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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Microbiol.</journal-id>
<journal-title>Frontiers in Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Microbiol.</abbrev-journal-title>
<issn pub-type="epub">1664-302X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmicb.2024.1403825</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Microbiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The causality between gut microbiota and non-Hodgkin lymphoma: a two-sample bidirectional Mendelian randomization study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Fu</surname> <given-names>Jinjie</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1986709/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Hao</surname> <given-names>Zheng</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/project-administration/"/>
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</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Graduate School, Tianjin University of Traditional Chinese Medicine</institution>, <addr-line>Tianjin</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>College of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine</institution>, <addr-line>Tianjin</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Tianjin Key Laboratory of Modern Chinese Medicine Theory of Innovation and Application</institution>, <addr-line>Tianjin</addr-line>, <country>China</country></aff>
<aff id="aff4"><sup>4</sup><institution>Guo Aichun Institute of Medical History and Literature, Tianjin University of Traditional Chinese Medicine</institution>, <addr-line>Tianjin</addr-line>, <country>China</country></aff>
<author-notes>
<fn id="fn0001" fn-type="edited-by"><p>Edited by: Lifeng Zhu, Nanjing University of Chinese Medicine, China</p></fn>
<fn id="fn0002" fn-type="edited-by"><p>Reviewed by: Zhengrui Li, Shanghai Jiao Tong University, China</p>
<p>Hong Liu, Shandong University of Technology, China</p></fn>
<corresp id="c001">&#x002A;Correspondence: Zheng Hao, <email>1060256010@qq.com</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>27</day>
<month>05</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1403825</elocation-id>
<history>
<date date-type="received">
<day>20</day>
<month>03</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>10</day>
<month>05</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2024 Fu and Hao.</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Fu and Hao</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Background</title>
<p>Studies have indicated an association between gut microbiota (GM) and non-Hodgkin lymphoma (NHL). However, the causality between GM and NHL remains unclear. This study aims to investigate the causality between GM and NHL using Mendelian randomization (MR).</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>Data on GM is sourced from the MiBioGen consortium, while data on NHL and its subtypes is sourced from the FinnGen consortium R10 version. Inverse variance weighted (IVW) was employed for the primary MR analysis method, with methods such as Bayesian weighted Mendelian randomisation (BWMR) as an adjunct. Sensitivity analyses were conducted using Cochran&#x2019;s Q test, MR-Egger regression, MR-PRESSO, and the &#x201C;Leave-one-out&#x201D; method.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>The MR results showed that there is a causality between 27 GMs and NHL. Among them, 20 were negatively associated (OR&#x2009;&#x003C;&#x2009;1), and 7 were positively associated (OR&#x2009;&#x003E;&#x2009;1) with the corresponding diseases. All 27 MR results passed sensitivity tests, and there was no reverse causal association.</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>By demonstrating a causal link between GM and NHL, this research offers novel ideas to prevent, monitor, and cure NHL later.</p>
</sec>
</abstract>
<kwd-group>
<kwd>gut microbiota</kwd>
<kwd>non-Hodgkin lymphoma</kwd>
<kwd>diffuse large B-cell lymphoma</kwd>
<kwd>haematology system</kwd>
<kwd>Mendelian randomization</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="99"/>
<page-count count="13"/>
<word-count count="8546"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Microorganisms in Vertebrate Digestive Systems</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<label>1</label>
<title>Introduction</title>
<p>NHL is a prevalent malignancy tumor in the haematology system, accounting for about 90% of lymphomas overall. It can be classified into three basic types: B-cell type, T-cell type, and NK-cell type (<xref ref-type="bibr" rid="ref71">Shankland et al., 2012</xref>). The prevalence of NHL is progressively rising on an annual basis. Based on statistical data, the number of new NHL cases in 2020 was 544,000, with approximately 260,000 deaths (<xref ref-type="bibr" rid="ref46">Mafra et al., 2022</xref>). The number of new cases is projected to reach 778,000 by 2040, an increase of about 43% compared to 2020 (<xref ref-type="bibr" rid="ref19">Chu et al., 2023</xref>). While the etiology of NHL is not fully understood, infection, immunosuppression, immunodeficiency syndromes, and autoimmune diseases are commonly recognized as significant risk factors for the onset of NHL (<xref ref-type="bibr" rid="ref3">Ansell, 2015</xref>; <xref ref-type="bibr" rid="ref4">Armitage et al., 2017</xref>). In terms of treatment, from the anti-CD20 monoclonal antibody (rituximab) in 1982 (<xref ref-type="bibr" rid="ref53">Miller et al., 1982</xref>), to the current immune checkpoint inhibitors (ICI) and bispecific antibodies (<xref ref-type="bibr" rid="ref8">Bock et al., 2022</xref>; <xref ref-type="bibr" rid="ref1">Abou Dalle et al., 2024</xref>), immunotherapy combined with chemotherapy has always been a focus in the treatment of NHL. Despite some progress made in these treatment methods, the therapy of relapsed/refractory NHL is still a major dilemma in the field, with many unmet needs in NHL therapy (<xref ref-type="bibr" rid="ref17">Chaudhari et al., 2019</xref>).</p>
<p>The gastrointestinal tract, as the most common extranodal site involved in NHL (<xref ref-type="bibr" rid="ref31">Hanafy et al., 2020</xref>), harbors a large number of microbes, such as bacteria and fungi. This subset of microorganisms is collectively referred to as GM (<xref ref-type="bibr" rid="ref20">Costea et al., 2017</xref>). Recently, the close connection between GM and NHL has been increasingly confirmed. Research has shown that the abundance of GM in diffuse large B-cell lymphoma (DLBCL) patients is markedly greater than that in healthy individuals, as revealed by 16S rRNA gene sequencing (<xref ref-type="bibr" rid="ref93">Yuan et al., 2021</xref>). In terms of NHL occurrence, studies have found an association between mucosa-associated lymphoid tissue (MALT) lymphoma and the invasion of GM such as Burkholderia. GM like Burkholderia may influence the mechanism of MALT lymphoma occurrence through the synthesis of Mvin protein (<xref ref-type="bibr" rid="ref37">Kuo et al., 2019</xref>; <xref ref-type="bibr" rid="ref82">Tanaka et al., 2021</xref>). Regarding the diagnosis of NHL, some scholars have suggested that GM can serve as a diagnostic marker for NK/T cell lymphoma (<xref ref-type="bibr" rid="ref72">Shi et al., 2023</xref>). In addition, GM can also modulate the efficacy of immunotherapy. Studies have shown that the treatment response of cancer patients receiving immune checkpoint inhibitors (ICIs) is associated with the composition of GM. For example, GM such as Bacteroides may enhance patients&#x2019; anti-tumor capacity by improving the function of effector T cells in the tumor microenvironment (<xref ref-type="bibr" rid="ref27">Gopalakrishnan et al., 2018</xref>). Furthermore, studies have shown that oral administration of <italic>Akkermansia muciniphila</italic> and fecal microbiota transplantation can restore the efficacy of immune checkpoint inhibitors (ICI) in drug-resistant tumor mice through an interleukin-12-dependent mechanism (<xref ref-type="bibr" rid="ref63">Routy et al., 2018</xref>). Therefore, by modulating GM, it is possible to improve the therapeutic effect of immunotherapies such as ICB, lower associated side effects (<xref ref-type="bibr" rid="ref59">Park E. M. et al., 2022</xref>), and mitigate the development of resistance to ICIs in cancer patients (<xref ref-type="bibr" rid="ref63">Routy et al., 2018</xref>). Myeloablative conditioning and the use of broad-spectrum antibiotics before hematopoietic stem cell transplantation (HSCT) can damage the intestinal epithelium and mucosal barrier, leading to gastrointestinal mucositis, and consequently increasing the risk of infections in patients (<xref ref-type="bibr" rid="ref35">Keefe et al., 2007</xref>). Meanwhile, GM can influence the immune system and maintain intestinal homeostasis by regulating cells such as Treg and TH17 (<xref ref-type="bibr" rid="ref5">Arpaia et al., 2013</xref>; <xref ref-type="bibr" rid="ref77">Smith et al., 2013</xref>). Based on differences in GM, it is possible to predict and assess pre-transplant risks in NHL patients undergoing HSCT, aiding in the identification and prevention of high-risk individuals (<xref ref-type="bibr" rid="ref56">Montassier et al., 2016</xref>). For instance, assessing the diversity of gut microbiota (GM) in patients on the day of transplant surgery can predict those at high risk of mortality during HSCT (<xref ref-type="bibr" rid="ref83">Taur et al., 2014</xref>). In the future, GM may be a novel diagnostic biomarker and therapeutic target for NHL. Therefore, research on the causal relationship between the two is necessary.</p>
<p>MR explores the causality between exposure and outcome by utilizing instrumental variables (IVs) (<xref ref-type="bibr" rid="ref22">Davies et al., 2018</xref>). Under the principle of random assignment, MR studies could avoid confounding factors or reverse causation interference (<xref ref-type="bibr" rid="ref21">Davey Smith and Hemani, 2014</xref>), resulting in more stable and reliable research outcomes. For the research, we employ a two-sample MR methodology to investigate the causality between GM and NHL.</p>
</sec>
<sec sec-type="methods" id="sec6">
<label>2</label>
<title>Methods</title>
<sec id="sec7">
<label>2.1</label>
<title>Data sources</title>
<p>MiBioGen consortium provided genetic variation data on GM (<xref ref-type="bibr" rid="ref38">Kurilshikov et al., 2021</xref>). This research involved 18, 340 persons and generated corresponding genetic sequencing and genotyping data. It included 211 GMs, classified into five categories: phylum, class, order, family, and genus. Three unknown families and twelve unknown genera were excluded. Eventually, the study included nine phyla, sixteen classes, twenty orders, thirty-two families, and one hundred nineteen genera, totaling 196 GMs. The genetic variation data for NHL originates from the FinnGen consortium R10 version GWAS summary data (<xref ref-type="bibr" rid="ref39">Kurki et al., 2023</xref>). It includes NHL and its five subtypes: follicular lymphoma (FL), DLBCL, marginal zone B-cell lymphoma (MZBL), T/NK cell lymphoma, and mantle cell lymphoma (MCL) (<xref ref-type="table" rid="tab1">Table 1</xref>). The diagnostic criteria for NHL refer to ICD-10 codes C82, C83, C84, C85; The diagnostic criteria for FL refer to ICD-10 code C82; The diagnostic criteria for DLBCL refer to ICD-10 code C83.3; The diagnostic criteria for MZBL refer to ICD-10 codes C83.80, C83.89; The diagnostic criteria for T/NK cell lymphoma refer to ICD-10 code C84; The diagnostic criteria for MCL refer to ICD-10 code C83.1.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption><p>Detailed information on GMs and NHLs with their subtypes.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="left" valign="top">Trait</th>
<th align="center" valign="top">Year</th>
<th align="left" valign="top">Population</th>
<th align="center" valign="top">Case</th>
<th align="center" valign="top">Control</th>
<th align="left" valign="top">PMID/URL (Datadownload)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Exposure</td>
<td align="left" valign="middle">Gut microbiota</td>
<td align="center" valign="middle">2023</td>
<td align="left" valign="middle">European</td>
<td align="center" valign="middle">&#x2013;</td>
<td align="center" valign="middle">&#x2013;</td>
<td align="left" valign="middle">33462485</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="6">Outcome</td>
<td align="left" valign="middle">Non-Hodgkin lymphoma</td>
<td align="center" valign="middle">2023</td>
<td align="left" valign="middle">European</td>
<td align="center" valign="middle">1,072</td>
<td align="center" valign="middle">314193</td>
<td align="left" valign="middle"><ext-link xlink:href="https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_C3_NONHODGKIN_EXALLC.gz" ext-link-type="uri">https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_C3_NONHODGKIN_EXALLC.gz</ext-link></td>
</tr>
<tr>
<td align="left" valign="middle">Follicular lymphoma</td>
<td align="center" valign="middle">2023</td>
<td align="left" valign="middle">European</td>
<td align="center" valign="middle">1,181</td>
<td align="center" valign="middle">324650</td>
<td align="left" valign="middle"><ext-link xlink:href="https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_CD2_FOLLICULAR_LYMPHOMA_EXALLC.gz" ext-link-type="uri">https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_CD2_FOLLICULAR_LYMPHOMA_EXALLC.gz</ext-link></td>
</tr>
<tr>
<td align="left" valign="middle">Diffuse large B-cell lymphoma</td>
<td align="center" valign="middle">2023</td>
<td align="left" valign="middle">European</td>
<td align="center" valign="middle">1,050</td>
<td align="center" valign="middle">314193</td>
<td align="left" valign="middle"><ext-link xlink:href="https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_C3_DLBCL_EXALLC.gz" ext-link-type="uri">https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_C3_DLBCL_EXALLC.gz</ext-link></td>
</tr>
<tr>
<td align="left" valign="middle">Marginal zone B-cell lymphoma</td>
<td align="center" valign="middle">2023</td>
<td align="left" valign="middle">European</td>
<td align="center" valign="middle">202</td>
<td align="center" valign="middle">314193</td>
<td align="left" valign="middle"><ext-link xlink:href="https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_C3_MARGINAL_ZONE_LYMPHOMA_EXALLC.gz" ext-link-type="uri">https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_C3_MARGINAL_ZONE_LYMPHOMA_EXALLC.gz</ext-link></td>
</tr>
<tr>
<td align="left" valign="middle">Mantle cell lymphoma</td>
<td align="center" valign="middle">2023</td>
<td align="left" valign="middle">European</td>
<td align="center" valign="middle">210</td>
<td align="center" valign="middle">314193</td>
<td align="left" valign="middle"><ext-link xlink:href="https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_C3_MANTLE_CELL_LYMPHOMA_EXALLC.gz" ext-link-type="uri">https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_C3_MANTLE_CELL_LYMPHOMA_EXALLC.gz</ext-link></td>
</tr>
<tr>
<td align="left" valign="middle">T/NK-cell lymphomas</td>
<td align="center" valign="middle">2023</td>
<td align="left" valign="middle">European</td>
<td align="center" valign="middle">363</td>
<td align="center" valign="middle">324650</td>
<td align="left" valign="middle"><ext-link xlink:href="https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_CD2_TNK_LYMPHOMA_EXALLC.gz" ext-link-type="uri">https://storage.googleapis.com/finngen-public-data-r10/summary_stats/finngen_R10_CD2_TNK_LYMPHOMA_EXALLC.gz</ext-link></td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec8">
<label>2.2</label>
<title>Selection of IVs</title>
<p>IVs were screened based on the following criteria (<xref ref-type="fig" rid="fig1">Figure 1</xref>): (1) In order to obtain IVs that are strongly correlated with GM and have robust relationships, we set the significance threshold at <italic>p</italic>&#x2009;&#x003C;&#x2009;1.0&#x2009;&#x00D7;&#x2009;10<sup>&#x2212;8</sup>. However, the number of obtained IVs was small and difficult to meet the requirements of this study. Therefore, we referred to previous research (<xref ref-type="bibr" rid="ref67">Sanna et al., 2019</xref>) and set the significance threshold at <italic>p</italic>&#x2009;&#x003C;&#x2009;1.0&#x2009;&#x00D7;&#x2009;10<sup>&#x2212;5</sup>. At the same time, to ensure the mutual independence of the selected IVs, we removed linkage disequilibrium in the IVs (<italic>r</italic><sup>2</sup>&#x2009;&#x003C;&#x2009;0.001, kb&#x2009;=&#x2009;10,000); (2) To ensure the independence of the IVs, the IVs are unrelated to any confounding factors; (3) IVs can only influence the occurrence of NHL through GM and cannot affect NHL through other pathways. Additionally, to avoid bias from weak IVs, we excluded weak IVs using the F-statistic (<italic>F</italic>&#x2009;&#x003E;&#x2009;10). We also removed palindromic sequences from the IVs.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption><p>Three conditions met by filtering IVs.</p></caption>
<graphic xlink:href="fmicb-15-1403825-g001.tif"/>
</fig>
</sec>
<sec id="sec9">
<label>2.3</label>
<title>Positive MR analysis and sensitivity analysis</title>
<p>We utilized six methods, including IVW, MR Egger, weighted median, simple mode, weighted mode, and BWMR, to investigate the causality between GM and NHL. However, IVW was the primary evaluation method (<xref ref-type="bibr" rid="ref32">Hemani et al., 2018</xref>). Given the uniqueness of GWAS data, the IVW method is widely recognized as the primary method for exploring causal relationships in MR analysis. By conducting a meta-analysis of each Wald ratio of the included valid IVs, it can provide the most accurate estimate of the effect. This approach is also commonly seen in other literature (<xref ref-type="bibr" rid="ref41">Legason et al., 2017</xref>; <xref ref-type="bibr" rid="ref45">Lu et al., 2023</xref>; <xref ref-type="bibr" rid="ref49">Mart&#x00ED;n-Masot et al., 2023</xref>; <xref ref-type="bibr" rid="ref64">Ruan et al., 2023</xref>; <xref ref-type="bibr" rid="ref43">Li et al., 2024</xref>; <xref ref-type="bibr" rid="ref97">Zheng et al., 2024</xref>). The IVW method is divided into random-effects IVW and fixed-effects IVW, with the selection based on heterogeneity in MR results (<xref ref-type="bibr" rid="ref29">Greco et al., 2015</xref>). Since no single method can perfectly suit all situations, additional methods such as MR Egger and weighted median are used as supplements (<xref ref-type="bibr" rid="ref10">Bowden et al., 2015</xref>, <xref ref-type="bibr" rid="ref11">2016</xref>). For instance, when there is pleiotropy present, the MR Egger method is more suitable for inferring causal relationships. Finally, to mitigate the effects of multi-genic structure and pleiotropy, we utilized the BWMR method to further validate the obtained causal relationships (<xref ref-type="bibr" rid="ref96">Zhao et al., 2020</xref>).</p>
<p>Sensitivity analysis includes heterogeneity testing, leave-one-out testing, and multivariate testing (<xref ref-type="bibr" rid="ref32">Hemani et al., 2018</xref>). We evaluated the potential bias in the results by examining the pleiotropy of genes and the heterogeneity of the data. Cochran&#x2019;s Q test assesses heterogeneity, based on whether the <italic>p</italic>-value in Cochran&#x2019;s IVW is less than 0.05. MR-Egger regression detects horizontal pleiotropy, determined by the difference between its intercept and 0. MR-PRESSO can detect and lower horizontal pleiotropy (<xref ref-type="bibr" rid="ref14">Burgess et al., 2020</xref>). Additionally, &#x201C;leave-one-out&#x201D; analysis can identify outlier SNPs within the SNPs, thus avoiding bias introduced by individual outlier SNPs on the overall MR results and enhancing the stability of the results.</p>
</sec>
<sec id="sec10">
<label>2.4</label>
<title>Reverse MR analysis</title>
<p>In order to avoid interference from reverse causal relationships on the positive MR results, we conducted a reverse MR analysis with NHL and its five subtypes as exposure and GM as the outcome.</p>
</sec>
<sec id="sec11">
<label>2.5</label>
<title>Statistical analysis</title>
<p>The statistical analyses in R 4.3.0 used the &#x201C;TwoSampleMR&#x201D; package.</p>
</sec>
</sec>
<sec sec-type="results" id="sec12">
<label>3</label>
<title>Results</title>
<sec id="sec13">
<label>3.1</label>
<title>Obtained IVs</title>
<p>412 IVs related to non-Hodgkin lymphoma and its subtypes were obtained through screening (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table S1</xref>). Among them, there were no palindromic sequences, and the <italic>F</italic>&#x2009;&#x003E;&#x2009;10 (range 17.421&#x2013;88.429). The included GMs were divided into five categories, so there may be overlaps among SNPs under each GM.</p>
</sec>
<sec id="sec14">
<label>3.2</label>
<title>Results of positive MR analysis</title>
<p>The IVW results showed that there were 34 GMs associated with NHL and its subtypes. Among them, 8 were associated with NHL, 6 with FL, 4 with DLBCL, 5 with MZBL, 6 with MCL, and 5 with T/NK cell lymphoma (<xref ref-type="fig" rid="fig2">Figure 2</xref>).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption><p>MR results between 34 GMs and NHL.</p></caption>
<graphic xlink:href="fmicb-15-1403825-g002.tif"/>
</fig>
<p>According to the IVW analysis results, phylum Cyanobacteria (OR: 0.622, CI: 0.426&#x2013;0.908, <italic>p</italic>&#x2009;=&#x2009;0.014), order Bifidobacteriales (OR: 0.715, CI: 0.512&#x2013;0.998, <italic>p</italic>&#x2009;=&#x2009;0.049), genus <italic>Ruminococcus gnavus</italic> group (OR: 0.679, CI: 0.499&#x2013;0.924, <italic>p</italic>&#x2009;=&#x2009;0.014), genus <italic>Bifidobacterium</italic> (OR: 0.660, CI: 0.475&#x2013;0.916, <italic>p</italic>&#x2009;=&#x2009;0.013), and genus Lachnospiraceae UCG010 (OR: 0.570, CI: 0.352&#x2013;0.923, <italic>p</italic>&#x2009;=&#x2009;0.022) were negatively associated with an increased risk of NHL. Class Gammaproteobacteria (OR: 1.876, CI: 1.002&#x2013;3.513, <italic>p</italic>&#x2009;=&#x2009;0.049), genus <italic>Faecalibacterium</italic> (OR: 1.571, CI: 1.037&#x2013;2.381, <italic>p</italic>&#x2009;=&#x2009;0.033), and genus <italic>Sellimonas</italic> (OR: 1.542, CI: 1.220&#x2013;1.948, <italic>p</italic>&#x2009;=&#x2009;0.0002) were positively associated with an increased risk of NHL.</p>
<p>According to the IVW analysis results, order Pasteurellales (OR: 0.747, CI: 0.565&#x2013;0.988, <italic>p</italic>&#x2009;=&#x2009;0.041), genus <italic>Alistipes</italic> (OR: 0.554, CI: 0.327&#x2013;0.939, <italic>p</italic>&#x2009;=&#x2009;0.028), genus <italic>Coprobacter</italic> (OR: 0.728, CI: 0.537&#x2013;0.987, <italic>p</italic>&#x2009;=&#x2009;0.041), genus <italic>Haemophilus</italic> (OR: 0.702, CI: 0.502&#x2013;0.983, <italic>p</italic>&#x2009;=&#x2009;0.040), and genus Ruminococcaceae NK4A214 group (OR: 0.598, CI: 0.389&#x2013;0.920, <italic>p</italic>&#x2009;=&#x2009;0.019) were negatively associated with an increased risk of FL. Genus <italic>Catenibacterium</italic> (OR: 1.448, CI: 1.011&#x2013;2.076, <italic>p</italic>&#x2009;=&#x2009;0.044) was positively associated with an increased risk of FL.</p>
<p>According to the IVW analysis results, genus <italic>Alistipes</italic> (OR: 0.521, CI: 0.311&#x2013;0.873, <italic>p</italic>&#x2009;=&#x2009;0.013), genus Ruminococcaceae UCG011 (OR: 0.749, CI: 0.574&#x2013;0.978, <italic>p</italic>&#x2009;=&#x2009;0.034) were negatively associated with an increased risk of DLBCL. Family Desulfovibrionaceae (OR: 1.579, CI: 1.033&#x2013;2.487, <italic>p</italic>&#x2009;=&#x2009;0.049), genus <italic>Bilophila</italic> (OR: 1.777, CI: 1.053&#x2013;3.000, <italic>p</italic>&#x2009;=&#x2009;0.031) were positively associated with an increased risk of DLBCL.</p>
<p>According to the IVW analysis results, family Streptococcaceae (OR: 0.290, CI: 0.113&#x2013;0.746, <italic>p</italic>&#x2009;=&#x2009;0.010), genus <italic>Eubacterium ruminantium</italic> group (OR: 0.505, CI: 0.283&#x2013;0.900, <italic>p</italic>&#x2009;=&#x2009;0.021) were negatively associated with an increased risk of MZBL. Order Gastranaerophilales (OR: 2.445, CI: 1.064&#x2013;5.616, <italic>p</italic>&#x2009;=&#x2009;0.035), family Veillonellaceae (OR: 2.344, CI: 1.055&#x2013;5.207, <italic>p</italic>&#x2009;=&#x2009;0.036), genus Ruminococcaceae NK4A214 group (OR: 2.789, CI: 1.104&#x2013;7.044, <italic>p</italic>&#x2009;=&#x2009;0.030) were positively associated with an increased risk of MZBL.</p>
<p>According to the IVW analysis results, class Clostridia (OR: 0.317, CI: 0.107&#x2013;0.935, <italic>p</italic>&#x2009;=&#x2009;0.037), genus <italic>Bifidobacterium</italic> (OR: 0.441, CI: 0.211&#x2013;0.920, <italic>p</italic>&#x2009;=&#x2009;0.029), genus <italic>Marvinbryantia</italic> (OR: 0.328, CI: 0.115&#x2013;0.938, <italic>p</italic>&#x2009;=&#x2009;0.038), genus <italic>Parasutterella</italic> (OR: 0.441, CI: 0.207&#x2013;0.939, <italic>p</italic>&#x2009;=&#x2009;0.034), genus <italic>Ruminiclostridium</italic> 6 (OR: 0.397, CI: 0.70&#x2013;0.926, <italic>p</italic>&#x2009;=&#x2009;0.032) were negatively associated with an increased risk of MCL. Genus <italic>Faecalibacterium</italic> (OR: 2.755, CI: 1.084&#x2013;7.005, <italic>p</italic>&#x2009;=&#x2009;0.033) was positively associated with an increased risk of MCL.</p>
<p>According to the IVW analysis results, class Methanobacteria (OR: 0.574, CI: 0.371&#x2013;0.887, <italic>p</italic>&#x2009;=&#x2009;0.012), family Lactobacillaceae (OR: 0.538, CI: 0.308&#x2013;0.941, <italic>p</italic>&#x2009;=&#x2009;0.030), genus Christensenellaceae R 7group (OR: 0.359, CI: 0.134&#x2013;0.960, <italic>p</italic>&#x2009;=&#x2009;0.041), genus Lachnospiraceae UCG001 (OR: 0.350, CI: 0.196&#x2013;0.627, <italic>p</italic>&#x2009;=&#x2009;0.0004), genus Ruminococcaceae UCG014 (OR: 0.412, CI: 0.205&#x2013;0.829, <italic>p</italic>&#x2009;=&#x2009;0.013) were negatively associated with an increased risk of T/NK cell lymphoma.</p>
<p>Using BWMR to validate the 34 pairs of causalities between the obtained GMs and NHL (<xref ref-type="fig" rid="fig3">Figure 3</xref>), the results showed that class Gammaproteobacteria (<italic>p</italic>&#x2009;=&#x2009;0.340) and order Bifidobacteriales (<italic>p</italic>&#x2009;=&#x2009;0.051) were not causally related to NHL; genus <italic>Catenibacterium</italic> (<italic>p</italic>&#x2009;=&#x2009;0.050) and genus <italic>Coprobacter</italic> (<italic>p</italic>&#x2009;=&#x2009;0.052) were not causally related to FL; family Desulfovibrionaceae was not causally related to DLBCL. Comparing these 5 pairs of relationships between the results of BWMR and IVW (<xref ref-type="table" rid="tab2">Table 2</xref>), it was found that although causal relationships existed in the IVW results, their <italic>p</italic>-values were close to 0.05. Therefore, these 5 pairs of relationships were excluded from our study.</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption><p>BWMR results between 34 GMs and NHL.</p></caption>
<graphic xlink:href="fmicb-15-1403825-g003.tif"/>
</fig>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption><p>Comparison of IVW and BWMR results for 5 pairs of GMs and NHL.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Exposure</th>
<th align="left" valign="top" rowspan="2">Outcome</th>
<th align="center" valign="top" colspan="2">IVW</th>
<th align="center" valign="top" colspan="2">BWMR</th>
</tr>
<tr>
<th align="center" valign="top">Pval</th>
<th align="center" valign="top">OR(95%CI)</th>
<th align="center" valign="top">Pval</th>
<th align="center" valign="top">OR(95%CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle"><italic>class Gammaproteobacteria id.3303</italic></td>
<td align="left" valign="middle" rowspan="2">Non-Hodgkin lymphoma</td>
<td align="center" valign="middle">0.049</td>
<td align="center" valign="middle">1.876 (1.002&#x2013;3.513)</td>
<td align="center" valign="middle">0.340</td>
<td align="center" valign="middle">1.386 (0.710&#x2013;2.706)</td>
</tr>
<tr>
<td align="left" valign="middle"><italic>order Bifidobacteriales id.432</italic></td>
<td align="center" valign="middle">0.049</td>
<td align="center" valign="middle">0.715 (0.512&#x2013;0.998)</td>
<td align="center" valign="middle">0.051</td>
<td align="center" valign="middle">0.708 (0.501&#x2013;1.001)</td>
</tr>
<tr>
<td align="left" valign="middle"><italic>genus Catenibacterium id.2153</italic></td>
<td align="left" valign="middle" rowspan="2">Follicular lymphoma</td>
<td align="center" valign="middle">0.044</td>
<td align="center" valign="middle">1.448 (1.011&#x2013;2.076)</td>
<td align="center" valign="middle">0.050</td>
<td align="center" valign="middle">1.470 (1.000&#x2013;2.162)</td>
</tr>
<tr>
<td align="left" valign="middle"><italic>genus Coprobacter id.949</italic></td>
<td align="center" valign="middle">0.041</td>
<td align="center" valign="middle">0.728 (0.537&#x2013;0.987)</td>
<td align="center" valign="middle">0.052</td>
<td align="center" valign="middle">0.727 (0.527&#x2013;1.002)</td>
</tr>
<tr>
<td align="left" valign="middle"><italic>family Desulfovibrionaceae id.3169</italic></td>
<td align="left" valign="middle">Diffuse large B-cell lymphoma</td>
<td align="center" valign="middle">0.049</td>
<td align="center" valign="middle">1.579 (1.003&#x2013;2.487)</td>
<td align="center" valign="middle">0.059</td>
<td align="center" valign="middle">1.611 (0.982&#x2013;2.641)</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Finally, sensitivity analysis of the MR results was conducted (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table S1</xref>). The <italic>p</italic>-values of Cochran&#x2019;s Q test were all &#x003E;0.05, indicating no heterogeneity. The <italic>p</italic>-values of the MR-Egger intercept (<xref rid="SM4" ref-type="supplementary-material">Supplementary Figures S1, S2</xref>) and MR-PRESSO results were all &#x003E;0.05, indicating no horizontal pleiotropy. Results from the &#x201C;leave-one-out&#x201D; method (<xref rid="SM4" ref-type="supplementary-material">Supplementary Figures S3, S4</xref>) showed that removing any single SNP would not significantly affect the MR results.</p>
</sec>
<sec id="sec15">
<label>3.3</label>
<title>Results of reverse MR analysis</title>
<p>The reverse MR results showed that NHL and its subtypes were associated with 37 GMs (<xref rid="SM3" ref-type="supplementary-material">Supplementary Table S3</xref>). Among them, there were 7 associated with NHL, 10 with FL, 5 with DLBCL, 4 with MZBL, 9 with MCL, and 2 with T/NK cell lymphoma. Mapping the forest, see <xref ref-type="fig" rid="fig4">Figure 4</xref>. After comparing with the results of the forward MR, among the 34 forward MR results, FL was inversely associated with order Pasteurellales and genus <italic>Haemophilus</italic>, DLBCL was inversely associated with family Desulfovibrionaceae, and no other reverse causal associations were found in the remaining forward MR results. Sensitivity analysis was conducted for the three reverse causal associations mentioned above (<xref ref-type="table" rid="tab3">Table 3</xref>). Except for the presence of heterogeneity in the MR results between FL and order Pasteurellales (without horizontal pleiotropy), the remaining two MR results showed no heterogeneity or horizontal pleiotropy.</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption><p>Inverse MR results between GMs and NHL.</p></caption>
<graphic xlink:href="fmicb-15-1403825-g004.tif"/>
</fig>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption><p>Sensitivity analysis results for 3 GMs and NHL inverse MR results.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Exposure</th>
<th align="left" valign="top" rowspan="2">Outcome</th>
<th align="center" valign="top" rowspan="2">Q</th>
<th align="center" valign="top" rowspan="2">Q_pval</th>
<th align="center" valign="top" colspan="2">MR-Egger intercept test</th>
<th align="center" valign="top" colspan="2">MR-PRESSO global test</th>
</tr>
<tr>
<th align="center" valign="top">Egger_intercept</th>
<th align="center" valign="top">pval</th>
<th align="center" valign="top">RSS obs</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="2">Follicular lymphoma</td>
<td align="left" valign="middle"><italic>order Pasteurellales</italic></td>
<td align="center" valign="middle">21.424</td>
<td align="center" valign="middle">0.045</td>
<td align="center" valign="middle">&#x2212;0.006</td>
<td align="center" valign="middle">0.828</td>
<td align="center" valign="middle">25.277</td>
<td align="center" valign="middle">0.058</td>
</tr>
<tr>
<td align="left" valign="middle"><italic>genus Haemophilus</italic></td>
<td align="center" valign="middle">18.885</td>
<td align="center" valign="middle">0.063</td>
<td align="center" valign="middle">&#x2212;0.003</td>
<td align="center" valign="middle">0.925</td>
<td align="center" valign="middle">22.189</td>
<td align="center" valign="middle">0.087</td>
</tr>
<tr>
<td align="left" valign="middle">Diffuse large B-cell lymphoma</td>
<td align="left" valign="middle"><italic>family Desulfovibrionaceae</italic></td>
<td align="center" valign="middle">2.775</td>
<td align="center" valign="middle">0.993</td>
<td align="center" valign="middle">0.003</td>
<td align="center" valign="middle">0.876</td>
<td align="center" valign="middle">111.769</td>
<td align="center" valign="middle">0.468</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Therefore, we finally identified 27 GMs with clear causal relationships with NHL and its subtypes, and presented them in the form of a heatmap (<xref ref-type="fig" rid="fig5">Figures 5</xref>, <xref ref-type="fig" rid="fig6">6</xref>).</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption><p>Heatmap of ORs in MR results for 27 GMs and NHL.</p></caption>
<graphic xlink:href="fmicb-15-1403825-g005.tif"/>
</fig>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption><p>Ring thermograms of different MR results for 27 GMs and NHL.</p></caption>
<graphic xlink:href="fmicb-15-1403825-g006.tif"/>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="sec16">
<label>4</label>
<title>Discussion</title>
<p>In the 2020 cancer diagnosis statistics, NHL ranked 11th, and its incidence has been increasing year by year (<xref ref-type="bibr" rid="ref81">Sung et al., 2021</xref>). Although GMs play important roles in the occurrence, development, diagnosis, and treatment of NHL (<xref ref-type="bibr" rid="ref84">Upadhyay Banskota et al., 2023</xref>), the specific causality between the two is unknown. Previous studies have investigated the causal relationship between lipids (<xref ref-type="bibr" rid="ref36">Kleinstern et al., 2020</xref>) and diet (<xref ref-type="bibr" rid="ref98">Zhou et al., 2024</xref>), among other factors (<xref ref-type="bibr" rid="ref73">Shi et al., 2024</xref>), and NHL through MR. Our research identified 27 GMs with causal relationships with NHL and its subtypes through forward and reverse MR analyses, as well as sensitivity analysis. Among them, phylum Cyanobacteria, genus <italic>Ruminococcus gnavus</italic> group, genus <italic>Bifidobacterium</italic>, genus Lachnospiraceae UCG010, genus <italic>Alistipes</italic>, genus Ruminococcaceae NK4A214 group, genus Ruminococcaceae UCG011, family Streptococcaceae, genus <italic>Eubacterium ruminantium</italic> group, class Clostridia, genus <italic>Marvinbryantia</italic>, genus <italic>Parasutterella</italic>, genus <italic>Ruminiclostridium</italic> 6, class Methanobacteria, family Lactobacillaceae, genus Christensenellaceae R 7group, genus Lachnospiraceae UCG001, and genus Ruminococcaceae UCG014 were negatively associated with the disease (OR&#x2009;&#x003C;&#x2009;1), indicating a protective effect against the corresponding types of NHL. Genus <italic>Faecalibacterium</italic>, genus <italic>Sellimonas</italic>, genus <italic>Bilophila</italic>, order Gastranaerophilales, family Veillonellaceae, genus Ruminococcaceae NK4A214 group, and genus <italic>Faecalibacterium</italic> were positively associated with the disease (OR&#x2009;&#x003E;&#x2009;1), serving as risk factors for the corresponding types of NHL. It is worth mentioning that in our positive MR analysis between GM and NHL, we observed that the absence of order Pasteurellales and genus <italic>Haemophilus</italic> might play a promoting role in FL occurrence. However, in the reverse MR analysis, we found that the occurrence of FL could inhibit the production of order Pasteurellales and genus <italic>Haemophilus</italic>. Therefore, we cannot ascertain whether the lack of order Pasteurellales and genus <italic>Haemophilus</italic> is the cause or the consequence of FL occurrence. To avoid interference from reverse causal relationships, we excluded the portion of results that exhibited reverse causal associations from the positive MR results.</p>
<p>The relationship between GM and NHL is complex. With the development of technologies in fields like 16S rRNA sequencing or shotgun metagenomics sequencing, researchers have gained a clearer understanding of the specific taxonomic groups in the GM and their relationship with diseases. Due to the involvement of numerous GM species in NHL and its subtypes in this study, we focused our discussion on the MR results related to NHL.</p>
<p>The phylum Cyanobacteria is a group of ancient and diverse prokaryotes (<xref ref-type="bibr" rid="ref69">Schirrmeister et al., 2011</xref>) that can be divided into different genera such as Aphanothece, Leptolyngbya, and Spirulina (<xref ref-type="bibr" rid="ref88">Walter et al., 2017</xref>). Research has found that Cyanobacteria can synthesize 1,600 types of compounds (<xref ref-type="bibr" rid="ref9">Bohlin et al., 2010</xref>; <xref ref-type="bibr" rid="ref58">Nagarajan et al., 2012</xref>), which play positive roles in antiviral, antibacterial, and immunomodulatory aspects (<xref ref-type="bibr" rid="ref75">Sieber and Marahiel, 2005</xref>; <xref ref-type="bibr" rid="ref23">De Morais et al., 2015</xref>; <xref ref-type="bibr" rid="ref68">Sathasivam et al., 2019</xref>), thus they are widely applied in various fields. In addition, Cyanobacteria have significant anti-cancer effects, for example, Somocystinamide A (ScA), a lipopeptide compound isolated from Cyanobacteria, can inhibit tumor cell proliferation by inducing programmed cell death (<xref ref-type="bibr" rid="ref91">Wrasidlo et al., 2008</xref>, p. 8). Curacin A, produced by Cyanobacteria, is a hybrid polyketide-peptide compound and an effective anticancer agent (<xref ref-type="bibr" rid="ref15">Catassi et al., 2006</xref>). It can induce cancer cell death by inhibiting the activity of microtubule protein polymerization (<xref ref-type="bibr" rid="ref7">Blokhin et al., 1995</xref>). In the results of this study, the phylum Cyanobacteria was found to decrease the risk of NHL, which is similar to the aforementioned previous research findings. Based on previous studies, we speculate that Cyanobacteria may also exhibit similar anticancer effects in NHL. Furthermore, most cancer-related chemotherapy drugs are derived from natural products in nature (<xref ref-type="bibr" rid="ref76">Sithranga Boopathy and Kathiresan, 2010</xref>), and Cyanobacteria not only exist in the human gut but can also be obtained from marine (<xref ref-type="bibr" rid="ref55">Mondal et al., 2020</xref>), soil, and agricultural runoff (<xref ref-type="bibr" rid="ref70">Senousy et al., 2020</xref>). Hence, future research could delve into the anticancer mechanisms of Cyanobacteria in NHL, thereby laying the groundwork for the extraction and development of novel drugs related to NHL from natural products.</p>
<p><italic>Ruminococcus gnavus</italic> is a Gram-positive anaerobic bacterium found primarily within the gastrointestinal tract of humans and animals (<xref ref-type="bibr" rid="ref61">Qin et al., 2010</xref>). In terms of human health, <italic>Ruminococcus gnavus</italic> constitutes a significant proportion of the infant GM (<xref ref-type="bibr" rid="ref65">Sagheddu et al., 2016</xref>), correlating with infant nutrition absorption (<xref ref-type="bibr" rid="ref92">Yatsunenko et al., 2012</xref>) and growth development (<xref ref-type="bibr" rid="ref52">Mennella et al., 2022</xref>), with these effects persisting into adulthood. In terms of disease, <italic>Ruminococcus gnavus</italic> is closely associated with gastrointestinal diseases and immune regulation. Research revealed that the relative abundance of <italic>Ruminococcus gnavus</italic> in normal humans is usually below 1%, while in some inflammatory bowel disease patients, it can reach around 70% (<xref ref-type="bibr" rid="ref95">Zhang et al., 2023</xref>). However, some researchers found that after transferring <italic>Ruminococcus gnavus</italic> and other microbes into colorectal cancer mice, <italic>Ruminococcus gnavus</italic> could inhibit tumor growth and activate the immune surveillance function of CD8<sup>+</sup> T cells (<xref ref-type="bibr" rid="ref95">Zhang et al., 2023</xref>). Therefore, the role of <italic>Ruminococcus gnavus</italic> in the human body is complex, and its effects on disease are influenced by multiple factors. In this study, the genus <italic>Ruminococcus gnavus</italic> group was identified as a beneficial bacterium for NHL, which can reduce the risk of its occurrence. Lachnospiraceae and <italic>Ruminococcus gnavus</italic> belong to the phylum Firmicutes. Lachnospiraceae is a family of gut bacteria that is widely present in the gastrointestinal tract of fauna (<xref ref-type="bibr" rid="ref28">Gosalbes et al., 2011</xref>; <xref ref-type="bibr" rid="ref51">Meehan and Beiko, 2014</xref>). It is an important member of the human GM, accounting for approximately 10 to 45% of the total bacterial population (<xref ref-type="bibr" rid="ref44">Liu et al., 2021</xref>). Lachnospiraceae can be divided into different genera, such as Lachnospira, Oribacterium, and Dorea (<xref ref-type="bibr" rid="ref85">Vacca et al., 2020</xref>), which are the primary contributors to short-chain fatty acids that are beneficial to human health (<xref ref-type="bibr" rid="ref86">Vital et al., 2014</xref>; <xref ref-type="bibr" rid="ref16">Chambers et al., 2015</xref>; <xref ref-type="bibr" rid="ref13">Bui et al., 2021</xref>). Meloxicam, a nonsteroidal anti-inflammatory drug, is associated with reducing the risk of cancer, while Lachnospiraceae can produce meloxicam by altering the heterocyclic structure of flavonoids (<xref ref-type="bibr" rid="ref80">Sugiyama et al., 2013</xref>; <xref ref-type="bibr" rid="ref12">Braune and Blaut, 2016</xref>). Although there is limited research on the association between Lachnospiraceae and NHL, and it is not commonly found in other hematological tumors (<xref ref-type="bibr" rid="ref30">Guevara-Ram&#x00ED;rez et al., 2023</xref>), the viewpoint of Lachnospiraceae being considered beneficial bacteria in previous literature is similar to the results of this study. Therefore, more attention should be paid to the study of the association between the phylum Firmicutes and NHL as well as blood tumors, to clearly elucidate the specific mechanisms by which Lachnospiraceae may contribute to the treatment of NHL, thereby providing new insights into the prevention and treatment of NHL.</p>
<p>Bifidobacterium is a well-recognized beneficial microorganism for human health (<xref ref-type="bibr" rid="ref33">Hidalgo-Cantabrana et al., 2017</xref>; <xref ref-type="bibr" rid="ref42">Leser and Baker, 2023</xref>), with functions such as inhibiting intestinal pathogens (<xref ref-type="bibr" rid="ref57">Moreno Mu&#x00F1;oz et al., 2011</xref>), preventing gastrointestinal infections (<xref ref-type="bibr" rid="ref90">Weizman et al., 2005</xref>), improving gastrointestinal symptoms (<xref ref-type="bibr" rid="ref87">Waller et al., 2011</xref>), and regulating the immune system (<xref ref-type="bibr" rid="ref62">Roller et al., 2007</xref>), thus it is widely used in the food and pharmaceutical industries. Studies have shown that GM such as Bifidobacterium can influence the therapeutic effects of immunotherapy on tumors (<xref ref-type="bibr" rid="ref50">Matson et al., 2018</xref>). Bifidobacterium can also enhance the efficacy of ICIs in cancer mice by producing adenosine (<xref ref-type="bibr" rid="ref47">Mager et al., 2020</xref>). Chimeric antigen receptor T-cell immunotherapy (CAR-T) is a novel precision-targeted therapy for treating malignant tumors of the hematopoietic system. Studies have found that GM such as Bifidobacterium are associated with the efficacy of Chimeric antigen receptor T-cell therapy in BCL and can influence the progression of BCL (<xref ref-type="bibr" rid="ref79">Stein-Thoeringer et al., 2023</xref>). In addition, researchers have observed that the diversity of Bifidobacterium in multiple myeloma people after receiving CAR-T therapy vary depending on the efficacy of the treatment (<xref ref-type="bibr" rid="ref34">Hu et al., 2022</xref>). Therefore, the differences in the diversity and abundance of Bifidobacterium are important indicators for predicting the therapeutic effects of lymphoma and other malignant tumors of the hematopoietic system. This study found that Bifidobacterium can effectively reduce the risk of NHL, while previous literature has not addressed this aspect of research. Therefore, we hope that this study can provide valuable reference for future exploration. Moreover, existing studies indicate an association between Bifidobacterium and the immunotherapeutic effects on tumors such as BCL and multiple myeloma, yet they do not directly establish a connection between Bifidobacterium and BCL. Therefore, subsequent research can use this as a starting point.</p>
<p>In this study, we found that genus <italic>Faecalibacterium</italic> and genus <italic>Sellimonas</italic> are the only two intestinal microbiota that can increase the risk of NHL. However, it is worth noting that genus <italic>Faecalibacterium</italic> is commonly found in the population and is generally considered beneficial to health, with the potential to become the next generation of probiotics (<xref ref-type="bibr" rid="ref40">Langella et al., 2019</xref>). For example, <italic>Faecalibacterium prausnitzii</italic>, an important member of the genus <italic>Faecalibacterium</italic>, constitutes more than 5 percent of the overall fecal microbiome of healthy individuals. It can maintain the stability of the healthy gut environment (<xref ref-type="bibr" rid="ref54">Miquel et al., 2013</xref>) and also act as a probiotic to regulate the intestinal environment of Crohn&#x2019;s disease patients (<xref ref-type="bibr" rid="ref78">Sokol et al., 2008</xref>). Additionally, some species within the genus <italic>Faecalibacterium</italic> can produce significant amounts of fructose, providing energy for human colonic epithelial cells and supporting epithelial cell growth (<xref ref-type="bibr" rid="ref25">Fagundes et al., 2021</xref>; <xref ref-type="bibr" rid="ref60">Park J.-H. et al., 2022</xref>). Therefore, the results regarding genus <italic>Faecalibacterium</italic> in this study differ somewhat from previous related research. However, some researchers suggest that the interaction between <italic>Faecalibacterium</italic> and its host is not always constant (<xref ref-type="bibr" rid="ref48">Mart&#x00ED;n et al., 2023</xref>). Since the discovery of <italic>Faecalibacterium</italic>, with the continuous advancement of techniques such as 16S rRNA gene sequence as well as whole-genome sequencing, the taxonomy of this genus has been evolving. In 2021, two new species were added: <italic>Faecalibacterium butyricigenerans</italic> and <italic>Faecalibacterium longum</italic> (<xref ref-type="bibr" rid="ref99">Zou et al., 2021</xref>); and in 2022, three more new species were discovered, namely: <italic>Faecalibacterium duncaniae</italic>, <italic>Faecalibacterium hattorii</italic>, and <italic>Faecalibacterium gallinarum</italic> (<xref ref-type="bibr" rid="ref66">Sakamoto et al., 2022</xref>). Therefore, the interactions between the genus <italic>Faecalibacterium</italic> and the host are continually being updated. Further research is needed to explore the impact of <italic>Faecalibacterium</italic> on NHL.</p>
<p>The causal relationship between GM and NHL is influenced not only by internal factors but also by external factors such as diet, medication, and delivery type. Dietary fiber is an important nutrient that is difficult for the human body to digest and absorb. However, there is a significant association between a high consumption of fruits, soy, and green vegetables and a reduced risk of NHL (<xref ref-type="bibr" rid="ref18">Chiu, 1996</xref>; <xref ref-type="bibr" rid="ref89">Wei et al., 2016</xref>). It is worth noting that certain GM, such as Lachnospiraceae, can ferment dietary fiber and produce substances like short-chain fatty acids, increasing the content of butyrate in the body, thereby promoting apoptosis of lymphoma cells (<xref ref-type="bibr" rid="ref89">Wei et al., 2016</xref>; <xref ref-type="bibr" rid="ref94">Zaplana et al., 2024</xref>). Therefore, increasing the intake of dietary fiber in the body appropriately can promote the growth of GM such as Lachnospiraceae. Additionally, certain living biotherapeutic products (LBPs) associated with Lachnospiraceae have been attempted to be developed as probiotics to improve conditions such as metabolic syndrome (<xref ref-type="bibr" rid="ref26">Gilijamse et al., 2020</xref>). Probiotics are a type of beneficial active microorganisms for the human body. Bifidobacterium, as a crucial member of probiotics, plays an important role in the prevention and treatment of cancers such as colon cancer (<xref ref-type="bibr" rid="ref6">Bahmani et al., 2019</xref>), gastric cancer (<xref ref-type="bibr" rid="ref24">Devi et al., 2021</xref>), breast cancer (<xref ref-type="bibr" rid="ref74">Shimizu et al., 2020</xref>), and lung cancer (<xref ref-type="bibr" rid="ref2">An et al., 2020</xref>). This study identified a significant number of GM, including Bifidobacterium and <italic>Ruminococcus gnavus</italic>, that may potentially reduce the risk of NHL. Whether these GM can participate in the prevention and treatment of NHL as probiotics or other forms such as LBPs in the future is worth exploring.</p>
<p>The research has a few restrictions. Firstly, since the data on GM and NHL and its subtypes are all from European populations, we cannot guarantee whether the results are applicable to other populations. The GM dataset included in this study is currently the largest GWAS dataset of GM, but it predominantly focuses on the European population, hence there are limitations in generalizing to other populations. As GWAS databases of GM in various populations continue to be updated, we will continue to monitor research on the causal relationship between GM and NHL in other populations. Secondly, there are fewer cases in certain subtypes of NHL, such as MZBL, MCL, and T/NK cell lymphoma, which limits the scope of the study. We will continue to monitor this aspect of the research as the FinnGen database is continually updated. Lastly, this study only elucidates the causality between GM and NHL, and the underlying mechanisms driving this association are not yet clear, requiring further research for support.</p>
</sec>
<sec sec-type="conclusions" id="sec17">
<label>5</label>
<title>Conclusion</title>
<p>Through this study, we have identified the causality between GM and NHL, and determined the beneficial and harmful microbiota for NHL. In the future, it may be considered to selectively alter these GM through measures such as diet, probiotics, and prebiotics to influence NHL. Additionally, the development of targeted and effective GM in clinical settings holds certain reference significance as novel therapeutic modalities and monitoring indicators for NHL. Therefore, this research offers novel ideas to prevent, monitor, and cure NHL later.</p>
</sec>
<sec sec-type="data-availability" id="sec18">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="sec23">Supplementary material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="author-contributions" id="sec19">
<title>Author contributions</title>
<p>JF: Data curation, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing, Software. ZH: Funding acquisition, Project administration, Resources, Supervision, Validation, Writing &#x2013; review &#x0026; editing.</p>
</sec>
</body>
<back>
<sec sec-type="funding-information" id="sec20">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the scientific research project of the State Administration of Traditional Chinese Medicine (GZY-KJS-2020-037).</p>
</sec>
<ack>
<p>We express our sincere gratitude to the FinnGen and GWAS Catalog personnel and volunteers, as well as the MiBioGen consortium, for their invaluable contribution in supplying gut microbiology data.</p>
</ack>
<sec sec-type="COI-statement" id="sec21">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="sec22">
<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 sec-type="supplementary-material" id="sec23">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fmicb.2024.1403825/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fmicb.2024.1403825/full#supplementary-material</ext-link></p>
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