study is the first to collect transcriptomic data on such a large scale in correlation with clinical and cellular phenotypes, providing a rich genomic resource to address NPC1 clinical heterogeneity and discover potential biomarkers, disease modifiers, or therapeutic targets.
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