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<?covid-19-tdm?>
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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
<issn pub-type="epub">1664-3224</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fimmu.2021.784989</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Activation of Sphingomyelinase-Ceramide-Pathway in COVID-19 Purposes Its Inhibition for Therapeutic Strategies</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Abusukhun</surname>
<given-names>Murad</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1528632"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Winkler</surname>
<given-names>Martin S.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1181562"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>P&#xf6;hlmann</surname>
<given-names>Stefan</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/21311"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Moerer</surname>
<given-names>Onnen</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1451919"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Meissner</surname>
<given-names>Konrad</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tampe</surname>
<given-names>Bj&#xf6;rn</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/576062"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hofmann-Winkler</surname>
<given-names>Heike</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bauer</surname>
<given-names>Michael</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/587377"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Gr&#xe4;ler</surname>
<given-names>Markus H.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/245741"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Claus</surname>
<given-names>Ralf A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/109967"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital</institution>, <addr-line>Jena</addr-line>, <country>Germany</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Center for Molecular Biomedicine (CMB), Jena University Hospital</institution>, <addr-line>Jena</addr-line>, <country>Germany</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Anesthesiology, Emergency and Intensive Care Medicine, University of G&#xf6;ttingen</institution>, <addr-line>G&#xf6;ttingen</addr-line>, <country>Germany</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Infection Biology Unit, German Primate Center-Leibniz Institute for Primate Research</institution>, <addr-line>G&#xf6;ttingen</addr-line>, <country>Germany</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Faculty of Biology and Psychology, University G&#xf6;ttingen</institution>, <addr-line>G&#xf6;ttingen</addr-line>, <country>Germany</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Department of Nephrology, University of G&#xf6;ttingen</institution>, <addr-line>G&#xf6;ttingen</addr-line>, <country>Germany</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Center for Sepsis Control and Care (CSCC), Jena University Hospital</institution>, <addr-line>Jena</addr-line>, <country>Germany</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Beate E. Kehrel, University Hospital M&#xfc;nster, Germany</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Ursula Rescher, University of M&#xfc;nster, Germany; Aikaterini Alexaki, Centre Hospitalier Universitaire Vaudois (CHUV), Switzerland</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Ralf A. Claus, <email xlink:href="mailto:Ralf.claus@med.uni-jena.de">Ralf.claus@med.uni-jena.de</email> </p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work and share first authorship</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Inflammation, a section of the journal Frontiers in Immunology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>20</day>
<month>12</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>12</volume>
<elocation-id>784989</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>09</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>02</day>
<month>12</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Abusukhun, Winkler, P&#xf6;hlmann, Moerer, Meissner, Tampe, Hofmann-Winkler, Bauer, Gr&#xe4;ler and Claus</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Abusukhun, Winkler, P&#xf6;hlmann, Moerer, Meissner, Tampe, Hofmann-Winkler, Bauer, Gr&#xe4;ler and Claus</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Effective treatment strategies for severe coronavirus disease (COVID-19) remain scarce. Hydrolysis of membrane-embedded, inert sphingomyelin by stress responsive sphingomyelinases is a hallmark of adaptive responses and cellular repair. As demonstrated in experimental and observational clinical studies, the transient and stress-triggered release of a sphingomyelinase, SMPD1, into circulation and subsequent ceramide generation provides a promising target for FDA-approved drugs. Here, we report the activation of sphingomyelinase-ceramide pathway in 23 intensive care patients with severe COVID-19. We observed an increase of circulating activity of sphingomyelinase with subsequent derangement of sphingolipids in serum lipoproteins and from red blood cells (RBC). Consistent with increased ceramide levels derived from the inert membrane constituent sphingomyelin, increased activity of acid sphingomyelinase (ASM) accurately distinguished the patient cohort undergoing intensive care from healthy controls. Positive correlational analyses with biomarkers of severe clinical phenotype support the concept of an essential pathophysiological role of ASM in the course of SARS-CoV-2 infection as well as of a promising role for functional inhibition with anti-inflammatory agents in SARS-CoV-2 infection as also proposed in independent observational studies. We conclude that large-sized multicenter, interventional trials are now needed to evaluate the potential benefit of functional inhibition of this sphingomyelinase in critically ill patients with COVID-19.</p>
</abstract>
<kwd-group>
<kwd>molecular biology of critical care</kwd>
<kwd>ceramide</kwd>
<kwd>organ failure</kwd>
<kwd>sphingomyelinase</kwd>
<kwd>FIASMA</kwd>
<kwd>drug repurposing</kwd>
<kwd>molecular markers</kwd>
</kwd-group>
<counts>
<fig-count count="4"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="99"/>
<page-count count="12"/>
<word-count count="5704"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>The rampant spreading of the novel severe acute respiratory virus-2 (SARS-CoV-2) with an estimated global infection rate of 10% causing coronavirus disease 2019 (COVID-19) has resulted in an unprecedented pandemic crisis of health care systems worldwide (<xref ref-type="bibr" rid="B1">1</xref>). COVID-19 is a new disease entity and severe cases have a high mortality due to the fact that SARS-CoV-2 is systemic and potentially affects all organs (<xref ref-type="bibr" rid="B2">2</xref>&#x2013;<xref ref-type="bibr" rid="B4">4</xref>). The clinical course of COVID-19 is highly variable, which is also reflected by a wide range of symptoms, such as an asymptomatic course up to self-induced, over-exuberant inflammation and acute respiratory distress syndrome (ARDS) with multiple organ dysfunction and death (<xref ref-type="bibr" rid="B5">5</xref>). The underlying reasons for heterogeneous clinical courses are not yet completely understood, but current data suggest that a plethora of epidemiological factors such as age, gender or pre-existing conditions and its medical treatment combined with genetic susceptibility and as well as virus associated factors such as viral load contribute to the outcome of patients (<xref ref-type="bibr" rid="B6">6</xref>&#x2013;<xref ref-type="bibr" rid="B10">10</xref>). Beside continuously increasing vaccination rates in developed countries, therapeutic strategies targeting the immune response, the cytokine release, and endothelial cell barrier integrity are under development in larger clinical trials (<xref ref-type="bibr" rid="B11">11</xref>). However, a majority of trials is based on vague assumptions regarding the pathophysiological mechanisms of COVID-19, and the development of causative treatment strategies is hampered due to lack of disease-specific knowledge (<xref ref-type="bibr" rid="B12">12</xref>&#x2013;<xref ref-type="bibr" rid="B14">14</xref>).</p>
<p>As an adaptive response mechanism towards cellular damage, the conserved stress responsive enzyme acid sphingomyelinase (ASM, systematically SMPD1) is released into circulation and is held responsible for the rapid and transient formation of ceramide, which is a highly bioactive lipid mediator involved in cellular activation, damage repair, pathogen penetration, danger signaling, maintenance of endothelial integrity and induction of apoptosis (<xref ref-type="bibr" rid="B15">15</xref>&#x2013;<xref ref-type="bibr" rid="B17">17</xref>). ASM is released from lysosomes to the outer leaflet of cellular membranes, which are composed from high amounts of sphingomyelin functioning as the embedded substrate to the enzyme. ASM occurs at a low level under physiological conditions, however, the release of the enzyme as a consequence of lysosomal exocytosis in response to stress (<xref ref-type="bibr" rid="B18">18</xref>) is suggested to be mostly relevant as a major source of circulating activity in the course of sepsis (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B20">20</xref>) and pneumonia (<xref ref-type="bibr" rid="B21">21</xref>). Activity levels of the enzyme are discriminative for prediction of unfavorable outcome in patients with polymicrobial sepsis (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B22">22</xref>).</p>
<p>Recently<italic>, in-vitro</italic> observations showed that ASM is also activated upon infection of epithelial cells with SARS-CoV-2. Neutralization or inhibition of subsequent ceramide generation is able to prevent both entry and propagation of SARS-CoV-2 as well as of pseudoviral particles presenting SARS-CoV-2 spike protein, a <italic>bona fide</italic> system mimicking SARS-CoV-2 infection (<xref ref-type="bibr" rid="B23">23</xref>&#x2013;<xref ref-type="bibr" rid="B25">25</xref>).</p>
<p>There is accumulating evidence that a substantial number of critically ill COVID-19 patients frequently exhibit viral RNAemia accompanied with a dysregulated immune response (<xref ref-type="bibr" rid="B26">26</xref>) fulfilling SEPSIS-III criteria (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B28">28</xref>) with hyperinflammation manifesting as a cytokine storm or as cytokine release syndrome, which in turn contributes to the high mortality rates (<xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). From a molecular perspective, inhibition and inactivation of ASM provide anti-inflammatory properties by a decrease of tumor necrosis factor (TNF) &#x3b1; and interleukin (IL)-6 as well as - in a reflective manner - of IL-10 (<xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B32">32</xref>), which are all highly correlated with morbidity and mortality rate of COVID-19 (<xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B34">34</xref>).</p>
<p>In this inter-relationship, we hypothesize that activation of sphingomyelinase-ceramide pathway might play a crucial role in the pathogenesis of COVID-19: (1) epithelial tissue damage to infection and subsequent repair might result in the serum appearance of ASM in critically ill patients, of which the activity is associated with severity markers, as well as (2) in rather long-lasting compartments (lipoproteins and erythrocytic membranes) the change of activity is mirrored by an increase of ceramides, reflecting the deteriorated status of the patients.</p>
</sec>
<sec id="s2">
<title>Methods</title>
<p>Twenty-three COVID-19 patients treated in the intensive care unit (ICU) of the Department of Anesthesiology at G&#xf6;ttingen University Medical Centre (UMG) from March 2020 to May 2020 were enrolled into this study. The local ethics board at UMG approved inclusion of all ICU patients (reference 15/4/19&#xdc;). Informed consent has been obtained from patients or their legal representatives from all study participants prior to inclusion. Data from this report are partially achieved from a re-analysis of samples firstly reported in 2021<xref ref-type="fn" rid="fn1">
<sup>1</sup>
</xref>.</p>
<p>For clinical evaluation, SOFA scores were calculated on admission according to the published guidelines (<xref ref-type="bibr" rid="B35">35</xref>). Within the first 24h after inclusion, serum samples were taken to measure ceramide profile and circulating sphingomyelinase activity. Leukocyte-free RBC were harvested from separate samples by density gradient centrifugation, washed and stored in plasma-free conditions at 4&#xb0;C.</p>
<p>Ceramide measurements were performed according to an established protocol using liquid chromatography coupled to triple-quadrupole mass spectrometry (LC-MS/MS) (<xref ref-type="bibr" rid="B36">36</xref>). From serum samples as well as pelleted RBC, proteins were precipitated by addition of methanol supplemented with appropriate internal standard solutions. Following separation of supernatant, evaporation and resolubilization, detection was performed with the QTrap triple-quadrupole mass spectrometer (Sciex, Darmstadt, Germany) interfaced with the 1100 series chromatograph and the Hitachi Elite LaChrom column oven and autosampler. Positive electrospray ionization (ESI) LC/MS/MS analysis was used for detection of sphingomyelins, positive atmospheric pressure chemical ionization (APCI) for ceramides. Standard curves were generated by adding increasing concentrations of ceramide up to 100 pmol of the internal standard C15-ceramide. Linearity of the standard curves and correlation coefficients were obtained by linear regression analyses (r<sup>2</sup> &gt; 0.99). Data analyses were performed using Analyst 1.6 (Sciex).</p>
<p>For determination of circulating sphingomyelinase activity, serum samples were dissolved with reaction buffer and supplemented with substrate solution. After incubation, extraction, evaporation and resolubilization, detection of C17-Cer (d18:1) for the conversion from C17-SM (d18:1) was performed with the API2000 triple-quadrupole mass spectrometer.</p>
<p>For statistical analysis, primary variables were ceramide isoforms (n=6) either in serum or RBC, and C17-Cer(d18:1) as product of sphingomyelinase activity. Outliers were identified according to the ROUT method with the desired maximum false discovery rate Q set to 1% (<xref ref-type="bibr" rid="B37">37</xref>). Differences between two groups were tested for significance using the unpaired Student&#x2019;s t-test with nonparametric correction using the Mann-Whitney U-test. A p-value &lt;0.05 was considered to be significant. Statistical analyses were performed using Graph Pad Prism 7.0a, April 2016 (La Jolla, CA, USA). Graphical illustration of variations and principal component analyses were performed using metaboanalyst platform [5.0 (<xref ref-type="bibr" rid="B38">38</xref>)].</p>
<p>Additional detail on the methods for making these measurements is provided in an online data supplement.</p>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Study Population</title>
<p>In order to investigate the ASM/ceramide signaling in SARS-CoV-2 infection, blood samples of 23 patients and six healthy volunteers were collected. Clinical data in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> summarize socio-demographic and selected clinical characteristics of the study group (day 1 of patients at intensive care unit due to COVID-19) and healthy controls. All patients received standard treatment by the time of admission, which did not include specific anti-viral or general anti-inflammatory drugs such as dexamethasone, because it was not standard of care at time of inclusion. The clinical severity assessment by use of sequential organ failure assessment (SOFA) and the simplified acute physiology score (SAPS II) were 9 (5-11, SOFA) and 41 (34-49, SAPS II) at enrollment. Predicted mortality rate of COVID-19 patients was matching that observed at ICU (26.6. vs. 30%). Parameters of healthy controls were all found in normal range. In contrast, a significant reduction in hemoglobin, hematocrit, RBC count, mean corpuscular hemoglobin concentration (MCHC), serum albumin, and lipoproteins were observed in COVID-19 patients.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Socio-demographic and clinical parameters of patients and healthy controls.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Parameter</th>
<th valign="top" align="center">Normal range</th>
<th valign="top" align="center">COVID-19</th>
<th valign="top" align="center">Healthy controls</th>
<th valign="top" align="center">p-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">n</td>
<td valign="top" align="center"/>
<td valign="top" align="center">23</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Hemoglobin, g/dL</td>
<td valign="top" align="center">13.5-17.5</td>
<td valign="top" align="center">10.5 (8.8-12.5)</td>
<td valign="top" align="center">15.6 (14.0-15.9)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Hematocrit, %</td>
<td valign="top" align="center">39-51</td>
<td valign="top" align="center">33 (27-37)</td>
<td valign="top" align="center">46 (41-46)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Red blood cells, 10<sup>6</sup>/&#xb5;L</td>
<td valign="top" align="center">4.4-5.9</td>
<td valign="top" align="center">3.79 (3.17-4.26)</td>
<td valign="top" align="center">5.1 (4,3-5.3)</td>
<td valign="top" align="center">&lt;0.01</td>
</tr>
<tr>
<td valign="top" align="left">MCV, fL</td>
<td valign="top" align="center">81-95</td>
<td valign="top" align="center">87 (77-93)</td>
<td valign="top" align="center">91 (86-95)</td>
<td valign="top" align="center">0.219</td>
</tr>
<tr>
<td valign="top" align="left">MCH, pg</td>
<td valign="top" align="center">26-32</td>
<td valign="top" align="center">28 (24-31)</td>
<td valign="top" align="center">31 (29-32)</td>
<td valign="top" align="center">0.104</td>
</tr>
<tr>
<td valign="top" align="left">MCHC, g/dL</td>
<td valign="top" align="center">32-36</td>
<td valign="top" align="center">32.6 (31.5-33.3)</td>
<td valign="top" align="center">34 (33.8-34.2)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Platelets, 10<sup>3</sup>/&#xb5;L</td>
<td valign="top" align="center">150-350</td>
<td valign="top" align="center">195 (131-327)</td>
<td valign="top" align="center">285 (245-309)</td>
<td valign="top" align="center">0.343</td>
</tr>
<tr>
<td valign="top" align="left">Leucocytes, 10<sup>3</sup>/&#xb5;L</td>
<td valign="top" align="center">4.0-11.0</td>
<td valign="top" align="center">11.1 (5.6-13.6)</td>
<td valign="top" align="center">5.6 (5.5-7.2)</td>
<td valign="top" align="center">0.110</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Lymphocyte, %</td>
<td valign="top" align="center">20-45</td>
<td valign="top" align="center">9.5 (5.9-25.1)</td>
<td valign="top" align="center">37.0 (33.0-47.5)</td>
<td valign="top" align="center">&lt;0.01</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Monocytes, %</td>
<td valign="top" align="center">3-13</td>
<td valign="top" align="center">7.1 (4.2-8.2)</td>
<td valign="top" align="center">8.0 (7.0-9.5)</td>
<td valign="top" align="center">0.148</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Eosinophiles, %</td>
<td valign="top" align="center">&#x2264;8</td>
<td valign="top" align="center">1.0 (0.35-1.5)</td>
<td valign="top" align="center">3.0 (2.5-3.0)</td>
<td valign="top" align="center">&lt;0.05</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Basophiles, %</td>
<td valign="top" align="center">&#x2264;2</td>
<td valign="top" align="center">0.40 (0.15-1.0)</td>
<td valign="top" align="center">0.05 (0.03-0.08)</td>
<td valign="top" align="center">N/D</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Neutrophiles, %</td>
<td valign="top" align="center">40-76</td>
<td valign="top" align="center">69 (56-82)</td>
<td valign="top" align="center">52 (41-53)</td>
<td valign="top" align="center">&lt;0.05</td>
</tr>
<tr>
<td valign="top" align="left">Serum albumin, g/dL</td>
<td valign="top" align="center">3.4-5.5</td>
<td valign="top" align="center">2.1 (1.7-2.3)</td>
<td valign="top" align="center">4.7 (4.6-4.7)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Cholesterol, mg/dL</td>
<td valign="top" align="center">&#x2264;200</td>
<td valign="top" align="center">120 (96-143)</td>
<td valign="top" align="center">225 (178-246)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Triglycerides, mg/dl</td>
<td valign="top" align="center">&#x2264;150</td>
<td valign="top" align="center">135 (102-243)</td>
<td valign="top" align="center">100 (94-141)</td>
<td valign="top" align="center">0.182</td>
</tr>
<tr>
<td valign="top" align="left">LDL mg/dL</td>
<td valign="top" align="center">&#x2264;115</td>
<td valign="top" align="center">71 (50-85)</td>
<td valign="top" align="center">150 (124-183)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">HDL mg/dL</td>
<td valign="top" align="center">&gt;40</td>
<td valign="top" align="center">18 (11-32)</td>
<td valign="top" align="center">54 (44-64)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Parameter</bold>
</td>
<td valign="top" align="center">
<bold>Normal range</bold>
</td>
<td valign="top" align="center">
<bold>COVID-19</bold>
</td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left">SARS-CoV-2, GE/reaction</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">468 (28-22011)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">Age, y</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">69 (66-75)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">Died, n (%)</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">7 (30%)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">ICU days</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">16 (7-24)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">ECMO, n (%)</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">3 (13%)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">SAPS II</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">41 (34-49)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">Predicted mortality, %</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">26.6 (15.3-43.8)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">SOFA</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">9 (5-11)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">FiO<sub>2</sub>
</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">0.50 (0.37-0.75)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">paO<sub>2</sub>, mmHg</td>
<td valign="top" align="center">65-105</td>
<td valign="top" align="center">73 (66-88)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">paCO<sub>2</sub>, mmHg</td>
<td valign="top" align="center">36-42</td>
<td valign="top" align="center">44 (36-62)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">paO<sub>2</sub>/FiO<sub>2</sub>
</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">133 (86-217)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">SpO<sub>2</sub>
</td>
<td valign="top" align="center">94-98</td>
<td valign="top" align="center">96 (95-98)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">pH</td>
<td valign="top" align="center">7.34-7.45</td>
<td valign="top" align="center">7.42 (7.34-7.46)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">Temperature, &#xb0;C</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">38.0 (37.0-38.5)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">D-Dimers, mg/L</td>
<td valign="top" align="center">&lt;0.5</td>
<td valign="top" align="center">1.34 (0.72-3.52)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">C-reactive protein, mg/dL</td>
<td valign="top" align="center">&#x2264;5</td>
<td valign="top" align="center">118.7 (29.7-186.6)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">Ferritine, &#xb5;g/L</td>
<td valign="top" align="center">22-275</td>
<td valign="top" align="center">732 (163-1337)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">Procalcitonin, &#xb5;g/L</td>
<td valign="top" align="center">&lt;0.07</td>
<td valign="top" align="center">0.50 (0.15-1.30)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">Interleukin-6, pg/mL</td>
<td valign="top" align="center">&lt;7</td>
<td valign="top" align="center">75.4 (45.1-514.1)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
<tr>
<td valign="top" align="left">Lactate, mmol/L</td>
<td valign="top" align="center">&#x2264;1.8</td>
<td valign="top" align="center">1.1 (0.6-1.6)</td>
<td valign="top" colspan="2" align="left"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>GE, genome equivalent; N/A, not available.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Metabolite Detection</title>
<p>First, we analyzed the pattern of sphingomyelin in lipid extracts of red blood cells and serum samples. Analysis of serum samples revealed that sphingomyelin levels in circulating lipoproteins were decreased in COVID-19 patients as compared to healthy controls (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>). Since host response and hypoxia have profound effects on RBCs&#x2019; morphology, rheology and functional activity (<xref ref-type="bibr" rid="B39">39</xref>), we thus sought to assess the composition of this cellular subpopulation. Similar results were obtained in RBCs, a reduction of sphingolipid content in these cells supports the concept of a deranged sphingomyelin balance in RBC-membranes in COVID-19 (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1B</bold>
</xref>). Next, we analyzed metabolites and degradation products of sphingomyelin. Therefore, we analyzed ceramide species with a naturally occurring sphingoid backbone (d18:1), but without any modification (n=11) with a chain length in a range between 12 and 26 carbon atoms and in part with an unsaturated double bond (<italic>i.e.</italic> 12:0, 14:0, 16:0, 18:0, 18:1, 20:0, 22:0, 24:0, 24:1, 26:0 and 26:1). Thereof, six ceramide species were found above lower limit of detection (LOD) in &gt; 75% of all samples, which were included in subsequent analyses. Our results - presenting a specific disease pattern of concurring ceramide specimen - are in line with information from previously published cohorts (<xref ref-type="bibr" rid="B21">21</xref>). In serum as well as in RBC, Cer was found to be increased in COVID-19 patients and this increase was paralleled by a decrease of SM (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Heatmap of spingolipids (SM and ceramides) as well as ASM activity either in <bold>(A)</bold> serum and <bold>(B)</bold> RBC. Shown are hierarchical cluster analyses from data obtained by monitoring the profile of sphingomyelins and ceramides as well as ASM activity (measured in serum samples). Specimen of sphingolipids are given in rows, individual patients samples in columns comparing patients (P1 &#x2013;P23, marked in green) and healthy controls (HC 1-6, gray). Color code: increase in sphingolipid content is given in red, decrease in blue. Distance measure is given in euclidian manner.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-12-784989-g001.tif"/>
</fig>
</sec>
<sec id="s3_3">
<title>Changes in Ceramide Profile in Patients With COVID-19</title>
<p>Principal component analysis was then used to test whether differences in the ceramide profile reflected the clinical diagnosis (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). In both compartments, serum samples as well as extracts from RBC, values clustered distinctly between patients and healthy controls. For RBC the first and second principal components parameters were 76.5 and 12.1% (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>), for serum 68.4 and 15.6% (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>), respectively.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Reprogramming of ceramide generation. Variation of ceramide profile either in RBC <bold>(A)</bold> or serum <bold>(B)</bold> in patients with COVID-19 compared to healthy volunteers. Principal component analysis (PCA) based on concentration profile of six ceramide specimen (16:0, 18:0, 20:0, 22:0, 24:0, 24:1) that passed the quality screen. Each circle represents the centroid of all samples in the representative group at day 1 of intensive care of COVID-19 patients). Healthy controls are given as asterisks, patients in triangles.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-12-784989-g002.tif"/>
</fig>
<p>Concentration levels of the majority of ceramide specimens were significantly changed in patients with COVID-19 with respect to controls, either in serum or RBC. The absolute amount of investigated specimen varied with respect to expected baseline levels (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). An overview of resulting p-values comparing the groups is given in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. Median values of individual ceramide specimen including interquartile range (Q1/Q3) are given in <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref> showing increased values in both compartments, either in serum or RBC.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Ceramide profile in lipid extracts obtained from RBC and from serum samples. In patients with COVID-19, ceramide synthesis is increased in all specimen passing quality screen in RBC, and nearly in all investigated in serum (one exception: 24:0). Total amount of ceramide specimen is differing as expected between serum and RBC, absolute values are given in <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>. Statistical analysis was performed using Mann-Whitney U-Test and p-values &lt;0.05 were considered to be significant. COVID-19 <italic>vs.</italic> healthy controls: *p &lt; 0.05; **p &lt; 0.01; ***p &lt; 0.001. Exact parameters indicating statistical difference area also given in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-12-784989-g003.tif"/>
</fig>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Overview on p-values on day of admission (day 1) to intensive care in samples obtained from COVID-19 patients either from serum or RBC with respect to ceramide concentration differing in chain length of acylated fatty acid 16:0 to 24:1.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" align="center"/>
<th valign="top" align="center">16:0</th>
<th valign="top" align="center">18:0</th>
<th valign="top" align="center">20:0</th>
<th valign="top" align="center">22:0</th>
<th valign="top" align="center">24:0</th>
<th valign="top" align="center">24:1</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>HC vs. COVID-19</bold>
</td>
<td valign="top" align="left">RBC</td>
<td valign="top" align="center">0.001</td>
<td valign="top" align="center">&lt; 0.0005</td>
<td valign="top" align="center">0.004</td>
<td valign="top" align="center">0.004</td>
<td valign="top" align="center">&lt; 0.05</td>
<td valign="top" align="center">0.007</td>
</tr>
<tr>
<td valign="top" align="left">serum</td>
<td valign="top" align="center">0.007</td>
<td valign="top" align="center">0.001</td>
<td valign="top" align="center">&lt; 0.0003</td>
<td valign="top" align="center">0.001</td>
<td valign="top" align="center">0.028</td>
<td valign="top" align="center">0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Statistical analysis was performed using Mann-Whitney U-Test and p-values &lt;0.05 were considered to be significant.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Comparing concentration of ceramides differing in chain length of acylated fatty acid 16:0 to 24:1.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">RBC [nmol/mL]</th>
<th valign="top" align="center"/>
<th valign="top" align="center">16:0</th>
<th valign="top" align="center">18:0</th>
<th valign="top" align="center">20:0</th>
<th valign="top" align="center">22:0</th>
<th valign="top" align="center">24:0</th>
<th valign="top" align="center">24:1</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>COVID-19</bold>
</td>
<td valign="top" align="left">median</td>
<td valign="top" align="center">3.42</td>
<td valign="top" align="center">1.10</td>
<td valign="top" align="center">0.33</td>
<td valign="top" align="center">2.00</td>
<td valign="top" align="center">1.82</td>
<td valign="top" align="center">6.47</td>
</tr>
<tr>
<td valign="top" align="left">Q1/Q3</td>
<td valign="top" align="center">2,98/4,44</td>
<td valign="top" align="center">0,83/1,37</td>
<td valign="top" align="center">0,26/0,40</td>
<td valign="top" align="center">1,76/2,59</td>
<td valign="top" align="center">1,44/2,42</td>
<td valign="top" align="center">5,49/8,05</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Healthy controls</bold>
</td>
<td valign="top" align="left">median</td>
<td valign="top" align="center">1.36</td>
<td valign="top" align="center">0.43</td>
<td valign="top" align="center">0.20</td>
<td valign="top" align="center">1.22</td>
<td valign="top" align="center">1.31</td>
<td valign="top" align="center">3.43</td>
</tr>
<tr>
<td valign="top" align="left">Q1/Q3</td>
<td valign="top" align="center">1,36/1,38</td>
<td valign="top" align="center">0,42/0,47</td>
<td valign="top" align="center">0,12/0,20</td>
<td valign="top" align="center">0,97/1,34</td>
<td valign="top" align="center">1,18/1,46</td>
<td valign="top" align="center">3,01/3,60</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Serum [nmol/mL]</bold>
</td>
<td valign="top" align="center"/>
<td valign="top" align="center">
<bold>16:0</bold>
</td>
<td valign="top" align="center">
<bold>18:0</bold>
</td>
<td valign="top" align="center">
<bold>20:0</bold>
</td>
<td valign="top" align="center">
<bold>22:0</bold>
</td>
<td valign="top" align="center">
<bold>24:0</bold>
</td>
<td valign="top" align="center">
<bold>24:1</bold>
</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>COVID-19</bold>
</td>
<td valign="top" align="left">median</td>
<td valign="top" align="center">1.41</td>
<td valign="top" align="center">0.39</td>
<td valign="top" align="center">0.14</td>
<td valign="top" align="center">0.89</td>
<td valign="top" align="center">0.78</td>
<td valign="top" align="center">1.09</td>
</tr>
<tr>
<td valign="top" align="left">Q1/Q3</td>
<td valign="top" align="center">1,16/1,67</td>
<td valign="top" align="center">0,25/0,48</td>
<td valign="top" align="center">0,12/0,19</td>
<td valign="top" align="center">0,76/1,08</td>
<td valign="top" align="center">0,67/0,95</td>
<td valign="top" align="center">1,01/1,41</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Healthy controls</bold>
</td>
<td valign="top" align="left">median</td>
<td valign="top" align="center">0.89</td>
<td valign="top" align="center">0.15</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">0.37</td>
<td valign="top" align="center">0.60</td>
<td valign="top" align="center">0.52</td>
</tr>
<tr>
<td valign="top" align="left">Q1/Q3</td>
<td valign="top" align="center">0,77/1,03</td>
<td valign="top" align="center">0,10/0,16</td>
<td valign="top" align="center">0,05/0,06</td>
<td valign="top" align="center">0,33/0,47</td>
<td valign="top" align="center">0,48/0,61</td>
<td valign="top" align="center">0,50/0,54</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Given are the median values [nmol/mL] and the interquartile range Q1/Q3 either from serum or RBC samples. Data for statistical comparison are given in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_4">
<title>Activity of Circulating Sphingomyelinase as Potential Source of Deranged Ceramide Profiles</title>
<p>Considering the increase of all investigated ceramide specimen in COVID-19 patients in serum and RBC, we then tested whether the corresponding stress associated enzyme ASM - converting sphingomyelin to ceramide - was more abundant and/or more active in COVID-19 patients. Indeed, in serum of COVID-19 patients the enzyme activity was markedly increased: median 4.525 (Q25% 3.827; Q75% 5.832) nmol/(mL x h) as opposed to 0.948 nmol/(mL x h) (Q25% 0.857; Q75% 0.999) in healthy controls and this effect was statistically significant (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>) reflecting an inflammation-driven sphingolipid reprogramming. In patients with unfavorable outcome (n=7), the highly increased activity levels remained nearly unchanged, but in patients with recovery (n=16), we observed decreasing values (data not shown).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Activity levels of acid sphingomyelinase (ASM) in serum samples. Shown are medians with interquartile ranges of ASM activity levels from 23 severe COVID-19 patients and six volunteers as healthy controls, measured in separate aliquots used for ceramide profiling. Statistical significance was tested using the Mann-Whitney U-test; statistical difference is indicated by asterisks: ***p &lt; 0.0001.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-12-784989-g004.tif"/>
</fig>
</sec>
<sec id="s3_5">
<title>Association of ASM-Activity With Clinical Severity by Correlational Analyses</title>
<p>Correlating ASM activity with clinical parameters at day of ICU admission revealed a clear association of ASM activity and severity of COVID-19 (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). Most prominently, we found that the concentration of high density lipoprotein (HDL) negatively correlated with ASM-activity, followed by biomarkers of metabolic dysfunction such as base excess, concentration of lactate and hydrogen carbonate. Further, the concentration of long chain sphingomyelin from serum constituents (lipoproteins) was found to be negatively correlated with ASM-activity. A positive correlation was found for plasma magnesium concentration, alanine aminotransferase (ALT), total bilirubin, ferritin and lactate dehydrogenase.</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Correlational analysis of ASM-activity with clinical and laboratory data.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" align="center">rho</th>
<th valign="top" align="center">CI</th>
<th valign="top" align="center">p-value</th>
<th valign="top" align="center">Pairs</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">High density lipoprotein</td>
<td valign="top" align="center">-0.6379</td>
<td valign="top" align="center">-0,8466 to -0,2592</td>
<td valign="top" align="center">0.0025</td>
<td valign="top" align="center">20</td>
</tr>
<tr>
<td valign="top" align="left">Base Excess art.</td>
<td valign="top" align="center">-0.5721</td>
<td valign="top" align="center">-0,8012 to -0,1969</td>
<td valign="top" align="center">0.0043</td>
<td valign="top" align="center">23</td>
</tr>
<tr>
<td valign="top" align="left">Base Excess ven.</td>
<td valign="top" align="center">-0.5003</td>
<td valign="top" align="center">-0,7669 to -0,08661</td>
<td valign="top" align="center">0.0177</td>
<td valign="top" align="center">22</td>
</tr>
<tr>
<td valign="top" align="left">C26-SM (Serum)</td>
<td valign="top" align="center">-0.5310</td>
<td valign="top" align="center">-0,7790 to -0,1394</td>
<td valign="top" align="center">0.0091</td>
<td valign="top" align="center">23</td>
</tr>
<tr>
<td valign="top" align="left">Lactate ven.</td>
<td valign="top" align="center">0.5380</td>
<td valign="top" align="center">0,1375 to 0,7873</td>
<td valign="top" align="center">0.0098</td>
<td valign="top" align="center">22</td>
</tr>
<tr>
<td valign="top" align="left">Lactate art.</td>
<td valign="top" align="center">0.5218</td>
<td valign="top" align="center">0,1269 to 0,7739</td>
<td valign="top" align="center">0.0107</td>
<td valign="top" align="center">23</td>
</tr>
<tr>
<td valign="top" align="left">HCO<sub>3</sub> stand. art.</td>
<td valign="top" align="center">-0.5928</td>
<td valign="top" align="center">-0,8459 to -0,1216</td>
<td valign="top" align="center">0.0173</td>
<td valign="top" align="center">16</td>
</tr>
<tr>
<td valign="top" align="left">HCO<sub>3</sub> akt. art.</td>
<td valign="top" align="center">-0.4550</td>
<td valign="top" align="center">-0,7363 to -0,03981</td>
<td valign="top" align="center">0.0291</td>
<td valign="top" align="center">23</td>
</tr>
<tr>
<td valign="top" align="left">HCO<sub>3</sub>, stand. ven.</td>
<td valign="top" align="center">-0.5097</td>
<td valign="top" align="center">-0,8011 to -0,02305</td>
<td valign="top" align="center">0.0383</td>
<td valign="top" align="center">17</td>
</tr>
<tr>
<td valign="top" align="left">pH(T) ven.</td>
<td valign="top" align="center">-0.5012</td>
<td valign="top" align="center">-0,7673 to -0,08772</td>
<td valign="top" align="center">0.0175</td>
<td valign="top" align="center">22</td>
</tr>
<tr>
<td valign="top" align="left">pH ven.</td>
<td valign="top" align="center">-0.4825</td>
<td valign="top" align="center">-0,7570 to -0,06326</td>
<td valign="top" align="center">0.0229</td>
<td valign="top" align="center">22</td>
</tr>
<tr>
<td valign="top" align="left">Mg</td>
<td valign="top" align="center">0.5493</td>
<td valign="top" align="center">0,09609 to 0,8139</td>
<td valign="top" align="center">0.0182</td>
<td valign="top" align="center">18</td>
</tr>
<tr>
<td valign="top" align="left">Alanine aspartat transferase</td>
<td valign="top" align="center">0.4955</td>
<td valign="top" align="center">0,08016 to 0,7642</td>
<td valign="top" align="center">0.0190</td>
<td valign="top" align="center">22</td>
</tr>
<tr>
<td valign="top" align="left">total Bilirubin</td>
<td valign="top" align="center">0.4464</td>
<td valign="top" align="center">0,02901 to 0,7313</td>
<td valign="top" align="center">0.0327</td>
<td valign="top" align="center">23</td>
</tr>
<tr>
<td valign="top" align="left">Ferritin</td>
<td valign="top" align="center">0.4758</td>
<td valign="top" align="center">0,01312 to 0,7707</td>
<td valign="top" align="center">0.0395</td>
<td valign="top" align="center">19</td>
</tr>
<tr>
<td valign="top" align="left">Lactate dehydrogenase</td>
<td valign="top" align="center">0.4631</td>
<td valign="top" align="center">-0,003281 to 0,7640</td>
<td valign="top" align="center">0.0459</td>
<td valign="top" align="center">19</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Given are the rho-coefficient of correlation (Spearman), the interval of 95% confidence (CI), the absolute p-value (two tailed) and the number of available data for pairwise analysis. C26-SM sphingomyelin with an acylated fatty acid of 26 carbon atoms, respectively.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>In this observational trial, activation of plasma circulating sphingomyelinase in response to infection was found in COVID-19 patients undergoing intensive care treatment resulting in an increase of ceramide isoforms generated from inert membrane constituent sphingomyelin in RBC.</p>
<sec id="s4_1">
<title>Release of ASM by an Imbalanced Repair Mechanism</title>
<p>It might be speculated, that the origin of the circulating enzyme activity might be ascribed to loss of integrity of epithelial tissues in affected lungs, of which severe damage of alveolae beyond remodeling of parenchyma is manifest along histopathological findings of the disease (<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B41">41</xref>). Exocytosis of ASM is a common and rather protective mechanism for rapid membrane resealing and restoration of its integrity (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B42">42</xref>). The appearance of ASM in circulation is a sensitive, but unspecific event in patients with severe inflammation resulting from infection such as polymicrobial sepsis (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B20">20</xref>), pneumonia (<xref ref-type="bibr" rid="B21">21</xref>), radiation therapy (<xref ref-type="bibr" rid="B43">43</xref>) or chronic inflammation (<xref ref-type="bibr" rid="B44">44</xref>). In community-acquired pneumonia patients, Arshad et&#xa0;al. recently reported a nearly threefold increase of plasma ASM activity, its close correlation with severity markers (C-reactive protein, procalcitonin), a concomitant increase of SMPD1-expression in circulating white blood cells (twofold), and, most interestingly, a derangement of plasma ceramide profile (<xref ref-type="bibr" rid="B21">21</xref>), which is very similar to that we found in our study. There are several reports on correlations between plasma ceramide concentration and unfavorable outcome of critically ill patients (<xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B46">46</xref>), especially in the lungs (<xref ref-type="bibr" rid="B47">47</xref>). On a molecular level, ceramides have been reported to activate inflammatory pathways in several abnormal physiological circumstances involving insulin resistance, mitochondrial dysfunction and endoplasmatic reticulum stress (<xref ref-type="bibr" rid="B48">48</xref>&#x2013;<xref ref-type="bibr" rid="B51">51</xref>), which are attributed to worsen the clinical condition of COVID-19 patients (<xref ref-type="bibr" rid="B52">52</xref>&#x2013;<xref ref-type="bibr" rid="B54">54</xref>). Despite the fact, that we are only presenting ceramide data from accessible compartments from these patients (serum and RBC), a close similarity of membrane bound ceramides in bodies&#x2019; tissues with that we analyzed is persuasive, since the hydrolyzing capacity is restricted to ASM in these conditions.</p>
</sec>
<sec id="s4_2">
<title>Ceramide Functioning During Development of Long-Term Sequelae of COVID-19</title>
<p>As a long-term sequelae of COVID-19, lung fibrosis is characterized by deterioration of organ function and subsequent respiratory failure (<xref ref-type="bibr" rid="B55">55</xref>). Since high quality data regarding long-term clinical outcomes from COVID-19 survivors are still unavailable, predictions for long-term outcome thereof are speculative at best, but it is well known that lung fibrosis as a result of other diseases closely correlates with poor prognosis (<xref ref-type="bibr" rid="B56">56</xref>). The underlying, irreversible process is driven by sometimes excessive release of pro-fibrotic factors (<xref ref-type="bibr" rid="B56">56</xref>), especially TGF-&#x3b2; from injured lung tissue, turning a well-controlled healing response into a pathogenic fibrotic response (<xref ref-type="bibr" rid="B56">56</xref>, <xref ref-type="bibr" rid="B57">57</xref>). In follow-up chest imaging from severe courses, the presence of intestitial thickening, irregular interface and parenchymal bands have been suggested as predictors of COVID-19 pulmonary fibrosis (<xref ref-type="bibr" rid="B58">58</xref>). Generation and accumulation of ceramides were identified as pacemakers in pathogenesis of pulmonary fibrosis in cystic fibrosis in mice and men (<xref ref-type="bibr" rid="B59">59</xref>&#x2013;<xref ref-type="bibr" rid="B61">61</xref>). As a consequence, inhibition of ASM resulted in normalization of pulmonary ceramide levels, inflammation and bacterial infection (<xref ref-type="bibr" rid="B62">62</xref>&#x2013;<xref ref-type="bibr" rid="B64">64</xref>).</p>
<p>These and also previous observations from our group demonstrated that an increase of ASM-activity, ceramide formation, TGF-&#x3b2; circulation and - ultimately - liver fibrosis in a mouse model of polymicrobial sepsis might be abrogated by ASM-inhibition (<xref ref-type="bibr" rid="B65">65</xref>). These findings also support the concept that activation of the sphingomyelinase-ceramide-pathway is a universal response mechanism during host response. Furthermore, inhibition of the enzyme might have both, short- and long-term beneficial effects during the course of the disease. Especially, in high risk patients anti-fibrotic therapy is a matter of debate (<xref ref-type="bibr" rid="B66">66</xref>). Strikingly, data from a small series of independent retrospective studies, clearly attest a benefit for patients undergoing anti-depressive therapy precedent to hospitalization due to COVID-19 (<xref ref-type="bibr" rid="B67">67</xref>&#x2013;<xref ref-type="bibr" rid="B70">70</xref>). There is an anticipation that anti-depressive drugs as <bold>f</bold>unctional <bold>i</bold>nhibitors of <bold>s</bold>phingo<bold>m</bold>yelin<bold>a</bold>se (FIASMA) (<xref ref-type="bibr" rid="B71">71</xref>) exhibit anti-infective properties in epithelial cell with respect to SARS-CoV-2 (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B72">72</xref>). Hoertel et&#xa0;al. showed a significant association between the prehospital use of antidepressants with subsequent inhibition of ASM and reduced likelihood of intubation or risk of death due to SARS-CoV-2 complication (<xref ref-type="bibr" rid="B67">67</xref>). Notably in older adults, the short-term use of FIASMA is generally well tolerated (<xref ref-type="bibr" rid="B73">73</xref>, <xref ref-type="bibr" rid="B74">74</xref>). A trend for beneficial effects of FIASMA with respect to in-hospital mortality rate (potentially marked by older age and higher prevalence of comorbidities) was superimposed by co-medication with amlodipine (<xref ref-type="bibr" rid="B70">70</xref>). The later drug also exerts inhibitory capacity to ASM, but also antiviral effects <italic>in-vitro</italic> (<xref ref-type="bibr" rid="B75">75</xref>, <xref ref-type="bibr" rid="B76">76</xref>) might be exaggerated by the Ca<sup>++</sup>-modulating mechanism (<xref ref-type="bibr" rid="B77">77</xref>). In line with these results, there are similar data from small studies demonstrating a lower mortality rate after treatment with nifedipine or amlodipine (<xref ref-type="bibr" rid="B75">75</xref>, <xref ref-type="bibr" rid="B78">78</xref>). A recent update on the potential role of either a chronic expose to FIASMA or as an interventional measure following hospitalization due to SARS-CoV-2 infection underlines the interest to evaluate these drugs as off-label therapy in SARS-CoV-2 infection (<xref ref-type="bibr" rid="B79">79</xref>). Interestingly, recent reports demonstrated a synergistic effect of the FIASMA fluoxetine and the direct anti-viral agent remdesivir and its metabolite in an <italic>in-vitro</italic>-model of polarized Calu-3-cells: super-additive effectiveness highlighted key advantages of a combined approach against the propagation of the viral pathogen as well as maintenance of endosomal lipid balance for entry processing into the host at low concentrations minimizing potential adverse effects of the drugs (<xref ref-type="bibr" rid="B80">80</xref>, <xref ref-type="bibr" rid="B81">81</xref>).</p>
</sec>
<sec id="s4_3">
<title>Ceramide Function in RBC</title>
<p>RBC play an important role in oxygen transport and supply as well as they are fulfilling a plethora of metabolic activities. Within this cell population, ASM-triggered ceramide generation contributes to Ca<sup>++</sup>-sensitivity resulting in the release of extracellular vesicles by shaping the membrane&#x2019;s curvature (<xref ref-type="bibr" rid="B82">82</xref>) and induction of eryptosis, the suicidal death of RBC (<xref ref-type="bibr" rid="B83">83</xref>, <xref ref-type="bibr" rid="B84">84</xref>). Also, ASM induced ceramide generation changes the biophysical properties (<xref ref-type="bibr" rid="B85">85</xref>) resulting in an increase of rigidity in membranes (<xref ref-type="bibr" rid="B86">86</xref>, <xref ref-type="bibr" rid="B87">87</xref>) impairing the function of RBC. This is in line with observations from anemic COVID-19 patients, exhibiting RBC shape abnormalities and morphological changes leading to a spherocyte shape, which are all characterized by loss of elastic properties (<xref ref-type="bibr" rid="B88">88</xref>). After recovery, blood smear showed unremarkable morphology (<xref ref-type="bibr" rid="B88">88</xref>). The same is true with respect to formation and release of extracellular vesicles, since ceramide generation is pace-making as shown by studies using inhibitors of both isoforms of sphingomyelinase (<italic>i.e.</italic> GW4869, imipramine) (<xref ref-type="bibr" rid="B89">89</xref>). Beside the fact of increased levels of circulating extracellular vesicles that may drive thrombosis in patients undergoing COVID-19 (<xref ref-type="bibr" rid="B90">90</xref>), to the best of our knowledge, there are no clinical observations of RBC-borne vesicles as yet.</p>
<p>Data from our correlational analyses support the hypothesis that ASM activity is either a mediator or marker of a severe clinical course in our patient cohort. It is well described that patients with decreased HDL-levels are at an increased risk to develop a severe disease course compared to patients with high HDL levels (<xref ref-type="bibr" rid="B91">91</xref>). Here, low HDL values are found to be decreased in COVID-19 patients (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) and are associated with increased ASM activity (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). Most interestingly, ASM activity is found to be associated with biomarkers of metabolic dysfunction such as hydrogen carbonate, base excess and lactate concentration, of which the latter one was found in our patients in normal range (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Unlike polymicrobial sepsis, in COVID-19 lactate levels are usually normal despite severe pneumonia or manifest ARDS without any prognostic value with respect to outcome (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B92">92</xref>). In our study, ASM-activity and lactate levels are highly correlating at the day of admission to the intensive care unit. It is unclear, whether low levels of lactate are caused by increased consumption by lactate dehydrogenase (<xref ref-type="bibr" rid="B93">93</xref>), which is also found to be associated with ASM-activity. Increased values of lactate dehydrogenase activity (LDH) at hospitalization are positively associated with mortality (<xref ref-type="bibr" rid="B93">93</xref>). Considering the parallel alteration of ASM and LDH, one might speculate that both enzymes might be released probably from injured heart and lung tissue (<xref ref-type="bibr" rid="B27">27</xref>). Therefore, it might be interesting to determine the enzymatic activity of proteins in bronchoalveolar fluid, where a similar change might be expected. Furthermore ASM activity is positively associated with marker of impaired liver function such as ALT and bilirubin, which are both (beyond LDH) previously described as screening prognosticators of severe courses at early stages of the disease (<xref ref-type="bibr" rid="B94">94</xref>). The same is true with respect to ferritin as a surrogate for hyper-immune responsiveness, since baseline levels at ICU-admission are increased (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) (<xref ref-type="bibr" rid="B95">95</xref>). Established biomarkers such as procalcitonin (p= 0.065) or SOFA-values (0.138) failed to reach the level of significance due to the small cohort of patients. Interestingly, there is no association of ASM activity with values of troponin I in patients as a surrogate for damage of myocardial tissue (p=0.3365), thus the serum abundant ASM activity in COVID-19 is proposed to be released from epithelial tissue of the affected lungs as previously described in asthma (<xref ref-type="bibr" rid="B96">96</xref>, <xref ref-type="bibr" rid="B97">97</xref>) and acute respiratory syncytial virus bronchiolitis (<xref ref-type="bibr" rid="B98">98</xref>).</p>
</sec>
<sec id="s4_4">
<title>Limitations</title>
<p>Regardless of these promising new results, this study is also confronted with particular limitations. Our study was carried out at a single center with a quite limited number of patients, all of them admitted to the intensive care unit. Nevertheless, we are convinced, that the cohort is sufficiently powered for the presented results. However, the size of the cohort does not allow for the analysis of distinct subsets such as outcome, need for ventilation, or any prediction of the consequences of high/low levels of sphingomyelinase from circulation or in RBC. Furthermore, we cannot exclude that our results are biased by sample size or (anti-depressant) treatment strategies. We agree that data about prehospital treatment with FIASMAs would strengthen our results but due to the observational design and the confirmative character of the study of an unknown hypothesis we are not able to provide those data. Thus, also considering the small group size, a comparative analysis of our patients with respect to pretreatment with FIASMAs might over expand the interpretation of our results.</p>
<p>We measured sphingomyelinase activity and subsequent derangement of ceramide profile in serum/RBC and correlated the measured values with clinical and laboratory parameters. But our observations cannot explain cause-consequences at the end, especially whether the increase of enzyme activity is an epiphenomenon of or a reason for deterioration with subsequent need for intensive care treatment. Our study, without external validation, was primarily not designed to assess long-term outcomes and was therefore not feasible to screen for prognostic biomarkers for long-term sequelae. Nonetheless, our data highlight a potentially crucial signaling pathway in COVID-19 patients that warrants further investigations. Notably, the activation of circulating sphingomyelinase (ASM) and subsequent ceramide generation during host response in these patients provide a promising approach for functional inhibition by FDA-approved drugs to control resulting organ dysfunction to help the body maintaining homeostasis. Larger multicenter, interventional trials are now needed to test the potential benefit of an inhibitory strategy in critically ill patients with COVID-19.</p>
</sec>
<sec id="s4_5">
<title>Conclusions</title>
<p>The data from our study close the gap between retrospective observations by presenting a potential mechanism of ASM release and action in COVID-19 patients. Keeping the paucity of proven host-directed therapies in mind, the low level of evidence of the majority of all running trials (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B99">99</xref>) and due to the fact that a panel of FDA-approved drugs with low risk of adverse effects is awaiting consequent investigation, the potential usefulness of anti-depressants in patients with COVID-19 taking FIASMA for other indications with now known guiding principles should be prioritized for RCT and can minimize the risk of being exposed to novel, potentially harmful of ineffective compounds or compounds with unknown mode of action. As also recommended by others, the results support the continuation of FIASMA medication in these patients (<xref ref-type="bibr" rid="B69">69</xref>). Moreover, the fact of pretreatment with FIASMA should be considered while interpreting the results from hundreds of running clinical trials (<xref ref-type="bibr" rid="B17">17</xref>). Double-blind controlled randomized clinical trials of antidepressive medication with FIASMA for transient inhibition of ASM in COVID-19 are of great interest to investigate how the ASM/ceramide-pathway affects disease severity, organ damage and improvement of clinical course.</p>
</sec>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics Statement</title>
<p>The local ethics board at UMG approved inclusion of all ICU patients (reference 15/4/19&#xdc;). The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author Contributions</title>
<p>Conceptualization: MW and RC. Methodology: MA, MG, RC, and MW. Formal analysis: MA, MG, and RC. Investigation: MA, MW, MG, and RC. Clinical characterization: MW, OM, BT, SP, KM, and HH-W. Resources: MG and MB. Writing &#x2013; Original Draft: MA, MG, MW, and RC. Writing &#x2013; Review &amp; Editing: all authors. Visualization: MA, RC, MG, and MW. Supervision: RC and MW. Project Administration: MW, RC, and MG. Funding Acquisition: MG and KM. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>The study was supported by institutional grants to RC, MG, and MW. We also acknowledge support by the German Research Foundation and the Open Access Publication Fund of the Thueringer Universitaets- und Landesbibliothek Jena Projekt-Nr. 433052568. MW received unrestricted funding from SARTORIUS. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.</p>
</sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgments</title>
<p>We thank Brigitte Specht and Mareike Schilder for excellent technical assistance with sample preparation. We are grateful to Ha-Yeun Chung, M.D., from the Section &#x2018;Translational Neuroimmunology&#x2019; from our Department of Neurology, Jena University Hospital, for critical reading and editing the manuscript.</p>
</ack>
<sec id="s11" sec-type="supplementary-material">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fimmu.2021.784989/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fimmu.2021.784989/full#supplementary-material</ext-link>
</p>
  <supplementary-material xlink:href="DataSheet_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
</sec>
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