一种新的机器学习衍生的四基因签名预测STEMI和STEMI后心力衰竭
Jialu Yao1, Yujia Zhou2, Zhichao Yao3
1Department of Cardiology, the First Affiliated Hospital of Soochow University, Suzhou, China; Department of Cardiology, Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University, Institute for Hypertension of Soochow University, Jiangsu Engineering Laboratory of Novel Functional Polymeric Materials of Soochow University, Suzhou, Jiangsu Province, China.
Biomolecules & biomedicine
|September 16, 2023
概括
使用单细胞的新四基因测定可以预测ST升高心肌梗塞 (STEMI) 和心力衰竭 (HF) 风险. 这一发现有助于个性化的冠状动脉疾病管理,并改善患者的治疗结果.
科学领域:
- 心血管医学 心血管医学
- 基因组学就是基因组学.
- 生物标志物发现发现
背景情况:
- 与ST升高心肌梗塞 (STEMI) 和STEMI后心力衰竭 (HF) 相关的高死亡率和发病率强调需要有效的冠状动脉疾病 (CAD) 风险分层.
- 目前的风险评估方法需要提高临床应用的特异性和方便性.
研究的目的:
- 开发一种基于单细胞的新型基因试验,用于预测STEMI和STEMI后高血压.
- 为了确定一个特定的基因面板,能够准确地对CAD患者进行风险分层.
主要方法:
- 1,956个单细胞表达特征和来自多个来源的临床数据的整合.
- 应用权重基因共同表达网络分析 (WGCNA) 和差异分析来识别与STEMI相关的基因.
- 使用已识别的基因对机器学习模型 (决策树,支持矢量机,随机森林) 的训练和验证.
主要成果:
- 建立了一个由四个基因组成的小组 (HLA-J,CFP,STX11和NFYC),证明了优异的歧视性表现.
- 基因小组在区分STEMI和HF方面实现了0.86或更高的曲线下面面积 (AUC).
- 基因组丰富分析 (GSEA) 证实了四个基因小组与心脏病变和心血管疾病途径的关联.
结论:
- 一种经过验证的单细胞四基因测定可以准确预测STEMI和HF的风险.
- 这种预测模型促进了最佳的风险分层和个人化CAD管理.
- 开发的试验有望改善心血管疾病患者个体结果.
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