García-López David Alejandro, Monárrez-Espino Joel, Borrego-Moreno Juan Carlos, Zheng Jiamin, Mandal Rupasri, Torres-Calzada Claudia, Oropeza-Valdez Juan José, Tenório Nunes Alanne, Sánchez Rodríguez Sergio Hugo, López Jesús Adrián, Calzada Rodríguez Blanca Estela, Wishart David S, López-Hernández Yamilé
Metabolomics and Proteomics Laboratory, Academic Unit for Biological Sciences, Autonomous University of Zacatecas, Zacatecas, Mexico.
Departamento de investigación en salud, Hospital Christus Muguerza Chihuahua, Chihuahua, Mexico.
Front Mol Biosci. 2025 Jun 18;12:1607583. doi: 10.3389/fmolb.2025.1607583. eCollection 2025.
As of mid-2024, COVID-19 has affected over 676 million people worldwide, leading to more than 6.8 million deaths. Numerous studies have documented metabolic changes occurring during both the acute phase of the disease and the recovery phase, which, in some cases, contribute to the development of long COVID syndrome.
In this study, we aimed to evaluate clinical, laboratory, and comprehensive metabolomic data from hospitalized COVID-19 patients during the second, third and fourth waves (Alpha, Delta, and Omicron). A targeted, fully quantitative metabolomics assay (TMIC MEGA Assay) was used to measure 529 metabolites and lipids in plasma samples. The metabolomic profiles of these patients were compared according to different and relevant factors impacting COVID-19 outcome, such as age, sex, comorbidities, and vaccination status.
Among the 21 classes of compounds evaluated in this study, amino acids and lipids were the most dysregulated when comparing age, sex, comorbidities, vaccination status, and the different epidemiological waves. This is the most comprehensive analysis in Mexico providing absolute quantitative data for 529 metabolites and lipids measured in hospitalized COVID-19 patients, which could be used to monitor their metabolic status and clinical outcomes associated with COVID-19 infection or with long COVID syndrome.
截至2024年年中,新冠病毒已影响全球超过6.76亿人,导致超过680万人死亡。众多研究记录了该疾病急性期和恢复期出现的代谢变化,在某些情况下,这些变化会导致长期新冠综合征的发展。
在本研究中,我们旨在评估第二波、第三波和第四波(阿尔法、德尔塔和奥密克戎)期间住院的新冠患者的临床、实验室和综合代谢组学数据。采用靶向、全定量代谢组学分析方法(TMIC MEGA分析)测量血浆样本中的529种代谢物和脂质。根据影响新冠病毒感染结果的不同相关因素,如年龄、性别、合并症和疫苗接种状况,对这些患者的代谢组学特征进行比较。
在本研究评估的21类化合物中,比较年龄、性别、合并症、疫苗接种状况和不同疫情波次时,氨基酸和脂质的失调最为明显。这是墨西哥最全面的分析,为住院新冠患者测量的529种代谢物和脂质提供了绝对定量数据,可用于监测他们与新冠病毒感染或长期新冠综合征相关的代谢状态和临床结果。