A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease
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PROVIDER: PRJNA593734 | ENA |
REPOSITORIES: ENA
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Project description:Background: Late-onset Alzheimer’s disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer’s have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes. Results: This resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of three mouse models based on LOAD genetics, carrying APOE4 and TREM2*R47H alleles and the 5xFAD mouse, a widely used amyloid pathology model, demonstrated overlaps with distinct human AD modules that, in turn, are functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq shows strong correlation between gene expression changes independent of experimental platform. Conclusions: Taken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models
2020-02-03 | GSE141509 | GEO
Project description:BackgroundLate-onset Alzheimer's disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer's have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes.ResultsThis resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of the 5xFAD mouse, a widely used amyloid pathology model, and three mouse models based on LOAD genetics carrying APOE4 and TREM2*R47H alleles demonstrated overlaps with distinct human AD modules that, in turn, were functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq showed strong correlation between gene expression changes independent of experimental platform.ConclusionsTaken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models.
| S-EPMC7656729 | biostudies-literature
Project description:A systems-biology approach connects aging mechanisms with Alzheimer’s disease pathogenesis
| PRJNA1089313 | ENA
Project description:Age is the strongest risk factor for developing Alzheimer’s disease, the most common neurodegenerative disorder. However, the mechanisms connecting advancing age to neurodegeneration in Alzheimer’s disease are incompletely understood. We conducted an unbiased, genome-scale, forward genetic screen for age-associated neurodegeneration in Drosophila to identify the underlying biological processes required for maintenance of aging neurons. To connect genetic screen hits to Alzheimer’s disease pathways, we measured proteomics, phosphoproteomics, and metabolomics in Drosophila models of Alzheimer’s disease. We further identified Alzheimer’s disease human genetic variants that modify expression in disease-vulnerable neurons. Through multi-omic, multi-species network integration of these data, we identified relationships between screen hits and tau-mediated neurotoxicity. Furthermore, we computationally and experimentally identified relationships between screen hits and DNA damage in Drosophila and human iPSC-derived neural progenitor cells. Our work identifies candidate pathways that could be targeted to attenuate the effects of age on neurodegeneration and Alzheimer’s disease.
2025-02-07 | GSE261878 | GEO
Project description:Age is the strongest risk factor for developing Alzheimer’s disease, the most common neurodegenerative disorder. However, the mechanisms connecting advancing age to neurodegeneration in Alzheimer’s disease are incompletely understood. We conducted an unbiased, genome-scale, forward genetic screen for age-associated neurodegeneration in Drosophila to identify the underlying biological processes required for maintenance of aging neurons. To connect genetic screen hits to Alzheimer’s disease pathways, we measured proteomics, phosphoproteomics, and metabolomics in Drosophila models of Alzheimer’s disease. We further identified Alzheimer’s disease human genetic variants that modify expression in disease-vulnerable neurons. Through multi-omic, multi-species network integration of these data, we identified relationships between screen hits and tau-mediated neurotoxicity. Furthermore, we computationally and experimentally identified relationships between screen hits and DNA damage in Drosophila and human iPSC-derived neural progenitor cells. Our work identifies candidate pathways that could be targeted to attenuate the effects of age on neurodegeneration and Alzheimer’s disease.
2025-02-07 | GSE261775 | GEO
Project description:A systems-biology approach connects aging mechanisms with Alzheimer’s disease pathogenesis [TCPY]
| PRJNA1088842 | ENA
Project description:Alzheimer’s disease (AD) is the most common neurodegenerative dementia. Around 10% of cases present an age of onset before 65 years-old, which in turn can be divided in monogenic or familial AD (FAD) and sporadic early-onset AD (EOAD). Mutations in PSEN1, PSEN2 and APP genes have been linked with FAD. The aim of our study was to describe the brain whole-genome RNA expression profile of the posterior cingulate area in EOAD and FAD caused by PSEN1 mutations (FAD-PSEN1). 14 patients (7 EOAD and 7 FAD-PSEN1) and 7 neurologically healthy controls were selected and samples were hybridized in a Human Gene 1.1 microarray from Affymetrix. When comparing controls with EOAD and controls with FAD-PSEN1, we found 3183 and 3351 differentially expressed genes (DEG) respectively (FDR corrected p<0.05). However, any DEG was found in the comparison of the two groups of patients. Microarrays were validated through quantitative-PCR of 17 DEG. In silico analysis of the DEG revealed an alteration in biological pathways related to calcium-signaling, axon guidance and long-term potentiation (LTP), among others, in both groups of patients. These pathways are mainly related with cell signalling cascades, synaptic plasticity and learning and memory processes. In conclusion, the altered biological final pathways in EOAD and FAD-PSEN1 are highly coincident. Also, the findings are in line with those previously reported for late-onset AD (LOAD, onset >65 years-old), which implies that the consequences of the disease at the molecular level are similar in the final stages of the disease. 21 Samples were analyzed: 7 controls, 7 Early-onset Alzheimer's disease (AD) patients and 7 early-onset AD genetically determined by a mutation in PSEN1 gene.
2015-01-20 | E-GEOD-39420 | biostudies-arrayexpress
Project description:Lithium Deficiency and the Onset of Alzheimer’s Disease
| PRJNA1150257 | ENA
Project description:Lithium Deficiency and the Onset of Alzheimer’s Disease
| PRJNA1136488 | ENA
Project description:Lithium Deficiency and the Onset of Alzheimer’s Disease [3xTG_LiO]
| PRJNA1256375 | ENA