key: cord-0903292-72tv3q48
authors: Biagini, Denise; Franzini, Maria; Oliveri, Paolo; Lomonaco, Tommaso; Ghimenti, Silvia; Bonini, Andrea; Vivaldi, Federico; Macera, Lisa; Balas, Laurence; Durand, Thierry; Oger, Camille; Galano, Jean-Marie; Maggi, Fabrizio; Celi, Alessandro; Paolicchi, Aldo; Di Francesco, Fabio
title: MS-based targeted profiling of oxylipins in COVID-19: A new insight into inflammation regulation
date: 2022-01-25
journal: Free Radic Biol Med
DOI: 10.1016/j.freeradbiomed.2022.01.021
sha: 9f840a43c41e49ac790d81eed98e79dcab88e289
doc_id: 903292
cord_uid: 72tv3q48

The key role of inflammation in COVID-19 induced many authors to study the cytokine storm, whereas the role of other inflammatory mediators such as oxylipins is still poorly understood. IMPRECOVID was a monocentric retrospective observational pilot study with COVID-19 related pneumonia patients (n = 52) admitted to Pisa University Hospital between March and April 2020. Our MS-based analytical platform permitted the simultaneous determination of sixty plasma oxylipins in a single run at ppt levels for a comprehensive characterisation of the inflammatory cascade in COVID-19 patients. The datasets containing oxylipin and cytokine plasma levels were analysed by principal component analysis (PCA), computation of Fisher’s canonical variable, and a multivariate receiver operating characteristic (ROC) curve. Differently from cytokines, the panel of oxylipins clearly differentiated samples collected in COVID-19 wards (n = 43) and Intensive Care Units (ICUs) (n = 27), as shown by the PCA and the multivariate ROC curve with a resulting AUC equal to 0.92. ICU patients showed lower (down to two orders of magnitude) plasma concentrations of anti-inflammatory and pro-resolving lipid mediators, suggesting an impaired inflammation response as part of a prolonged and unsolvable pro-inflammatory status. In conclusion, our targeted oxylipidomics platform helped shedding new light in this field. Targeting the lipid mediator class switching is extremely important for a timely picture of a patient’s ability to respond to the viral attack. A prediction model exploiting selected lipid mediators as biomarkers seems to have good chances to classify patients at risk of severe COVID-19.

Severe patients are characterized by a hyper immuno-activation leading generally to respiratory failure, systemic inflammation and multi-organ fibrosis. Markers associated with this acute immune-inflammatory response and severe COVID-19 symptoms could be found among chemicals involved in the cytokine and oxylipin storm [1] .

The cytokine storm results in a detrimental dysregulation of T cell responses and in an uncontrolled overproduction of immune cells and cytokines, such as tumour necrosis factor-α (TNF-α), interferon-γ (IFN-γ), interleukins (IL-1β, IL-2, IL-6, IL-7, IL-8), and a large number of chemokines (CCL2, CCL3, CCL5, CCL9, CCL10) [2] . Besides cytokines, other important inflammatory mediators, e.g., oxylipins, sustain the inflammatory response observed in severe COVID-19 cases [3] [4] [5] [6] [7] . COVID-19 patients showed higher levels of these mediators compared to healthy subjects [4, 5, 7] . Bosio et al. suggested a lipid dysregulation from moderate to severe disease. However, neither clear lipidome dysregulation nor significant separation between the two groups was observed [6] .

Oxylipins are bioactive lipids generated from both ω-3 and ω-6 polyunsaturated fatty acids (PUFAs) through enzymatic (e.g., prostanoids, epoxy, and hydroxy fatty acids) and nonenzymatic (e.g., isoprostanoids) oxidation reactions [8, 9] . Because of their anti-inflammatory action, ω-3 PUFAs seem to limit the level and duration of the critical inflammatory phase [10] , and reduce ICU admissions of COVID-19 patients [11] . At the same time, PUFAs act as precursors for pro-inflammatory, anti-inflammatory, and specialized pro-resolving lipid mediators (SPM) [12, 13] . Firstly, pro-inflammatory mediators such as prostaglandins, thromboxanes, and leukotrienes are released into the body, leading to the classic signs of inflammation [14] . The production of oxylipins then undergoes lipid mediator class switching mainly because of CYP450-derived epoxy fatty acids, thus shifting from the lipoxygenase pathway to the specialized pro-resolving mediators [14] . SPMs mostly consist of lipoxins, resolvins, maresins, and protectins, which could lower the inflammatory response and even J o u r n a l P r e -p r o o f promote its resolution [15, 16] without being immunosuppressive unlike classic antiinflammatory drugs [17] .

Consequently, a better understanding of the cytokine storm and its coupling with the oxylipin storm should provide new insights into the complex immuno-inflammatory cascade induced by SARS-CoV-2 and lead to novel strategies for managing patients. The levels of these bioactive mediators may mirror basic biological processes determining the evolution of the pathology and could provide clinicians with clear indications regarding the urgency of patient transfer to ICU.

In this paper, a powerful in-house oxylipidomics platform was successfully employed for the monitoring of the inflammatory response in COVID-19. In more detail, the plasma levels of 48 oxylipins and 5 cytokines in COVID-19 ward and ICU patients were compared. The results highlighted that the oxylipin plasma levels can be used to discriminate between the two groups by multivariate analysis. A biological interpretation linking the findings of the present study to a possible evolution of the inflammatory process are proposed, shedding new light on the pathophysiological mechanism of the COVID-19 disease.

This monocentric retrospective observational study (IMPRE-COVID-19) was approved by the local Ethics Committee. Patients eligible for enrolment were aged 18 years or older and admitted to the University Hospital of Pisa (Pisa, Italy) in March-April 2020 with COVID-19 related pneumonia (wild type). SARS-CoV-2 infection was confirmed by polymerase chain reaction in a nasopharyngeal swab, while pneumonia was demonstrated by CT scan. Members of the Pisa COVID group collected all the clinical information, including co-morbidities, drug intake and routine laboratory data, which were de-identified and stored according to the recommendations of the Ethics Committee and made available to academic researchers. Quantification of oxylipins The MS-based targeted profiling of 60 oxylipins (e.g., prostaglandins, lipoxins, protectins, resolvins, hydroxy-and epoxy-fatty acids, F2-isoprostanes, F3-isoprostanes, F2-dihomoisoprostanes, and F4-neuroprostane) [18] [19] [20] was performed using micro-extraction by packed sorbent (MEPS) ultra-high performances liquid chromatography tandem mass spectrometry (MEPS-UHPLC-MS/MS) platform [21] [22] [23] . Briefly, plasma proteins were precipitated by the sequential addition of salts (i.e., 250 µL of CuSO4·5 H2O 10% w/v and 250 µL of Na2WO4·2 H2O 12% w/v) and acetonitrile (500 µL) to the plasma sample (500 µL). The supernatant was then diluted (1:6 v/v) with water and loaded onto the MEPS C18 cartridge. (Table S1 ). Compounds were quantified by calibration curves plotting the analyte to an internal standard peak area ratio (Quantifier transition) versus the corresponding concentration ratio. Table S2 lists the main analytical figures of merit of the MEPS-UHPLC-MS/MS platform. Figure S1 shows the chromatographic profiles for the sixty oxylipins.

Quantification of cytokines Plasma cytokines (i.e., IL-6, IL-1β, IL-10, TNF-α, and CCL2) and granulocyte-macrophage colony-stimulating factor (GM-CSF) were quantified by automated ELISA assays according to the manufacturer's instructions (see supplementary information).

Datasets D1 and D2, which include the plasma levels of 48 oxylipins (TableS2) and 5 cytokines (IL-6, IL-1β, IL-10, TNF-α, and CCL2, Table S4 ), respectively, were obtained from the analyses of 70 samples collected from patients hospitalised in COVID-19 wards (patients = 32, samples = 43) and ICUs (patients = 24, samples = 27) (four patients were in both groups).

Twelve out of sixty oxylipins (Table S2) were excluded from D1 as the concentrations were below the limit of quantification for more than 50% of samples. A decimal logarithmic transform was used to correct for asymmetry characterising all the variables [24] . Samples were randomly split into a training (n = 56) and a test set (n = 14): the former was used to build the models and the latter to independently estimate performances and consistency.

Data were analysed by a multivariate exploratory method (principal component analysis, PCA) [25, 26] .

In the present study, PCA was applied after column autoscaling to ensure the same importance a priori to be given to all variables, irrespectively of their magnitude [27] .

Fisher's canonical variable was then computed in the plane described by the two lowest-order PCs, as the direction that maximises the ratio between inter-class and intra-class variances [28] .

This axis represents the most discriminant direction, and its loadings, multiplied by the loadings of the PCs considered, indicate the importance of the original input variables in the differentiation of the classes.

Finally, a multivariate receiver operating characteristic (ROC) curve was obtained by varying the confidence level of unequal class models and computing, at each step, sensitivity and specificity [29] [30] [31] . Multivariate data processing was performed by in-house Matlab routines (The MathWorks, Inc., Natick, USA, Version 2019b).

Between 1 March and 30 April 2020, 52 patients were admitted to Pisa University Hospital, 28

in COVID-19 wards, 20 in ICUs and 4, initially hospitalised in COVID-19 wards, who were then transferred to the ICUs due to deteriorating health conditions. The clinical characteristics, comorbidities and outcome of patients are reported in Table 1 . Baseline characteristics were generally similar between the two groups, with the exception of diabetes prevalence, which was higher in ICU patients, and of the Horowitz index for lung function (P/F ratio) that identified the acute hypoxemic respiratory condition of ICU patients.

These patients were also characterized by leucocytosis, lymphocytopenia and higher D-dimer levels, which were all related to the enhanced inflammatory response and more severe viral infection. Pharmacological therapy was similar in the two-study group except for the antiretroviral drugs that were more represented in the ward group.

The full data-set concerning the plasma concentrations of oxylipins and cytokines are reported in Table S3 and Table S4 , respectively. A clear separation of samples collected from COVID-19 wards (blue symbols) and ICUs (red symbols) is visible in the oxylipin score plot ( Figure   1a ), whereas it is not observed in the case of cytokines (Figure 1b ). This pattern is consistent for items of both the training set (full symbols), used to build the model and calculate PCs, and the test set (empty symbols), which were simply projected onto the PC plane [24] for validation purposes.

Interestingly, many borderline samples were collected from COVID-19 ward patients who were subsequently transferred to the ICUs a few days after sample collection due to their deteriorating health conditions. Samples collected from the same patient on different days (stars) are connected by coloured arrows: shifts in the oxylipin score plot from the blue to the red zone seem to replicate the movements of patients from COVID-19 wards to the ICUs, however this is not reflected in the cytokine score plot.

J o u r n a l P r e -p r o o f Figure S3 ).

To further confirm the classification capacity of the full oxylipin set, a multivariate ROC curve was obtained by the UNEQ class-modelling strategy (Figure 3 ). The multivariate model was computed using the four lowest-order PCs as the input variables and COVID-19 ward samples as the target class. The resulting area under the curve (AUC, 0.92) exceeded all the AUC outcomes obtained for individual oxylipins (selected univariate ROC curves are reported in Figure S4 ). prevents oxidation of the RyR ryanodine receptors, a family of Ca 2+ release channels that controls the intracellular calcium exchange and whose oxidation may cause leaks of Ca 2+ and lead to heart failure, pulmonary insufficiency and cognitive dysfunction in COVID-19 [36] .

Furthermore, TX-B2 was the only prostanoid with an enzymatic origin over-expressed in ICU patients, which agrees with the need for heparin therapy in these patients to prevent microcirculatory damage.

Inflammation is a highly coordinated transcriptional process whose evolution towards resolution or persistence depends on a dynamic balance between pro-and anti-inflammatory mediators. In a controlled inflammatory process, immune tissue-resident cells activate processes producing chemokines and cytokines. Endothelial cells then respond thereby facilitating the recruitment of neutrophils (first) and monocytes (at a later stage), which differentiate into pro-inflammatory M1 macrophages ( Figure 4 ) [37] . Pro-inflammatory cytokines activate the phospholipase A2 enzymes, which cause the release from membranes of AA, which is then converted into prostanoids or leukotrienes by cell-specific enzymatic activities. This phase is characterized by a prevalence of COX-2, both in neutrophils and M1macrophages, and 5-LOX activity, above all in neutrophils. COX-2 and 5-LOX are responsible for the production of prostaglandins (PGD2 and PGE2) and leukotrienes (LTs), respectively [38] .

J o u r n a l P r e -p r o o f The switch of lipid mediators from prostanoids to lipoxins and SPMs (i.e., resolvins, protectins, and maresins) is critical for inflammation resolution [39] . In fact, PGE2 facilitates the transformation of pro-inflammatory M1 into anti-inflammatory M2-macrophages characterized by the up-regulation of the 15-LOX enzyme, which is primarily involved in the synthesis of SPMs [40] . PGE2 also helps to switch the pro-inflammatory (e.g., TNF-α, IL-1β, and IL-6) into the anti-inflammatory interleukins synthetized by M2-macrophages (e.g., IL-10) [41] . The For these reasons, we speculate that the oxylipin pattern observed in ICU patients affected by severe COVID-19 mirrors an impaired inflammation response which is part of a prolonged and unsolvable pro-inflammatory status characterized by a relative lack of oxylipins produced from the enzymatic processing of PUFAs. The impaired production of anti-inflammatory and proresolving oxylipins is not a consequence of the reduced availability of PUFA precursors, which appear unchanged or even increased in ICU patients. The presence of soluble isoprostanoids in both classes of patients confirms that the availability of membrane PUFAs is not a limitation for their enzymatic processing [43] .

Much remains to be understood regarding the pathogenetic mechanism of COVID-19, however defective innate and specific immune responses are likely to be critical features [44] . Schulte-Schrepping et al. [45] showed an increase in dysfunctional neutrophils and monocytes in severe COVID-19 patients that seems to be in agreement with our findings.

A massive endothelial dysfunction resulting from the cytokine storm and the infiltration of SARS-CoV-2 is a further characteristic of severe COVID-19 that determines the loss of vessel barrier, the promotion of leukocyte infiltration, and the activation of platelet aggregation and coagulation [44, 46] . Interestingly, in ICU patients we found higher levels of TX-B2, the biological inactive catabolite of TX-A2 (a potent activator of platelet aggregation and thus of coagulation). This is in line with the diffused microthrombosis observed in COVID-19 [44, 47] and with the lower levels of EETs, which are mainly produced by endothelial epoxygenase and are important mediators of all pro-resolving mechanisms [48] , including the lipid mediator class switching [49, 50] .

In conclusion, our powerful in-house oxylipidomics platform revealed that the more severe 

The authors declare no competing interests.

All de-identified data will be shared upon approval from the IMPRE-COVID-19 steering committee and a signed data access agreement. All requests should be sent to denise.biagini@dcci.unipi.it.

The Supporting Information section contains a detailed description of materials, 

Institutional funds from the University of Pisa supported the study.

The funders of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. All the authors had full access to all data and shared the final responsibility for the decision to submit for publication.

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