Tina Kramaric, Onn Shaun Thein, Dhruv Parekh, Aaron Scott, Andrine Vangberg, Manfred Beckmann, Helen Phillips, David Thickett, Luis A J Mur
{"title":"SARS-CoV2 变异体对血浆代谢组的不同影响","authors":"Tina Kramaric, Onn Shaun Thein, Dhruv Parekh, Aaron Scott, Andrine Vangberg, Manfred Beckmann, Helen Phillips, David Thickett, Luis A J Mur","doi":"10.1007/s11306-025-02238-y","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Infection with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) leads to COVID19 disease and caused a worldwide pandemic in 2019. Since the first wave of infections, there has been significant antigenic shifts, leading to the emergence of new variants. Today, infections have shifted away from the severe, fatal infection seen in 2019.</p><p><strong>Objective: </strong>This study aimed to assess how the plasma metabolomes from patients varied with infection with different strains and could reflect disease severity.</p><p><strong>Methods: </strong>Patients with COVID19 not requiring intensive care were recruited between January 2021 and May 2022 from the Queen Elizabeth Hospital Birmingham; 33 patients with alpha, 13 delta and 14 omicron variants. These were compared to 26 age matched contemporaneously recruited controls. Plasma samples were extracted into chloroform/methanol/water (1:2.5/1 v/v) and assessed by flow injection electrospray mass spectrometry (FIE-MS) using an Exactive Orbitrap mass spectrometer. Derived data were assessed using the R based MetaboAnalyst platform.</p><p><strong>Results: </strong>Plasma metabolomes from COVID19 patients were clearly different from controls. Metabolite variation could be related to infection with different SARS-CoV2 variants. Variant showed different levels of some phospholipids, ganglioside GD1a and a dihydroxyvitamin D3 derivative. Correlations of the plasma metabolomes indicated negative correlations between selected phospholipids and the levels of C-reactive protein, creatinine, neutrophil and D-dimer.</p><p><strong>Conclusion: </strong>The plasma metabolomes of COVID19 patients show changes, particularly in phospholipids, which could reflect disease severity and SARS-CoV2 variant infection.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 2","pages":"50"},"PeriodicalIF":3.5000,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11972186/pdf/","citationCount":"0","resultStr":"{\"title\":\"SARS-CoV2 variants differentially impact on the plasma metabolome.\",\"authors\":\"Tina Kramaric, Onn Shaun Thein, Dhruv Parekh, Aaron Scott, Andrine Vangberg, Manfred Beckmann, Helen Phillips, David Thickett, Luis A J Mur\",\"doi\":\"10.1007/s11306-025-02238-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Infection with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) leads to COVID19 disease and caused a worldwide pandemic in 2019. Since the first wave of infections, there has been significant antigenic shifts, leading to the emergence of new variants. Today, infections have shifted away from the severe, fatal infection seen in 2019.</p><p><strong>Objective: </strong>This study aimed to assess how the plasma metabolomes from patients varied with infection with different strains and could reflect disease severity.</p><p><strong>Methods: </strong>Patients with COVID19 not requiring intensive care were recruited between January 2021 and May 2022 from the Queen Elizabeth Hospital Birmingham; 33 patients with alpha, 13 delta and 14 omicron variants. These were compared to 26 age matched contemporaneously recruited controls. Plasma samples were extracted into chloroform/methanol/water (1:2.5/1 v/v) and assessed by flow injection electrospray mass spectrometry (FIE-MS) using an Exactive Orbitrap mass spectrometer. Derived data were assessed using the R based MetaboAnalyst platform.</p><p><strong>Results: </strong>Plasma metabolomes from COVID19 patients were clearly different from controls. Metabolite variation could be related to infection with different SARS-CoV2 variants. Variant showed different levels of some phospholipids, ganglioside GD1a and a dihydroxyvitamin D3 derivative. Correlations of the plasma metabolomes indicated negative correlations between selected phospholipids and the levels of C-reactive protein, creatinine, neutrophil and D-dimer.</p><p><strong>Conclusion: </strong>The plasma metabolomes of COVID19 patients show changes, particularly in phospholipids, which could reflect disease severity and SARS-CoV2 variant infection.</p>\",\"PeriodicalId\":18506,\"journal\":{\"name\":\"Metabolomics\",\"volume\":\"21 2\",\"pages\":\"50\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11972186/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metabolomics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11306-025-02238-y\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11306-025-02238-y","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
SARS-CoV2 variants differentially impact on the plasma metabolome.
Introduction: Infection with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) leads to COVID19 disease and caused a worldwide pandemic in 2019. Since the first wave of infections, there has been significant antigenic shifts, leading to the emergence of new variants. Today, infections have shifted away from the severe, fatal infection seen in 2019.
Objective: This study aimed to assess how the plasma metabolomes from patients varied with infection with different strains and could reflect disease severity.
Methods: Patients with COVID19 not requiring intensive care were recruited between January 2021 and May 2022 from the Queen Elizabeth Hospital Birmingham; 33 patients with alpha, 13 delta and 14 omicron variants. These were compared to 26 age matched contemporaneously recruited controls. Plasma samples were extracted into chloroform/methanol/water (1:2.5/1 v/v) and assessed by flow injection electrospray mass spectrometry (FIE-MS) using an Exactive Orbitrap mass spectrometer. Derived data were assessed using the R based MetaboAnalyst platform.
Results: Plasma metabolomes from COVID19 patients were clearly different from controls. Metabolite variation could be related to infection with different SARS-CoV2 variants. Variant showed different levels of some phospholipids, ganglioside GD1a and a dihydroxyvitamin D3 derivative. Correlations of the plasma metabolomes indicated negative correlations between selected phospholipids and the levels of C-reactive protein, creatinine, neutrophil and D-dimer.
Conclusion: The plasma metabolomes of COVID19 patients show changes, particularly in phospholipids, which could reflect disease severity and SARS-CoV2 variant infection.
期刊介绍:
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.