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Lipidome is a valuable tool for the severity prediction of coronavirus disease 2019.
Zhang, Shan-Shan; Zhao, Zhiling; Zhang, Wan-Xue; Wu, Rui; Li, Fei; Yang, Han; Zhang, Qiang; Wei, Ting-Ting; Xi, Jingjing; Zhou, Yiguo; Wang, Tiehua; Du, Juan; Huang, Ninghua; Ge, Qinggang; Lu, Qing-Bin.
Afiliação
  • Zhang SS; Department of Laboratorial Science and Technology and Vaccine Research Center, School of Public Health, Peking University, Beijing, China.
  • Zhao Z; Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China.
  • Zhang WX; Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China.
  • Wu R; Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China.
  • Li F; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
  • Yang H; Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China.
  • Zhang Q; Department of General Surgery, Peking University Third Hospital, Beijing, China.
  • Wei TT; Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China.
  • Xi J; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
  • Zhou Y; Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China.
  • Wang T; Department of Laboratorial Science and Technology and Vaccine Research Center, School of Public Health, Peking University, Beijing, China.
  • Du J; Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China.
  • Huang N; Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China.
  • Ge Q; Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China.
  • Lu QB; Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China.
Front Immunol ; 15: 1337208, 2024.
Article em En | MEDLINE | ID: mdl-38799463
ABSTRACT

Objective:

To describe the lipid metabolic profile of different patients with coronavirus disease 2019 (COVID-19) and contribute new evidence on the progression and severity prediction of COVID-19.

Methods:

This case-control study was conducted in Peking University Third Hospital, China. The laboratory-confirmed COVID-19 patients aged ≥18 years old and diagnosed as pneumonia from December 2022 to January 2023 were included. Serum lipids were detected. The discrimination ability was calculated with the area under the curve (AUC). A random forest (RF) model was conducted to determine the significance of different lipids.

Results:

Totally, 44 COVID-19 patients were enrolled with 16 mild and 28 severe patients. The top 5 super classes were triacylglycerols (TAG, 55.9%), phosphatidylethanolamines (PE, 10.9%), phosphatidylcholines (PC, 6.8%), diacylglycerols (DAG, 5.9%) and free fatty acids (FFA, 3.6%) among the 778 detected lipids from the serum of COVID-19 patients. Certain lipids, especially lysophosphatidylcholines (LPCs), turned to have significant correlations with certain immune/cytokine indexes. Reduced level of LPC 200 was observed in severe patients particularly in acute stage. The AUC of LPC 200 reached 0.940 in discriminating mild and severe patients and 0.807 in discriminating acute and recovery stages in the severe patients. The results of RF models also suggested the significance of LPCs in predicting the severity and progression of COVID-19.

Conclusion:

Lipids probably have the potential to differentiate and forecast the severity, progression, and clinical outcomes of COVID-19 patients, with implications for immune/inflammatory responses. LPC 200 might be a potential target in predicting the progression and outcome and the treatment of COVID-19.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Índice de Gravidade de Doença / Lipidômica / SARS-CoV-2 / COVID-19 Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: Front Immunol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Suíça
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Índice de Gravidade de Doença / Lipidômica / SARS-CoV-2 / COVID-19 Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: Front Immunol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Suíça