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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.2024.1475528</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Gut microbiome and metabolomics in systemic sclerosis: feature, link and mechanisms</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Yao</surname>
<given-names>Qicen</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2780508"/>
<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/validation/"/>
<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/methodology/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Tan</surname>
<given-names>Wenfeng</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/498311"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/resources/"/>
<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 contrib-type="author" corresp="yes">
<name>
<surname>Bai</surname>
<given-names>Feihu</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2299944"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/resources/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/validation/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Rheumatology and Immunology, The Second Affiliated Hospital of Hainan Medical University</institution>, <addr-line>Haikou</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Nanjing Medical University</institution>, <addr-line>Nanjing</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Rheumatology, The First Affiliated Hospital of Nanjing Medical University</institution>, <addr-line>Nanjing</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Gastroenterology, The Second Affiliated Hospital of Hainan Medical University</institution>, <addr-line>Haikou</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Matilde Otero-Losada, National Scientific and Technical Research Council (CONICET), Argentina</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Lihua Duan, Jiangxi Provincial People&#x2019;s Hospital, China</p>
<p>Mathieu Garand, Washington University in St. Louis, United States</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Feihu Bai, <email xlink:href="mailto:baifeihu_hy@163.com">baifeihu_hy@163.com</email>; Wenfeng Tan, <email xlink:href="mailto:tanwenfeng2005@126.com">tanwenfeng2005@126.com</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>04</day>
<month>11</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1475528</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>08</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>14</day>
<month>10</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Yao, Tan and Bai</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Yao, Tan and Bai</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>Systemic sclerosis (SSc) is a rare and highly heterogeneous chronic autoimmune disease characterized by multi-organ and tissue fibrosis, often accompanied by a poor prognosis and high mortality rates. The primary pathogenic mechanisms of SSc are considered to involve tissue fibrosis, autoimmune dysfunction, and microvascular abnormalities. Recent studies have shed light on the gut microbiota (GM) and metabolites in SSc patients, revealing their association with gastrointestinal symptoms and disease phenotypes. However, further elucidation is needed on the specific mechanisms underlying the interactions between GM, metabolites, and the immune system and their roles in the pathogenesis of SSc. This review outlines the characteristics of GM and metabolites in SSc patients, exploring their interrelationships and analyzing their correlations with the clinical phenotypes of SSc. The findings indicate that while the &#x3b1;-diversity of GM in SSc patients resembles that of healthy individuals, notable differences exist in the &#x3b2;-diversity and the abundance of specific bacterial genera, which are closely linked to gastrointestinal symptoms. Moreover, alterations in the levels of amino acids and lipid metabolites in SSc patients are prominently observed and significantly associated with clinical phenotypes. Furthermore, this review delves into the potential immunopathological mechanisms of GM and metabolites in SSc, emphasizing the critical role of interactions between GM, metabolites, and the immune system in comprehending the immunopathological processes of SSc. These insights may offer new scientific evidence for the development of future treatment strategies.</p>
</abstract>
<kwd-group>
<kwd>systemic sclerosis</kwd>
<kwd>gut microbiota dysbiosis</kwd>
<kwd>metabolites</kwd>
<kwd>correlation analysis</kwd>
<kwd>pathogenesis</kwd>
</kwd-group>
<counts>
<fig-count count="2"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="116"/>
<page-count count="16"/>
<word-count count="7759"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Systems 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>Systemic sclerosis (SSc) is a rare and complex chronic autoimmune disease that causes fibrosis in multiple organs, particularly the skin and lungs (<xref ref-type="bibr" rid="B1">1</xref>). Among the skin lesions associated with SSc, the most common types are limited cutaneous SSc (lcSSc) and diffused cutaneous SSc (dcSSc). Despite these common typical presentations, SSc displays a broad range of clinical manifestations and diverse prognostic features, holding the highest mortality rate among all rheumatic diseases (<xref ref-type="bibr" rid="B2">2</xref>). A comprehensive study by EUSTAR (EULAR Scleroderma Trials and Research) revealed that pulmonary fibrosis (PF) is responsible for 35% of SSc-related deaths, while pulmonary arterial hypertension (PAH) and cardiac complications each account for 26% (<xref ref-type="bibr" rid="B3">3</xref>). Therefore, the extensive multi-organ and tissue fibrosis caused by SSc, along with its poor prognosis and high mortality rates, severely affect patients&#x2019; quality of life and overall survival. Additionally, the SCORE project&#x2019;s multicenter study highlighted that gastrointestinal tract (GIT) complications are the third most common cause of death in SSc patients, following PAH and interstitial lung disease (ILD) (<xref ref-type="bibr" rid="B4">4</xref>). Notably, about 90% of SSc patients experience some degree of GIT fibrosis during the disease course (<xref ref-type="bibr" rid="B3">3</xref>). Thus, the widespread multi-organ and tissue fibrosis secondary to SSc, coupled with its poor prognosis and elevated mortality rates, significantly impact patients&#x2019; quality of life and overall survival.</p>
<p>The pathogenesis of SSc remains complex and multifactorial, involving tissue fibrosis, autoimmune dysfunction, and microvascular abnormalities (<xref ref-type="bibr" rid="B4">4</xref>). Key cell types such as immune cells, fibroblasts, and endothelial cells, alongside the inflammatory mediators, are central to the initiation and progression of SSc (<xref ref-type="bibr" rid="B5">5</xref>&#x2013;<xref ref-type="bibr" rid="B7">7</xref>). Recent research has highlighted the role of the gut microbiota (GM) in maintaining host health through interactions with environmental factors, genetic predispositions, metabolites, and immune signals (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>). Disruptions in the GM and their metabolites have been implicated as potential triggers for the development or progression of SSc and associated multi-organ damage (<xref ref-type="bibr" rid="B10">10</xref>&#x2013;<xref ref-type="bibr" rid="B14">14</xref>), closely intertwined with inflammatory responses, vascular impairment, and fibrotic processes (<xref ref-type="bibr" rid="B11">11</xref>). The evolution of multi-omics and high-throughput sequencing technologies has significantly enriched our comprehension of the actions of GM and metabolomics in the host (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>). However, investigations into the relationship between the two realms remain somewhat limited.&#xa0;Hence, further investigation into the interplay between GM,&#xa0;metabolites, and the immune system holds significant importance&#xa0;in elucidating the immunopathological mechanisms underlying SSc.</p>
<p>This review aims to synthesize the most recent research advancements, elucidate the methodologies and features of detecting GM and metabolites in SSc, and better understand the interconnection between GM and metabolites, along with their possible mechanisms of influence in SSc. By conducting this thorough analysis, our goal is to offer a fresh insight into the pathophysiology of SSc and establish a sound scientific foundation for forthcoming therapeutic approaches.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Alterations in the intestinal microenvironment of SSc patients and their clinical relevance</title>
<p>The intestinal microbiota has emerged as a focal point of research in SSc, with numerous studies highlighting the presence of microbial imbalance in SSc patients (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). These imbalance have shown significant correlations with disease progression, subtypes, prognosis, and treatment outcomes in SSc. Additionally, abnormalities in the microbiota composition have been observed at fibrotic sites, such as the skin and intestines, in SSc (<xref ref-type="bibr" rid="B17">17</xref>). However, the presence of a lung microbiome remains controversial. To date, only a few studies have explored the relationship between the gut microbiome and SSs-ILD. Interestingly, the bronchoalveolar lavage fluid from patients with rheumatoid arthritis-associated ILD showed significantly lower microbial diverse and abundant (<xref ref-type="bibr" rid="B18">18</xref>). These findings indicate a potential association between GM&#x2019;s dysregulation and SSc&#x2019;s pathogenesis.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Alterations of the gut microbiome in SSc.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Year</th>
<th valign="top" align="center">Region</th>
<th valign="top" align="center">Subjects<break/>(n)</th>
<th valign="top" align="center">Sample type</th>
<th valign="top" align="center">Methods</th>
<th valign="top" align="center">Gut microbiota in patients with SSc</th>
<th valign="top" align="center">Reference</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">2016</td>
<td valign="top" align="center">Sweden</td>
<td valign="top" align="center">SSc (98)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">GA-map&#x2122; Dysbiosis Test</td>
<td valign="top" align="center">Faecalibacterium prausnitzii and Clostridiaceae and Lactobacillus&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B29">29</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2016</td>
<td valign="top" align="center">United States</td>
<td valign="top" align="center">SSc (17) VS HC (17)</td>
<td valign="top" align="center">Cecum<break/>and sigmoid mucosal lavage samples</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">Commensal bacteria:<break/>Faecalibacterium and Clostridium &#x2193;.<break/>Pathobiont bacteria:<break/>Fusobacterium and &#x3b3;-Proteobacteria&#x2191;.<break/>Commensal genera:<break/>Bifidobacterium and Lactobacillus&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B22">22</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2017</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc-GI+ (9) VS SSc-GI- (9) VS HC (9)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">SSc-GI+ vs HC:<break/>Lactobacillus, Eubacterium and Acinetobacter&#x2191;.<break/>Roseburia, Clostridium, and Ruminococcus&#x2193;.<break/>SSc-GI- vs HC:<break/>Streptococcus salivarius&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B28">28</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2017</td>
<td valign="top" align="center">United States, Norway</td>
<td valign="top" align="center">UCLA-SSc (17), OUH-SSc (17) VS HC (17)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">UCLA VS HC<break/>Phylum:<break/>Firmicutes&#x2191;, Bacteroidetes&#x2193;.<break/>Commensal genera:<break/>Fusobacterium, Ruminococcus, &#x3b3;-Proteobacteria, Erwinia and Lactobacillus &#x2191;,<break/>Faecalibacterium and Bacteroides &#x2193;.<break/>OUH VS HC<break/>Phylum:<break/>Bacteroidetes&#x2193;.<break/>Commensal genera:<break/>Lactobacillus &#x2191;, Clostridium, and Bacteroides &#x2193;.<break/>OUH VS UCLA<break/>Commensal genera: Faecalibacterium and Bacteroides &#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B21">21</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (59) VS HC (28)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">Parabacterioides, Firmicutes, Butyricimonas, and Desulfovibrio&#x2191;.<break/>Turicibacter and Lachnospiraceae &#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B20">20</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (63) VS HC (17)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">Lactobacillus and Streptococcus&#x2191;.<break/>Sutterella&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B19">19</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">USA</td>
<td valign="top" align="center">SSc (19)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">Genus:<break/>Clostridiales&#x2191;, Bacteroides&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B23">23</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2021</td>
<td valign="top" align="center">Canada</td>
<td valign="top" align="center">SSc (29) VS HC (20)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">phyla:<break/>Proteobacteria and Bacteroidetes &#x2191;, Firmicutes&#x2193;.<break/>Genus:<break/>Bacteroides and Lachnospira&#x2191;, Enterococcus, and Lactococcus&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B26">26</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">2021</td>
<td valign="top" align="center">United States</td>
<td valign="top" align="center">SSc (90)<break/>and IgG4-RD (58) VS HC (165)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">Metagenomic sequencing</td>
<td valign="top" align="center">SSc and IgG4-RD VS HC<break/>pathogenic Clostridium and oral Streptococcus&#x2191;,<break/>Alistipes and Bacteroides&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B31">31</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2022</td>
<td valign="top" align="center">United States, Sweden</td>
<td valign="top" align="center">UCLA-SSc (71), LU-SSc (106) VS HC (85)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">UCLA VS HC<break/>pathobionts Streptococcus, Enterococcus&#x2191;,<break/>LU VS HC<break/>pathobiont genera:<break/>Desulfovibrio &#x2191;<break/>commensal genera:<break/>Faecalibacterium &#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B30">30</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">Singapore</td>
<td valign="top" align="center">SSc (23) VS HC (19)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">Metagenomic sequencing</td>
<td valign="top" align="center">Phyla:<break/>Firmicutes, Actinobacteria&#x2191;, Bacteroidetes&#x2193;.<break/>Genus:<break/>Lactobacillus, Bifidobacterium and Coprococcus&#x2191;</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B10">10</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">United States</td>
<td valign="top" align="center">SSc (66)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" align="center">16S rRNA</td>
<td valign="top" align="center">Non-low FODMAP diet group:<break/>pathobiont Enterococcus&#x2191;.<break/>Severe GI symptoms group: Lactobacillus and Firmicutes&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B25">25</xref>)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="center">2024</td>
<td valign="top" rowspan="2" align="center">Italy</td>
<td valign="top" rowspan="2" align="center">SSc (25)</td>
<td valign="top" rowspan="2" align="center">Feces</td>
<td valign="top" rowspan="2" align="center">16S rRNA</td>
<td valign="top" align="center">SSc<break/>Phyla(top 5):<break/>Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, and Verrucomicrobia&#x2191;.</td>
<td valign="top" rowspan="2" align="center">(<xref ref-type="bibr" rid="B24">24</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">ACA+ VS anti-Scl70+:<break/>Phylum:<break/>Lentisphaerae&#x2191;.<break/>Genus:<break/>NA-Acidaminococcaceae&#x2191;.<break/>Classes:<break/>Lentisphaeria and Opitutae&#x2191;.</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>&#x2191; increased, &#x2193; decreased. HC, healthy controls; 16S rRNA, 16S ribosomal RNA sequencing; GI+, gastrointestinal involvement; UCLA, the University of California, Los Angeles; OUH, Oslo University Hospital; IgG4-RD, immunoglobulin G4-related disease; LU, Lund University; FODMAP, a low versus non-low fermentable oligosaccharides, disaccharides, monosaccharides, and polyols; ACA, anticentromere antibody.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<sec id="s2_1">
<label>2.1</label>
<title>Alterations of the GM in SSc</title>
<p>Recent research indicates that the &#x3b1; diversity in SSc patients mirrors that of healthy controls (HC) (<xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B22">22</xref>). Moreover, a year-long longitudinal study revealed no notable alterations in &#x3b1; and &#x3b2; diversity or the relative abundance of GM throughout the disease progression in SSc patients (<xref ref-type="bibr" rid="B23">23</xref>). However, variations exist in the abundance of different taxa within the GM. At the phylum level, Firmicutes (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>), Proteobacteria (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B26">26</xref>), and Actinobacteria (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B24">24</xref>) exhibit increased abundance, while Bacteroidetes display a fluctuating trend of abundance (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B26">26</xref>). Additionally, a higher relative abundance of Fusobacteria has been noted (<xref ref-type="bibr" rid="B24">24</xref>). These observations underscore distinct differences in the GM composition between SSc patients and the healthy population (<xref ref-type="bibr" rid="B27">27</xref>). At the genus level, several genera, including Lactobacillus (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B29">29</xref>), Streptococcus (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B30">30</xref>, <xref ref-type="bibr" rid="B31">31</xref>), Fusobacterium (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>), Enterococcus (<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B30">30</xref>), Desulfovibrio (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B30">30</xref>), Faecalibacterium (<xref ref-type="bibr" rid="B29">29</xref>), and Bacteroides (<xref ref-type="bibr" rid="B26">26</xref>) show elevated relative abundances in SSc patients. Conversely, commensal genera associated with anti-inflammatory effects, such as Faecalibacterium (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B30">30</xref>) and Bacteroides (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B31">31</xref>), exhibit reduced relative abundance. Clostridium, known for inducing the expansion of regulatory T cells (<xref ref-type="bibr" rid="B32">32</xref>), also shows decreased relative abundance in SSc patients (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B28">28</xref>). On the other hand, pathogenic Clostridium (<xref ref-type="bibr" rid="B31">31</xref>) and Bacteroides (<xref ref-type="bibr" rid="B26">26</xref>) exhibit increased relative abundance, while Roseburia (<xref ref-type="bibr" rid="B28">28</xref>) shows a decline. These shifts in the abundance of various microbial genera, including Faecalibacterium (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B30">30</xref>) and Clostridium (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B28">28</xref>), suggest a potential association between GM abnormalities and immunoinflammation in SSc.</p>
<p>Furthermore, intriguing trends in the relative abundance of Bifidobacterium and Lactobacillus (<xref ref-type="bibr" rid="B34">34</xref>) in SSc contrast with patterns typically observed in inflammatory bowel disease. For instance, Lactobacillus (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>) and Bifidobacterium (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B23">23</xref>) exhibit elevated relative abundances. Specifically, two independent studies reported a significant increase in Lactobacillus counts among SSc patients (<xref ref-type="bibr" rid="B22">22</xref>). Additionally, a separate cohort study observed a higher abundance of commensal bacteria, specifically Bifidobacteria, in the University of California Los Angeles cohort than in the Oslo University Hospital cohort (<xref ref-type="bibr" rid="B30">30</xref>). The study suggested that genetic factors, dietary patterns, or the presence of SSc-associated ILD may play a role in this diversity among cohorts. Moreover, Natalello et&#xa0;al. highlighted elevated levels of Lactobacillus and Streptococcus in SSc patients compared to healthy controls (HCs), alongside reduced expression of Sartellabacteria, which is negatively associated with inflammation (<xref ref-type="bibr" rid="B19">19</xref>). The genus Ruminalococcus displayed variable abundance levels across studies (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B28">28</xref>). These findings suggest a potential correlation between GM abnormalities and immunoinflammation in SSc.</p>
<p>The GM has been implicated in the pathogenesis and clinical manifestations of various rheumatic diseases, contributing to fibrotic processes in specific internal organs (<xref ref-type="bibr" rid="B33">33</xref>). Previous evidence has indicated a decrease in GM diversity in SSc patients, notably in those who are overweight and have a disease duration exceeding three years (<xref ref-type="bibr" rid="B19">19</xref>). Research conducted by Andreasson et&#xa0;al. proposed a potential association between GM richness and the progression of SSc, ILD, small intestinal bacterial overgrowth (SIBO), and the utilization of immunosuppressants (<xref ref-type="bibr" rid="B30">30</xref>). Additionally, GM is believed to influence immune cell activity in SSc, with variations in bacterial flora abundance observed between SSc patients positive for anticentromere antibody (ACA) and those positive for anti-Scl-70 (anti-DNA topoisomerase I) (<xref ref-type="bibr" rid="B24">24</xref>). A study exploring the connection between SSc and immunoglobulin G4-related disease (IgG4-RD), which predisposes individuals to fibrotic disorders, revealed heightened levels of pathogenic Clostridium difficile and typical oral streptococci in comparison to HC (<xref ref-type="bibr" rid="B31">31</xref>). The study also highlighted an increase in E. lenta cgr+ strains capable of activating Th17, while homocysteine (Hcy)-producing Clostridium difficile displayed a preferential colonization in SSc. Concurrently, reductions in Alistipes, Bacteroides, and species producing butyrate were noted in both diseases (<xref ref-type="bibr" rid="B31">31</xref>). These alterations imply a decrease in beneficial commensal species and an increase in potentially harmful and proinflammatory strains that may influence inflammatory and fibrotic processes by modulating Th17 cell responses. While the literature has progressively reported on the association between GM and SSc subtypes, there are conflicting studies suggesting that ecological dysbiosis is not linked to age, disease duration, disease subtype, or the extent of dermal fibrosis (<xref ref-type="bibr" rid="B29">29</xref>). Therefore, the predominant GM profile in SSc remains ambiguous, and its relationship with disease subtypes and fibrosis continues to be discussed and investigated.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Association of GM dysbiosis with gastrointestinal symptoms in SSc</title>
<p>Despite GIT involvement being prevalent in up to 90% of SSc patients, most exhibit unremarkable symptoms with a diverse clinical presentation. The UCLA Scleroderma Clinical Trials Consortium&#x2019;s Gastrointestinal Tract Scoring Tool 2.0 (UCLA-GIT 2.0) is a widely utilized tool for evaluating GIT involvement in SSc (<xref ref-type="bibr" rid="B34">34</xref>). Dysregulation of GM and SSc-related GIT symptoms can manifest at any stage of the disease (<xref ref-type="bibr" rid="B30">30</xref>). Research revealed that SSc patients with GIT symptoms (SSc/GIT+) displayed a significantly lower &#x3b1; diversity index compared to both HCs and SSc patients without GIT symptoms (SSc/GIT-). Moreover, SSc/GIT+ patients exhibited reduced fecal microbiota abundance yet higher homogeneity (<xref ref-type="bibr" rid="B28">28</xref>). However, &#x3b2;-diversity analyses indicated greater variability in fecal microbiota among SSc/GIT+ patients (<xref ref-type="bibr" rid="B28">28</xref>). Specifically, a decrease in Bacteroides abundance was correlated with the duration of GIT symptoms (<xref ref-type="bibr" rid="B23">23</xref>). Esophageal dysfunction, commonly seen in SSc-GIT, may present as reflux disease with or without esophagitis (<xref ref-type="bibr" rid="B29">29</xref>). In addition, about 50% of SSc patients experience lower GIT involvement, which correlates with increased morbidity and mortality, showcasing clinical signs such as malabsorption, constipation, diarrhea, recurrent pseudo-obstruction, and fecal incontinence (<xref ref-type="bibr" rid="B1">1</xref>). Remarkably, SSc patients with concurrent SIBO exhibit higher bacterial diversity and abundance. However, there was no significant symptom discrepancy between SIBO-positive and SIBO-negative patients that could be independently linked to microbial composition (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B30">30</xref>).</p>
<p>Recent studies have validated the association between gastrointestinal symptoms and GM imbalances. Specifically, an escalation in the abundance of pathogenic genera such as Klebsiella and Enterococcus was noted among patients with more severe symptoms (<xref ref-type="bibr" rid="B25">25</xref>). In the aforementioned independent cohort study involving SSc patients, it was observed that Clostridium was prevalent in those with lower gastrointestinal symptom severity, while Lactobacillus levels were higher in individuals experiencing none-to-mild constipation. Additionally, Prevotella showed heightened presence in patients with moderate-to-severe gastrointestinal symptom severity (<xref ref-type="bibr" rid="B21">21</xref>). Lactobacillus, a widely recognized probiotic strain crucial for maintaining GM equilibrium, has consistently shown increased levels in SSc patients across various studies (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B29">29</xref>), suggesting its potential role in alleviating gastrointestinal symptoms in SSc. Conversely, a separate investigation highlighted a reduction in <italic>Bacteroides fragilis</italic> abundance and an elevation in Fusobacterium levels among SSc patients with moderate to severe gastrointestinal symptoms (<xref ref-type="bibr" rid="B22">22</xref>). These findings underscore a probable correlation between specific microbial flora and the intensity of gastrointestinal symptoms in patients, offering prospective microbial targets for future therapeutic interventions.</p>
</sec>
</sec>
<sec id="s3">
<label>3</label>
<title>Alterations of the metabolism in SSc</title>
<p>Recent literature reports significant changes in metabolite levels in the blood, fecal, and urine samples of SSc patients, with these alterations showing correlations with the SSc phenotype (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B13">13</xref>). Nevertheless, our current knowledge regarding the specific functions of these metabolites in the pathophysiological pathways of SSc remains restricted. Therefore, a detailed examination of the advancements in metabolomics research related to SSc is crucial for a comprehensive comprehension of the pathophysiological mechanisms involved. Moreover, metabolomics is anticipated to offer valuable data to support SSc diagnosis, disease classification, personalized therapeutic approaches, as well as the identification and validation of biomarkers.</p>
<sec id="s3_1">
<label>3.1</label>
<title>Alterations in metabolites and their metabolic pathways in SSc</title>
<p>Several studies have examined changes in the plasma, serum, and urine concentrations of amino acids and their derivatives or metabolites in SSc patients (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). The findings reveal elevated levels of amino acids such as glutamine, proline, glutamate, alanine, arginine, and Hcy, alongside metabolites linked to amino acid derivatives (betaine, 1-methylhistidine, 3-methylhistidine, dimethylarginine, phenylacetylglutamine, methylnicotinamide, kynurenine, malondialdehyde) in the plasma/serum of SSc patients (<xref ref-type="bibr" rid="B35">35</xref>&#x2013;<xref ref-type="bibr" rid="B43">43</xref>). Conversely, some studies have reported reduced levels of alanine, aspartate, glutamate, and L-tyrosine (<xref ref-type="bibr" rid="B42">42</xref>&#x2013;<xref ref-type="bibr" rid="B44">44</xref>). Furthermore, various studies have noted decreased levels of tryptophan (Trp) in SSc patients (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B41">41</xref>&#x2013;<xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B45">45</xref>), a finding corroborated in hypochlorite- and bleomycin-induced mouse models of SSc (<xref ref-type="bibr" rid="B45">45</xref>). Notably, kynurenine, a classic Trp metabolite, was found at heightened concentrations in the plasma and serum of SSc patients (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B42">42</xref>). While some studies indicated higher plasma Hcy levels in SSc patients compared to HCs (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>), others reported no significant difference in Hcy levels between these groups (<xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B47">47</xref>). Moreover, elevated levels of &#x3b1;-N-phenylacetyl-L-glutamine were detected in SSc patients, contrasting with decreased levels of proline betaine (<xref ref-type="bibr" rid="B48">48</xref>). Collectively, these findings suggest that amino acid dysregulation may play a crucial role in the metabolic pathways associated with SSc.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Alterations of metabolites in SSc.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Year</th>
<th valign="top" align="center">Region</th>
<th valign="top" align="center">Subjects<break/>(n)</th>
<th valign="top" align="center">Sample type</th>
<th valign="top" align="center">Methods</th>
<th valign="top" align="center">Altered metabolites in SSc vs HC</th>
<th valign="top" align="center">References</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">2000</td>
<td valign="top" align="center">Sweden</td>
<td valign="top" align="center">SSc (27) VS HC (27)</td>
<td valign="top" align="center">Plasma,</td>
<td valign="top" align="center">GC-MS</td>
<td valign="top" align="left">Nitrate&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B115">115</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2003</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (71)VS HC (30)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-FLD</td>
<td valign="top" align="left">Homocysteine&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B37">37</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2006</td>
<td valign="top" align="center">South Africa</td>
<td valign="top" align="center">SSc (15) VS HC (13)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">GC-MS</td>
<td valign="top" align="left">Malondialdehyde&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B35">35</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2007</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (60) VS HC (30)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-FLD</td>
<td valign="top" align="left">Homocysteine&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B36">36</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2009</td>
<td valign="top" align="center">United States</td>
<td valign="top" align="center">SSc (10)VS HC (14)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HPLC-QTRAP-MS</td>
<td valign="top" align="left">Arachidonoyl-lysophosphatidic acid, sphingosine 1-phosphate&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B57">57</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2016</td>
<td valign="top" align="center">Sweden</td>
<td valign="top" align="center">SSc (19) VS HC (18)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">GC-MS</td>
<td valign="top" align="left">arginine&#x2191;.<break/>2-oxoglutaric acid&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B40">40</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2016</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (40) VS HC (40)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-MS</td>
<td valign="top" align="left">25-hydroxivitamin D3 &#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B116">116</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (37) VS HC (20)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">H-NMRS and GC-MS</td>
<td valign="top" align="left">Glutamine, 3-OH-butyrate&#x2191;.<break/>Citrate, aspartate, alanine, choline, glutamate, glutarate, glycerate, and threonate&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B38">38</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (59) VS HC (28)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">UHPLC-Q-TOF-MS</td>
<td valign="top" align="left">DL-2-aminooctanoic acid, Diacylglycerol 38:5, 1-(9Zpentadecenoyl)-glycero-3-phosphate, phosphatidylcholine 36:4, 2,4-dinitrobenzenesulfonic acid, alpha-N-phenylacetyl-l-gl&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B20">20</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">United Kingdom</td>
<td valign="top" align="center">SSc (97) VS HC (10)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HPLC-FLD</td>
<td valign="top" align="left">Kynurenine&#x2191;.<break/>Tryptophan&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B39">39</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (59) VS HC (28)</td>
<td valign="top" align="center">Plasma,<break/>Urine</td>
<td valign="top" align="center">HPLC-ESI-QTOF-MS</td>
<td valign="top" align="left">Plasma:<break/>Alpha-N-phenyl acetyl-L-glutamine, Butyrylcarnitine, Valerylcarnitine, 2-4-dinitrobenzenesulfonic acid, Oleic acid, 1arachidonoylglycerol monoacylglycerol, Monoacylglycerol&#x2191;.<break/>Urine:<break/>D-Sorbitol, N-cyclohexylformamide, Ser-Pro-Pro, Dihydroxy1H-indole glucuronide, 2-(2-Phenylacetoxy)propinylglycine, Alpha-Nphenylacetyl-L glutamine, Pyroglutamic acid&#x2191;.<break/>N-Methylnicotinamide, Proline betaine, Creatinine, Vinylacetylglycine, N1-methyl-4pyridine-3-carboxamide, N1-methyl-2pyridine-5-carboxamide, Hydroxyprolyl-valine, L-beta-aspartyl-L-Leucine, Hypaphorine, 2-octanoyl-carnitine, Decatrienoylcarnitine, 2-Nonenoylcarnitine, 2,6-Dimethylheptanoyl carnitine, 9-Decenoylcarnitine, Hydroxydodecenoylcarnitine, Undecenoyl carnitine&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B48">48</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">Switzerl</td>
<td valign="top" align="center">SSc (36) VS HC (12)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">UHPLC-Q-TOF-MS</td>
<td valign="top" align="left">1-methyladenosine&#x2191;.<break/>L-tryptophan, L-tyrosine&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B43">43</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc (20) VS HC (7)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">UHPLC-Orbitrap-MS</td>
<td valign="top" align="left">Lauric acid, myristic acid, arachidic acid, carnitine, isovalerylcarnitine&#x2191;.<break/>Octanoyl-carnitine, palmitoyl-carnitine&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B54">54</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">Poland</td>
<td valign="top" align="center">SSc (42) VS HC (27)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">LC/MS</td>
<td valign="top" align="left">Glutamine, proline, 1-methylhistidine, betaine, methylnicotinamide, asymmetric dimethylarginine&#x2191;.<break/>Tryptophan&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B41">41</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2021</td>
<td valign="top" align="center">Austria</td>
<td valign="top" align="center">SSc (58) VS HC (48)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-IM-Q-TOF-MS</td>
<td valign="top" align="left">Phosphatidylcholine 34:1, 34:2, 34:3; sphingomyelin 33:1, 35:1, 35:2&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B56">56</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">2022</td>
<td valign="top" align="center">Austria</td>
<td valign="top" align="center">SSc (52) VS HC (48)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-IM-Q-TOF-MS</td>
<td valign="top" align="left">Kynurenine, dimethylarginine, citrulline, ornithine,<break/>phenylacetylglutamine, 1-methylhistidine, 3-methyl&#x2191;.<break/>Tryptophan, OH-tryptophan, alanine, lysophosphatidylcholine 22:4a, 22:4b, 20:2; sphingomyelin 34:1, 40:3&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B42">42</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">China</td>
<td valign="top" align="center">SSc (30) VS HC (30)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HILIC UHPLC-Q-TOF MS</td>
<td valign="top" align="left">Vitamin E, Alpha-N-phenylacetyl-L-glutamine, L-glutamine, L-isoleucine, phenol, 2-oxoadipic acid, 1-palmitoyl-2-hydroxy-sn, glycero-3-phosphoethanolamine, Chenodeoxycholate, Indoxyl sulfate, D-quinovose&#x2191;.<break/>Confertifoline, Azelaic acid, Vanillin, 3b-hydroxy-5-cholenoic acid, 1-stearoyl-sn-glycerol, Magnolol, Trans-dehydroandrosterone, 4-Nonylphenol, Norethindrone acetate, cis-9,10-epoxystearic acid, 16-Hydroxypalmitic acid, 2-Ethyl-2-hydroxybutyric acid, Stearic acid, Hexadecanedioic acid, Embelin, 3-Hydroxycapric acid, Androsterone sulfate, Benzenebutanoic acid, Pregnenolone sulfate, Arachidonic acid, Dodecanoic acid, Palmitic acid, myristic acid, Cholesterol 3-sulfate, Caprylic acid, Cis- (6,9,12)-linolenic acid, Alpha-ketocaproic acid&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B44">44</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">Poland</td>
<td valign="top" align="center">SSc (63) VS HC (47)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-MS</td>
<td valign="top" align="left">Trimethylamine N-oxide (TMAO) &#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B60">60</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">Poland</td>
<td valign="top" align="center">SSc (50) VS HC (30)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">ELISA</td>
<td valign="top" align="left">Markers of Intestinal Permeability: lipopolysaccharides&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B59">59</xref>)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="center">2023</td>
<td valign="top" rowspan="2" align="center">China</td>
<td valign="top" align="center">SSc baseline (127)VS HC(30)</td>
<td valign="top" rowspan="2" align="center">Serum</td>
<td valign="top" rowspan="2" align="center">HPLC-Q-TOF-MS</td>
<td valign="top" align="left">Hydroxyisocaproic acid, citric acid, isobutyric acid, phloretin 2&#x2019;-O-glucuronide, and thromboxane A2&#x2191;.<break/>5-methoxytryptophol, 12 (13)Ep-9-KODE, alpha-tocotrienol, chlorogenic acid, and cholic acid glucuronide&#x2193;.</td>
<td valign="top" rowspan="2" align="center">(<xref ref-type="bibr" rid="B45">45</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">SSc treatment (57) VS HC (30)</td>
<td valign="top" align="left">Amidosulfonic acid, L-proline, L-glutamic acid and betaine&#x2191;.<break/>Uracil, phthalic acid, guanidinosuccinic acid, and isovalerylglycine&#x2193;.</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>&#x2191; increased, &#x2193; decreased. GC-MS, Gas chromatography-mass spectrometry; HPLC-FLD, High-performance liquid chromatography with fluorescence detection; HPLC-QTRAP-MS, High-performance liquid chromatography quadrupole-linear ion trap hybrid mass spectrometry; HPLC-MS, High-performance liquid chromatography-mass spectrometry; H-NMRS and GC-MS, H-Nuclear Magnetic Resonance Spectroscopy and Gas Chromatography-Mass Spectrometry; UHPLC-Q-TOF-MS, Ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry; HPLC-ESI-QTOF-MS, High-performance liquid chromatography coupled to electrospray ionization and quadrupole time-of-flight mass spectrometry; UHPLC-Orbitrap-MS, Ultra-high-performance liquid chromatography coupled with ion trap mass spectrometry; LC/MS, liquid chromatography/mass spectrometry; HPLC-IM-Q-TOF-MS, High-performance liquid chromatography coupled to ion mobility quadrupole time-of-flight mass spectrometry; HILIC-UHPLC-Q-TOF MS, Hydrophilic Interaction Liquid Chromatography-UHPLC-Q-TOF MS; ELISA, Enzyme-Linked Immunosorbent Assay; HPLC-Q-TOF-MS, High-performance liquid chromatography quadrupole time-of-flight mass spectrometry.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Phospholipids are essential components for constructing cell and organelle membranes, and they play various cellular roles, including regulating cell shape, migration, and intercellular interactions (<xref ref-type="bibr" rid="B49">49</xref>, <xref ref-type="bibr" rid="B50">50</xref>). Phospholipid signaling pathways are highly complex, and even minor changes in phospholipid levels can significantly impact cell survival (<xref ref-type="bibr" rid="B49">49</xref>). Studies have demonstrated the involvement of phospholipids in a range of diseases, including neurodegenerative and metabolic disorders, cancer, as well as inflammatory and autoimmune conditions (<xref ref-type="bibr" rid="B49">49</xref>, <xref ref-type="bibr" rid="B51">51</xref>&#x2013;<xref ref-type="bibr" rid="B53">53</xref>). Notably, variations in serum lipid content have been observed in SSc patients, with investigations primarily focusing on plasma and serum samples. Specifically concerning carnitine and its derivatives, studies have identified heightened concentrations of short-chain carnitines (e.g., carnitine, butyrylcarnitine, and acetylcarnitine) (<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B54">54</xref>), while long-chain fatty acid (FA)-related acylcarnitines (e.g., octanoyl-carnitine, palmitoyl-carnitine) exhibit a propensity for decrease in SSc patients compared to HCs (<xref ref-type="bibr" rid="B54">54</xref>). Carnitine plays a critical role in transporting FA into mitochondria for oxidation, which is vital for cellular energy metabolism (<xref ref-type="bibr" rid="B55">55</xref>). Furthermore, acylcarnitine levels in urine samples from SSc patients are lower than those in HCs (<xref ref-type="bibr" rid="B48">48</xref>). In the realm of FA and metabolites in SSc, diversity exists with no discernible trends. Some studies indicate elevated plasma levels of specific FAs, such as saturated FAs (e.g., lauric, myristic, arachidic acids) and unsaturated Fas (<xref ref-type="bibr" rid="B54">54</xref>), while others report a decrease in myristic acid levels (<xref ref-type="bibr" rid="B44">44</xref>). Additionally, <italic>glycerolipids</italic> (e.g., diacylglycerol and monoacylglycerol) exhibit an increasing tendency (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B48">48</xref>). Glycerol phospholipids (e.g., arachidonoyl-lysophosphatidic acid, phosphatidylcholine) have demonstrated elevated levels (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B56">56</xref>, <xref ref-type="bibr" rid="B57">57</xref>), contrasting with the down-regulation of lysophosphatidylcholine and phosphatidylethanolamine (<xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B56">56</xref>). Moreover, sphingomyelin levels were noted to be elevated among SSc patients in the context of sphingolipids (<xref ref-type="bibr" rid="B56">56</xref>). In urine analyses, saccharides (e.g., D-sorbitol) were found to increase, while levels of carnitine and its derivatives showed a decrease (<xref ref-type="bibr" rid="B48">48</xref>). Collectively, these findings underscore lipid metabolism disorders as a vital metabolic pathway in the progression of SSc.</p>
<p>Regarding other metabolites and metabolic pathways in serum, reductions were observed in levels of citrate within the tricarboxylic acid cycle metabolites, glycerate in the glycolytic pathway (<xref ref-type="bibr" rid="B38">38</xref>), 2-ketoglutarate within the tricarboxylic acid cycle (<xref ref-type="bibr" rid="B40">40</xref>). Lipopolysaccharides (LPS), metabolic byproducts of bacteria, are closely linked with intestinal inflammation (<xref ref-type="bibr" rid="B58">58</xref>). The early stages of SSc are typically characterized by inflammatory changes, with the intestinal inflammatory state potentially impacting mucosal permeability. Furthermore, a cross-sectional investigation identified a significant elevation in LPS levels in the serum of early-stage SSc patients (<xref ref-type="bibr" rid="B59">59</xref>), implicating LPS in the early intestinal inflammatory state of SSc. Additionally, various other metabolites exhibited alterations, including heightened levels of 3-OH-butyrate, pyrimidine, and trimethylamine N-oxide (TMAO) (<xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B60">60</xref>) and reduced levels of choline and glutarate (<xref ref-type="bibr" rid="B44">44</xref>). Aida et&#xa0;al. discovered that estradiol upregulated fibronectin expression in human dermal fibroblasts and induced dermal fibrosis <italic>in vitro</italic> (<xref ref-type="bibr" rid="B61">61</xref>).</p>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Metabolic alterations in the clinical subtypes of SSc</title>
<p>Significant variations in metabolites exist among the clinical subtypes of SSc (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>) (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B41">41</xref>&#x2013;<xref ref-type="bibr" rid="B44">44</xref>). In terms of amino acid metabolism, patients with dcSSc exhibited notably higher levels of valine, glutamate, and lysine, alongside decreased levels of glutamine compared to lcSSc and HCs (<xref ref-type="bibr" rid="B38">38</xref>). Furthermore, derivatives linked to amino acid metabolisms, such as betaine (<xref ref-type="bibr" rid="B44">44</xref>), Kyn (<xref ref-type="bibr" rid="B42">42</xref>), 1-methylhistidine, and phenylacetyl glutamine (<xref ref-type="bibr" rid="B42">42</xref>), were elevated, while Trp levels decreased (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B42">42</xref>). Notably, the Trp/Kyn ratio was highest in dcSSc patients positive for antiribonucleoprotein antibody ARA (<xref ref-type="bibr" rid="B39">39</xref>). In terms of lipid metabolism, individuals in the dcSSc group demonstrated elevated levels of lecithin (32:0) and reduced levels of phosphatidylethanolamine (38:5, 38:6), sphingomyelin (32:2, 40:4, 30:1) (<xref ref-type="bibr" rid="B56">56</xref>) and lysophosphatidylcholine (22:4) (<xref ref-type="bibr" rid="B42">42</xref>). Organic acid metabolism analysis revealed significantly increased levels of acetic acid, fructose, glycerol, glycerophosphate, and glutaric acid in dcSSc patients (<xref ref-type="bibr" rid="B38">38</xref>), while sorbitol, glucose, and lactate levels decreased (<xref ref-type="bibr" rid="B38">38</xref>). Moreover, a noteworthy finding was the presence of the NOS inhibitor L-asymmetric dimethylarginine (L-NAME) in patients with dcSSc or capillary dilatation, potentially indicating an association with vascular endothelial dysfunction and microangiopathy (<xref ref-type="bibr" rid="B41">41</xref>). Elevated Hcy levels may contribute to endothelial injury complexity in SSc, with plasma Hcy concentrations correlating with microvascular involvement and increasing with the progression of nailfold capillaroscopy patterns (<xref ref-type="bibr" rid="B36">36</xref>), subsequently leading to pulmonary vasculopathy secondary to ILD development (<xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B46">46</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Deregulation of metabolites in SSc subtypes.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Year</th>
<th valign="top" align="center">Region</th>
<th valign="top" align="center">Subjects<break/>(n)</th>
<th valign="top" align="center">Sample type</th>
<th valign="top" align="center">Methods</th>
<th valign="top" align="center">Altered metabolites in SSc VS HC</th>
<th valign="top" align="center">References</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="top" colspan="7" align="center">dcSSc and lcSSc</th>
</tr>
<tr>
<td valign="top" align="center">2009</td>
<td valign="top" align="center">United States</td>
<td valign="top" align="center">dcSSc (7) VS lcSSc (<xref ref-type="bibr" rid="B3">3</xref>)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HPLC-QTRAP-MS</td>
<td valign="top" align="left">Sphingosine 1-phosphate&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B57">57</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">dcSSc (14) VS lcSSc (23)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">H-NMRS and GC-MS</td>
<td valign="top" align="left">Valine, acetate, fructose, glutamate, glycerol, lysine, glycerate, glutarate&#x2191;.<break/>Sorbitol, glucose, lactate, glutamine&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B38">38</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">United Kingdom</td>
<td valign="top" align="center">dcSSc (58) VS lcSSc (39)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HPLC-FLD</td>
<td valign="top" align="left">Tryptophan&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B39">39</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">dcSSc (10) VS lcSSc (43)</td>
<td valign="top" align="center">Urine</td>
<td valign="top" align="center">HPLC-ESI-QTOF-MS</td>
<td valign="top" align="left">L-arogenate, N (5-amino-2hydroxybenzoyl)glycine, Indospicine&#x2191;.<break/>3-methylglutarylcarnitine, 5-hydroxyindoleacetic acid&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B48">48</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">Poland</td>
<td valign="top" align="center">dcSSc (21) VS lcSSc (21)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">LC/MS</td>
<td valign="top" align="left">Sarcosine, beta-alanine, methylnicotinamide, N(G)nitro-L-arginine methyl ester (L-NAME)&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B41">41</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2021</td>
<td valign="top" align="center">Austria</td>
<td valign="top" align="center">dcSSc (11) VS lcSSc (39)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-IM-Q-TOF-MS</td>
<td valign="top" align="left">Phosphatidylcholine 32:0&#x2191;.<break/>Phosphatidylethanolamine 38:5, 38:6, sphingomyelin 32:2, 40:4, 30:1&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B56">56</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">2022</td>
<td valign="top" align="center">Austria</td>
<td valign="top" align="center">dcSSc (11) VS lcSSc (39)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-IM-Q-TOF-MS</td>
<td valign="top" align="left">Kynurenine, citrulline, ornithine, Phenylacetylglutamine&#x2191;.<break/>Tryptophan, lysophosphatidylcholine 22:4&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B42">42</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">China</td>
<td valign="top" align="center">dcSSc (12) VS lcSSc (18)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HILIC UHPLC-Q-TOF MS</td>
<td valign="top" align="left">Trans-dehydroandrosterone, betaine, and SOPC&#x2191;.<break/>1-palmitoyl-sn-glycero-3-phosphocholine&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B44">44</xref>)</td>
</tr>
<tr>
<th valign="top" colspan="7" align="center">SSc with ILD</th>
</tr>
<tr>
<td valign="top" align="center">2014</td>
<td valign="top" align="center">Japan</td>
<td valign="top" align="center">SSc-ILD (65) VS SSc Non-ILD (86)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-FLD</td>
<td valign="top" align="left">Homocysteine&#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B46">46</xref>)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="center">2019</td>
<td valign="top" rowspan="2" align="center">Italy</td>
<td valign="top" rowspan="2" align="center">SSc-ILD (18) VS SSc non-ILD (41)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" rowspan="2" align="center">HPLC-ESI-QTOF-MS</td>
<td valign="top" align="left">N-(1-deoxy-1-fructosyl)-Valine, N-(1-deoxy-1-fructosyl)-leucine, N-(1-deoxy-1-fructosyl)-Isoleucine&#x2191;.</td>
<td valign="top" rowspan="2" align="center">(<xref ref-type="bibr" rid="B48">48</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">Urine</td>
<td valign="top" align="left">Valyl valine, kynurenic acid, L-proline, proline-histidine, quinolinic acid, &#x3b2;-D-glucopyrapyranosil anthranilate&#x2191;.</td>
</tr>
<tr>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">Switzerland</td>
<td valign="top" align="center">Stable SSc-ILD (12) VS Progressive SSc-ILD (12)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">UHPLC-Q-TOF-MS</td>
<td valign="top" align="left">L-Leucine, L-Isoleucine, Xanthosine&#x2191;.<break/>Adenosine monophosphate&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B43">43</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">China</td>
<td valign="top" align="center">SSc-ILD (19) VS SSc non-ILD (11)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HILIC UHPLC-Q-TOF MS</td>
<td valign="top" align="left">M-Glutamine&#x2191;.<break/>Ile-Ala, Androsterone sulfate&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B44">44</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">Poland</td>
<td valign="top" align="center">SSc-ILD (47) VS SSc non-ILD (16)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-MS</td>
<td valign="top" align="left">Trimethylamine N-oxide (TMAO) &#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B60">60</xref>)</td>
</tr>
<tr>
<th valign="top" colspan="7" align="center">SSc with PAH</th>
</tr>
<tr>
<td valign="top" align="center">2016</td>
<td valign="top" align="center">Australia</td>
<td valign="top" align="center">SSc-PAH (15) VS SSc Non-PAH (30)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HPLC-FLD</td>
<td valign="top" align="left">Asymmetric dimethylarginine,<break/>symmetric dimethylarginine&#x2191;.<break/>L-Arginine&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B65">65</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">2017</td>
<td valign="top" align="center">Italy</td>
<td valign="top" align="center">SSc-PAH (8) VS SSc Non-PAH (10)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">H NMRS</td>
<td valign="top" align="left">Acetoacetate, Alanine, Lactate,<break/>VLDL, LDL&#x2191;.<break/>&#x3b3;-Aminobutyrate, arginine, betaine, choline, creatinine, glucose, glutamate, glycine, histidine, phenylalanine, tyrosine&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B62">62</xref>)</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">2023</td>
<td valign="top" rowspan="3" align="center">United States</td>
<td valign="top" align="center">PVDOMIC cohort:<break/>SSc-PAH (62) VS SSc non-PAH (19) VS HC (85)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" rowspan="3" align="center">LC-MS</td>
<td valign="top" align="left">kynurenine, N-acetylputrescine, kyn/trp and 1-methyladenosine&#x2191;.</td>
<td valign="top" rowspan="3" align="center">(<xref ref-type="bibr" rid="B64">64</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">PVDOMIC cohort:<break/>SSc-PAH (32) VS HC (12)</td>
<td valign="top" align="center">Mixed and wedged venous</td>
<td valign="top" align="left">Kynurenine and kyn/trp&#x2191;.</td>
</tr>
<tr>
<td valign="top" align="center">JHSC cohort:<break/>SSc-PAH (81) VS HC (81)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="left">Kynurenine/tryptophan (kyn/trp)&#x2191;.</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="center">2023</td>
<td valign="top" rowspan="2" align="center">United States</td>
<td valign="top" align="center">SSC-PAH (400) VS IPAH (1082)</td>
<td valign="top" rowspan="2" align="center">Plasma</td>
<td valign="top" rowspan="2" align="center">LC/MS</td>
<td valign="top" align="left">Fatty acid metabolism: Lignoceric acid fatty acyl esters of hydroxy fatty acid, nitrooleate, and Nervonic acid&#x2191;.<break/>Steroid hormones metabolism: 11-Testosterone and 17b estradiol&#x2191;.<break/>Arachidonic acid metabolism: Novel eicosanoid, prostaglandin F2a and leukotriene B4&#x2191;.</td>
<td valign="top" rowspan="2" align="center">(<xref ref-type="bibr" rid="B63">63</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">SSc-PAH (44) VS SSc no-PAH (100)</td>
<td valign="top" align="left">SSc-PAH: Fatty acyl esters of hydroxy fatty acid,<break/>nervonic acid, 17b estradiol, prostaglandin F2a,<break/>And eicosanoid&#x2191;.<break/>SSc Non-PAH: Lignoceric acid and leukotriene B4&#x2191;.</td>
</tr>
<tr>
<th valign="top" colspan="7" align="center">Autoantibodies are positive in SSc</th>
</tr>
<tr>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">United Kingdom</td>
<td valign="top" align="center">ARA + (47) VS ACA + (25) and Anti-Scl70 + (<xref ref-type="bibr" rid="B25">25</xref>)</td>
<td valign="top" align="center">Serum</td>
<td valign="top" align="center">HPLC-FLD</td>
<td valign="top" align="left">Kynurenine&#x2191;.<break/>Tryptophan&#x2193;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B39">39</xref>)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="center">2024</td>
<td valign="top" rowspan="2" align="center">Italy</td>
<td valign="top" rowspan="2" align="center">SSc (<xref ref-type="bibr" rid="B25">25</xref>)</td>
<td valign="top" align="center">Feces</td>
<td valign="top" rowspan="2" align="center">GC-MS</td>
<td valign="top" align="left">Anti-Scl70 +: propionic acid&#x2191;.<break/>ACA +: hexanoic acid&#x2191;.</td>
<td valign="top" rowspan="2" align="center">(<xref ref-type="bibr" rid="B24">24</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">Serum</td>
<td valign="top" align="left">ACA +:octanoic acids and octanoic acids&#x2191;.</td>
</tr>
<tr>
<th valign="top" colspan="7" align="center">SSc with others</th>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">2020</td>
<td valign="top" rowspan="3" align="center">Poland</td>
<td valign="top" align="center">SSc calcinosis (<xref ref-type="bibr" rid="B6">6</xref>) VS SSc non-calcinosis (<xref ref-type="bibr" rid="B36">36</xref>)</td>
<td valign="top" rowspan="3" align="center">Plasma</td>
<td valign="top" rowspan="3" align="center">LC/MS</td>
<td valign="top" align="left">Glutamate, sarcosine, proline, tyrosine,<break/>4-methylhistidine, ornithine&#x2191;.</td>
<td valign="top" rowspan="3" align="center">(<xref ref-type="bibr" rid="B41">41</xref>)</td>
</tr>
<tr>
<td valign="top" align="center">SSc JP (<xref ref-type="bibr" rid="B28">28</xref>) VS SSc non-JP (<xref ref-type="bibr" rid="B14">14</xref>)</td>
<td valign="top" align="left">Ornithine, 1-methylhistidine&#x2191;.<break/>Glutamine&#x2193;.</td>
</tr>
<tr>
<td valign="top" align="center">SSc-TE (24) VS SSc non-TE (18)</td>
<td valign="top" align="left">Glutamate, lysine, L-asymmetric dimethylarginine (NAME)&#x2191;.</td>
</tr>
<tr>
<td valign="top" align="center">2023</td>
<td valign="top" align="center">Poland</td>
<td valign="top" align="center">SSc-ED (37) VS SSc non-ED (26)</td>
<td valign="top" align="center">Plasma</td>
<td valign="top" align="center">HPLC-MS</td>
<td valign="top" align="left">TMAO &#x2191;.</td>
<td valign="top" align="center">(<xref ref-type="bibr" rid="B60">60</xref>)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>&#x2191; increased, &#x2193; decreased. dcSSc, diffused cutaneous SSc; lcSSc, limited cutaneous SSc; HPLC-QTRAP-MS, High-performance liquid chromatography quadrupole-linear ion trap hybrid mass spectrometry; H-NMRS and GC-MS, H-Nuclear Magnetic Resonance Spectroscopy and Gas Chromatography-Mass Spectrometry; HPLC-FLD, High-performance liquid chromatography with fluorescence detection; HPLC-ESI-QTOF-MS, High-performance liquid chromatography coupled to electrospray ionization and quadrupole time-of-flight mass spectrometry; LC/MS, liquid chromatography/mass spectrometry; LC/MS, liquid chromatography/mass spectrometry; HPLC-IM-Q-TOF-MS, High-performance liquid chromatography coupled to ion mobility quadrupole time-of-flight mass spectrometry; HILIC-UHPLC-Q-TOF MS, Hydrophilic Interaction Liquid Chromatography-Ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry; SOPC, 1-stearoyl-2-oleoyl-sn-glycerol 3-phosphocholine; ILD, interstitial lung disease; HPLC-MS, High-performance liquid chromatography-mass spectrometry; PAH, pulmonary arterial hypertension; H NMRS, proton nuclear magnetic resonance spectrometry; VLDL, very-low-density lipoprotein; LDL, low-density lopoprotein; PVDOMI, pulmonary vascular disease phenomics; JHSC, JohnsHopkins Scleroderma Center; IPAH, idiopathic pulmonary arterial hypertension; JP, joint pain; TE, telangiectasia.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>In recent years, researchers have shifted their focus towards exploring the metabolic profile of SSc patients with pulmonary complications, offering new insights into the diagnosis and management of the disease. Within ILD patients, notable alterations in amino acid metabolism are observed. Contrasting with non-ILD patients, those with ILD exhibit elevated levels of specific amino acids (including Hcy, arginine, and valine) and fructosamine derived from branched-chain amino acids, while glycerophosphoethanolamine (e.g., phosphatidylethanolamine 36:3, 38:5, 38:6) and steroids (such as androstenolone 3-sulphate) are reduced (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B56">56</xref>). Moreover, a study distinguishing stable from progressive SSc-ILD patients revealed that metabolite levels like L-leucine, L-isoleucine, xanthine, and adenosine monophosphate could potentially serve as biomarkers to differentiate between the two phenotypes (<xref ref-type="bibr" rid="B43">43</xref>), offering additional insights into SSc-ILD biomarkers. Sun et&#xa0;al. further supported that glutamine metabolism stands out as a major metabolic pathway in SSc-ILD patients (<xref ref-type="bibr" rid="B44">44</xref>). Notably, proinflammatory metabolites like TMAO were significantly elevated in SSc-ILD patients with esophageal motility dysfunction, with a notable correlation between TMAO concentrations, N-terminal precursor brain natriuretic peptide (a cardiac involvement marker), and ILD severity (<xref ref-type="bibr" rid="B60">60</xref>). Amino acid levels such as valine, kynurenine, L-proline, and proline-histidine were also found to be higher in urine samples from ILD patients compared to those without ILD (<xref ref-type="bibr" rid="B48">48</xref>).</p>
<p>In patients with SSc-PAH, metabolic abnormalities likely play a pivotal role in the pathophysiology of PAH. Compared to SSc patients without PAH, those with PAH demonstrate increased levels of specific amino acids and their derivatives (e.g., alanine), lipids (e.g., very-low-density lipoprotein, low-density lipoprotein), and lactic acid. Conversely, there is a reduction in levels of other amino acids and their derivatives (e.g., &#x3b3;-amino-butyric acid, arginine, phenylalanine, tyrosine, histidine, glycine, glutamate, glutamine, betaine), as well as choline, creatine, and glucose (<xref ref-type="bibr" rid="B62">62</xref>). When compared with patients with Idiopathic Pulmonary Arterial Hypertension (IPAH), individuals with SSc-PAH exhibit significantly higher levels of fatty acid metabolism (e.g., lignoceric acid, nervonic acid), steroid hormone metabolism (11-testosterone and 17&#x3b2; estradiol), and arachidonic acid metabolism (novel classes of eicosanoids, prostaglandins F2&#x3b1;, and leukotriene B4), indicating distinct metabolic profiles between the two conditions (<xref ref-type="bibr" rid="B63">63</xref>). Various studies have consistently demonstrated lowered Trp levels in SSc patients (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B41">41</xref>&#x2013;<xref ref-type="bibr" rid="B43">43</xref>). Additionally, a study by Simpson et&#xa0;al. revealed significantly elevated levels of Kyn and Kyn/Trp ratio in wedge veins compared to mixed vein samples from SSc-PAH patients (<xref ref-type="bibr" rid="B64">64</xref>), hinting at the potential involvement of the Kyn pathway metabolism in PAH development. Moreover, elevated levels of L-NAME and decreased levels of L-arginine in SSc-PAH patients compared to those with SSc alone suggest impaired vasodilation functions (<xref ref-type="bibr" rid="B65">65</xref>), potentially contributing to PAH development. Given that L-arginine serves as a precursor to NO, its reduction might exacerbate NO deficiency, impacting vascular tone and blood flow. These metabolites seem closely linked to the pathophysiological mechanisms of SSc-PAH. Notably, significant differences in Hcy concentrations have been observed in SSc patients with macrovascular issues and thromboembolic events (<xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B47">47</xref>). Elevated plasma Hcy levels (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>) in SSc patients are associated with complications like vascular embolic events, PAH, finger ulcers, limb osteolysis, and ILD (<xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B47">47</xref>). Elevated Hcy levels in the context of SSc could potentially serve as a serum marker for the disease.</p>
<p>There is limited data on metabolite studies related to autoantibody positivity in SSc. In a plasma sample analysis, elevated levels of Kyn and decreased levels of Trp were observed in patients positive for ARA compared to those with ACA and anti-Scl70 antibodies (<xref ref-type="bibr" rid="B39">39</xref>). This finding suggests a potential influence of Kyn and its metabolites on B lymphocyte differentiation and activation, contributing to the immunomodulatory processes in SSc. A comprehensive review of the Kyn and Kyn/Trp levels in different SSc subtypes revealed heightened concentrations in SSc-associated PAH, dcSSc, and ARA subtypes (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B64">64</xref>), indicating that these metabolites from the Kyn/Trp pathway could serve as biomarkers for early disease detection and stratification, particularly in vascular-associated SSc lesions. Moreover, Russo et&#xa0;al. highlighted that patients positive for anti-Scl-70 antibodies presented increased levels of propionic acid in fecal samples, while ACA-positive patients exhibited elevated hexanoic acid levels in their fecal samples. Plasma valeric acid levels tended to be higher in ACA-positive patients (<xref ref-type="bibr" rid="B24">24</xref>). In other subtypes of SSc, a plasma sample analysis revealed elevated levels of glutamate, sarcosine, proline, tyrosine, 4-methylhistidine, and ornithine in patients with SSc-associated calcinosis. Conversely, patients experiencing SSc joint pain had increased ornithine and 1-methylhistidine levels but decreased glutamine levels (<xref ref-type="bibr" rid="B41">41</xref>). Collectively, these findings suggest that the observed metabolite abnormalities in SSc patients may be linked to autoimmune dysregulations in SSc.</p>
</sec>
</sec>
<sec id="s4">
<label>4</label>
<title>Association of GM and metabolites in SSc and potential molecular mechanisms</title>
<p>Exploring the involvement of GM and their metabolites in the development of skin and lung complications in SSc has recently advanced through proposed mechanisms like the gut-skin axis (<xref ref-type="bibr" rid="B66">66</xref>, <xref ref-type="bibr" rid="B67">67</xref>) and the gut-lung axis (<xref ref-type="bibr" rid="B68">68</xref>, <xref ref-type="bibr" rid="B69">69</xref>). Despite these advances, the precise mechanisms of action remain ambiguous. In this context, we address the specific or potential metabolic interactions between gut flora and SSc, drawing from existing literature evidence.</p>
<sec id="s4_1">
<label>4.1</label>
<title>Association of GM with Trp metabolism</title>
<p>Within the extensive investigations on amino acid metabolism, notable changes in Trp metabolism emerge, characterized by reduced Trp levels in SSc patients (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B41">41</xref>&#x2013;<xref ref-type="bibr" rid="B43">43</xref>). Trp, an indispensable aromatic amino acid, holds significance as a biosynthetic precursor for a myriad of microbial and host metabolites despite being the least abundant amino acid in proteins and cells (<xref ref-type="bibr" rid="B70">70</xref>). In the GIT, Trp metabolism encompasses three primary pathways (<xref ref-type="bibr" rid="B71">71</xref>) (<xref ref-type="bibr" rid="B1">1</xref>): direct conversion by gut microbes into molecules like aryl hydrocarbon receptor (AhR) ligands (<xref ref-type="bibr" rid="B2">2</xref>); catalytic conversion to Kyn by indoleamine 2,3-dioxygenase (IDO) 1 in immune and epithelial cells (<xref ref-type="bibr" rid="B3">3</xref>); transformation into 5-hydroxytryptamine by Trp hydroxylase 1 in enterochromaffin cells. This metabolic cascade yields various bioactive compounds that modulate key physiological functions spanning inflammation, metabolism, immune response, and neurological activity (<xref ref-type="bibr" rid="B72">72</xref>). Notably, elevated levels of Kyn and Kyn/Trp are observed in specific SSc subtypes, including SSc-PAH, dcSSc, and ARA-positive isoforms (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B64">64</xref>). The involvement of the Kyn pathway and its metabolites in inhibiting T-cell proliferation and inducing T-cell apoptosis has been underscored (<xref ref-type="bibr" rid="B73">73</xref>, <xref ref-type="bibr" rid="B74">74</xref>). Most microbiota, aside from viruses and archaea, metabolize Trp through diverse pathways to produce bioactive compounds (<xref ref-type="bibr" rid="B75">75</xref>, <xref ref-type="bibr" rid="B76">76</xref>). Montgomery et&#xa0;al. identified that the gut commensal Lactobacillus reuteri metabolizes Trp to generate various derivatives, activating AhR and potentially enhancing the T-cell response to produce IL-17, thereby regulating autoimmunity (<xref ref-type="bibr" rid="B77">77</xref>). Additionally, commensal bacteria may combat viral infections by AhR activation (<xref ref-type="bibr" rid="B78">78</xref>). A synthesis of existing literature highlights that several commensal bacteria exhibit anomalies in SSc patients, with Lactobacillus showing elevated relative abundance (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B29">29</xref>), suggesting that intestinal commensals could influence the immune system in SSc by modulating host Trp production and its metabolites, thereby eliciting diverse responses in epithelial and immune cell populations.</p>
</sec>
<sec id="s4_2">
<label>4.2</label>
<title>Association of GM with lipid metabolism</title>
<p>While previous studies on the GM-metabolome co-axis have predominantly explored water-soluble, polar metabolites like Trp catabolic metabolites and amino acids, the microbial-host-lipid co-axis has not received adequate attention. In SSc, the relationship between GM and lipid metabolism is variably interconnected. Ottria et&#xa0;al. conducted experiments applying etoposide, a carnitine transporter protein inhibitor, to incubated dendritic cells (DCs) from healthy individuals and those with SSc, revealing inhibition of proinflammatory cytokine production through the suppression of fatty acid oxidation. This suggests a potential role of fatty acids in augmenting inflammation in SSc patients (<xref ref-type="bibr" rid="B54">54</xref>). Current emerging evidence highlights the involvement of lipids in autoimmune diseases and IBD (<xref ref-type="bibr" rid="B79">79</xref>). Recent research indicates the significance of intestinal commensal bacteria, such as Bacteroides, in sphingolipid production for maintaining intestinal homeostasis and symbiosis (<xref ref-type="bibr" rid="B80">80</xref>). Furthermore, the Lactobacillus genus appears to be closely associated with fatty acyls (<xref ref-type="bibr" rid="B81">81</xref>&#x2013;<xref ref-type="bibr" rid="B83">83</xref>). Conversely, commensal genera believed to possess anti-inflammatory properties, such as Bacteroides, demonstrate reduced relative abundance in SSc (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B31">31</xref>). Additionally, commensal genera recognized for their anti-inflammatory effects, like Anabaena spp., also exhibit diminished relative abundance in SSc.</p>
<p>Butyrate, a short-chain fatty acid (SCFA), serves as a crucial energy source for intestinal epithelial cells, bolsters various components of the colonic defense barrier, reduces oxidative stress, and exerts anti-inflammatory and immunomodulatory effects (<xref ref-type="bibr" rid="B84">84</xref>). Studies have consistently highlighted the significant role of SCFAs in lung disease by inhibiting the histone deacetylase enzyme and&#xa0;maintaining intrapulmonary homeostasis (<xref ref-type="bibr" rid="B85">85</xref>). Butyrate, propionate, and acetate collectively regulate intrapulmonary homeostasis and immunity (<xref ref-type="bibr" rid="B86">86</xref>, <xref ref-type="bibr" rid="B87">87</xref>). Faecalibacterium and Clostridium are prevalent in the GIT of healthy individuals, fortifying the epithelial barrier through butyrate production and aiding in mucosal inflammation regulation. Yet, the occurrence of these beneficial commensal genera is reduced in SSc. Several investigations emphasize the decline of butyrate-producing commensal bacteria in both SSc and IgG4-RD contexts (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B31">31</xref>). Studies confirm that Desulfovibrio, a pathogenic bacterium linked to intestinal dysregulation in SSc, induces inflammatory responses in the ileum and colon (<xref ref-type="bibr" rid="B88">88</xref>, <xref ref-type="bibr" rid="B89">89</xref>). Desulfovibrio interacts with amino acid metabolism and glycerophospholipids, forming heterodimers with SCFAs such as butyrate and ultimately contributing to intestinal dysregulation and inflammation (<xref ref-type="bibr" rid="B20">20</xref>). Pathogenic bacteria-mediated host pathophysiology is driven not only by the production of harmful metabolites but also by a reduction in beneficial metabolites. Patients with SSc exhibit elevated levels of pro-inflammatory bacteria like Desulfovibrio and reduced levels of protective butyrate, indicating a disturbance in the balance of GM (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B31">31</xref>). Consequently, the GM in SSc may impact the host&#x2019;s immune response by influencing SCFA metabolism, particularly the butyrate pathway, thereby exacerbating inflammatory and fibrotic processes.</p>
</sec>
<sec id="s4_3">
<label>4.3</label>
<title>The potential molecular mechanisms of GM and metabolites in SSc</title>
<p>SSc is characterized by three primary pathogenic mechanisms: microvascular damage, immune dysregulation, and multiorgan fibrosis. T-cell subsets play a crucial role in maintaining protective immunity against pathogens while regulating inflammatory responses to self and microbial antigens. Guided by environmental cues and antigen-presenting cells, CD4<sup>+</sup> T helper (Th) cells differentiate into distinct subsets like Th1, Th2, Th17, and regulatory T cells (<xref ref-type="bibr" rid="B90">90</xref>). The equilibrium of these cell populations, particularly the Th17/Treg balance, is pivotal in the transition from homeostasis to disease and is significantly shaped by the GM (<xref ref-type="bibr" rid="B91">91</xref>, <xref ref-type="bibr" rid="B92">92</xref>). Disruption of the GM can disturb the intricate balance between microbiota and the immune system, leading to inflammation and fibrosis and potentially contributing to the development and progression of SSc. Fibrosis, a complex pathological process, involves the abnormal accumulation of extracellular matrix (ECM) components post-tissue damage (<xref ref-type="bibr" rid="B93">93</xref>). An imbalance in the GM can result in the accumulation of harmful compounds and depletion of beneficial substances such as SCFAs (<xref ref-type="bibr" rid="B94">94</xref>, <xref ref-type="bibr" rid="B95">95</xref>). This dysbiosis is often associated with compromised intestinal barrier integrity, facilitating the translocation of bacteria and their byproducts into the bloodstream, triggering systemic immune and inflammatory responses that may lead to tissue damage, either directly or indirectly (<xref ref-type="bibr" rid="B96">96</xref>).</p>
<p>Chronic inflammation is recognized as the primary trigger of intestinal fibrosis. Prolonged exposure to chronic inflammatory stimuli induces the activation and proliferation of mesenchymal cells (e.g., fibroblasts, myofibroblasts, or smooth muscle cells) to produce ECM, ultimately leading to fibrosis. PF is a common complication and a poor prognostic indicator in advanced stages of SSc-ILD. PF is primarily marked by lung inflammation and excessive ECM deposition, resulting in structural alterations in lung tissue, such as thickening and scarring of the lung parenchyma, particularly concentrated in the interstitium (<xref ref-type="bibr" rid="B97">97</xref>). Recent research has shed light on the existence of a bidirectional gut-lung axis (<xref ref-type="bibr" rid="B68">68</xref>, <xref ref-type="bibr" rid="B69">69</xref>), where microorganisms (<xref ref-type="bibr" rid="B98">98</xref>&#x2013;<xref ref-type="bibr" rid="B100">100</xref>), immune functions (<xref ref-type="bibr" rid="B98">98</xref>, <xref ref-type="bibr" rid="B101">101</xref>, <xref ref-type="bibr" rid="B102">102</xref>), and metabolites (<xref ref-type="bibr" rid="B69">69</xref>, <xref ref-type="bibr" rid="B102">102</xref>) are exchanged through the blood and lymphatic system, influencing the pathophysiological processes of the disease. Although in-depth studies on the gut-lung axis in SSc are limited, evidence suggests that various intestinal microbial metabolites, such as amino acids, SCFAs, and bile acids, can impact fibroblasts, myofibroblasts, extracellular matrix accumulation, immune regulation, and other pathways, potentially contributing to ILD or PF (<xref ref-type="bibr" rid="B103">103</xref>). Amino acids are prevalent intestinal metabolites in SSc patients, including compounds like arginine (<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B62">62</xref>) and glutamine (<xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B44">44</xref>). Arginine, in particular, has been implicated in collagen deposition, apoptosis, and ammonia elimination in individuals with idiopathic PF (IPF). Cellular experiments have shown that glutamine contributes to apoptosis resistance in lung fibroblasts derived from IPF patients. Reduced glutamine metabolism increases the susceptibility of IPF fibroblasts to Fas ligand (FasL)-induced apoptosis, downregulates the expression of anti-apoptotic genes, and induces epigenetic changes in these cells (<xref ref-type="bibr" rid="B104">104</xref>). The gut-lung axis involves multiple pathways of immune communication. For example, SCFAs and amino acids circulate through the bloodstreams activating bone marrow-derived immune cells, which subsequently influence immune cell development and trigger immune responses in the lungs. Additionally, innate lymphocytes 2/3 (ILC 2/3) and Th 17 cells may migrate from the gut to the lung, impacting pulmonary immune responses (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>) (<xref ref-type="bibr" rid="B105">105</xref>&#x2013;<xref ref-type="bibr" rid="B107">107</xref>). This emerging perspective on the gut-lung axis offers valuable insights into the cellular mechanisms underlying PF and provides a novel framework for studying the pathogenesis of SSc-ILD.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Potential mechanisms of the gut-lung axis and gut-skin axis in SSc (created by figdraw). 1. gut-lung axis: (i) Microbial metabolites, such as SCFAs and amino acids (AAs), enter the bloodstream and influence the development of immune cells; (ii) Activation of bone marrow-derived immune cells triggers immune responses in the lungs; (iii) Cells migrating from the gut, including innate lymphoid cells 2/3 (ILC2/3) and Th17 cells, can affect pulmonary immunity by migrating to the lungs; and (iv) hence, microorganisms and metabolites influence the course of pulmonary fibrosis through the intermediate link of immune disorders. 2. gut-skin axis: <bold>(A)</bold> Gut microbes and metabolites alter immune cells (e.g., impairing T cell differentiation and promoting B cell hyperresponsiveness), which in turn affect skin disorders through circulation; <bold>(B)</bold> SCFAs upregulate DCs and enhance the production of IL-6, IFN, and tumor necrosis factor (TNF); <bold>(C)</bold> The combined effects of A and B leads to skin lesions in SSc through the induction of oxidative stress, inflammatory response, disruption of immune homeostasis, and inhibition of ECM remodeling. DCs: dendritic cells.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1475528-g001.tif"/>
</fig>
<p>Furthermore, a similar bidirectional relationship is observed between the gut and skin, referred to as the gut-skin axis. Skin and gut both are active, complex immunological and neuroendocrine organs, impairment of the intestinal barrier permits the passage of intestinal microbiota and metabolites into the bloodstream, affecting autoimmune responses and inflammatory conditions in skin (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B67">67</xref>). Communication between the gut and skin occurs through immune cross-talk. Dysbiotic gut microbes, toxic products, neurotransmitters, and altered immune cells, including impaired T cell differentiation and hyperresponsive B cells, circulate through the bloodstream, contributing to dysbiotic skin conditions (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>) (<xref ref-type="bibr" rid="B108">108</xref>). SCFAs, as metabolic by-products, can upregulate DCs and enhance the production of proinflammatory cytokines, which in turn trigger an inflammatory response (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1B</bold>
</xref>). Probiotics, including <italic>Nitrobacter</italic>, <italic>Lactobacillus</italic>, and <italic>Bifidobacterium</italic>, help restore intestinal homeostasis by correcting imbalances in the gut microbiota and repairing damage to the intestinal mucosal barrier (<xref ref-type="bibr" rid="B109">109</xref>). These probiotics can improve skin diseases by inhibiting oxidative stress, reducing inflammatory responses, and restoring immune homeostasis, as well as modulating ECM remodeling (<xref ref-type="bibr" rid="B108">108</xref>, <xref ref-type="bibr" rid="B110">110</xref>). Thus, the regulation of skin conditions via the gut-skin axis may involve mechanisms such as the inhibition of oxidative stress, suppression of inflammatory responses, restoration of immune homeostasis, and inhibition of ECM remodeling (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1C</bold>
</xref>). Numerous studies have demonstrated that disruptions in the gut microbiota can contribute to the development of various skin diseases, such as atopic dermatitis (<xref ref-type="bibr" rid="B111">111</xref>) and psoriasis (<xref ref-type="bibr" rid="B112">112</xref>, <xref ref-type="bibr" rid="B113">113</xref>). The gut-skin microbiome axis may also play a role in systemic autoimmune diseases, with studies suggesting that skin commensals are implicated in systemic lupus erythematosus (<xref ref-type="bibr" rid="B114">114</xref>). Recent findings by E. Russo et&#xa0;al. suggest that specific circulating autoantibodies may guide the differential dynamics of the gut-skin microbiota axis in SSc subsets. Notably, ACA-positive and anti-Scl70-positive patients exhibit distinct microbial signatures in both affected skin and gut regions, along with differing profiles of serum and fecal free fatty acids (<xref ref-type="bibr" rid="B24">24</xref>). This accumulating evidence underscores the significant impact of gut dysbiosis and metabolic disruptions in the progression of fibrosis in the skin, gut, and lungs in SSc (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Potential mechanisms of the gut microbiota and its metabolism in SSc (created by figdraw). In SSc, gut dysbiosis can compromise the integrity of the intestinal barrier, leading to increased intestinal permeability. Consequently, this breach permits the entry of abnormal metabolites (e.g., kynurenine, etc.) and other contents from the gut lumen into the bloodstream. This influx, facilitated by the intestinal-skin/lung axis pathway, has the potential to exacerbate autoimmune disorders and inflammation, culminating in damage to target organs like the skin, intestines, and lungs. DCs: dendritic cells.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1475528-g002.tif"/>
</fig>
</sec>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion and prospects</title>
<p>In conclusion, GM and metabolism display diverse abnormalities in SSc and are linked to symptoms and disease subtypes. Nevertheless, there is a paucity of definitive studies regarding the significance of pathogenic or probiotic bacteria and their metabolites in SSc. The interplay among microbiota, metabolites, and the immune system may act as a potential triggering factor, influencing the overall health of the host through pathways such as the gut-skin and gut-lung axis. Despite encountering challenges, the integration of multi-omics for SSc analysis holds significant promise. The successful merging of macro-genomics and metabolomics has revealed insights into the relationship between gene regulation, microbes, and metabolism within the microbiome, although additional validation studies are required. Integrated multi-omics data analysis provides a more comprehensive understanding of DNA identification and metabolite functions in the microbiome, thus enhancing the informative value of microbial research in SSc.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="author-contributions">
<title>Author contributions</title>
<p>QY: Conceptualization, Data curation, Validation, Writing &#x2013; original draft, Formal analysis, Methodology. WT: Conceptualization, Resources, Supervision, Validation, Writing &#x2013; review &amp; editing. FB: Conceptualization, Formal analysis, Funding acquisition, Methodology, Resources, Writing &#x2013; review &amp; editing, Validation.</p>
</sec>
<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 work was supported by National Clinical Key Speciality Capacity Building Project (No. 202330), Hainan Province Clinical Medical Center (No. 2021818), the specific research fund of The Innovation Platform for Academicians of Hainan Province (YSPTZX202313), Joint Project on Health Science and Technology Innovation in Hainan Province (WSJK2024MS150), and Hainan Provincial Postgraduate Innovation Research Project (Qhyb2022-133), Hainan Province Education Reform Project(hnjg2024-67).</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>
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