ArticleBiomaterials research2024
Systemic Treatment with siRNA Targeting Gamma-Secretase Activating Protein Inhibits Amyloid-β Accumulation in Alzheimer's Disease.
Article in Biomaterials research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- The Potential Use of Matrix Metalloproteinases in Alzheimer's Disease Therapy.Journal of clinical medicine · 2026Review
- An overview of gene and cell therapy approaches for Alzheimer's disease.Metabolic brain disease · 2025Review
- Exosome-membrane and polymer-based hybrid-complex for systemic delivery of plasmid DNA into brains for the treatment of glioblastoma.Asian journal of pharmaceutical sciences · 2025Article
- The manipulator behind "Scissors": γ -secretase and its modulators in Alzheimer's disease.Frontiers in aging neuroscience · 2025Review
- Neurotrophic Effects ofInternational journal of molecular sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Amyloid-β (Aβ) peptide aggregation in the brain is a key factor in Alzheimer's disease. However, direct inhibition of β-secretase or γ-secretase proves ineffective in reducing Aβ accumulation and improving cognition in Alzheimer's. Recent findings suggest that inhibiting gamma-secretase activating protein (GSAP) can decrease Aβ generation without affecting crucial γ-secretase substrates. Dimerization of Lep9R3LC (diLep9R3LC) was confirmed by Ellman's test. The peptide-small interfering RNA (siRNA) complex ratio, particle size, and surface charge were analyzed using electrophoretic mobility shift assay, and dynamic light scattering, respectively. In a 3xTg mice model of Alzheimer's disease, diLep9R3LC:siRNA complexes were intravenously administered twice a week for 8 weeks. Assessments included gene silencing, protein expression, and behavioral improvement using reverse transcription polymerase chain reaction, quantitative polymerase chain reaction, western blotting, Y-maze, and object recognition tests. The efficacy of Lep9R3LC dimerization was ~80% after a 3-d reaction by Ellman's test. In N2a cells, diLep9R3LC:siGSAP complexes achieved ~70% silencing at 48 h posttransfection. In 7-month-old male 3xTg mice, GSAP knockdown was ~30% in the cortex and ~50% in the hippocampus. The behavior improved in mice treated with diLep9R3LC:siGSAP complexes, showing a 60% increase in entries and an 80% increase object recognition. A novel dipeptide, diLep9R3LC, complexed with siRNA targeting GSAP (siGSAP), efficiently delivers siRNA to the mouse brain, targeting the hippocampus. The treatment inhibits Aβ accumulation, reduces GSK-3β-associated with tau hyperphosphorylation, and improves Alzheimer's behavior. Our findings highlight diLep9R3LC:siGSAP's potential for Alzheimer's and as a siRNA carrier for central nervous system-related diseases.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.