Inflammatory gene expression profiling in peripheral blood from patients with Alzheimer’s disease reveals key pathways and hub genes with potential diagnostic utility
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE168813 | GEO | 2021/03/13
REPOSITORIES: GEO
Similar Datasets
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: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.
2015-01-20 | GSE39420 | GEO
Project description:We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We now have analyzed additional samples with a confirmed pathologic diagnosis of late onset Alzheimer's disease (LOAD, final n=187 controls, 176 cases). Nine percent of the cortical transcripts we analyzed had expression profiles correlated with their genotypes in the combined cohort and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power to find risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease. see DOI:10.1016/j.ajhg.2009.03.011 for further details and complete author list.
2009-04-10 | GSE15222 | GEO
Project description:The genetics of complex disease produce alterations in molecular interactions of cellular pathways which collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer´s disease (LOAD), we constructed gene regulatory networks in hundreds of autopsied brain tissues from LOAD patients and non-demented subjects. We demonstrate that LOAD reconfigures specific portions of the molecular interaction structure, and via an integrative network-based approach we rank ordered these sub-networks (modules) for relevance to LOAD pathology, highlighting the immune/microglia module as the top ranking. Through a Bayesian inference approach we identified multiple key causal regulators for LOAD brains.
2013-04-25 | GSE44770 | GEO
Project description:The genetics of complex disease produce alterations in molecular interactions of cellular pathways which collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer´s disease (LOAD), we constructed gene regulatory networks in hundreds of autopsied brain tissues from LOAD patients and non-demented subjects. We demonstrate that LOAD reconfigures specific portions of the molecular interaction structure, and via an integrative network-based approach we rank ordered these sub-networks (modules) for relevance to LOAD pathology, highlighting the immune/microglia module as the top ranking. Through a Bayesian inference approach we identified multiple key causal regulators for LOAD brains.
2013-04-25 | GSE44768 | GEO
Project description:The genetics of complex disease produce alterations in molecular interactions of cellular pathways which collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer´s disease (LOAD), we constructed gene regulatory networks in hundreds of autopsied brain tissues from LOAD patients and non-demented subjects. We demonstrate that LOAD reconfigures specific portions of the molecular interaction structure, and via an integrative network-based approach we rank ordered these sub-networks (modules) for relevance to LOAD pathology, highlighting the immune/microglia module as the top ranking. Through a Bayesian inference approach we identified multiple key causal regulators for LOAD brains.
2013-04-25 | GSE44771 | GEO
Project description: Not available
| S-EPMC10642492 | biostudies-literature
Project description:Alzheimer’s disease (AD) manifested before age 65 is commonly referred to as early-onset AD (EOAD). While the majority (> 90%) of EOAD cases are not caused by autosomal-dominant mutations in PSEN1, PSEN2, and APP, they do have a higher heritability (92–100%) than sporadic late-onset AD (LOAD, 70%). Although the endpoint clinicopathological changes, i.e., Aβ plaques, tau tangles, and cognitive decline, are common across EOAD and LOAD, the disease progression is highly heterogeneous. This heterogeneity, leading to temporally distinct age at onset (AAO) and stages of cognitive decline, may be caused by myriad combinations of distinct disease-associated molecular mechanisms. We and others have used transcriptome profiling in AD patient-derived neuron models of autosomal-dominant EOAD and sporadic LOAD to identify disease endotypes. Further, analyses of large postmortem brain cohorts demonstrate that only one-third of AD patients show hallmark disease endotypes like increased inflammation and decreased synaptic signaling. Areas of the brain less affected by AD pathology at early disease stages—such as the primary visual cortex—exhibit similar transcriptomic dysregulation as those regions traditionally affected and, therefore, may offer a view into the molecular mechanisms of AD without the associated inflammatory changes and gliosis induced by pathology. To this end, we analyzed AD patient samples from the primary visual cortex (19 EOAD, 20 LOAD) using transcriptomic signatures to identify patient clusters and disease endotypes. Interestingly, although the clusters showed distinct combinations and severity of endotypes, each patient cluster contained both EOAD and LOAD cases, suggesting that AAO may not directly correlate with the identity and severity of AD endotypes.
2022-10-12 | GSE203206 | GEO
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.
2015-04-01 | E-GEOD-67333 | biostudies-arrayexpress
Project description:Evidence suggests that extracellular vesicles (EVs) act as mediators and biomarkers of neurodegenerative diseases. Two distinct forms of Alzheimer Disease (AD) are known: a late-onset sporadic form (SAD) and an early-onset familial form (FAD). This project aims to characterize and compare the protein profile of systemic EVs from postmortem SAD and FAD patients and compared them to postmortem controls. We used LC-MS/MS label-free analysis.
2021-09-09 | PXD021718 | Pride