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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.2022.857573</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Laboratory Biomarkers for Diagnosis and Prognosis in COVID-19</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Battaglini</surname>
<given-names>Denise</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="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/990025"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lopes-Pacheco</surname>
<given-names>Miqu&#xe9;ias</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/248643"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Castro-Faria-Neto</surname>
<given-names>Hugo C.</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/394039"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pelosi</surname>
<given-names>Paolo</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/803249"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Rocco</surname>
<given-names>Patricia R. M.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/175776"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Anesthesia and Intensive Care, San Martino Policlinico Hospital, Instituto di Ricovero e Cura a Carattere Scientifico (IRCCS) for Oncology and Neuroscience</institution>, <addr-line>Genoa</addr-line>, <country>Italy</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Surgical Science and Integrated Diagnostics (DISC), University of Genoa</institution>, <addr-line>Genoa</addr-line>, <country>Italy</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Medicine, University of Barcelona</institution>, <addr-line>Barcelona</addr-line>, <country>Spain</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Laboratory of Pulmonary Investigation, Carlos Chagas Filho Biophysics Institute, Federal University of Rio de Janeiro</institution>, <addr-line>Rio de Janeiro</addr-line>, <country>Brazil</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Laboratory of Immunopharmacology, Oswaldo Cruz Institute - Fiocruz</institution>, <addr-line>Rio de Janeiro</addr-line>, <country>Brazil</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>COVID-19 Virus Network from Brazilian Council for Scientific and Technological Development</institution>, <addr-line>Bras&#xed;lia</addr-line>, <country>Brazil</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>COVID-19 Virus Network from Foundation Carlos Chagas Filho Research Support of the State of Rio de Janeiro</institution>, <addr-line>Rio de Janeiro</addr-line>, <country>Brazil</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Xin-Xin Zhang, Shanghai Public Health Clinical Center, China</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Barbara Bottazzi, University of Milan, Italy; Chun Fang Gao, Shanghai University of Traditional Chinese Medicine, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Patricia R. M. Rocco, <email xlink:href="mailto:prmrocco@gmail.com">prmrocco@gmail.com</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Viral Immunology, a section of the journal Frontiers in Immunology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>27</day>
<month>04</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>13</volume>
<elocation-id>857573</elocation-id>
<history>
<date date-type="received">
<day>18</day>
<month>01</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>31</day>
<month>03</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Battaglini, Lopes-Pacheco, Castro-Faria-Neto, Pelosi and Rocco</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Battaglini, Lopes-Pacheco, Castro-Faria-Neto, Pelosi and Rocco</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>Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) causes a wide spectrum of clinical manifestations, with progression to multiorgan failure in the most severe cases. Several biomarkers can be altered in coronavirus disease 2019 (COVID-19), and they can be associated with diagnosis, prognosis, and outcomes. The most used biomarkers in COVID-19 include several proinflammatory cytokines, neuron-specific enolase (NSE), lactate dehydrogenase (LDH), aspartate transaminase (AST), neutrophil count, neutrophils-to-lymphocytes ratio, troponins, creatine kinase (MB), myoglobin, D-dimer, brain natriuretic peptide (BNP), and its N-terminal pro-hormone (NT-proBNP). Some of these biomarkers can be readily used to predict disease severity, hospitalization, intensive care unit (ICU) admission, and mortality, while others, such as metabolomic and proteomic analysis, have not yet translated to clinical practice. This narrative review aims to identify laboratory biomarkers that have shown significant diagnostic and prognostic value for risk stratification in COVID-19 and discuss the possible clinical application of novel analytic strategies, like metabolomics and proteomics. Future research should focus on identifying a limited but essential number of laboratory biomarkers to easily predict prognosis and outcome in severe COVID-19.</p>
</abstract>
<kwd-group>
<kwd>biomarkers</kwd>
<kwd>COVID-19</kwd>
<kwd>inflammation</kwd>
<kwd>metabolomics</kwd>
<kwd>proteomics</kwd>
</kwd-group>
<contract-sponsor id="cn001">Conselho Nacional de Desenvolvimento Cient&#xed;fico e Tecnol&#xf3;gico<named-content content-type="fundref-id">10.13039/501100003593</named-content>
</contract-sponsor>
<contract-sponsor id="cn002">Conselho Nacional de Desenvolvimento Cient&#xed;fico e Tecnol&#xf3;gico<named-content content-type="fundref-id">10.13039/501100003593</named-content>
</contract-sponsor>
<contract-sponsor id="cn003">Funda&#xe7;&#xe3;o Carlos Chagas Filho de Amparo &#xe0; Pesquisa do Estado do Rio de Janeiro<named-content content-type="fundref-id">10.13039/501100004586</named-content>
</contract-sponsor>
<contract-sponsor id="cn004">Financiadora de Estudos e Projetos<named-content content-type="fundref-id">10.13039/501100004809</named-content>
</contract-sponsor>
<counts>
<fig-count count="2"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="112"/>
<page-count count="11"/>
<word-count count="4777"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) causes a wide spectrum of clinical manifestations, from mild respiratory symptoms to pneumonia and, in more severe cases, multiple organ failure (<xref ref-type="bibr" rid="B1">1</xref>). The mechanisms underlying multisystem involvement may include an unbalanced immune response that facilitates the progression of coronavirus disease-2019 (COVID-19). This hypothesis has been confirmed by laboratory biomarker alterations, showing greater potential for abnormal immune response, mainly an increase in neutrophil counts and a substantial reduction in lymphocyte counts, thus altering the neutrophil-to-lymphocyte ratio. Such an abnormal immune response is driven by an increased serum concentration of many pro-inflammatory mediators. These include interleukin (IL)-1&#x3b2;, IL-2, IL-6, IL-8, interferon (IFN)-&#x3b3;-induced protein 10, granulocyte colony-stimulating factor, monocyte chemoattractant protein 1, macrophage inflammatory protein-1&#x3b1;, and tumor necrosis factor-&#x3b1;, among others (<xref ref-type="bibr" rid="B2">2</xref>&#x2013;<xref ref-type="bibr" rid="B5">5</xref>). Nevertheless, the inflammatory cytokine storm in patients with COVID-19 is less injurious than that observed in patients with sepsis or acute respiratory distress syndrome (ARDS) but without COVID-19 (<xref ref-type="bibr" rid="B6">6</xref>), thus raising questions regarding the mechanisms underlying multiorgan involvement in COVID-19.</p>
<p>Several biomarkers other than cytokines have been found altered in COVID-19, and are associated with diagnosis, prognosis and outcomes (<xref ref-type="bibr" rid="B7">7</xref>). Some of these biomarkers can be easily used to predict disease severity, hospitalization, intensive care unit (ICU) admission, and mortality, while others, like metabolomic and proteomic analysis, are still of purely investigational concern and difficult to translate into clinical practice, despite their prognostic potential (<xref ref-type="bibr" rid="B8">8</xref>&#x2013;<xref ref-type="bibr" rid="B10">10</xref>).</p>
<p>The aim of this narrative review is to identify laboratory biomarkers that have shown significant diagnostic and prognostic value for risk stratification in COVID-19 and to discuss the possible clinical application of novel analytic strategies, such as metabolomics and proteomics.</p>
</sec>
<sec id="s2">
<title>Potential for Multiorgan Involvement in COVID-19</title>
<p>SARS-CoV-2 is an enveloped, single-stranded ribonucleic acid (ssRNA) virus. The SARS-CoV-2 genome is composed of two polypeptides encoded between two open-reading frames that are processed by viral proteases to produce nonstructural proteins (<xref ref-type="bibr" rid="B11">11</xref>). These proteins are involved in viral replication and suppression of host innate immune defense. On the other hand, structural proteins of SARS-CoV-2 include the spike (S), envelope (E), and nucleocapsid (N) protein, as well as the membrane (M) glycoprotein. The S protein is a transmembrane glycoprotein that is located on the viral surface and cleaved by host-cell proteases. After anchoring the S protein, SARS-CoV-2 enters host cells <italic>via</italic> angiotensin receptor-2 (ACE2), thus activating transmembrane serine protease 2 (TMPRSS2), cathepsin B and L. The E protein is a glycoprotein involved in virion maturation and pathogenesis, while the M protein is involved in viral assembly and delineates the shape of the viral envelope; finally, the N protein binds directly to viral RNA (<xref ref-type="bibr" rid="B11">11</xref>). The pathogenic mechanisms of SARS-CoV-2 include 1) direct epithelial damage, 2) dysregulated immune response, 3) ACE2 dysregulation and downregulation of the renin-angiotensin- aldosterone system (RAAS), 4) direct endothelial damage, and, possibly, 5) tissue fibrosis (<xref ref-type="bibr" rid="B11">11</xref>). Hence, patients with severe COVID-19 are at high risk of multiple organ involvement and, ultimately, death. Indeed, the virus has been identified in multiple tissues, including endothelial, liver, kidney, pulmonary, and neuronal cells, suggesting direct invasion as possible pathological mechanism underlying systemic effects (<xref ref-type="bibr" rid="B1">1</xref>). Therefore, laboratory biomarkers of organ damage play a key role in the diagnosis, prediction, and prognosis of patients at high risk of multiorgan involvement, and their use should be implemented in clinical practice (<xref ref-type="bibr" rid="B1">1</xref>). <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> summarizes the most investigated biomarkers in COVID-19, while <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref> depicts possible multiorgan involvement in COVID-19. In the following section, we will describe individual organ systems and how they can be affected by severe COVID-19, associated laboratory and clinical biomarkers of damage, severity, and outcome, and their potential utility for patient management.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Laboratory biomarkers in COVID-19.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" align="center">Biomarkers</th>
<th valign="top" align="center">Clinical significance</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="7" align="left">
<bold>Pulmonary function</bold>
</td>
<td valign="top" align="left">NSE</td>
<td valign="top" align="left">Dyspnea</td>
</tr>
<tr>
<td valign="top" align="left">LDH, AST</td>
<td valign="top" align="left">Mortality at admission, longer IMV</td>
</tr>
<tr>
<td valign="top" align="left">Surfactant protein-D, angiopoietin-2, TREM-1, TREM-2</td>
<td valign="top" align="left">Severity</td>
</tr>
<tr>
<td valign="top" align="left">Thiol, ferritin, LDH</td>
<td valign="top" align="left">ARDS development</td>
</tr>
<tr>
<td valign="top" align="left">Platelet count, neutrophils/lymphocyte ratio, CRP, D-dimer, ferritin</td>
<td valign="top" align="left">Survival at extubation</td>
</tr>
<tr>
<td valign="top" align="left">Kynurenine, <italic>p</italic>-cresol sulphate</td>
<td valign="top" align="left">Longer IMV</td>
</tr>
<tr>
<td valign="top" align="left">Metabolomic/proteomic: PPAR, D-arginine, D-ornithine, TRP, alpha linoleic</td>
<td valign="top" align="left">Fibrosis</td>
</tr>
<tr>
<td valign="top" rowspan="4" align="left">
<bold>Inflammation and infection</bold>
</td>
<td valign="top" align="left">PCT</td>
<td valign="top" align="left">Severity, mortality</td>
</tr>
<tr>
<td valign="top" align="left">Neutrophil count</td>
<td valign="top" align="left">Clinical outcome, mortality</td>
</tr>
<tr>
<td valign="top" align="left">Neutrophil/lymphocyte ratio</td>
<td valign="top" align="left">Severity, mortality</td>
</tr>
<tr>
<td valign="top" align="left">Lymphocyte count, CD3+, 4+, 8+, 25+, 127-, NK cells</td>
<td valign="top" align="left">Severity, mortality</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="left">
<bold>Cardiovascular function</bold>
</td>
<td valign="top" align="left">NPs, troponins</td>
<td valign="top" align="left">CV disease, inflammation, mortality</td>
</tr>
<tr>
<td valign="top" align="left">MR-proADM</td>
<td valign="top" align="left">Survival</td>
</tr>
<tr>
<td valign="top" align="left">CK-MB, myoglobin, D-dimer, BNP, NT-proBNP, neutrophil/lymphocyte ratio</td>
<td valign="top" align="left">Prognosis</td>
</tr>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Coagulation and hemostasis</bold>
</td>
<td valign="top" align="left">D-dimer</td>
<td valign="top" align="left">Mortality</td>
</tr>
<tr>
<td valign="top" align="left">Plasma fibrinogen</td>
<td valign="top" align="left">Hyperinflammation, severity</td>
</tr>
<tr>
<td valign="top" align="left">sVCAM-1, vWF, thrombomodulin, sTNFRI, HS, C5b9, PAI-1, alpha-2 antiplasmin</td>
<td valign="top" align="left">Severity</td>
</tr>
<tr>
<td valign="top" align="left">vWF, ADAMTS13</td>
<td valign="top" align="left">Mortality</td>
</tr>
<tr>
<td valign="top" align="left">Endothelial dysfunction</td>
<td valign="top" align="left">Severity of pulmonary impairment</td>
</tr>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Metabolic system</bold>
</td>
<td valign="top" align="left">HDL cholesterol</td>
<td valign="top" align="left">Risk of hospitalization</td>
</tr>
<tr>
<td valign="top" align="left">LDL cholesterol</td>
<td valign="top" align="left">Inflammation</td>
</tr>
<tr>
<td valign="top" align="left">Vitamin A</td>
<td valign="top" align="left">ARDS development, mortality</td>
</tr>
<tr>
<td valign="top" align="left">Metabolomic/proteomic: cAMP</td>
<td valign="top" align="left">Mortality</td>
</tr>
<tr>
<td valign="top" align="left">Thyroid hormones</td>
<td valign="top" align="left">Severity, mortality</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Neurological manifestations</bold>
</td>
<td valign="top" align="left">GFAP, NfL, tau, S100B, NSE, inflammatory markers</td>
<td valign="top" align="left">Inflammation, severity</td>
</tr>
<tr>
<td valign="top" align="left">D-dimer, LDH, ESR, CRP, lymphocytes, PCT, creatinine</td>
<td valign="top" align="left">Occurrence of ischemic stroke</td>
</tr>
<tr>
<td valign="top" rowspan="6" align="left">
<bold>Kidney and liver function</bold>
</td>
<td valign="top" align="left">Urine 11-dehydro-thromboxane B2, 8-hydroxy-2&#x2019;-deoxyguanosine, L-FABP</td>
<td valign="top" align="left">Hospitalization</td>
</tr>
<tr>
<td valign="top" align="left">N-acetyl-&#x3b2;-D-glucosaminidase, &#x3b2;2-microglobulin, &#x3b1;1-microglobulin, L-FABP</td>
<td valign="top" align="left">Hyperinflammation</td>
</tr>
<tr>
<td valign="top" align="left">PCT, arterial saturation of oxygen, blood urea nitrogen</td>
<td valign="top" align="left">Acute kidney injury</td>
</tr>
<tr>
<td valign="top" align="left">Creatinine</td>
<td valign="top" align="left">Acute kidney injury, mortality</td>
</tr>
<tr>
<td valign="top" align="left">Urine blood, urine weight</td>
<td valign="top" align="left">Mortality</td>
</tr>
<tr>
<td valign="top" align="left">Albumin, direct albumin, neutrophils, lymphocytes, mean corpuscular hemoglobin</td>
<td valign="top" align="left">Severity</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ADAMTS, a disintegrin and metalloproteinase with thrombospondin motifs, ARDS, acute respiratory distress syndrome, AST, aspartate aminotransferase, BNP, brain natriuretic peptide, cAMP, adenosine cyclic monophosphate, CD, cluster differentiation, CK-MB, creatine kinase, CRP, C-reactive protein, CV, cardiovascular, ESR, erythrocyte sedimentation rate, GFAP, glial fibrillary acidic protein, HDL, high density lipoproteins, HS, heparan sulfate, IMV, invasive mechanical ventilation, L-FABP, liver-type fatty acid binding protein, LDH, lactate dehydrogenase, LDL, low density lipoproteins, MR-proADM, mid-regional pro-adrenomedullin, NfL, neurofilament light polypeptide, NK, natural killer, NPs, natriuretic peptides, NSE, neuron specific enolase, NT-proBNP, N-terminal pro-hormone, PAI, plasminogen activator inhibitor, PCT, procalcitonin, PPAR, peroxisome proliferator-activated receptors, sTNFRI soluble tumor necrosis factor receptor I, sVCAM-1, vascular cells adhesion molecule-1, TREM, triggering receptor expressed on myeloid cells, TRP, transient receptor potential channel, vWF, von Willebrand.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>COVID-19 multiple organ dysfunction. This figure shows the potential for multiorgan involvement in COVID-19. Respiratory (AIP, acute interstitial pneumonia; ARDS, acute respiratory distress syndrome; DAD, diffuse alveolar damage), renal, cardiovascular, coagulative/hemostatic, liver, gastrointestinal, metabolic/endocrine, and cerebral functions and systems, as well as their possible alterations, are presented.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-857573-g001.tif"/>
</fig>
</sec>
<sec id="s3">
<title>Diagnostic and Prognostic Value of Biomarkers</title>
<p>Biomarkers reflecting multiple organ involvement and/or pharmacological effects have been widely examined in critically ill patients. Some of these biomarkers are also used to monitor dysfunction in distinct organs at the same time, due to their redundancy or non-specificity. However, the most appropriate biomarkers to be studied in critically ill patients with COVID-19 have yet to be defined. <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref> depicts a proposed algorithm for critical care management which includes the investigation of biomarkers in severe COVID-19 patients at ICU admission.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Proposed algorithm for the management of patients with COVID-19 at ICU admission. This figure shows a potential algorithm for initial patient management at ICU admission, including the most useful biomarkers to be used in the COVID-19 critical care setting. Neurological system: sequential transcranial doppler (TCD) and/or optic nerve sheath diameter (ONSD) in sedated patients for whom conventional neurological evaluation is impossible. Cardiovascular system: electrocardiogram and echocardiography, as well as continuous monitoring of mean arterial pressure (MAP) and heart rate (HR), are suggested on ICU admission. Respiratory system: computed tomography (CT) scan is the gold standard; if not feasible, chest X-ray, CT angiography, and/or lung ultrasound should be performed. Lactate dehydrogenase (LDH), C-reactive protein (CRP), neuron specific enolase (NSE), neurofilament light polypeptide (NfL), glial fibrillary acidic protein (GFAP), thyrotropic stimulating hormone (TSH), NGAL, aspartate transaminase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (&#x3b3;GT), interleukin-6 (IL-6). BNP, brain natriuretic peptide; UN, urea nitrogen; NT-proBNP, N-terminal pro-hormone.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-857573-g002.tif"/>
</fig>
<sec id="s3_1">
<title>Respiratory System</title>
<p>The lungs are usually the organs affected primarily by SARS-CoV-2, due to their large and highly vascularized surface area (<xref ref-type="bibr" rid="B11">11</xref>). The pathogenesis of COVID-19 in the lung includes an initial phase of local inflammation, endothelial cell damage, and antifibrinolytic activation in the upper and lower respiratory tracts, followed by repair mechanisms that can elicit the restoration of normal pulmonary architecture. Inflammation is followed by platelet recruitment with degranulation, clot formation, altered vessel permeability, and accumulation of leukocytes in the injury site, leading to the recruitment of other inflammatory cells with the involvement of specific cytokines (i.e., IL-4, IL-13, transforming growth factor-&#x3b2;) that are also responsible for pro-fibrotic activity (<xref ref-type="bibr" rid="B12">12</xref>).</p>
<p>SARS-CoV-2 lung infection causes a wide variety of clinical manifestations and symptoms, from asymptomatic, mild, and moderate disease to severe COVID-19. Severe and critical illness accounts for up to 14% and 5% of cases, respectively, with the ARDS occurring in 10-20% of patients; multiorgan failure and death may supervene (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>). Various phenotypes have been identified by computed tomography (CT) (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>), including phenotype L or 1, which is characterized by low compliance, altered ventilation and perfusion, and shunting with focal hypo/hyper-perfused ground-glass opacities; and phenotype H or 2, which is identified by an inhomogeneous distribution of atelectasis with a patchy ARDS-like pattern (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>). Progressive evolution of COVID-19 (<xref ref-type="bibr" rid="B19">19</xref>) may lead to phenotype F, caused by mechanical stretch of lung epithelial cells and pathological fibro-proliferation and remodeling of the extracellular matrix, with increased expression of pro-fibrotic markers, as is mainly typical of severe forms of lung disease (<xref ref-type="bibr" rid="B20">20</xref>).</p>
<p>Although not specific to pulmonary disease, several biomarkers of different stages of lung involvement in COVID-19 have been identified and have been associated with pulmonary and systemic hyperinflammation and fibrotic damage (<xref ref-type="bibr" rid="B12">12</xref>). In the early disease course, neuron-specific enolase (NSE) can be used to differentiate patients who are going to develop dyspnea (<xref ref-type="bibr" rid="B21">21</xref>). On admission, higher lymphocyte and platelet counts and lower ferritin, D-dimer, lactate dehydrogenase (LDH), and aspartate transaminase (AST) have all been associated with lower risk of mortality in COVID-19 patients who ultimately required intubation and mechanical ventilation (<xref ref-type="bibr" rid="B22">22</xref>). Surfactant protein-D, angiopoietin-2, triggering receptor expressed on myeloid cell (TREM)-1, and TREM-2 levels were found to be higher in mild/moderate and severe/critical COVID-19 pneumonia than in asymptomatic and uncomplicated cases. Moreover, these biomarkers correlated well with clinical severity (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>). In severe COVID-19 cases, total thiol, ferritin, and LDH were identified as prognostic biomarkers for ARDS development (<xref ref-type="bibr" rid="B25">25</xref>). At extubation, COVID-19 survivors had higher platelet counts and neutrophil-to-lymphocyte ratios and lower C-reactive protein (CRP), D-dimer, ferritin, LDH, and AST (<xref ref-type="bibr" rid="B22">22</xref>).</p>
</sec>
<sec id="s3_2">
<title>Infection and Systemic Inflammatory Response</title>
<p>Following SARS-CoV-2 invasion of the host cells, the virus replicates at the infection site, thus triggering activation of the innate and adaptive immune responses (<xref ref-type="bibr" rid="B26">26</xref>). Neutrophils are rapidly recruited to infection foci, while innate cells recognize the virus and secrete multiple cytokines. Antigen-presenting cells recognize viral antigens which are carried to the local lymph nodes, while activating the T-helper cell response, which is also responsible for stimulating B cells to secrete antibodies (<xref ref-type="bibr" rid="B27">27</xref>). The systemic immune-inflammatory response is activated; if left unchecked, this may progress to multiorgan illness (<xref ref-type="bibr" rid="B28">28</xref>).</p>
<p>Patients with severe COVID-19 are highly susceptible to superimposed bacterial, fungal, and viral infections, including ventilator-associated pneumonia and bloodstream infection, among others (<xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). As for systemic biomarkers of infection, procalcitonin is a predictor of disease severity (<xref ref-type="bibr" rid="B31">31</xref>), and can be useful to guide antimicrobial stewardship (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B33">33</xref>). Another study found an association between procalcitonin and mortality in COVID-19 patients more than 75 years old (<xref ref-type="bibr" rid="B34">34</xref>). Neutrophil count was also predictive of clinical outcome in hospitalized COVID-19 patients (<xref ref-type="bibr" rid="B35">35</xref>), while the neutrophil-to-lymphocyte ratio was strongly associated with severity and mortality in COVID-19 (<xref ref-type="bibr" rid="B36">36</xref>). Additionally, total lymphocyte count, cluster differentiation (CD)3<sup>+</sup>, CD4<sup>+</sup>, CD8<sup>+</sup>, CD25<sup>+</sup>, CD127<sup>&#x2013;</sup> T cells, and natural killer (NK) cells were found to be depressed in severe COVID-19 (<xref ref-type="bibr" rid="B37">37</xref>), whereas C-reactive protein, erythrocyte sedimentation rate, and IL-6 &#x2013; common markers of inflammation &#x2013; were elevated (<xref ref-type="bibr" rid="B38">38</xref>).</p>
</sec>
<sec id="s3_3">
<title>Cardiovascular System</title>
<p>SARS-CoV-2 can directly trigger endothelial dysfunction, causing a status known as COVID-19-associated coagulopathy. After viral entry into the cells, increased vascular permeability and tissue factor expression in subendothelial cells, with activation of platelets and leukocytes, may trigger the coagulation cascade. Endothelial damage and a generalized inflammatory state are drivers of thrombosis, which can contribute to cardiovascular manifestations (<xref ref-type="bibr" rid="B39">39</xref>).</p>
<p>Cardiovascular manifestations of COVID-19 are frequently reported (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B40">40</xref>). Acute heart failure and exacerbation of chronic heart failure are reported in up to 20-30% of hospitalized patients, and carry high mortality rates, especially in patients with severe comorbidities (<xref ref-type="bibr" rid="B41">41</xref>&#x2013;<xref ref-type="bibr" rid="B43">43</xref>). Acute coronary syndrome has been reported in a high proportion of patients, probably because of plaque rupture, coronary spasm, or microthrombi triggered by systemic inflammation and cytokine storm (<xref ref-type="bibr" rid="B44">44</xref>). In general, the mechanisms underlying cardiovascular manifestations include increased cardiac workload, hypoxemia, hypervolemia, myocardial injury, arrhythmias, myocarditis, stress-induced cardiomyopathy, acute kidney injury, and, as noted above, systemic inflammatory response with the release of several cytokines and chemokines (<xref ref-type="bibr" rid="B45">45</xref>). Triggering mechanisms may be attributed to an imbalance between heightened cardiac workload and reduced oxygen supply secondary to systemic conditions, with possible type-2 myocardial infarction (<xref ref-type="bibr" rid="B46">46</xref>).</p>
<p>Cardiac biomarkers (<xref ref-type="bibr" rid="B47">47</xref>), electrocardiography (ECG), and transthoracic echocardiography (TTE) play a pivotal role in risk stratification and early detection of cardiovascular complications, as well as to guide treatment (<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B49">49</xref>). Recent evidence confirmed that cardiac biomarkers, including natriuretic peptides (NPs) and troponins, may reflect cardiovascular involvement and inflammation in COVID-19, and are strongly associated with poor prognosis and mortality (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B50">50</xref>&#x2013;<xref ref-type="bibr" rid="B53">53</xref>). In some cases, troponin elevation in COVID-19 has been associated with ECG changes (<xref ref-type="bibr" rid="B54">54</xref>), ICU admission, and in-hospital death (<xref ref-type="bibr" rid="B55">55</xref>, <xref ref-type="bibr" rid="B56">56</xref>). However, despite the confirmed prognostic impact of troponins, routine testing is still a matter of debate, because of several other variables that have been associated with outcome and prognosis (<xref ref-type="bibr" rid="B48">48</xref>). Additionally, pre-existing cardiac disease and/or acute stress injury may justify mild elevations in cardiac troponins, while myocarditis, Takotsubo syndrome, type 2 myocardial infarction triggered by severe respiratory failure, systemic hypoxemia, or shock are mostly associated with more marked increase in troponins (<xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B57">57</xref>, <xref ref-type="bibr" rid="B58">58</xref>). Other cardiac and non-cardiac biomarkers are common findings in COVID-19-associated cardiovascular disease, including creatine kinase (CK)-MB, myoglobin, D-dimer, brain natriuretic peptide (BNP) and its N-terminal pro-hormone (NT-proBNP), and neutrophil-to-lymphocyte ratio (<xref ref-type="bibr" rid="B55">55</xref>, <xref ref-type="bibr" rid="B59">59</xref>&#x2013;<xref ref-type="bibr" rid="B61">61</xref>). Myoglobin seems to offer higher prognostic accuracy than other cardiac-specific biomarkers (troponins and CK-MB) in COVID-19 (<xref ref-type="bibr" rid="B62">62</xref>). Moreover, mid-regional pro-adrenomedullin (MR-proADM) levels were found to be associated with endothelial dysfunction and mortality in COVID-19, potentially making it an optimal biomarker for the prediction of survival in this patient population (<xref ref-type="bibr" rid="B63">63</xref>). Nevertheless, only limited evidence exists so far to define any of these biomarkers as an independent predictor of prognosis in COVID-19 (<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B64">64</xref>).</p>
</sec>
<sec id="s3_4">
<title>Coagulation and Hemostasis</title>
<p>Coagulation derangement is a well-known systemic effect of COVID-19 that can originate from direct or indirect viral impact on the endothelium, or from immunothrombosis (<xref ref-type="bibr" rid="B65">65</xref>). COVID-19 can cause alterations in the coagulation cascade, with imbalance of the regulatory mechanisms of coagulation and fibrinolysis, altered platelet function, and a hyperinflammatory response (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B65">65</xref>). In this context, D-dimer has been identified among the first altered coagulation biomarkers in COVID-19, and is predictive of mortality on admission (<xref ref-type="bibr" rid="B66">66</xref>). Similarly, plasma fibrinogen appears to be associated with hyperinflammation and disease severity in COVID-19 (<xref ref-type="bibr" rid="B67">67</xref>). A coagulopathy signature diagnostic of COVID-19 has been identified, including elevated levels of soluble vascular cell adhesion molecule (sVCAM)-1 (<xref ref-type="bibr" rid="B68">68</xref>), von Willebrand Factor (vWF), thrombomodulin, soluble tumor necrosis factor (TNF) receptor I (sTNFRI), heparan sulfate, C5b9 complement, plasminogen activator inhibitor (PAI)-1, and alpha-2 antiplasmin, among others. Some of these markers, such as sVCAM-1, vWF, sTNFRI, and heparan sulfate, were also associated with disease severity (<xref ref-type="bibr" rid="B69">69</xref>). Fibrinogen, thrombin peak, vWF, and ADAMTS13 at admission and elevated vWF : Ag to ADAMTS13 activity ratio were associated with severity and higher risk of death (<xref ref-type="bibr" rid="B70">70</xref>, <xref ref-type="bibr" rid="B71">71</xref>). Endothelial dysfunction seems to be persistent after resolution of COVID-19, and directly associated with the severity of pulmonary impairment (<xref ref-type="bibr" rid="B72">72</xref>).</p>
</sec>
<sec id="s3_5">
<title>Metabolic Function</title>
<p>Sphingolipid metabolism regulates the inflammation and immune response through the conversion of sphingosine to sphingosine 1-phosphate, increasing the release of lymphocytes into the blood, with subsequent systemic inflammation and release of cytokines and chemokines in COVID-19 (<xref ref-type="bibr" rid="B73">73</xref>). Like lipid metabolism, fat-soluble vitamins such as vitamin D have been implicated in suppressing the cytokine storm and enhancing the immune response (<xref ref-type="bibr" rid="B74">74</xref>). Investigating lipid metabolism and its biomarkers could thus be of diagnostic and prognostic value in COVID-19.</p>
<p>Metabolic comorbidities including obesity, diabetes, cardiovascular, and hypertension have been associated with poor prognosis in COVID-19 (<xref ref-type="bibr" rid="B75">75</xref>). A certain degree of metabolic dysregulation has been found in COVID-19, possibly due to immune-triggered inflammation and hypercoagulability, as well as microbial changes in host physiology (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B76">76</xref>). Indeed, COVID-19 patients with lower levels of high-density lipoprotein (HDL) cholesterol are more susceptible to hospitalization, while low-density lipoprotein (LDL) cholesterol was associated with higher inflammation (<xref ref-type="bibr" rid="B77">77</xref>). Critically ill patients with COVID-19 showed significantly lower levels of vitamin A than non-critical ones, and this was associated with higher inflammation (<xref ref-type="bibr" rid="B78">78</xref>). Vitamin A levels below 0.2 mg/L were significantly associated with the developments of ARDS and higher mortality (<xref ref-type="bibr" rid="B78">78</xref>). Vitamin D, a well-known regulator of phosphate and calcium metabolism with immunomodulatory functions, seems to not influence mortality or hospital length of stay in COVID-19 (<xref ref-type="bibr" rid="B79">79</xref>, <xref ref-type="bibr" rid="B80">80</xref>). Finally, thyroid hormones showed marked association with disease severity and mortality, suggesting the importance of early assessment of thyroid function &#x2013; and, when necessary, initiation of treatment &#x2013; in hospitalized COVID-19 patients (<xref ref-type="bibr" rid="B81">81</xref>).</p>
</sec>
<sec id="s3_6">
<title>Neurologic Involvement</title>
<p>Pathogenetic mechanisms of SARS-CoV-2 neurologic manifestations include possible spreading of the virus across the blood-brain barrier <italic>via</italic> leukocyte migration or sluggish movement of blood within the microcirculation, thus binding to endothelial cells. Cells which may present ACE2 receptors, including neurons, astrocytes, and oligodendrocytes, can all be affected directly by viral entry and activate the local immune response. As a consequence of neuronal involvement, several biomarkers of neuroinflammation and damage can be detected (<xref ref-type="bibr" rid="B82">82</xref>).</p>
<p>Although COVID-19 rarely affects the brain as a primary manifestation, neurological complications are common in this patient population (<xref ref-type="bibr" rid="B82">82</xref>&#x2013;<xref ref-type="bibr" rid="B84">84</xref>). Patients with neurological complications, compared to those without, may experience longer hospital stays, and the duration of mechanical ventilation can be associated with the risk of developing new neurological complications (<xref ref-type="bibr" rid="B84">84</xref>, <xref ref-type="bibr" rid="B85">85</xref>). CT and magnetic resonance imaging (MRI) are considered the gold standard for detecting cerebral derangements, although the use of methods which involve exposure to ionizing radiation in non-primarily brain-injured patients can only be justified in case of high suspicion of neurological complications (<xref ref-type="bibr" rid="B86">86</xref>). The use of multimodal neuromonitoring has received increasing attention as a means of identifying patients at higher risk of brain derangement because of its low cost, speed, safety, and ready availability. However, the use of neuromonitoring tools is still mainly limited to specific settings (i.e., ICU) and patient populations (i.e., those with primary brain injury) (<xref ref-type="bibr" rid="B84">84</xref>).</p>
<p>Other than imaging, blood biomarkers can detect brain damage and predict prognosis efficiently. Blood biomarkers for the study of brain derangements include glial fibrillary acidic protein (GFAP), neurofilament light polypeptide (NfL), tau, S100B calcium binding protein, NSE, and inflammatory markers. Increased GFAP staining has been found in postmortem analysis of brain tissue from patients with COVID-19 (<xref ref-type="bibr" rid="B87">87</xref>), and NfL was significantly associated with COVID-19 status (<xref ref-type="bibr" rid="B88">88</xref>). Another study reported that GFAP was increased in both moderate and severe COVID-19 cases, whereas serum NfL was increased only in severe cases compared to controls (<xref ref-type="bibr" rid="B89">89</xref>). However, another study reported that serum NfL, although elevated across patients hospitalized with COVID-19, was not associated with neurological manifestations. Additionally, the usual close correlation between cerebrospinal fluid and serum NfL was not found, suggesting serum NfL elevation in the non-neurological patients may reflect peripheral nerve damage in response to severe illness (<xref ref-type="bibr" rid="B90">90</xref>). In COVID-19 patients with altered NfL and GFAP, values of these markers had normalized in all individuals at 6-month follow-up, suggesting that post-COVID-19 neurological sequelae may be not accompanied by ongoing brain injury (<xref ref-type="bibr" rid="B91">91</xref>). Inflammatory and coagulatory markers like D-dimer, LDH, erythrocyte sedimentation rate (ESR), and CRP were independently associated with the occurrence of ischemic stroke in COVID-19 (<xref ref-type="bibr" rid="B92">92</xref>, <xref ref-type="bibr" rid="B93">93</xref>), while higher age, diabetes mellitus, and hypertension were found not to be significant predictors of stroke in this population, despite being known predictors of non-COVID-19 stroke (<xref ref-type="bibr" rid="B93">93</xref>). Levels of lymphocytes, procalcitonin, and creatinine were higher in COVID-19 stroke patients (<xref ref-type="bibr" rid="B94">94</xref>). S100B was higher in patients with mild and severe COVID-19 than in healthy controls, and may be a marker of disease severity (<xref ref-type="bibr" rid="B95">95</xref>). Antiphospholipid antibodies (i.e., anti-phosphatidylserine/prothrombin) were higher in COVID-19 patients, particularly those with neurological manifestations, than in controls. In contrast, anticardiolipin antibodies were not associated with neurologic involvement in COVID-19 (<xref ref-type="bibr" rid="B96">96</xref>).</p>
</sec>
<sec id="s3_7">
<title>Kidney and Liver</title>
<p>COVID-19 may cause kidney and liver injury by either direct infection of cells, <italic>via</italic> host immune clearance and immune tolerance disorders, endothelium-associated vasculitis, thrombus formation, metabolism and glucose disorder, or tissue hypoxia. As a consequence, biomarkers of endothelial, renal, hepatic, vascular, or hypoxic damage can help in the detection of new organ involvement and assist in determining prognosis (<xref ref-type="bibr" rid="B97">97</xref>).</p>
<p>As part of multiorgan involvement in COVID-19, kidney function might be altered directly by viral invasion or may occur secondary to multiple organ failure due to systemic inflammation or aggressive therapies (<xref ref-type="bibr" rid="B98">98</xref>). Around 25% of patients hospitalized with COVID-19 were reported to develop acute kidney injury, including low molecular weight proteinuria, Fanconi syndrome, and tubular injury (<xref ref-type="bibr" rid="B98">98</xref>). Moreover, regional inflammation, endothelial injury, and microthrombi have been identified as major causative factors of renal pathology in COVID-19. This is also sustained by the fact that anti-inflammatory drugs, such as steroids, play a key role in limiting renal disease progression (<xref ref-type="bibr" rid="B98">98</xref>). Classic diagnostic biomarkers of kidney damage include creatinine, neutrophil gelatinase-associated lipocalin (NGAL), cystatin C, kidney injury molecule-1 (KIM-1), blood and urinary urea nitrogen, and urinary proteins (<xref ref-type="bibr" rid="B99">99</xref>, <xref ref-type="bibr" rid="B100">100</xref>).</p>
<p>Novel urinary biomarkers have been proposed in COVID-19, including urine 11-dehydro-thromboxane B2, 8-hydroxy-2&#x2032;-deoxyguanosine, and liver-type fatty acid binding protein (L-FABP) levels, all of which were higher in this patient cohort at the time of hospitalization (<xref ref-type="bibr" rid="B101">101</xref>). N-acetyl-&#x3b2;-D-glucosaminidase, &#x3b2;2-microglobulin, &#x3b1;1-microglobulin, and L-FABP, which are all markers of tubular injury, were significantly associated with inflammation, as were IL-6 levels (<xref ref-type="bibr" rid="B102">102</xref>). Indeed, another observational study confirmed the association between pro-inflammatory cytokines, urinary cytokines, and urinary kidney injury markers (<xref ref-type="bibr" rid="B103">103</xref>). Procalcitonin was associated with acute kidney injury in COVID-19, and a score including simple and easily accessible variables such as procalcitonin, arterial saturation of oxygen, and blood urea nitrogen was shown to be predictive of acute kidney injury (<xref ref-type="bibr" rid="B104">104</xref>).</p>
<p>Altered serum creatinine levels with decreased kidney function at admission and up to 24 hours thereafter were significantly associated with acute kidney injury and in-hospital mortality (<xref ref-type="bibr" rid="B105">105</xref>). Additionally, urine blood &gt;0.03 mg/dL and urine specific gravity &gt;1.026 were associated with acute kidney injury, ICU admission, and higher mortality (<xref ref-type="bibr" rid="B106">106</xref>).</p>
<p>Abnormal liver and hepatobiliary function have been also identified in COVID-19 (<xref ref-type="bibr" rid="B107">107</xref>). A systematic review and meta-analysis showed a cumulative prevalence of liver disease of 24% in COVID-19, with possible alterations in albuminemia, liver enzymes, and total bilirubin (<xref ref-type="bibr" rid="B108">108</xref>). Recent findings showed that some liver and renal biomarkers, including albumin, direct bilirubin, neutrophil and lymphocyte counts, and mean corpuscular hemoglobin, are associated with risk of developing severe COVID-19 (<xref ref-type="bibr" rid="B107">107</xref>). Moreover, the presence of pre-existing liver fibrosis with silent liver injury significantly influenced mortality in COVID-19 (<xref ref-type="bibr" rid="B109">109</xref>).</p>
</sec>
</sec>
<sec id="s4">
<title>Future Perspectives: Metabolomic and Proteomic Biomarkers and Machine Learning Models</title>
<p>Given the significant immune dysregulation of COVID-19 patients, the interplay between metabolism and immunity may play a pivotal role in the disease course (<xref ref-type="bibr" rid="B110">110</xref>). Additionally, oxygen deprivation may affect homeostasis in tissues and organs such as the lung, brain, kidney, and liver. The modulation of oxygen homeostasis and response to hypoxia is mainly mediated by glycolysis and the lactate cycle. This has increased research interest in proteomic and metabolomic methods to investigate pathways linked to energy production and amino acid metabolism in patients with SARS-CoV-2 infections (<xref ref-type="bibr" rid="B110">110</xref>). Metabolomic analyses in COVID-19 patients with and without pulmonary fibrosis revealed that pathways including the peroxisome proliferator-activated receptor (PPAR), D-arginine and D-ornithine metabolism, inflammatory tryptophan metabolic pathway (TRP), and alpha-linolenic acid metabolism were significantly increased in fibrotic lungs, thus suggesting that PPAR signaling is one of the main pathways involved in the formation and development of lung fibrosis in COVID-19 (<xref ref-type="bibr" rid="B9">9</xref>). A proteomic and metabolomic analysis identified hypoxanthine and betaine as predictors of ICU stay, and early ICU admission, elevated creatinine, and D-dimer were found to be associated with these pathways (<xref ref-type="bibr" rid="B8">8</xref>). Longer duration of invasive mechanical ventilation was associated with the kynurenine and <italic>p</italic>-cresol sulfate pathways (<xref ref-type="bibr" rid="B8">8</xref>). Several markers of metabolic function identified <italic>via</italic> metabolomic analysis were associated with in-hospital mortality, including cyclic adenosine monophosphate (cAMP), which plays a role in SARS-CoV2 endocytosis in the initial phase of the disease (<xref ref-type="bibr" rid="B10">10</xref>). Another major signature of the serum metabolome in COVID-19 was lactic acid, as well as spermidine and spermine. Many other metabolites were commonly increased, including glutamate, aspartate, phenylalanine, &#x3b2;-alanine, ornithine, arachidonic acid, choline, and xanthine (<xref ref-type="bibr" rid="B110">110</xref>). Recent machine learning models have been developed to support decision making and risk stratification in COVID-19. Most predictive models rely on demographic and clinical variables. However, biomarkers have recently shown good correlation with severity of disease and mortality in COVID-19 modeling (<xref ref-type="bibr" rid="B111">111</xref>). One example was a large study of 2,895 consecutive patients with COVID-19 in whom three biomarkers measured at admission were found to reflect pathobiological axes of myocardial injury, altered coagulation, and inflammation. The machine learning model concluded that patients with low levels of these biomarkers were at lower risk of critical disease and in-hospital mortality (<xref ref-type="bibr" rid="B112">112</xref>). In conclusion, the alterations found in the serum metabolome of patients with COVID-19 may reflect a more complex systemic derangement affecting carbon and nitrogen liver metabolism, but further research is needed to completely understand the impact of these alterations on routine clinical practice. Machine learning models can be promising in risk stratification in COVID-19. However, further investigations are needed to develop mathematical models that can help clinicians select the right parameters and interpret results.</p>
</sec>
<sec id="s5">
<title>Conclusions</title>
<p>Laboratory biomarkers have shown significant diagnostic and prognostic value for risk stratification in COVID-19. Furthermore, novel analytic strategies including metabolomics and proteomics offer interesting insights for early detection of patients at higher risk of severe disease and death. However, their limited availability restricts their widespread clinical use. Further investigations are warranted to identify a core set of laboratory biomarkers which can be used in daily clinical practice to easily predict prognosis and outcome in hospitalized patients with severe COVID-19.</p>
</sec>
<sec id="s6" sec-type="author-contributions">
<title>Author Contributions</title>
<p>DB and ML-P: review, design, writing, editing. HC-F-N and PP: editing. PR: review, design, editing, senior contribution. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s7" sec-type="funding-information">
<title>Funding</title>
<p>This work was supported by the Brazilian Council for Scientific and Technological Development (COVID-19-CNPq; 401700/2020-8 and 403485/2020-7); Rio de Janeiro State Research Foundation (COVID-19-FAPERJ; E-26/210.181/2020); and Funding Authority for Studies and Projects (01200008.00), Brazil.</p>
</sec>
<sec id="s8" 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="s9" 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>The authors express their gratitude to Mrs. Moira Elizabeth Schottler and Mr Filippe Vasconcellos for their assistance in editing the paper.</p>
</ack>
<sec id="s10">
<title>Abbreviations</title>
<p>ACE2, angiotensin receptor 2; ARDS, acute respiratory distress syndrome; AST, aspartate transaminase; BNP, brain natriuretic peptide; cAMP, cyclic adenosine monophosphate; CD, cluster differentiation; CK, creatine kinase; COVID-19, coronavirus disease 2019; CRP, C-reactive protein; CT, computed tomography; ECG, electrocardiography; ESR, erythrocyte sedimentation rate; GFAP, glial fibrillary acidic protein; HDL, high-density lipoprotein; ICU, intensive care unit; IL, interleukin; KIM, kidney injury molecule; L-FABP, liver-type fatty acid binding protein; LDH, lactate dehydrogenase; LDL, low-density lipoprotein; MR-proADM, mid-regional pro-adrenomedullin; MRI, magnetic resonance imaging; NfL, neurofilament light polypeptide; NGAL, neutrophil gelatinase-associated lipocalin; NK, natural killer; NP, natriuretic peptides; NSE, neuron-specific enolase; NT-proBNP, N-terminal pro-hormone BNP; PPAR, peroxisome proliferator-activated receptor; RASS, renin-angiotensin- aldosterone system; SARS-CoV-2, severe acute respiratory syndrome-coronavirus-2; ssRNA, single-stranded ribonucleic acid; sTNFRI, soluble TNF receptor I; sVCAM, soluble vascular cell adhesion molecule; TMPRSS2, transmembrane serine protease 2; TNF, tumor necrosis factor; TREM, triggering receptor expressed on myeloid cell; TRP, tryptophan metabolic pathway; TTE, transthoracic electrocardiography; vWF, von Willebrand Factor.</p>
</sec>
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