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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Public Health</journal-id>
<journal-title>Frontiers in Public Health</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Public Health</abbrev-journal-title>
<issn pub-type="epub">2296-2565</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpubh.2021.678856</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Public Health</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Data-Independent Acquisition Proteomics Reveals Long-Term Biomarkers in the Serum of C57BL/6J Mice Following Local High-Dose Heart Irradiation</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Azimzadeh</surname> <given-names>Omid</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="http://loop.frontiersin.org/people/1264228/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>von Toerne</surname> <given-names>Christine</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Subramanian</surname> <given-names>Vikram</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Sievert</surname> <given-names>Wolfgang</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/596126/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Multhoff</surname> <given-names>Gabriele</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/30408/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Atkinson</surname> <given-names>Michael J.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/139252/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Tapio</surname> <given-names>Soile</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/318922/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Institute of Radiation Biology, Helmholtz Zentrum M&#x000FC;nchen - German Research Center for Environmental Health</institution>, <addr-line>Neuherberg</addr-line>, <country>Germany</country></aff>
<aff id="aff2"><sup>2</sup><institution>Section Radiation Biology, Federal Office for Radiation Protection</institution>, <addr-line>Oberschleissheim</addr-line>, <country>Germany</country></aff>
<aff id="aff3"><sup>3</sup><institution>Research Unit Protein Science, Helmholtz Zentrum M&#x000FC;nchen - German Research Center for Environmental Health</institution>, <addr-line>Munich</addr-line>, <country>Germany</country></aff>
<aff id="aff4"><sup>4</sup><institution>Department of Radiation Oncology, Center for Translational Cancer Research (TranslaTUM), Campus Klinikum rechts der Isar, Technical University of Munich</institution>, <addr-line>Munich</addr-line>, <country>Germany</country></aff>
<aff id="aff5"><sup>5</sup><institution>Radiation Biology, Technical University of Munich</institution>, <addr-line>Munich</addr-line>, <country>Germany</country></aff>
<aff id="aff6"><sup>6</sup><institution>Institute for Biological and Medical Imaging, Helmholtz Zentrum M&#x000FC;nchen - German Research Center for Environmental Health</institution>, <addr-line>Neuherberg</addr-line>, <country>Germany</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Lorenzo Manti, University of Naples Federico II, Italy</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Giusi Irma Forte, National Research Council, Italy; Chihaya Koriyama, Kagoshima University, Japan</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Soile Tapio <email>soile.tapio&#x00040;helmholtz-muenchen.de</email></corresp>
<fn fn-type="other" id="fn001"><p>This article was submitted to Radiation and Health, a section of the journal Frontiers in Public Health</p></fn></author-notes>
<pub-date pub-type="epub">
<day>02</day>
<month>07</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>9</volume>
<elocation-id>678856</elocation-id>
<history>
<date date-type="received">
<day>10</day>
<month>03</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>18</day>
<month>05</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2021 Azimzadeh, von Toerne, Subramanian, Sievert, Multhoff, Atkinson and Tapio.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Azimzadeh, von Toerne, Subramanian, Sievert, Multhoff, Atkinson and Tapio</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><bold>Background and Purpose:</bold> Cardiotoxicity is a well-known adverse effect of radiation therapy. Measurable abnormalities in the heart function indicate advanced and often irreversible heart damage. Therefore, early detection of cardiac toxicity is necessary to delay and alleviate the development of the disease. The present study investigated long-term serum proteome alterations following local heart irradiation using a mouse model with the aim to detect biomarkers of radiation-induced cardiac toxicity.</p>
<p><bold>Materials and Methods:</bold> Serum samples from C57BL/6J mice were collected 20 weeks after local heart irradiation with 8 or 16 Gy X-ray; the controls were sham-irradiated. The samples were analyzed by quantitative proteomics based on data-independent acquisition mass spectrometry. The proteomics data were further investigated using bioinformatics and ELISA.</p>
<p><bold>Results:</bold> The analysis showed radiation-induced changes in the level of several serum proteins involved in the acute phase response, inflammation, and cholesterol metabolism. We found significantly enhanced expression of proinflammatory cytokines (TNF-&#x003B1;, TGF-&#x003B2;, IL-1, and IL-6) in the serum of the irradiated mice. The level of free fatty acids, total cholesterol, low-density lipoprotein (LDL), and oxidized LDL was increased, whereas that of high-density lipoprotein was decreased by irradiation.</p>
<p><bold>Conclusions:</bold> This study provides information on systemic effects of heart irradiation. It elucidates a radiation fingerprint in the serum that may be used to elucidate adverse cardiac effects after radiation therapy.</p></abstract>
<kwd-group>
<kwd>radiation therapy</kwd>
<kwd>proteomics</kwd>
<kwd>data-independent acquisition</kwd>
<kwd>inflammation</kwd>
<kwd>ionizing radiation</kwd>
<kwd>biomarker</kwd>
<kwd>radiation-induced heart disease</kwd>
<kwd>cardiac lipid metabolism</kwd>
</kwd-group>
<contract-sponsor id="cn001">Bundesministerium f&#x000FC;r Bildung und Forschung<named-content content-type="fundref-id">10.13039/501100002347</named-content></contract-sponsor>
<contract-sponsor id="cn002">Deutscher Akademischer Austauschdienst<named-content content-type="fundref-id">10.13039/501100001655</named-content></contract-sponsor>
<counts>
<fig-count count="5"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="76"/>
<page-count count="12"/>
<word-count count="7874"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>It is, nowadays, commonly acknowledged that the exposure of the heart to ionizing radiation, as in radiation therapy for breast cancer, Hodgkin&#x00027;s disease, or other cancers of the chest, increases the risk of heart disease (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). This has become a growing problem with the advancements in cancer therapy that have successfully reduced both mortality rates and the recurrence, expanding the life expectancy of the survivors (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B4">4</xref>).</p>
<p>Manifestations of radiation-induced heart disease include pericarditis, pericardial fibrosis, diffuse myocardial fibrosis, coronary artery disease, microvascular damage, and stenosis of the valves (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>). Considering causal biological processes in the development of the disease, persistent inflammation and oxidative stress, fibrosis, and pre-mature endothelial senescence are thought to be salient (<xref ref-type="bibr" rid="B7">7</xref>&#x02013;<xref ref-type="bibr" rid="B9">9</xref>). Recently, the role of mitochondrial dysfunction and related metabolic perturbations has become more and more evident (<xref ref-type="bibr" rid="B10">10</xref>&#x02013;<xref ref-type="bibr" rid="B12">12</xref>).</p>
<p>Detecting cardiac toxicity by assessing left ventricular function often requires a large amount of myocardial damage, characteristic of irreversible heart injury (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>). There is increasing emphasis on the use of biomarkers to detect cardiotoxicity at a stage before it becomes irreversible.</p>
<p>The most important blood biomarkers of heart injury are cardiac troponins T (cTnT) and I (cTnI), heart proteins controlling the calcium-mediated interaction between actin and myosin filaments (<xref ref-type="bibr" rid="B15">15</xref>). While cTnT is expressed to a small extent in skeletal muscle, cTnI has been found only in the myocardium. A previous study by Skytt&#x000E4; et al. showed that cTnT levels increased during adjuvant whole-breast radiation therapy in one out of five patients. Moreover, the increase in cTnT release was positively associated with cardiac radiation dose and with minor changes in the left ventricular diastolic function (<xref ref-type="bibr" rid="B16">16</xref>). A sustained irreversible leakage of cardiac troponins to the blood stream is due to the degradation of the myofibrils after heart damage (<xref ref-type="bibr" rid="B17">17</xref>).</p>
<p>Since irradiation tends to stimulate inflammatory processes, C-reactive protein (CPR), an acute phase protein, could be an additional potential predictive marker of cardiotoxicity after irradiation. Increased CRP level was associated with the severity of radiation-induced cardiomyopathy after radiation therapy of lung or breast cancer (<xref ref-type="bibr" rid="B18">18</xref>). We have shown elevated levels of inflammatory cytokines such as interleukin (IL)-1, IL-6, and tissue necrosis factor alpha (TNF-&#x003B1;) in serum after local cardiac irradiation in mice (<xref ref-type="bibr" rid="B19">19</xref>), but data on their role in the prediction of myocardial changes in clinical trials are lacking to date (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>).</p>
<p>Although cardiac troponins and CRP are established sensitive biomarkers of myocardial injury and inflammation, respectively, there is no specificity for radiation-associated heart disease. In fact, there are no biomarkers available to identify radiotherapy patients who are in the process of developing radiation-associated heart disease, although the current data suggest that certain blood biomarkers may be associated with myocardial dysfunction (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B23">23</xref>).</p>
<p>Proteomics represents a promising global technology to discover new types of biomarkers for radiation-induced cardiac injury (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B24">24</xref>). However, identification and quantification of serum/plasma proteins remains an analytical challenge, mainly due to the dominance of albumins and immunoglobulins and the high dynamic range of protein abundances (<xref ref-type="bibr" rid="B25">25</xref>). This is particularly true for disease-specific biomarkers that are mainly low-abundance proteins (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B27">27</xref>). The newly established quantitative proteomics technology based on the data-independent acquisition (DIA) mass spectrometry (MS) was introduced recently to overcome the limitation of previous approaches (<xref ref-type="bibr" rid="B26">26</xref>). The aim of this study was to identify biomarkers of cardiac toxicity in the serum proteome of mice after local heart irradiation by using DIA-MS.</p>
</sec>
<sec sec-type="materials and methods" id="s2">
<title>Materials and Methods</title>
<sec>
<title>Irradiation and Sample Preparation</title>
<p>Local heart irradiation was carried out on male C57BL/6J mice at the age of 8 weeks as previously described (<xref ref-type="bibr" rid="B28">28</xref>). Briefly, mice were irradiated with a single X-ray dose of 8 or 16 Gy locally to the heart (200 kV, 10 mA) (Gulmay, West Byfleet, UK). The age-matched control mice were sham irradiated. Mice were not anesthetized during irradiation but were held in a prone position in restraining jigs with the thorax fixed using adjustable hinges. The position and field size (9 &#x000D7; 13 mm<sup>2</sup>) of the heart was determined by pilot studies using soft X-rays; the rest of the body was shielded with a 2-mm-thick lead plate. With this beam size, 40% of the lung volume receives, by necessity, the full heart dose (<xref ref-type="bibr" rid="B29">29</xref>). Blood samples were collected from all mice by cardiac puncture after animals were sacrificed 20 weeks post-radiation. The serum was isolated and kept at &#x02212;80&#x000B0;C for further analyses. All animal experiments were approved and licensed under Bavarian federal law (Certificate No. AZ 55.2-1-54-2532-114-2014). Altogether, 15 mice were used in this study, with five mice in each group.</p>
</sec>
<sec>
<title>Proteome Profiling</title>
<p>Serum protein concentrations were determined by Bradford assay, and 50 &#x003BC;g per sample was prepared using PreOmics&#x00027; iST Kit (Preomics GmbH, Martinsried, Germany) according to manufacturers&#x00027; specifications. After drying, the peptides were resuspended in 2% acetonitrile (ACN) and 0.5% trifluoroacetic acid. The HRM Calibration Kit (Biognosys, Schlieren, Switzerland) was added to all of the samples according to the manufacturer&#x00027;s instructions.</p>
<p>The MS data were acquired in DIA mode on a Q Exactive HF mass spectrometer (Thermo Fisher Scientific Inc., Waltham, MA, USA). Samples were automatically loaded to the online coupled RSLC (Ultimate 3000, Thermo Fisher Scientific Inc.) HPLC system. A Nano-Trap column was used (300-&#x003BC;m inner diameter (ID) &#x000D7; 5 mm, packed with Acclaim PepMap100 C18, 5 &#x003BC;m, 100 &#x000C5; from LC Packings, Sunnyvale, CA, USA, before separation by reversed-phase chromatography (Acquity UPLC M-Class HSS T3 Column 75 &#x003BC;m ID &#x000D7; 250 mm, 1.8 &#x003BC;m from Waters, Eschborn, Germany) at 40&#x000B0;C. Peptides were eluted from the column at 250 nl/min using increasing ACN concentration in 0.1% formic acid from 3 to 40% over a 45-min gradient.</p>
<p>The DIA method consisted of a survey scan from 300 to 1,500 m/z at 120,000 resolution and an automatic gain control (AGC) target of 3e6 or 120-ms maximum injection time. Fragmentation was performed via higher-energy collisional dissociation with a target value of 3e6 ions determined with predictive AGC. Precursor peptides were isolated with 17 variable windows spanning from 300 to 1,500 m/z at 30,000 resolution with an AGC target of 3e6 and automatic injection time. The normalized collision energy was 28, and the spectra were recorded in profile type.</p>
<p>Selected LC-MS/MS data encompassing 164 raw files were analyzed using Proteome Discoverer (Version 2.1, Thermo Fisher Scientific Inc.) using Byonic (Version 2.0, Proteinmetrics, San Carlos, CA, USA) search engine node maintaining 1% peptide and protein FDR threshold. The peptide spectral library was generated in Spectronaut (Version 10, Biognosys, Schlieren, Switzerland) with default settings using the Proteome Discoverer result file. Spectronaut was equipped with the Swiss-Prot mouse database (Release 2017.02, 16,869 sequences, <ext-link ext-link-type="uri" xlink:href="http://www.uniprot.org">www.uniprot.org</ext-link>) with a few spiked proteins (e.g., Biognosys iRT peptide sequences). The final spectral library generated in Spectronaut contained 10,525 protein groups and 322,041 peptide precursors. The DIA-MS data were analyzed using the Spectronaut 10 software applying default settings with the exception: quantification was limited to proteotypic peptides, data filtering was set to <italic>Q</italic>-value 25% percentile, summing-up peptide abundances. For this study, the proteins with a <italic>q</italic>-value &#x0003C;0.05 were considered as significantly differentially expressed.</p>
<p>Additional differential abundance testing was performed in Spectronaut as unpaired ratio based <italic>t</italic>-test on peptide level to identify the candidates&#x00027; differential between the experimental groups (i) sham irradiation, (ii) 8-Gy irradiation, or (iii) 16-Gy irradiation.</p>
</sec>
<sec>
<title>Interaction and Signaling Network Analysis</title>
<p>The analyses of protein&#x02013;protein interaction and signaling networks were performed by the software tools INGENUITY Pathway Analysis (IPA) (Qiagen, Inc., Hilden, Germany, <ext-link ext-link-type="uri" xlink:href="https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis">https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis</ext-link>) (<xref ref-type="bibr" rid="B30">30</xref>).</p>
</sec>
<sec>
<title>Serum Inflammatory Molecule Analysis</title>
<p>The expression levels of different mediators including TNF-&#x003B1;, TGF-&#x003B2;, monocyte chemoattractant protein 1 (MCP1), IL-1 &#x003B1;, IL-1 &#x003B2;, IL-6, IL-10, IL-12, interferon (IFN) gamma, granulocyte-colony stimulating factor (G-CSF), and granulocyte&#x02013;macrophage colony-stimulating factor (GM-CSF) were measured using ELISA strip colorimetric kits &#x00023;EA-1401, &#x00023; EA-1051, and &#x00023; EA-1131 (Signosis, Inc., Santa Clara, CA, USA) according to the manufacturer&#x00027;s instructions.</p>
</sec>
<sec>
<title>Serum Lipid Profiling</title>
<p>The levels of circulating free fatty acids (ab65341), triglyceride (ab65336), total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) (ab65390), all from Abcam, Cambridge, MA, USA, and oxidized low-density lipoprotein (oxLDL) (MBS2512757, MyBioSource, San Diego, CA, USA) were measured according to the manufacturer&#x00027;s instructions.</p>
</sec>
<sec>
<title>Statistical Analysis</title>
<p>The 3D principal component analysis (PCA) was performed by R (4.0.5) (<ext-link ext-link-type="uri" xlink:href="https://www.R-project.org/">https://www.R-project.org/</ext-link>) and the hierarchical clustering using the Heatmapper web server (<ext-link ext-link-type="uri" xlink:href="http://www.heatmapper.ca/">http://www.heatmapper.ca/</ext-link>) (<xref ref-type="bibr" rid="B31">31</xref>). Student&#x00027;s <italic>t</italic>-test (unpaired) was used for proteomics and ELISA comparisons. The error bars were calculated as the standard error of the mean (SEM).</p>
</sec>
<sec>
<title>Data Availability</title>
<p>The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (<xref ref-type="bibr" rid="B32">32</xref>) partner repository with the dataset identifier PXD024446.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec>
<title>Serum Proteome Alterations Following Local Heart Irradiation</title>
<p>The serum proteome of mice was analyzed 20 weeks in sham-irradiated and irradiated (8 and 16 Gy) mice using DIA-MS. The analysis identified and quantified 499 proteins (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>). Among the quantified proteins, the expression of 42 and 59 proteins was significantly changed (<italic>q</italic>-value &#x0003C;0.05, identification by at least two unique peptides) at 8 and 16 Gy, respectively, suggesting a dose-dependent increase in the number of significantly deregulated proteins (<xref ref-type="table" rid="T1">Table 1</xref>). The majority of these proteins (76% at 8 Gy and 83% at 16 Gy) have been previously annotated as serum proteins based on the Plasma Proteome Database (PPD) (<ext-link ext-link-type="uri" xlink:href="http://plasmaproteomedatabase.org/index.html">http://plasmaproteomedatabase.org/index.html</ext-link>).</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Significantly deregulated serum proteins in heart-irradiated mice.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>&#x00023;</bold></th>
<th valign="top" align="left"><bold>Protein accession</bold></th>
<th valign="top" align="left"><bold>Protein ID</bold></th>
<th valign="top" align="left"><bold>Protein description</bold></th>
<th valign="top" align="center"><bold>Total unique peptides</bold></th>
<th valign="top" align="center"><bold>Ratio 8/0 Gy</bold></th>
<th valign="top" align="center"><bold>Ratio 16/0 Gy</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">1</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P48410">P48410</ext-link></td>
<td valign="top" align="left">ABCD1</td>
<td valign="top" align="left">ATP-binding cassette subfamily D member 1</td>
<td valign="top" align="center">20</td>
<td/>
<td valign="top" align="center">0.712</td>
</tr>
<tr>
<td valign="top" align="left"><bold>2</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P29699"><bold>P29699</bold></ext-link></td>
<td valign="top" align="left"><bold>AHSG</bold></td>
<td valign="top" align="left"><bold>Alpha-2-HS-glycoprotein</bold></td>
<td valign="top" align="center"><bold>12</bold></td>
<td valign="top" align="center"><bold>0.989</bold></td>
<td valign="top" align="center"><bold>1.043</bold></td>
</tr>
<tr>
<td valign="top" align="left">3</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P05064">P05064</ext-link></td>
<td valign="top" align="left">ALDOA</td>
<td valign="top" align="left">Fructose-bisphosphate aldolase A</td>
<td valign="top" align="center">48</td>
<td valign="top" align="center">0.435</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">4</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q91Y97">Q91Y97</ext-link></td>
<td valign="top" align="left">ALDOB</td>
<td valign="top" align="left">Fructose-bisphosphate aldolase B</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">0.476</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">5</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P12246">P12246</ext-link></td>
<td valign="top" align="left">APCS</td>
<td valign="top" align="left">Serum amyloid P-component</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">2.375</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">6</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P09813">P09813</ext-link></td>
<td valign="top" align="left">APOA2</td>
<td valign="top" align="left">Apolipoprotein A-II</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">0.812</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>7</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P06728"><bold>P06728</bold></ext-link></td>
<td valign="top" align="left"><bold>APOA4</bold></td>
<td valign="top" align="left"><bold>Apolipoprotein A-IV</bold></td>
<td valign="top" align="center"><bold>28</bold></td>
<td valign="top" align="center"><bold>0.891</bold></td>
<td valign="top" align="center"><bold>0.993</bold></td>
</tr>
<tr>
<td valign="top" align="left"><bold>8</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="E9Q414"><bold>E9Q414</bold></ext-link></td>
<td valign="top" align="left"><bold>APOB</bold></td>
<td valign="top" align="left"><bold>Apolipoprotein B-100</bold></td>
<td valign="top" align="center"><bold>16</bold></td>
<td valign="top" align="center"><bold>1.301</bold></td>
<td valign="top" align="center"><bold>1.271</bold></td>
</tr>
<tr>
<td valign="top" align="left">9</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P34928">P34928</ext-link></td>
<td valign="top" align="left">APOC1</td>
<td valign="top" align="left">Apolipoprotein C-I</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">0.801</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">10</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P08226">P08226</ext-link></td>
<td valign="top" align="left">APOE</td>
<td valign="top" align="left">Apolipoprotein E</td>
<td valign="top" align="center">24</td>
<td/>
<td valign="top" align="center">1.340</td>
</tr>
<tr>
<td valign="top" align="left">11</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q02105">Q02105</ext-link></td>
<td valign="top" align="left">C1QC</td>
<td valign="top" align="left">Complement C1q subcomponent subunit C</td>
<td valign="top" align="center">5</td>
<td/>
<td valign="top" align="center">0.857</td>
</tr>
<tr>
<td valign="top" align="left">12</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q80X80">Q80X80</ext-link></td>
<td valign="top" align="left">C2CD2L</td>
<td valign="top" align="left">C2 domain-containing protein 2-like</td>
<td valign="top" align="center">31</td>
<td/>
<td valign="top" align="center">0.039</td>
</tr>
<tr>
<td valign="top" align="left"><bold>13</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P01027"><bold>P01027</bold></ext-link></td>
<td valign="top" align="left"><bold>C3</bold></td>
<td valign="top" align="left"><bold>Complement C3</bold></td>
<td valign="top" align="center"><bold>99</bold></td>
<td valign="top" align="center"><bold>1.153</bold></td>
<td valign="top" align="center"><bold>0.895</bold></td>
</tr>
<tr>
<td valign="top" align="left"><bold>14</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P01029"><bold>P01029</bold></ext-link></td>
<td valign="top" align="left"><bold>C4B</bold></td>
<td valign="top" align="left"><bold>Complement C4-B</bold></td>
<td valign="top" align="center"><bold>45</bold></td>
<td valign="top" align="center"><bold>1.452</bold></td>
<td valign="top" align="center"><bold>1.151</bold></td>
</tr>
<tr>
<td valign="top" align="left">15</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P06684">P06684</ext-link></td>
<td valign="top" align="left">C5</td>
<td valign="top" align="left">Complement C5</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">1.134</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">16</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P55284">P55284</ext-link></td>
<td valign="top" align="left">CDH5</td>
<td valign="top" align="left">Cadherin-5</td>
<td valign="top" align="center">27</td>
<td/>
<td valign="top" align="center">1.468</td>
</tr>
<tr>
<td valign="top" align="left">17</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P04186">P04186</ext-link></td>
<td valign="top" align="left">CFB</td>
<td valign="top" align="left">Complement factor B</td>
<td valign="top" align="center">19</td>
<td/>
<td valign="top" align="center">0.923</td>
</tr>
<tr>
<td valign="top" align="left">18</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P06909">P06909</ext-link></td>
<td valign="top" align="left">CFH</td>
<td valign="top" align="left">Complement factor H</td>
<td valign="top" align="center">45</td>
<td valign="top" align="center">1.234</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">19</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61129">Q61129</ext-link></td>
<td valign="top" align="left">CFI</td>
<td valign="top" align="left">Complement factor I</td>
<td valign="top" align="center">8</td>
<td/>
<td valign="top" align="center">0.870</td>
</tr>
<tr>
<td valign="top" align="left">20</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P12960">P12960</ext-link></td>
<td valign="top" align="left">CNTN1</td>
<td valign="top" align="left">Contactin-1</td>
<td valign="top" align="center">59</td>
<td/>
<td valign="top" align="center">1.214</td>
</tr>
<tr>
<td valign="top" align="left">21</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61147">Q61147</ext-link></td>
<td valign="top" align="left">CP</td>
<td valign="top" align="left">Ceruloplasmin</td>
<td valign="top" align="center">54</td>
<td valign="top" align="center">1.116</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">22</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P09581">P09581</ext-link></td>
<td valign="top" align="left">CSF1R</td>
<td valign="top" align="left">Macrophage colony-stimulating factor 1 receptor</td>
<td valign="top" align="center">5</td>
<td/>
<td valign="top" align="center">1.178</td>
</tr>
<tr>
<td valign="top" align="left">23</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P63037">P63037</ext-link></td>
<td valign="top" align="left">DNAJA1</td>
<td valign="top" align="left">DnaJ homolog subfamily A member 1</td>
<td valign="top" align="center">26</td>
<td/>
<td valign="top" align="center">0.258</td>
</tr>
<tr>
<td valign="top" align="left"><bold>24</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61508"><bold>Q61508</bold></ext-link></td>
<td valign="top" align="left"><bold>ECM1</bold></td>
<td valign="top" align="left"><bold>Extracellular matrix protein 1</bold></td>
<td valign="top" align="center"><bold>18</bold></td>
<td valign="top" align="center"><bold>0.767</bold></td>
<td valign="top" align="center"><bold>0.846</bold></td>
</tr>
<tr>
<td valign="top" align="left">25</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q01279">Q01279</ext-link></td>
<td valign="top" align="left">EGFR</td>
<td valign="top" align="left">Epidermal growth factor receptor</td>
<td valign="top" align="center">46</td>
<td/>
<td valign="top" align="center">1.137</td>
</tr>
<tr>
<td valign="top" align="left">26</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P19221">P19221</ext-link></td>
<td valign="top" align="left">F2</td>
<td valign="top" align="left">Prothrombin</td>
<td valign="top" align="center">26</td>
<td/>
<td valign="top" align="center">0.972</td>
</tr>
<tr>
<td valign="top" align="left">27</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q9QXC1">Q9QXC1</ext-link></td>
<td valign="top" align="left">FETUB</td>
<td valign="top" align="left">Fetuin-B</td>
<td valign="top" align="center">8</td>
<td/>
<td valign="top" align="center">1.214</td>
</tr>
<tr>
<td valign="top" align="left">28</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="E9PV24">E9PV24</ext-link></td>
<td valign="top" align="left">FGA</td>
<td valign="top" align="left">Fibrinogen alpha chain</td>
<td valign="top" align="center">30</td>
<td valign="top" align="center">1.435</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">29</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P11276">P11276</ext-link></td>
<td valign="top" align="left">FN1</td>
<td valign="top" align="left">Fibronectin</td>
<td valign="top" align="center">145</td>
<td/>
<td valign="top" align="center">1.008</td>
</tr>
<tr>
<td valign="top" align="left">30</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P21614">P21614</ext-link></td>
<td valign="top" align="left">GC</td>
<td valign="top" align="left">Vitamin D-binding protein</td>
<td valign="top" align="center">23</td>
<td/>
<td valign="top" align="center">1.253</td>
</tr>
<tr>
<td valign="top" align="left"><bold>31</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P13020"><bold>P13020</bold></ext-link></td>
<td valign="top" align="left"><bold>GSN</bold></td>
<td valign="top" align="left"><bold>Gelsolin</bold></td>
<td valign="top" align="center"><bold>44</bold></td>
<td valign="top" align="center"><bold>0.902</bold></td>
<td valign="top" align="center"><bold>0.987</bold></td>
</tr>
<tr>
<td valign="top" align="left">32</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P01898">P01898</ext-link></td>
<td valign="top" align="left">H2-Q10</td>
<td valign="top" align="left">H-2 class I, Q10 alpha chain</td>
<td valign="top" align="center">11</td>
<td/>
<td valign="top" align="center">1.212</td>
</tr>
<tr>
<td valign="top" align="left">33</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P01942">P01942</ext-link></td>
<td valign="top" align="left">HBA</td>
<td valign="top" align="left">Hemoglobin subunit alpha</td>
<td valign="top" align="center">18</td>
<td valign="top" align="center">1.467</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>34</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P02088"><bold>P02088</bold></ext-link></td>
<td valign="top" align="left"><bold>HBB-B1</bold></td>
<td valign="top" align="left"><bold>Hemoglobin subunit beta-1</bold></td>
<td valign="top" align="center"><bold>19</bold></td>
<td valign="top" align="center"><bold>1.460</bold></td>
<td valign="top" align="center"><bold>1.309</bold></td>
</tr>
<tr>
<td valign="top" align="left">35</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61646">Q61646</ext-link></td>
<td valign="top" align="left">HP</td>
<td valign="top" align="left">Haptoglobin</td>
<td valign="top" align="center">14</td>
<td valign="top" align="center">3.311</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">36</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q91X72">Q91X72</ext-link></td>
<td valign="top" align="left">HPX</td>
<td valign="top" align="left">Hemopexin</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">1.328</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">37</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P06330">P06330</ext-link></td>
<td valign="top" align="left">IG HEAVY C</td>
<td valign="top" align="left">Ig heavy chain V region AC38 205.12</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">1.116</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>38</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P01864"><bold>P01864</bold></ext-link></td>
<td valign="top" align="left"><bold>IGG</bold></td>
<td valign="top" align="left"><bold>Ig gamma-2A chain C region secreted form</bold></td>
<td valign="top" align="center"><bold>4</bold></td>
<td valign="top" align="center"><bold>1.310</bold></td>
<td valign="top" align="center"><bold>1.849</bold></td>
</tr>
<tr>
<td valign="top" align="left"><bold>39</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P01867"><bold>P01867</bold></ext-link></td>
<td valign="top" align="left"><bold>IGH-3</bold></td>
<td valign="top" align="left"><bold>Ig gamma-2B chain C region</bold></td>
<td valign="top" align="center"><bold>9</bold></td>
<td valign="top" align="center"><bold>1.821</bold></td>
<td valign="top" align="center"><bold>2.659</bold></td>
</tr>
<tr>
<td valign="top" align="left"><bold>40</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P01872"><bold>P01872</bold></ext-link></td>
<td valign="top" align="left"><bold>IGHM</bold></td>
<td valign="top" align="left"><bold>Ig mu chain C region</bold></td>
<td valign="top" align="center"><bold>16</bold></td>
<td valign="top" align="center"><bold>1.585</bold></td>
<td valign="top" align="center"><bold>1.696</bold></td>
</tr>
<tr>
<td valign="top" align="left"><bold>41</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P01837"><bold>P01837</bold></ext-link></td>
<td valign="top" align="left"><bold>IGK</bold></td>
<td valign="top" align="left"><bold>Ig kappa chain C region</bold></td>
<td valign="top" align="center"><bold>5</bold></td>
<td valign="top" align="center"><bold>1.242</bold></td>
<td valign="top" align="center"><bold>1.514</bold></td>
</tr>
<tr>
<td valign="top" align="left">42</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61702">Q61702</ext-link></td>
<td valign="top" align="left">ITIH1</td>
<td valign="top" align="left">Inter-alpha-trypsin inhibitor heavy chain H1</td>
<td valign="top" align="center">17</td>
<td valign="top" align="center">1.174</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">43</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61703">Q61703</ext-link></td>
<td valign="top" align="left">ITIH2</td>
<td valign="top" align="left">Inter-alpha-trypsin inhibitor heavy chain H2</td>
<td valign="top" align="center">33</td>
<td/>
<td valign="top" align="center">0.907</td>
</tr>
<tr>
<td valign="top" align="left"><bold>44</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61704"><bold>Q61704</bold></ext-link></td>
<td valign="top" align="left"><bold>ITIH3</bold></td>
<td valign="top" align="left"><bold>Inter-alpha-trypsin inhibitor heavy chain H3</bold></td>
<td valign="top" align="center"><bold>14</bold></td>
<td valign="top" align="center"><bold>1.518</bold></td>
<td valign="top" align="center"><bold>0.937</bold></td>
</tr>
<tr>
<td valign="top" align="left"><bold>45</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="A6X935"><bold>A6X935</bold></ext-link></td>
<td valign="top" align="left"><bold>ITIH4</bold></td>
<td valign="top" align="left"><bold>Inter alpha-trypsin inhibitor, heavy chain 4</bold></td>
<td valign="top" align="center"><bold>23</bold></td>
<td valign="top" align="center"><bold>1.632</bold></td>
<td valign="top" align="center"><bold>0.993</bold></td>
</tr>
<tr>
<td valign="top" align="left">46</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P04104">P04104</ext-link></td>
<td valign="top" align="left">KRT1</td>
<td valign="top" align="left">Keratin, type II cytoskeletal 1</td>
<td valign="top" align="center">10</td>
<td/>
<td valign="top" align="center">0.533</td>
</tr>
<tr>
<td valign="top" align="left">47</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P08730">P08730</ext-link></td>
<td valign="top" align="left">KRT13</td>
<td valign="top" align="left">Keratin, type I cytoskeletal 13</td>
<td valign="top" align="center">30</td>
<td/>
<td valign="top" align="center">0.933</td>
</tr>
<tr>
<td valign="top" align="left">48</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q6NXH9">Q6NXH9</ext-link></td>
<td valign="top" align="left">KRT73</td>
<td valign="top" align="left">Keratin, type II cytoskeletal 73</td>
<td valign="top" align="center">10</td>
<td/>
<td valign="top" align="center">0.588</td>
</tr>
<tr>
<td valign="top" align="left">49</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61233">Q61233</ext-link></td>
<td valign="top" align="left">LCP1</td>
<td valign="top" align="left">Plastin-2</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">0.672</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>50</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P42703"><bold>P42703</bold></ext-link></td>
<td valign="top" align="left"><bold>LIFR</bold></td>
<td valign="top" align="left"><bold>Leukemia inhibitory factor receptor</bold></td>
<td valign="top" align="center"><bold>25</bold></td>
<td valign="top" align="center"><bold>0.736</bold></td>
<td valign="top" align="center"><bold>0.712</bold></td>
</tr> <tr>
<td valign="top" align="left">51</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q80XG9">Q80XG9</ext-link></td>
<td valign="top" align="left">LRRTM4</td>
<td valign="top" align="left">Leucine-rich repeat transmembrane neuronal protein 4</td>
<td valign="top" align="center">9</td>
<td/>
<td valign="top" align="center">0.751</td>
</tr>
<tr>
<td valign="top" align="left">52</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P51885">P51885</ext-link></td>
<td valign="top" align="left">LUM</td>
<td valign="top" align="left">Lumican</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">0.922</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">53</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="O09159">O09159</ext-link></td>
<td valign="top" align="left">MAN2B1</td>
<td valign="top" align="left">Lysosomal alpha-mannosidase</td>
<td valign="top" align="center">40</td>
<td valign="top" align="center">0.800</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">54</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P04247">P04247</ext-link></td>
<td valign="top" align="left">MB</td>
<td valign="top" align="left">Myoglobin</td>
<td valign="top" align="center">13</td>
<td/>
<td valign="top" align="center">1.354</td>
</tr>
<tr>
<td valign="top" align="left">55</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q99KE1">Q99KE1</ext-link></td>
<td valign="top" align="left">ME2</td>
<td valign="top" align="left">NAD-dependent malic enzyme, mitochondrial</td>
<td valign="top" align="center">37</td>
<td/>
<td valign="top" align="center">0.751</td>
</tr>
<tr>
<td valign="top" align="left">56</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P28665">P28665</ext-link></td>
<td valign="top" align="left">MUG1</td>
<td valign="top" align="left">Murinoglobulin-1</td>
<td valign="top" align="center">63</td>
<td valign="top" align="center">0.877</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">57</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P11589">P11589</ext-link></td>
<td valign="top" align="left">MUP2</td>
<td valign="top" align="left">Major urinary protein 2</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">0.896</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">58</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P97863">P97863</ext-link></td>
<td valign="top" align="left">NFIB</td>
<td valign="top" align="left">Nuclear factor 1 B-type</td>
<td valign="top" align="center">21</td>
<td/>
<td valign="top" align="center">0.358</td>
</tr>
<tr>
<td valign="top" align="left">59</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="O89084">O89084</ext-link></td>
<td valign="top" align="left">PDE4A</td>
<td valign="top" align="left">cAMP- 3&#x02032;,5&#x02032;-cyclic phosphodiesterase 4A</td>
<td valign="top" align="center">21</td>
<td/>
<td valign="top" align="center">0.718</td>
</tr>
<tr>
<td valign="top" align="left">60</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P52480">P52480</ext-link></td>
<td valign="top" align="left">PKM</td>
<td valign="top" align="left">Pyruvate kinase PKM</td>
<td valign="top" align="center">60</td>
<td valign="top" align="center">0.605</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">61</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q60963">Q60963</ext-link></td>
<td valign="top" align="left">PLA2G7</td>
<td valign="top" align="left">Platelet-activating factor acetylhydrolase</td>
<td valign="top" align="center">18</td>
<td/>
<td valign="top" align="center">1.110</td>
</tr>
<tr>
<td valign="top" align="left">62</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P20918">P20918</ext-link></td>
<td valign="top" align="left">PLG</td>
<td valign="top" align="left">Plasminogen</td>
<td valign="top" align="center">39</td>
<td/>
<td valign="top" align="center">1.073</td>
</tr>
<tr>
<td valign="top" align="left"><bold>63</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P55065"><bold>P55065</bold></ext-link></td>
<td valign="top" align="left"><bold>PLTP</bold></td>
<td valign="top" align="left"><bold>Phospholipid transfer protein</bold></td>
<td valign="top" align="center"><bold>12</bold></td>
<td valign="top" align="center"><bold>1.102</bold></td>
<td valign="top" align="center"><bold>1.420</bold></td>
</tr>
<tr>
<td valign="top" align="left">64</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P52430">P52430</ext-link></td>
<td valign="top" align="left">PON1</td>
<td valign="top" align="left">Serum paraoxonase/arylesterase 1</td>
<td valign="top" align="center">14</td>
<td/>
<td valign="top" align="center">1.137</td>
</tr>
<tr>
<td valign="top" align="left">65</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q62009">Q62009</ext-link></td>
<td valign="top" align="left">POSTN</td>
<td valign="top" align="left">Periostin</td>
<td valign="top" align="center">39</td>
<td/>
<td valign="top" align="center">1.183</td>
</tr>
<tr>
<td valign="top" align="left"><bold>66</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61171"><bold>Q61171</bold></ext-link></td>
<td valign="top" align="left"><bold>PRDX2</bold></td>
<td valign="top" align="left"><bold>Peroxiredoxin-2</bold></td>
<td valign="top" align="center"><bold>17</bold></td>
<td valign="top" align="center"><bold>1.303</bold></td>
<td valign="top" align="center"><bold>1.280</bold></td>
</tr>
<tr>
<td valign="top" align="left">67</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61838">Q61838</ext-link></td>
<td valign="top" align="left">PZP</td>
<td valign="top" align="left">Pregnancy zone protein</td>
<td valign="top" align="center">70</td>
<td/>
<td valign="top" align="center">1.052</td>
</tr>
<tr>
<td valign="top" align="left">68</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P07758">P07758</ext-link></td>
<td valign="top" align="left">SERPINA1A</td>
<td valign="top" align="left">Alpha-1-antitrypsin 1-1</td>
<td valign="top" align="center">18</td>
<td/>
<td valign="top" align="center">0.963</td>
</tr>
<tr>
<td valign="top" align="left">69</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P22599">P22599</ext-link></td>
<td valign="top" align="left">SERPINA1B</td>
<td valign="top" align="left">Alpha-1-antitrypsin 1-2</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">0.824</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>70</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q00897"><bold>Q00897</bold></ext-link></td>
<td valign="top" align="left"><bold>SERPINA1D</bold></td>
<td valign="top" align="left"><bold>Alpha-1-antitrypsin 1-4</bold></td>
<td valign="top" align="center"><bold>8</bold></td>
<td valign="top" align="center"><bold>0.835</bold></td>
<td valign="top" align="center"><bold>0.832</bold></td>
</tr>
<tr>
<td valign="top" align="left">71</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P07759">P07759</ext-link></td>
<td valign="top" align="left">SERPINA3K</td>
<td valign="top" align="left">Serine protease inhibitor A3K</td>
<td valign="top" align="center">14</td>
<td/>
<td valign="top" align="center">1.076</td>
</tr>
<tr>
<td valign="top" align="left">72</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q91WP6">Q91WP6</ext-link></td>
<td valign="top" align="left">SERPINA3N</td>
<td valign="top" align="left">Serine protease inhibitor A3N</td>
<td valign="top" align="center">17</td>
<td/>
<td valign="top" align="center">1.503</td>
</tr>
<tr>
<td valign="top" align="left">73</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P32261">P32261</ext-link></td>
<td valign="top" align="left">SERPINC1</td>
<td valign="top" align="left">Antithrombin-III</td>
<td valign="top" align="center">26</td>
<td/>
<td valign="top" align="center">0.926</td>
</tr>
<tr>
<td valign="top" align="left">74</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P49182">P49182</ext-link></td>
<td valign="top" align="left">SERPIND1</td>
<td valign="top" align="left">Heparin cofactor 2</td>
<td valign="top" align="center">9</td>
<td/>
<td valign="top" align="center">0.994</td>
</tr>
<tr>
<td valign="top" align="left">75</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P97298">P97298</ext-link></td>
<td valign="top" align="left">SERPINF1</td>
<td valign="top" align="left">Pigment epithelium-derived factor</td>
<td valign="top" align="center">18</td>
<td valign="top" align="center">0.946</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">76</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q61247">Q61247</ext-link></td>
<td valign="top" align="left">SERPINF2</td>
<td valign="top" align="left">Alpha-2-antiplasmin</td>
<td valign="top" align="center">6</td>
<td/>
<td valign="top" align="center">0.841</td>
</tr>
<tr>
<td valign="top" align="left">77</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P97290">P97290</ext-link></td>
<td valign="top" align="left">SERPING1</td>
<td valign="top" align="left">Plasma protease C1 inhibitor</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">1.149</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">78</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P70441">P70441</ext-link></td>
<td valign="top" align="left">SLC9A3R1</td>
<td valign="top" align="left">Na(&#x0002B;)/H(&#x0002B;) exchange regulatory cofactor</td>
<td valign="top" align="center">29</td>
<td/>
<td valign="top" align="center">1.156</td>
</tr>
<tr>
<td valign="top" align="left">79</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P35441">P35441</ext-link></td>
<td valign="top" align="left">THBS1</td>
<td valign="top" align="left">Thrombospondin-1</td>
<td valign="top" align="center">63</td>
<td/>
<td valign="top" align="center">1.233</td>
</tr>
<tr>
<td valign="top" align="left">80</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="Q9Z1T2">Q9Z1T2</ext-link></td>
<td valign="top" align="left">THBS4</td>
<td valign="top" align="left">Thrombospondin-4</td>
<td valign="top" align="center">23</td>
<td/>
<td valign="top" align="center">1.220</td>
</tr>
<tr>
<td valign="top" align="left">81</td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P07309">P07309</ext-link></td>
<td valign="top" align="left">TTR</td>
<td valign="top" align="left">Transthyretin</td>
<td valign="top" align="center">10</td>
<td/>
<td valign="top" align="center">1.242</td>
</tr>
<tr>
<td valign="top" align="left"><bold>82</bold></td>
<td valign="top" align="left"><ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="P29788"><bold>P29788</bold></ext-link></td>
<td valign="top" align="left"><bold>VTN</bold></td>
<td valign="top" align="left"><bold>Vitronectin</bold></td>
<td valign="top" align="center"><bold>10</bold></td>
<td valign="top" align="center"><bold>1.168</bold></td>
<td valign="top" align="center"><bold>1.042</bold></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>The UniProt protein identifiers (ID), protein IPA code, full name, and fold changes (FC) of significantly differentially expressed proteins (q-value &#x0003C; 0.05) following local heart irradiation at 8 or 16 Gy are shown. Cells without any value mean that the protein did not pass the selection criteria in the proteomics analysis (q-value &#x0003C; 0.05, protein identification with at least two unique peptides). The shared proteins are in bold</italic>.</p>
</table-wrap-foot>
</table-wrap>
<p>To assess the global variation in the samples, a multivariate analysis was performed using three-dimensional principal component analysis (3D-PCA). The 3D-PCA, based on the normalized intensities of all serum proteins, showed a clustering among the different groups (PC1: 15.9%, PC2: 15.1%, and PC3: 12.3%) (<xref ref-type="fig" rid="F1">Figures 1A,B</xref>). The 8- and 16-Gy treated samples were separated mainly on the PC2 axis, whereas the discrimination between the controls and 8-Gy treated samples was visible on the PC3 axis.</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p>Multivariate, pathway, and cardiotoxicity analyses of the significantly differentially expressed serum proteins after local heart irradiation using 0 (control), 8, or 16 Gy. The principal component analysis (PCA) performed on normalized intensities of all proteins resulted in PC1, PC2, and PC3 as follows: PC1 15.9%, PC2 15.1%, and PC3 12.3%. The control samples are represented as yellow balls, the samples exposed to 8 Gy in green cubes, and the 16 Gy treated samples in blue pyramids <bold>(A,B)</bold>. A dose-dependent alteration is observed in the pathways involved in the inflammation and lipid metabolism <bold>(C)</bold>. Several proteins were identified associated with different heart pathologies <bold>(D)</bold>. The pathway and cardiotoxicity scores are displayed using a purple color gradient; the darker the color, the higher the scores and, thereby, statistical significance. The score is the negative log of the <italic>p</italic>-value derived from the Fisher&#x00027;s Exact test. By default, the rows (pathways) with the highest total scores across the set of observations are sorted to the top. The analysis was performed using Ingenuity Pathway Analysis (IPA) (Qiagen Inc., <ext-link ext-link-type="uri" xlink:href="https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis">https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis</ext-link>). The heat maps show hierarchical clustering (complete linkage, Spearman ranked correlation) of significantly deregulated proteins belonging to the high-density lipoprotein (HDL)/low-density lipoprotein (LDL) metabolism <bold>(E)</bold> and acute phase response <bold>(F)</bold> pathways in the control and irradiated samples. The green bars indicate downregulation and the red bars upregulation. The analysis was performed by the Heatmapper web server (<ext-link ext-link-type="uri" xlink:href="http://www.heatmapper.ca/">http://www.heatmapper.ca/</ext-link>) (<xref ref-type="bibr" rid="B31">31</xref>). Detailed information of the proteomics features and individual samples is given in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>.</p></caption>
<graphic xlink:href="fpubh-09-678856-g0001.tif"/>
</fig>
<p>In particular, apolipoproteins, serpins, immunoglobulins, and inter-alpha-trypsin inhibitors were differentially regulated in the irradiated mice at both doses (<xref ref-type="table" rid="T1">Table 1</xref>). These shared proteins are mainly involved in the inflammatory response, and cholesterol and lipid metabolism. A detailed analysis of functional interactions and biological pathways based on differentially regulated proteins showed that acute phase response signaling, LXR/RXR cascade, cholesterol metabolism, coagulation system, and atherosclerosis signaling were the most affected pathways (<xref ref-type="fig" rid="F1">Figure 1C</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 2</xref>). The differentially regulated proteins are associated with several heart pathologies such as infarction, hypertrophy, and fibrosis (<xref ref-type="fig" rid="F1">Figure 1D</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 3</xref>). The analysis indicated a dose-dependent increase in the significance of the influenced pathways and in the cardiac pathologies.</p>
<p>Based on the list of canonical pathways (<xref ref-type="fig" rid="F1">Figure 1C</xref>) the deregulated proteins belonging to two of the significantly affected pathways, namely, HDL/LDL metabolism and acute phase response signaling, were subjected to hierarchical clustering analysis (<xref ref-type="fig" rid="F1">Figures 1E,F</xref>) (<xref ref-type="bibr" rid="B31">31</xref>). The heat map showed a clustering associated with the irradiation status of the groups.</p>
<p>The significantly deregulated proteins built a functional network associated with cholesterol metabolism and transport (<xref ref-type="fig" rid="F2">Figure 2</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 4</xref>). All deregulated proteins formed a tight cluster interacting with regulatory proteins of the inflammatory and acute phase response pathways.</p>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p>Graphical representation of cholesterol-associated networks based on radiation-induced alterations in the serum proteome. The protein clusters are shown at 8 Gy <bold>(A)</bold> and 16 Gy <bold>(B)</bold>. The upregulated proteins are marked in red and the downregulated in green. The nodes represent proteins connected with arrows; the solid arrows represent direct interactions and the dotted arrows indirect interactions. The cholesterol nodes are marked inside red circles and boxes. The IPA codes and corresponding full protein names are shown in <xref ref-type="table" rid="T1">Table 1</xref> and in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>. The analysis was performed using the Ingenuity Pathway Analysis (IPA) (<ext-link ext-link-type="uri" xlink:href="https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis">https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis</ext-link>).</p></caption>
<graphic xlink:href="fpubh-09-678856-g0002.tif"/>
</fig>
<p>The prediction analysis of the upstream regulators of the significantly deregulated proteins identified transcription factors involved in proinflammatory response (IL-6, TGF-&#x003B2;, and STAT3) and lipid metabolism (PPAR&#x003B1;, PGC-1). The proinflammatory regulators were predicted to be activated, while PPAR&#x003B1; was predicted to be inactivated (<xref ref-type="fig" rid="F3">Figure 3</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 5</xref>).</p>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption><p>Predicted upstream regulators of the deregulated serum proteins. Predicted upstream regulators are displayed using a purple color gradient where the intensity of the purple color corresponds to statistical significance (the deeper the color, the higher the significance). The score is the negative log of the <italic>p</italic>-value derived from Fisher&#x00027;s exact test. By default, the rows (upstream regulators) with the highest total scores across the set of observations are sorted to the top <bold>(A)</bold>. The predicted upstream regulators and their activity status at 16 Gy are shown: TGF-&#x003B2; <bold>(B)</bold>, IL-6 <bold>(C)</bold>, PPAR&#x003B1; <bold>(D)</bold>, and STAT3 <bold>(E)</bold>. The orange and the blue color of the nodes indicate activation and deactivation, respectively; the solid arrows represent direct interactions and the dotted arrows indirect interactions. The deregulated proteins forming the wheel around the nodes are marked in red (upregulation) and green (downregulation). The IPA codes and corresponding full protein names are shown in <xref ref-type="table" rid="T1">Table 1</xref> and in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>. The analysis was performed using Ingenuity Pathway Analysis (IPA) (<ext-link ext-link-type="uri" xlink:href="https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis">https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis</ext-link>).</p></caption>
<graphic xlink:href="fpubh-09-678856-g0003.tif"/>
</fig>
</sec>
<sec>
<title>Radiation-Induced Serum Inflammatory Markers</title>
<p>Since the inflammatory response was the main affected pathway in the serum proteome following local heart irradiation, the level of 11 different cytokines and inflammatory mediators was measured in serum using ELISA. At 8 Gy, only the level of IL-6 significantly increased. In contrast, following 16 Gy, the serum levels of TNF-&#x003B1;, TGF-&#x003B2;, MCP-1, IL-1 &#x003B1; and &#x003B2;, IL-6, IL-12, and G-CSF were significantly increased in comparison with controls (<xref ref-type="fig" rid="F4">Figure 4</xref>). The level of IFN-&#x003B3;, IL-10, and GM-CSF remained unchanged after irradiation.</p>
<fig id="F4" position="float">
<label>Figure 4</label>
<caption><p>The ELISA analysis of serum cytokines. The level of cytokines was measured in 100 &#x003BC;g of serum in mice following 8 or 16 Gy local heart radiation using ELISA (<italic>t</italic>-test; &#x0002A;<italic>p</italic> &#x0003C; 0.05, mean with SEM, <italic>n</italic> = 5).</p></caption>
<graphic xlink:href="fpubh-09-678856-g0004.tif"/>
</fig>
</sec>
<sec>
<title>Radiation-Associated Changes in Serum Lipids</title>
<p>The changes in the serum proteome indicated alterations in lipid metabolism. Therefore, the level of free fatty acid (FFA), total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglyceride (TG) was measured in the serum of the control and irradiated mice. The level of FFA was increased at both radiation doses, while the levels of total cholesterol and LDL were increased only at 16 Gy. Similarly, the level of HDL was reduced only at 16 Gy (<xref ref-type="fig" rid="F5">Figure 5</xref>). The level of TG remained unchanged in irradiated mice.</p>
<fig id="F5" position="float">
<label>Figure 5</label>
<caption><p>The ELISA analysis of serum lipid levels. The levels of free fatty acid (FFA), triglyceride (TG), total cholesterol, HDL, LDL, and oxidized low-density lipoprotein (oxLDL) were measured in 100 &#x003BC;g of serum of mice at 8- or 16-Gy local heart irradiation using ELISA (<italic>t</italic>-test; &#x0002A;<italic>p</italic> &#x0003C; 0.05, mean with SEM, <italic>n</italic> = 5).</p></caption>
<graphic xlink:href="fpubh-09-678856-g0005.tif"/>
</fig>
<p>To examine the effect of oxidative stress on the level of serum lipids, the level of oxidized LDL (oxLDL) was analyzed. The analysis confirmed an enhanced level of oxLDL at both radiation doses (<xref ref-type="fig" rid="F5">Figure 5</xref>).</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>The serum proteome is a reliable mirror of the individual&#x00027;s healthy and diseased states (<xref ref-type="bibr" rid="B33">33</xref>). In this study, we used global serum proteomics analysis as a starting point to predict radiation effects outside the target tissue. Applying a multivariate analysis on the data, in this case principal component analysis and hierarchical clustering, we could separate the control group from the irradiated groups. Although the analysis could even differentiate between the two irradiated groups based on the radiation dose, it also highlighted a panel of proteins being differentially expressed in both irradiated groups. This panel, rather than one single protein, can be considered as a radiation biomarker in the serum proteome.</p>
<p>This analysis also clearly showed that local heart irradiation is able to induce systemic inflammation and hypercholesterolemia in mice. These two responses are similar to those found in a multiomics study comparing atherogenic and dyslipidemic mice with wild-type mice and, more importantly, when comparing familial hypercholesterolemia patients with healthy controls (<xref ref-type="bibr" rid="B34">34</xref>).</p>
<p>The degree of this systemic inflammatory and dyslipidemic effect was dose-dependent and thereby presumably also related to the degree of the heart damage. The dose of 8 Gy was only partly able to induce similar proteome changes as the 16-Gy dose, and the proteome was, in general, altered to a lesser extent. Furthermore, the lower radiation dose was not able to alter the cytokine or lipid profile of the serum as strongly as the higher dose.</p>
<p>The pathological changes in the locally irradiated heart tissue of these mice have been described in our previous study (<xref ref-type="bibr" rid="B35">35</xref>) where we showed radiation-induced elevation of inactive phosphorylated PPAR&#x003B1; and increased expression levels of proteins involved in SMAD-dependent and SMAD-independent TGF-&#x003B2; signaling. Furthermore, we showed enhanced levels of proteins involved in fibroblast to myofibroblast conversion and inflammation at 16 Gy. Some, but not all, of these protein expression changes were also present at 8 Gy (<xref ref-type="bibr" rid="B35">35</xref>). Histological examination in similarly treated C57BL/6J mice revealed a significant increase in epicardial thickness (8 and 16 Gy), enhanced levels of inflammatory cells, and iron-containing macrophages (16 Gy) after 20 weeks (<xref ref-type="bibr" rid="B36">36</xref>). These changes are in line with the alterations found in the serum of irradiated mice in this study.</p>
<p>We have shown previously that, particularly, cardiac endothelial cells respond to high-dose radiation by secreting proinflammatory cytokines <italic>in vivo</italic> and <italic>in vitro</italic> (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B37">37</xref>&#x02013;<xref ref-type="bibr" rid="B39">39</xref>). TNF-&#x003B1; that we found significantly elevated at the 16-Gy dose modulates the inflammatory response by activating the expression of IL-1 and IL-6 (<xref ref-type="bibr" rid="B40">40</xref>). These cytokines that also were upregulated in the serum of irradiated animals serve as significant predictors of cardiovascular disease (<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B41">41</xref>). In agreement with our data, elevated levels of IL-1 and IL-6 were found in patients after radiation therapy for lung cancer (<xref ref-type="bibr" rid="B42">42</xref>).</p>
<p>We found in this study changed levels in serum proteins involved in blood clotting in irradiated mice, indicating not only inflammatory but also thrombotic changes. Among these were several serpins, plasminogen, fibronectin, and fibrinogen. Fibrinogen is a serum adhesion molecule identified in individuals with a high risk for cardiovascular disorders (<xref ref-type="bibr" rid="B43">43</xref>). IL-1 and IL-6 positively influence the synthesis of fibrinogen (<xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B45">45</xref>). Fibrinogens contribute to atherosclerotic plaque formation by inducing endothelial permeability and increase the probability for thrombus formation by enhancing the blood viscosity and platelet aggregation (<xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B47">47</xref>). In agreement with our results, previous studies show an induction of thrombotic responses in locally irradiated carotid and saphenous arteries and in the heart (<xref ref-type="bibr" rid="B48">48</xref>&#x02013;<xref ref-type="bibr" rid="B50">50</xref>).</p>
<p>The proteomics data in this study predicted radiation-induced activation of TGF-&#x003B2;, and its upregulation in the serum was confirmed at 16 Gy using ELISA. TGF-&#x003B2; is a multifunctional cytokine regulating inflammation and fibrosis in the heart (<xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B52">52</xref>). The consequences of cardiac fibrosis are severe including contractile dysfunction, deformation and remodeling of the cardiac structure, and heart failure (<xref ref-type="bibr" rid="B53">53</xref>). Enhanced levels of TGF-&#x003B2; mediate also radiation-induced cardiac fibrosis that is characterized by excess fibroblast proliferation and deposition of collagen fibers (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B54">54</xref>). We have shown previously the activation of TGF-&#x003B2; signaling and induction of fibrosis in the mouse heart exposed to local high-dose radiation (16 Gy) (<xref ref-type="bibr" rid="B35">35</xref>, <xref ref-type="bibr" rid="B55">55</xref>).</p>
<p>In contrast to the systemic inflammatory effect, this is, to the best of our knowledge, the first study to show that local heart irradiation has a profound effect on serum lipids. Enhanced levels of free fatty acids and total cholesterol that we find here, especially in the 16-Gy irradiated mice, are strong risk factors for cardiovascular disease (<xref ref-type="bibr" rid="B56">56</xref>, <xref ref-type="bibr" rid="B57">57</xref>). Similarly, increased LDL and decreased HDL levels, particularly in combination, are associated with increased risk for cardiovascular disease in humans since, if long lasting, they are known to lead to hardening of the arteries and atherosclerosis (<xref ref-type="bibr" rid="B58">58</xref>). The enhancement of oxLDL serum level that we have observed already in a previous study (<xref ref-type="bibr" rid="B19">19</xref>) is a strong predictive marker for upcoming coronary heart disease events in healthy men and a potential risk factor for cardiovascular disease (<xref ref-type="bibr" rid="B59">59</xref>, <xref ref-type="bibr" rid="B60">60</xref>). OxLDL is involved in the early progression of the atherosclerotic plaque formation including endothelial injury, increased levels of adhesion molecules, leukocyte recruitment and extravasation, and foam cell and thrombus formation (<xref ref-type="bibr" rid="B61">61</xref>). Moreover, it activates the inflammatory response and increases the production of cytokines (<xref ref-type="bibr" rid="B62">62</xref>).</p>
<p>The transcription factor PPAR&#x003B1; that was predicted to be inactivated in irradiated animals, based on the serum proteome profiling, is the main regulator of lipid metabolism (<xref ref-type="bibr" rid="B63">63</xref>). Furthermore, it exerts anti-inflammatory effects in the vascular wall and, thereby, protects against initiation and progression of atherosclerosis (<xref ref-type="bibr" rid="B64">64</xref>). The PPAR&#x003B1; protein is highly expressed in the heart but not excreted in the serum. We have shown previously that cardiac PPAR&#x003B1; is inactivated after local heart irradiation in mice (<xref ref-type="bibr" rid="B28">28</xref>). More importantly, it was inactivated in a dose-dependent manner in the cardiac left ventricle of Mayak nuclear workers exposed to varying total body doses of external gamma radiation when compared with Mayak workers not exposed to irradiation (<xref ref-type="bibr" rid="B10">10</xref>). Both exposed and control workers were diagnosed and died of ischemic heart disease. These data indicate that, although deactivation of PPAR&#x003B1; is a common feature in ischemic heart disease and has been observed in human heart failure patients (<xref ref-type="bibr" rid="B65">65</xref>&#x02013;<xref ref-type="bibr" rid="B69">69</xref>), it is especially prominent in radiation-induced heart disease and, therefore, a radiation target in the heart. It is particularly interesting that this is reflected in the serum proteome and cytokine and lipid profiles.</p>
<p>Immunoglobulins G and M were significantly upregulated in the serum of irradiated mice. Increased levels of both immunoglobulins in blood have been associated with adverse cardiovascular events, particularly in dyslipidemic men, but the epidemiological data are contradictory (<xref ref-type="bibr" rid="B70">70</xref>&#x02013;<xref ref-type="bibr" rid="B73">73</xref>). In contrast, we did not identify cardiac troponins that are immediate markers of cardiac damage in humans as in mice. In mice, cardiac TnI concentrations in serum peaked at 1 to 4 h and declined to baseline by 48&#x02013;72 h after a single administration of isoproterenol (<xref ref-type="bibr" rid="B74">74</xref>). This rapid decline is probably the reason why we did not find it elevated in the mouse serum 20 weeks after local heart radiation. Nevertheless, cardiac troponins seem to stay downregulated in the cardiac tissue a long time after radiation exposure. We have shown previously a dose-dependent decrease in cTnT in the human left ventricle in the Mayak worker study (<xref ref-type="bibr" rid="B10">10</xref>) and cTnI in the locally irradiated mouse heart (8 and 16 Gy) (<xref ref-type="bibr" rid="B28">28</xref>) suggesting an early leakage of cardiac troponins to the serum after radiation-induced myofibril degradation.</p>
<p>All in all, the data presented here suggest that the serum proteins and lipids function as potential biomarkers of cardiac injury following heart high-dose radiation exposure. They confirm our previous findings in the heart proteome following high-dose irradiation suggesting radiation-associated activation of TGF-&#x003B2; but inactivation of PPAR&#x003B1; (<xref ref-type="bibr" rid="B35">35</xref>, <xref ref-type="bibr" rid="B56">56</xref>). Especially, PPAR&#x003B1; has become an interesting therapeutic target due to its pleiotropic activity in controlling lipid metabolism and energy homeostasis, inhibiting inflammation, reducing oxidative stress and apoptosis, and ameliorating contractile function. However, the clinical trials using PPAR&#x003B1; agonists have shown contradictory outcomes so far (<xref ref-type="bibr" rid="B75">75</xref>). We suggest that administering such agonists could be particularly beneficial in connection with radiation therapy for thoracic malignancies where the heart may receive considerable radiation doses leading to adverse cardiovascular events (<xref ref-type="bibr" rid="B76">76</xref>). Furthermore, the data from this serum study could be beneficial in identifying patients who may develop radiation-associated cardiac toxicity.</p>
</sec>
<sec sec-type="data-availability-statement" id="s5">
<title>Data Availability Statement</title>
<p>The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/<xref ref-type="supplementary-material" rid="SM1">Supplementary Material</xref>.</p>
</sec>
<sec id="s6">
<title>Ethics Statement</title>
<p>All animal experiments were approved and licensed under Bavarian federal law (Certificate No. AZ 55.2-1-54-2532-114-2014).</p>
</sec>
<sec id="s7">
<title>Author Contributions</title>
<p>The study was designed by OA, VS, MA, GM, and ST. The irradiation was done by WS and VS. Serum collection was done by VS. The proteomics analysis was done by CT and OA. The ELISA experiments were performed by OA. The multivariate analysis was done by OA. OA and ST wrote the draft manuscript. All authors contributed to the revision of the manuscript, read it, discussed, and approved the final version.</p>
</sec>
<sec sec-type="COI-statement" id="conf1">
<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>
</body>
<back>
<ack><p>We thank Fabian Gruhn for the technical assistance, Lucas Duchrow for the help with the multivariate analysis, and Mona Aghaee for the critical feedback.</p>
</ack>
<sec sec-type="supplementary-material" id="s8">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fpubh.2021.678856/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fpubh.2021.678856/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.XLSX" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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<fn fn-type="financial-disclosure"><p><bold>Funding.</bold> This research was funded by the Federal Ministry of Education and Research of Germany (BMBF) with grant number 02NUK064B (ST). VS was a recipient of a scholarship from the German Academic Exchange Service (DAAD), grant number 91524248.</p>
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