Clinical and metabolomics characterization of hospitalized COVID-19 patients during the Delta and Omicron epidemiological waves in Mexico

COVID-19, caused by the SARS-CoV-2 virus, was first identified in Wuhan, China, in December 2019 and quickly escalated into a global pandemic by early 2020. As of mid-2024, it has affected over 676 million people worldwide, leading to more than 6.8 million deaths. Systematic reviews and meta-analyses of COVID-19 metabolomics studies have revealed consistent biomarkers reflecting immune response, inflammation, energy metabolism, oxidative stress, and liver dysfunction. COVID-19’s impact has varied across epidemiological waves. Methods: In this study, we evaluated clinical, laboratory, and metabolomic data from 42 hospitalized COVID-19 patients in Mexico during the third and fourth waves (Delta and Omicron). A targeted metabolomics assay (TMIC MEGA Assay) was used to quantify 529 metabolites and lipids in plasma samples. The metabolomic profiles of these 42 samples were compared according to different factors such as age, gender, comorbidities, and vaccination status. Additionally, 82 hospitalized patients from the Alfa COVID-19 strain (2020) were compared with the 42 patients from the Delta and Omicron epidemiological waves. Results: Among the 21 families of compounds evaluated in this study, amino acids and lipids were the most dysregulated when comparing age, gender, comorbidities, vaccination status, and epidemiological waves. Conclusion: This comprehensive analysis enhances the/our understanding of COVID-19’s clinical and metabolic impact across different epidemic waves, aiding in the identification of metabolic factors affecting patient outcomes.

由SARS-CoV-2病毒引发的新型冠状病毒肺炎（COVID-19）于2019年12月在中国武汉首次被发现，并在2020年初迅速升级为全球大流行疫情。截至2024年中期，全球累计感染人数已超过6.76亿，累计死亡病例逾680万。针对新冠病毒肺炎代谢组学（metabolomics）研究的系统综述（systematic reviews）与荟萃分析（meta-analyses）已揭示出可反映免疫应答、炎症反应、能量代谢、氧化应激及肝功能异常的一致性生物标志物（biomarkers）。新冠疫情的影响随不同流行波次存在显著差异。
方法：本研究对墨西哥地区第三、第四波疫情（德尔塔Delta株与奥密克戎Omicron株）期间收治的42名新冠住院患者的临床、实验室及代谢组学数据进行了评估。本研究采用靶向代谢组学检测（targeted metabolomics assay，TMIC MEGA Assay）对血浆样本中的529种代谢物与脂质进行定量分析。依据年龄、性别、合并症及疫苗接种状态等不同因素，对这42份样本的代谢组特征展开比较。此外，本研究还将2020年阿尔法（Alfa）新冠毒株感染的82名住院患者与上述德尔塔、奥密克戎流行波次的42名患者进行了对比分析。
结果：在本研究评估的21类化合物家族中，当对比年龄、性别、合并症、疫苗接种状态及流行波次的差异时，氨基酸与脂质的表达失调情况最为显著。
结论：本项全面的分析深化了我们对新冠病毒肺炎在不同流行波次下的临床与代谢影响的认知，有助于识别影响患者预后的代谢相关因素。