ArticleLipids in health and disease2023
Identification of key lipid metabolism-related genes in Alzheimer's disease.
Article in Lipids in health and disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 12 citations in OpenAlex.
- Mitochondrial Hsp60/10 Client Protein Decline Reveals Braak/Tau- and Cognition-Linked Proteostasis Vulnerabilities in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2026Article
- Integrating epidemiological and transcriptomic data reveals novel lipid metabolic drivers of obstructive sleep apnea.Nutrition & metabolism · 2026Article
- Unfolding Immune Dysregulation in COPD: Identification of a Three-Gene Signature and Functional Validation ofInternational journal of molecular sciences · 2026Article
- Structural basis for the catalytic mechanism of human lipid phosphate phosphatases.Nature chemical biology · 2026Article
- DEVELOPMENT AND APPLICATION OF BRAIN TISSUE BASED MULTI-OMICS PROFILE SCORES FOR ALZHEIMER'S DISEASE.Research square · 2026Article
- Genomic and Transcriptomic Approaches Advance the Diagnosis and Prognosis of Neurodegenerative Diseases.Genes · 2025Review
- Integrating causal human genetics andFrontiers in molecular biosciences · 2025Article
- Bioinformatics Analysis of Lactylation-related Biomarkers and Potential Pathogenesis Mechanisms in Age-related Macular Degeneration.Current genomics · 2025Article
- Exploring the Potential Role of Oligodendrocyte-Associated PIP4K2A in Alzheimer's Disease Complicated with Type 2 Diabetes Mellitus via Multi-Omic Analysis.International journal of molecular sciences · 2024Article
- New insights in lipid metabolism: potential therapeutic targets for the treatment of Alzheimer's disease.Frontiers in neuroscience · 2024Review
- Identification of potential short-chain fatty acid biomarkers in Alzheimer's disease through bioinformatics analysis.Journal of Alzheimer's disease reportsArticle
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundAlzheimer's disease (AD) represents profound degenerative conditions of the brain that cause significant deterioration in memory and cognitive function. Despite extensive research on the significant contribution of lipid metabolism to AD progression, the precise mechanisms remain incompletely understood. Hence, this study aimed to identify key differentially expressed lipid metabolism-related genes (DELMRGs) in AD progression.
methodsComprehensive analyses were performed to determine key DELMRGs in AD compared to controls in GSE122063 dataset from Gene Expression Omnibus. Additionally, the ssGSEA algorithm was utilized for estimating immune cell levels. Subsequently, correlations between key DELMRGs and each immune cell were calculated specifically in AD samples. The key DELMRGs expression levels were validated via two external datasets. Furthermore, gene set enrichment analysis (GSEA) was utilized for deriving associated pathways of key DELMRGs. Additionally, miRNA-TF regulatory networks of the key DELMRGs were constructed using the miRDB, NetworkAnalyst 3.0, and Cytoscape software. Finally, based on key DELMRGs, AD samples were further segmented into two subclusters via consensus clustering, and immune cell patterns and pathway differences between the two subclusters were examined.
resultsSeventy up-regulated and 100 down-regulated DELMRGs were identified. Subsequently, three key DELMRGs (DLD, PLPP2, and PLAAT4) were determined utilizing three algorithms [(i) LASSO, (ii) SVM-RFE, and (iii) random forest]. Specifically, PLPP2 and PLAAT4 were up-regulated, while DLD exhibited downregulation in AD cerebral cortex tissue. This was validated in two separate external datasets (GSE132903 and GSE33000). The AD group exhibited significantly altered immune cell composition compared to controls. In addition, GSEA identified various pathways commonly associated with three key DELMRGs. Moreover, the regulatory network of miRNA-TF for key DELMRGs was established. Finally, significant differences in immune cell levels and several pathways were identified between the two subclusters.
conclusionThis study identified DLD, PLPP2, and PLAAT4 as key DELMRGs in AD progression, providing novel insights for AD prevention/treatment.
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