NPC1 deficiency engages a lysosome - genome - immune program linked to neurodegeneration and cellular aging signatures
Abyadeh, M.; Zarei, M.; Hou, P.-C.; Sari, V.; Lee, K.; Hameed, R.; Mehkri, B.; Malaugh, E.; Newton, J.; Kordula, T.; Wang, Y.-H.; Kaya, A.
Show abstract
Lysosomal dysfunction is a prominent feature of neurodegeneration and aging, yet how primary defects in lysosomal trafficking are converted into progressive cellular decline remains poorly understood. Niemann Pick disease type C (NPC), caused by impaired NPC1 dependent cholesterol export, provides a genetically defined model to address this question. Here, we show that NPC1 deficiency activates a lysosome, genome, immune axis linking cholesterol trafficking failure to neurodegeneration and hallmarks of cellular aging. In Npc1 mutant mice, NPC1 loss triggered DNA damage, neuroinflammation, microglial and astrocytic activation, Purkinje neuron degeneration, and motor dysfunction. Consistently, NPC patient-derived fibroblasts exhibited mitochondrial abnormalities and widespread DNA double-strand breaks. Genome-wide DNA break mapping and transcriptomic analyses revealed extensive genomic instability at regulatory regions, including enrichment of DNA breaks at transcription start sites and G quadruplex associated loci, accompanied by widespread transcriptional reprogramming, activation of innate immune pathways, disruption of fibroblast identity, and induction of cellular aging signatures. We further identify Fingolimod, an FDA approved sphingosine - 1 phosphate receptor modulator, as a potent modifier of this disease network. Fingolimod improved lysosomal cholesterol trafficking, increased LAMP1 abundance, attenuated STING associated inflammatory signaling, normalized mitochondrial function, reduced neuroinflammatory and neurodegenerative phenotypes in Npc1 mutant mice, and broadly shifted disease-associated transcriptional programs toward a healthier state. Extending these findings beyond NPC, Fingolimod improved age-associated phenotypes in C. elegans and prolonged lifespan in aged male mice. Together, these findings identify genome instability and chronic innate immune activation as major downstream consequences of lysosomal cholesterol trafficking failure and establish Fingolimod as a clinically actionable modulator of lysosomal dysfunction, neurodegeneration, and aging-related decline.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Functional genomic analyses highlights a shift in Gpr17-regulated cellular processes in oligodendrocyte progenitor cells (OPC) and underlying myelin dysregulation in the aged forebrain 95%
- Ghrelin delays premature aging in Hutchinson-Gilford progeria syndrome 95%
- Nuclear Import Defects Drive Cell Cycle Dysregulation in Neurodegeneration 95%
Similar papers in this journal
Similar papers in this journal
- A Trem2*R47H mouse model without cryptic splicing drives age- and disease-dependent tissue damage and synaptic loss in response to plaques 95%
- LRRK2 Kinase Activity Regulates Parkinson's Disease-Relevant Lipids at the Lysosome 94%
- β-Amyloid Induces Microglial Expression of GPC4 and APOE Leading to Increased Neuronal Tau Pathology and Toxicity 94%
Similar papers in this journal
- Microglial MHC-I induction with aging and Alzheimer's is conserved in mouse models and humans 96%
- Amyloid β accelerates age-related proteome-wide protein insolubility. 94%
- Activation of the muscle-to-brain axis ameliorates neurocognitive deficits in an Alzheimer disease mouse model via enhancing neurotrophic and synaptic signaling 94%
Similar papers in this journal
- Pharmacological rescue of impaired mitophagy in Parkinson's disease-related LRRK2 G2019S knock-in mice 95%
- Steady-state neuron-predominant LINE-1 encoded ORF1p protein and LINE-1 RNA increase with aging in the mouse and human brain 95%
- Autophagy in T cells from aged donors is maintained by spermidine, and correlates with function and vaccine responses 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.