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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.2024.1380720</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Immunophenotypic variations in syphilis: insights from Mendelian randomization analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Xie</surname>
<given-names>Qinghui</given-names>
</name>
<uri xlink:href="https://loop.frontiersin.org/people/1133924"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/visualization/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tang</surname>
<given-names>Yijie</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Shen</surname>
<given-names>Lingyun</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yang</surname>
<given-names>Dandan</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Jiaqin</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Luo</surname>
<given-names>Qingqiong</given-names>
</name>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1181316"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
<role content-type="https://credit.niso.org/contributor-roles/validation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<institution>Department of Clinical Laboratory Medicine, Shanghai Skin Disease Hospital, School of Medicine, Tongji University</institution>, <addr-line>Shanghai</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Jean-louis Mege, Aix-Marseille Universit&#xe9;, France</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Debora Decote-Ricardo, Federal Rural University of Rio de Janeiro, Brazil</p>
<p>Werner Solbach, University of L&#xfc;beck, Germany</p>
<p>Anthony Levasseur, Aix-Marseille Universit&#xe9;, France</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Qingqiong Luo, <email xlink:href="mailto:luoqingqiong2007@126.com">luoqingqiong2007@126.com</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>17</day>
<month>04</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1380720</elocation-id>
<history>
<date date-type="received">
<day>02</day>
<month>02</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>04</day>
<month>04</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Xie, Tang, Shen, Yang, Zhang and Luo</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Xie, Tang, Shen, Yang, Zhang and Luo</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>
<sec>
<title>Background</title>
<p>Infection with <italic>Treponema pallidum</italic> instigates complex immune responses. Prior research has suggested that persistent <italic>Treponema pallidum</italic> infection can manipulate host immune responses and circumvent host defenses. However, the precise role of immune cells in <italic>Treponema pallidum</italic> infection across different stages remains a contentious issue.</p>
</sec>
<sec>
<title>Methods</title>
<p>Utilizing summary data from genome-wide association studies, we employed a two-sample Mendelian randomization method to investigate the association between 731 immunophenotypes and syphilis. Syphilis was categorized into early and late stages in this study to establish a more robust correlation and minimize bias in database sources.</p>
</sec>
<sec>
<title>Results</title>
<p>Our findings revealed that 33, 36, and 27 immunophenotypes of peripheral blood were associated with syphilis (regardless of disease stage), early syphilis and late syphilis, respectively. Subsequent analysis demonstrated significant variations between early and late syphilis in terms of immunophenotypes. Specifically, early syphilis showcased activated, secreting, and resting regulatory T cells, whereas late syphilis was characterized by resting Treg cells. More B cells subtypes emerged in late syphilis. Monocytes in early syphilis exhibited an intermediate and non-classical phenotype, transitioning to classical in late syphilis. Early syphilis featured naive T cells, effector memory T cells, and terminally differentiated T cells, while late syphilis predominantly presented terminally differentiated T cells. Immature myeloid-derived suppressor cells were evident in early syphilis, whereas the dendritic cell immunophenotype was exclusive to late syphilis.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Multiple immunophenotypes demonstrated associations with syphilis, showcasing substantial disparities between the early and late stages of the disease. These findings hold promise for informing immunologically oriented treatment strategies, paving the way for more effective and efficient syphilis interventions.</p>
</sec>
</abstract>
<kwd-group>
<kwd>Mendelian randomization</kwd>
<kwd>syphilis</kwd>
<kwd>immunophenotypes</kwd>
<kwd>peripheral blood</kwd>
<kwd>variation</kwd>
</kwd-group>
<counts>
<fig-count count="5"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="35"/>
<page-count count="9"/>
<word-count count="2780"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Microbial Immunology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Syphilis, a chronic sexually transmitted disease caused by the bacterium <italic>Treponema pallidum</italic> (TP), poses a significant threat to global health. The World Health Organization reported a surge in cases, reaching 7.1 million in 2020 (<xref ref-type="bibr" rid="B1">1</xref>). Syphilis is classified as early stages (primary, secondary, and latent syphilis) and late stages (late latent and tertiary syphilis) (<xref ref-type="bibr" rid="B2">2</xref>). Untreated latent syphilis can progress to neurosyphilis, cardiosyphilis or syphilitic gumma, causing damages to the brain, heart or nerves (<xref ref-type="bibr" rid="B3">3</xref>).</p>
<p>During the initial stages of infection, TP lipoproteins activate dendritic cells (DCs) and macrophages through Toll-like receptor 2 (TLR2)-dependent signaling pathways. As these lipoproteins are primarily located beneath the outer membrane of TP, systemic inflammation in early syphilis is not evident (<xref ref-type="bibr" rid="B4">4</xref>). Rare TP&#x2019;s outer membrane proteins makes it difficult for pathogen-associated pattern molecules to engage TLRs on macrophages and DCs, hindering the activation of the innate pathogen recognition system (<xref ref-type="bibr" rid="B4">4</xref>). TP appears to be primarily cleared through cellular immunity, which is mediated by CD4<sup>+</sup> and CD8<sup>+</sup> T cells (<xref ref-type="bibr" rid="B5">5</xref>&#x2013;<xref ref-type="bibr" rid="B8">8</xref>). Research has predominantly focused on the changes in CD4<sup>+</sup>/CD8<sup>+</sup> T cell ratios during disease development (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>), TP immune evasion facilitated by regulatory T (Treg) cells (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>), and immunosuppression resulting from an imbalance in T helper (Th)1/Th2 cell differentiation (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>). B cells have been less studied in TP infection compared to T cells. However, some studies demonstrate their role as immunoregulatory cells in addition to antibody production and activation of T cells as antigen-presenting cells (<xref ref-type="bibr" rid="B15">15</xref>). Notably, regulatory B cells have been found to inhibit CD4<sup>+</sup>T cell proliferation and enhance forkhead box protein P3 (Foxp3) and cytotoxic T-lymphocyte associated protein (CTLA)-4 expression in Treg cells (<xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B17">17</xref>). Understanding how immune cells function after syphilis infection requires further study. Although progress has been made <italic>in vitro</italic> culturing of syphilis (<xref ref-type="bibr" rid="B18">18</xref>), the lack of a suitable inbred animal model and <italic>in vitro</italic> culture model poses challenges for syphilis immunologic studies (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B20">20</xref>). Despite studying differences in immune cell types and functions in syphilis patients with varying disease courses, how syphilis evades the immune system remains controversial. Additionally, different samples including peripheral blood (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B21">21</xref>), cerebrospinal fluid (<xref ref-type="bibr" rid="B22">22</xref>), blister fluid (<xref ref-type="bibr" rid="B21">21</xref>), and tissue (<xref ref-type="bibr" rid="B6">6</xref>) exhibit distinct immunological compartments.</p>
<p>As a &#x201c;natural randomized controlled trial&#x201d;, Mendelian randomization (MR) minimizes the impact of confounding factors on results by using complementary base pairing between alleles for passage (<xref ref-type="bibr" rid="B23">23</xref>). This study employs MR to analyze how different syphilis courses correlate with distinct immunophenotypes, providing a foundation for testing syphilis detection targets, developing, and delving deeper into the study of disease mechanisms.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>The assumptions of MR</title>
<p>Single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) for genetic variation. In a two-sample MR analysis, these SNPs were employed to explore the correlation between 731 immunophenotypes across 7 panels and syphilis. To minimize the potential bias affecting the results, three crucial hypotheses were adopted as follows (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>): (1) Strength of the correlation between IVs and exposure was assessed using F statistics. A robust relationship was defined by F &gt; 10. (2) IVs were assumed to be independent of confounding variables, safeguarding against potential sources of bias. (3) IVs were postulated to exert their impact solely through the exposure, ensuring a direct and unadulterated influence on the outcome.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Overview of MR assumptions.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1380720-g001.tif"/>
</fig>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>IVs selection</title>
<p>To ensure the robustness of our findings, the significance level of immunophenotype IVs was set to 1 &#xd7; 10<sup>&#x2212;5</sup>. The selection process involved SNPs from Genome-wide association studies (GWAS) with stringent criteria, including <italic>P</italic> &lt; 5 &#xd7; 10<sup>-8</sup> and no linkage disequilibrium (r<sup>2</sup> &lt; 0.001, clustering distance = 10000 kb) in summary statistics (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). The strength of each IV was evaluated through the calculation of the F statistic. After filtering out IVs with low F statistics (F &lt; 10), 17097 IVs were retained for subsequent analysis.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Overview of  MR analysis.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1380720-g002.tif"/>
</fig>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Data sources for immunophenotypes</title>
<p>Comprehensive information on 731 immunophenotypes in peripheral blood was obtained from published articles (<xref ref-type="bibr" rid="B24">24</xref>). These immunophenotypes were classified into 4 trait types, comprising 118 absolute counts (AC), 389 median fluorescence intensity (MFI), 32 morphological parameters (MP) and 192 relative counts (RC). These trait types were further divided into 7 panels, including B cell, circulating DC, Treg cell, mature stages of T cell, TBNK (T cell, B cell, natural killer cell), monocyte and myeloid cell (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>).</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>GWAS data sources for syphilis</title>
<p>Syphilis GWAS summary statistics were sourced from 3 different GWAS datasets available in IEU OpenGWAS (<ext-link ext-link-type="uri" xlink:href="https://gwas.mrcieu.ac.uk/">https://gwas.mrcieu.ac.uk/</ext-link>) (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). The syphilis GWAS, irrespective of the disease stage, involved 213302 European individuals (N<sub>case</sub> = 350, N<sub>control</sub> = 212952). A total of 213117 European individuals were part of the early syphilis GWAS (N<sub>case</sub> = 165, N<sub>control</sub> = 212952), and 213125 European individuals participated in the late syphilis GWAS (N<sub>case</sub> = 173, N<sub>control</sub> = 212952).</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Statistical analysis</title>
<p>R 4.2.2 software was used for data analysis. The &#x201c;TwoSample MR&#x201d; software package (version 0.5.7) was utilized to assess the correlation between 731 immunophenotypes and syphilis. The MR analysis was conducted using three methods: inverse variance weighting (IVW), MR Egger, and weighted median, with IVW as the primary method. Details could be reached in Supplementary files.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<p>A total of 17907 SNPs were identified as IVs for GWAS. Each SNP demonstrated an F statistic exceeding the empirical threshold of 10, indicating robust validity.</p>
<sec id="s3_1">
<label>3.1</label>
<title>Correlation between immunophenotypes and syphilis (regardless of disease stage)</title>
<p>Two-sample MR analysis using IVW method unveiled a significant correlation between 731 immunophenotypes and syphilis (regardless of disease stage). Among these, 33 immunophenotypes exhibited significant association to syphilis (<italic>P</italic> &lt; 0.05). Notably, B cell panels accounted for 27.3% (9/33), Treg cells for 24.2% (8/33), cDC for 18.2% (6/33), TBNK for 12.12% (4/33), monocytes for 9.09% (3/33), maturation stages of T cells for 6.06% (2/33), and myeloid cells for 3.03% (1/33). The forest pot depicting these correlations is presented in <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Forest plot: 33 immunophenotypes correlated with syphilis (regardless of disease stage).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1380720-g003.tif"/>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Correlation between immunophenotypes and early syphilis</title>
<p>In the analysis of early syphilis, 36 immunophenotypes demonstrated significant correlations (<italic>P</italic> &lt; 0.05). Treg cell panels were prominent, accounting for 44.44% (16/36), followed by B cell panels at 16.67% (6/36), maturation stages of T cell panels at 16.67% (6/36), monocyte panels at 8.33% (3/36), myeloid cell panels at 8.33% (3/36), TBNK panels at 5.56% (2/36). The forest plot depicting these correlations is presented in <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Forest plot: 36 immunophenotypes correlated with early syphilis.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1380720-g004.tif"/>
</fig>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Correlation between immunophenotypes and late syphilis</title>
<p>In the context of late syphilis, 27 immunophenotypes displayed significant correlations (<italic>P</italic> &lt; 0.05). B cell panels were prevalent, constituting 48.15% (13/27), followed by Treg cell panels at 7.41% (2/27), TBNK panels at 11.11% (3/27), monocyte panels at 11.11% (3/27), cDC panels at 11.11% (3/27), myeloid cell panels at 7.41% (2/27), maturation stages of T cell panels at 3.70% (1/27). The forest plot depicting these correlations is presented in <xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref>.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Forest plot: 27 immunophenotypes correlated with late syphilis.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1380720-g005.tif"/>
</fig>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Comparison of immunophenotypes across syphilis stages</title>
<p>Upon comparing all immunophenotypes across the three syphilis stages, early syphilis exhibited 13 shared immunophenotypes with syphilis (regardless of disease stage), while late syphilis shared 10 immunophenotypes. Notably, CD25 on IgD<sup>+</sup>CD38<sup>-</sup>B cells and IgD<sup>+</sup>CD38<sup>dim</sup>B cells were consistently present in all stages of syphilis, emphasizing their potential as key markers (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Treg cell immunophenotypes, especially activated and secreting types, were predominantly associated with early syphilis. Monocytes in early syphilis displayed intermediate type (CD14<sup>+</sup>CD16<sup>+</sup>). Effector memory mature T cells were present in early syphilis, while terminally differentiated mature T cells were found in late syphilis. Intriguingly, cDC immunophenotypes only emerged in late syphilis, indicating distinctive immune responses across syphilis stages.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>The immunophenotypes that overlap with syphilis (regardless of disease stage) in early or late syphilis.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">outcome</th>
<th valign="top" align="left">trait type</th>
<th valign="top" align="left">panel</th>
<th valign="top" align="left">exposure</th>
<th valign="top" align="left">nsnp</th>
<th valign="top" align="left">pval</th>
<th valign="top" align="left">or(95%CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="13" align="left">
<bold>Early syphilis</bold>
</td>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">B cell</td>
<td valign="top" align="left">IgD- CD38dim B cell</td>
<td valign="top" align="right">25</td>
<td valign="top" align="right">0.040</td>
<td valign="top" align="right">1.13 (1.01 - 1.26)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">B cell</td>
<td valign="top" align="left">
<bold>IgD+ CD38dim B cell</bold>
</td>
<td valign="top" align="right">32</td>
<td valign="top" align="right">0.006</td>
<td valign="top" align="right">0.88 (0.80 - 0.96)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">B cell</td>
<td valign="top" align="left">
<bold>CD25 on IgD+ CD38- B cell</bold>
</td>
<td valign="top" align="right">27</td>
<td valign="top" align="right">0.011</td>
<td valign="top" align="right">1.10 (1.02 - 1.19)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">Treg</td>
<td valign="top" align="left">Activated CD4 Treg cell</td>
<td valign="top" align="right">19</td>
<td valign="top" align="right">0.048</td>
<td valign="top" align="right">0.83 (0.69 - 1.00)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">Treg</td>
<td valign="top" align="left">CD39+ secreting CD4 Treg cell</td>
<td valign="top" align="right">20</td>
<td valign="top" align="right">0.017</td>
<td valign="top" align="right">0.87 (0.78 - 0.98)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">Treg</td>
<td valign="top" align="left">CD28- CD127- CD25++ CD8+ T cell</td>
<td valign="top" align="right">20</td>
<td valign="top" align="right">0.023</td>
<td valign="top" align="right">1.23 (1.03 - 1.46)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">Treg</td>
<td valign="top" align="left">CD28- CD4-CD8- T cell</td>
<td valign="top" align="right">24</td>
<td valign="top" align="right">0.029</td>
<td valign="top" align="right">0.81 (0.67 - 0.98)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">Treg</td>
<td valign="top" align="left">CD3 on CD39+ activated CD4 Treg cell</td>
<td valign="top" align="right">27</td>
<td valign="top" align="right">0.009</td>
<td valign="top" align="right">1.22 (1.05 - 1.41)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">Treg</td>
<td valign="top" align="left">CD28 on CD4 Treg cell</td>
<td valign="top" align="right">25</td>
<td valign="top" align="right">0.031</td>
<td valign="top" align="right">1.10 (1.01 - 1.21)</td>
</tr>
<tr>
<td valign="top" align="left">AC</td>
<td valign="top" align="left">TBNK</td>
<td valign="top" align="left">CD4+ CD8dim T cell</td>
<td valign="top" align="right">17</td>
<td valign="top" align="right">0.047</td>
<td valign="top" align="right">1.25 (1.00 - 1.55)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">Maturation stages<break/>of T cell</td>
<td valign="top" align="left">CD4 on effector memory CD4+ T cell</td>
<td valign="top" align="right">20</td>
<td valign="top" align="right">0.004</td>
<td valign="top" align="right">0.77 (0.64 - 0.92)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">Monocyte</td>
<td valign="top" align="left">CD40 on CD14+ CD16+ monocyte</td>
<td valign="top" align="right">20</td>
<td valign="top" align="right">0.004</td>
<td valign="top" align="right">0.85 (0.76 - 0.95)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">Monocyte</td>
<td valign="top" align="left">CD14 on CD14+ CD16+ monocyte</td>
<td valign="top" align="right">17</td>
<td valign="top" align="right">0.014</td>
<td valign="top" align="right">0.69 (0.52 - 0.93)</td>
</tr>
<tr>
<td valign="middle" rowspan="10" align="left">
<bold>Late syphilis</bold>
</td>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">B cell</td>
<td valign="top" align="left">
<bold>IgD+ CD38dim B cell</bold>
</td>
<td valign="top" align="right">15</td>
<td valign="top" align="right">0.024</td>
<td valign="top" align="right">1.32 (1.04 - 1.68)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">B cell</td>
<td valign="top" align="left">
<bold>CD25 on IgD+ CD38- B cell</bold>
</td>
<td valign="top" align="right">27</td>
<td valign="top" align="right">0.011</td>
<td valign="top" align="right">1.10 (1.02 - 1.19)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">B cell</td>
<td valign="top" align="left">CD20- B cell</td>
<td valign="top" align="right">18</td>
<td valign="top" align="right">0.007</td>
<td valign="top" align="right">1.22 (1.05 - 1.41)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">B cell</td>
<td valign="top" align="left">CD20 on IgD+ CD38dim B cell</td>
<td valign="top" align="right">29</td>
<td valign="top" align="right">0.043</td>
<td valign="top" align="right">1.19 (1.01 - 1.40)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">B cell</td>
<td valign="top" align="left">IgD+ CD24- B cell</td>
<td valign="top" align="right">18</td>
<td valign="top" align="right">0.045</td>
<td valign="top" align="right">1.18 (1.00 - 1.39)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">cDC</td>
<td valign="top" align="left">HLA DR on myeloid DC</td>
<td valign="top" align="right">16</td>
<td valign="top" align="right">0.021</td>
<td valign="top" align="right">1.18 (1.02 - 1.35)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">cDC</td>
<td valign="top" align="left">HLA DR on plasmacytoid DC</td>
<td valign="top" align="right">22</td>
<td valign="top" align="right">0.037</td>
<td valign="top" align="right">1.17 (1.01 - 1.35)</td>
</tr>
<tr>
<td valign="top" align="left">MFI</td>
<td valign="top" align="left">cDC</td>
<td valign="top" align="left">HLA DR on DC</td>
<td valign="top" align="right">19</td>
<td valign="top" align="right">0.038</td>
<td valign="top" align="right">1.19 (1.01 - 1.41)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">TBNK</td>
<td valign="top" align="left">TCRgd T cell</td>
<td valign="top" align="right">18</td>
<td valign="top" align="right">0.041</td>
<td valign="top" align="right">1.16 (1.01 - 1.34)</td>
</tr>
<tr>
<td valign="top" align="left">RC</td>
<td valign="top" align="left">Maturation stages<break/>of T cell</td>
<td valign="top" align="left">Terminally differentiated CD4+ T cell</td>
<td valign="top" align="right">22</td>
<td valign="top" align="right">0.044</td>
<td valign="top" align="right">0.75 (0.56 - 0.99)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>AC, absolute count; MFI, median fluorescence intensitie; MP, morphological parameter; RC, relative count; DC, dendritic cell; nsnp, single nucleotide polymorphisms; Treg cell, regulatory T cell. Bold value indicates immunophenotypes  observed in all stages of syphilis.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>In this study, we conducted a comprehensive analysis using publicly available GWAS data to explore the correlation between syphilis and 731 immune immunophenotypes. The findings revealed significant associations between syphilis and immune cell panels, including B cells, cDCs, Tregs, TBNKs, monocytes, myeloid cells, and maturation stages of T cells. Moreover, distinctive immunophenotypic differences were identified between early and late syphilis in peripheral blood.</p>
<p>In the context of early syphilis, a distinctive prominence of Treg cell immunophenotypes was observed, constituting a substantial 44.44% of the identified correlations. Intriguingly, a spectrum of Treg cell activity was noted, encompassing activated, secreting, and resting Treg cells during this stage. In contrast, late syphilis predominantly featured resting Treg cells, indicating a shift in Treg cell dynamics over the course of the disease progression. Treg cells, as a vital subset of CD4<sup>+</sup>T cells, played a crucial role in inhibiting the host immune response during early syphilis. This inhibition facilitated the evasion of TP from the host immune defense mechanisms, thereby contributing to the progression of the disease (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B25">25</xref>). Remarkably, individuals with early syphilis exhibited a higher prevalence of Treg cells in peripheral blood compared to healthy counterparts (<xref ref-type="bibr" rid="B25">25</xref>). This phenomenon might be attributed to the stimulation of monocytes by TpF1 (miniferritin produced by TP), resulting in the release of immunosuppressive factors such as interleukin (IL)-10 and transforming growth factor (TGF)-&#x3b2;, consequently fostering the differentiation of Treg cells (<xref ref-type="bibr" rid="B11">11</xref>). Moreover, an augmentation in mature CD4<sup>+</sup>T cells and CD8<sup>+</sup>T cells was observed in early syphilis, aligning with analogous findings in TBNK results. However, the available data did not allow for conclusive inferences regarding alterations in the CD4<sup>+</sup>/CD8<sup>+</sup> ratio. Notably, the peripheral blood of early syphilis patients exhibited a significant decrease in CD4<sup>+</sup>T cells compared to CD8<sup>+</sup>T cells, potentially attributed to the pyroptosis of CD4<sup>+</sup>T cells (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>). In the context of late syphilis, B cell-related immunophenotypes took center stage, constituting 48.15% of the identified correlations. This prevalence included various B cell subtypes such as plasma cells, memory B cells, transitional B cells, naive cells (IgD<sup>+</sup>CD38<sup>-</sup>), and activated B cells (IgD<sup>+</sup>CD38<sup>dim</sup>). The presence of these B cell subsets in early syphilis indicated a diverse and dynamic immune response. Notably, neurosyphilis patients exhibited elevated levels of CXCL13 in their cerebrospinal fluid, suggesting a potential mediation of B cell aggregation (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B27">27</xref>). However, the precise mechanism by which B cells in the peripheral blood of syphilis patients regulate immunity remains unclear and warrants further investigation.</p>
<p>The differentiation of monocytes from hematopoietic precursor cells in the bone marrow into macrophages and DCs plays a pivotal role in the immune response (<xref ref-type="bibr" rid="B28">28</xref>). Monocyte subpopulations, broadly categorized as classical (CD14<sup>+</sup>CD16<sup>&#x2212;</sup>), non-classical (CD14<sup>&#x2212;</sup>CD16<sup>+</sup>), and intermediate (CD14<sup>+</sup>CD16<sup>+</sup>), exhibit distinct functions (<xref ref-type="bibr" rid="B24">24</xref>). Our data illuminate that the monocyte immunophenotype in early syphilis is characterized by an abundance of intermediate (CD14<sup>+</sup>CD16<sup>+</sup>) and non-classical (CD14<sup>&#x2212;</sup>CD16<sup>+</sup>) monocytes, while late syphilis is marked by classical (CD14<sup>+</sup>CD16<sup>&#x2212;</sup>) monocytes. Intermediate monocytes are actively involved in antigen presentation and inflammation, whereas classical monocytes primarily function as immune surveillance cells, specializing in immune phagocytosis (<xref ref-type="bibr" rid="B29">29</xref>). Consistent with our findings, studies by Liu et&#xa0;al. have demonstrated that TP can augment the expression of CD14 and CD16 in monocytes <italic>in vitro</italic>, leading to the differentiation of monocytes into intermediate monocytes (<xref ref-type="bibr" rid="B30">30</xref>). This increase in intermediate monocytes may exert a profound impact on T cell subset differentiation and contribute to immune evasion. Notably, stimulated by TP, intermediate monocytes have the capacity to release immunosuppressive factors such as IL-10 and TGF-&#x3b2;, thereby promoting the proliferation and differentiation of Treg cells (<xref ref-type="bibr" rid="B11">11</xref>). In the immunological milieu of early syphilis, a significant upregulation of interferon-gamma (IFN-&#x3b3;) is noted in the plasma, accompanied by a propensity of Th cells to differentiate towards the Th1 phenotype (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B14">14</xref>). Concurrently, the pro-inflammatory characteristics of non-classical monocytes tilt the immune response towards Th2 (<xref ref-type="bibr" rid="B31">31</xref>). Furthermore, TP, through the TLR2 signaling pathway, can stimulate the maturation of DCs. These activated DCs, in turn, secrete a repertoire of cytokines, including IL-2, IL-6, and tumor necrosis factor (TNF)-&#x3b1;, triggering an inflammatory response (<xref ref-type="bibr" rid="B32">32</xref>). Intriguingly, our early syphilis data did not reveal a distinct conventional cDC immunophenotype. A plausible hypothesis posits that DCs may initially encounter the skin mucous membranes during early infection (<xref ref-type="bibr" rid="B33">33</xref>), as blister fluid from skin lesions has been reported to contain higher concentrations of activated monocytes, macrophages, and DCs compared to peripheral blood (<xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B35">35</xref>). This underlines the dynamic interplay of immune cells at the site of infection, offering valuable insights into the localized immune responses during early syphilis.</p>
<p>Despite the robust analysis conducted in this study, several limitations must be acknowledged. The lack of complete information on the database hindered a precise definition and distinction between early and late syphilis. Additionally, the study&#x2019;s reliance on a European database may limit the generalizability of conclusions to other ethnic groups. Future research should aim to address these limitations and conduct reverse MR verification. The identified syphilis-related immunophenotypes offer valuable insights for vaccine development, disease prevention, and research into immune escape mechanisms. Further investigations, especially in diverse populations, will enhance our understanding of syphilis immunopathogenesis.</p>
<p>In conclusion, this study provides a comprehensive analysis of the correlation between syphilis and immune immunophenotypes, unraveling distinct immune responses in early and late syphilis. The findings may contribute to the broader understanding of syphilis pathogenesis and offer implications for therapeutic and preventive interventions.</p>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s6" sec-type="author-contributions">
<title>Author contributions</title>
<p>XQ: Conceptualization, Data curation, Writing &#x2013; original draft, Formal analysis, Visualization. YT: Methodology, Writing &#x2013; original draft. LS: Methodology, Writing &#x2013; original draft. DY: Data curation, Writing &#x2013; original draft. JZ: Data curation, Writing &#x2013; original draft. QL: Funding acquisition, Supervision, Validation, Writing &#x2013; review &amp; editing.</p>
</sec>
</body>
<back>
<sec id="s7" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Talent Introduction Special Fund of Shanghai Skin Disease Hospital (No. 2022KYQD03).</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>
<sec id="s10" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fimmu.2024.1380720/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fimmu.2024.1380720/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet_1.csv" id="SM1" mimetype="text/csv"/>
<supplementary-material xlink:href="DataSheet_2.csv" id="SM2" mimetype="text/csv"/>
<supplementary-material xlink:href="DataSheet_3.csv" id="SM3" mimetype="text/csv"/>
</sec>
<fn-group>
<title>Abbreviations</title>
<fn fn-type="abbr">
<p>TP, <italic>Treponema pallidum</italic>; GWAS, genome-wide association studies; MR, Mendelian randomization; cDCs, circulating dendritic cells; SNPs, single nucleotide polymorphisms; IVs, instrumental variables; AC, absolute count; MFI, median fluorescence intensity; MP, morphological parameter; RC, relative count; OR, odds ratio; 95%CI, 95% confidence interval; DCs, dendritic cells.</p>
</fn>
</fn-group>
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