Polyunsaturated fatty acids are metabolized into regulatory lipids important for initiating inflammatory responses in the event of disease or injury and for signaling the resolution of inflammation and return to homeostasis. The epoxides of linoleic acid (leukotoxins) regulate skin barrier function, perivascular and alveolar permeability and have been associated with poor outcomes in burn patients and in sepsis. It was later reported that blocking metabolism of leukotoxins into the vicinal diols ameliorated the deleterious effects of leukotoxins, suggesting that the leukotoxin diols are contributing to the toxicity. During quantitative profiling of fatty acid chemical mediators (eicosanoids) in COVID-19 patients, we found increases in the regioisomeric leukotoxin diols in plasma samples of hospitalized patients suffering from severe pulmonary involvement. In rodents these leukotoxin diols cause dramatic vascular permeability and are associated with acute adult respiratory like symptoms. Thus, pathways involved in the biosynthesis and degradation of these regulatory lipids should be investigated in larger biomarker studies to determine their significance in COVID-19 disease. In addition, incorporating diols in plasma multi-omics of patients could illuminate the COVID-19 pathological signature along with other lipid mediators and blood chemistry.

Detailed Methods.

This is a retrospective study using prospectively collected plasma samples and clinical data. For oxylipin analysis, heparinized plasma was collected from six patients with laboratory-confirmed SARS-CoV-2 infection and admitted to the University of California Davis Medical Center in Sacramento, CA and 44 samples from healthy controls carefully chosen from a recently completed clinical study. For comparison of cytokines, plasma from healthy volunteers was collected from the California Central Valley Delta Blood Bank (Stockton, CA) prior to the COVID-19 pandemic. The methods used for blood collection, plasma processing, use of anti-coagulants/antioxidant/preservatives, and flash-freeze protocol were well-matched between case and control groups. The UC Davis and UC San Diego Institutional Review Boards approved the use of anonymized biospecimens for this study.

Lipid mediator Profiling         

Plasma (200 μL) samples were aliquoted to a cocktail solution including 600 μL of methanol with 10 μL of 500 nM of surrogate solution including 9 isotope-labeled oxylipins (d4 PGF1a, d4 PGE2, d4 TXB2, d4 LTB4, d6 20 HETE, d11 14,15 DiHETrE, d8 9 HODE, d8 5 HETE, d11 11,12 EpETrE). Before the extraction, the samples were vortexed and centrifuged at 3000 rpm in a biosafety hood. The supernatants were then loaded on prewashed SPE cartridges and washed with two column volumes of 5% MeOH solution before elution by 0.5 mL of MeOH and 1.5 mL of ethyl acetate. The eluents were dried under vacuum using the Nutec MaxiVac vacuum concentrator (Farmingdale, NY USA) before reconstitution with 50 μL of 100 nM CUDA solution in methanol. Then, the extracted samples were analyzed using the UPLC/MS/MS system (Waters Acquity UPLC (Milford, MA, USA) hyphenated to AB Sciex 6500+ QTrap system (Redwood City, CA USA). The detailed parameters for the UPLC/MS/MS method were described previously (13, 14).

Statistical analysis

To test for differences between the COVID-19 and the control group cytokine levels, cytokine levels were log₁₀ transformed to fit a normal distribution and analyzed in Graphpad Prism (version 8.4.3) using the Wilcoxon rank-sum test with COVID positive and negative status as the main effect.

Lipid mediator results were analyzed using MetaboAnalyst (https://www.metaboanalyst.ca/) and scaled using autoscaling before analysis. Multiple data sets described below were integrated to prioritize the oxylipins as possible biomarkers contributing to the severity of COVID. Oxylipins were analyzed by multiple independent t-tests using patient vs. control as the variable and the two-stage step-up method of Benjamini, Krieger and Yekutieli to determine a false discovery rate (15) to generate the volcano plot.

The lipid mediators were then ranked by their effect sizes (i.e., the fold-difference between mean analyte concentration in each group). The analytes with the largest effect sizes were further evaluated by random effect ANOVA models. We minimized type 1 errors by testing for between-group differences among the analytes with the largest effect sizes and to improve the likelihood of identifying analytes that showed best potential to seve as biomarkers of disease severity. Each analyte with an effect size above 8 (i.e., analyte concentrations >8-fold different) was used as a response variable. Random effect ANOVAs were run with ‘patient’ as a random effect to account for the multiple measurements from the same patient, and the fixed effect was ‘group’ (i.e., COVID positive or control). The log₁₀-transformation of the analyte concentrations was applied. The analysis was done in JMP Pro Version15.