Patient-derived Induced Pluripotent Stem Cells as a Model to Study Frontotemporal Dementia Pathologies
Barber, D. L.; Infante-Tadeo, S.
Show abstract
The neurodegenerative disorder Frontotemporal Dementia (FTD) can be caused by a repeat expansion (GGGGCC; G4C2) in C9orf72. The function of wild-type C9orf72 and the mechanism by which the C9orf72-G4C2 mutation causes FTD, however, remain unresolved. Diverse disease models including human brain samples and differentiated neurons from patient-derived induced pluripotent stem cells (iPSCs) identified some hallmarks associated with FTD, but these models have limitations, including biopsies capturing only a static snapshot of dynamic processes and differentiated neurons being labor-intensive, costly, and post-mitotic. We find that patient-derived iPSCs, without being differentiated into neurons, exhibit established FTD hallmarks, including increased lysosome pH, decreased lysosomal cathepsin activity, cytosolic TDP-43 proteinopathy, and increased nuclear TFEB. Moreover, lowering lysosome pH in FTD iPSCs mitigates TDP-43 proteinopathy, suggesting a key role for lysosome dysfunction. RNA-seq reveals dysregulated transcripts in FTD iPSCs affecting calcium signaling, cell death, synaptic function, and neuronal development. We confirm differences in protein expression for some dysregulated genes not previously linked to FTD, including CNTFR (neuronal survival), Annexin A2 (anti-apoptotic), NANOG (neuronal development), and moesin (cytoskeletal dynamics). Our findings underscore the potential of FTD iPSCs as a model for studying FTD cellular pathology and for drug screening to identify therapeutics. SIGNIFICANCE STATEMENTO_LIUnderstanding the cellular pathology of Frontotemporal Dementia linked to a GGGGCC expansion in the C9orf72 gene remains a challenge. C_LIO_LIThis study shows that undifferentiated patient-derived iPSCs exhibit hallmark FTD characteristics, including lysosome dysfunction and TDP-43 proteinopathy, and identifies dysregulated genes related to neurodegeneration. C_LIO_LIThese findings highlight patient-derived iPSCs as a valuable model for studying FTD pathology and for drug screening, potentially guiding future research in therapeutic development. C_LI
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Bioenergetic and Protein Processing Imbalances Synergize in iPSC-Dopamine neurons from Individuals with Idiopathic Parkinsons Disease 95%
- Chchd10 Or Chchd2 Are Not Required For Human Motor Neuron Differentiation In Vitro But Modify Synaptic Transcriptomes 95%
- Extracellular tau clearance is governed by its aggregation state and independent of microglial activation by LPS and IFN-γ 94%
Similar papers in this journal
- The LRRK2 G2019S mutation alters astrocyte-to-neuron communication via extracellular vesicles and induces neuron atrophy in a human iPSC-derived model of Parkinson's disease 96%
- Exploring therapeutic strategies for Infantile Neuronal Axonal Dystrophy (INAD/PARK14) 95%
- APOE Expression and Secretion are Modulated by Mitochondrial Dysfunction 94%
Similar papers in this journal
- The LRRK2 kinase substrates Rab8a and Rab10 contribute complementary but distinct disease-relevant phenotypes in human neurons 98%
- NMDA receptor misalignment in iPSC-derivedneurons from a multi-generational family withinherited Creutzfeldt-Jakob disease 95%
- Sonlicromanol improves neuronal network dysfunction and transcriptome changes linked to m.3243A > G heteroplasmy in iPSC-derived neurons 94%
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 93%
- TREM2-H157Y Increases Soluble TREM2 Production and Reduces Amyloid Pathology 93%
- SETD7-mediated lysine monomethylation is abundant on non-hyperphosphorylated nuclear Tau 93%
"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.