Project description:Late-onset Alzheimer’s disease (LOAD) is the most common form of AD. However, modeling sporadic LOAD, without clear genetic predispositions, to capture hallmark neuronal pathologies such as extracellular amyloid-β (Aβ) plaque deposition, intracellular tau tangles, and neuronal loss, remains an unmet need. Here, we demonstrate that neurons generated by microRNA-based direct reprogramming of fibroblasts from patients affected by autosomal dominant AD (ADAD) and LOAD in a three-dimensional (3D) environment, effectively recapitulate key neuropathological features of AD without additional cellular or genetic insults. These LOAD neurons exhibit Aβ-dependent neurodegeneration, as treatment with β- or γ-secretase inhibitors before (but not subsequent to) Aβ deposit formation mitigated neuronal death. Moreover, inhibiting age-associated retrotransposable elements (RTEs) in LOAD neurons reduced both Ab deposition and neurodegeneration. Our study underscores the efficacy of modeling late-onset neuropathology of LOAD through high-efficiency microRNA-based neuronal reprogramming.
Project description:Late-onset Alzheimer’s disease (LOAD) is the most common form of AD. However, modeling sporadic LOAD, without clear genetic predispositions, to capture hallmark neuronal pathologies such as extracellular amyloid-β (Aβ) plaque deposition, intracellular tau tangles, and neuronal loss, remains an unmet need. Here, we demonstrate that neurons generated by microRNA-based direct reprogramming of fibroblasts from patients affected by autosomal dominant AD (ADAD) and LOAD in a three-dimensional (3D) environment, effectively recapitulate key neuropathological features of AD without additional cellular or genetic insults. These LOAD neurons exhibit Aβ-dependent neurodegeneration, as treatment with β- or γ-secretase inhibitors before (but not subsequent to) Aβ deposit formation mitigated neuronal death. Moreover, inhibiting age-associated retrotransposable elements (RTEs) in LOAD neurons reduced both Ab deposition and neurodegeneration. Our study underscores the efficacy of modeling late-onset neuropathology of LOAD through high-efficiency microRNA-based neuronal reprogramming.
Project description:Late-onset Alzheimer’s disease (LOAD) is the most common form of AD. However, modeling sporadic LOAD, without clear genetic predispositions, to capture hallmark neuronal pathologies such as extracellular amyloid-β (Aβ) plaque deposition, intracellular tau tangles, and neuronal loss, remains an unmet need. Here, we demonstrate that neurons generated by microRNA-based direct reprogramming of fibroblasts from patients affected by autosomal dominant AD (ADAD) and LOAD in a three-dimensional (3D) environment, effectively recapitulate key neuropathological features of AD without additional cellular or genetic insults. These LOAD neurons exhibit Aβ-dependent neurodegeneration, as treatment with β- or γ-secretase inhibitors before (but not subsequent to) Aβ deposit formation mitigated neuronal death. Moreover, inhibiting age-associated retrotransposable elements (RTEs) in LOAD neurons reduced both Ab deposition and neurodegeneration. Our study underscores the efficacy of modeling late-onset neuropathology of LOAD through high-efficiency microRNA-based neuronal reprogramming.
Project description:Our data provide a comprehensive list of transcriptomics alterations and warrant holistic approach including both coding and non-coding RNAs in functional studies aimed to understand the pathophysiology of LOAD We performed directional RNA sequencing on high quality RNA samples extracted from hippocampi of 4 late onset Alzheimer's diseas (LOAD) and 4 age-matched controls.
Project description:Cerebrospinal fluid proteomic profiling reflects biological heterogeneity of early-onset Alzheimer's disease dementia from The First Affiliated Hospital of USTC
Project description:To identify the gene expression of early-onset colorectal cancer, we sampled early-onset colorectal cancer patients (age < 50) and late-onset colorectal cancer paitients (age > 70) We then performed gene expression profiling analysis using data obtained from RNA-seq of early-onset colorectal cancer tissues and late-onset colorectal cancer tissues.