Exploring the Key Genes and Identification of Potential Diagnosis Biomarkers in Alzheimer's Disease Using Bioinformatics Analysis

被引:25
|
作者
Yu, Wuhan [1 ]
Yu, Weihua [2 ]
Yang, Yan [3 ]
Lu, Yang [1 ]
机构
[1] Chongqing Med Univ, Dept Geriatr, Affiliated Hosp 1, Chongqing, Peoples R China
[2] Chongqing Med Univ, Inst Neurosci, Chongqing, Peoples R China
[3] Chongqing Univ, Coll Elect Engn, State Key Lab Power Transmiss Equipment & Syst Se, Chongqing, Peoples R China
来源
关键词
Alzheimer's disease; diagnosis biomarkers; hub genes; integrative analysis; aging; MISSENSE MUTATIONS; EXPRESSION; ASSOCIATION; HIPPOCAMPUS; MECHANISMS; DISORDERS; DEMENTIA;
D O I
10.3389/fnagi.2021.602781
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Background Alzheimer's disease (AD) is one of the major threats of the twenty-first century and lacks available therapy. Identification of novel molecular markers for diagnosis and treatment of AD is urgently demanded, and genetic biomarkers show potential prospects. Method We identify and intersected differentially expressed genes (DEGs) from five microarray datasets to detect consensus DEGs. Based on these DEGs, we conducted Gene Ontology (GO), performed the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, constructed a protein-protein interaction (PPI) network, and utilized Cytoscape to identify hub genes. The least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify potential diagnostic biomarkers. Gene set enrichment analysis (GSEA) was performed to investigate the biological functions of the key genes. Result We identified 608 consensus DEGs, several dysregulated pathways, and 18 hub genes. Sixteen hub genes dysregulated as AD progressed. The diagnostic model of 35 genes was constructed, which has a high area under the curve (AUC) value in both the validation dataset and combined dataset (AUC = 0.992 and AUC = 0.985, respectively). The model can also differentiate mild cognitive impairment and AD patients from controls in two blood datasets. Brain-derived neurotrophic factor (BDNF) and WW domain-containing transcription regulator protein 1 (WWTR1), which are associated with the Braak stage, A beta 42 levels, and beta-secretase activity, were identified as critical genes of AD. Conclusion Our study identified 16 hub genes correlated to the neuropathological stage and 35 potential biomarkers for the diagnosis of AD. WWTR1 were identified as candidate genes for future studies. This study deepens our understanding of the transcriptomic and functional features and provides new potential diagnostic biomarkers and therapeutic targets for AD.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] Identification of potential key molecular biomarkers in lung adenocarcinoma by bioinformatics analysis
    Guo, Pengyi
    Xu, Tinghui
    Jiang, Ying
    Shen, Wenming
    TRANSLATIONAL CANCER RESEARCH, 2022, 11 (01) : 227 - 241
  • [22] Integrated bioinformatics analysis for exploring potential biomarkers related to Parkinson's disease progression
    Huang, Zhenchao
    Song, En'peng
    Chen, Zhijie
    Yu, Peng
    Chen, Weiwen
    Lin, Huiqin
    BMC MEDICAL GENOMICS, 2024, 17 (01)
  • [23] Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through RNA sequencing analysis
    Daichi Shigemizu
    Taiki Mori
    Shintaro Akiyama
    Sayuri Higaki
    Hiroshi Watanabe
    Takashi Sakurai
    Shumpei Niida
    Kouichi Ozaki
    Alzheimer's Research & Therapy, 12
  • [24] Identification of potential blood biomarkers for early diagnosis of Alzheimer's disease through RNA sequencing analysis
    Shigemizu, Daichi
    Mori, Taiki
    Akiyama, Shintaro
    Higaki, Sayuri
    Watanabe, Hiroshi
    Sakurai, Takashi
    Niida, Shumpei
    Ozaki, Kouichi
    ALZHEIMERS RESEARCH & THERAPY, 2020, 12 (01)
  • [25] Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through immune landscape analysis
    Daichi Shigemizu
    Shintaro Akiyama
    Risa Mitsumori
    Shumpei Niida
    Kouichi Ozaki
    npj Aging, 8
  • [26] Identification of potential blood biomarkers for early diagnosis of Alzheimer's disease through immune landscape analysis
    Shigemizu, Daichi
    Akiyama, Shintaro
    Mitsumori, Risa
    Niida, Shumpei
    Ozaki, Kouichi
    NPJ AGING, 2022, 8 (01):
  • [27] Identification of immune-infiltrated hub genes as potential biomarkers of Moyamoya disease by bioinformatics analysis
    Jin, Fa
    Duan, Chuanzhi
    ORPHANET JOURNAL OF RARE DISEASES, 2022, 17 (01)
  • [28] Identification of immune-infiltrated hub genes as potential biomarkers of Moyamoya disease by bioinformatics analysis
    Fa Jin
    Chuanzhi Duan
    Orphanet Journal of Rare Diseases, 17
  • [29] Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics
    Fu-peng Ding
    Jia-yi Tian
    Jing Wu
    Dong-feng Han
    Ding Zhao
    Cancer Cell International, 21
  • [30] Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics
    Ding, Fu-peng
    Tian, Jia-yi
    Wu, Jing
    Han, Dong-feng
    Zhao, Ding
    CANCER CELL INTERNATIONAL, 2021, 21 (01)