高级检索
当前位置: 首页 > 详情页

Unveiling the mitophagy puzzle in non-alcoholic fatty liver disease (NAFLD): Six hub genes for early diagnosis and immune modulatory roles

文献详情

资源类型:
WOS体系:

收录情况: ◇ SCIE

机构: [1]Soochow Univ, Peoples Hosp Changzhou 1, Affiliated Hosp 3, Dept Internal Med, Changzhou, Jiangsu, Peoples R China [2]Soochow Univ, Peoples Hosp Changzhou 1, Affiliated Hosp 3, Dept Gastroenterol, Changzhou, Jiangsu, Peoples R China [3]Kunming Univ Sci & Technol, 926th Hosp Joint Logist Support Force PLA, Affiliated Hosp, Dept Cardiol, Kaiyuan, Yunnan, Peoples R China
出处:

关键词: Non-alcoholic fatty liver disease Mitophagy Diagnostic model Immune infiltration Bioinformatics analysis

摘要:
Background: Non-alcoholic fatty liver disease (NAFLD) stands as a predominant chronic liver ailment globally, yet its pathogenesis remains elusive. This study aims to identify Hub mitophagyrelated genes (MRGs), and explore the underlying pathological mechanisms through which these hub genes regulate NAFLD. Methods: A total of 3 datasets were acquired from the GEO database and integrated to identify differentially expressed genes (DEGs) in NAFLD and perform Gene Set Enrichment Analysis (GSEA). By intersecting DEGs with MRGs, mitophagy-related differentially expressed genes (MRDEGs) were obtained. Then, hub MRGs with diagnostic biomarker capability for NAFLD were screened and a diagnostic prediction model was constructed and assessed using Nomogram, Decision Curve Analysis (DCA), and ROC curves. Functional enrichment analysis was conducted on the identified hub genes to explore their biological significance. Additionally, regulatory networks were constructed using databases. NAFLD was stratified into high and low -risk groups based on the Riskscore from the diagnostic prediction model. Furthermore, single -sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithms were employed to analyze immune cell infiltration patterns and the relationship between Hub MRGs and immune cells. Results: The integrated dataset comprised 122 NAFLD samples and 31 control samples. After screening, 18 MRDEGs were identified. Subsequently, six hub MRGs (NR4A1, PPP2R2A, P4HA1, TUBB6, DUSP1, NAMPT) with diagnostic potential were selected through WGCNA, logistic regression, SVM, RF, and LASSO models, all significantly downregulated in NAFLD samples compared to the control group. A diagnostic prediction model based on these six genes demonstrated robust predictive performance. Functional enrichment analysis of the six hub genes revealed involvement in processes such as protein phosphorylation or dephosphorylation. Correlation analysis demonstrated a significant association between hub MRGs and infiltrating immune cells. Conclusion: We identified six hub MRGs in NAFLD and constructed a diagnostic prediction model based on these six genes, applicable for early NAFLD diagnosis. These genes may participate in regulating NAFLD progression through the modulation of mitophagy and immune activation. Our findings may contribute to subsequent clinical and basic research on NAFLD.

语种:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2024]版:
最新[2023]版:
大类 | 3 区 综合性期刊
小类 | 3 区 综合性期刊
JCR分区:
出版当年[2023]版:
Q1 MULTIDISCIPLINARY SCIENCES
最新[2023]版:
Q1 MULTIDISCIPLINARY SCIENCES

影响因子: 最新[2023版] 最新五年平均 出版当年[2023版] 出版当年五年平均 出版前一年[2022版]

第一作者:
第一作者机构: [1]Soochow Univ, Peoples Hosp Changzhou 1, Affiliated Hosp 3, Dept Internal Med, Changzhou, Jiangsu, Peoples R China
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:82325 今日访问量:0 总访问量:681 更新日期:2025-01-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 云南省第一人民医院 技术支持:重庆聚合科技有限公司 地址:云南省昆明市西山区金碧路157号