基于机器学习的新型阿诺基斯相关诊断生物标志物用于大动脉剖析
Hanyi Zhang1,2,3,4, Zhen Ouyang1,2,4, Tianji Zhou5
1Department of Dermatology, Hunan Key Laboratory of Skin Cancer and Psoriasis, Hunan Engineering Research Center of Skin Health and Disease, Xiangya Clinical Research Center for Cancer Immunotherapy, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, China.
Scientific reports
|December 29, 2024
概括
大动脉剖析 (AD) 的病原性仍然不清楚. 这项研究使用生物信息学识别了三种与阿诺基斯相关的基因 (ARG),表明它们在阿尔茨海默病的诊断和发病过程中通过氧化应激等途径发挥了潜在的作用.
科学领域:
- 心血管生物学 心血管生物学
- 细胞死亡机制 细胞死亡机制
- 生物信息学是一种生物信息学.
背景情况:
- 大动脉解剖 (AD) 是一种危及生命的心血管疾病,其病因不明确,预后不佳.
- 固定性细胞死亡 (Anoikis) 是一种在细胞外矩阵脱离后的编程细胞死亡形式,越来越多地被研究,特别是在瘤学中.
- 了解AD的发病因子对于及时诊断和改善患者结果至关重要.
研究的目的:
- 为了确定大动脉剖析 (AD) 诊断的潜在分子标记.
- 探索阿诺基斯相关基因 (ARG) 在阿尔茨海默病的发病过程中的作用.
- 研究可能将ARG与AD联系在一起的途径,例如氧化应激和炎症.
主要方法:
- 生物信息学分析整合了基因本体学 (GO) 和基因和基因组的京都百科全书 (KEGG) 数据库.
- 机器学习算法用于识别候选无基因相关基因 (ARG).
- 使用接收器操作特征 (ROC) 曲线,基因组丰富分析 (GSEA) 和基因组变异分析 (GSVA) 验证选定的ARG (TP53,TUBB3).
主要成果:
- 鉴定了与大动脉剖析 (AD) 相关的三个关键的阿诺基斯相关基因 (ARG).
- 验证了TP53和TUBB3作为AD的显著潜在生物标志物.
- 假设ARG在AD病变发生过程中通过包括氧化应激,炎症反应和细胞外矩阵重塑在内的途径参与ARG.
结论:
- 与阿诺基斯相关的基因 (ARG) 代表了大动脉剖析 (AD) 的潜在诊断因素.
- 对ARG的进一步研究可以阐明AD的病原体,并导致新的诊断策略.
- 针对氧化应激和炎症等途径可能与AD管理有关.
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