使用生物信息学和机器学习在败血症引起的ARDS中识别与巨相关的基因
Qiuyue Li1, Hongyu Zheng2, Bing Chen3
1Department of Emergency Medicine, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Hexi District, Tianjin, 300211, China.
Scientific reports
|June 19, 2023
概括
这项研究确定了三个关键的巨相关基因 (SGK1,DYSF,MSRB1) 作为诊断败血症引起的急性呼吸困扰综合征 (ARDS) 的潜在生物标志物. 这些发现为早期发现和治疗这种关键疾病提供了新的目标.
科学领域:
- 生物医学研究的研究.
- 基因组学就是基因组学.
- 计算生物学是一种计算生物学.
背景情况:
- 败血症引起的急性呼吸困扰综合征 (ARDS) 是重症患者死亡的主要原因.
- 巨细胞在败血症引起的ARDS的发病和治疗中至关重要.
- 确定可靠的生物标志物对于早期诊断和有效管理至关重要.
研究的目的:
- 用生物信息学和机器学习来选与巨相关的生物标志物来诊断和治疗因败血症引起的ARDS.
- 为了确定关键的基因与巨细胞的功能在败血症诱导的ARDS.
- 为了验证已识别的生物标志物的诊断疗效.
主要方法:
- 从基因表达综合 (GEO) 数据库下载了基因表达数据.
- 使用生物信息学工具,包括limma,ssGSEA,WGCNA和PPI分析.
- 使用外部数据集进行基因查和验证的应用机器学习算法 (SVM-RFE,随机森林).
主要成果:
- 鉴定了325个差异表达的基因,富含免疫和反应性氧代谢途径.
- 使用WGCNA选了506个巨相关基因,确定了48个差异表达的基因.
- 通过ROC曲线和名录模型验证了三种关键基因 (SGK1,DYSF,MSRB1) 具有显著的诊断疗效.
结论:
- SGK1,DYSF和MSRB1是早期诊断败血症引起的ARDS的有希望的生物标志物.
- 这些已识别的基因为改善诊断准确性和治疗策略提供了新的点.
- 这项研究强调了综合生物信息学和机器学习方法在关键疾病生物标志物发现中的有用性.
相关概念视频
01:11Genome-wide Association Studies-GWAS
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...
01:29Pharmacogenomics: Identification of New Drug Targets
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...