Project description:<p>Alzheimer disease is the most common neurodegenerative disorder of the elderly affecting an estimated five million Americans. Genetic factors contribute to the risk for disease with heritability estimates ranging from 57% to 79%. More than a decade ago, the ε4 variant of APOE was identified and remains the most consistently replicated genetic variant influencing the risk of late onset Alzheimer disease. A segregation analysis suggests there may be four additional genes influencing the age-at-onset of Alzheimer disease. In 2007 there were 968 association studies in 398 candidate genes reported, but none replicated consistently. There are many reasons for the lack of consistency, but one important reason for the lack of progress is the paucity of a sufficient number of well characterized families and patients available to the entire scientific community. The extensive effort and expense required to ascertain such a population has been addressed by the NIA-LOAD Family Study. Its goal is to identify and recruit families with two or more siblings with the late-onset form of Alzheimer's disease and a cohort of unrelated, non-demented controls similar in age and ethnic background, and to make the samples, the clinical and genotyping data and preliminary analyses available to qualified investigators world-wide. Genotyping by the Center for Inherited Disease Research (CIDR) was performed using the Illumina Infinium II assay protocol with hybridization to Illumina Human 610Quadv1_B Beadchips. This genotyping represents the largest collection of families ever assembled with Alzheimer's disease combining the NIA-LOAD Genetics Initiative Multiplex Family Study, the National Cell Repository for Alzheimer's Disease (NCRAD) with additional controls from the University of Kentucky. These genotyping results will serve as a focal point for future research that will identify all of the remaining genetic variants in Alzheimer's disease.</p>
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: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.