Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Characterization of Global DNA Methylome in Mild Cognitive Impairment and Alzheimer's Disease

ABSTRACT: Genome-wide profiling of DNA methylation in blood leukocytes from Chinese patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD). The Illumina Infinium MethylationEPIC BeadChip array (850K chip) was used to detect DNA methylation profiles throughout approximately 850,000 CpG sites in peripheral blood white cells of MCI- and AD-affected Chinese patients, as well as cognitively healthy controls. All samples included 20 Chinese patients with MCI, 20 Chinese patients with AD, and 20 cognitively healthy controls.

ORGANISM(S): Homo sapiens

PROVIDER: GSE208623 | GEO | 2023/09/11

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

RNA sequencing of AD, MCI and control OM cells

Project description:Total RNA sequencing of cultured OM cells derived from patients with Alzheimer's disease (AD), individuals with mild cognitive impairment (MCI) and cognitively healthy controls.

| EGAS00001006195 | EGA

c1524d4c-cf60-4487-92bf-8984a10c423f - samples

| EGAD00001008707 | EGA

7a6baa50-bfb2-41f2-afff-2121a1bc19d6 - samples

Project description:Total RNA sequencing of cultured ONS cells derived from patients with Alzheimer's disease (AD), individuals with mild cognitive impairment (MCI) and cognitively healthy controls.

| EGAD00001009395 | EGA

RNA-seq of human plasma microRNAs in Alzheimer Disease

Project description:MicroRNAs (miRNAs) could play an important role as potential Alzheimer Disease (AD) biomarkers. Plasma samples were collected from participants: Mild cognitive impairment (MCI) due to AD patients (n= 20), preclinical AD patients (n= 8) and healthy controls (n= 20). Then, small RNA sequencing analysis, followed by miRNA differential expression analysis comparing different methods (DESeq2, edgeR, NOISeq) were carried out.

2022-05-08 | E-MTAB-11103 | biostudies-arrayexpress

Mitochondrial RNA in Alzheimer’s Disease Circulating Extracellular Vesicles

Project description:Alzheimer's disease (AD) is the most common type of dementia. Extracellular amyloid β (Aβ) plaques and intracellular Tau-containing neurofibrillary tangles are major AD lesions that identify Alzheimer’s pathology and to neuronal loss. However, given that these structures are also seen in cognitively normal persons (healthy controls, HC) and in persons who have mild cognitive impairment (MCI), extensive efforts have been undertaken to identify other diagnostic or prognostic indicators. Here, we characterized the RNA contents of extracellular vesicles (EVs) in the plasma of age-matched individuals who are healthy or have MCI or AD. Using RNA sequencing analysis, we found that mitochondrial (mt)RNAs, including MT-ND1 through MT-ND6 and other protein-coding and noncoding mtRNAs, were strikingly elevated in MCI- and AD-associated plasma EVs compared with healthy control EVs. In cultured cells derived from astrocytes, microglia, and neurons, exposure to the toxic conditions in the AD environment (Aβ fibers and H2O2), EVs contained mitochondrial structures (as detected by electron microscopy) as well as mitochondrial RNAs. We propose that in the MCI and AD brain environment, toxicity causing mitochondrial damage results in the packaging of mitochondrial components for export in EVs, and further propose that mitochondrial RNAs in plasma EVs are robust diagnostic and prognostic markers in AD.

2020-12-15 | GSE153881 | GEO

Prognosis prediction model for Alzheimer’s disease conversion from mild cognitive impairment by integrative analysis of multi-omics data

Project description:Mild cognitive impairment (MCI) is a clinical precursor of Alzheimer’s disease (AD). Many MCI subjects convert to AD, although others remain stable as MCI or sometimes return to cognitive normal. Currently, there are no curative treatments for patients who are already in AD, and therefore biomarkers for early detection of high risk MCI-to-AD conversion subjects are rapidly required. Here, we investigated potential biomarkers from blood-based miRNA (miR) expression profiles and genomic data of 197 Japanese MCI patients. Using the candidate biomarkers, we constructed a prognosis prediction model based on a Cox proportional hazard model. The final prediction model, composed of 24 miR-eQTLs (i.e. SNP-miRNA pairs) and three clinical factors (age, sex and ApoE ε4 carriers), successfully classified MCI patients into two groups, low and high, in terms of risk of MCI-to-AD conversion (log-rank trend test P=3.44×10^(-4)), and achieved a concordance index of 0.702 on an independent test set. Network-based meta-analysis using target genes of the miR-eQTLs further revealed four important hub genes (SHC1, FOXO1, GSK3B, and PTEN) associated with the pathogenesis of AD. Statistically significant differences were observed in PTEN expression between MCI and AD and SHC1 expression between cognitively normal elder subjects (CN) and AD when examining RNA-seq data from 610 blood samples (PTEN, P=0.023; SHC1, P=0.049), although FOXO1 and GSK3B showed low levels of expression in blood. Accurate prediction of MCI-to-AD conversion enables earlier appropriate intervention for those MCI patients and can lead to a reduction of MCI patients that convert to AD with high risk. We believe that further investigation with larger sample sizes will contribute to practical clinical use of our approach in MCI-to-AD conversion in the near future.

2020-11-11 | GSE150693 | GEO

Music compensates for altered gene expression in age-related cognitive disorders

Project description:Extensive literature has explored the beneficial effects of music in age-related cognitive disorders (ACD), but limited knowledge exists regarding its impact on gene expression. We analyzed transcriptomes of ACD patients and healthy controls, pre-post a music session (n=60), and main genes/pathways were compared to those dysregulated in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) as revealed by a multi-cohort study (n=1269 MCI/AD and controls). Music was associated with 2.3 times more whole-genome gene expression, particularly on neurodegeneration-related genes, in ACD than controls. Co-expressed gene-modules and pathways analysis demonstrated that music impacted autophagy, vesicle and endosome organization, biological processes commonly dysregulated in MCI/AD. Notably, the data indicated a strong negative correlation between musically-modified genes/pathways in ACD and those dysregulated in MCI/AD. These findings highlight the compensatory effect of music on genes/biological processes affected in MCI/AD, providing insights into the molecular mechanisms underlying the benefits of music on these disorders.

2023-10-26 | GSE239282 | GEO

RNA sequencing of AD, MCI and control ONS cells

Project description:We have generated human olfactory neurosphere-derived (ONS) cells from individuals with AD or mild cognitive impairment (MCI), and their cognitively healthy controls, and performed global RNA sequencing to determine gene expression changes in ONS cells.

| EGAS00001006594 | EGA

Transcriptomic predictors of rapid progression from mild cognitive impairment to Alzheimer's Disease

Project description:Background: Effective treatment for Alzheimer’s disease (AD) remains an unmet need. Thus, identifying patients with mild cognitive impairment (MCI) who are at high-risk of progressing to AD is crucial for early intervention. Methods: Blood-based transcriptomics analyses were performed using a longitudinal study cohort to compare progressive MCI (P-MCI, n=28), stable MCI (S-MCI, n=39), and AD patients (n=49). Statistical DESeq2 analysis and machine learning methods were employed to identify differentially expressed genes (DEGs) and develop prediction models. Results: We discovered a remarkable gender-specific difference in DEGs that distinguish P-MCI from S-MCI. Machine learning models achieved high accuracy in distinguishing P-MCI from S-MCI (AUC 0.93), AD from S-MCI (AUC 0.94), and AD from P-MCI (AUC 0.92). An 8-gene signature was identified for distinguishing P-MCI from S-MCI.

2024-11-30 | GSE282742 | GEO

Epigenome analysis of normal and ischemic stroke patients blood samples

Project description:Genome wide DNA methylation profiling of normal and ischemic stroke patients blood samples. The Illumina Infinium 850k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 850,000 CpGs in liquid. Samples included 3 healthy people blood samples, 3 ischemic stroke patients blood samples.

2022-09-28 | GSE197080 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data