Identification of hub genes significantly linked to tuberous sclerosis related-epilepsy and lipid metabolism via bioinformatics analysis

被引:2
|
作者
Wang, Weiliang [1 ]
Ren, Yinghao [2 ]
Hou, Weiliang [3 ,4 ]
Zhang, Xiaobin [1 ]
Yang, Chenglong [5 ]
An, Weimiao [1 ]
Fei, Xu [6 ]
Wang, Fengpeng [1 ]
机构
[1] Fujian Med Univ, Xiamen Humanity Hosp, Epilepsy Ctr, Xiamen, Fujian, Peoples R China
[2] Fujian Med Univ, Dept Dermatol, Xiamen Humanity Hosp, Xiamen, Fujian, Peoples R China
[3] Fudan Univ, Huashan Hosp, Minist Educ,Shanghai Med Coll,Frontiers Ctr Brain, Inst Brain Sci,Dept Neurosurg,State Key Lab Med Ne, Shanghai, Peoples R China
[4] Fudan Univ, Inst Brain Sci, Shanghai, Peoples R China
[5] Harbin Med Univ, Dept Neurosurg, Canc Hosp, Harbin, Heilongjiang, Peoples R China
[6] Harbin Med Univ, Coll Bioinformat & Sci Technol, Dept Pharmacogen, Harbin, Peoples R China
来源
FRONTIERS IN NEUROLOGY | 2024年 / 15卷
关键词
tuberou sclerosis complex; epilepsy; lipid metabolism; bioinformatics analysis; biomarkers;
D O I
10.3389/fneur.2024.1354062
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background Tuberous sclerosis complex (TSC) is one of the most common genetic causes of epilepsy. Identifying differentially expressed lipid metabolism related genes (DELMRGs) is crucial for guiding treatment decisions. Methods We acquired tuberous sclerosis related epilepsy (TSE) datasets, GSE16969 and GSE62019. Differential expression analysis identified 1,421 differentially expressed genes (DEGs). Intersecting these with lipid metabolism related genes (LMRGs) yielded 103 DELMRGs. DELMRGs underwent enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and AUCell analysis. Results In TSE datasets, 103 DELMRGs were identified. Four diagnostic biomarkers (ALOX12B, CBS, CPT1C, and DAGLB) showed high accuracy for epilepsy diagnosis, with an AUC value of 0.9592. Significant differences (p < 0.05) in Plasma cells, T cells regulatory (Tregs), and Macrophages M2 were observed between diagnostic groups. Microglia cells were highly correlated with lipid metabolism functions. Conclusions Our research unveiled potential DELMRGs (ALOX12B, CBS, CPT1C and DAGLB) in TSE, which may provide new ideas for studying the psathogenesis of epilepsy.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] Identification of hub genes, pathways, and related transcription factors in systemic lupus erythematosus A preliminary bioinformatics analysis
    Wang, Yanfeng
    Ma, Qian
    Huo, Zhenghao
    MEDICINE, 2021, 100 (25) : E26499
  • [42] Identification of potential hub genes related to the progression and prognosis of hepatocellular carcinoma through integrated bioinformatics analysis
    Song, Xiudao
    Du, Rao
    Gui, Huan
    Zhou, Mi
    Zhong, Wen
    Mao, Chenmei
    Ma, Jin
    ONCOLOGY REPORTS, 2020, 43 (01) : 133 - 146
  • [43] Identification of mitophagy and ferroptosis-related hub genes associated with intracerebral haemorrhage through bioinformatics analysis
    Wang, Yan
    Wang, Rufeng
    Zhu, Jianzhong
    Chen, Ling
    ANNALS OF HUMAN BIOLOGY, 2024, 51 (01)
  • [44] Identification of hub genes and small molecule therapeutic drugs related to breast cancer with comprehensive bioinformatics analysis
    Hao, Mingqian
    Liu, Wencong
    Ding, Chuanbo
    Peng, Xiaojuan
    Zhang, Yue
    Chen, Huiying
    Dong, Ling
    Liu, Xinglong
    Zhao, Yingchun
    Chen, Xueyan
    Khatoon, Sadia
    Zheng, Yinan
    PEERJ, 2020, 8
  • [45] Bioinformatics analysis and identification of hub genes and immune-related molecular mechanisms in chronic myeloid leukemia
    Yao, Fangyi
    Zhao, Cui
    Zhong, Fangmin
    Qin, Tingyu
    Li, Shuqi
    Liu, Jing
    Huang, Bo
    Wang, Xiaozhong
    PEERJ, 2022, 10
  • [46] Identification of immune-related hub genes and potential molecular mechanisms involved in COVID-19 via integrated bioinformatics analysis
    Zhu, Rui
    Zhao, Yaping
    Yin, Hui
    Shu, Linfeng
    Ma, Yuhang
    Tao, Yingli
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [47] Identification and analysis of lipid metabolism-related genes in allergic rhinitis
    Tao, Qilei
    Zhu, Yajing
    Wang, Tianyu
    Deng, Yue
    Liu, Huanhai
    Wu, Jian
    LIPIDS IN HEALTH AND DISEASE, 2023, 22 (01)
  • [48] Identification of Potential Hub Genes Related to Aflatoxin B1, Liver Fibrosis and Hepatocellular Carcinoma via Integrated Bioinformatics Analysis
    Hamdy, Hayam
    Yang, Yi
    Cheng, Cheng
    Liu, Qizhan
    BIOLOGY-BASEL, 2023, 12 (02):
  • [49] Identification of potential key lipid metabolism-related genes involved in tubular injury in diabetic kidney disease by bioinformatics analysis
    Fan, Yuanshuo
    He, Juan
    Shi, Lixin
    Zhang, Miao
    Chen, Ye
    Xu, Lifen
    Han, Na
    Jiang, Yuecheng
    ACTA DIABETOLOGICA, 2024, 61 (08) : 1053 - 1068
  • [50] Identification of the Hub Genes Associated with the Prognosis of Ovarian Cancer Patients via Integrated Bioinformatics Analysis and Experimental Validation
    Zhao, Yuzi
    Pi, Jie
    Liu, Lihua
    Yan, Wenjie
    Ma, Shufang
    Hong, Li
    CANCER MANAGEMENT AND RESEARCH, 2021, 13 : 707 - 721