Wang Chunhua, Yu Tingyu, Xia Ying, Tao Feng, Sun Jiali, Zhao Jianzhong, Mao Xiaogang, Tang Mengjun, Yin Lijuan, Yang Yang, Tan Wenjie, Shen Liang, Zhang Shuaijie
Department of Clinical Laboratory, Xiangyang No. 1 People's Hospital, Hubei University of Medicine, Xiangyang, Hubei Province, China.
Department of Central Laboratory, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei Province, China.
Virulence. 2025 Dec;16(1):2497907. doi: 10.1080/21505594.2025.2497907. Epub 2025 May 1.
Currently, the Omicron variant of the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to circulate globally. In our multiplex respiratory pathogen detection, we identified numerous instances of co-infection with Echovirus (ECHO) among Coronavirus Disease 2019 (COVID-19) patients, which exacerbated the clinical symptoms of these patients. Such co-infections are likely to impact the subsequent medical treatment. To date, there are no reports on the pathogenic mechanisms related to COVID-19 co-infected with ECHO. Therefore, this study employed the TM Widely-Targeted metabolomics approach to analyze the serum metabolomes of COVID-19 patients with single SARS-CoV-2 infection (COVID-19), COVID-19 patients co-infected with ECHO (COVID-19 + ECHO), and healthy individuals (Control) recruited from routine physical examinations during the same period. Concurrent clinical laboratory tests were performed on the patients to reveal the differences in metabolomic characteristics between the COVID-19 patients and the COVID-19 + ECHO patients, as well as to explore potential metabolic pathways that may exacerbate disease progression. Our findings indicate that both clinical examination indicators and the pathways enriched by differential metabolites confirm that patients with dual infection exhibit higher inflammatory and immune responses compared to those with single COVID-19 infections. This difference is likely reflected through abnormalities in the glycerophospholipid metabolic pathway, with the metabolite Sn-Glycero-3-Phosphocholine playing a crucial role in this process. Finally, we established a diagnostic model based on logistic regression using five differential metabolites, which accurately differentiates between the dual infection population and the single COVID-19 infection population (AUC = 0.828).
目前，严重急性呼吸综合征冠状病毒2（SARS-CoV-2）的奥密克戎变异株仍在全球传播。在我们的多重呼吸道病原体检测中，我们在2019冠状病毒病（COVID-19）患者中发现了大量与埃可病毒（ECHO）合并感染的病例，这加剧了这些患者的临床症状。这种合并感染可能会影响后续的治疗。迄今为止，尚无关于COVID-19合并ECHO感染的致病机制的报道。因此，本研究采用TM广泛靶向代谢组学方法，分析了同期招募的单一SARS-CoV-2感染的COVID-19患者（COVID-19）、合并ECHO感染的COVID-19患者（COVID-19 + ECHO）和健康个体（对照）的血清代谢组。对患者进行了同步临床实验室检测，以揭示COVID-19患者与COVID-19 + ECHO患者之间代谢组学特征的差异，并探索可能加剧疾病进展的潜在代谢途径。我们的研究结果表明，临床检查指标和差异代谢物富集的途径均证实，与单一COVID-19感染患者相比，双重感染患者表现出更高的炎症和免疫反应。这种差异可能通过甘油磷脂代谢途径的异常反映出来，代谢物Sn-甘油-3-磷酸胆碱在此过程中起关键作用。最后，我们使用五种差异代谢物建立了基于逻辑回归的诊断模型，该模型能够准确区分双重感染人群和单一COVID-19感染人群（AUC = 0.828）。
