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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Psychiatry</journal-id>
<journal-title>Frontiers in Psychiatry</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Psychiatry</abbrev-journal-title>
<issn pub-type="epub">1664-0640</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpsyt.2021.757139</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Psychiatry</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Altered Fecal Microbiota Signatures in Patients With Anxiety and Depression in the Gastrointestinal Cancer Screening: A Case-Control Study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Zhu</surname> <given-names>Juan</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/912316/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Minjuan</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/1515590/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Shao</surname> <given-names>Dantong</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/1515637/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Ma</surname> <given-names>Shanrui</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/585366/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Wei</surname> <given-names>Wenqiang</given-names></name>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/350539/overview"/>
</contrib>
</contrib-group>
<aff><institution>National Central Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Domenico De Berardis, Azienda Usl Teramo, Italy</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Alessandra Borsini, King&#x00027;s College London, United Kingdom; Mohsen Khosravi, Zahedan University of Medical Sciences, Iran</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Wenqiang Wei <email>weiwq&#x00040;cicams.ac.cn</email></corresp>
<fn fn-type="other" id="fn001"><p>This article was submitted to Psychosomatic Medicine, a section of the journal Frontiers in Psychiatry</p></fn></author-notes>
<pub-date pub-type="epub">
<day>08</day>
<month>11</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>12</volume>
<elocation-id>757139</elocation-id>
<history>
<date date-type="received">
<day>12</day>
<month>08</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>27</day>
<month>09</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2021 Zhu, Li, Shao, Ma and Wei.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Zhu, Li, Shao, Ma and Wei</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:</bold> Increasing attention has been devoted to cancer screening and microbiota in recent decades, but currently there is less focus on microbiota characterization among screeners and its relationship to anxiety and depression.</p>
<p><bold>Methods:</bold> We characterized the microbial communities of fecal samples collected through the FOBT card from anxiety and depression screeners and paired controls in Henan, China (1:2, <italic>N</italic> = 69). DNA was extracted using the MOBIO PowerSoil kit. The V4 region of the 16S rRNA gene was sequenced using MiniSeq and processed using QIIME1. LEfSe was used to identify differentially abundant microbes, the Wilcoxon rank-sum test was used to test alpha diversity differences, and permutational multivariate analysis of variance was used to test for differences in beta diversity.</p>
<p><bold>Results:</bold> Similar fecal microbiota signatures in composition were found among screeners. The intestinal microbial environments by phylum were all composed primarily of <italic>Firmicutes, Bacteroidetes</italic>, and <italic>Proteobacteria</italic>, and the corresponding top genera were <italic>Faecalibacterium, Roseburia</italic>, and <italic>Prevotella</italic>. Compared with controls, the ranking of the top five genera in the anxiety and depression group changed, and the dominant genus was <italic>Prevotella</italic> in the anxiety and depression group and <italic>Faecalibacterium</italic> in the control group. There was a lower relative abundance of <italic>Gemmiger</italic> (1.4 vs. 2.3%, <italic>P</italic> = 0.025), <italic>Ruminococcus</italic> (0.6 vs. 0.8%, <italic>P</italic> = 0.037), and <italic>Veillonella</italic> (0.6 vs. 1.3%, <italic>P</italic> = 0.020). This may be linked to the lower alpha diversity in participants with anxiety and depression (Observed OTUs: 122.35 vs. 143.24; Chao1: 127.35 vs. 149.98), although no significant differences were observed. Distinct clustering in microbial composition between the two groups was detected for the Jaccard distance (<italic>P</italic> = 0.011).</p>
<p><bold>Conclusions:</bold> Our study showed differing microbial characterization among participants with anxiety and depression in the endoscopic screening of upper gastrointestinal cancer. <italic>Gemmiger, Ruminococcus</italic>, and <italic>Veillonella</italic> were informative and have potential clinical implications, which need to be confirmed by large-scale, prospective cohort studies and biological mechanism research.</p></abstract>
<kwd-group>
<kwd>anxiety</kwd>
<kwd>depression</kwd>
<kwd>gut microbiota</kwd>
<kwd>16S rRNA gene sequencing</kwd>
<kwd>microbiota-gut-brain axis</kwd>
<kwd>gastrointestinal cancer</kwd>
<kwd>endoscopic screening</kwd>
</kwd-group>
<contract-sponsor id="cn001">National Key Research and Development Program of China<named-content content-type="fundref-id">10.13039/501100012166</named-content></contract-sponsor>
<counts>
<fig-count count="4"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="55"/>
<page-count count="11"/>
<word-count count="6908"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>In excess of 100 trillion microorganisms colonize the human intestinal plot, which assumes a vital part in human wellbeing and illness conditions (<xref ref-type="bibr" rid="B1">1</xref>). The normal intestinal microbiota act as significant functions in host metabolism, xenobiotics, integrity maintenance of the intestinal mucosal barrier, immunomodulation, and assurance against microorganisms (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B3">3</xref>). The microbiota-gut-brain axis, a research hotspot, refers to the bidirectional communication between the microorganisms residing in the gut and our brain function, behavior, and emotion (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). Adequate evidence highlighted the multifaceted role of the intestinal microbiota in carcinogenesis (e.g., gastrointestinal cancer) and psychological distress (e.g., anxiety and depression disorders) (<xref ref-type="bibr" rid="B6">6</xref>&#x02013;<xref ref-type="bibr" rid="B9">9</xref>). Previous research showed that anxiety and depression patients were characterized by a higher abundance of proinflammatory species (<italic>Enterobacteriaceae</italic> and <italic>Desulfovibrio</italic>), lower microbiota diversity, and a lower abundance of short-chain fatty acid-producing species (<italic>Faecalibacterium</italic>) (<xref ref-type="bibr" rid="B10">10</xref>).</p>
<p>Current national cancer screening recommendations referenced the potential harm of mental health owing to cancer screening (<xref ref-type="bibr" rid="B11">11</xref>). As people increase their emphasis on health problems, studies on cancer screening and psychology represent a growing field. Invasive endoscopic screening for gastrointestinal cancer is often accompanied by negative psychosocial consequences to participants (anxiety and depression symptoms) (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>). Considering the psychological distress in cancer screening and the microbiota-gut-brain axis, the relationship of microbiota and anxiety and depression among screeners becomes interesting. Discovering the microbial characteristics of screeners and microbiota diversity and characteristic genera affecting anxiety and depression would be valuable to optimize the strategy of cancer screening and reduce the negative psychological effects (anxiety and depression) caused by cancer screening. However, so far reliable evidence on microbiota characterization among screeners is limited and insufficient. No known research has investigated the relationship between intestinal microbiota and anxiety and depression among screeners. Therefore, the study aimed to explore the microbial characterization of participants in endoscopic screening and to identify psychological distress-associated gut microbiota.</p></sec>
<sec sec-type="materials and methods" id="s2">
<title>Materials and Methods</title>
<sec>
<title>Study Participants and Sample Collection</title>
<p>Based on the endoscopic screening of the National Cohort of Esophageal Cancer (NCEC) project in China, we retrospectively recruited permanent residents aged 40&#x02013;69 years in August 2019. Fecal samples were collected before endoscopic screening of upper gastrointestinal cancer in Linzhou Cancer Hospital, Henan Province. Fecal sample collection process: (<xref ref-type="bibr" rid="B1">1</xref>) The fecal collection kit, including a fecal collection box and fecal occult blood test card (FOBT) for smearing feces, was prepared in advance. (<xref ref-type="bibr" rid="B2">2</xref>) The kit was distributed to the participants, and the sampling box was directly placed in the squatting stool by themselves. The fresh fecal collection was completed before endoscopy. (<xref ref-type="bibr" rid="B3">3</xref>) After defecation, the FOBT card was opened, the stool collection stick was used to pick up a small number of feces and smear them on the two panes of the FOBT card, and then the card was closed and the FOBT card was placed in the sealed bags. (<xref ref-type="bibr" rid="B4">4</xref>) The sealed bags were stored in the &#x02212;80&#x000B0;C refrigerator in the biobank of Linzhou Cancer Hospital and shipped to the laboratory with dry ice.</p>
<p>Only people with both anxiety and depression symptoms were regarded as anxiety and depression screeners. Those who had neither anxiety nor depression symptoms were regarded as the control group (screeners without anxiety and depression). The control group was matched by age and sex (1:2). A total of 69 participants were included, with 23 anxiety and depression screeners and 46 paired screeners in the control group.</p>
<p>All participants signed written informed consent. This study was approved by the Institutional Review Board of the Cancer Hospital of the Chinese Academy of Medical Sciences (No. 16-171/1250). Participants&#x00027; sociodemographic information was gathered by trained staff <italic>via</italic> a uniform questionnaire.</p></sec>
<sec>
<title>Laboratory Handling and Bioinformatics (DNA Extraction, Amplification, and Sequencing)</title>
<p>Total bacterial deoxyribonucleic acid (DNA) was extracted from the fecal samples using the MOBIO PowerSoil&#x000AE; DNA Isolation Kit protocol. Barcoded amplicons were generated covering the V4 region of the 16S ribosomal RNA (16S rRNA) gene using the 515F (5&#x02032;-GTGYCAGCMGCCGCGGTAA-3&#x02032;) and 806R (5&#x02032;-GGACTACNVGGGTWTCTAAT-3&#x02032;) primers (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B15">15</xref>). Polymerase chain reaction (PCR) mixtures contained 1 &#x003BC;L of forward and reverse primer, 1 &#x003BC;L of template DNA, 4 &#x003BC;L of deoxyribonucleoside-triphosphates (dNTPs), 5 &#x003BC;L of 10&#x000D7; EasyPfu Buffer, 1 &#x003BC;L of EasyPfu DNA Polymerase, and 1 &#x003BC;L of double distilled water into a 50 &#x003BC;L total reaction volume. The PCR amplicons were quantified using the Qubit dsDNA HS Assay Kit (Thermo Fisher/Invitrogen Cat. no. Q32854, Waltham, USA) following the manufacturer&#x00027;s instructions. All sequencing was acted in a solitary MiniSeq run and exported in the FASTQ format. Illumina MiniSeq Reporter was carried out to remove adapter and primer sequences.</p>
<p>All specimens collected were successfully amplified and sequenced. Sequencing data were performed with the Quantitative Insights into Microbial Ecology (QIIME2) platform (<xref ref-type="bibr" rid="B16">16</xref>). The raw sequences were processed to remove low-quality reads, under strict quality control and feature table construction using the Divisive Amplicon Denoising Algorithm 2 (DADA2) algorithm (<xref ref-type="bibr" rid="B17">17</xref>). A similarity threshold of 97% was matched. The taxonomic assignment of the sequence variants was assigned using the Greengenes 13_8 (<xref ref-type="bibr" rid="B18">18</xref>). The Shannon index rarefaction curve was represented in <xref ref-type="supplementary-material" rid="SM2">Supplementary Figure 1</xref>. A total of 23 positive anxiety and depression screeners with a mean of 51,272 reads and 46 non-anxiety and depression screeners with a mean of 60,697 reads were included in the analysis. Then we generated alpha diversity metrics and beta diversity metrics using QIIME.</p></sec>
<sec>
<title>Measurement of Anxiety and Depression</title>
<p>The anxiety symptoms were evaluated by the seven-item Generalized Anxiety Disorder (GAD-7), a widely used and acknowledged measurement tool worldwide. Good psychometrics of GAD-7 has been proved in primary medical care (<xref ref-type="bibr" rid="B19">19</xref>). The reliability of internal consistency of GAD-7 in the study was strong (Cronbach&#x00027;s alpha = 0.888). GAD-7 was used to identify anxiety symptoms of individuals in the past 2 weeks, with seven items and four responses (0 = <italic>never</italic>; 1 = <italic>sometimes</italic>; 2 &#x02265; <italic>half of day</italic>; 3 = <italic>almost every day</italic>). The anxiety score was calculated by adding the answers for each of the items and ranges from 0 to 21. The higher the score, the worse anxious symptoms. A result of five was regarded as the threshold for positive anxiety symptoms (<xref ref-type="bibr" rid="B20">20</xref>).</p>
<p>The nine-item Patient Health Questionnaire (PHQ-9), one of the most well-known self-reported tools for assessing depression symptoms (<xref ref-type="bibr" rid="B21">21</xref>), has shown good performance for evaluating depressive disorder (<xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B23">23</xref>). Cronbach&#x00027;s alpha coefficients of PHA-9 in our study were 0.896. PHQ-9 was used to identify depressive symptoms of individuals in the past 2 weeks, with nine items and four responses (similar to GAD-7). The PHQ-9 score was the sum of each item. The higher the score, the worse the depression symptoms. People with a PHQ-9 score of 5 or higher were considered positive for depression symptoms (<xref ref-type="bibr" rid="B23">23</xref>).</p></sec>
<sec>
<title>Statistical Analysis</title>
<p>Chi-square tests and <italic>T</italic>-tests were used to compare basic characteristics between anxiety and depression screeners and the controls. Evenness index, Shannon index, Observed OTUs, and Chao1 index were used to reflect the alpha diversity. Differences in alpha diversity were analyzed between the anxiety and depression group and paired control group by Wilcoxon rank-sum test. Permutational Multivariate Analysis of Variance (PERMANOVA, R-vegan function adonis) was used to explore whether the flora composition differed by anxiety and depression status (beta diversity). Principal coordinate analysis (PCoA) was used to visualize clustering and find discrepancy among the independent &#x003B2; diversity matrices, based on Bary-Curtis dissimilarity, Jaccard distance, and weighted and unweighted unifrac distances. High relative abundance (&#x02265;0.01) genera were compared between the two groups by the Wilcoxon rank-sum test.</p>
<p>Linear discriminant analysis effect size (LEfSe) was used to identify microbes associated with anxiety and depression symptoms (<xref ref-type="bibr" rid="B24">24</xref>). Using Wilcoxon rank-sum test, LEfSe detects microbiota with significant differences between the two groups. Microbiota, with linear discriminant analysis scores (LDA) &#x02265; 2.032, were identified as potential characteristic flora associated with anxiety and depression symptoms. <italic>P</italic> &#x0003C; 0.05 were considered statistically significant. All analyses were conducted using the software program R Studio (Version 1.1.456).</p></sec></sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec>
<title>Baseline Characteristics of Participants</title>
<p>The average age of screeners in the anxiety and depression group and control group was 55.30 (SD = 8.20) and 55.63 (SD = 7.78), respectively. No statistically significant differences were observed for the baseline characteristics, including BMI, marital status, highest education level, household income, smoking status, alcohol drinking, hot food, and life satisfaction between the anxiety and depression group and the control group (see <xref ref-type="table" rid="T1">Table 1</xref>).</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Baseline characteristics of the anxiety and depression group and the control group.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left"><bold>Characteristics</bold></th>
<th valign="top" align="center" colspan="2" style="border-bottom: thin solid #000000;"><bold>Total</bold></th>
<th valign="top" align="center" colspan="2" style="border-bottom: thin solid #000000;"><bold>Anxiety and depression group</bold></th>
<th valign="top" align="center" colspan="2" style="border-bottom: thin solid #000000;"><bold>Control group</bold></th>
<th valign="top" align="center"><bold><italic>P</italic></bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>Frequency</bold></th>
<th valign="top" align="center"><bold>%</bold></th>
<th valign="top" align="center"><bold>Frequency</bold></th>
<th valign="top" align="center"><bold>%</bold></th>
<th valign="top" align="center"><bold>Frequency</bold></th>
<th valign="top" align="center"><bold>%</bold></th>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><italic>N</italic></td>
<td valign="top" align="center" colspan="2">69</td>
<td valign="top" align="center" colspan="2">23</td>
<td valign="top" align="center" colspan="2">46</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Age, year</td>
<td valign="top" align="center" colspan="2">55.52 &#x000B1; 7.86</td>
<td valign="top" align="center" colspan="2">55.30 &#x000B1; 8.20</td>
<td valign="top" align="center" colspan="2">55.63 &#x000B1; 7.78</td>
<td valign="top" align="center">0.872</td>
</tr>
<tr>
<td valign="top" align="left">BMI, kg/m<sup>2</sup></td>
<td valign="top" align="center" colspan="2">25.15 &#x000B1; 3.40</td>
<td valign="top" align="center" colspan="2">24.43 &#x000B1; 3.21</td>
<td valign="top" align="center" colspan="2">25.51 &#x000B1; 3.47</td>
<td valign="top" align="center">0.213</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">49.3</td>
<td valign="top" align="center">13</td>
<td valign="top" align="center">56.5</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">45.7</td>
<td valign="top" align="center">0.395</td>
</tr>
<tr>
<td valign="top" align="left">Married</td>
<td valign="top" align="center">66</td>
<td valign="top" align="center">95.7</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">91.3</td>
<td valign="top" align="center">45</td>
<td valign="top" align="center">97.8</td>
<td valign="top" align="center">0.210</td>
</tr>
<tr>
<td valign="top" align="left"><bold>Highest education level</bold></td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
<td valign="top" align="center">0.114</td>
</tr>
<tr>
<td valign="top" align="left">Primary school or below</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">42</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">43.5</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">19.6</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Junior or senior high school</td>
<td valign="top" align="center">38</td>
<td valign="top" align="center">55.1</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">47.8</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">58.7</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Undergraduate or over</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">2.9</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">8.7</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>Household income (10,000 RMB/year)</bold></td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
<td valign="top" align="center">0.886</td>
</tr>
<tr>
<td valign="top" align="left">&#x0003C;3.0</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">17.4</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">17.4</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">17.4</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">3.0&#x02013;7.0</td>
<td valign="top" align="center">47</td>
<td valign="top" align="center">68.1</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">65.2</td>
<td valign="top" align="center">32</td>
<td valign="top" align="center">69.6</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">7.0&#x02013;11.0</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">14.5</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">17.4</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">13</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>Smoking status</bold></td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
<td valign="top" align="center">0.175</td>
</tr>
<tr>
<td valign="top" align="left">Do not smoke now</td>
<td valign="top" align="center">58</td>
<td valign="top" align="center">84.1</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">82.6</td>
<td valign="top" align="center">39</td>
<td valign="top" align="center">84.8</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Only occasionally</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">5.8</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">8.7</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Most days or almost every day</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">10.1</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">17.4</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">6.5</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>Alcohol consumption</bold></td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
<td valign="top" align="center">0.102</td>
</tr>
<tr>
<td valign="top" align="left">Never or almost never</td>
<td valign="top" align="center">61</td>
<td valign="top" align="center">88.4</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">91.3</td>
<td valign="top" align="center">40</td>
<td valign="top" align="center">87</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Only occasionally</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">7.2</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">10.9</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Most days or almost every day</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">4.3</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">8.7</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">2.2</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>Hot food (high temperature)</bold></td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
<td valign="top" align="center">0.549</td>
</tr>
<tr>
<td valign="top" align="left">Often</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">2.9</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">4.3</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Seldom</td>
<td valign="top" align="center">67</td>
<td valign="top" align="center">97.1</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">100</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">95.7</td>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>Life satisfaction</bold></td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
<td valign="top" align="center">0.084</td>
</tr>
<tr>
<td valign="top" align="left">Very satisfied</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">11.6</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">17.4</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Satisfied</td>
<td valign="top" align="center">58</td>
<td valign="top" align="center">84.1</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">95.7</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">78.3</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Just so so</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">4.3</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">4.3</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">4.3</td>
<td/>
</tr>
</tbody>
</table>
</table-wrap></sec>
<sec>
<title>Microbial Characterization of Participants in Endoscopic Screening</title>
<p>Similar fecal microbiota signatures in composition were found among screeners. The relative abundance of <italic>Firmicutes</italic> (relative abundance: 71.2%), <italic>Bacteroidetes</italic> (14.6%), <italic>Proteobacteria</italic> (5.8%), <italic>Actinobacteria</italic> (2.8%), and <italic>Unknown</italic> (1.8%) were the top five by phylum. The top five genera in specimens of participants of gastrointestinal cancer screening included <italic>Faecalibacterium</italic> (11.3%), <italic>Roseburia</italic> (10.4%), <italic>Prevotella</italic> (10.3%), <italic>Blautia</italic> (10.0%), and <italic>Escherichia</italic> (3.0%). As for alpha diversity, the Evenness index, Observed OTUs, Shannon index, and Chao1 index were 0.67, 135.77, 4.69, and 142.43. The results were displayed in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>.</p></sec>
<sec>
<title>Microbiota Characterization and Diversity of Screeners, by Anxiety and Depression</title>
<sec>
<title>Alpha Diversity</title>
<p>As shown in <xref ref-type="fig" rid="F1">Figure 1</xref>, the alpha diversity in the anxiety and depression group was decreased compared with the control group, although no significant differences were observed (Observed OTUs: 122.35 vs. 143.24; Shannon index: 4.66 vs. 4.70; Chao1 index: 127.35 vs. 149.98).</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p>Microbial comparison between anxiety and depression group and control group for alpha diversity. <bold>(A)</bold> Evenness index, <bold>(B)</bold> observed OTUs, <bold>(C)</bold> Shannon index, and <bold>(D)</bold> Chao1 index.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpsyt-12-757139-g0001.tif"/>
</fig></sec>
<sec>
<title>Beta Diversity</title>
<p>When considering microbial community composition (i.e., beta diversity), significant clustering was found for the Jaccard distance (<italic>P</italic> = 0.011) between the anxiety and depression group and the control group but not for the Bray-Curtis dissimilarity, Weighted and Unweighted Unifrac distance (<xref ref-type="fig" rid="F2">Figure 2</xref>).</p>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p>Microbial comparison between anxiety and depression group and control group for beta diversity. <bold>(A)</bold> Bray-curtis dissimilarity, <bold>(B)</bold> Jaccard distance, <bold>(C)</bold> unweighted UniFrac, and <bold>(D)</bold> weighted UniFrac.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpsyt-12-757139-g0002.tif"/>
</fig></sec>
<sec>
<title>Microbial Composition</title>
<p>Microbial relative abundances at the phylum, family, genus, and species levels for anxiety and depression group and control group were shown in <xref ref-type="fig" rid="F3">Figure 3</xref>. Similar fecal microbiota signatures in composition were found between the two groups. At the phylum level, the intestinal microbial environments of the two groups were all comprised primarily of <italic>Firmicutes</italic> (66.6 vs. 73.4%, <italic>P</italic> = 0.240), <italic>Bacteroidetes</italic> (15.5 vs. 14.1%, <italic>P</italic> = 0.620), <italic>Proteobacteria</italic> (7.8 vs. 4.7%, <italic>P</italic> = 0.100), and <italic>Actinobacteria</italic> (2.2 vs.3.1%, <italic>P</italic> = 0.541). The <italic>Bacteroidetes</italic> and <italic>Proteobacteria</italic> in feces of patients with anxiety and depression increased, while the <italic>Firmicutes</italic> and <italic>Actinobacteria</italic> decreased, although there was no significant difference.</p>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption><p>Microbial relative abundances for anxiety and depression group and control group. <bold>(A)</bold> Phylum, <bold>(B)</bold> Family, <bold>(C)</bold> Genus, and <bold>(D)</bold> Species.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpsyt-12-757139-g0003.tif"/>
</fig>
<p>At the genus level, compared with controls, the <italic>prevotella</italic> and <italic>Blautia</italic> in feces of anxious and depressed patients showed an increasing trend, while the <italic>Faecalibacterium</italic> and <italic>Roseburia</italic> showed a downward trend, although the difference is not statistically significant. The relative abundance of <italic>prevotella</italic> (10.9 vs. 10.0%, <italic>P</italic> = 0.600), <italic>Faecalibacterium</italic> (10.5 vs. 11.8%, <italic>P</italic> = 0.470), <italic>Blautia</italic> (10.2 vs. 9.8%, <italic>P</italic> = 0.720), <italic>Roseburia</italic> (9.2 vs. 10.9%, <italic>P</italic> = 0.600), and <italic>Escherichia</italic> (3.9 vs. 2.6, <italic>P</italic> = 0.679) were the top five in both groups, but the ranking of the top five genera changed for subjects with anxiety and depression symptoms. The top one genera were <italic>Prevotella</italic> in the anxiety and depression group and <italic>Faecalibacterium</italic> in the control group (<xref ref-type="fig" rid="F3">Figure 3</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>). Microbial relative abundances of each sample for the anxiety and depression group and control group were shown in <xref ref-type="supplementary-material" rid="SM3">Supplementary Figure 2</xref>.</p></sec>
<sec>
<title>Microbial Diversity and Characteristic Genus</title>
<p>The microbiota associated with anxiety and depression symptoms from LEfSe is shown in <xref ref-type="fig" rid="F4">Figure 4</xref>. Screeners with positive anxiety and depression symptoms had greater abundances of <italic>Pediococcus, Erysipelatoclostridium, Granulicatella, Kluyvera, Shuttleworthia, Vagococcus, Faecalicatena</italic>, and lower greater abundances of <italic>Gemmiger, Veillonella, Ruminococcus, Anaerovorax</italic>, and <italic>Barnesiella</italic> at the genus level. Compared with controls, screeners with anxiety and depression symptoms had a less relative abundance of <italic>Gemmiger</italic> (1.4 vs. 2.3%, <italic>P</italic> = 0.025), <italic>Ruminococcus</italic> (0.6 vs. 0.8%, <italic>P</italic> = 0.037), and <italic>Veillonella</italic> (0.6 vs. 1.3%, <italic>P</italic> = 0.020) at genus level (see <xref ref-type="supplementary-material" rid="SM4">Supplementary Figure 3</xref> for more details).</p>
<fig id="F4" position="float">
<label>Figure 4</label>
<caption><p>The microbiota associated with anxiety and depression from LEfSe.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpsyt-12-757139-g0004.tif"/>
</fig></sec></sec></sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>In this study, we investigated the microbial characterization of participants in gastrointestinal cancer screening and identified psychological distress-associated gut microbiota. The microbial environments of screeners all comprised primarily of <italic>Firmicutes, Bacteroidetes</italic>, and <italic>Proteobacteria</italic> at the phylum level and <italic>Faecalibacterium, Roseburia</italic>, and <italic>Prevotella</italic> at the genus level. Compared with the controls, the microbial characterization of screeners was distinct among participants with anxiety and depression, and the ranking of the top five genera in the anxiety and depression group changed. There was a lower relative abundance of <italic>Gemmiger, Ruminococcus</italic>, and <italic>Veillonella</italic> in participants with anxiety and depression, which was also reflected by the decreased alpha diversity in screeners who suffered psychological distress, although the difference was not significant. The findings filled the gap in the field of screening and contribute to a better understanding of endoscopic screening for gastrointestinal cancer and psychological distress, which would provide innovative strategies for relieving anxiety and depression and the optimization and implementation of endoscopic screening programs for upper gastrointestinal cancer in China.</p>
<p>It was evidently clear from the findings that participation in endoscopic screening may increase screeners&#x00027; anxiety and depression symptoms. Current national cancer screening recommendations referenced the potential mental harm owing to cancer screening (<xref ref-type="bibr" rid="B11">11</xref>). The role of psychological status on screening has been seriously underestimated (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>). The psychological impact of the screening procedure itself is a common problem in all cancer screenings, but the psychological problem caused by endoscopic screening is more prominent due to its invasive nature, which presents a challenge to screeners&#x00027; psychological states and emotions, increasing anxiety and depression levels. Taking esophageal cancer as an example, on the one hand, waiting for an invasive endoscopic examination may trigger or increase anxiety and depression levels. On the other hand, screeners are worried about screening results. Even low-risk grade health states (e.g., mild dysplasia and moderate dysplasia) are screened and diagnosed, and the risk of esophageal cancer is nearly 3&#x02013;10 times higher than that of normal people. In this situation, patients may be scared of malignant deterioration and metastasis. Low-risk grade health states, such as moderate dysplasia, had &#x0007E;28 times higher esophageal cancer incidence than normal individuals (<xref ref-type="bibr" rid="B25">25</xref>). In this case, it is difficult for patients to accept the fact in a short time, which may act as a serious stressor and stimulation of life-stress events, especially for patients who have been screened for EC and precancerous lesions. Considering cancer progression, recurrence, and prognosis, they are prone to distress (<xref ref-type="bibr" rid="B26">26</xref>).</p>
<p>Although debate is ongoing, the microbiota-gut-brain axis is becoming as significant as the microbiota for monitoring bidirectional gut-brain communication pathways (<xref ref-type="bibr" rid="B27">27</xref>). Reliable evidence has demonstrated the relationship among brain cognitive function, mood, and intestinal flora (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). Reviews have shown that germ-free animals and animals with pathogenic bacterial infections played a vital role in the intestinal microbiota in the modulation of mood and cognition (<xref ref-type="bibr" rid="B27">27</xref>). Growing evidence indicates that the gastrointestinal microbiota is connected with anxiety and depression disorders. A wide range of studies consistently proposed that anxiety and depression impaired microbial characterization and diversity (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>). The study found that subjects with anxiety and depression had lower alpha diversity, although no significant differences were observed. The results were consistent with findings from previous research that the diversity and abundance of intestinal flora in patients with anxiety and depression decreased overall (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B28">28</xref>). An important systematic review showed that &#x003B1; and &#x003B2; diversity were inconsistent. It indicated that the difference of bacterial taxa related to disorders may be manifested in a higher abundance of prion-flammatory species (e.g., <italic>Enterobacteriaceae</italic>) and lower bacteria producing short-chain fatty acid (e.g., <italic>Faecalibacterium</italic>) (<xref ref-type="bibr" rid="B10">10</xref>). Strong and consistent evidence has shown that <italic>Firmicutes</italic> and <italic>Bacteroidetes</italic> are dominant in human intestinal microbial flora (<xref ref-type="bibr" rid="B29">29</xref>). The change was inconspicuous in our study due to the relatively small sample size.</p>
<p>Several studies found consistent taxonomic differences among participants with generalizing anxiety disorders or depression relative to healthy controls, including higher <italic>Bacteroidetes</italic> and <italic>Proteobacteria</italic> and lower <italic>Firmicutes</italic> at the phylum level (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B30">30</xref>) and higher <italic>Prevotella</italic> and lower <italic>Faecalibacterium</italic> at the genus level (<xref ref-type="bibr" rid="B31">31</xref>), which is consistent with our results. Although these studies have found that the fecal flora of depressed patients is different from that of healthy individuals, the specific difference may vary, which may be related to the diagnostic criteria of research, inclusion criteria, and fecal detection methods (<xref ref-type="bibr" rid="B32">32</xref>). Animal experiments also found that the flora composition of depressed animals was similar to that of depressed patients, such as increased <italic>Bacteroidetes</italic> and decreased <italic>Firmicutes</italic> (<xref ref-type="bibr" rid="B33">33</xref>). However, several studies found the <italic>Lactobacillus</italic> and <italic>Bifidobacterium</italic> were decreased in depressed patients or animal models, which was not found in our study. It may be affected by the selection of subjects, inclusion criteria, and sample size.</p>
<p>In addition, we found that the specific genera <italic>Gemmiger, Ruminococcus</italic>, and <italic>Veillonella</italic> decreased in participants with anxiety and depression. Song et al. (<xref ref-type="bibr" rid="B34">34</xref>) proposed that a higher abundance of <italic>Bacteroides</italic> was linked with a higher fear of cancer recurrence. The relative abundance of <italic>Gemmiger</italic> in the anxiety and depression group was similar to that in another study related to diarrhea-predominant irritable bowel syndrome (2.4%) (<xref ref-type="bibr" rid="B35">35</xref>). In addition, Aranaz&#x00027;s study showed that the abundance of <italic>Gemmiger</italic> decreased in subjects with a higher inflammatory index (<xref ref-type="bibr" rid="B36">36</xref>). Similar results were found in a systematic review in which a reduced abundance of <italic>Ruminococcus</italic> was observed in depressed people (<xref ref-type="bibr" rid="B37">37</xref>). Evidence has shown that the high abundance of <italic>Parabacteroide, Oscillibacter, Paraprevotella, Veillonella, Klebsiella</italic>, and <italic>Desulfovibrio</italic> in patients with depression may demonstrate the role of flora in the emergence of depression (<xref ref-type="bibr" rid="B38">38</xref>). These results indicated that <italic>Gemmiger, Ruminococcus</italic>, and <italic>Veillonella</italic> may be the characteristic and specific genus of high-risk groups and vulnerable participants of anxiety and depression.</p>
<p>A growing body of evidence intriguingly suggests that the microbiota composition of individuals may affect their susceptibility to anxiety and depression (<xref ref-type="bibr" rid="B27">27</xref>). A key study presented the role of mouse microbiota transplantation in detecting the microbiota-gut-brain axis (<xref ref-type="bibr" rid="B39">39</xref>). A landmark study showed that sterile mice changed the function of the hypothalamic&#x02013;pituitary&#x02013;adrenal axis (HPA), which can be reversed by inhabiting specific bacterial strains early in life (<xref ref-type="bibr" rid="B40">40</xref>). The mechanism of how microbiota influences gut-brain signaling may be associated with the pathophysiology of anxiety and depression by delivering peripheral inflammation to the central nerve (<xref ref-type="bibr" rid="B28">28</xref>). These mechanisms may include modulating microbial composition, activating immunity, transducing vagal signals, alternating tryptophan metabolism, and producing specific microbial neuroactive metabolites (<xref ref-type="bibr" rid="B30">30</xref>).</p>
<p>In fact, due to the lack of longitudinal investigation in this study, we do not know how long psychological distress-associated gut microbiota would persist, and longitudinal investigations are sparse. First, we measured the symptoms of anxiety and depression with the GAD-7 and PHQ-9 in the past 2 weeks. Second, the intestinal flora was greatly influenced by diet, lifestyle, geography, and age, and the composition was dynamic and fluctuating (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B42">42</xref>). Large-scale population studies found that antibiotics used in anti-infective treatment significantly increased the risk of individual psychological diseases such as anxiety and depression (<xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B44">44</xref>). Once the microbiota becomes unbalanced, alteration may occur to the microenvironment and then lead to gastrointestinal diseases and even cancer (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B7">7</xref>). Experimental evidence has shown that the human gut flora affects the occurrence and progression of gastrointestinal tumors by activating carcinogenic signaling pathways, producing tumor-promoting metabolites and inhibiting antitumor immune responses (<xref ref-type="bibr" rid="B45">45</xref>). In addition, evidence from saliva and tissues showed that oral flora may act as potential risk factors for oral and gastrointestinal cancer (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B46">46</xref>), but there were differences in flora changes among various studies. <italic>Fusobacterium nucleatum</italic> mainly inhabits the oral cavity and causes periodontal disease, which may promote the aggressive behaviors of tumors by activating chemokines (e.g., CCL20) in esophageal cancer tissues (<xref ref-type="bibr" rid="B47">47</xref>). Therefore, given the important role of the gut microbiome in maintaining homeostasis, a better understanding of the microbiome in cancer screeners is increasingly important. We can develop innovative cancer prevention and therapeutic strategies by targeting the gut microbiota. The human intestinal microbiome plays an important role in cancer screening, especially for gastrointestinal cancer (<xref ref-type="bibr" rid="B48">48</xref>). Meta-analysis indicated that fecal bacteria and oral flora act as promising biomarkers for the noninvasive diagnosis of gastrointestinal cancer (<xref ref-type="bibr" rid="B49">49</xref>).</p>
<p>Since the gastrointestinal microbiota is altered through the rational use of prebiotics, probiotics, and antibiotics (<xref ref-type="bibr" rid="B50">50</xref>), the relationship between mental disorders, the microbiota, and tumors may be of clinical significance and implications. The novel concept of the microbiota-gut-brain axis indicated that regulation of the intestinal flora may be a feasible strategy to develop innovative therapeutics for psychological distress. These mechanisms may clear the way for microbial-based psychotherapies. Mind-altering microorganisms refer to the gut microbiota that could alter the brain and behavior. An important study showed that the potential probiotic could regulate behaviors related to anxiety and depressive disorders and alter central levels of &#x003B3;-aminobutyric acid receptors (<xref ref-type="bibr" rid="B51">51</xref>). Compared with the placebo control group, probiotic Bifidobacterium longum and Lactobacillus helveticus reduced depression scores and altered the brain activity of patients with anxiety and depression (<xref ref-type="bibr" rid="B52">52</xref>). An important study consistently confirmed that probiotics help prevent and relieve depression disorders (<xref ref-type="bibr" rid="B31">31</xref>). In addition, clinical studies found that taking prebiotics daily for 3 weeks reduced the activation of the cortex caused by negative information, thereby reducing anxiety-like and depressive-like behaviors (<xref ref-type="bibr" rid="B53">53</xref>).</p>
<p>The pattern of intestinal microbiota changed significantly in patients with anxiety and depression. Further evidence is needed to translate microbiome findings into innovative clinical treatments to improve therapeutic effects in patients with mental disorders. Anxiety and depression have the characteristics of a low treatment rate, poor compliance, and recurrence, and this study provides a new promising research direction to improve psychological distress, namely mind-altering microorganisms. This suggests that we can attempt to explore probiotics, prebiotics, and other microecological agents to regulate the balance and homeostasis of intestinal flora in cancer screening progress, which contributes to optimizing screening and maximizing the net benefits of cancer screening. However, little clinical and large-scale research on probiotics and prebiotics has been used in treatment strategies. To date, the selection of probiotics is relatively random and difficult to predict, and it is hard to show stable efficacy in different groups. There are some shortcomings in the existing studies, such as a small sample size and poor contrast in the use of probiotics. Therefore, more randomized controlled trials are needed to further verify the efficacy of probiotics and prebiotics.</p>
<p>Adequate evidence has shown the bidirectional relationship between cancer and intestinal microbiota (<xref ref-type="bibr" rid="B54">54</xref>), such as colorectal cancer and malignant gastrointestinal diseases. Evidence highlighted the multifaceted role of the intestinal microbiota in cancer. The occurrence of cancer is usually accompanied by inflammation and leads to microbial alteration and disorder of the intestinal microbial environment, such as increased abundance of <italic>Escherichia coli</italic> and <italic>Fusobacterium nucleatum</italic> in colorectal cancer (<xref ref-type="bibr" rid="B54">54</xref>, <xref ref-type="bibr" rid="B55">55</xref>). Conversely, the unbalanced microbiota could also cause a proinflammatory microenvironment and DNA damage, increasing the risk of cancer and deteriorating the prognosis, such as <italic>Helicobacter pylori</italic>, and invasive <italic>Escherichia coli</italic>. Further studies are needed to decipher whether there is a synergistic effect of microbial and psychological distress in tumor promotion, which may be exploited therapeutically in the future.</p>
<p>To our knowledge, first, this is the first study to explore the microbial characterization of participants in gastrointestinal cancer screening, filling the gap in the field of screening. This perspective is innovative and provides new ideas and optimization strategies for the comprehensive evaluation of cancer screening. Second, the included subjects were from the same regions, with similar dietary patterns, and the controls were matched by age and sex, which makes the findings more objective and credible to some extent. Some limitations of our work should be acknowledged. First, the stratified analysis of anxiety and depression separately was confined by the relatively small sample size. This may lead to no significant difference on some microbial characterizations and diversity, but the trend of our results provided scientific references in this field. Our exploratory study largely provides clues from a novel perspective. This study is an attempt to explore the microbial characterizations of screeners. Larger studies will be needed to reduce the uncertainty and confirm our associations. Second, we did not have specimens from non-screeners as bank controls. Third, selection bias may exist, and the sample may not be representative of all screeners. Further multicenter, large-scale, and prospective cohort studies, randomized controlled trials, and clinical trials are needed to validate the results. Fourth, anxiety and depression symptoms were evaluated in the study, not a clinical diagnosis of anxiety and depression disorders. In the future, psychiatrists could be considered in the screening process. Finally, considering the goal of this study and other factors (e.g., economy, efficiency, and data processing), we chose 16S rRNA gene sequencing. In the future, full metagenomics could be applied for further exploration of mechanisms, pathway in-depth, and functional prediction analysis.</p></sec>
<sec sec-type="conclusions" id="s5">
<title>Conclusions</title>
<p>Differing microbial characterization among participants with anxiety and depression was found in the endoscopic screening of upper gastrointestinal cancer in China. <italic>Gemmiger, Ruminococcus</italic>, and <italic>Veillonella</italic> were informative for psychological distress in cancer screening and have potential clinical implications for mental disorders, which provides references for optimizing cancer screening and minimizing psychological harm. The results should be explained cautiously, and more large-scale, prospective cohort studies are needed in the future to validate the results and further explore biological mechanisms and the relationship among gut microbiota, psychological distress, and cancer risk in cancer screening.</p></sec>
<sec sec-type="data-availability" id="s6">
<title>Data Availability Statement</title>
<p>The data presented in the study are deposited in the the Genome Sequence Archive (GSA) repository, accession number <ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="CRA005126">CRA005126</ext-link>.</p></sec>
<sec id="s7">
<title>Ethics Statement</title>
<p>This study was approved by the Institutional Review Board of the Cancer Hospital of the Chinese Academy of Medical Sciences (No. 21/030-2701; 16-171/1250). The patients/participants provided their written informed consent to participate in this study.</p></sec>
<sec id="s8">
<title>Author Contributions</title>
<p>This research was designed by WW. JZ drafted the manuscript. ML, DS, and JZ collected the related data and materials. JZ analyzed and interpreted the data. JZ, SM, and WW revised the manuscript. All authors contributed to the article and approved the submitted version.</p></sec>
<sec sec-type="funding-information" id="s9">
<title>Funding</title>
<p>This work was supported by the National Natural Science Foundation of China (Grant/Award Number: 81974493) and the National Key Research and Development Program (Precision Medicine Research) (Grant/Award Number: 2016YFC0901400, 2016YFC0901404).</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>
<sec sec-type="disclaimer" id="s10">
<title>Publisher&#x00027;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
</body>
<back>
<ack><p>The chief acknowledgment was to the participants for accepting and completing the interview. We thank Linzhou Cancer Hospital for valuable support for our work.</p>
</ack><sec sec-type="supplementary-material" id="s11">
<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/fpsyt.2021.757139/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fpsyt.2021.757139/full#supplementary-material</ext-link></p>
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<supplementary-material xlink:href="Data_Sheet_2.PDF" id="SM3" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Data_Sheet_3.PDF" id="SM4" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<ref-list>
<title>References</title>
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