基于机器学习的心力衰竭诊断特征基因和亚型的识别
Yanlong Zhang1, Yanming Fan1, Fei Cheng1
1Department of Cardiology, Xingtai People's Hospital, Xingtai, Hebei, China.
Frontiers in cardiovascular medicine
|April 29, 2025
概括
研究人员确定了四个基因 (FCN3,FREM1,MNS1和SMOC2) 作为早期心力衰竭 (HF) 检测的潜在生物标志物. 这一发现可能会为患有HF的人提供更个性化的治疗策略.
科学领域:
- 基因组学和生物信息学
- 心血管研究研究心血管研究
- 机器学习在医学中的应用
背景情况:
- 心力衰竭 (HF) 是一种复杂的疾病,对其遗传基础的理解有限.
- 转录组分析为早期HF检测和向治疗提供了潜力.
研究的目的:
- 使用转录基因数据识别心力衰竭的新型诊断基因.
- 探索HF亚型及其相关的免疫学特征.
- 为了研究已识别的高频率相关基因的泛癌相关性.
主要方法:
- 从基因表达综合 (GEO) 数据库 (GSE57338) 获取的HF数据集.
- 应用生物信息学和机器学习算法 (随机森林,LASSO,SVM) 来识别候选基因.
- 在其他GEO数据集 (GSE21610,GSE76701) 上验证了诊断潜力,并使用癌症基因组图谱进行了泛癌症分析.
主要成果:
- 鉴定了114个关键的HF基因,确定了具有诊断潜力 (AUC>0.7) 的四个枢纽基因 (FCN3,FREM1,MNS1,SMOC2).
- 发现了三种HF患者亚组,其中C3被确定为免疫亚型.
- 全癌症分析表明,这四个基因与瘤发育之间存在强烈的关联.
结论:
- 鉴定出了四种新型基因 (FCN3,FREM1,MNS1,SMOC2),进步了对HF病变发生的理解.
- 这些基因有望成为心力衰竭的诊断生物标志物.
- 这些发现支持为HF患者开发个性化治疗方法.
更多相关视频
07:15Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
10.9K
08:51Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
Published on: September 20, 2024
1.0K
相关概念视频
01:17Pathophysiology of Heart Failure
1.4K
Heart failure (HF) is a progressive syndrome involving ventricles that leads to inadequate cardiac output. It can be classified based on location and output or ejection fraction. Ejection fraction (EF) is an essential measurement in the diagnosis and surveillance of HF. Reduced EF corresponds to systolic heart failure (HFrEF). However, HF with preserved ejection fraction (HFpEF) is becoming increasingly prevalent. Also known as diastolic HF, this form of HF is related to aging. The...
1.4K
01:11Genome-wide Association Studies-GWAS
12.0K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
12.0K