Lin Jinting, Ma Qinglan, Chen Lei, Guo Wei, Feng Kaiyan, Huang Tao, Cai Yu-Dong
School of Life Sciences, Shanghai University, Shanghai 200444, China.
College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.
Life (Basel). 2025 Jun 18;15(6):981. doi: 10.3390/life15060981.
Vaccination with ChAdOx1 nCoV-19 is an important countermeasure to fight the COVID-19 pandemic. This vaccine enhances human immunoprotection against SARS-CoV-2 by inducing an immune response against the SARS-CoV-2 S protein. However, the immune-related genes induced by vaccination remain to be identified. This study employs feature ranking algorithms, an incremental feature selection method, and classification algorithms to analyze transcriptomic data from an experimental group vaccinated with the ChAdOx1 nCoV-19 vaccine and a control group vaccinated with the MenACWY meningococcal vaccine. According to different time points, vaccination status, and SARS-CoV-2 infection status, the transcriptomic data was divided into five groups, including a pre-vaccination group, ChAdOx1-onset group, MenACWY-onset group, ChAdOx1-7D group, and MenACWY-7D group. Each group contained samples with 13,383 RNA features and 1662 small RNA features. The results identified key genes that could indicate the efficacy of the ChAdOx1 nCoV-19 vaccine, and a classifier was developed to classify samples into the above groups. Additionally, effective classification rules were established to distinguish between different vaccination statuses. It was found that subjects vaccinated with ChAdOx1 nCoV-19 vaccine and infected with SARS-CoV-2 were characterized by up-regulation of HIST1H3G expression and down-regulation of CASP10 expression. In addition, IGHG1, FOXM1, and CASP10 genes were strongly associated with ChAdOx1 nCoV-19 vaccine efficacy. Compared with previous omics-driven studies, the machine learning algorithms used in this study were able to analyze transcriptome data faster and more comprehensively to identify potential markers associated with vaccine effect and investigate ChAdOx1 nCoV-19 vaccine-induced gene expression changes. These observations contribute to an understanding of the immune protection and inflammatory responses induced by the ChAdOx1 nCoV-19 vaccine during symptomatic episodes and provide a rationale for improving vaccine efficacy.
接种ChAdOx1 nCoV-19疫苗是对抗新冠疫情的一项重要对策。该疫苗通过诱导针对严重急性呼吸综合征冠状病毒2（SARS-CoV-2）刺突蛋白的免疫反应，增强人体对SARS-CoV-2的免疫保护。然而，接种疫苗后诱导的免疫相关基因仍有待确定。本研究采用特征排名算法、增量特征选择方法和分类算法，分析接种ChAdOx1 nCoV-19疫苗的实验组和接种A群C群脑膜炎球菌结合疫苗（MenACWY）的对照组的转录组数据。根据不同时间点、接种状态和SARS-CoV-2感染状态，转录组数据被分为五组，包括接种前组、ChAdOx1发病组、MenACWY发病组、ChAdOx1-7天组和MenACWY-7天组。每组包含具有13383个RNA特征和1662个小RNA特征的样本。研究结果确定了可指示ChAdOx1 nCoV-19疫苗效力的关键基因，并开发了一种分类器将样本分类到上述各组。此外，还建立了有效的分类规则以区分不同的接种状态。研究发现，接种ChAdOx1 nCoV-19疫苗并感染SARS-CoV-2的受试者的特征是组蛋白H2B家族成员G（HIST1H3G）表达上调和含半胱氨酸的天冬氨酸蛋白水解酶10（CASP10）表达下调。此外，免疫球蛋白G1（IGHG1）、叉头框蛋白M1（FOXM1）和CASP10基因与ChAdOx1 nCoV-19疫苗效力密切相关。与以往的组学驱动研究相比，本研究中使用的机器学习算法能够更快、更全面地分析转录组数据，以识别与疫苗效果相关的潜在标志物，并研究ChAdOx1 nCoV-19疫苗诱导的基因表达变化。这些观察结果有助于理解ChAdOx1 nCoV-19疫苗在症状发作期间诱导的免疫保护和炎症反应，并为提高疫苗效力提供理论依据。
