Identification of key lipid metabolism-related genes in Alzheimer's disease

被引:3
|
作者
Zeng, Youjie [1 ]
Cao, Si [1 ]
Li, Nannan [2 ]
Tang, Juan [2 ]
Lin, Guoxin [1 ]
机构
[1] Cent South Univ, Xiangya Hosp 3, Dept Anesthesiol, Changsha 410013, Hunan, Peoples R China
[2] Cent South Univ, Xiangya Hosp 3, Dept Nephrol, Changsha 410013, Hunan, Peoples R China
关键词
Alzheimer's disease; Bioinformatics; Biomarkers; Lipid metabolism; Differentially expressed genes; Differential expression analysis; Hub genes; Immune cell infiltration; Key genes; CEREBROSPINAL-FLUID; DEHYDROGENASE; BRAIN; ACTIVATION; DATABASE; BLOOD; RISK;
D O I
10.1186/s12944-023-01918-9
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Background Alzheimer'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. Methods Comprehensive 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. Results Seventy 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. Conclusion This study identified DLD, PLPP2, and PLAAT4 as key DELMRGs in AD progression, providing novel insights for AD prevention/treatment.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] Lipid metabolism in Alzheimer's disease
    Liu, Qiang
    Zhang, Juan
    NEUROSCIENCE BULLETIN, 2014, 30 (02) : 331 - 345
  • [42] Lipid metabolism in Alzheimer’s disease
    Qiang Liu
    Juan Zhang
    Neuroscience Bulletin, 2014, 30 : 331 - 345
  • [43] Analysis of immune-related key genes in Alzheimer's disease
    Wu, You
    Liang, Shunli
    Zhu, Hong
    Zhu, Yaping
    BIOENGINEERED, 2021, 12 (02) : 9610 - 9624
  • [44] Modulatory Effects of Fingolimod (FTY720) on the Expression of Sphingolipid Metabolism-Related Genes in an Animal Model of Alzheimer’s Disease
    Henryk Jęśko
    Przemysław L. Wencel
    Walter J. Lukiw
    Robert P. Strosznajder
    Molecular Neurobiology, 2019, 56 : 174 - 185
  • [45] Modulatory Effects of Fingolimod (FTY720) on the Expression of Sphingolipid Metabolism-Related Genes in an Animal Model of Alzheimer's Disease
    Jesko, Henryk
    Wencel, Przemyslaw L.
    Lukiw, Walter J.
    Strosznajder, Robert P.
    MOLECULAR NEUROBIOLOGY, 2019, 56 (01) : 174 - 185
  • [46] Identification of lipid metabolism-related biomarkers for diagnosis and molecular classification of atherosclerosis
    Pan, Xue
    Liu, Jifeng
    Zhong, Lei
    Zhang, Yunshu
    Liu, Chaosheng
    Gao, Jing
    Pang, Min
    LIPIDS IN HEALTH AND DISEASE, 2023, 22 (01)
  • [47] Identification of lipid metabolism-related biomarkers for diagnosis and molecular classification of atherosclerosis
    Xue Pan
    Jifeng Liu
    Lei Zhong
    Yunshu Zhang
    Chaosheng Liu
    Jing Gao
    Min Pang
    Lipids in Health and Disease, 22
  • [48] Identification of Featured Metabolism-Related Genes in Patients with Acute Myocardial Infarction
    Xie, Hang
    Zha, Enfa
    Zhang, Yushun
    DISEASE MARKERS, 2020, 2020
  • [49] Identification of metabolism-related subtypes and feature genes of pre-eclampsia
    Xiong, Zhihui
    Guan, Hailian
    Pei, Shuping
    Wang, Caijiao
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [50] Identification of a prognostic signature of nine metabolism-related genes for hepatocellular carcinoma
    Tang, Chaozhi
    Ma, Jiakang
    Liu, Xiuli
    Liu, Zhengchun
    PEERJ, 2020, 8