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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.2020.575047</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>Increased Plasma Heparanase Activity in COVID-19 Patients</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Buijsers</surname><given-names>Baranca</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn003"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1096758"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yanginlar</surname><given-names>Cansu</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn003"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/387856"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>de Nooijer</surname><given-names>Aline</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn004"><sup>&#x2021;</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Grondman</surname><given-names>Inge</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn004"><sup>&#x2021;</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Maciej-Hulme</surname><given-names>Marissa L.</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/779800"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jonkman</surname><given-names>Inge</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Janssen</surname><given-names>Nico A. F.</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Rother</surname><given-names>Nils</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/228595"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>de Graaf</surname><given-names>Mark</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pickkers</surname><given-names>Peter</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/135356"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kox</surname><given-names>Matthijs</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/311134"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Joosten</surname><given-names>Leo A. B.</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/500291"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Nijenhuis</surname><given-names>Tom</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/162126"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Netea</surname><given-names>Mihai G.</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/22651"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hilbrands</surname><given-names>Luuk</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>van de Veerdonk</surname><given-names>Frank L.</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/83255"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Duivenvoorden</surname><given-names>Rapha&#xeb;l</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>de Mast</surname><given-names>Quirijn</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/206726"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>van der Vlag</surname><given-names>Johan</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn001"><sup>*</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/25609"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Nephrology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center</institution>, <addr-line>Nijmegen</addr-line>, <country>Netherlands</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center</institution>, <addr-line>Nijmegen</addr-line>, <country>Netherlands</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Intensive Care Medicine, Radboud University Medical Center</institution>, <addr-line>Nijmegen</addr-line>, <country>Netherlands</country></aff>
<aff id="aff4"><sup>4</sup><institution>Deparment of Immunology and Metabolism, Life &amp; Medical Sciences Institute, University of Bonn</institution>, <addr-line>Bonn</addr-line>, <country>Germany</country></aff>
<aff id="aff5"><sup>5</sup><institution>Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai</institution>, <addr-line>New York, NY</addr-line>, <country>United States</country></aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Christoph Thiemermann, Queen Mary University of London, United Kingdom</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Fausto Chiazza, University of Eastern Piedmont, Italy; Gareth S. D. Purvis, University of Oxford, United Kingdom; Michael Rutzler, ApoGlyx, Sweden</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Johan van der Vlag, <email xlink:href="mailto:Johan.vanderVlag@radboudumc.nl">Johan.vanderVlag@radboudumc.nl</email>; <uri xlink:href="https://orcid.org/0000-0001-7843-5918">orcid.org/0000-0001-7843-5918</uri></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>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors share first authorship</p>
</fn>
<fn fn-type="equal" id="fn004">
<p>&#x2021;These authors share last authorship</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>06</day>
<month>10</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="collection">
<year>2020</year>
</pub-date>
<volume>11</volume>
<elocation-id>575047</elocation-id>
<history>
<date date-type="received">
<day>22</day>
<month>06</month>
<year>2020</year>
</date>
<date date-type="accepted">
<day>14</day>
<month>09</month>
<year>2020</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2020 Buijsers, Yanginlar, de Nooijer, Grondman, Maciej-Hulme, Jonkman, Janssen, Rother, de Graaf, Pickkers, Kox, Joosten, Nijenhuis, Netea, Hilbrands, van de Veerdonk, Duivenvoorden, de Mast and van der Vlag</copyright-statement>
<copyright-year>2020</copyright-year>
<copyright-holder>Buijsers, Yanginlar, de Nooijer, Grondman, Maciej-Hulme, Jonkman, Janssen, Rother, de Graaf, Pickkers, Kox, Joosten, Nijenhuis, Netea, Hilbrands, van de Veerdonk, Duivenvoorden, de Mast and van der Vlag</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>Reports suggest a role of endothelial dysfunction and loss of endothelial barrier function in COVID-19. It is well established that the endothelial glycocalyx-degrading enzyme heparanase contributes to vascular leakage and inflammation. Low molecular weight heparins (LMWH) serve as an inhibitor of heparanase. We hypothesize that heparanase contributes to the pathogenesis of COVID-19, and that heparanase may be inhibited by LMWH. To test this hypothesis, heparanase activity and heparan sulfate levels were measured in plasma of healthy controls (n = 10) and COVID-19 patients (n = 48). Plasma heparanase activity and heparan sulfate levels were significantly elevated in COVID-19 patients. Heparanase activity was associated with disease severity including the need for intensive care, lactate dehydrogenase levels, and creatinine levels. Use of prophylactic LMWH in non-ICU patients was associated with a reduced heparanase activity. Since there is no other clinically applied heparanase inhibitor currently available, therapeutic treatment of COVID-19 patients with low molecular weight heparins should be explored.</p>
</abstract>
<kwd-group>
<kwd>inflammation</kwd>
<kwd>heparanase</kwd>
<kwd>LMWH (low molecular weight heparin)</kwd>
<kwd>vascular leakage</kwd>
<kwd>glycocalyx damage</kwd>
<kwd>COVID-19</kwd>
</kwd-group>
<counts>
<fig-count count="4"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="58"/>
<page-count count="9"/>
<word-count count="4532"/>
</counts>
</article-meta>
</front>
<body>
<fig id="f4" position="float">
<label>Graphical Abstract</label>
<caption>
<p>Heparin and low molecular weight heparins (LMWH) inhibit heparanase activity which is associated with disease severity in COVID-19.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-11-575047-g004.tif"/>
</fig>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>The coronavirus disease-2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (<xref ref-type="bibr" rid="B1">1</xref>). Severe COVID-19 usually manifests as pneumonitis or acute respiratory distress syndrome (ARDS) (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B3">3</xref>). Studies showed that upon hospital admission 59% of COVID-19 patients had proteinuria (<xref ref-type="bibr" rid="B4">4</xref>), and 22% of the non-ventilated patients and 90% of the ventilated patients developed acute kidney injury (AKI) (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>).</p>
<p>Endothelial barrier function is crucial in the regulation of fluid and protein extravasation, particularly in the lungs (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B8">8</xref>) and in the kidneys (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>). An important role for endothelial cell dysfunction in the pathogenesis of the complications of COVID-19 has been proposed by several studies (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>). As pulmonary edema occurs when fluid leaks into alveoli, dysfunction of the endothelium is likely to contribute to pulmonary edema in COVID-19. Furthermore, it has been well established that proteinuria occurs when the endothelial barrier function in the glomerulus is compromised (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B13">13</xref>).</p>
<p>Endothelial cells are covered with a thick layer of negatively charged glycosaminoglycans (GAGs), termed the glycocalyx. Heparan sulfate (HS) is the predominant sulfated GAG in the glycocalyx. HS contributes to the endothelial charge-dependent barrier function due to its negative charge (<xref ref-type="bibr" rid="B14">14</xref>). Degradation of HS by heparanase (HPSE), the only known mammalian HS-degrading enzyme, disrupts the endothelial glycocalyx and subsequent loss of endothelial barrier function, as observed in ARDS and proteinuric kidney diseases (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B15">15</xref>&#x2013;<xref ref-type="bibr" rid="B17">17</xref>). In addition to compromising barrier function, HPSE generates a pro-inflammatory glycocalyx that promotes the binding of chemokines, cytokines, and leukocytes to the endothelial cell surface (<xref ref-type="bibr" rid="B18">18</xref>). Inhibition of HPSE and/or HPSE deficiency is beneficial in experimental lung and kidney diseases (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B15">15</xref>&#x2013;<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B19">19</xref>). Notably, heparins and low molecular weight heparins (LMWH) that have been suggested to be beneficial for COVID-19 patients (<xref ref-type="bibr" rid="B20">20</xref>), are potent inhibitors of HPSE activity (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>).</p>
<p>Taken together, we hypothesize that increased HPSE activity is one of the driving forces in severe COVID-19 manifestations and that HPSE may be inhibited by the use of LMWH in COVID-19.</p>
</sec>
<sec id="s2">
<title>Methods</title>
<sec id="s2_1">
<title>Human Samples, Demographics, and Baseline Characteristics</title>
<p>This study was performed according to the latest version of the declaration of Helsinki and guidelines for good clinical practice. The local independent ethical committee approved the study protocol (CMO 2020-6344, CMO 2020-6359, CMO 2016-2923). All patients admitted to the Radboud University Medical Center (Radboudumc) with a PCR-proven SARS-CoV-2 infection was asked for informed consent for participation in this study. After obtaining informed consent, ethylenediaminetetraacetic acid (EDTA) blood was collected and centrifuged for 10&#xa0;min at 2,954 <italic>xg</italic> at room temperature (RT), plasma was collected and stored at &#x2212;80&#xb0;C for later analysis. For most patients in the non-ICU group, the blood samples collected between day 2 and 4 upon hospitalization were selected for this study except for the patients in the LMWH- group for whom the sample had to be collected immediately upon hospital admission prior to initiation of any standard medical intervention. Demographic data, medical history, and clinical laboratory measurements were collected from the medical file and processed in encoded form in electronic case report forms using Castor electronic data capture (Castor EDC, Amsterdam, Netherlands).</p>
</sec>
<sec id="s2_2">
<title>HPSE Activity Assay</title>
<p>The activity of HPSE in EDTA plasma was determined by an in-house developed activity assay, which was optimized by the use of recombinant active human HPSE (Bio-techne, Abingdon, United Kingdom, Cat#7570-GH-005). In detail, Nunc maxisorp flat bottom 96 plates (Thermo scientific, Breda, Netherlands) were coated with 10 ug/ml heparan sulfate from bovine kidney (HSBK) (Sigma-Aldrich, Zwijndrecht, Netherlands) in optimized HS coating buffer, overnight in a humidified chamber at RT. Subsequently, plates were washed with 0.05% PBS-Tween 20 (Sigma-Aldrich) (PBST) and blocked for minimal 2&#xa0;h with 1% bacto-gelatin (Difco laboratories, Detroit, Michigan, USA) in PBS at RT. Plates were washed with PBST, followed by a final washing step with PBS prior to 2&#xa0;h incubation at 37&#xb0;C with 4 times diluted plasma sample in HPSE buffer. Samples were randomly distributed over plates. The HPSE buffer consisted of 50 mM citric acid-sodium citrate (Merck, Zwijndrecht, Netherlands) buffer supplemented with 50 mM NaCl (Merck), 1 mM CaCl<sub>2</sub> (Sigma-Aldrich), and 1 mM DTT (Sigma-Aldrich) at final pH 5.0. Next, plates were washed with PBST and incubated with primary mouse anti-rat IgM HS antibody JM403 (Amsbio, Abingdon, United Kingdom, cat. no. #370730-S, RRID: AB_10890960, 1 &#x3bc;g/ml in PBST) for 1&#xa0;h at RT. Subsequently, plates were washed with PBST and incubated with secondary goat anti-mouse IgM HRP antibody (Southern Biotech, Uden, Netherlands, cat. no. #1020-05, RRID: AB_2794201, dilution 1:10000 in PBST) for 1&#xa0;h at RT. Finally, plates were washed with PBST and 3,3&#x2019;,5,5&#x2019;-tetramethylbenzidine (TMB) substrate (Invitrogen, Breda, Netherlands) was added and reaction was stopped by addition of 2 M sulfuric acid, and absorbance was measured at 450 nm. The HPSE activity in plasma was related to a standard curve of recombinant human HPSE in healthy control EDTA plasma.</p>
<p>For the <italic>in vitro</italic> HPSE inhibition experiment with dalteparin (Pfizer, Capelle a/d Ijssel, Netherlands, Fragmin 12,500 IU/0.5&#xa0;ml), the HPSE activity was determined using the HPSE activity assay as outlined above. For inhibition studies 0&#x2013;1 IU/ml dalteparin was used with a constant amount of 150 ng/ml recombinant human HPSE.</p>
</sec>
<sec id="s2_3">
<title>HS Competition Assay</title>
<p>HS in EDTA plasma samples was quantified by a previously described HS competition assay (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>). Importantly, this assay is specific to HS, therefore the measurement is not affected by the presence of LMWH use. Plates were coated with HSBK and blocked with bacto-gelatin as outlined for the HPSE activity assay. Uncoated plates, blocked with bacto-gelatin, were washed with PBST. The plasma samples were four times diluted in PBST containing primary mouse anti-rat IgM HS antibody JM403 (1.3 &#x3bc;g/ml) and incubated for 1&#xa0;h at RT. Samples were randomly distributed over plates. Subsequently, the samples were transferred from the uncoated plates to the HSBK-coated plates and incubated for 1&#xa0;h at RT. Plates were washed with PBST and incubated with secondary goat anti-mouse IgM HRP antibody for 1&#xa0;h at RT. Plates were developed and measured as outlined for the HPSE activity assay. The amount of HS detected in plasma is expressed in arbitrary units since HS from bovine kidney was coated and used to prepare the standard curve.</p>
</sec>
<sec id="s2_4">
<title>IL-6 Measurements</title>
<p>IL-6 concentration was measured in plasma of COVID-19 patients using commercial ELISA kits for human IL-6 (Bio-techne, Abingdon, United Kingdom) according to manufacturer&#x2019;s instruction.</p>
</sec>
<sec id="s2_5">
<title>Statistical Analysis</title>
<p>Values are expressed as mean &#xb1; SEM. D&#x2019;Agostino &amp; Pearson normality test was performed to test for normality of data. Significance was determined by Fisher&#x2019;s exact test to compare categorical variables, by Student&#x2019;s t-test or Mann Whitney test to compare two groups and by Kruskal-Wallis test followed by Dunn&#x2019;s test to compare more than two groups using GraphPad Prism V.8.4.2 (La Jolla, USA). P values less than 0.05 were considered as statistically significant.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Demographics and Baseline Characteristics of COVID-19 Patients</title>
<p>Plasma was collected from 48 PCR-confirmed COVID-19 patients admitted to the ICU (n = 14) or to designated COVID-19 clinical wards (n = 34). More men than women were included (<xref ref-type="table" rid="T1"><bold>Table 1</bold></xref>). All ICU patients received LMWH as part of standard ICU treatment. The non-ICU patients were further aggregated in those receiving prophylactic LMWH (LMWH+) (in general dalteparin 5,000 IU subcutaneously once daily) (n = 17) and those receiving either alternative anticoagulation (n = 8; vitamin K antagonist n = 6, direct oral anticoagulant n = 2) or patients for whom the sample collection was performed before initiation of any standard medical intervention (LMWH&#x2212;) (n = 9). Hospital stay duration was significantly different between ICU and non-ICU groups as well as between LMWH&#x2212; and LMWH+ groups, while number of deaths was not significantly different between the different subgroups. Notably, ICU patients had a significantly higher C-reactive protein concentration than non-ICU patients (<xref ref-type="table" rid="T2"><bold>Table 2</bold></xref>). The LMWH+ group had significantly higher median D-dimer concentrations compared to LMWH&#x2212; group, whereas the concentrations of the inflammatory markers C-reactive protein and serum ferritin were similar between LMWH+ and LMWH&#x2212;.</p>
<table-wrap id="T1" position="float">
<label>Table 1</label>
<caption>
<p>Demographics of COVID-19 patients.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Characteristics</th>
<th valign="top" rowspan="2" align="center">All patients n = 48</th>
<th valign="top" rowspan="2" align="center">ICU n = 14</th>
<th valign="top" colspan="4" align="center">Non-ICU</th>
<th valign="top" rowspan="2" align="center">p<sub>2</sub></th>
</tr>
<tr>
<th valign="top" align="left">LMWH&#x2212; n = 17</th>
<th valign="top" align="center">LMWH+ n = 17</th>
<th valign="top" align="center">Total n = 34</th>
<th valign="top" align="center">p<sub>1</sub></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><bold>Sex, male, n (%)</bold></td>
<td valign="top" align="center">37 (77)</td>
<td valign="top" align="center">11 (78.5)</td>
<td valign="top" align="center">13 (76.5)</td>
<td valign="top" align="center">13 (76.5)</td>
<td valign="top" align="center">26 (76.5)</td>
<td valign="top" align="center">1.0000<sup>1</sup></td>
<td valign="top" align="center">1.0000<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Age, median (IQR), years</bold></td>
<td valign="top" align="center">67.5 (57.3&#x2013;74.75)</td>
<td valign="top" align="center">62.5 (53.0&#x2013; 69.5)</td>
<td valign="top" align="center">69 (62.5&#x2013;76.5)</td>
<td valign="top" align="center">69 (53.5&#x2013;77.0)</td>
<td valign="top" align="center">69 (58.8&#x2013;77.0)</td>
<td valign="top" align="center">0.6792<sup>3</sup></td>
<td valign="top" align="center">0.2428<sup>2</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Hospital stay, median (IQR), days</bold></td>
<td valign="top" align="center">9 (5&#x2013;16)</td>
<td valign="top" align="center">26 (16&#x2013;&#x2026;)<sup>&amp;</sup></td>
<td valign="top" align="center">5 (5&#x2013;8)</td>
<td valign="top" align="center">9 (6&#x2013;12)</td>
<td valign="top" align="center">7 (5&#x2013;9)</td>
<td valign="top" align="center">0.0443<sup>3</sup></td>
<td valign="top" align="center">0.0001<sup>3</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Deaths, n (%)</bold></td>
<td valign="top" align="center">7 (15)</td>
<td valign="top" align="center">3 (21)</td>
<td valign="top" align="center">3 (18)</td>
<td valign="top" align="center">1 (6)</td>
<td valign="top" align="center">4 (12)</td>
<td valign="top" align="center">0.6012<sup>1</sup></td>
<td valign="top" align="center">0.4004<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Transfer non-ICU to ICU, n (%)</bold></td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">0 (0)</td>
<td valign="top" align="center">0 (0)</td>
<td valign="top" align="center">N/A</td>
<td valign="top" align="center">1.0000<sup>1</sup></td>
<td valign="top" align="center">N/A</td>
</tr>
<tr>
<td valign="top" align="left"><bold>Day of sampling, median (IQR)</bold></td>
<td valign="top" align="center">2 (1&#x2013;4)</td>
<td valign="top" align="center">3 (1&#x2013;6)</td>
<td valign="top" align="center">1 (1&#x2013;4)</td>
<td valign="top" align="center">2 (2&#x2013;4)</td>
<td valign="top" align="center">2 (1&#x2013;4)</td>
<td valign="top" align="center">0.3940<sup>3</sup></td>
<td valign="top" align="center">0.0945<sup>2</sup></td>
</tr>
<tr>
<td valign="top" colspan="2" align="left"><bold>Coexisting disorder, n (%)</bold></td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left"><bold>Heart disease</bold></td>
<td valign="top" align="center">8 (16.7)</td>
<td valign="top" align="center">3 (21.4)</td>
<td valign="top" align="center">3 (17.6)</td>
<td valign="top" align="center">2 (11.8)</td>
<td valign="top" align="center">5 (14.7)</td>
<td valign="top" align="center">1.0000<sup>1</sup></td>
<td valign="top" align="center">0.6757<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Lung disease</bold></td>
<td valign="top" align="center">16 (33.3)</td>
<td valign="top" align="center">4 (28.6)</td>
<td valign="top" align="center">2 (11.8)</td>
<td valign="top" align="center">10 (58.8)</td>
<td valign="top" align="center">12 (35.3)</td>
<td valign="top" align="center">0.0104<sup>1</sup></td>
<td valign="top" align="center">0.7460<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Diabetes</bold></td>
<td valign="top" align="center">6 (12.5)</td>
<td valign="top" align="center">2 (14.3)</td>
<td valign="top" align="center">3 (17.6)</td>
<td valign="top" align="center">1 (5.9)</td>
<td valign="top" align="center">4 (11.8)</td>
<td valign="top" align="center">0.6012<sup>1</sup></td>
<td valign="top" align="center">1.0000<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Hypertension</bold></td>
<td valign="top" align="center">18 (37.5)</td>
<td valign="top" align="center">8 (72.7)</td>
<td valign="top" align="center">5 (29.4)</td>
<td valign="top" align="center">5 (29.4)</td>
<td valign="top" align="center">10 (29.4)</td>
<td valign="top" align="center">1.0000<sup>1</sup></td>
<td valign="top" align="center">0.1032<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Malignancy</bold></td>
<td valign="top" align="center">9 (18.8)</td>
<td valign="top" align="center">1 (7.1)</td>
<td valign="top" align="center">4 (23.5)</td>
<td valign="top" align="center">4 (23.5)</td>
<td valign="top" align="center">8 (23.5)</td>
<td valign="top" align="center">1.0000<sup>1</sup></td>
<td valign="top" align="center">0.2501<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Immunocompromised</bold></td>
<td valign="top" align="center">7 (14.6)</td>
<td valign="top" align="center">0 (0)</td>
<td valign="top" align="center">2 (11.8)</td>
<td valign="top" align="center">5 (29.4)</td>
<td valign="top" align="center">7 (20.6)</td>
<td valign="top" align="center">0.3983<sup>1</sup></td>
<td valign="top" align="center">0.0898<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Renal disease</bold></td>
<td valign="top" align="center">4 (8.3)</td>
<td valign="top" align="center">2 (14.3)</td>
<td valign="top" align="center">0 (0)</td>
<td valign="top" align="center">2 (11.8)</td>
<td valign="top" align="center">2 (5.9)</td>
<td valign="top" align="center">0.4848<sup>1</sup></td>
<td valign="top" align="center">0.5659<sup>1</sup></td>
</tr>
<tr>
<td valign="top" colspan="2" align="left"><bold>COVID-19 treatment, n (%)</bold></td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left"><bold>(hydroxy)chloroquine</bold></td>
<td valign="top" align="center">19 (39.6)</td>
<td valign="top" align="center">6 (42.9)</td>
<td valign="top" align="center">4 (42.9)</td>
<td valign="top" align="center">9 (52.9)</td>
<td valign="top" align="center">13 (38.2)</td>
<td valign="top" align="center">0.1571<sup>1</sup></td>
<td valign="top" align="center">1.0000<sup>1</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Remdesivir</bold></td>
<td valign="top" align="center">1 (2.1)</td>
<td valign="top" align="center">1 (7.1)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">0.1153<sup>1</sup></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Data are presented as median (IQR) or percentage (%). P values comparing LMWH&#x2212; with LMWH+ patients (p<sub>1</sub>) or ICU patients with non-ICU patients (p<sub>2</sub>) are calculated with Fisher&#x2019;s exact test<sup>1</sup>, and with unpaired two-tailed Student&#x2019;s t test<sup>2</sup> or unpaired two-tailed Mann Whitney test<sup>3</sup> based on the distribution of data determined by D&#x2019;Agostino &amp; Pearson omnibus normality test. ICU, intensive care unit; COVID-19, coronavirus disease-2019; IQR, interquartile range; LMWH&#x2212;, patients without prophylactic LMWH; LMWH+, patients with prophylactic LMWH. <sup>&amp;</sup>75% quartile is unknown due to prolonged hospitalization of some patients.</p>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T2" position="float">
<label>Table 2</label>
<caption>
<p>Baseline characteristics of COVID-19 patients.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Characteristics</th>
<th valign="top" rowspan="2" align="center">All patients n = 48</th>
<th valign="top" rowspan="2" align="center">ICU n = 14</th>
<th valign="top" colspan="4" align="center">Non-ICU</th>
<th valign="top" rowspan="2" align="center">p<sub>2</sub></th>
</tr>
<tr>
<th valign="top" align="left">LMWH&#x2212; n = 17</th>
<th valign="top" align="center">LMWH+ n = 17</th>
<th valign="top" align="center">Total n = 34</th>
<th valign="top" align="center">p<sub>1</sub></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><bold>CT severity score*, median (IQR)</bold></td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">9.0 (7.3&#x2013;13.0)<sup>+</sup></td>
<td valign="top" align="center">13.0 (9.3&#x2013;16.5)<sup>+</sup></td>
<td valign="top" align="center">11.5 (8.0&#x2013;15.0)<sup>++</sup></td>
<td valign="top" align="center">0.0743<sup>3</sup></td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" colspan="2" align="left"><bold>Laboratory, median (IQR)</bold></td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left"><bold>WBC, &#xd7;10<sup>9</sup>/L*</bold></td>
<td valign="top" align="center">6.8 (5.2&#x2013;9.6)</td>
<td valign="top" align="center">6.7 (5.9&#x2013;7.9)</td>
<td valign="top" align="center">6.8 (4.3&#x2013;9.5)</td>
<td valign="top" align="center">7.4 (4.8&#x2013;9.8)</td>
<td valign="top" align="center">6.8 (4.7&#x2013;9.8)</td>
<td valign="top" align="center">0.7101<sup>2</sup></td>
<td valign="top" align="center">0.8648<sup>3</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Platelets, &#xd7;10<sup>9</sup>/L*</bold></td>
<td valign="top" align="center">216 (159&#x2013;286)</td>
<td valign="top" align="center">220 (176&#x2013;281)</td>
<td valign="top" align="center">163 (139&#x2013;256)</td>
<td valign="top" align="center">250 (189&#x2013;330)</td>
<td valign="top" align="center">216 (154&#x2013;308)</td>
<td valign="top" align="center">0.1054<sup>3</sup></td>
<td valign="top" align="center">0.8033<sup>2</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>C-reactive protein, mg/L*</bold></td>
<td valign="top" align="center">98 (54&#x2013;171) <sup>++</sup></td>
<td valign="top" align="center">171 (120&#x2013;259) <sup>+</sup></td>
<td valign="top" align="center">96 (41&#x2013;154) <sup>+</sup></td>
<td valign="top" align="center">78 (41&#x2013;136)</td>
<td valign="top" align="center">86 (42&#x2013;140)<sup>+</sup></td>
<td valign="top" align="center">0.3197<sup>2</sup></td>
<td valign="top" align="center">0.0013<sup>3</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Ferritin, &#xb5;g/L</bold></td>
<td valign="top" align="center">955 (567&#x2013;1,658)</td>
<td valign="top" align="center">1,363 (872&#x2013;1917)</td>
<td valign="top" align="center">762 (362&#x2013;1,239)</td>
<td valign="top" align="center">950 (571&#x2013;1,854)</td>
<td valign="top" align="center">835 (481&#x2013;1,483)</td>
<td valign="top" align="center">0.2629<sup>3</sup></td>
<td valign="top" align="center">0.1374<sup>3</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>D-dimer, ng/ml*</bold></td>
<td valign="top" align="center">1,080 (319&#x2013;1,973)<sup>+++++++</sup></td>
<td valign="top" align="center">1,870 (313&#x2013;5,275)<sup>+</sup></td>
<td valign="top" align="center">407 (210&#x2013;650)<sup>+</sup></td>
<td valign="top" align="center">1,335 (1,130&#x2013;2,775)<sup>+++++</sup></td>
<td valign="top" align="center">720 (318&#x2013;1,335)<sup>++++++</sup></td>
<td valign="top" align="center">0.0003<sup>3</sup></td>
<td valign="top" align="center">0.1084<sup>3</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Lactate dehydrogenase, U/L*</bold></td>
<td valign="top" align="center">314 (258&#x2013;413)<sup>+</sup></td>
<td valign="top" align="center">307 (273&#x2013;400)</td>
<td valign="top" align="center">318 (238&#x2013;436)<sup>+</sup></td>
<td valign="top" align="center">317 (259&#x2013;362)</td>
<td valign="top" align="center">317 (257&#x2013;418)<sup>+</sup></td>
<td valign="top" align="center">0.9856<sup>3</sup></td>
<td valign="top" align="center">0.6780<sup>2</sup></td>
</tr>
<tr>
<td valign="top" align="left"><bold>Creatinine, &#xb5;mol/L*<sup>#</sup></bold></td>
<td valign="top" align="center">92.0 (69.0&#x2013;115.8)<sup>+++++</sup></td>
<td valign="top" align="center">101.0 (73.0&#x2013;145.5)<sup>++</sup></td>
<td valign="top" align="center">92.0 (73.0&#x2013;117.0)<sup>++</sup></td>
<td valign="top" align="center">85.0 (62.3&#x2013;97.8)<sup>+</sup></td>
<td valign="top" align="center">87.0 (66.0&#x2013;112.0)<sup>+++</sup></td>
<td valign="top" align="center">0.3325<sup>3</sup></td>
<td valign="top" align="center">0.2685<sup>3</sup></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Data are presented as median (IQR). P values comparing LMWH&#x2212; with LMWH+ patients (p<sub>1</sub>) or ICU patients with non-ICU patients (p<sub>2</sub>) are calculated with unpaired two-tailed Student&#x2019;s t test<sup>2</sup> or unpaired two-tailed Mann Whitney test<sup>3</sup> based on the distribution of data determined by D&#x2019;Agostino &amp; Pearson omnibus normality test. ICU, intensive care unit; COVID-19, coronavirus disease-2019; IQR, interquartile range; LMWH&#x2212;, patients without prophylactic LMWH; LMWH+, patients with prophylactic LMWH. Measurements with missing values are indicated with * and the number of <sup>+</sup> signs indicates the number of missing patients per characteristic and group. <sup>#</sup>Four patients with history of renal disease were excluded.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Plasma HPSE Activity Is Elevated in COVID-19 Patients</title>
<p>Several (experimental) disease models have shown that increased HPSE activity can lead to endothelial barrier dysfunction, which may be involved in the development of ARDS and proteinuria/AKI (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B26">26</xref>). Measurement of plasma HPSE activity levels in COVID-19 patients and healthy controls revealed that HPSE activity was significantly elevated in COVID-19 patients compared to healthy controls (<xref ref-type="fig" rid="f1"><bold>Figure 1A</bold></xref>). In line with the increased HPSE activity, HS plasma levels were also significantly elevated in COVID-19 patients compared to healthy controls (<xref ref-type="fig" rid="f1"><bold>Figure 1B</bold></xref>). Similarly, we detected significantly elevated IL-6 levels in COVID-19 patients compared to healthy controls (<xref ref-type="fig" rid="f1"><bold>Figure 1C</bold></xref>). Overall, these results suggest that SARS-CoV-2 infection is associated with an increase in the activity of HPSE in plasma and an increase in plasma HS and IL-6 levels.</p>
<fig id="f1" position="float">
<label>Figure 1</label>
<caption>
<p>COVID-19 patients display increased HPSE activity, and elevated levels of heparan sulfate and IL-6 in plasma. <bold>(A)</bold> HPSE activity was increased in plasma of COVID-19 patients compared to healthy controls. HPSE activity was measured using an in-house developed ELISA with a specific anti-HS antibody. <bold>(B)</bold> HS levels were increased in plasma of COVID-19 patients compared to healthy controls. HS levels were measured by an in-house developed competition ELISA using a specific anti-HS antibody. <bold>(C)</bold> IL-6 levels were increased in plasma of COVID-19 patients compared to healthy controls. IL-6 levels were measured using a commercial IL-6 ELISA. Data were presented as mean &#xb1; SEM and tested for normal distribution with D&#x2019;Agostino &amp; Pearson omnibus normality test and statistical differences were calculated using Mann Whitney test (n = 10 healthy; n = 48 COVID-19; **p &lt; 0.01; ****p &lt; 0.0001). HPSE, heparanase; HS, heparan sulfate; Healthy, healthy controls; COVID-19, coronavirus disease-19 patients; AU, arbitrary units.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-11-575047-g001.tif"/>
</fig>
</sec>
<sec id="s3_3">
<title>HPSE Activity Associates With COVID-19 Disease Severity</title>
<p>Next, we investigated whether HPSE activity levels were associated with COVID-19 disease severity. Plasma HPSE activity was significantly increased in both non-ICU and ICU patients compared to healthy controls, and HPSE levels in ICU patients, who all received mechanical ventilation, were higher than in non-ICU patients (<xref ref-type="fig" rid="f2"><bold>Figure 2A</bold></xref>). Moreover, HS (<xref ref-type="fig" rid="f2"><bold>Figure 2B</bold></xref>) and IL-6 levels (<xref ref-type="fig" rid="f2"><bold>Figure 2C</bold></xref>) in plasma were also higher in both non-ICU and ICU patients compared to healthy controls. Finally, plasma HPSE activity was significantly higher in patients with elevated LDH values (<xref ref-type="fig" rid="f2"><bold>Figure 2D</bold></xref>), and in patients with elevated serum creatinine values (<xref ref-type="fig" rid="f2"><bold>Figure 2E</bold></xref>). These findings reveal that patients with severe COVID-19 disease display higher plasma HPSE activity levels than patients with moderate COVID-19 disease.</p>
<fig id="f2" position="float">
<label>Figure 2</label>
<caption>
<p>Increased plasma HPSE activity associates with COVID-19 disease severity. <bold>(A)</bold> Plasma HPSE activity was significantly higher in ICU and non-ICU patients compared to healthy controls, and higher in ICU patients compared to non-ICU patients (n = 10 healthy; n = 34 non-ICU; n = 14 ICU). <bold>(B)</bold> HS plasma levels were significantly increased in plasma of ICU and non-ICU patients compared to healthy controls (n = 10 healthy; n = 34 non-ICU; n = 14 ICU). <bold>(C)</bold> IL-6 plasma levels were significantly increased in plasma of ICU and non-ICU patients compared to healthy controls (n = 10 healthy; n = 34 non-ICU; n = 14 ICU). <bold>(D)</bold> HPSE activity was significantly higher in plasma of patients with elevated LDH (&gt;280 U/L) values compared to patients with normal LDH levels (n = 15 normal LDH; n = 26 elevated LDH). <bold>(E)</bold> HPSE activity was significantly higher in plasma of patients with elevated creatinine (&gt;110 &#xb5;mol/L for men and &gt;90 &#xb5;mol/L for women) values compared to patients with normal creatinine values (n = 30 normal creatinine; n = 11 elevated creatinine; patients with history of renal disease were excluded from this analysis). HPSE activity was measured using an in-house developed ELISA with a specific anti-HS antibody and HS plasma levels were measured using an in-house developed competition ELISA with a specific anti-HS antibody. Data were presented as mean &#xb1; SEM and tested for normal distribution with D&#x2019;Agostino &amp; Pearson omnibus normality test and statistical differences were calculated using Kruskal Wallis test followed by Dunn&#x2019;s multiple comparison test, unpaired one-tailed Student&#x2019;s t-test or unpaired one-tailed Mann Whitney test (*p &lt; 0.05; **p &lt; 0.01; ***p &lt; 0.001; ****p &lt; 0.0001). HPSE, heparanase; HS, heparan sulfate; LDH, lactate dehydrogenase; Healthy, healthy controls; non-ICU, COVID-19 patients in normal hospital ward; ICU, COVID-19 patients in ICU; AU, arbitrary units.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-11-575047-g002.tif"/>
</fig>
</sec>
<sec id="s3_4">
<title>Use of LMWH Is Associated With Lower HPSE Activity in Plasma of COVID-19 Patients</title>
<p>Prophylactic treatment with LMWH is recommended for patients hospitalized with COVID-19 (<xref ref-type="bibr" rid="B27">27</xref>), whereas some experts recommend higher doses for critically ill patients (<xref ref-type="bibr" rid="B28">28</xref>). As LMWH inhibits HPSE activity and it is known that HPSE deficiency reduces expression of various cytokines (<xref ref-type="bibr" rid="B15">15</xref>), we analyzed the effect of prophylactic LMWH on HPSE activity, HS levels and IL-6 levels in plasma of COVID-19 patients. Markedly, non-ICU patients who received LMWH displayed significantly lower plasma HPSE activity compared to non-ICU patients without LMWH prophylaxis (<xref ref-type="fig" rid="f3"><bold>Figure 3A</bold></xref>), whereas no statistically significant differences could be observed on HS levels (<xref ref-type="fig" rid="f3"><bold>Figure 3B</bold></xref>) or IL-6 levels (<xref ref-type="fig" rid="f3"><bold>Figure 3C</bold></xref>) between non-ICU patients with or without LMWH prophylaxis. According to literature, a single injection of 5,000 units dalteparin would result in an estimated concentration of around 0.37 U/ml <italic>in vivo</italic> (<xref ref-type="bibr" rid="B29">29</xref>). We found a dose dependent inhibition of recombinant HPSE at concentrations between 0.0025 and 0.05 U/ml and full inhibition starting from 0.25 U/ml dalteparin <italic>in vitro</italic> (<xref ref-type="fig" rid="f3"><bold>Figure 3D</bold></xref>). These data suggest that the applied prophylactic LMWH dose is already effective in inhibition of HPSE activity within plasma of moderately diseased, while HPSE activity remained high in severely ill, COVID-19 patients.</p>
<fig id="f3" position="float">
<label>Figure 3</label>
<caption>
<p>LMWH reduces plasma HPSE activity, but not plasma HS or IL-6 levels in moderately diseased COVID-19 patients. <bold>(A)</bold> LMWH reduces HPSE activity in plasma of non-ICU patients with COVID-19, which was measured using in-house developed HPSE activity assay (n = 17 for both groups, **p &lt; 0.01). <bold>(B)</bold> LMWH does not reduce HS levels in plasma of non-ICU patients with COVID-19, which was measured with an in-house developed competition ELISA with a specific anti-HS antibody. <bold>(C)</bold> LMWH does not reduce IL-6 levels in plasma of non-ICU patients with COVID-19, which was measured using an in-house developed competition ELISA with a specific anti-HS antibody. Data were presented as mean &#xb1; SEM and tested for normal distribution with D&#x2019;Agostino &amp; Pearson omnibus normality test and statistical difference was calculated using unpaired one-tailed Mann Whitney test. <bold>(D)</bold> LMWH inhibits recombinant HPSE activity <italic>in vitro</italic> in a dose-dependent manner. HPSE activity was measured using an in-house developed ELISA with a specific anti-HS antibody (n = 5). HPSE, heparanase; HS, heparan sulfate; LMWH, low molecular weight heparin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-11-575047-g003.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>COVID-19 appears to be a disease that leads to endothelial dysfunction and disruption of the endothelial barrier, which may underly development of ARDS and proteinuria/AKI (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B30">30</xref>). Here, we report increased HPSE activity and HS levels in plasma of COVID-19 patients, which were also associated with severity of the disease.</p>
<p>Several mechanisms are currently proposed to explain pulmonary edema and ARDS in COVID-19. One suggested mechanism focuses on the kallikrein/kinin system, which is involved in the local inflammation and vascular leakage in the lung (<xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B32">32</xref>). Over-activation of the bradykinin pathway may occur due to consumption of angiotensin converting enzyme-2 (ACE2) during viral entry (<xref ref-type="bibr" rid="B32">32</xref>). Interestingly, endothelial cell surface GAGs, such as HS, regulate activation of bradykinin pathways whereas degradation of HS by bacterial heparinases promotes proteolytic bradykinin generation (<xref ref-type="bibr" rid="B33">33</xref>). Therefore, increased plasma HPSE activity in COVID-19 patients could contribute to activation of the bradykinin pathway, and subsequently vascular leakage and local inflammation. The renin-angiotensin system also could be involved in endothelial dysfunction in COVID-19 patients (<xref ref-type="bibr" rid="B34">34</xref>). Increased angiotensin II levels have been reported in COVID-19 patients (<xref ref-type="bibr" rid="B35">35</xref>). Angiotensin II induces vasoconstriction, inflammation, fibrosis, and proliferation, which in turn can cause thrombosis, ARDS, and AKI. Importantly, we have previously shown that Angiotensin II is a potent inducer of HPSE expression (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>). Moreover, it is feasible that endothelin-1, one of the downstream mediators activated by angiotensin II (<xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B39">39</xref>) is also increased in COVID-19 and it is known that endothelin-1 can induce HPSE expression as well (<xref ref-type="bibr" rid="B40">40</xref>).</p>
<p>Besides the role of HPSE in compromising the endothelial glycocalyx, HPSE and HS fragments play an important role in inflammation (<xref ref-type="bibr" rid="B41">41</xref>). HPSE can activate macrophages, resulting in secretion of MCP-1, TNF-&#x3b1;, and IL-1&#x3b2;, independent of HS-degrading activity (<xref ref-type="bibr" rid="B42">42</xref>). Released HS fragments also induce a pro-inflammatory response by binding to TLR2 and TLR4 (<xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B43">43</xref>). Moreover, cleavage of HS by HPSE releases HS bound molecules, such as chemokines and cytokines, thereby promoting inflammation (<xref ref-type="bibr" rid="B44">44</xref>). Furthermore, cells exposed to HPSE show an enhanced response to pro-inflammatory cytokines like IFN-&#x3b3; (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B46">46</xref>). Interestingly, cytokines such as IL-1&#x3b2;, IL-6, TNF-&#x3b1;, and MCP-1 appear to be elevated in COVID-19 patients (<xref ref-type="bibr" rid="B47">47</xref>&#x2013;<xref ref-type="bibr" rid="B49">49</xref>) and also can induce HPSE expression (<xref ref-type="bibr" rid="B15">15</xref>). These data suggest the formation of a HPSE-mediated positive feed forward loop for inflammation in COVID-19. Notably, HPSE appears to have a direct effect in shaping the cytokine milieu, since HPSE deficiency reduces expression of a wide range of cytokines including TNF-&#x3b1;, IL-6, IFN-&#x3b3; in experimental models (<xref ref-type="bibr" rid="B15">15</xref>).</p>
<p>Potential beneficial effects of prophylactic as well as therapeutic doses of LMWH in COVID-19 patients have been reported (<xref ref-type="bibr" rid="B50">50</xref>&#x2013;<xref ref-type="bibr" rid="B53">53</xref>). Our data reveal that prophylactic doses of LMWH is associated with reduced HPSE activity in moderately diseased COVID-19 patients while this reduction of HPSE activity with LMWH prophylaxis was not accompanied with a reduction in HS or IL-6 plasma levels. Moreover, HPSE activity remained high in COVID-19 patients in ICU, all of whom received prophylactic LMWH as part of standard ICU treatment regimen. Therefore, therapeutic LMWH dose instead of prophylactic dose might be required to further inhibit HPSE both in non-ICU and ICU COVID-19 patients. This further reduction of HPSE activity might eventually lead to additional beneficial effect, such as reduced HS and IL-6 plasma levels. In addition to inhibition of HPSE, LMWH has other non-anticoagulant functions that may be beneficial for patients with COVID-19, such as neutralization of chemokines/cytokines, interference with leukocyte trafficking, neutralization of extracellular cytotoxic histones, neutralization of high molecular weight kinogen, and reduction of viral entry (<xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B54">54</xref>&#x2013;<xref ref-type="bibr" rid="B57">57</xref>).</p>
<p>In summary, this cross-sectional study shows that HPSE activity and HS levels are significantly elevated in plasma of COVID-19 patients, which is associated with the severity of COVID-19. Targeting of HPSE activity could be beneficial for the clinical outcome of COVID-19 patients, since it is well established that increased HPSE activity compromises the endothelial glycocalyx and contributes to a pro-inflammatory cytokine milieu. Considering the fact that no specific clinically approved heparanase inhibitors are currently available, prospective studies evaluating the clinical outcome of COVID-19 patients treated with therapeutic doses of LMWH are urgently needed.</p>
</sec>
<sec id="s5">
<title>Author&#x2019;s Note</title>
<p>This manuscript has been released as a preprint at medRxiv (<xref ref-type="bibr" rid="B58">58</xref>).</p>
</sec>
<sec id="s6">
<title>Data Availability Statement</title>
<p>All datasets presented in this study are included in the article/supplementary material.</p>
</sec>
<sec id="s7">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by the Local Independent Ethical Committee, Radboud University Medical Center, Nijmegen, Netherlands. The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s8">
<title>Author Contributions</title>
<p>BB, CY, QdM, and JvdV designed the experiments, analyzed data, and wrote the manuscript. BB, CY, and MdG performed the experiments. AdN, IG, NAFJ, LABJ, MGN, and FLvdV were co-investigators on CMO 2020-6344, which provided COVID-19 patient samples. BB, CY, IJ, NR, RD, and JvdV were co-investigators on CMO 2020-6359, which provided COVID-19 patient samples. MK and PP were co-investigators on CMO 2016-2923, which facilitated COVID-19 ICU patient sampling. MLM-H created the graphical abstract and wrote the manuscript. TN and LH helped with analysis of the clinical data. JvdV has full access to all the data in the study and takes responsibility for the integrity of the data. All authors contributed to the article and approved the submitted version. BB and CY share first authorship and AdN and IG are co-second authors, listed in alphabetical order.</p>
</sec>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>This study was financially supported by the Radboud University Medical Center PhD fellow program and consortium grant LSHM16058-SGF (GLYCOTREAT; a collaborative project financed by the PPP allowance made available by Top Sector Life Sciences &amp; Health to the Dutch Kidney Foundation to stimulate public-private partnerships) coordinated by JvdV. MGN was supported by an ERC Advanced grant (#833247) and a Spinoza Grant of the Netherlands Organization for Scientific Research. The graphical abstract was created with BioRender.com.</p>
</sec>
<sec id="s10">
<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>
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