Lipidome is a valuable tool for the severity prediction of coronavirus disease 2019

• DOI: 10.3389/fimmu.2024.1337208
• Publication Date: 2024-05-10T05:05:20Z
• Authors: Shan-Shan Zhang; Zhiling Zhao; Wan-Xue Zhang; Rui Wu; Fei Li; Han Yang; Qiang Zhang; Ting-Ting Wei; Jingjing Xi; Yiguo Zhou; Tiehua Wang; Juan Du; Ninghua Huang; Qinggang Ge; Qing-Bin Lu
• Keywords: Lipidome; Coronavirus

Objective To describe the lipid metabolic profile of different patients with coronavirus disease 2019 (COVID-19) and contribute new evidence on progression severity prediction COVID-19. Methods This case–control study was conducted in Peking University Third Hospital, China. The laboratory-confirmed COVID-19 aged ≥18 years old diagnosed as pneumonia from December 2022 to January 2023 were included. Serum lipids detected. discrimination ability calculated area under curve (AUC). A random forest (RF) model determine significance lipids. Results Totally, 44 enrolled 16 mild 28 severe patients. top 5 super classes triacylglycerols (TAG, 55.9%), phosphatidylethanolamines (PE, 10.9%), phosphatidylcholines (PC, 6.8%), diacylglycerols (DAG, 5.9%) free fatty acids (FFA, 3.6%) among 778 detected serum Certain lipids, especially lysophosphatidylcholines (LPCs), turned have significant correlations certain immune/cytokine indexes. Reduced level LPC 20:0 observed particularly acute stage. AUC reached 0.940 discriminating 0.807 recovery stages results RF models also suggested LPCs predicting Conclusion Lipids probably potential differentiate forecast severity, progression, clinical outcomes patients, implications for immune/inflammatory responses. might be a target outcome treatment