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结合生物信息学和实验验证来探索乙型肝炎病毒相关急性肝衰竭中与乳酰化相关的生物标志物。

Bioinformatics and experimental validation were combined to explore lactylation-related biomarkers in HBV-associated acute liver failure.

作者信息

Pei Hao, Chen Yue-Qiao, Wu Feng-Lan, Zhang Yan-Yan, Zhang Xue, Li Jian-Yu, Pan Li-Yi, Chen Yu, Huang Yu-Wen

机构信息

Graduate School, Guangxi University of Traditional Chinese Medicine, Nanning, China.

First Clinical Medical College, Guangxi University of Traditional Chinese Medicine, Nanning, China.

出版信息

J Gastroenterol Hepatol. 2024 Dec;39(12):2903-2915. doi: 10.1111/jgh.16739. Epub 2024 Sep 16.

Abstract

BACKGROUND AND AIM

Currently, hepatitis B virus-related acute liver failure (HBV-ALF) has limited treatment options. Studies have shown that histone lactylation plays a role in the progression of liver-related diseases. Therefore, it is essential to explore lactylation-related gene (LRGs) biomarkers in HBV-ALF to provide new information for the treatment of HBV-ALF.

METHODS

Two HBV-ALF-related datasets (GSE38941 and GSE14668) and 65 LRGs were used. First, the differentially expressed genes (DEGs) were derived from differential expression analysis, the key module genes from weighted gene co-expression network analysis; and LRGs were used to intersect to obtain the candidate genes. Subsequently, the feature genes obtained from least absolute shrinkage and selection operator regression analysis and support vector machine analysis were intersected to obtain the candidate key genes. Among them, genes with consistent and significant expression trends in both GSE38941 and GSE14668 were used as biomarkers. Subsequently, biomarkers were analyzed for functional enrichment, immune infiltration, and sensitive drug prediction.

RESULTS

In this study, five candidate genes (PIGM, PIGA, EGR1, PIGK, and PIGL) were identified by intersecting 6461 DEGs and 2496 key module genes with 65 LRGs. We then screened four candidate key genes from the machine learning algorithm, among which PIGM and PIGA were considered biomarkers in HBV-ALF. Moreover, the results of enrichment analysis showed that the significant enrichment signaling pathways for biomarkers included allograft rejection and valine, leucine, and isoleucine degradation. Thereafter, 11 immune cells differed significantly between groups, with resting memory CD4+ T cells having the strongest positive correlation with biomarkers. Methylphenidate hydrochloride is a potential therapeutic drug for PIGM.

CONCLUSION

Two genes, PIGM and PIGA, were identified as biomarkers related to LRGs in HBV-ALF, providing a basis for understanding HBV-ALF pathogenesis.

摘要

背景与目的

目前,乙型肝炎病毒相关急性肝衰竭(HBV-ALF)的治疗选择有限。研究表明,组蛋白乳酰化在肝脏相关疾病的进展中起作用。因此,探索HBV-ALF中与乳酰化相关的基因(LRGs)生物标志物,可为HBV-ALF的治疗提供新的信息。

方法

使用两个与HBV-ALF相关的数据集(GSE38941和GSE14668)以及65个LRGs。首先,通过差异表达分析得出差异表达基因(DEGs),通过加权基因共表达网络分析得出关键模块基因;然后将LRGs与之相交以获得候选基因。随后,将通过最小绝对收缩和选择算子回归分析及支持向量机分析得到的特征基因相交,以获得候选关键基因。其中,在GSE38941和GSE14668中表达趋势一致且显著的基因用作生物标志物。随后,对生物标志物进行功能富集、免疫浸润和敏感药物预测分析。

结果

在本研究中,通过将6461个DEGs和2496个关键模块基因与65个LRGs相交,鉴定出五个候选基因(PIGM、PIGA、EGR1、PIGK和PIGL)。然后我们从机器学习算法中筛选出四个候选关键基因,其中PIGM和PIGA被认为是HBV-ALF中的生物标志物。此外,富集分析结果表明,生物标志物的显著富集信号通路包括同种异体移植排斥反应以及缬氨酸、亮氨酸和异亮氨酸降解。此后,两组之间有11种免疫细胞存在显著差异,静息记忆CD4+ T细胞与生物标志物的正相关性最强。盐酸哌甲酯是PIGM的一种潜在治疗药物。

结论

PIGM和PIGA这两个基因被鉴定为HBV-ALF中与LRGs相关的生物标志物,为理解HBV-ALF的发病机制提供了依据。

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