ArticleJournal of Alzheimer's disease & Parkinsonism2020
Identification of Dysregulated Genes for Late-Onset Alzheimer's Disease Using Gene Expression Data in Brain.
Article in Journal of Alzheimer's disease & Parkinsonism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Alcohol use disorder is associated with DNA methylation-based shortening of telomere length and regulated by TESPA1: implications for aging.Molecular psychiatry · 2022Pooled it
- Allele-specific splicing modulates protein isoforms and Alzheimer's risk.bioRxiv : the preprint server for biology · 2026Article
- LimROTS: a hybrid method integrating empirical Bayes and reproducibility-optimized statistics for robust differential expression analysis.Bioinformatics (Oxford, England) · 2025Article
- Discovery and validation of biomarkers for Parkinson's disease from human cerebrospinal fluid using mass spectrometry-based proteomics analysis.EBioMedicine · 2025Article
- Deficits of Alzheimer's Disease Neuropsychological Architecture Correlate with Specific Exosomal mRNA Expression: Evidence of a Continuum?International journal of molecular sciences · 2025Article
- Sex-specific genetic architecture of late-life memory performance.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Lower expression ofJournal of Alzheimer's disease reportsArticle
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundAlzheimer's Disease (AD) is a neurodegenerative complex brain disease that represents a public health concern. AD is considered the fifth leading cause of death in Americans who are older than 65 years which prioritizes the importance of understanding the etiology of AD in its early stages before the onset of symptoms. This study attempted to further understand Alzheimer's disease (AD) etiology by investigating the dysregulated genes using gene expression data from multiple brain regions.
methodsA linear mixed-effects model for differential gene expression analysis was used in a sample of 15 AD and 30 control subjects, each with data from four different brain regions, in order to deal with the hierarchical multilevel data. Post-hoc Gene Ontology and pathway enrichment analyses provided insights on the biological implications in AD progression. Supervised machine learning algorithms were used to assess the discriminative power of the top 10 candidate genes in distinguishing between the two groups.
resultsEnrichment analyses revealed biological processes and pathways that are related to structural constituents and organization of the axons and synapses. These biological processes and pathways imply dysfunctional axon and synaptic transmission between neuronal cells in AD. Random Forest classification algorithm gave the best accuracy on the test data with F1-score of 0.88.
conclusionThe differentially expressed genes were associated with axon and synaptic transmissions which affect the neuronal connectivity in cognitive systems involved in AD pathophysiology. These genes may open ways to explore new effective treatments and early diagnosis before the onset of clinical symptoms.
Indexed as
Identifiers
33282526PMC7717689W3112476477What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.