ArticleFrontiers in neuroscience2019
Meta-Analysis of Gene Expression and Identification of Biological Regulatory Mechanisms in Alzheimer's Disease.
Article in Frontiers in neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 6 of them syntheses that pooled it.
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Who cites it
37 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Meta-Analysis of Transcriptomic Studies of Blood and Six Brain Regions Identifies a Consensus of 15 Cross-Tissue Mechanisms in Alzheimer's Disease and Suggests an Origin of Cross-Study Heterogeneity.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2025Pooled it
- Transcriptomics Meta-Analysis Reveals Phagosome and Innate Immune System Dysfunction as Potential Mechanisms in the Cortex of Alzheimer's Disease Mouse Strains.Journal of molecular neuroscience : MN · 2023Pooled it
- Alzheimer's disease large-scale gene expression portrait identifies exercise as the top theoretical treatment.Scientific reports · 2022Pooled it
- Differentially Expressed miRNAs in Age-Related Neurodegenerative Diseases: A Meta-Analysis.Genes · 2022Pooled it
- Genetically regulated expression in late-onset Alzheimer's disease implicates risk genes within known and novel loci.Translational psychiatry · 2021Pooled it
- Meta-Analysis of Gene Expression Changes in the Blood of Patients with Mild Cognitive Impairment and Alzheimer's Disease Dementia.International journal of molecular sciences · 2019Pooled it
- Cellular transcriptomic signatures underpinning the heterogeneity of depression in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Sex- and brain region-specific gene expression in Alzheimer's disease.Journal of Alzheimer's disease : JAD · 2026Article
- Leveraging multiomic approaches to elucidate mechanisms of heterogeneity in Alzheimer's disease: Neuropsychiatric symptoms, co-pathologies, and sex differences.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Development and Assessment of a Prediction Model for Alzheimer's Disease Diagnosis Based on Thermoregulation-Related Genes.Combinatorial chemistry & high throughput screening · 2025Article
- A Comprehensive Review of Membrane Transporters and MicroRNA Regulation in Alzheimer's Disease.Molecular neurobiology · 2024Review
- Steroid inhibited Serpina3n expression which was positively correlated with the degrees of spinal cord injury.Heliyon · 2024Article
- A semi-supervised approach for the integration of multi-omics data based on transformer multi-head self-attention mechanism and graph convolutional networks.BMC genomics · 2024Article
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- A review and analysis of key biomarkers in Alzheimer's disease.Frontiers in neuroscience · 2024Review
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- A Comprehensive Bioinformatics Approach to Identify Molecular Signatures and Key Pathways for the Huntington Disease.Bioinformatics and biology insights · 2023Article
- Characterization of gene expression patterns in mild cognitive impairment using a transcriptomics approach and neuroimaging endophenotypes.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2022Article
- Differential Gene Expression and DNA Methylation in the Risk of Depression in LOAD Patients.Biomolecules · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's disease (AD), also known as senile dementia, is a progressive neurodegenerative disease. The etiology and pathogenesis of AD have not yet been elucidated. We examined common differentially expressed genes (DEGs) from different AD tissue microarray datasets by meta-analysis and screened the AD-associated genes from the common DEGs using GCBI. Then we studied the gene expression network using the STRING database and identified the hub genes using Cytoscape. Furthermore, we analyzed the microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and single nucleotide polymorphisms (SNPs) associated with the AD-associated genes, and then identified feed-forward loops. Finally, we performed SNP analysis of the AD-associated genes. Our results identified 207 common DEGs, of which 57 have previously been reported to be associated with AD. The common DEG expression network identified eight hub genes, all of which were previously known to be associated with AD. Further study of the regulatory miRNAs associated with the AD-associated genes and other genes specific to neurodegenerative diseases revealed 65 AD-associated miRNAs. Analysis of the miRNA associated transcription factor-miRNA-gene-gene associated TF (mTF-miRNA-gene-gTF) network around the AD-associated genes revealed 131 feed-forward loops (FFLs). Among them, one important FFL was found between the gene
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