Identification and validation of aging-related genes and their classification models based on myelodysplastic syndromes

IF 1 Q4 ENGINEERING, BIOMEDICAL
Xiao-Li Gu, Li Yu, Yu Du, Xiu-Peng Yang, Yong-Gang Xu
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引用次数: 0

Abstract

Background

Myelodysplastic syndrome is a malignant clonal disorder of hematopoietic stem cells (HSC) with both myelodysplastic problems and hematopoietic disorders. The greatest risk factor for the development of MDS is advanced age, and aging causes dysregulation and decreased function of the immune and hematopoietic systems. However, the mechanisms by which this occurs remain to be explored. Therefore, we explore the association between MDS and aging genes through a classification model and use bioinformatics analysis tools to explore the relationship between MDS aging subtypes and the immune microenvironment.

Methods

The dataset of MDS in the paper was obtained from the GEO database, and aging-related genes were taken from HAGR. Specific genes were screened by three machine learning algorithms. Then, artificial neural network (ANN) models and Nomogram models were developed to validate the effectiveness of the methods. Finally, aging subtypes were established, and the correlation between MDS and the immune microenvironment was analyzed using bioinformatics analysis tools. Weighted correlation network analysis (WGCNA) and single cell analysis were also added to validate the consistency of the result analysis.

Results

Seven core genes associated with ARG were screened by differential analysis, enrichment analysis and machine learning algorithms for accurate diagnosis of MDS. Subsequently, two subtypes of senescent expressions were identified based on ARG, illustrating that different subtypes have different biological and immune functions. The cell clustering results obtained from manual annotation were validated using single cell analysis, and the expression of 7 pivotal genes in MDS was verified by flow cytometry and RT-PCR.

Discussion

The findings demonstrate a key role of senescence in the immunological milieu of MDS, giving new insights into MDS pathogenesis and potential treatments. The findings also show that aging plays an important function in the immunological microenvironment of MDS, giving new insights into the pathogenesis of MDS and possible immunotherapy.

基于骨髓增生异常综合征的衰老相关基因及其分类模型的鉴定和验证
& lt; abstract> & lt; sec>& lt; title> Background< / title>骨髓增生异常综合征是一种恶性造血干细胞(HSC)克隆性疾病,同时伴有骨髓增生异常和造血功能障碍。MDS发生的最大危险因素是高龄,衰老会导致免疫和造血系统的失调和功能下降。然而,发生这种情况的机制仍有待探索。因此,我们通过分类模型探索MDS与衰老基因之间的关系,并利用生物信息学分析工具探索MDS衰老亚型与免疫微环境之间的关系。& lt; / sec> & lt; sec>& lt; title> Methods< / title>< >本文MDS数据集来源于GEO数据库,衰老相关基因来源于HAGR。通过三种机器学习算法筛选特定基因。然后,建立了人工神经网络模型和Nomogram模型来验证方法的有效性。最后,建立衰老亚型,并利用生物信息学分析工具分析MDS与免疫微环境的相关性。同时加入加权相关网络分析(WGCNA)和单细胞分析,验证结果分析的一致性。& lt; / sec> & lt; sec>& lt; title> Results< / title>通过差异分析、富集分析和机器学习算法筛选7个与ARG相关的核心基因,用于MDS的准确诊断。随后,基于ARG鉴定出两种衰老表达亚型,说明不同亚型具有不同的生物学和免疫功能。通过单细胞分析验证手工注释获得的细胞聚类结果,并通过流式细胞术和RT-PCR验证MDS中7个关键基因的表达。& lt; / sec> & lt; sec>& lt; title> Discussion< / title>这些发现表明衰老在MDS的免疫环境中起着关键作用,为MDS的发病机制和潜在的治疗提供了新的见解。研究结果还表明,衰老在MDS的免疫微环境中起着重要作用,为MDS的发病机制和可能的免疫治疗提供了新的见解。& lt; / sec> & lt; / abstract>
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来源期刊
AIMS Bioengineering
AIMS Bioengineering ENGINEERING, BIOMEDICAL-
自引率
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发文量
17
审稿时长
4 weeks
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