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<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
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<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
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<issn pub-type="epub">1664-3224</issn>
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<article-id pub-id-type="doi">10.3389/fimmu.2025.1665585</article-id>
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<subj-group subj-group-type="heading">
<subject>Original Research</subject>
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<title-group>
<article-title>Altered acetate metabolism and signaling in IgA nephropathy: an integrated gut microbiome and glomerular spatial transcriptome analysis</article-title>
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<name><surname>Koh</surname><given-names>Jung Hun</given-names></name>
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<xref ref-type="aff" rid="aff8"><sup>8</sup></xref>
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<aff id="aff1"><label>1</label><institution>Department of Internal Medicine, Seoul National University Hospital</institution>, <city>Seoul</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<aff id="aff2"><label>2</label><institution>Department of Internal Medicine, Seoul National University College of Medicine</institution>, <city>Seoul</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<aff id="aff3"><label>3</label><institution>Department of Biomedical Sciences, Seoul National University Graduate School</institution>, <city>Seoul</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<aff id="aff4"><label>4</label><institution>Department of Internal Medicine, Kangwon National University Hospital</institution>, <city>Chuncheon</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<aff id="aff5"><label>5</label><institution>Department of Internal Medicine, Dongguk University Ilsan Hospital</institution>, <city>Ilsan</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<aff id="aff6"><label>6</label><institution>Department of Internal Medicine, Chungbuk National University Hospital</institution>, <city>Cheongju</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<aff id="aff7"><label>7</label><institution>Department of Internal Medicine, Korea University Guro Hospital</institution>, <city>Seoul</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<aff id="aff8"><label>8</label><institution>College of Pharmacy, Natural Products Research Institute, Seoul National University</institution>, <city>Seoul</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<aff id="aff9"><label>9</label><institution>Department of Pathology, Seoul National University College of Medicine</institution>, <city>Seoul</city>,&#xa0;<country country="check-value">Republic of Korea</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Hajeong Lee, <email xlink:href="mailto:mdhjlee9@snu.ac.kr">mdhjlee9@snu.ac.kr</email></corresp>
<fn fn-type="other" id="fn003">
<label>&#x2020;</label>
<p>These authors share first authorship</p></fn>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-14">
<day>14</day>
<month>01</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1665585</elocation-id>
<history>
<date date-type="received">
<day>14</day>
<month>07</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>18</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>04</day>
<month>11</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Koh, Park, Kang, Park, Lee, Cho, Kim, Nam, Kim, Li, Park, Moon, Kim, Kim, Kim and Lee.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Koh, Park, Kang, Park, Lee, Cho, Kim, Nam, Kim, Li, Park, Moon, Kim, Kim, Kim and Lee</copyright-holder>
<license>
<ali:license_ref start_date="2026-01-14">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. 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.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>IgA nephropathy (IgAN) is the most common primary glomerulonephritis, and emerging evidence implicates the gut microbiome in its pathogenesis. Additional studies focusing on the molecular mechanisms linking gut microbial signals to intraglomerular changes are warranted.</p>
</sec>
<sec>
<title>Methods</title>
<p>We performed 16S rRNA-based microbial profiling of fecal samples of 172 IgAN patients, 51 healthy controls, and other glomerular disease controls including 15 diabetic nephropathy, 35 minimal change disease, and 63 membranous nephropathy cases. Serum and fecal acetate levels were measured by liquid chromatography&#x2013;mass spectrometry. Glomerular spatial transcriptomic profiling was performed with the GeoMx Digital Spatial Profiler. DESeq2 analysis was performed to identify differentially expressed genes, followed by gene ontology annotations.</p>
</sec>
<sec>
<title>Results</title>
<p>Beta diversity differed significantly between IgAN and healthy controls (<italic>p</italic> =&#xa0;0.001). While no single taxon showed consistent differences in abundance, the methanogenesis from acetate pathway was significantly enriched in IgAN, accompanied by an increased proportion of major acetate-producing gut microbial genera. Serum acetate levels were elevated in IgAN (<italic>p</italic> =&#xa0;0.03), while fecal acetate levels were comparable to those in healthy controls. In glomerular transcriptomes, functional annotations of 1,227 upregulated and 1,078 downregulated genes in IgAN indicated decreased activities of G protein-coupled receptors, short-chain fatty acid transporters, and beta-1,3-galactosyltransferases.</p>
</sec>
<sec>
<title>Discussion</title>
<p>IgAN is characterized by gut microbial enrichment in acetate metabolism and increased systemic acetate levels, along with altered intraglomerular expression of metabolic and signaling genes. These findings suggest a gut microbiome&#x2013;glomerular signaling axis contributing to disease pathogenesis.</p>
</sec>
</abstract>
<kwd-group>
<kwd>glomerulonephritis</kwd>
<kwd>gut microbiome</kwd>
<kwd>IgA nephropathy</kwd>
<kwd>short-chain fatty acid</kwd>
<kwd>spatial transcriptomics</kwd>
</kwd-group>
<funding-group>
<award-group id="gs1">
<funding-source id="sp1">
<institution-wrap>
<institution>National Research Foundation of Korea</institution>
<institution-id institution-id-type="doi" vocab="open-funder-registry" vocab-identifier="10.13039/open_funder_registry">10.13039/501100003725</institution-id>
</institution-wrap>
</funding-source>
<award-id rid="sp1">RS-2019-NR039661, RS-2022-NR070373, RS-2023-00219548, RS-2024-00345867</award-id>
</award-group>
<award-group id="gs2">
<funding-source id="sp2">
<institution-wrap>
<institution>Korea Health Industry Development Institute</institution>
<institution-id institution-id-type="doi" vocab="open-funder-registry" vocab-identifier="10.13039/open_funder_registry">10.13039/501100003710</institution-id>
</institution-wrap>
</funding-source>
</award-group>
<funding-statement>The author(s) declared that financial support was received for work and/or its publication. This research was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and Future Planning (grant numbers RS-2019-NR039661, RS-2022-NR070373, RS-2023-00219548, and RS-2024-00345867). This research was also supported by a grant of the Korea Health Technology R&amp;D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health &amp; Welfare, Republic of Korea (grant number: RS-2024-00403375).</funding-statement>
</funding-group>
<counts>
<fig-count count="4"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="76"/>
<page-count count="15"/>
<word-count count="6810"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Mucosal Immunity</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Kidney diseases, spanning a broad spectrum of etiologies, are a growing health concern worldwide (<xref ref-type="bibr" rid="B1">1</xref>). Beyond traditional risk factors, gut microbial dysbiosis has been increasingly implicated in their pathophysiology (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B3">3</xref>). Alterations in gut microbial composition and related metabolite profiles have been reported in chronic kidney disease (CKD) and in specific glomerular diseases (<xref ref-type="bibr" rid="B4">4</xref>&#x2013;<xref ref-type="bibr" rid="B6">6</xref>), with associations to systemic consequences such as cardiorenal syndrome and mineral bone disorder (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B8">8</xref>). The crosstalk between the gut microbiota and the kidney, dubbed the gut-kidney axis, involves multiple mediators including microbe-derived uremic toxins and other amino acid derivatives (<xref ref-type="bibr" rid="B9">9</xref>&#x2013;<xref ref-type="bibr" rid="B11">11</xref>), whose causal associations to glomerular diseases were demonstrated by recent Mendelian randomization studies (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>). Together, a growing body of evidence indicates a key role of intestinal dysbiosis and metabolite imbalance across kidney diseases.</p>
<p>Immunoglobulin A (IgA) nephropathy (IgAN), the most prevalent primary glomerulonephritis worldwide, is closely connected to the gut microbiota in its immune-mediated pathophysiology. Central to its pathogenesis is the overproduction of galactose deficient-IgA1 (Gd-IgA1) and associated immune complexes (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>). Given the established role of IgA in mucosal immunity, host-microbiota interactions in mucosa-associated lymphoid tissues have been proposed as a key driver of Gd-IgA1 production (<xref ref-type="bibr" rid="B13">13</xref>). Supporting this concept, genome-wide association studies have also suggested genetic associations between IgAN and mucosal immune pathways including those related to microbial sensing and response (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>). These findings have motivated the introduction of tonsillectomy and enteric budesonide as therapeutic options (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>), and efforts are underway to utilize microbiota-modulating therapies including probiotics and fecal microbiota transplantation (<xref ref-type="bibr" rid="B19">19</xref>).</p>
<p>Nevertheless, the development of IgAN requires additional components, as described by the &#x201c;multi-hit&#x201d; model (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B20">20</xref>). Mesangial cells actively contribute by binding IgA1 and driving proliferative signals (<xref ref-type="bibr" rid="B21">21</xref>). B cells play a pivotal role in producing Gd-IgA1 as well as autoantibodies against Gd-IgA1, although relatively little is known about their activation and potential interactions with the kidney glomeruli in IgAN (<xref ref-type="bibr" rid="B22">22</xref>). Unraveling the crosstalk among the gut microbiota, mucosal and systemic immune systems, and the kidney as a target organ is therefore critical for developing additional therapeutic strategies.</p>
<p>Data-driven, multi-omics approaches have the potential to yield novel insights into the complex pathophysiology of IgAN. Advances in high-throughput sequencing techniques have enabled comparative analyses of tonsillar or gut microbiome in patients with IgAN versus healthy or disease controls (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B23">23</xref>&#x2013;<xref ref-type="bibr" rid="B25">25</xref>). However, reported taxonomic differences varied among studies, and their functional relevance remains largely unclear. Spatial transcriptomics represent another key advancement, allowing for substructure-specific profiling of gene expression in elaborately organized structures like the nephron (<xref ref-type="bibr" rid="B26">26</xref>). We previously explored human IgAN-specific glomerular transcriptomic changes to uncover proinflammatory signals associated with mesangial proliferation preceding overt morphologic changes (<xref ref-type="bibr" rid="B27">27</xref>).</p>
<p>In this study, we performed 16S rRNA-based gut microbiome profiling integrated with Nanostring GeoMx-based glomerular spatial transcriptomics to characterize the molecular signature of IgAN. Comparisons with healthy controls and other glomerular disease patients enabled identification of specific changes in both the gut microbiome and the glomerular transcriptome. Specifically, IgAN showed gut microbial alterations in short-chain fatty acid (SCFA) metabolism, particularly acetate, along with glomerular transcriptional changes in SCFA transporters and G protein-coupled receptors (GPCRs). Together, these findings suggest a previously underappreciated axis of gut microbial metabolites and impaired renal sensing via GPCR downregulation, offering a potential channel for the gut-kidney interaction in IgAN.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Ethics approval</title>
<p>This study was conducted in accordance with the Declaration of Helsinki, and ethical approval was granted by the Institutional Review Board (IRB) of Seoul National University Hospital (SNUH) for gut microbiome analysis (IRB No. 2205-104-1325) and spatial transcriptomic profiling (IRB No. 2205-085-1324). Written informed consent was obtained from all patients included in the study prior to collection of any samples or clinical information.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Participant cohorts and biospecimen acquisition</title>
<p>For gut microbial analysis, stool samples were sourced from the KOrea Renal biobank NEtwoRk System TOward Next-generation analysis (KORNERSTONE) repository (<xref ref-type="bibr" rid="B28">28</xref>). Biopsy-proven cases of IgAN and other common glomerular diseases, namely diabetic nephropathy (DN), minimal change disease (MCD), and membranous nephropathy (MN), were included. In addition, stool samples from consenting live kidney donors at SNUH were included as healthy controls. The following inclusion criteria were applied: (1) age &#x2265;18 years, (2) estimated glomerular filtration rate (eGFR) &#x2265;60 mL/min/1.73 m<sup>2</sup> to minimize the potential confounding from uremic metabolites we previously observed (<xref ref-type="bibr" rid="B29">29</xref>), (3) no exposure to antibiotics or immunosuppressant treatment within one month of sample collection, (4) no history of bowel resection or inflammatory bowel disease.</p>
<p>For spatial transcriptomics analysis, IgAN samples were chosen from archived formalin-fixed paraffin-embedded (FFPE) slides, with biopsies performed between 2018 and 2022. Time-zero allograft biopsies after living donor kidney transplantation served as healthy controls, while DN, MCD, and MN samples archived between 2009 and 2021 were selected as disease controls. The selected participants had age 18&#x2013;70 years, eGFR &#x2265;30 mL/min/1.73 m<sup>2</sup>, and no immunosuppressant admission prior to biopsy to minimize the confounding from changes related to advanced aging, late-stage chronic kidney disease, or treatment decisions. Cases with fewer than 10 sampled glomeruli and non-DN cases with DN involvement on pathology were excluded.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Gut microbiome profiling</title>
<p>Stool DNA extraction and sequencing protocols were performed as described previously (<xref ref-type="bibr" rid="B29">29</xref>). Stool samples were collected on the day of kidney biopsy, immediately stored at -20&#xa0;&#xb0;C, then moved to -80 &#xb0;C storage within 24 hours. DNA was extracted with the QIAamp Fast DNA Stool Mini Kit (Qiagen, Hilden, Germany). The V3-V4 hypervariable region of the 16S rRNA gene was amplified, followed by library preparation and sequencing through the Illumina MiSeq system according to the manufacturer&#x2019;s protocol (Illumina, CA, USA).</p>
<p>For data analysis, raw sequence reads in FASTQ format were imported into the Quantitative Insights Into Microbial Ecology (QIIME2) microbiome analysis platform. The sequences were processed through DADA2 for filtering, trimming, and correction for low-quality reads and chimeric sequences (<xref ref-type="bibr" rid="B30">30</xref>). The denoised amplicon sequence variants were then annotated up to the genus level using the SILVA 138 database as reference (<xref ref-type="bibr" rid="B31">31</xref>). For diversity analysis, the samples were rarefied to a sampling depth of 10,000, and Shannon diversity indices and Bray-Curtis distances were computed through the QIIME2 q2-diversity plugin. Prediction of metagenomic functions was performed through Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2 (PICRUSt2) (<xref ref-type="bibr" rid="B32">32</xref>), and the predicted functions for each sample were expressed in terms of MetaCyc pathway abundances (<xref ref-type="bibr" rid="B33">33</xref>). Microbial genera and functional pathway abundances were compared between IgAN and each control group using ANOVA-like differential expression 2 (ALDEx2) (<xref ref-type="bibr" rid="B34">34</xref>), where false-discovery rates (FDR) &lt; 0.05 were considered statistically significant.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Spatial transcriptomic profiling of glomeruli</title>
<p>Slide preparation and processing procedures for spatial transcriptomics profiling were described in detail previously (<xref ref-type="bibr" rid="B27">27</xref>). Briefly, 5 &#xb5;m FFPE kidney biopsy sections underwent deparaffinization and epitope retrieval. A total of 18,677 target genes were labeled via <italic>in situ</italic> hybridization with the GeoMx Whole Transcriptome Atlas, which contains ultraviolet-photocleavable oligonucleotide identifiers. Three representative glomeruli per sample were selected as regions of interest. The oligonucleotide identifiers were collected, amplified through polymerase chain reactions, and sequenced on an Illumina NovaSeq 6000.</p>
<p>Data preprocessing and quality control were performed with the GeoMx Digital Spatial Profiler Data Analysis Suite (v2.4), removing low-performing genes, defined as those expressed in fewer than 50% of samples or below the limit of quantitation (LOQ). The LOQ was set as 2.0 standard deviations above the geometric mean of negative probes. The DESeq2 R package (v3.6.2), which employs negative binomial generalized linear models with median-of-ratios normalization, was used to identify differentially expressed genes (DEGs) between IgAN and each control group (<xref ref-type="bibr" rid="B35">35</xref>). Significant DEGs, defined as those with FDR &lt; 0.10, were extracted for each comparison. Finally, the significant DEGs that show consistently high or low expression in IgAN across all comparisons were processed through the ToppGene Suite for Gene Ontology-based functional enrichment analysis, where a FDR &lt; 0.05 was considered significant (<xref ref-type="bibr" rid="B36">36</xref>).</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Serum and fecal acetate quantification by LC-MS</title>
<p>Acetate concentrations in serum and fecal samples were quantified using liquid chromatography&#x2013;mass spectrometry (LC-MS) after derivatization with 3-nitrophenylhydrazine (3-NPH), as previously described (<xref ref-type="bibr" rid="B37">37</xref>). Fecal samples (~20 mg) were extracted in assay diluent buffer (water:acetonitrile, 1:1), centrifuged, and the supernatants were used for derivatization. For serum, 20 &#xb5;L of sample was directly derivatized without prior extraction. Derivatized samples were incubated at 40&#xa0;&#xb0;C for 30 minutes and then diluted for analysis. LC-MS analysis was performed using a Q-Exactive Focus Orbitrap mass spectrometer (Thermo Fisher Scientific) coupled to a BEH C18 column (2.1 &#xd7; 100&#xa0;mm, 1.7 &#xb5;m, Waters) under electrospray ionization in negative mode. Chromatographic separation was achieved using a water/acetonitrile gradient containing 0.1% formic acid at a flow rate of 0.35 mL/min. The mass spectrometer was operated in full scan mode (m/z 70&#x2013;900), and acetate was identified and quantified by the retention time and m/z (194.1) of its derivatized form, which matched a derivatized acetate standard.</p>
</sec>
<sec id="s2_6">
<label>2.6</label>
<title>Statistical analysis and data visualization</title>
<p>All statistical analysis was performed in R (v4.4.0) except for gut microbial diversity analysis, which was performed on the QIIME2 platform using the q2-diversity plugin. For clinical characteristics, normality of continuous variables was assessed using histograms and skewness evaluations. For statistical comparisons between groups, Mann-Whitney U tests were used for two groups and Kruskal-Wallis was used for three or more groups. Linear associations between continuous variables were evaluated using the Pearson correlation coefficient. Permutational multivariate analysis of variance (PERMANOVA) with 999 permutations was used to evaluate differences in beta diversities among groups using the vegan R package (v2.7-1) (<xref ref-type="bibr" rid="B38">38</xref>). The Benjamini&#x2013;Hochberg method was applied in calculations of false-discovery rates in cases of multiple testing. All boxplots and scatterplots were created with the ggpubr R package (v0.6.1) (<xref ref-type="bibr" rid="B39">39</xref>). Dotplot of the enriched Gene Ontology terms was visualized with the scToppR R package (v0.99.0) (<xref ref-type="bibr" rid="B40">40</xref>).</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Participant demographics and clinical profiles</title>
<p>A total of 336 participants were included in the gut microbiome analysis comprising 172 IgAN patients, 51 healthy donor controls, and 113 disease controls (<xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>). The IgAN patients had a mean age of 41.8, and 52% were female. The mean body mass index was 24.6 kg/m<sup>2</sup> for IgAN, comparable to control groups, which ranged between 23.7 and 25.5 kg/m<sup>2</sup>. The mean eGFR ranged from 85.4 to 104.9 mL/min/1.73 m<sup>2</sup> for each group.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Baseline clinical characteristics of study participants subject to gut microbial profiling.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Characteristic</th>
<th valign="middle" align="center">IgA nephropathy <break/>(N = 172)</th>
<th valign="middle" align="center">Healthy donor <break/>(N = 51)</th>
<th valign="middle" align="center">Diabetic nephropathy <break/>(N = 15)</th>
<th valign="middle" align="center">Minimal change disease <break/>(N = 35)</th>
<th valign="middle" align="center">Membranous nephropathy <break/>(N = 63)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">Age (years)</td>
<td valign="middle" align="center">41.8 &#xb1; 14.8</td>
<td valign="middle" align="center">46.8 &#xb1; 12.2</td>
<td valign="middle" align="center">47.1 &#xb1; 13.3</td>
<td valign="middle" align="center">45.6 &#xb1; 18.0</td>
<td valign="middle" align="center">55.8 &#xb1; 11.1</td>
</tr>
<tr>
<td valign="middle" align="center">Female sex (N (%))</td>
<td valign="middle" align="center">90 (52.3)</td>
<td valign="middle" align="center">27 (52.9)</td>
<td valign="middle" align="center">6 (40.0)</td>
<td valign="middle" align="center">18 (51.4)</td>
<td valign="middle" align="center">26 (41.3)</td>
</tr>
<tr>
<td valign="middle" align="center">Body mass index (kg/m<sup>2</sup>)</td>
<td valign="middle" align="center">24.6 &#xb1; 4.0</td>
<td valign="middle" align="center">23.7 &#xb1; 2.8</td>
<td valign="middle" align="center">25.5 &#xb1; 3.5</td>
<td valign="middle" align="center">25.5 &#xb1; 3.6</td>
<td valign="middle" align="center">25.1 &#xb1; 3.0</td>
</tr>
<tr>
<td valign="middle" align="center">Body weight (kg)</td>
<td valign="middle" align="center">67.2 &#xb1; 13.6</td>
<td valign="middle" align="center">63.6 &#xb1; 10.3</td>
<td valign="middle" align="center">72.3 &#xb1; 11.6</td>
<td valign="middle" align="center">69.7 &#xb1; 12.8</td>
<td valign="middle" align="center">67.6 &#xb1; 13.0</td>
</tr>
<tr>
<td valign="middle" align="center">Systolic BP (mmHg)</td>
<td valign="middle" align="center">125.2 &#xb1; 15.3</td>
<td valign="middle" align="center">121.0 &#xb1; 13.4</td>
<td valign="middle" align="center">126.0 &#xb1; 17.5</td>
<td valign="middle" align="center">123.0 &#xb1; 13.8</td>
<td valign="middle" align="center">126.7 &#xb1; 14.6</td>
</tr>
<tr>
<td valign="middle" align="center">Diastolic BP (mmHg)</td>
<td valign="middle" align="center">77.7 &#xb1; 11.0</td>
<td valign="middle" align="center">76.5 &#xb1; 8.3</td>
<td valign="middle" align="center">81.7 &#xb1; 13.3</td>
<td valign="middle" align="center">77.5 &#xb1; 10.2</td>
<td valign="middle" align="center">78.7 &#xb1; 9.3</td>
</tr>
<tr>
<td valign="middle" align="center">Diabetes mellitus (N (%))</td>
<td valign="middle" align="center">8 (4.7)</td>
<td valign="middle" align="center">0 (0.0)</td>
<td valign="middle" align="center">15 (100)</td>
<td valign="middle" align="center">1 (2.9)</td>
<td valign="middle" align="center">9 (14.3)</td>
</tr>
<tr>
<td valign="middle" align="center">Hypertension (N (%))</td>
<td valign="middle" align="center">63 (36.6)</td>
<td valign="middle" align="center">8 (15.7)</td>
<td valign="middle" align="center">12 (80.0)</td>
<td valign="middle" align="center">7 (20.0)</td>
<td valign="middle" align="center">29 (46.0)</td>
</tr>
<tr>
<td valign="middle" align="center">eGFR (mL/min/1.73 m<sup>2</sup>)</td>
<td valign="middle" align="center">96.4 &#xb1; 23.7</td>
<td valign="middle" align="center">104.9 &#xb1; 12.1</td>
<td valign="middle" align="center">85.4 &#xb1; 21.8</td>
<td valign="middle" align="center">100.5 &#xb1; 20.7</td>
<td valign="middle" align="center">98.7 &#xb1; 16.3</td>
</tr>
<tr>
<td valign="middle" align="center">Hemoglobin (g/dL)</td>
<td valign="middle" align="center">13.2 &#xb1; 1.8</td>
<td valign="middle" align="center">14.0 &#xb1; 1.3</td>
<td valign="middle" align="center">13.1 &#xb1; 2.1</td>
<td valign="middle" align="center">14.5 &#xb1; 1.9</td>
<td valign="middle" align="center">13.1 &#xb1; 1.5</td>
</tr>
<tr>
<td valign="middle" align="center">Albumin (g/dL)</td>
<td valign="middle" align="center">4.0 &#xb1; 0.5</td>
<td valign="middle" align="center">4.4 &#xb1; 0.4</td>
<td valign="middle" align="center">4.0 &#xb1; 0.6</td>
<td valign="middle" align="center">2.5 &#xb1; 0.7</td>
<td valign="middle" align="center">2.9 &#xb1; 0.7</td>
</tr>
<tr>
<td valign="middle" align="center">Total cholesterol (mg/dL)</td>
<td valign="middle" align="center">186 [161, 212]</td>
<td valign="middle" align="center">186 [162, 218]</td>
<td valign="middle" align="center">169 [148, 202]</td>
<td valign="middle" align="center">385 [284, 514]</td>
<td valign="middle" align="center">232 [182, 280]</td>
</tr>
<tr>
<td valign="middle" align="center">Spot urine PCR (g/g)</td>
<td valign="middle" align="center">0.97 [0.48, 1.75]</td>
<td valign="middle" align="center">0.05 [0.04, 0.08]</td>
<td valign="middle" align="center">3.40 [1.01, 3.92]</td>
<td valign="middle" align="center">7.41 [4.34, 9.88]</td>
<td valign="middle" align="center">4.51 [2.29, 6.66]</td>
</tr>
<tr>
<td valign="middle" align="right">&#x2265; 3.0 (N (%))</td>
<td valign="middle" align="center">11 (6.4)</td>
<td valign="middle" align="center">0 (0.0)</td>
<td valign="middle" align="center">8 (53.3)</td>
<td valign="middle" align="center">30 (85.7)</td>
<td valign="middle" align="center">44 (69.8)</td>
</tr>
<tr>
<td valign="middle" align="right">&lt; 3.0 (N (%))</td>
<td valign="middle" align="center">160 (93.0)</td>
<td valign="middle" align="center">47 (92.2)</td>
<td valign="middle" align="center">7 (46.7)</td>
<td valign="middle" align="center">5 (14.3)</td>
<td valign="middle" align="center">19 (30.2)</td>
</tr>
<tr>
<td valign="middle" align="right">Not quantified (N (%))</td>
<td valign="middle" align="center">1 (0.6)</td>
<td valign="middle" align="center">4 (7.8)</td>
<td valign="middle" align="center">0 (0.0)</td>
<td valign="middle" align="center">0 (0.0)</td>
<td valign="middle" align="center">0 (0.0)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>BP, blood pressure; eGFR, estimated glomerular filtration rate; N, number; PCR, protein-to-creatinine ratio.</p></fn>
<fn>
<p>Parameters with normal distributions are shown as mean &#xb1; standard deviation, while other parameters are presented as median [interquartile range].</p></fn>
</table-wrap-foot>
</table-wrap>
<p>For spatial transcriptomic analysis, 8 biopsy-proven IgAN cases were subject to spatial transcriptomics profiling along with 10 healthy controls and 35 disease controls (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>). The IgAN patients had a mean age of 36.6, younger than control groups. They were more female, while control groups had a male majority. Lower eGFRs were observed among other disease controls, with the DN group having the lowest mean eGFR at 56.3 mL/min/1.73 m<sup>2</sup>.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Baseline clinical characteristics of study participants subject to glomerular spatial transcriptomics profiling.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Characteristic</th>
<th valign="middle" align="center">IgA nephropathy (N = 8)</th>
<th valign="middle" align="center">Healthy donor (N = 10)</th>
<th valign="middle" align="center">Diabetic nephropathy (N = 6)</th>
<th valign="middle" align="center">Minimal change disease (N = 13)</th>
<th valign="middle" align="center">Membranous nephropathy (N = 16)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">Age (years)</td>
<td valign="middle" align="center">36.6 &#xb1; 12.4</td>
<td valign="middle" align="center">51.2 &#xb1; 8.6</td>
<td valign="middle" align="center">56.0 &#xb1; 9.8</td>
<td valign="middle" align="center">48.0 &#xb1; 12.4</td>
<td valign="middle" align="center">52.1 &#xb1; 10.3</td>
</tr>
<tr>
<td valign="middle" align="center">Female sex (N (%))</td>
<td valign="middle" align="center">6 (75.0)</td>
<td valign="middle" align="center">5 (50.0)</td>
<td valign="middle" align="center">0 (0.0)</td>
<td valign="middle" align="center">4 (30.8)</td>
<td valign="middle" align="center">3 (18.8)</td>
</tr>
<tr>
<td valign="middle" align="center">eGFR (mL/min/1.73 m<sup>2</sup>)</td>
<td valign="middle" align="center">109.6 &#xb1; 20.3</td>
<td valign="middle" align="center">89.2 &#xb1; 7.5</td>
<td valign="middle" align="center">56.3 &#xb1; 24.4</td>
<td valign="middle" align="center">75.7 &#xb1; 38.3</td>
<td valign="middle" align="center">92.3 &#xb1; 23.5</td>
</tr>
<tr>
<td valign="middle" align="right">&#x2265; 90 (N (%))</td>
<td valign="middle" align="center">7 (87.5)</td>
<td valign="middle" align="center">4 (40.0)</td>
<td valign="middle" align="center">1 (16.7)</td>
<td valign="middle" align="center">6 (46.2)</td>
<td valign="middle" align="center">11 (68.8)</td>
</tr>
<tr>
<td valign="middle" align="right">&#x2265; 60 and &lt; 90 (N (%))</td>
<td valign="middle" align="center">1 (12.5)</td>
<td valign="middle" align="center">6 (60.0)</td>
<td valign="middle" align="center">1 (16.7)</td>
<td valign="middle" align="center">2 (15.4)</td>
<td valign="middle" align="center">3 (18.8)</td>
</tr>
<tr>
<td valign="middle" align="right">&#x2265; 45 and &lt; 60 (N (%))</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">1 (16.7)</td>
<td valign="middle" align="center">2 (15.4)</td>
<td valign="middle" align="center">1 (6.3)</td>
</tr>
<tr>
<td valign="middle" align="right">&#x2265; 30 and &lt; 45 (N (%))</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">3 (50.0)</td>
<td valign="middle" align="center">3 (23.1)</td>
<td valign="middle" align="center">1 (6.3)</td>
</tr>
<tr>
<td valign="middle" align="center">Hemoglobin (g/dL)</td>
<td valign="middle" align="center">12.0 &#xb1; 1.3</td>
<td valign="middle" align="center">14.5 &#xb1; 1.4</td>
<td valign="middle" align="center">11.6 &#xb1; 2.0</td>
<td valign="middle" align="center">13.2 &#xb1; 1.6</td>
<td valign="middle" align="center">12.8 &#xb1; 1.2</td>
</tr>
<tr>
<td valign="middle" align="center">Albumin (g/dL)</td>
<td valign="middle" align="center">4.2 &#xb1; 0.4</td>
<td valign="middle" align="center">4.0 &#xb1; 0.3</td>
<td valign="middle" align="center">3.8 &#xb1; 0.7</td>
<td valign="middle" align="center">2.1 &#xb1; 0.5</td>
<td valign="middle" align="center">2.4 &#xb1; 0.7</td>
</tr>
<tr>
<td valign="middle" align="center">Total cholesterol (mg/dL)</td>
<td valign="middle" align="center">227 [205, 249]</td>
<td valign="middle" align="center">201 [191, 213]</td>
<td valign="middle" align="center">193 [177, 210]</td>
<td valign="middle" align="center">360 [338, 440]</td>
<td valign="middle" align="center">282 [216, 338]</td>
</tr>
<tr>
<td valign="middle" align="center">Spot urine PCR (g/g)</td>
<td valign="middle" align="center">1.03 [0.34, 1.97]</td>
<td valign="middle" align="center">0 [0, 0]</td>
<td valign="middle" align="center">2.73 [1.60, 3.07]</td>
<td valign="middle" align="center">9.27 [6.86, 11.30]</td>
<td valign="middle" align="center">7.36 [4.48, 9.03]</td>
</tr>
<tr>
<td valign="middle" align="right">&#x2265; 3.0 (N (%))</td>
<td valign="middle" align="center">1 (12.5)</td>
<td valign="middle" align="center">0 (0.0)</td>
<td valign="middle" align="center">2 (33.3)</td>
<td valign="middle" align="center">12 (92.3)</td>
<td valign="middle" align="center">14 (87.5)</td>
</tr>
<tr>
<td valign="middle" align="right">&lt; 3.0 (N (%))</td>
<td valign="middle" align="center">7 (87.5)</td>
<td valign="middle" align="center">10 (100.0)</td>
<td valign="middle" align="center">4 (66.7)</td>
<td valign="middle" align="center">1 (7.7)</td>
<td valign="middle" align="center">2 (12.5)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>eGFR, estimated glomerular filtration rate; N, number; PCR, protein-to-creatinine ratio.</p></fn>
<fn>
<p>Parameters with normal distributions are shown as mean &#xb1; standard deviation, while other parameters are presented as median [interquartile range].</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>IgAN-specific functional enrichment of gut microbiota</title>
<p>A total of 466 microbial genera and 332 predicted metagenomic functional pathways were identified. While alpha diversities did not differ among groups (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1A</bold></xref>), beta diversities were significantly differed among diagnostic groups (PERMANOVA, <italic>p</italic> =&#xa0;0.001) (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1B</bold></xref>). IgAN microbiota composition was distinct from that of healthy controls (<italic>p</italic> =&#xa0;0.001), MCD (<italic>p</italic> =&#xa0;0.034), and MN (<italic>p</italic> =&#xa0;0.013) but not from DN (<italic>p</italic> =&#xa0;0.34). Significant differences between IgAN and healthy controls were consistently observed across different beta diversity metrics including Jaccard indices (<italic>p</italic> =&#xa0;0.001), unweighted UniFrac (<italic>p</italic>&#xa0;=&#xa0;0.006), and weighted UniFrac (<italic>p</italic> =&#xa0;0.001), as were the differences among the five diagnostic groups (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure&#xa0;1</bold></xref>). Beta diversities based on the Bray-Curtis metric also significantly differed among groups (<italic>p</italic> &lt;&#xa0;0.001) when major covariates (age, sex, and eGFR) were included in the model.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Characteristics of the gut microbiome in IgA nephropathy (IgAN). <bold>(A)</bold> Alpha diversity based on Shannon indices. The Kruskal-Wallis test was used to evaluate statistical significance. (HC: healthy controls, DN: diabetic nephropathy, MCD: minimal change disease, MN: membranous nephropathy) <bold>(B)</bold> Beta diversity based on Bray-Curtis dissimilarity indices represented as a principal coordinate analysis plot. Statistical significance was evaluated by permutational multivariate analysis of variance (PERMANOVA). (PC: principal coordinate) <bold>(C)</bold> Predicted abundances of the methanogenesis from acetate MetaCyc pathway grouped by diagnosis. Absolute pathways abundances were derived from PICRUSt2-predicted metagenome functions.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-16-1665585-g001.tif">
<alt-text content-type="machine-generated">Three charts compare five groups: IgAN, HC, DN, MCD, and MN. Chart A shows box plots of the Shannon index with a p-value of 0.72. Chart B is a PCA plot with a p-value of 0.001, showing clusters for each group. Chart C shows box plots of pathway abundance. Each group is represented by different colors.</alt-text>
</graphic></fig>
<p>In taxonomic differential abundance analysis, eight genera (<italic>Bacteroides</italic>, <italic>Parabacteroides</italic>, <italic>Alistipes</italic>, <italic>Blautia</italic>, <italic>Romboutsia</italic>, <italic>Dorea</italic>, <italic>Lachnospira</italic>, and <italic>Butyricicoccus</italic>) differed between IgAN and healthy controls, but none were consistently different from all disease controls (<xref ref-type="table" rid="T3"><bold>Table&#xa0;3</bold></xref>). As for functional analysis, Methanogenesis from Acetate (METH-ACETATE-PWY) was the only pathway significantly enriched in IgAN relative to both healthy controls and to each of the different glomerular disease controls, as visualized in a plot of the predicted pathway abundances (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1C</bold></xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Microbial genera with statistically significant differential abundance for IgA nephropathy compared to healthy and disease controls.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center">Family</th>
<th valign="middle" rowspan="2" align="center">Genus</th>
<th valign="middle" colspan="2" align="left">HC</th>
<th valign="middle" colspan="2" align="left">DN</th>
<th valign="middle" colspan="2" align="left">MCD</th>
<th valign="middle" colspan="2" align="left">MN</th>
</tr>
<tr>
<th valign="middle" align="left"><italic>P</italic>-value</th>
<th valign="middle" align="left">FDR</th>
<th valign="middle" align="left"><italic>P</italic>-value</th>
<th valign="middle" align="left">FDR</th>
<th valign="middle" align="left"><italic>P</italic>-value</th>
<th valign="middle" align="left">FDR</th>
<th valign="middle" align="left"><italic>P</italic>-value</th>
<th valign="middle" align="left">FDR</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">Lachnospiraceae</td>
<td valign="middle" align="center"><italic>Blautia</italic></td>
<td valign="middle" align="left">5.45E-08</td>
<td valign="middle" align="left">1.89E-05</td>
<td valign="middle" align="left">0.185</td>
<td valign="middle" align="left">0.868</td>
<td valign="middle" align="left">3.07E-03</td>
<td valign="middle" align="left">0.204</td>
<td valign="middle" align="left">2.73E-04</td>
<td valign="middle" align="left">0.0714</td>
</tr>
<tr>
<td valign="middle" align="center">Bacteroidaceae</td>
<td valign="middle" align="center"><italic>Bacteroides</italic></td>
<td valign="middle" align="left">2.11E-07</td>
<td valign="middle" align="left">4.02E-05</td>
<td valign="middle" align="left">0.550</td>
<td valign="middle" align="left">0.941</td>
<td valign="middle" align="left">0.0493</td>
<td valign="middle" align="left">0.445</td>
<td valign="middle" align="left">0.0176</td>
<td valign="middle" align="left">0.453</td>
</tr>
<tr>
<td valign="middle" align="center">Rikenellaceae</td>
<td valign="middle" align="center"><italic>Alistipes</italic></td>
<td valign="middle" align="left">7.59E-06</td>
<td valign="middle" align="left">8.53E-04</td>
<td valign="middle" align="left">0.228</td>
<td valign="middle" align="left">0.878</td>
<td valign="middle" align="left">0.116</td>
<td valign="middle" align="left">0.567</td>
<td valign="middle" align="left">0.0304</td>
<td valign="middle" align="left">0.517</td>
</tr>
<tr>
<td valign="middle" align="center">Lachnospiraceae</td>
<td valign="middle" align="center"><italic>Lachnospira</italic></td>
<td valign="middle" align="left">3.40E-05</td>
<td valign="middle" align="left">2.79E-03</td>
<td valign="middle" align="left">0.328</td>
<td valign="middle" align="left">0.896</td>
<td valign="middle" align="left">0.737</td>
<td valign="middle" align="left">0.923</td>
<td valign="middle" align="left">0.468</td>
<td valign="middle" align="left">0.898</td>
</tr>
<tr>
<td valign="middle" align="center">Tannerellaceae</td>
<td valign="middle" align="center"><italic>Parabacteroides</italic></td>
<td valign="middle" align="left">1.22E-04</td>
<td valign="middle" align="left">7.29E-03</td>
<td valign="middle" align="left">0.889</td>
<td valign="middle" align="left">0.981</td>
<td valign="middle" align="left">0.511</td>
<td valign="middle" align="left">0.851</td>
<td valign="middle" align="left">0.331</td>
<td valign="middle" align="left">0.874</td>
</tr>
<tr>
<td valign="middle" align="center">Butyricicoccaceae</td>
<td valign="middle" align="center"><italic>Butyricicoccus</italic></td>
<td valign="middle" align="left">3.37E-04</td>
<td valign="middle" align="left">0.0150</td>
<td valign="middle" align="left">0.867</td>
<td valign="middle" align="left">0.977</td>
<td valign="middle" align="left">0.0353</td>
<td valign="middle" align="left">0.403</td>
<td valign="middle" align="left">0.155</td>
<td valign="middle" align="left">0.773</td>
</tr>
<tr>
<td valign="middle" align="center">Peptostreptococcaceae</td>
<td valign="middle" align="center"><italic>Romboutsia</italic></td>
<td valign="middle" align="left">3.89E-04</td>
<td valign="middle" align="left">0.0162</td>
<td valign="middle" align="left">8.07E-03</td>
<td valign="middle" align="left">0.556</td>
<td valign="middle" align="left">0.346</td>
<td valign="middle" align="left">0.757</td>
<td valign="middle" align="left">0.575</td>
<td valign="middle" align="left">0.924</td>
</tr>
<tr>
<td valign="middle" align="center">Lachnospiraceae</td>
<td valign="middle" align="center"><italic>Dorea</italic></td>
<td valign="middle" align="left">6.51E-04</td>
<td valign="middle" align="left">0.0243</td>
<td valign="middle" align="left">0.856</td>
<td valign="middle" align="left">0.977</td>
<td valign="middle" align="left">0.0783</td>
<td valign="middle" align="left">0.490</td>
<td valign="middle" align="left">0.0944</td>
<td valign="middle" align="left">0.690</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>DN, diabetic nephropathy, FDR, false-discovery rate, HC, healthy control, MCD, minimal change disease, MN, membranous nephropathy.</p></fn>
<fn>
<p>Statistical significance was determined by ALDEx2 with a false-discovery rate threshold of 0.05 by the Benjamini-Hochberg method.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Altered acetate metabolism in IgAN</title>
<p>To assess the generation of acetate by the gut microbiota, we next compared relative acetate-producing potential based on the abundances of eight common gut microbial genera that contain species known to contribute to acetate production (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2A</bold></xref>). IgAN showed the highest mean total relative abundances of the eight genera at 39.8%, followed by disease controls at 37.3% (<italic>p</italic> =&#xa0;0.037, FDR <italic>=</italic> 0.037) and healthy control at 30.6% (<italic>p</italic> &lt;&#xa0;0.001, FDR &lt; 0.001). Among the 8 genera, <italic>Bacteroides</italic> and <italic>Blautia</italic> revealed higher abundance in IgAN than in healthy controls (<xref ref-type="table" rid="T3"><bold>Table&#xa0;3</bold></xref>). MCD (<italic>p</italic> =&#xa0;0.008, FDR&#xa0;=&#xa0;0.041) and MN (<italic>p</italic> =&#xa0;0.014, FDR&#xa0;=&#xa0;0.046) also showed elevated proportions of major acetate producers. Meanwhile, the acetotrophic methanogens recognized to possess the methanogenesis from acetate pathway, <italic>Methanosarcina</italic> and <italic>Methanothrix</italic>, were not detected in any sample. In addition to this, we found that IgAN patients had higher serum acetate levels than healthy controls (<italic>p</italic> =&#xa0;0.03) but similar fecal acetate levels (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2B</bold></xref>). There was negligible correlation between serum and fecal acetate levels (<italic>R</italic> =&#xa0;-0.17, <italic>p</italic> =&#xa0;0.15) (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2C</bold></xref>). The identified IgAN-associated gut microbial signatures, namely the relative acetate-producing potential and the methanogenesis from acetate pathway, did not show significant correlations with baseline clinical parameters or with serum and fecal acetate levels (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table&#xa0;1</bold></xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Acetate metabolism in IgA nephropathy (IgAN). <bold>(A)</bold> Relative abundances of major acetate-producing microbial taxa. The bar plot depicts the relative abundances of major acetate-producing genera for each sample, compiled into mean relative abundances for each diagnosis group. Pairwise Mann-Whitney U tests were performed for the combined mean relative abundances, and asterisks indicate statistically significant differences based on false discovery rates (FDR): *FDR &lt; 0.05, ***FDR &lt; 0.001. (HC: healthy controls, DN: diabetic nephropathy, MCD: minimal change disease, MN: membranous nephropathy) <bold>(B)</bold> Serum and fecal acetate levels in IgAN (N = 55) and HC (N = 23). Measurements from liquid chromatography&#x2013;mass spectrometry are shown as intensities in arbitrary units (a.u.), and statistical significance was evaluated with Mann-Whitney U tests. <bold>(C)</bold> Correlation between measured serum and fecal acetate levels. Pearson correlation coefficient is shown, along with the corresponding <italic>p</italic>-value.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-16-1665585-g002.tif">
<alt-text content-type="machine-generated">Three-panel figure showing microbiome and metabolite data. Panel A presents a stacked bar graph and bar chart of microbiome genus relative abundance across five groups: IgAN, HC, DN, MCD, and MN. Panel B includes box plots comparing serum and fecal acetate levels between IgAN and HC groups, with significant p-value for serum acetate. Panel C displays a scatter plot correlating serum and fecal acetate, with IgAN and HC differentiation, showing a weak correlation. Legends indicate genus and group color codes.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Glomerular spatial transcriptomics reveals altered signaling pathways in IgAN</title>
<p>Glomerular expression profiles of 17,834 genes were subject to analysis. Relative log expression plots showed no extreme outliers in count distributions (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure&#xa0;2A</bold></xref>), and compartment-specific gene expressions supported appropriate region selection (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure&#xa0;2B</bold></xref>). A total of 1,227 and 1,078 genes were consistently upregulated and downregulated, respectively, in IgAN relative to healthy controls and to each disease control group (<xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3A</bold></xref>, <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Tables&#xa0;2</bold></xref>, <xref ref-type="supplementary-material" rid="SM1"><bold>3</bold></xref>). The highest fold increase was found in <italic>COL3A1</italic> (collagen type III alpha 1 chain), a key component of the extracellular matrix. The highly expressed DEGs were associated with 1,209 Gene Ontology terms (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table&#xa0;4</bold></xref>), where the top categories included cell adhesion, extracellular matrix organization, protein complex assembly, and mitochondrial function (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4</bold></xref>). Meanwhile, the lowly expressed DEGs were enriched in 18 functional terms (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4</bold></xref>, <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table&#xa0;5</bold></xref>). GPCR activity was the top enriched function, alongside terms pertaining to olfactory receptors, which belong to the GPCR superfamily. Beta-1,3-galactosyltransferase activity, involved in <italic>O</italic>-galactosylation of glycoproteins including immunoglobulins, also showed significant enrichment. Moreover, the majority of SCFA transmembrane transporter and calcium, potassium:sodium antiporter genes were downregulated in IgAN (<xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3B</bold></xref>). As for the acetate-sensing GPCRs, IgAN displayed undetectable <italic>GPR41</italic> (<italic>FFAR3</italic>) expression as well as lower <italic>GPR43</italic> (<italic>FFAR2</italic>) and <italic>Olfr78</italic> (<italic>OR51E2</italic>) expressions, although the latter was only significant relative to MCD and MN (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4</bold></xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Differential gene expression analysis in the glomerular transcriptome of IgA nephropathy (IgAN). <bold>(A)</bold> Volcano plot of differentially expressed genes (DEGs) for the glomerulus of IgAN compared to healthy controls. Red and blue colors indicate DEGs with log<sub>2</sub> fold change above 1.5 or below -1.5, respectively. <bold>(B)</bold> Gene Ontology (GO) terms significantly enriched among DEGs with decreased expression in IgAN. The x-axis, gene ratio, shows the ratio between the count of contributing DEGs and the total gene count for each GO term. Dot sizes show the absolute number of DEGs contributing to each GO term, while the dot colors correspond to the false discovery rate (FDR).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-16-1665585-g003.tif">
<alt-text content-type="machine-generated">A) Volcano plot showing gene expression data with log2 fold change on the x-axis and negative log10 adjusted p-value on the y-axis. Genes are indicated by dots, with blue and red highlights for significant genes. B) Dot plot displaying gene ontology enrichment with gene ratio on the x-axis and terms on the y-axis. Dot colors represent the false discovery rate, and dot sizes show the number of genes in each gene set. Biological process terms are in orange, and molecular function terms are in blue.</alt-text>
</graphic></fig>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Top gene ontologies for differentially expressed genes (DEGs) consistently upregulated or downregulated in IgA nephropathy.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Aspect</th>
<th valign="middle" align="left">Terms increased in IgA nephropathy (up to 10 per aspect)</th>
<th valign="middle" align="left">B-H FDR</th>
<th valign="middle" align="left">Terms decreased in IgA nephropathy (up to 10 per aspect)</th>
<th valign="middle" align="left">B-H FDR</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="10" align="left">Molecular<break/>function</td>
<td valign="middle" align="left">oxidoreduction-driven active transmembrane transporter activity (GO:0015453)</td>
<td valign="middle" align="left">6.27E-18</td>
<td valign="middle" align="left">G protein-coupled receptor activity (GO:0004930)</td>
<td valign="middle" align="left">3.74E-04</td>
</tr>
<tr>
<td valign="middle" align="left">electron transfer activity (GO:0009055)</td>
<td valign="middle" align="left">6.27E-18</td>
<td valign="middle" align="left">beta-1,3-galactosyltransferase activity (GO:0048531)</td>
<td valign="middle" align="left">3.32E-03</td>
</tr>
<tr>
<td valign="middle" align="left">proton transmembrane transporter activity (GO:0015078)</td>
<td valign="middle" align="left">7.04E-16</td>
<td valign="middle" align="left">calcium, potassium:sodium antiporter activity (GO:0008273)</td>
<td valign="middle" align="left">1.29E-02</td>
</tr>
<tr>
<td valign="middle" align="left">cell adhesion molecule binding (GO:0050839)</td>
<td valign="middle" align="left">1.82E-15</td>
<td valign="middle" align="left">short-chain fatty acid transmembrane transporter activity (GO:0015636)</td>
<td valign="middle" align="left">1.29E-02</td>
</tr>
<tr>
<td valign="middle" align="left">NADH dehydrogenase (ubiquinone) activity (GO:0008137)</td>
<td valign="middle" align="left">7.03E-13</td>
<td valign="middle" align="left">transmembrane signaling receptor activity (GO:0004888)</td>
<td valign="middle" align="left">1.75E-02</td>
</tr>
<tr>
<td valign="middle" align="left">cadherin binding (GO:0045296)</td>
<td valign="middle" align="left">3.95E-12</td>
<td valign="middle" align="left">olfactory receptor activity (GO:0004984)</td>
<td valign="middle" align="left">1.82E-02</td>
</tr>
<tr>
<td valign="middle" align="left">primary active transmembrane activity (GO:0015399)</td>
<td valign="middle" align="left">3.95E-12</td>
<td valign="middle" align="left">sodium-independent organic anion transmembrane transporter activity (GO:0015347)</td>
<td valign="middle" align="left">4.05E-02</td>
</tr>
<tr>
<td valign="middle" align="left">oxidoreductase activity, acting on NAD(P)H, quinone or similar compound as acceptor (GO:0016655)</td>
<td valign="middle" align="left">4.79E-10</td>
<td valign="middle" align="left">N-acetyl-beta-D-glucosaminide beta-(1,3)-galactosyltransferase activity (GO:0008499)</td>
<td valign="middle" align="left">4.05E-02</td>
</tr>
<tr>
<td valign="middle" align="left">molecular adaptor activity (GO:0060090)</td>
<td valign="middle" align="left">6.69E-09</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">protein-macromolecule adaptor activity (GO:0030674)</td>
<td valign="middle" align="left">1.51E-08</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="top" rowspan="10" align="left">Biological<break/>process</td>
<td valign="middle" align="left">protein-containing complex assembly (GO:0065003)</td>
<td valign="middle" align="left">3.04E-19</td>
<td valign="middle" align="left">detection of chemical stimulus involved in sensory perception (GO:0050907)</td>
<td valign="middle" align="left">2.59E-03</td>
</tr>
<tr>
<td valign="middle" align="left">aerobic respiration (GO:0009060)</td>
<td valign="middle" align="left">1.21E-18</td>
<td valign="middle" align="left">detection of stimulus (GO:0051606)</td>
<td valign="middle" align="left">2.59E-03</td>
</tr>
<tr>
<td valign="middle" align="left">oxidative phosphorylation (GO:0006119)</td>
<td valign="middle" align="left">1.64E-17</td>
<td valign="middle" align="left">nervous system process (GO:0050877)</td>
<td valign="middle" align="left">2.59E-03</td>
</tr>
<tr>
<td valign="middle" align="left">cellular respiration (GO:0045333)</td>
<td valign="middle" align="left">1.02E-16</td>
<td valign="middle" align="left">detection of chemical stimulus (GO:0009593)</td>
<td valign="middle" align="left">2.59E-03</td>
</tr>
<tr>
<td valign="middle" align="left">ATP biosynthetic process (GO:0006754)</td>
<td valign="middle" align="left">1.17E-16</td>
<td valign="middle" align="left">detection of stimulus involved in sensory perception (GO:0050906)</td>
<td valign="middle" align="left">2.59E-03</td>
</tr>
<tr>
<td valign="middle" align="left">proton motive force-driven ATP synthesis (GO:0015986)</td>
<td valign="middle" align="left">1.44E-16</td>
<td valign="middle" align="left">G protein-coupled receptor signaling pathway (GO:0007186)</td>
<td valign="middle" align="left">2.83E-03</td>
</tr>
<tr>
<td valign="middle" align="left">aerobic electron transport chain (GO:0019646)</td>
<td valign="middle" align="left">2.31E-16</td>
<td valign="middle" align="left">sensory perception of chemical stimulus (GO:0007606)</td>
<td valign="middle" align="left">2.83E-03</td>
</tr>
<tr>
<td valign="middle" align="left">ribonucleoside triphosphate biosynthetic process (GO:0009201)</td>
<td valign="middle" align="left">5.83E-16</td>
<td valign="middle" align="left">sensory perception of smell (GO:0007608)</td>
<td valign="middle" align="left">5.98E-03</td>
</tr>
<tr>
<td valign="middle" align="left">nucleoside triphosphate biosynthetic process (GO:0009142)</td>
<td valign="middle" align="left">5.83E-16</td>
<td valign="middle" align="left">sensory perception (GO:0007600)</td>
<td valign="middle" align="left">5.98E-03</td>
</tr>
<tr>
<td valign="middle" align="left">purine ribonucleoside triphosphate biosynthetic process (GO:0009206)</td>
<td valign="middle" align="left">5.83E-16</td>
<td valign="middle" align="left">detection of chemical stimulus involved in sensory perception of smell (GO:0050911)</td>
<td valign="middle" align="left">8.76E-03</td>
</tr>
<tr>
<td valign="top" rowspan="10" align="left">Cellular<break/>component</td>
<td valign="middle" align="left">mitochondrion (GO:0005739)</td>
<td valign="middle" align="left">1.30E-22</td>
<td valign="middle" align="left">None</td>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">mitochondrial envelope (GO:0005740)</td>
<td valign="middle" align="left">1.20E-21</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">organelle envelope (GO:0031967)</td>
<td valign="middle" align="left">8.34E-21</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">organelle inner membrane (GO:0019866)</td>
<td valign="middle" align="left">1.31E-20</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">mitochondrial inner membrane (GO:0005743)</td>
<td valign="middle" align="left">1.31E-20</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">catalytic complex (GO:1902494)</td>
<td valign="middle" align="left">1.37E-20</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">mitochondrial membrane (GO:0031966)</td>
<td valign="middle" align="left">2.10E-20</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">focal adhesion (GO:0005925)</td>
<td valign="middle" align="left">8.61E-20</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">cell-substrate junction (GO:0030055)</td>
<td valign="middle" align="left">1.20E-19</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left">respiratory chain complex (GO:0098803)</td>
<td valign="middle" align="left">2.15E-17</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>B-H FDR, Benjamini&#x2013;Hochberg false-discovery rate.</p></fn>
<fn>
<p>Up to 10 gene ontology terms with lowest false discovery rates for each aspect are shown.</p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Glomerular expression of short-chain fatty acid-sensing G protein-coupled receptors. Statistically significant differences based on pairwise Mann-Whitney U tests are indicated with asterisks: *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001, ***<italic>p</italic> &lt; 0.0001.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-16-1665585-g004.tif">
<alt-text content-type="machine-generated">Box plots displaying expression levels of GPR41 (FFAR3), GPR43 (FFAR2), and Olfr78 (OR51E2) genes across different groups: IgAN, HC, DN, MCD, and MN. GPR41 shows multiple significant differences, marked by asterisks, indicating varying expression levels. GPR43 and Olfr78 also show statistical significance across the groups. Counts per million are plotted on the y-axis, with significant differences denoted by asterisks (*, **, ***) indicating p-values.</alt-text>
</graphic></fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>In this study, we integrated gut microbiome profiling and glomerular spatial transcriptomics to characterize the microbial and transcriptomic changes in IgAN that potentially modulate the gut-kidney axis. The gut microbiome in IgAN showed an enrichment of major acetate-producing taxa and the methanogenesis from acetate pathway, accompanied by elevated serum acetate levels. At the same time, the glomerular transcriptome of IgAN demonstrated a downregulation of SCFA transporters and SCFA-sensing GPCRs, suggesting a mismatch between systemic metabolite availability and kidney sensing capacity.</p>
<p>Mounting evidence suggests acetate plays a key role in regulating immunity and inflammation, including in kidney diseases. Primarily generated through gut bacterial fermentation, acetate is the predominant SCFA, constituting 60-75% of total gut SCFAs (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B42">42</xref>) and over 90% of those in serum (<xref ref-type="bibr" rid="B43">43</xref>). As both an energy source and a signaling molecule, it supports maintenance of the intestinal epithelial barrier while suppressing proinflammatory mediators (<xref ref-type="bibr" rid="B41">41</xref>). <italic>In vivo</italic>, acetate prevented acute kidney injury in an ischemia-reperfusion injury model and reduced kidney fibrosis in an unilateral ureteral obstruction model (<xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B45">45</xref>), and it also attenuated clinical manifestations in a mouse model of IgAN (<xref ref-type="bibr" rid="B46">46</xref>). Hence, acetate may have renoprotective effects specific to IgAN as well as across kidney disease more broadly.</p>
<p>Our gut microbial analysis suggests that acetate production and consumption in the gut are both modulated in IgAN. Functional analysis indicated an increase in predicted enzymatic activities attributable to acetate consumption by methanogens. While methanogens have been associated with several diseases including inflammatory bowel disease (<xref ref-type="bibr" rid="B47">47</xref>), research on their role in the human gut is relatively sparse. Since methanogens were not identified in our taxonomic annotations, possibly because archaea comprise only 0.1% of reads in non-targeted sequencing (<xref ref-type="bibr" rid="B48">48</xref>), the observed metabolic activities may also reflect contributions from other acetate utilizers. As for acetate production, a previous study reported significantly decreased fecal SCFA levels in IgAN, with correlations to gut microbiota composition and clinical parameters, suggesting that disruption of SCFA levels could be relevant to IgAN (<xref ref-type="bibr" rid="B49">49</xref>). However, we did not observe differences in fecal acetate levels, and the relative increase in major acetate-producing genera in IgAN suggests that acetate production may not be compromised in IgAN. Our results are therefore most consistent with a simultaneous increase in the consumption and production of gut acetate in IgAN.</p>
<p>In addition, the glomerular transcriptome of IgAN shows potential evidence of altered acetate signaling in the kidney. Acetate in circulation can signal across diverse tissues through specific GPCRs (GPR41, GPR43, Olfr78) (<xref ref-type="bibr" rid="B50">50</xref>), which were downregulated in the glomerular transcriptome of IgAN: <italic>GPR41</italic> was undetectable, and <italic>GPR43</italic> and <italic>Olfr78</italic> had significantly lower expression compared to MCD and MN. As <italic>GPR41</italic> expression was also undetected in some of the healthy controls, the observed lack of <italic>GPR41</italic> expression in IgAN likely reflects its low baseline expression below the detection threshold. We also observed a downregulation of SCFA transmembrane transporters, namely <italic>SMCT</italic> (<italic>SLC5A8</italic>), <italic>OAT4</italic> (<italic>SLC22A9</italic>), <italic>OAT5</italic> (<italic>SLC22A10</italic>), and <italic>UST5</italic> (<italic>SLC22A25</italic>). These transporters are mainly associated with renal tubules rather than the glomerulus, but they are also part of the organic anion transporter family, whose members can mediate interorgan communication by modulating metabolite levels (<xref ref-type="bibr" rid="B51">51</xref>). The downregulation of olfactory receptor activity in IgAN could also reflect decreased SCFA signaling, as some renal olfactory receptors have physiological functions. Olfr78, as a prime example, localizes to the juxtaglomerular apparatus and modulates renin homeostasis through acetate and propionate signaling (<xref ref-type="bibr" rid="B52">52</xref>). Other downregulated orphan olfactory receptors may similarly localize to the glomerulus and contribute to acetate signaling. While these findings may indicate compensatory responses to elevated acetate levels, negative feedback is not universal. Indeed, a recent study showed that acetate exposure upregulated, rather than downregulated, <italic>GPR43</italic> expression in kidney tubular cells (<xref ref-type="bibr" rid="B53">53</xref>). Hence, the glomerular downregulation of SCFA-related genes in IgAN may reflect pathologic suppression of acetate signaling, which would leave the kidney vulnerable to inflammation and oxidative stress.</p>
<p>Collectively, our analyses present a nuanced picture of acetate biology in IgAN that involves potential changes from synthesis in the gut to signaling in the glomerulus. While serum acetate levels were elevated in IgAN, this may be a reactive change rather than a pathological mechanism. Elevations in circulating acetate levels have been observed in acute stress conditions such as bacterial infections, where acetate facilitates memory T cell activity (<xref ref-type="bibr" rid="B54">54</xref>). Thus, the absolute increase in serum acetate levels in IgAN may not meet physiologic needs in acute inflammatory conditions, exacerbated by the downregulation of potential SCFA sensors in the glomerulus. The lack of correlation between fecal and serum acetate levels further demonstrates the complexity of acetate dynamics in IgAN. Previous studies in healthy individuals also did not report clear correlations between the two measurements despite rapid absorption of fecal acetate (<xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B55">55</xref>).</p>
<p>In the kidney, acetate signaling may modulate diverse molecular pathways, with potential links to pathophysiologic processes underlying glomerular diseases. One possibly relevant mechanism is the nuclear transcription factor kappa B (NF-&#x3ba;B) pathway, a key regulator of inflammation across glomerular diseases and CKD (<xref ref-type="bibr" rid="B56">56</xref>&#x2013;<xref ref-type="bibr" rid="B58">58</xref>). SCFA-activated GPR43 inhibits the NF-&#x3ba;B pathway and oxidative stress in DN, suggesting protective actions of acetate (<xref ref-type="bibr" rid="B59">59</xref>). At the same time, SCFAs can also amplify signaling from aryl hydrocarbon receptors, which can stimulate NF-&#x3ba;B-driven inflammation and suppress Nrf2 antioxidant pathways (<xref ref-type="bibr" rid="B60">60</xref>, <xref ref-type="bibr" rid="B61">61</xref>). Acetate may also affect the kidney by modulating the renin-angiotensin system. Given the increased circulating acetate levels in IgAN, Olfr78 in the juxtaglomerular apparatus could be highly activated, promoting renin secretion and leading to glomerular hypertension. Indeed, a study of early DN identified elevated serum acetate levels in a rat model and suggested that excess acetate may promote kidney injury through the renin-angiotensin system (<xref ref-type="bibr" rid="B62">62</xref>). Also downstream of the renin-angiotensin system is the Wnt/&#x3b2;-catenin pathway, whose persistent activation can lead to kidney fibrosis in glomerular diseases and CKD (<xref ref-type="bibr" rid="B63">63</xref>, <xref ref-type="bibr" rid="B64">64</xref>). Conversely, the counterbalancing effects of GPR41 on blood pressure, together with the downregulation of Olfr78, could blunt or even reverse these effects on the regulation of renin (<xref ref-type="bibr" rid="B65">65</xref>). As such, renal acetate signaling in IgAN may affect multiple molecular mechanisms, whose contributions to pathophysiology are likely context dependent.</p>
<p>Beyond its effects on glomerular inflammation, acetate may also contribute to the pathophysiology of IgAN through signaling in other cell populations. Although not directly addressed by the current analysis, earlier <italic>in vivo</italic> studies have suggested that acetate can regulate gut mucosal immune cells. Specifically, acetate supplementation induced gut IgA production and regulated IgA reactivity to microbes through stimulation of dendritic cells, which promote IgA class switching and gut homing in B cells (<xref ref-type="bibr" rid="B66">66</xref>). In certain contexts, acetate can also induce dendritic cells to produce B-cell activating factor (BAFF) (<xref ref-type="bibr" rid="B66">66</xref>, <xref ref-type="bibr" rid="B67">67</xref>), an emerging therapeutic target whose levels are elevated in IgAN (<xref ref-type="bibr" rid="B14">14</xref>). In addition, acetate stimulates CD4<sup>+</sup>CCR6<sup>+</sup> T follicular helper-like cells by promoting CCL20 production in colonic epithelial cells, regulating T cell-dependent IgA production in germinal centers by modulating Toll-like receptor (TLR) signaling (<xref ref-type="bibr" rid="B68">68</xref>). This may also be relevant to IgAN pathogenesis, as a recent study found that transplanting gut microbiota from IgAN patients into mice activates TLR4 signaling and induces the disease phenotype, while TLR4 inhibition suppresses Gd-IgA1 production (<xref ref-type="bibr" rid="B69">69</xref>). In all, acetate can modulate IgA biology through its interactions with gut immune cells, such as dendritic cells and helper T cells, which may have potential relevance to the pathogenesis of IgAN.</p>
<p>Recent studies associate gut dysbiosis and metabolite dysregulation with kidney injury across glomerular diseases. Uremic toxin generation and impaired SCFA production, along with intestinal barrier dysfunction, have been identified as major pathways whereby gut dysbiosis contribute to CKD (<xref ref-type="bibr" rid="B70">70</xref>). The gut microbiome in MN shows reductions in <italic>Lactobacillus</italic>, whose tryptophan-derived metabolites can attenuate kidney damage by inhibition of aryl hydrocarbon receptor signaling (<xref ref-type="bibr" rid="B71">71</xref>). Significant gut dysbiosis was also observed in MCD that includes decreased abundance of the butyrate producer <italic>Faecalibacterium</italic> (<xref ref-type="bibr" rid="B72">72</xref>). As for DN, the gut microbiome is associated with multiple potentially pathogenic mechanisms including increased endotoxin levels, decreased SCFA levels, and dysregulated bile acid metabolism (<xref ref-type="bibr" rid="B73">73</xref>). As such, SCFAs are associated with multiple kidney diseases, typically showing reduced production, but their mechanistic roles remain incompletely defined.</p>
<p>SCFAs, in particular acetate, may therefore play a disease-specific role in IgAN. Our analysis suggests an overall increased activity of acetate metabolism in the gut, where it can boost IgA production and reactivity as previously discussed. At the same time, downregulation of genes responsible for SCFA transport and sensing in the glomerulus would limit acetate uptake and signaling, which can contribute to glomerular injury through impaired regulation of anti-inflammatory pathways, disruption of renin signaling, and promotion of local metabolic stress. The observed elevation in serum acetate may represent both a systemic response to inflammation and a compensatory adaptation to defective acetate signaling in the kidney.</p>
<p>Human studies demonstrate the clinical relevance of gut dysbiosis in IgAN, but the contribution of SCFAs such as acetate remains to be established. Gut microbiota profile could predict treatment response in IgAN (<xref ref-type="bibr" rid="B74">74</xref>), and a pilot trial suggested fecal microbiota transplantation (FMT) may serve as an adjunctive treatment (<xref ref-type="bibr" rid="B75">75</xref>). Nonetheless, despite several reports of decreased serum and fecal acetate levels in IgAN and in broader CKD (<xref ref-type="bibr" rid="B49">49</xref>, <xref ref-type="bibr" rid="B76">76</xref>), SCFAs were not among the intestinal metabolites altered by FMT in IgAN in the pilot study. Adding to this complexity, our glomerular transcriptomic data indicated that acetate signaling in the kidney may depend on systemic availability as well as renal sensing capacity, highlighting the need to assess associated receptor functions when interpreting SCFA biology in kidney disease.</p>
<p>The current study has several limitations. First, the 16S rRNA data had limited resolution. Taxonomic annotation was restricted to the genus level, and certain taxa may not have been detected, particularly archaeal species for which the primer designs and taxonomic databases are less optimized. Functional annotation was also performed indirectly through PICRUSt2, which first derives the predicted metagenome from the 16S data and then algorithmically infers pathway composition. Further validation through metagenomic sequencing and functional assays is needed to verify the observed genus- and pathway-level associations. Second, due to the relatively low number of reads in our spatial transcriptomics data, we could not reliably localize gene expression patterns within the glomerulus, and some genes with low expression levels may have not been detected, as was likely the case for <italic>GPR41</italic>. Third, while efforts were made to select representative cases, our study may not reflect the entire spectrum of IgAN. The cases included in this study are all relatively young Koreans, which may not fully capture the nature of the disease in other ethnicities, especially given the known differences in clinical severity and gender distributions in Asian-Pacific populations (<xref ref-type="bibr" rid="B14">14</xref>). The low number of samples subject to glomerular transcriptomics also limits the generalizability of our findings. Finally, because this is a data-driven, observational study, the contributions of metabolites, glomerular genes, and gut microbial functions to IgAN pathophysiology remain to be established by experimental studies. Other SCFAs may also signal through the involved GPCRs and contribute to the postulated mechanisms, and additional confounding factors, such as dietary patterns, could influence gut microbial composition as well as SCFA levels. There may also be important transcriptional and microbial characteristics not captured by our analysis due to the limited sample size and the study design, which compared IgAN with four different control groups separately to minimize false positive results.</p>
<p>In conclusion, we have identified elevations in gut microbial acetate production and consumption activities as well as glomerular downregulation of GPCR, SCFA transport, and galactosylation functions in IgAN. Our results suggest that acetate may contribute to the pathophysiology of IgAN by mediating the gut-kidney interaction through GPCR signaling.</p>
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<back>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The data presented in the study are deposited in the NCBI SRA repository, accession number PRJNA1399494.</p></sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The studies involving humans were approved by Seoul National University Hospital. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.</p></sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>JHK: Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Data curation, Formal Analysis, Investigation, Methodology, Software, Visualization. SP: Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Visualization. MK: Writing &#x2013; review &amp; editing, Formal Analysis, Investigation, Methodology, Resources, Software. JP: Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Investigation, Resources. JL: Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Investigation, Resources. HC: Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Investigation, Resources. JEK: Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Investigation, Resources. HN: Writing &#x2013; review &amp; editing, Formal Analysis, Investigation, Methodology, Resources, Software. SP: Writing &#x2013; review &amp; editing, Conceptualization, Formal Analysis, Investigation, Methodology, Resources. KM: Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Investigation, Methodology, Resources. HK: Writing &#x2013; review &amp; editing, Conceptualization, Investigation, Methodology, Resources, Software. YK: Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Investigation, Methodology, Resources. DKK: Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Investigation, Methodology, Resources. HL: Writing &#x2013; review &amp; editing, Writing &#x2013; original draft, Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision. DK: Writing &#x2013; review &amp; editing, Formal Analysis, Investigation, Methodology, Resources. ML: Writing &#x2013; review &amp; editing, Formal Analysis, Investigation, Methodology, Resources.</p></sec>
<ack>
<title>Acknowledgments</title>
<p>The Biospecimens and data used for this study were provided by the Biobank of Seoul National University Hospital, a member of the Korea Biobank Network (project No. 2024ER050800).</p>
</ack>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p></sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p></sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fimmu.2025.1665585/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fimmu.2025.1665585/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="DataSheet1.pdf" id="SM1" mimetype="application/pdf"/>
<supplementary-material xlink:href="Table1.xlsx" id="SM2" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/></sec>
<ref-list>
<title>References</title>
<ref id="B1">
<label>1</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Li</surname> <given-names>Z</given-names></name>
<name><surname>He</surname> <given-names>R</given-names></name>
<name><surname>Wang</surname> <given-names>Y</given-names></name>
<name><surname>Qu</surname> <given-names>Z</given-names></name>
<name><surname>Liu</surname> <given-names>J</given-names></name>
<name><surname>Yu</surname> <given-names>R</given-names></name>
<etal/>
</person-group>. 
<article-title>Global trends of chronic kidney disease from 1990 to 2021: A systematic analysis for the global burden of disease study 2021</article-title>. <source>BMC Nephrol</source>. (<year>2025</year>) <volume>26</volume>:<fpage>385</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1186/s12882-025-04309-7</pub-id>, PMID: <pub-id pub-id-type="pmid">40660180</pub-id>
</mixed-citation>
</ref>
<ref id="B2">
<label>2</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zhu</surname> <given-names>J</given-names></name>
<name><surname>Fu</surname> <given-names>Y</given-names></name>
<name><surname>Olovo</surname> <given-names>CV</given-names></name>
<name><surname>Xu</surname> <given-names>J</given-names></name>
<name><surname>Wu</surname> <given-names>Q</given-names></name>
<name><surname>Wei</surname> <given-names>W</given-names></name>
<etal/>
</person-group>. 
<article-title>The influence of gut microbiota on the gut-brain-kidney axis and its implications for chronic kidney disease</article-title>. <source>Front Microbiol</source>. (<year>2025</year>) <volume>16</volume>:<elocation-id>1535356</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fmicb.2025.1535356</pub-id>, PMID: <pub-id pub-id-type="pmid">40703243</pub-id>
</mixed-citation>
</ref>
<ref id="B3">
<label>3</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Tao</surname> <given-names>P</given-names></name>
<name><surname>Huo</surname> <given-names>J</given-names></name>
<name><surname>Chen</surname> <given-names>L</given-names></name>
</person-group>. 
<article-title>Bibliometric analysis of the relationship between gut microbiota and chronic kidney disease from 2001&#x2013;2022</article-title>. <source>Integr Med Nephrol Andrology</source>. (<year>2024</year>) <volume>11</volume>:<fpage>e00017</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1097/imna-d-23-00017</pub-id>
</mixed-citation>
</ref>
<ref id="B4">
<label>4</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Miao</surname> <given-names>H</given-names></name>
<name><surname>Liu</surname> <given-names>F</given-names></name>
<name><surname>Wang</surname> <given-names>YN</given-names></name>
<name><surname>Yu</surname> <given-names>XY</given-names></name>
<name><surname>Zhuang</surname> <given-names>S</given-names></name>
<name><surname>Guo</surname> <given-names>Y</given-names></name>
<etal/>
</person-group>. 
<article-title>Targeting <italic>lactobacillus johnsonii</italic> to reverse chronic kidney disease</article-title>. <source>Signal Transduct Target Ther</source>. (<year>2024</year>) <volume>9</volume>:<fpage>195</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41392-024-01913-1</pub-id>, PMID: <pub-id pub-id-type="pmid">39098923</pub-id>
</mixed-citation>
</ref>
<ref id="B5">
<label>5</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zhang</surname> <given-names>L</given-names></name>
<name><surname>Hu</surname> <given-names>L</given-names></name>
<name><surname>Tan</surname> <given-names>L</given-names></name>
<name><surname>Zhang</surname> <given-names>Z</given-names></name>
<name><surname>Chen</surname> <given-names>M</given-names></name>
<name><surname>Gan</surname> <given-names>W</given-names></name>
<etal/>
</person-group>. 
<article-title>The dysbiosis of gut microbiota and dysregulation of metabolites in iga nephropathy and membranous nephropathy</article-title>. <source>Front Med (Lausanne)</source>. (<year>2025</year>) <volume>12</volume>:<elocation-id>1618947</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fmed.2025.1618947</pub-id>, PMID: <pub-id pub-id-type="pmid">40740937</pub-id>
</mixed-citation>
</ref>
<ref id="B6">
<label>6</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Wang</surname> <given-names>X</given-names></name>
<name><surname>Liu</surname> <given-names>X</given-names></name>
<name><surname>Gong</surname> <given-names>F</given-names></name>
<name><surname>Jiang</surname> <given-names>Y</given-names></name>
<name><surname>Zhang</surname> <given-names>C</given-names></name>
<name><surname>Zhou</surname> <given-names>W</given-names></name>
<etal/>
</person-group>. 
<article-title>Targeting gut microbiota for diabetic nephropathy treatment: probiotics, dietary interventions, and fecal microbiota transplantation</article-title>. <source>Front Endocrinol (Lausanne)</source>. (<year>2025</year>) <volume>16</volume>:<elocation-id>1621968</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fendo.2025.1621968</pub-id>, PMID: <pub-id pub-id-type="pmid">40661744</pub-id>
</mixed-citation>
</ref>
<ref id="B7">
<label>7</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Lai</surname> <given-names>Y</given-names></name>
<name><surname>Zhu</surname> <given-names>Y</given-names></name>
<name><surname>Zhang</surname> <given-names>X</given-names></name>
<name><surname>Ding</surname> <given-names>S</given-names></name>
<name><surname>Wang</surname> <given-names>F</given-names></name>
<name><surname>Hao</surname> <given-names>J</given-names></name>
<etal/>
</person-group>. 
<article-title>Gut microbiota-derived metabolites: potential targets for cardiorenal syndrome</article-title>. <source>Pharmacol Res</source>. (<year>2025</year>) <volume>214</volume>:<elocation-id>107672</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.phrs.2025.107672</pub-id>, PMID: <pub-id pub-id-type="pmid">40010448</pub-id>
</mixed-citation>
</ref>
<ref id="B8">
<label>8</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Evenepoel</surname> <given-names>P</given-names></name>
<name><surname>Stenvinkel</surname> <given-names>P</given-names></name>
<name><surname>Shanahan</surname> <given-names>C</given-names></name>
<name><surname>Pacifici</surname> <given-names>R</given-names></name>
</person-group>. 
<article-title>Inflammation and gut dysbiosis as drivers of ckd-mbd</article-title>. <source>Nat Rev Nephrol</source>. (<year>2023</year>) <volume>19</volume>:<page-range>646&#x2013;57</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41581-023-00736-7</pub-id>, PMID: <pub-id pub-id-type="pmid">37488276</pub-id>
</mixed-citation>
</ref>
<ref id="B9">
<label>9</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Corradi</surname> <given-names>V</given-names></name>
<name><surname>Caprara</surname> <given-names>C</given-names></name>
<name><surname>Barzon</surname> <given-names>E</given-names></name>
<name><surname>Mattarollo</surname> <given-names>C</given-names></name>
<name><surname>Zanetti</surname> <given-names>F</given-names></name>
<name><surname>Ferrari</surname> <given-names>F</given-names></name>
<etal/>
</person-group>. 
<article-title>A possible role of P-cresyl sulfate and indoxyl sulfate as biomarkers in the prediction of renal function according to the gfr (G) categories</article-title>. <source>Integr Med Nephrol Andrology</source>. (<year>2024</year>) <volume>11</volume>:<fpage>e24</fpage>&#x2013;<lpage>00002</lpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1097/imna-d-24-00002</pub-id>
</mixed-citation>
</ref>
<ref id="B10">
<label>10</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Miao</surname> <given-names>H</given-names></name>
<name><surname>Zhang</surname> <given-names>SJ</given-names></name>
<name><surname>Wu</surname> <given-names>X</given-names></name>
<name><surname>Li</surname> <given-names>P</given-names></name>
<name><surname>Zhao</surname> <given-names>YY</given-names></name>
</person-group>. 
<article-title>Tryptophan metabolism as a target in gut microbiota, ageing and kidney disease</article-title>. <source>Int J Biol Sci</source>. (<year>2025</year>) <volume>21</volume>:<page-range>4374&#x2013;87</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.7150/ijbs.115359</pub-id>, PMID: <pub-id pub-id-type="pmid">40765836</pub-id>
</mixed-citation>
</ref>
<ref id="B11">
<label>11</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Cao</surname> <given-names>BN</given-names></name>
<name><surname>Zhang</surname> <given-names>CY</given-names></name>
<name><surname>Wang</surname> <given-names>Z</given-names></name>
<name><surname>Wang</surname> <given-names>YX</given-names></name>
</person-group>. 
<article-title>Causal relationship between 412 gut microbiota, 1,400 blood metabolites, and diabetic nephropathy: A randomized mendelian study</article-title>. <source>Front Endocrinol (Lausanne)</source>. (<year>2024</year>) <volume>15</volume>:<elocation-id>1450428</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fendo.2024.1450428</pub-id>, PMID: <pub-id pub-id-type="pmid">39897958</pub-id>
</mixed-citation>
</ref>
<ref id="B12">
<label>12</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Song</surname> <given-names>S</given-names></name>
<name><surname>Ning</surname> <given-names>L</given-names></name>
<name><surname>Yu</surname> <given-names>J</given-names></name>
</person-group>. 
<article-title>Elucidating the causal relationship between gut microbiota, metabolites, and diabetic nephropathy in european patients: revelations from genome-wide bidirectional mendelian randomization analysis</article-title>. <source>Front Endocrinol (Lausanne)</source>. (<year>2024</year>) <volume>15</volume>:<elocation-id>1391891</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fendo.2024.1391891</pub-id>, PMID: <pub-id pub-id-type="pmid">39845884</pub-id>
</mixed-citation>
</ref>
<ref id="B13">
<label>13</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Gesualdo</surname> <given-names>L</given-names></name>
<name><surname>Di Leo</surname> <given-names>V</given-names></name>
<name><surname>Coppo</surname> <given-names>R</given-names></name>
</person-group>. 
<article-title>The mucosal immune system and iga nephropathy</article-title>. <source>Semin Immunopathol</source>. (<year>2021</year>) <volume>43</volume>:<page-range>657&#x2013;68</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1007/s00281-021-00871-y</pub-id>, PMID: <pub-id pub-id-type="pmid">34642783</pub-id>
</mixed-citation>
</ref>
<ref id="B14">
<label>14</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Cheung</surname> <given-names>CK</given-names></name>
<name><surname>Alexander</surname> <given-names>S</given-names></name>
<name><surname>Reich</surname> <given-names>HN</given-names></name>
<name><surname>Selvaskandan</surname> <given-names>H</given-names></name>
<name><surname>Zhang</surname> <given-names>H</given-names></name>
<name><surname>Barratt</surname> <given-names>J</given-names></name>
</person-group>. 
<article-title>The pathogenesis of iga nephropathy and implications for treatment</article-title>. <source>Nat Rev Nephrol</source>. (<year>2025</year>) <volume>21</volume>:<fpage>9</fpage>&#x2013;<lpage>23</lpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41581-024-00885-3</pub-id>, PMID: <pub-id pub-id-type="pmid">39232245</pub-id>
</mixed-citation>
</ref>
<ref id="B15">
<label>15</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Kiryluk</surname> <given-names>K</given-names></name>
<name><surname>Sanchez-Rodriguez</surname> <given-names>E</given-names></name>
<name><surname>Zhou</surname> <given-names>XJ</given-names></name>
<name><surname>Zanoni</surname> <given-names>F</given-names></name>
<name><surname>Liu</surname> <given-names>L</given-names></name>
<name><surname>Mladkova</surname> <given-names>N</given-names></name>
<etal/>
</person-group>. 
<article-title>Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for iga nephropathy</article-title>. <source>Nat Genet</source>. (<year>2023</year>) <volume>55</volume>:<page-range>1091&#x2013;105</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41588-023-01422-x</pub-id>, PMID: <pub-id pub-id-type="pmid">37337107</pub-id>
</mixed-citation>
</ref>
<ref id="B16">
<label>16</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Kiryluk</surname> <given-names>K</given-names></name>
<name><surname>Li</surname> <given-names>Y</given-names></name>
<name><surname>Scolari</surname> <given-names>F</given-names></name>
<name><surname>Sanna-Cherchi</surname> <given-names>S</given-names></name>
<name><surname>Choi</surname> <given-names>M</given-names></name>
<name><surname>Verbitsky</surname> <given-names>M</given-names></name>
<etal/>
</person-group>. 
<article-title>Discovery of new risk loci for iga nephropathy implicates genes involved in immunity against intestinal pathogens</article-title>. <source>Nat Genet</source>. (<year>2014</year>) <volume>46</volume>:<page-range>1187&#x2013;96</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/ng.3118</pub-id>, PMID: <pub-id pub-id-type="pmid">25305756</pub-id>
</mixed-citation>
</ref>
<ref id="B17">
<label>17</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Lafayette</surname> <given-names>R</given-names></name>
<name><surname>Kristensen</surname> <given-names>J</given-names></name>
<name><surname>Stone</surname> <given-names>A</given-names></name>
<name><surname>Floege</surname> <given-names>J</given-names></name>
<name><surname>Tesar</surname> <given-names>V</given-names></name>
<name><surname>Trimarchi</surname> <given-names>H</given-names></name>
<etal/>
</person-group>. 
<article-title>Efficacy and safety of a targeted-release formulation of budesonide in patients with primary iga nephropathy (Nefigard): 2-year results from a randomised phase 3 trial</article-title>. <source>Lancet</source>. (<year>2023</year>) <volume>402</volume>:<page-range>859&#x2013;70</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/S0140-6736(23)01554-4</pub-id>, PMID: <pub-id pub-id-type="pmid">37591292</pub-id>
</mixed-citation>
</ref>
<ref id="B18">
<label>18</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Feriozzi</surname> <given-names>S</given-names></name>
<name><surname>Polci</surname> <given-names>R</given-names></name>
</person-group>. 
<article-title>The role of tonsillectomy in iga nephropathy</article-title>. <source>J Nephrol</source>. (<year>2016</year>) <volume>29</volume>:<page-range>13&#x2013;9</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1007/s40620-015-0247-4</pub-id>, PMID: <pub-id pub-id-type="pmid">26582216</pub-id>
</mixed-citation>
</ref>
<ref id="B19">
<label>19</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Dong</surname> <given-names>Z</given-names></name>
<name><surname>Zhang</surname> <given-names>R</given-names></name>
<name><surname>Shen</surname> <given-names>L</given-names></name>
<name><surname>Ji</surname> <given-names>HF</given-names></name>
<name><surname>He</surname> <given-names>H</given-names></name>
<name><surname>Ji</surname> <given-names>X</given-names></name>
<etal/>
</person-group>. 
<article-title>Gut microbiota and immunoglobulin a nephropathy: exploration of dietary intervention and treatment strategies</article-title>. <source>Food Sci Nutr</source>. (<year>2025</year>) <volume>13</volume>:<fpage>e70218</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1002/fsn3.70218</pub-id>, PMID: <pub-id pub-id-type="pmid">40321610</pub-id>
</mixed-citation>
</ref>
<ref id="B20">
<label>20</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Pattrapornpisut</surname> <given-names>P</given-names></name>
<name><surname>Avila-Casado</surname> <given-names>C</given-names></name>
<name><surname>Reich</surname> <given-names>HN</given-names></name>
</person-group>. 
<article-title>Iga nephropathy: core curriculum 2021</article-title>. <source>Am J Kidney Dis</source>. (<year>2021</year>) <volume>78</volume>:<page-range>429&#x2013;41</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1053/j.ajkd.2021.01.024</pub-id>, PMID: <pub-id pub-id-type="pmid">34247883</pub-id>
</mixed-citation>
</ref>
<ref id="B21">
<label>21</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Luvizotto</surname> <given-names>MJ</given-names></name>
<name><surname>Menezes-Silva</surname> <given-names>L</given-names></name>
<name><surname>Woronik</surname> <given-names>V</given-names></name>
<name><surname>Monteiro</surname> <given-names>RC</given-names></name>
<name><surname>Camara</surname> <given-names>NOS</given-names></name>
</person-group>. 
<article-title>Gut-kidney axis in iga nephropathy: role on mesangial cell metabolism and inflammation</article-title>. <source>Front Cell Dev Biol</source>. (<year>2022</year>) <volume>10</volume>:<elocation-id>993716</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fcell.2022.993716</pub-id>, PMID: <pub-id pub-id-type="pmid">36467425</pub-id>
</mixed-citation>
</ref>
<ref id="B22">
<label>22</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Popova</surname> <given-names>A</given-names></name>
<name><surname>Slisere</surname> <given-names>B</given-names></name>
<name><surname>Racenis</surname> <given-names>K</given-names></name>
<name><surname>Kuzema</surname> <given-names>V</given-names></name>
<name><surname>Karklins</surname> <given-names>R</given-names></name>
<name><surname>Saulite</surname> <given-names>M</given-names></name>
<etal/>
</person-group>. 
<article-title>Iga class-switched cd27-cd21+ B cells in iga nephropathy</article-title>. <source>Nephrol Dial Transplant</source>. (<year>2025</year>) <volume>40</volume>:<page-range>505&#x2013;15</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1093/ndt/gfae173</pub-id>, PMID: <pub-id pub-id-type="pmid">39020236</pub-id>
</mixed-citation>
</ref>
<ref id="B23">
<label>23</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Sanchez-Russo</surname> <given-names>L</given-names></name>
<name><surname>Rajasekaran</surname> <given-names>A</given-names></name>
<name><surname>Bin</surname> <given-names>S</given-names></name>
<name><surname>Faith</surname> <given-names>J</given-names></name>
<name><surname>Cravedi</surname> <given-names>P</given-names></name>
</person-group>. 
<article-title>The gut and kidney crosstalk in immunoglobulin a nephropathy</article-title>. <source>Kidney360</source>. (<year>2022</year>) <volume>3</volume>:<page-range>1630&#x2013;9</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.34067/KID.0002382022</pub-id>, PMID: <pub-id pub-id-type="pmid">36245664</pub-id>
</mixed-citation>
</ref>
<ref id="B24">
<label>24</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zhao</surname> <given-names>J</given-names></name>
<name><surname>Bai</surname> <given-names>M</given-names></name>
<name><surname>Ning</surname> <given-names>X</given-names></name>
<name><surname>Qin</surname> <given-names>Y</given-names></name>
<name><surname>Wang</surname> <given-names>Y</given-names></name>
<name><surname>Yu</surname> <given-names>Z</given-names></name>
<etal/>
</person-group>. 
<article-title>Expansion of escherichia-shigella in gut is associated with the onset and response to immunosuppressive therapy of iga nephropathy</article-title>. <source>J Am Soc Nephrol</source>. (<year>2022</year>) <volume>33</volume>:<page-range>2276&#x2013;92</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1681/ASN.2022020189</pub-id>, PMID: <pub-id pub-id-type="pmid">36041791</pub-id>
</mixed-citation>
</ref>
<ref id="B25">
<label>25</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Park</surname> <given-names>JI</given-names></name>
<name><surname>Kim</surname> <given-names>TY</given-names></name>
<name><surname>Oh</surname> <given-names>B</given-names></name>
<name><surname>Cho</surname> <given-names>H</given-names></name>
<name><surname>Kim</surname> <given-names>JE</given-names></name>
<name><surname>Yoo</surname> <given-names>SH</given-names></name>
<etal/>
</person-group>. 
<article-title>Comparative analysis of the tonsillar microbiota in iga nephropathy and other glomerular diseases</article-title>. <source>Sci Rep</source>. (<year>2020</year>) <volume>10</volume>:<fpage>16206</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41598-020-73035-x</pub-id>, PMID: <pub-id pub-id-type="pmid">33004860</pub-id>
</mixed-citation>
</ref>
<ref id="B26">
<label>26</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Jain</surname> <given-names>S</given-names></name>
<name><surname>Eadon</surname> <given-names>MT</given-names></name>
</person-group>. 
<article-title>Spatial transcriptomics in health and disease</article-title>. <source>Nat Rev Nephrol</source>. (<year>2024</year>) <volume>20</volume>:<page-range>659&#x2013;71</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41581-024-00841-1</pub-id>, PMID: <pub-id pub-id-type="pmid">38719971</pub-id>
</mixed-citation>
</ref>
<ref id="B27">
<label>27</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Park</surname> <given-names>S</given-names></name>
<name><surname>Kang</surname> <given-names>M</given-names></name>
<name><surname>Kim</surname> <given-names>YC</given-names></name>
<name><surname>Kim</surname> <given-names>DK</given-names></name>
<name><surname>Oh</surname> <given-names>KH</given-names></name>
<name><surname>Joo</surname> <given-names>KW</given-names></name>
<etal/>
</person-group>. 
<article-title>Glomerular spatial transcriptomics of iga nephropathy according to the presence of mesangial proliferation</article-title>. <source>Sci Rep</source>. (<year>2024</year>) <volume>14</volume>:<fpage>2211</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41598-024-52581-8</pub-id>, PMID: <pub-id pub-id-type="pmid">38278877</pub-id>
</mixed-citation>
</ref>
<ref id="B28">
<label>28</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Kang</surname> <given-names>E</given-names></name>
<name><surname>Kim</surname> <given-names>Y</given-names></name>
<name><surname>Kim</surname> <given-names>YC</given-names></name>
<name><surname>Kim</surname> <given-names>E</given-names></name>
<name><surname>Lee</surname> <given-names>N</given-names></name>
<name><surname>Kim</surname> <given-names>Y</given-names></name>
<etal/>
</person-group>. 
<article-title>Biobanking for glomerular diseases: A study design and protocol for korea renal biobank network system toward next-generation analysis (Kornerstone)</article-title>. <source>BMC Nephrol</source>. (<year>2020</year>) <volume>21</volume>:<fpage>367</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1186/s12882-020-02016-z</pub-id>, PMID: <pub-id pub-id-type="pmid">32842999</pub-id>
</mixed-citation>
</ref>
<ref id="B29">
<label>29</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Kim</surname> <given-names>JE</given-names></name>
<name><surname>Kim</surname> <given-names>HE</given-names></name>
<name><surname>Park</surname> <given-names>JI</given-names></name>
<name><surname>Cho</surname> <given-names>H</given-names></name>
<name><surname>Kwak</surname> <given-names>MJ</given-names></name>
<name><surname>Kim</surname> <given-names>BY</given-names></name>
<etal/>
</person-group>. 
<article-title>The association between gut microbiota and uremia of chronic kidney disease</article-title>. <source>Microorganisms</source>. (<year>2020</year>) <volume>8</volume>:<elocation-id>907</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3390/microorganisms8060907</pub-id>, PMID: <pub-id pub-id-type="pmid">32560104</pub-id>
</mixed-citation>
</ref>
<ref id="B30">
<label>30</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Callahan</surname> <given-names>BJ</given-names></name>
<name><surname>McMurdie</surname> <given-names>PJ</given-names></name>
<name><surname>Rosen</surname> <given-names>MJ</given-names></name>
<name><surname>Han</surname> <given-names>AW</given-names></name>
<name><surname>Johnson</surname> <given-names>AJ</given-names></name>
<name><surname>Holmes</surname> <given-names>SP</given-names></name>
</person-group>. 
<article-title>Dada2: high-resolution sample inference from illumina amplicon data</article-title>. <source>Nat Methods</source>. (<year>2016</year>) <volume>13</volume>:<page-range>581&#x2013;3</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/nmeth.3869</pub-id>, PMID: <pub-id pub-id-type="pmid">27214047</pub-id>
</mixed-citation>
</ref>
<ref id="B31">
<label>31</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Glockner</surname> <given-names>FO</given-names></name>
<name><surname>Yilmaz</surname> <given-names>P</given-names></name>
<name><surname>Quast</surname> <given-names>C</given-names></name>
<name><surname>Gerken</surname> <given-names>J</given-names></name>
<name><surname>Beccati</surname> <given-names>A</given-names></name>
<name><surname>Ciuprina</surname> <given-names>A</given-names></name>
<etal/>
</person-group>. 
<article-title>25 years of serving the community with ribosomal rna gene reference databases and tools</article-title>. <source>J Biotechnol</source>. (<year>2017</year>) <volume>261</volume>:<page-range>169&#x2013;76</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.jbiotec.2017.06.1198</pub-id>, PMID: <pub-id pub-id-type="pmid">28648396</pub-id>
</mixed-citation>
</ref>
<ref id="B32">
<label>32</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Douglas</surname> <given-names>GM</given-names></name>
<name><surname>Maffei</surname> <given-names>VJ</given-names></name>
<name><surname>Zaneveld</surname> <given-names>JR</given-names></name>
<name><surname>Yurgel</surname> <given-names>SN</given-names></name>
<name><surname>Brown</surname> <given-names>JR</given-names></name>
<name><surname>Taylor</surname> <given-names>CM</given-names></name>
<etal/>
</person-group>. 
<article-title>Picrust2 for prediction of metagenome functions</article-title>. <source>Nat Biotechnol</source>. (<year>2020</year>) <volume>38</volume>:<page-range>685&#x2013;8</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41587-020-0548-6</pub-id>, PMID: <pub-id pub-id-type="pmid">32483366</pub-id>
</mixed-citation>
</ref>
<ref id="B33">
<label>33</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Caspi</surname> <given-names>R</given-names></name>
<name><surname>Billington</surname> <given-names>R</given-names></name>
<name><surname>Ferrer</surname> <given-names>L</given-names></name>
<name><surname>Foerster</surname> <given-names>H</given-names></name>
<name><surname>Fulcher</surname> <given-names>CA</given-names></name>
<name><surname>Keseler</surname> <given-names>IM</given-names></name>
<etal/>
</person-group>. 
<article-title>The metacyc database of metabolic pathways and enzymes and the biocyc collection of pathway/genome databases</article-title>. <source>Nucleic Acids Res</source>. (<year>2016</year>) <volume>44</volume>:<page-range>D471&#x2013;80</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1093/nar/gkv1164</pub-id>, PMID: <pub-id pub-id-type="pmid">26527732</pub-id>
</mixed-citation>
</ref>
<ref id="B34">
<label>34</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Fernandes</surname> <given-names>AD</given-names></name>
<name><surname>Macklaim</surname> <given-names>JM</given-names></name>
<name><surname>Linn</surname> <given-names>TG</given-names></name>
<name><surname>Reid</surname> <given-names>G</given-names></name>
<name><surname>Gloor</surname> <given-names>GB</given-names></name>
</person-group>. 
<article-title>Anova-like differential expression (Aldex) analysis for mixed population rna-seq</article-title>. <source>PloS One</source>. (<year>2013</year>) <volume>8</volume>:<fpage>e67019</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1371/journal.pone.0067019</pub-id>, PMID: <pub-id pub-id-type="pmid">23843979</pub-id>
</mixed-citation>
</ref>
<ref id="B35">
<label>35</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Love</surname> <given-names>MI</given-names></name>
<name><surname>Huber</surname> <given-names>W</given-names></name>
<name><surname>Anders</surname> <given-names>S</given-names></name>
</person-group>. 
<article-title>Moderated estimation of fold change and dispersion for rna-seq data with deseq2</article-title>. <source>Genome Biol</source>. (<year>2014</year>) <volume>15</volume>:<elocation-id>550</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1186/s13059-014-0550-8</pub-id>, PMID: <pub-id pub-id-type="pmid">25516281</pub-id>
</mixed-citation>
</ref>
<ref id="B36">
<label>36</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Chen</surname> <given-names>J</given-names></name>
<name><surname>Bardes</surname> <given-names>EE</given-names></name>
<name><surname>Aronow</surname> <given-names>BJ</given-names></name>
<name><surname>Jegga</surname> <given-names>AG</given-names></name>
</person-group>. 
<article-title>Toppgene suite for gene list enrichment analysis and candidate gene prioritization</article-title>. <source>Nucleic Acids Res</source>. (<year>2009</year>) <volume>37</volume>:<page-range>W305&#x2013;11</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1093/nar/gkp427</pub-id>, PMID: <pub-id pub-id-type="pmid">19465376</pub-id>
</mixed-citation>
</ref>
<ref id="B37">
<label>37</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Meng</surname> <given-names>X</given-names></name>
<name><surname>Pang</surname> <given-names>H</given-names></name>
<name><surname>Sun</surname> <given-names>F</given-names></name>
<name><surname>Jin</surname> <given-names>X</given-names></name>
<name><surname>Wang</surname> <given-names>B</given-names></name>
<name><surname>Yao</surname> <given-names>K</given-names></name>
<etal/>
</person-group>. 
<article-title>Simultaneous 3-nitrophenylhydrazine derivatization strategy of carbonyl, carboxyl and phosphoryl submetabolome for lc-ms/ms-based targeted metabolomics with improved sensitivity and coverage</article-title>. <source>Anal Chem</source>. (<year>2021</year>) <volume>93</volume>:<page-range>10075&#x2013;83</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1021/acs.analchem.1c00767</pub-id>, PMID: <pub-id pub-id-type="pmid">34270209</pub-id>
</mixed-citation>
</ref>
<ref id="B38">
<label>38</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Oksanen</surname> <given-names>J</given-names></name>
<name><surname>Simpson</surname> <given-names>G</given-names></name>
<name><surname>Blanchet</surname> <given-names>F</given-names></name>
<name><surname>Kindt</surname> <given-names>R</given-names></name>
<name><surname>Legendre</surname> <given-names>P</given-names></name>
<name><surname>Minchin</surname> <given-names>P</given-names></name>
<etal/>
</person-group>. 
<article-title>Vegan: community ecology package</article-title>. (<year>2025</year>).
</mixed-citation>
</ref>
<ref id="B39">
<label>39</label>
<mixed-citation publication-type="book">
<person-group person-group-type="author">
<name><surname>Kassambara</surname> <given-names>A</given-names></name>
</person-group>. <source>Ggpubr: 'Ggplot2' Based publication ready plots</source>. (<year>2025</year>).
</mixed-citation>
</ref>
<ref id="B40">
<label>40</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Granger</surname> <given-names>B</given-names></name>
<name><surname>Berto</surname> <given-names>S</given-names></name>
</person-group>. 
<article-title>Sctoppr: A coding-friendly R interface to toppgene</article-title>. <source>Bioinformatics</source>. (<year>2024</year>) <volume>40</volume>. doi:&#xa0;<pub-id pub-id-type="doi">10.1093/bioinformatics/btae582</pub-id>, PMID: <pub-id pub-id-type="pmid">39340795</pub-id>
</mixed-citation>
</ref>
<ref id="B41">
<label>41</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Hosmer</surname> <given-names>J</given-names></name>
<name><surname>McEwan</surname> <given-names>AG</given-names></name>
<name><surname>Kappler</surname> <given-names>U</given-names></name>
</person-group>. 
<article-title>Bacterial acetate metabolism and its influence on human epithelia</article-title>. <source>Emerg Top Life Sci</source>. (<year>2024</year>) <volume>8</volume>:<fpage>1</fpage>&#x2013;<lpage>13</lpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1042/ETLS20220092</pub-id>, PMID: <pub-id pub-id-type="pmid">36945843</pub-id>
</mixed-citation>
</ref>
<ref id="B42">
<label>42</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zhang</surname> <given-names>D</given-names></name>
<name><surname>Jian</surname> <given-names>YP</given-names></name>
<name><surname>Zhang</surname> <given-names>YN</given-names></name>
<name><surname>Li</surname> <given-names>Y</given-names></name>
<name><surname>Gu</surname> <given-names>LT</given-names></name>
<name><surname>Sun</surname> <given-names>HH</given-names></name>
<etal/>
</person-group>. 
<article-title>Short-chain fatty acids in diseases</article-title>. <source>Cell Commun Signal</source>. (<year>2023</year>) <volume>21</volume>:<fpage>212</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1186/s12964-023-01219-9</pub-id>, PMID: <pub-id pub-id-type="pmid">37596634</pub-id>
</mixed-citation>
</ref>
<ref id="B43">
<label>43</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Manokasemsan</surname> <given-names>W</given-names></name>
<name><surname>Jariyasopit</surname> <given-names>N</given-names></name>
<name><surname>Poungsombat</surname> <given-names>P</given-names></name>
<name><surname>Kaewnarin</surname> <given-names>K</given-names></name>
<name><surname>Wanichthanarak</surname> <given-names>K</given-names></name>
<name><surname>Kurilung</surname> <given-names>A</given-names></name>
<etal/>
</person-group>. 
<article-title>Quantifying fecal and plasma short-chain fatty acids in healthy thai individuals</article-title>. <source>Comput Struct Biotechnol J</source>. (<year>2024</year>) <volume>23</volume>:<page-range>2163&#x2013;72</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.csbj.2024.05.007</pub-id>, PMID: <pub-id pub-id-type="pmid">38827233</pub-id>
</mixed-citation>
</ref>
<ref id="B44">
<label>44</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Andrade-Oliveira</surname> <given-names>V</given-names></name>
<name><surname>Amano</surname> <given-names>MT</given-names></name>
<name><surname>Correa-Costa</surname> <given-names>M</given-names></name>
<name><surname>Castoldi</surname> <given-names>A</given-names></name>
<name><surname>Felizardo</surname> <given-names>RJ</given-names></name>
<name><surname>de Almeida</surname> <given-names>DC</given-names></name>
<etal/>
</person-group>. 
<article-title>Gut bacteria products prevent aki induced by ischemia-reperfusion</article-title>. <source>J Am Soc Nephrol</source>. (<year>2015</year>) <volume>26</volume>:<page-range>1877&#x2013;88</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1681/ASN.2014030288</pub-id>, PMID: <pub-id pub-id-type="pmid">25589612</pub-id>
</mixed-citation>
</ref>
<ref id="B45">
<label>45</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Kawabata</surname> <given-names>C</given-names></name>
<name><surname>Hirakawa</surname> <given-names>Y</given-names></name>
<name><surname>Inagi</surname> <given-names>R</given-names></name>
<name><surname>Nangaku</surname> <given-names>M</given-names></name>
</person-group>. 
<article-title>Acetate attenuates kidney fibrosis in an oxidative stress-dependent manner</article-title>. <source>Physiol Rep</source>. (<year>2023</year>) <volume>11</volume>:<fpage>e15774</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.14814/phy2.15774</pub-id>, PMID: <pub-id pub-id-type="pmid">37463875</pub-id>
</mixed-citation>
</ref>
<ref id="B46">
<label>46</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Tan</surname> <given-names>J</given-names></name>
<name><surname>Dong</surname> <given-names>L</given-names></name>
<name><surname>Jiang</surname> <given-names>Z</given-names></name>
<name><surname>Tan</surname> <given-names>L</given-names></name>
<name><surname>Luo</surname> <given-names>X</given-names></name>
<name><surname>Pei</surname> <given-names>G</given-names></name>
<etal/>
</person-group>. 
<article-title>Probiotics ameliorate iga nephropathy by improving gut dysbiosis and blunting nlrp3 signaling</article-title>. <source>J Transl Med</source>. (<year>2022</year>) <volume>20</volume>:<fpage>382</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1186/s12967-022-03585-3</pub-id>, PMID: <pub-id pub-id-type="pmid">36038927</pub-id>
</mixed-citation>
</ref>
<ref id="B47">
<label>47</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Chaudhary</surname> <given-names>PP</given-names></name>
<name><surname>Conway</surname> <given-names>PL</given-names></name>
<name><surname>Schlundt</surname> <given-names>J</given-names></name>
</person-group>. 
<article-title>Methanogens in humans: potentially beneficial or harmful for health</article-title>. <source>Appl Microbiol Biotechnol</source>. (<year>2018</year>) <volume>102</volume>:<page-range>3095&#x2013;104</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1007/s00253-018-8871-2</pub-id>, PMID: <pub-id pub-id-type="pmid">29497795</pub-id>
</mixed-citation>
</ref>
<ref id="B48">
<label>48</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Borrel</surname> <given-names>G</given-names></name>
<name><surname>Brugere</surname> <given-names>JF</given-names></name>
<name><surname>Gribaldo</surname> <given-names>S</given-names></name>
<name><surname>Schmitz</surname> <given-names>RA</given-names></name>
<name><surname>Moissl-Eichinger</surname> <given-names>C</given-names></name>
</person-group>. 
<article-title>The host-associated archaeome</article-title>. <source>Nat Rev Microbiol</source>. (<year>2020</year>) <volume>18</volume>:<page-range>622&#x2013;36</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41579-020-0407-y</pub-id>, PMID: <pub-id pub-id-type="pmid">32690877</pub-id>
</mixed-citation>
</ref>
<ref id="B49">
<label>49</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Chai</surname> <given-names>L</given-names></name>
<name><surname>Luo</surname> <given-names>Q</given-names></name>
<name><surname>Cai</surname> <given-names>K</given-names></name>
<name><surname>Wang</surname> <given-names>K</given-names></name>
<name><surname>Xu</surname> <given-names>B</given-names></name>
</person-group>. 
<article-title>Reduced fecal short-chain fatty acids levels and the relationship with gut microbiota in iga nephropathy</article-title>. <source>BMC Nephrol</source>. (<year>2021</year>) <volume>22</volume>:<fpage>209</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1186/s12882-021-02414-x</pub-id>, PMID: <pub-id pub-id-type="pmid">34082732</pub-id>
</mixed-citation>
</ref>
<ref id="B50">
<label>50</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Foresto-Neto</surname> <given-names>O</given-names></name>
<name><surname>Ghirotto</surname> <given-names>B</given-names></name>
<name><surname>Camara</surname> <given-names>NOS</given-names></name>
</person-group>. 
<article-title>Renal sensing of bacterial metabolites in the gut-kidney axis</article-title>. <source>Kidney360</source>. (<year>2021</year>) <volume>2</volume>:<page-range>1501&#x2013;9</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.34067/KID.0000292021</pub-id>, PMID: <pub-id pub-id-type="pmid">35373097</pub-id>
</mixed-citation>
</ref>
<ref id="B51">
<label>51</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Nigam</surname> <given-names>SK</given-names></name>
<name><surname>Bush</surname> <given-names>KT</given-names></name>
<name><surname>Martovetsky</surname> <given-names>G</given-names></name>
<name><surname>Ahn</surname> <given-names>SY</given-names></name>
<name><surname>Liu</surname> <given-names>HC</given-names></name>
<name><surname>Richard</surname> <given-names>E</given-names></name>
<etal/>
</person-group>. 
<article-title>The organic anion transporter (Oat) family: A systems biology perspective</article-title>. <source>Physiol Rev</source>. (<year>2015</year>) <volume>95</volume>:<fpage>83</fpage>&#x2013;<lpage>123</lpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1152/physrev.00025.2013</pub-id>, PMID: <pub-id pub-id-type="pmid">25540139</pub-id>
</mixed-citation>
</ref>
<ref id="B52">
<label>52</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Shepard</surname> <given-names>BD</given-names></name>
<name><surname>Pluznick</surname> <given-names>JL</given-names></name>
</person-group>. 
<article-title>How does your kidney smell? Emerging roles for olfactory receptors in renal function</article-title>. <source>Pediatr Nephrol</source>. (<year>2016</year>) <volume>31</volume>:<page-range>715&#x2013;23</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1007/s00467-015-3181-8</pub-id>, PMID: <pub-id pub-id-type="pmid">26264790</pub-id>
</mixed-citation>
</ref>
<ref id="B53">
<label>53</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Wang</surname> <given-names>H</given-names></name>
<name><surname>Kang</surname> <given-names>T</given-names></name>
<name><surname>Li</surname> <given-names>W</given-names></name>
</person-group>. 
<article-title>Reduced maternal scfas in gdm diminish gpr43 signaling and induce offspring cakut</article-title>. <source>Commun Biol</source>. (<year>2025</year>) <volume>8</volume>:<fpage>1063</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s42003-025-08469-y</pub-id>, PMID: <pub-id pub-id-type="pmid">40676152</pub-id>
</mixed-citation>
</ref>
<ref id="B54">
<label>54</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Balmer</surname> <given-names>ML</given-names></name>
<name><surname>Ma</surname> <given-names>EH</given-names></name>
<name><surname>Bantug</surname> <given-names>GR</given-names></name>
<name><surname>Grahlert</surname> <given-names>J</given-names></name>
<name><surname>Pfister</surname> <given-names>S</given-names></name>
<name><surname>Glatter</surname> <given-names>T</given-names></name>
<etal/>
</person-group>. 
<article-title>Memory cd8(+) T cells require increased concentrations of acetate induced by stress for optimal function</article-title>. <source>Immunity</source>. (<year>2016</year>) <volume>44</volume>:<page-range>1312&#x2013;24</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.immuni.2016.03.016</pub-id>, PMID: <pub-id pub-id-type="pmid">27212436</pub-id>
</mixed-citation>
</ref>
<ref id="B55">
<label>55</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Yamamura</surname> <given-names>R</given-names></name>
<name><surname>Nakamura</surname> <given-names>K</given-names></name>
<name><surname>Kitada</surname> <given-names>N</given-names></name>
<name><surname>Aizawa</surname> <given-names>T</given-names></name>
<name><surname>Shimizu</surname> <given-names>Y</given-names></name>
<name><surname>Nakamura</surname> <given-names>K</given-names></name>
<etal/>
</person-group>. 
<article-title>Associations of gut microbiota, dietary intake, and serum short-chain fatty acids with fecal short-chain fatty acids</article-title>. <source>Biosci Microbiota Food Health</source>. (<year>2020</year>) <volume>39</volume>:<page-range>11&#x2013;7</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.12938/bmfh.19-010</pub-id>, PMID: <pub-id pub-id-type="pmid">32010539</pub-id>
</mixed-citation>
</ref>
<ref id="B56">
<label>56</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Chang</surname> <given-names>M</given-names></name>
<name><surname>Shi</surname> <given-names>X</given-names></name>
<name><surname>Yang</surname> <given-names>B</given-names></name>
<name><surname>Li</surname> <given-names>P</given-names></name>
<name><surname>Zhang</surname> <given-names>Y</given-names></name>
<name><surname>Zhang</surname> <given-names>Q</given-names></name>
<etal/>
</person-group>. 
<article-title>Modified huangqi chifeng decoction alleviates podocyte injury on rat with experimental membranous nephropathy</article-title>. <source>Ren Fail</source>. (<year>2025</year>) <volume>47</volume>:<elocation-id>2459896</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1080/0886022X.2025.2459896</pub-id>, PMID: <pub-id pub-id-type="pmid">39972601</pub-id>
</mixed-citation>
</ref>
<ref id="B57">
<label>57</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Tian</surname> <given-names>R</given-names></name>
<name><surname>Wang</surname> <given-names>L</given-names></name>
<name><surname>Chen</surname> <given-names>A</given-names></name>
<name><surname>Huang</surname> <given-names>L</given-names></name>
<name><surname>Liang</surname> <given-names>X</given-names></name>
<name><surname>Wang</surname> <given-names>R</given-names></name>
<etal/>
</person-group>. 
<article-title>Sanqi oral solution ameliorates renal damage and restores podocyte injury in experimental membranous nephropathy via suppression of nfkappab</article-title>. <source>BioMed Pharmacother</source>. (<year>2019</year>) <volume>115</volume>:<elocation-id>108904</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.biopha.2019.108904</pub-id>, PMID: <pub-id pub-id-type="pmid">31060008</pub-id>
</mixed-citation>
</ref>
<ref id="B58">
<label>58</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Yuan</surname> <given-names>Q</given-names></name>
<name><surname>Tang</surname> <given-names>B</given-names></name>
<name><surname>Zhang</surname> <given-names>C</given-names></name>
</person-group>. 
<article-title>Signaling pathways of chronic kidney diseases, implications for therapeutics</article-title>. <source>Signal Transduct Target Ther</source>. (<year>2022</year>) <volume>7</volume>:<fpage>182</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41392-022-01036-5</pub-id>, PMID: <pub-id pub-id-type="pmid">35680856</pub-id>
</mixed-citation>
</ref>
<ref id="B59">
<label>59</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Huang</surname> <given-names>W</given-names></name>
<name><surname>Man</surname> <given-names>Y</given-names></name>
<name><surname>Gao</surname> <given-names>C</given-names></name>
<name><surname>Zhou</surname> <given-names>L</given-names></name>
<name><surname>Gu</surname> <given-names>J</given-names></name>
<name><surname>Xu</surname> <given-names>H</given-names></name>
<etal/>
</person-group>. 
<article-title>Short-chain fatty acids ameliorate diabetic nephropathy via gpr43-mediated inhibition of oxidative stress and nf-kappab signaling</article-title>. <source>Oxid Med Cell Longev</source>. (<year>2020</year>) <volume>2020</volume>:<elocation-id>4074832</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1155/2020/4074832</pub-id>, PMID: <pub-id pub-id-type="pmid">32831998</pub-id>
</mixed-citation>
</ref>
<ref id="B60">
<label>60</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zheng</surname> <given-names>W</given-names></name>
<name><surname>Liu</surname> <given-names>M</given-names></name>
<name><surname>Lv</surname> <given-names>X</given-names></name>
<name><surname>He</surname> <given-names>C</given-names></name>
<name><surname>Yin</surname> <given-names>J</given-names></name>
<name><surname>Ma</surname> <given-names>J</given-names></name>
</person-group>. 
<article-title>Ahr governs lipid metabolism: the role of gut microbiota</article-title>. <source>Front Microbiol</source>. (<year>2025</year>) <volume>16</volume>:<elocation-id>1442282</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fmicb.2025.1442282</pub-id>, PMID: <pub-id pub-id-type="pmid">39944639</pub-id>
</mixed-citation>
</ref>
<ref id="B61">
<label>61</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Wang</surname> <given-names>YN</given-names></name>
<name><surname>Miao</surname> <given-names>H</given-names></name>
<name><surname>Yu</surname> <given-names>XY</given-names></name>
<name><surname>Guo</surname> <given-names>Y</given-names></name>
<name><surname>Su</surname> <given-names>W</given-names></name>
<name><surname>Liu</surname> <given-names>F</given-names></name>
<etal/>
</person-group>. 
<article-title>Oxidative stress and inflammation are mediated via aryl hydrocarbon receptor signalling in idiopathic membranous nephropathy</article-title>. <source>Free Radic Biol Med</source>. (<year>2023</year>) <volume>207</volume>:<fpage>89</fpage>&#x2013;<lpage>106</lpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.freeradbiomed.2023</pub-id>, PMID: <pub-id pub-id-type="pmid">37451370</pub-id>
</mixed-citation>
</ref>
<ref id="B62">
<label>62</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Lu</surname> <given-names>CC</given-names></name>
<name><surname>Hu</surname> <given-names>ZB</given-names></name>
<name><surname>Wang</surname> <given-names>R</given-names></name>
<name><surname>Hong</surname> <given-names>ZH</given-names></name>
<name><surname>Lu</surname> <given-names>J</given-names></name>
<name><surname>Chen</surname> <given-names>PP</given-names></name>
<etal/>
</person-group>. 
<article-title>Gut microbiota dysbiosis-induced activation of the intrarenal renin-angiotensin system is involved in kidney injuries in rat diabetic nephropathy</article-title>. <source>Acta Pharmacol Sin</source>. (<year>2020</year>) <volume>41</volume>:<page-range>1111&#x2013;8</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41401-019-0326-5</pub-id>, PMID: <pub-id pub-id-type="pmid">32203081</pub-id>
</mixed-citation>
</ref>
<ref id="B63">
<label>63</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Miao</surname> <given-names>H</given-names></name>
<name><surname>Wang</surname> <given-names>YN</given-names></name>
<name><surname>Su</surname> <given-names>W</given-names></name>
<name><surname>Zou</surname> <given-names>L</given-names></name>
<name><surname>Zhuang</surname> <given-names>SG</given-names></name>
<name><surname>Yu</surname> <given-names>XY</given-names></name>
<etal/>
</person-group>. 
<article-title>Sirtuin 6 protects against podocyte injury by blocking the renin-angiotensin system by inhibiting the wnt1/beta-catenin pathway</article-title>. <source>Acta Pharmacol Sin</source>. (<year>2024</year>) <volume>45</volume>:<page-range>137&#x2013;49</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41401-023-01148-w</pub-id>, PMID: <pub-id pub-id-type="pmid">37640899</pub-id>
</mixed-citation>
</ref>
<ref id="B64">
<label>64</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zhou</surname> <given-names>L</given-names></name>
<name><surname>Liu</surname> <given-names>Y</given-names></name>
</person-group>. 
<article-title>Wnt/beta-catenin signaling and renin-angiotensin system in chronic kidney disease</article-title>. <source>Curr Opin Nephrol Hypertens</source>. (<year>2016</year>) <volume>25</volume>:<page-range>100&#x2013;6</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1097/MNH.0000000000000205</pub-id>, PMID: <pub-id pub-id-type="pmid">26808707</pub-id>
</mixed-citation>
</ref>
<ref id="B65">
<label>65</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Pluznick</surname> <given-names>JL</given-names></name>
</person-group>. 
<article-title>Microbial short-chain fatty acids and blood pressure regulation</article-title>. <source>Curr Hypertens Rep</source>. (<year>2017</year>) <volume>19</volume>:<fpage>25</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1007/s11906-017-0722-5</pub-id>, PMID: <pub-id pub-id-type="pmid">28315048</pub-id>
</mixed-citation>
</ref>
<ref id="B66">
<label>66</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Wu</surname> <given-names>W</given-names></name>
<name><surname>Sun</surname> <given-names>M</given-names></name>
<name><surname>Chen</surname> <given-names>F</given-names></name>
<name><surname>Cao</surname> <given-names>AT</given-names></name>
<name><surname>Liu</surname> <given-names>H</given-names></name>
<name><surname>Zhao</surname> <given-names>Y</given-names></name>
<etal/>
</person-group>. 
<article-title>Microbiota metabolite short-chain fatty acid acetate promotes intestinal iga response to microbiota which is mediated by gpr43</article-title>. <source>Mucosal Immunol</source>. (<year>2017</year>) <volume>10</volume>:<page-range>946&#x2013;56</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/mi.2016.114</pub-id>, PMID: <pub-id pub-id-type="pmid">27966553</pub-id>
</mixed-citation>
</ref>
<ref id="B67">
<label>67</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Yang</surname> <given-names>W</given-names></name>
<name><surname>Xiao</surname> <given-names>Y</given-names></name>
<name><surname>Huang</surname> <given-names>X</given-names></name>
<name><surname>Chen</surname> <given-names>F</given-names></name>
<name><surname>Sun</surname> <given-names>M</given-names></name>
<name><surname>Bilotta</surname> <given-names>AJ</given-names></name>
<etal/>
</person-group>. 
<article-title>Microbiota metabolite short-chain fatty acids facilitate mucosal adjuvant activity of cholera toxin through gpr43</article-title>. <source>J Immunol</source>. (<year>2019</year>) <volume>203</volume>:<page-range>282&#x2013;92</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.4049/jimmunol.1801068</pub-id>, PMID: <pub-id pub-id-type="pmid">31076530</pub-id>
</mixed-citation>
</ref>
<ref id="B68">
<label>68</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Takeuchi</surname> <given-names>T</given-names></name>
<name><surname>Miyauchi</surname> <given-names>E</given-names></name>
<name><surname>Kanaya</surname> <given-names>T</given-names></name>
<name><surname>Kato</surname> <given-names>T</given-names></name>
<name><surname>Nakanishi</surname> <given-names>Y</given-names></name>
<name><surname>Watanabe</surname> <given-names>T</given-names></name>
<etal/>
</person-group>. 
<article-title>Acetate differentially regulates iga reactivity to commensal bacteria</article-title>. <source>Nature</source>. (<year>2021</year>) <volume>595</volume>:<page-range>560&#x2013;4</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41586-021-03727-5</pub-id>, PMID: <pub-id pub-id-type="pmid">34262176</pub-id>
</mixed-citation>
</ref>
<ref id="B69">
<label>69</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zhu</surname> <given-names>Y</given-names></name>
<name><surname>He</surname> <given-names>H</given-names></name>
<name><surname>Sun</surname> <given-names>W</given-names></name>
<name><surname>Wu</surname> <given-names>J</given-names></name>
<name><surname>Xiao</surname> <given-names>Y</given-names></name>
<name><surname>Peng</surname> <given-names>Y</given-names></name>
<etal/>
</person-group>. 
<article-title>Iga nephropathy: gut microbiome regulates the production of hypoglycosilated iga1 via the tlr4 signaling pathway</article-title>. <source>Nephrol Dial Transplant</source>. (<year>2024</year>) <volume>39</volume>:<page-range>1624&#x2013;41</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1093/ndt/gfae052</pub-id>, PMID: <pub-id pub-id-type="pmid">38402460</pub-id>
</mixed-citation>
</ref>
<ref id="B70">
<label>70</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Li</surname> <given-names>XJ</given-names></name>
<name><surname>Shan</surname> <given-names>QY</given-names></name>
<name><surname>Wu</surname> <given-names>X</given-names></name>
<name><surname>Miao</surname> <given-names>H</given-names></name>
<name><surname>Zhao</surname> <given-names>YY</given-names></name>
</person-group>. 
<article-title>Gut microbiota regulates oxidative stress and inflammation: A double-edged sword in renal fibrosis</article-title>. <source>Cell Mol Life Sci</source>. (<year>2024</year>) <volume>81</volume>:<fpage>480</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1007/s00018-024-05532-5</pub-id>, PMID: <pub-id pub-id-type="pmid">39636415</pub-id>
</mixed-citation>
</ref>
<ref id="B71">
<label>71</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Miao</surname> <given-names>H</given-names></name>
<name><surname>Wang</surname> <given-names>YN</given-names></name>
<name><surname>Yu</surname> <given-names>XY</given-names></name>
<name><surname>Zou</surname> <given-names>L</given-names></name>
<name><surname>Guo</surname> <given-names>Y</given-names></name>
<name><surname>Su</surname> <given-names>W</given-names></name>
<etal/>
</person-group>. 
<article-title>Lactobacillus species ameliorate membranous nephropathy through inhibiting the aryl hydrocarbon receptor pathway via tryptophan-produced indole metabolites</article-title>. <source>Br J Pharmacol</source>. (<year>2024</year>) <volume>181</volume>:<page-range>162&#x2013;79</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1111/bph.16219</pub-id>, PMID: <pub-id pub-id-type="pmid">37594378</pub-id>
</mixed-citation>
</ref>
<ref id="B72">
<label>72</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zhang</surname> <given-names>Y</given-names></name>
<name><surname>Zhou</surname> <given-names>Y</given-names></name>
<name><surname>Cui</surname> <given-names>W</given-names></name>
<name><surname>Wang</surname> <given-names>Z</given-names></name>
<name><surname>Wang</surname> <given-names>X</given-names></name>
<name><surname>Wu</surname> <given-names>F</given-names></name>
<etal/>
</person-group>. 
<article-title>Characterization and diagnostic value of the gut microbial composition in patients with minimal change disease</article-title>. <source>Front Physiol</source>. (<year>2022</year>) <volume>13</volume>:<elocation-id>1070569</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fphys.2022.1070569</pub-id>, PMID: <pub-id pub-id-type="pmid">36561217</pub-id>
</mixed-citation>
</ref>
<ref id="B73">
<label>73</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Chu</surname> <given-names>C</given-names></name>
<name><surname>Behera</surname> <given-names>TR</given-names></name>
<name><surname>Huang</surname> <given-names>Y</given-names></name>
<name><surname>Qiu</surname> <given-names>W</given-names></name>
<name><surname>Chen</surname> <given-names>J</given-names></name>
<name><surname>Shen</surname> <given-names>Q</given-names></name>
</person-group>. 
<article-title>Research progress of gut microbiome and diabetic nephropathy</article-title>. <source>Front Med (Lausanne)</source>. (<year>2024</year>) <volume>11</volume>:<elocation-id>1490314</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fmed.2024.1490314</pub-id>, PMID: <pub-id pub-id-type="pmid">39735707</pub-id>
</mixed-citation>
</ref>
<ref id="B74">
<label>74</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Dong</surname> <given-names>Y</given-names></name>
<name><surname>Yan</surname> <given-names>G</given-names></name>
<name><surname>Zhang</surname> <given-names>Y</given-names></name>
<name><surname>Zhou</surname> <given-names>Y</given-names></name>
<name><surname>Shang</surname> <given-names>J</given-names></name>
</person-group>. 
<article-title>Gut microbiota as a predictive tool for outcomes in iga nephropathy</article-title>. <source>Ren Fail</source>. (<year>2025</year>) <volume>47</volume>:<elocation-id>2514184</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1080/0886022X.2025.2514184</pub-id>, PMID: <pub-id pub-id-type="pmid">40629894</pub-id>
</mixed-citation>
</ref>
<ref id="B75">
<label>75</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Zhi</surname> <given-names>W</given-names></name>
<name><surname>Li</surname> <given-names>A</given-names></name>
<name><surname>Wang</surname> <given-names>Q</given-names></name>
<name><surname>Yuan</surname> <given-names>X</given-names></name>
<name><surname>Qing</surname> <given-names>J</given-names></name>
<name><surname>Zhang</surname> <given-names>C</given-names></name>
<etal/>
</person-group>. 
<article-title>Safety and efficacy assessment of fecal microbiota transplantation as an adjunctive treatment for iga nephropathy: an exploratory clinical trial</article-title>. <source>Sci Rep</source>. (<year>2024</year>) <volume>14</volume>:<fpage>22935</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41598-024-74171-4</pub-id>, PMID: <pub-id pub-id-type="pmid">39358432</pub-id>
</mixed-citation>
</ref>
<ref id="B76">
<label>76</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Wang</surname> <given-names>S</given-names></name>
<name><surname>Lv</surname> <given-names>D</given-names></name>
<name><surname>Jiang</surname> <given-names>S</given-names></name>
<name><surname>Jiang</surname> <given-names>J</given-names></name>
<name><surname>Liang</surname> <given-names>M</given-names></name>
<name><surname>Hou</surname> <given-names>F</given-names></name>
<etal/>
</person-group>. 
<article-title>Quantitative reduction in short-chain fatty acids, especially butyrate, contributes to the progression of chronic kidney disease</article-title>. <source>Clin Sci (Lond)</source>. (<year>2019</year>) <volume>133</volume>:<page-range>1857&#x2013;70</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1042/CS20190171</pub-id>, PMID: <pub-id pub-id-type="pmid">31467135</pub-id>
</mixed-citation>
</ref>
</ref-list>
<fn-group>
<fn id="n1" fn-type="custom" custom-type="edited-by">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/689720">Gabriela Barrientos</ext-link>, National Scientific and Technical Research Council (CONICET), Argentina</p></fn>
<fn id="n2" fn-type="custom" custom-type="reviewed-by">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1386549">Xiaoyong Yu</ext-link>, Shaanxi Provincial Hospital of Traditional Chinese Medicine, China</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2114227">Yijun Dong</ext-link>, First Affiliated Hospital of Zhengzhou University, China</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2762437">Sho Hamaguchi</ext-link>, Juntendo University, Japan</p></fn>
</fn-group>
</back>
</article>