Lipoxin A(4) levels correlate with severity in a Spanish COVID-19 cohort: potential use of endogenous pro-resolving mediators as biomarkers

西班牙新冠肺炎患者队列中脂氧素A(4)水平与疾病严重程度相关:内源性促消退介质作为生物标志物的潜在用途

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Abstract

BACKGROUND: SARS-CoV-2, the causative virus of the COVID-19 global pandemic, leads to a wide variety of responses among patients. Some of them present a very severe phenotype, while others only experience mild symptoms or are even asymptomatic. This differential prognosis is tightly related to the inflammatory status of the patient. Although WHO declared the end of the emergency, the pandemic caused a great socio-sanitary impact in all countries. Thus, the possible outbreak of new biological diseases in the future makes it necessary to deepen the knowledge of this uncontrolled immune response and look for reliable biomarkers to help us predict its potential health impact. Specialized pro-resolving lipid mediators (SPMs) as lipoxins are endogenous mediators synthesized from arachidonic acid in the resolution stage of any inflammatory process. These lipids have pro-resolving actions in several pathological models, including reducing NF-κB-mediated inflammation, and inducing the antioxidant response through the Nrf-2 pathway. Thus, although a potential relationship has already been suggested between low levels of SPMs and COVID-19 severity, their true role as a predictive biomarker is still unknown. METHODS AND RESULTS: In this study, we have analyzed by ELISA the serum levels of lipoxin A(4) (LXA(4)) in a representative Spanish cohort. We found reduced levels in deceased patients when compared to mild or severe patients, concomitant with a decrease in the LXA(4) biosynthetic pathway and an increase in its degradation pathway. Furthermore, we have studied the correlation between the levels of this SPM and several pathology indicators, finding a significant correlation between increased LXA(4) levels and a better prognosis of the patients. CONCLUSION: We propose to measure systemic LXA(4) as a new promising biomarker to predict the survival in patients affected by SARS-CoV-2 and presumably to other viruses that can affect humanity in the future.

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