<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="research-article"><front><journal-meta><journal-id journal-id-type="nlm-ta">Interact J Med Res</journal-id><journal-id journal-id-type="publisher-id">i-jmr</journal-id><journal-id journal-id-type="index">3</journal-id><journal-title>Interactive Journal of Medical Research</journal-title><abbrev-journal-title>Interact J Med Res</abbrev-journal-title><issn pub-type="epub">1929-073X</issn><publisher><publisher-name>JMIR Publications</publisher-name><publisher-loc>Toronto, Canada</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">v14i1e72244</article-id><article-id pub-id-type="doi">10.2196/72244</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Paper</subject></subj-group></article-categories><title-group><article-title>Association of Modifiable Lifestyle and Metabolic Factors With the Risk of Developing Sepsis: 2-Sample Mendelian Randomized Study</article-title></title-group><contrib-group><contrib contrib-type="author" equal-contrib="yes"><name name-style="western"><surname>Lv</surname><given-names>Haifeng</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="fn" rid="equal-contrib1">*</xref></contrib><contrib contrib-type="author" equal-contrib="yes"><name name-style="western"><surname>Liu</surname><given-names>Jing</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="equal-contrib1">*</xref></contrib><contrib contrib-type="author" equal-contrib="yes"><name name-style="western"><surname>Cao</surname><given-names>Yelin</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="fn" rid="equal-contrib1">*</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Fan</surname><given-names>Weina</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Shen</surname><given-names>Guojie</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Wang</surname><given-names>Feifei</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Ye</surname><given-names>Qingqing</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Wu</surname><given-names>Xiaoliang</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>Xu</surname><given-names>Kaijin</given-names></name><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="aff" rid="aff4">4</xref></contrib></contrib-group><aff id="aff1"><institution>Department of Intensive Care Unit, The First Affiliated Hospital, Zhejiang University School of Medicine</institution><addr-line>Hangzhou</addr-line><country>China</country></aff><aff id="aff2"><institution>Department of Hepatology, The Affiliated Hospital of Hangzhou Normal University</institution><addr-line>Hangzhou</addr-line><country>China</country></aff><aff id="aff3"><institution>State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, China-Singapore Belt and Road Joint Laboratory on Infection Research and Drug Development, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine</institution><addr-line>No.79 Qingchun Road, Shangcheng District, Zhejiang Province</addr-line><addr-line>Hangzhou</addr-line><country>China</country></aff><aff id="aff4"><institution>Yuhang Institute for Collaborative Innovation and Translational Research in Life Sciences and Technology</institution><addr-line>Hangzhou</addr-line><country>China</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Cahill</surname><given-names>Naomi</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>He</surname><given-names>Binsheng</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>Abasilim</surname><given-names>Ogochukwu</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Kaijin Xu, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, China-Singapore Belt and Road Joint Laboratory on Infection Research and Drug Development, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, No.79 Qingchun Road, Shangcheng District, Zhejiang Province, Hangzhou, 310003, China, 86 13750870030; <email>zdyxyxkj@zju.edu.cn</email></corresp><fn fn-type="equal" id="equal-contrib1"><label>*</label><p>these authors contributed equally</p></fn></author-notes><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>3</day><month>11</month><year>2025</year></pub-date><volume>14</volume><elocation-id>e72244</elocation-id><history><date date-type="received"><day>06</day><month>02</month><year>2025</year></date><date date-type="rev-recd"><day>01</day><month>10</month><year>2025</year></date><date date-type="accepted"><day>01</day><month>10</month><year>2025</year></date></history><copyright-statement>&#x00A9; Haifeng Lv, Jing Liu, Yelin Cao, Weina Fan, Guojie Shen, Feifei Wang, Qingqing Ye, Xiaoliang Wu, Kaijin Xu. Originally published in the Interactive Journal of Medical Research (<ext-link ext-link-type="uri" xlink:href="https://www.i-jmr.org/">https://www.i-jmr.org/</ext-link>), 3.11.2025. </copyright-statement><copyright-year>2025</copyright-year><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Interactive Journal of Medical Research, is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://www.i-jmr.org/">https://www.i-jmr.org/</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://www.i-jmr.org/2025/1/e72244"/><abstract><sec><title>Background</title><p>Sepsis is a life-threatening condition characterized by organ dysfunction resulting from dysregulated host response to infections. Approximately 48.9 million people worldwide are diagnosed with sepsis annually, leading to 11 million deaths and representing 19.7% of all global deaths. No specific, effective treatments for sepsis, which has a poor prognosis, are available.</p></sec><sec><title>Objective</title><p>The study aimed to systematically explore the association between genetically predicted modifiable risk factors and sepsis.</p></sec><sec sec-type="methods"><title>Methods</title><p>Univariable 2-sample Mendelian randomization (MR) analysis was performed to explore the association between 30 modifiable risk factors (12 lifestyle, 3 educational and psychological, and 15 metabolic factors) and sepsis. Heterogeneity was evaluated using the Cochran <italic>Q</italic> analysis. Sensitivity analyses were conducted using the MR-Egger regression intercept tests and leave-one-out analyses. Additionally, multivariable MR analyses were performed to adjust for genetic associations between the instruments and obesity.</p></sec><sec sec-type="results"><title>Results</title><p>Genetically predicted smoking (odds ratio [OR] 1.20, 95% CI 1.06&#x2010;1.36; <italic>P</italic>=.005), a higher number of cigarettes smoked daily (OR 1.70, 95% CI 1.29&#x2010;2.23; <italic>P</italic>&#x003C;.001), a higher overall health rating (OR 2.19, 95% CI 1.61&#x2010;2.98; <italic>P</italic>&#x003C;.001), BMI (OR 1.50, 95% CI 1.38&#x2010;1.63; <italic>P</italic>&#x003C;.001), waist circumference (OR 1.70, 95% CI 1.53&#x2010;1.89; <italic>P</italic>&#x003C;.001), whole body fat mass (OR 1.50, 95% CI 1.37&#x2010;1.64; <italic>P</italic>&#x003C;.001), trunk fat mass (OR 1.48, 95% CI 1.36&#x2010;1.62; <italic>P</italic>&#x003C;.001), arm fat mass (OR 1.57, 95% CI 1.43&#x2010;1.71; <italic>P</italic>&#x003C;.001), and leg fat mass (OR 1.69, 95% CI 1.51&#x2010;1.90; <italic>P</italic>&#x003C;.001) were associated with increased sepsis risk. However, light physical activity (OR 0.26, 95% CI 0.08&#x2010;0.83; <italic>P</italic>=.03), higher education attainment (OR 0.52, 95% CI 0.40&#x2010;0.67; <italic>P</italic>&#x003C;.001), and high-density lipoprotein cholesterol (OR 0.91, 95% CI 0.84&#x2010;0.98; <italic>P</italic>=.02) exhibited protective effects against sepsis. Using a multivariate analysis of obesity traits, the waist circumference (OR 2.16, 95% CI 1.18&#x2010;3.96; <italic>P</italic>=.01) was an independent risk factor of sepsis.</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>Our study demonstrated that genetic predictors of lifestyle (smoking and physical activity), educational level, and metabolic factors (waist circumference and high-density lipoprotein cholesterol) exhibited a causal association with sepsis risk. Future research should further investigate the underlying mechanisms of these associations to inform more effective preventive strategies against sepsis.</p></sec></abstract><kwd-group><kwd>Mendelian randomization</kwd><kwd>sepsis</kwd><kwd>modifiable factors</kwd><kwd>lifestyle</kwd><kwd>metabolism</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>Sepsis is a life-threatening condition characterized by organ dysfunction resulting from a dysregulated host response to infections [<xref ref-type="bibr" rid="ref1">1</xref>]. Epidemiological studies indicate that approximately 48.9 million people worldwide were diagnosed with sepsis annually, leading to 11 million deaths and representing 19.7% of all global deaths [<xref ref-type="bibr" rid="ref2">2</xref>]. In China, sepsis affects 20% of patients in intensive care units, with a 90-day mortality rate of 35.5% [<xref ref-type="bibr" rid="ref3">3</xref>]. The substantial epidemiological burden underscores the critical importance of sepsis as a public health issue [<xref ref-type="bibr" rid="ref4">4</xref>]. Despite decades of research, current therapies remain limited to organ support and antimicrobial interventions, without any targeted treatment available [<xref ref-type="bibr" rid="ref5">5</xref>-<xref ref-type="bibr" rid="ref7">7</xref>]. These limited therapeutic options highlight the urgent need for shifting focus toward modifiable risk factors for prevention. The World Health Organization 2020 Sepsis Report specifically highlights vulnerable populations and health care seekers, while outlining future research directions and priorities in sepsis epidemiology. Although sepsis manifests diversely and can be life-threatening, it remains preventable and reversible [<xref ref-type="bibr" rid="ref4">4</xref>].</p><p>Host risk factors for sepsis are multifaceted, encompassing extremes of age, immunosuppression, and comorbidities [<xref ref-type="bibr" rid="ref8">8</xref>,<xref ref-type="bibr" rid="ref9">9</xref>]. Emerging evidence suggests that socioeconomic determinants (eg, education level and occupation) and metabolic disorders (eg, obesity and diabetes) may influence susceptibility to sepsis [<xref ref-type="bibr" rid="ref10">10</xref>-<xref ref-type="bibr" rid="ref16">16</xref>]. However, the existing observational studies report inconsistent conclusions. For instance, although lower socioeconomic status is broadly linked to higher sepsis incidence [<xref ref-type="bibr" rid="ref10">10</xref>,<xref ref-type="bibr" rid="ref11">11</xref>], another study paradoxically found no association using adjusted models [<xref ref-type="bibr" rid="ref17">17</xref>]. Metabolic comorbidities further illustrate this ambiguity. Although obesity is widely implicated in sepsis risk [<xref ref-type="bibr" rid="ref18">18</xref>], some observational studies found that individuals with obesity showed a lower incidence and fatality than did those with underweight among patients with sepsis. These discrepancies may stem from methodological limitations in observational research, such as residual confounding and reverse causality. For instance, sepsis-induced systemic inflammation could transiently alter metabolic markers, obscuring true causal directions.</p><p>The core idea of Mendelian randomization (MR) is to use genetic variants (typically single-nucleotide polymorphisms [SNPs]) as instrumental variables to infer whether a potential causal association exists between an exposure and a health outcome. Recent MR studies have explored individual factors such as obesity, diabetes mellitus, and lipid profiles in patients with sepsis [<xref ref-type="bibr" rid="ref19">19</xref>-<xref ref-type="bibr" rid="ref23">23</xref>]; however, critical gaps persist. First, lifestyle factors (eg, smoking and diet) remain understudied despite their clinical relevance. Second, the existing MR analyses of sepsis predominantly examine isolated risk factors, neglecting potential synergies between socioeconomic, metabolic, and behavioral determinants [<xref ref-type="bibr" rid="ref8">8</xref>,<xref ref-type="bibr" rid="ref9">9</xref>,<xref ref-type="bibr" rid="ref24">24</xref>-<xref ref-type="bibr" rid="ref28">28</xref>]. Third, the interaction between modifiable factors and genetic predisposition remains unexplored, limiting personalized preventive strategies.</p><p>To address these gaps, we conducted a comprehensive 2-sample MR analysis of 30 modifiable factors spanning lifestyle, socioeconomic status, and metabolic health. This approach not only circumvents confounding biases but also systematically evaluates multifactorial contributions to sepsis pathogenesis. Our findings aimed to clarify controversial associations in prior literature and prioritize actionable targets for intervention.</p></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>MR Design</title><p>MR is based on three key assumptions: genetic variants are (1) linked to risk factors, (2) independent of confounding factors, and (3) influence outcomes solely through risk factors (<xref ref-type="fig" rid="figure1">Figure 1</xref>). A total of 30 prominent modifiable risk factors were included and grouped into lifestyle and metabolic factors. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines. Initially, we screened instrumental variables for MR analysis using lifestyle factors and metabolic comorbidities as &#x201C;exposures&#x201D; and sepsis as &#x201C;outcomes.&#x201D; Subsequently, we conducted a reverse MR analysis, with sepsis as the &#x201C;exposure&#x201D; and lifestyle and metabolic factors as the &#x201C;outcomes.&#x201D;</p><fig position="float" id="figure1"><label>Figure 1.</label><caption><p>Overview of the design and methods used in this Mendelian randomization (MR) study. MR analysis was used to explore the causal relationships, including the following groups: lifestyles and metabolic factors. Solid arrows represent causal effects, and dashed arrows and crosses represent causal effects prohibited by MR assumptions II and III. HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; T2DM: type 2 diabetes mellitus.</p></caption><graphic alt-version="no" mimetype="image" position="float" xlink:type="simple" xlink:href="i-jmr_v14i1e72244_fig01.png"/></fig></sec><sec id="s2-2"><title>Data Sources</title><p>Genome-wide association study (GWAS) data of sepsis were obtained from the OpenGWAS database, a dataset published by the UK Biobank in 2021, comprising a sample of 486,484 participants from European populations. Additionally, we used 30 parameters from the Integrative Epidemiology Unit OpenGWAS Project as our lifestyle, education and psychology, and metabolic traits. Data are listed in <xref ref-type="table" rid="table1">Table 1</xref>.</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Characteristics of the genome&#x2010;wide association study (GWAS) summary data in this study.</p></caption><table id="table1" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Exposure</td><td align="left" valign="bottom">Ethnicity</td><td align="left" valign="bottom">GWAS ID</td><td align="left" valign="bottom">Total population, n</td><td align="left" valign="bottom">SNPs<sup><xref ref-type="table-fn" rid="table1fn1">a</xref></sup>, n</td></tr></thead><tbody><tr><td align="left" valign="top" colspan="5">Diet</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Alcohol consumption</td><td align="left" valign="top">European</td><td align="left" valign="top">ieu-b-73</td><td align="left" valign="top">335,394</td><td align="left" valign="top">11,887,865</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Coffee consumption</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-5237</td><td align="left" valign="top">428,860</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Milk consumption</td><td align="left" valign="top">South Asian</td><td align="left" valign="top">ukb-e-100520_CSA</td><td align="left" valign="top">1469</td><td align="left" valign="top">9,797,409</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Sweets consumption</td><td align="left" valign="top">African American</td><td align="left" valign="top">ukb-e-102330_AFR</td><td align="char" char="." valign="top">1207</td><td align="left" valign="top">15,533,528</td></tr><tr><td align="left" valign="top" colspan="5">Smoking</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Smoking initiation</td><td align="left" valign="top">European</td><td align="left" valign="top">ieu-b-4877</td><td align="left" valign="top">607,291</td><td align="left" valign="top">11,802,365</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Age of smoking</td><td align="left" valign="top">European</td><td align="left" valign="top">ieu-b-24</td><td align="left" valign="top">341,427</td><td align="left" valign="top">11,894,779</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Number of cigarettes daily</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-6019</td><td align="char" char="." valign="top">108,946</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top" colspan="5">Physical activity</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Light activit<bold>y</bold></td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-11495</td><td align="left" valign="top">460,376</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Moderate to vigorous</td><td align="left" valign="top">European</td><td align="left" valign="top">ebi-a-GCST006097</td><td align="left" valign="top">377,234</td><td align="left" valign="top">11,808,007</td></tr><tr><td align="left" valign="top" colspan="5">Sleep habit</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Insomnia</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-3957</td><td align="left" valign="top">462,341</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Nap during day</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-4616</td><td align="left" valign="top">462,400</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Sleep duration</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-4424</td><td align="left" valign="top">460,099</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top" colspan="5">Physical and mental</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Unhealthy emotions</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-6991</td><td align="char" char="." valign="top">459,560</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Overall health rating</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-16489</td><td align="left" valign="top">458,079</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top">College or university</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-6306</td><td align="left" valign="top">460,844</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top" colspan="5">Blood lipid traits</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Triglycerides</td><td align="left" valign="top">European</td><td align="left" valign="top">ieu-b-4850</td><td align="left" valign="top">78,700</td><td align="left" valign="top">7,892,037</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Total cholesterol</td><td align="left" valign="top">European</td><td align="left" valign="top">met-d-Total_C</td><td align="left" valign="top">115,078</td><td align="left" valign="top">12,321,875</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>HDL&#x2010;c<sup><xref ref-type="table-fn" rid="table1fn2">b</xref></sup></td><td align="left" valign="top">European</td><td align="left" valign="top">met-d-HDL_C</td><td align="char" char="." valign="top">115,078</td><td align="left" valign="top">12,321,875</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>LDL&#x2010;c<sup><xref ref-type="table-fn" rid="table1fn3">c</xref></sup></td><td align="left" valign="top">European</td><td align="left" valign="top">ie,u-b-110</td><td align="left" valign="top">440,546</td><td align="left" valign="top">12,321,875</td></tr><tr><td align="left" valign="top" colspan="5">Obesity traits</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>BMI</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-19953</td><td align="left" valign="top">461,460</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Waist circumference</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-9405</td><td align="left" valign="top">462,166</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Whole body fat mass</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-19393</td><td align="left" valign="top">454,137</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Trunk fat mass</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-20044</td><td align="left" valign="top">454,588</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Arm fat mass (left)</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-8338</td><td align="left" valign="top">454,684</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Leg fat mass (left)</td><td align="left" valign="top">European</td><td align="left" valign="top">ukb-b-7212</td><td align="left" valign="top">454,823</td><td align="left" valign="top">9,851,867</td></tr><tr><td align="left" valign="top" colspan="5">Metabolic syndrome</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>T2DM<sup><xref ref-type="table-fn" rid="table1fn4">d</xref></sup></td><td align="left" valign="top">European</td><td align="left" valign="top">ebi-a-GCST010118</td><td align="left" valign="top">433,540</td><td align="left" valign="top">11,222,507</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Hypertension</td><td align="left" valign="top">European</td><td align="left" valign="top">finn-b-I9_HYPTENS</td><td align="left" valign="top">162,837</td><td align="left" valign="top">16,380,466</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Cardiovascular diseases</td><td align="left" valign="top">European</td><td align="left" valign="top">finn-b-I9_CVD</td><td align="left" valign="top">107,684</td><td align="left" valign="top">16,380,466</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Ischemic stroke</td><td align="left" valign="top">European</td><td align="left" valign="top">ebi-a-GCST006908</td><td align="left" valign="top">440,328</td><td align="left" valign="top">8,296,492</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Percent liver fat</td><td align="left" valign="top">European</td><td align="left" valign="top">ebi-a-GCST90016673</td><td align="char" char="." valign="top">32,858</td><td align="left" valign="top">9,275,407</td></tr></tbody></table><table-wrap-foot><fn id="table1fn1"><p><sup>a</sup>SNP: single-nucleotide polymorphism.</p></fn><fn id="table1fn2"><p><sup>b</sup>HDL&#x2010;C: high-density lipoprotein cholesterol.</p></fn><fn id="table1fn3"><p><sup>c</sup>LDL&#x2010;C: low-density lipoprotein cholesterol.</p></fn><fn id="table1fn4"><p><sup>d</sup>T2DM: type 2 diabetes mellitus.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s2-3"><title>Selection of Genetic Variants</title><p>In this MR analysis, instrumental variables were used to investigate the association between potentially modifiable risk factors and sepsis. These risk traits were categorized into three main parts: (1) lifestyle factors encompassing 4 dietary traits, 3 smoking-related traits, 2 pertaining to physical activity, and 3 regarding sleep habits; (2) educational and psychological factors, including physical and mental well-being and education level; and (3) metabolic factors comprising 4 traits linked to blood lipid parameters, 6 associated with obesity traits, and 5 related to metabolic comorbidities. SNPs were selected as independent genetic predictors based on the following criteria: first, a genome-wide significance threshold of <italic>P</italic>&#x003C;5&#x00D7;10<sup>&#x2212;8</sup> was applied. If there were insufficient significant SNPs under this threshold, a threshold of <italic>P</italic>&#x003C;1&#x00D7;10<sup>&#x2212;5</sup> was used. Second, the clump function was used to test for linkage disequilibrium with a threshold of <italic>R</italic><sup>2</sup>&#x003C;0.001 and a distance of 10,000 kb. Third, SNPs related to outcomes were excluded using the linkage disequilibrium link database to avoid confounding factors. Fourth, SNPs with an <italic>F</italic> statistic &#x003C;10 were excluded to avoid bias from weak instruments. The proportion of exposure variance explained by genetic instruments (<italic>R</italic><sup>2</sup>) was calculated to quantify the strength of the genetic tools. The <italic>F</italic> statistic for each SNP was calculated to assess the strength of the selected instruments.</p></sec><sec id="s2-4"><title>Ethical Considerations</title><p>This study is a secondary analysis of publicly available GWAS summary statistics obtained from the Integrative Epidemiology Unit OpenGWAS database [<xref ref-type="bibr" rid="ref29">29</xref>] as shown in <xref ref-type="table" rid="table1">Table 1</xref>. These datasets consist of deidentified data from participant studies approved by an ethics committee concerning human experimentation, comply with the ethical principles of the Declaration of Helsinki, and were approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang University (2025B-1097).</p></sec><sec id="s2-5"><title>Statistical Analysis</title><p>In this study, all analyses were performed using the <italic>TwoSampleMR</italic> package in R (version 4.2.1; R Foundation for Statistical Computing). The random-effects inverse variance weighted (IVW) method was used as the primary outcome; this method assumed that all instrumental variables (SNPs) were valid instruments (ie, satisfying the exclusion restriction assumption) and estimated the causal effect between exposure and outcome by calculating the weighted regression slope of the SNP-outcome associations on the SNP-exposure associations. Although the IVW approach offered the highest statistical power among MR methods, it was sensitive to directional pleiotropy, which might have biased causal estimates if invalid SNPs were present. Therefore, the MR-Egger and weighted median methods were used to refine the IVW estimation. These alternative methods offered more dependable estimates across a broader spectrum of scenarios, albeit with a trade-off of reduced efficiency, resulting in wider CIs. MR-Egger permitted all genetic variants to exhibit pleiotropy; however, pleiotropy must be independent of variant exposure associations. Meanwhile, the weighted median method allowed the incorporation of potentially invalid instrumental variables under the assumption that at least half of the instruments used in the MR analysis were valid. We performed reverse MR analyses by swapping the roles of the original exposure and outcome variables; IVW analysis tests were conducted using the same set of SNPs.</p><p>Heterogeneity was evaluated using the Cochran <italic>Q</italic> analysis. Sensitivity analyses were conducted using MR-Egger regression intercept tests and leave-one-out analyses, with statistical significance set at <italic>P</italic>&#x003C;.05. Additionally, multivariable MR analyses were performed to adjust for the genetic association of the instruments with the BMI.</p></sec></sec><sec id="s3" sec-type="results"><title>Results</title><sec id="s3-1"><title>Baseline Characteristics</title><p>We assessed 30 potentially modifiable risk factors to investigate their causal associations with sepsis and categorized them into 3 groups (<xref ref-type="table" rid="table1">Table 1</xref>): lifestyle, educational and psychological, and metabolic factors. The number of SNPs ranged between 7,892,037 and 15,533,528 (<xref ref-type="table" rid="table1">Table 1</xref>). Notably, the <italic>F</italic> statistics for all considered traits exceeded 10, indicating the absence of a potential weak instrumental bias.</p></sec><sec id="s3-2"><title>Lifestyle Factors</title><p>Regarding the investigation of lifestyle factors, our findings revealed that genetically predicted smoking initiation (odds ratio [OR] 1.20, 95% CI 1.06&#x2010;1.36; <italic>P</italic>=.005) and a higher number of cigarettes smoked daily (OR 1.70, 95% CI 1.29&#x2010;2.23; <italic>P</italic>&#x003C;.001) were associated with an increased risk of sepsis. Conversely, genetically predicted light physical activity (OR 0.26, 95% CI 0.08&#x2010;0.83; <italic>P</italic>=.02) was associated with a decreased risk of sepsis. These results remained consistent across the random-effects IVW and weighted median analyses (<xref ref-type="table" rid="table2">Table 2</xref>). Notably, no significant causal association was detected between genetically predicted alcohol, coffee, milk, and sweet consumptions; age at smoking; moderate to vigorous physical activity; insomnia; daytime napping; sleep duration; and sepsis (all <italic>P</italic>&#x003E;.05). We did not find statistically significant results when investigating reverse causality validation (<italic>P</italic>&#x003E;.05).</p><table-wrap id="t2" position="float"><label>Table 2.</label><caption><p>Mendelian randomization (MR) estimates for the causal effect of modifiable lifestyle and metabolic factors on sepsis.</p></caption><table id="table2" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Exposure</td><td align="left" valign="bottom">SNPs<sup><xref ref-type="table-fn" rid="table2fn1">a</xref></sup>, n</td><td align="left" valign="bottom">IVW<sup><xref ref-type="table-fn" rid="table2fn2">b</xref></sup>,<break/>OR<sup><xref ref-type="table-fn" rid="table2fn3">c</xref></sup> (95% CI)</td><td align="left" valign="bottom"><italic>P</italic> value</td><td align="left" valign="bottom">WM<sup><xref ref-type="table-fn" rid="table2fn4">d</xref></sup>,<break/>OR (95% CI)</td><td align="left" valign="bottom"><italic>P</italic> value</td><td align="left" valign="bottom">MR-Egger,<break/>OR (95% CI)</td><td align="left" valign="bottom"><italic>P</italic> value</td><td align="left" valign="bottom">Cochran <italic>Q</italic>&#x2013;derived <italic>P</italic> value</td><td align="left" valign="bottom">MR-Egger intercept&#x2013;derived <italic>P</italic> value</td></tr></thead><tbody><tr><td align="left" valign="top" colspan="10">Diet</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Alcohol consumption</td><td align="left" valign="top">35</td><td align="left" valign="top">1.00 (0.76&#x2010;1.32)</td><td align="left" valign="top">.99</td><td align="left" valign="top">1.04 (0.69&#x2010;1.57)</td><td align="left" valign="top">.85</td><td align="left" valign="top">1.02 (0.64&#x2010;1.61)</td><td align="left" valign="top">.94</td><td align="left" valign="top">.34</td><td align="left" valign="top">.92</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Coffee consumption</td><td align="left" valign="top">39</td><td align="left" valign="top">1.14 (0.79&#x2010;1.64)</td><td align="left" valign="top">.48</td><td align="left" valign="top">1.10 (0.71&#x2010;1.71)</td><td align="left" valign="top">.67</td><td align="left" valign="top">0.88 (0.42&#x2010;1.83)</td><td align="left" valign="top">.73</td><td align="left" valign="top">.06</td><td align="left" valign="top">.43</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Milk consumption</td><td align="left" valign="top">5</td><td align="left" valign="top">0.97 (0.92&#x2010;1.03)</td><td align="left" valign="top">.29</td><td align="left" valign="top">0.95 (0.89&#x2010;1.02)</td><td align="left" valign="top">.19</td><td align="left" valign="top">1.29 (0.73&#x2010;2.28)</td><td align="left" valign="top">.45</td><td align="left" valign="top">.71</td><td align="left" valign="top">.40</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Sweets consumption</td><td align="left" valign="top">11</td><td align="left" valign="top">0.99 (0.97&#x2010;1.01)</td><td align="left" valign="top">.47</td><td align="left" valign="top">0.99 (0.97&#x2010;1.02)</td><td align="left" valign="top">.64</td><td align="left" valign="top">1.05 (0.99&#x2010;1.11)</td><td align="left" valign="top">.110</td><td align="left" valign="top">.25</td><td align="left" valign="top">.06</td></tr><tr><td align="left" valign="top" colspan="10">Smoking</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Smoking initiation</td><td align="left" valign="top">86</td><td align="left" valign="top">1.20 (1.06&#x2010;1.36)</td><td align="left" valign="top">.005</td><td align="left" valign="top">1.22 (1.02&#x2010;1.47)</td><td align="left" valign="top">.034</td><td align="left" valign="top">1.72 (0.90&#x2010;3.28)</td><td align="left" valign="top">.10</td><td align="left" valign="top">.41</td><td align="left" valign="top">.27</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Age of smoking</td><td align="left" valign="top">7</td><td align="left" valign="top">0.89 (0.46&#x2010;1.71)</td><td align="left" valign="top">.723</td><td align="left" valign="top">1.25 (0.56&#x2010;2.79)</td><td align="left" valign="top">.59</td><td align="left" valign="top">0.32 (0.04&#x2010;2.68)</td><td align="left" valign="top">.34</td><td align="left" valign="top">.28</td><td align="left" valign="top">.37</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Number of cigarettes daily</td><td align="left" valign="top">6</td><td align="left" valign="top">1.70 (1.29&#x2010;2.23)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.72 (1.25&#x2010;2.36)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">2.30 (1.31&#x2010;4.04)</td><td align="left" valign="top">.04</td><td align="left" valign="top">.86</td><td align="left" valign="top">.29</td></tr><tr><td align="left" valign="top" colspan="10">Physical activity</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Light activity</td><td align="left" valign="top">12</td><td align="left" valign="top">0.26 (0.08&#x2010;0.83)</td><td align="left" valign="top">.03</td><td align="left" valign="top">0.12 (0.03&#x2010;0.58)</td><td align="left" valign="top">.007</td><td align="left" valign="top">1.12 (0.02&#x2010;78.84)</td><td align="left" valign="top">.96</td><td align="left" valign="top">.74</td><td align="left" valign="top">.50</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Moderate to vigorous</td><td align="left" valign="top">19</td><td align="left" valign="top">0.98 (0.61&#x2010;1.57)</td><td align="left" valign="top">.92</td><td align="left" valign="top">1.10 (0.58&#x2010;2.06)</td><td align="left" valign="top">.78</td><td align="left" valign="top">0.27 (0.03&#x2010;2.58)</td><td align="left" valign="top">.27</td><td align="left" valign="top">.68</td><td align="left" valign="top">.27</td></tr><tr><td align="left" valign="top" colspan="10">Sleep habit</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Insomnia</td><td align="left" valign="top">38</td><td align="left" valign="top">1.08 (0.63&#x2010;1.87)</td><td align="left" valign="top">.77</td><td align="left" valign="top">1.02 (0.50&#x2010;2.07)</td><td align="left" valign="top">.95</td><td align="left" valign="top">0.52 (0.09&#x2010;2.94)</td><td align="left" valign="top">.46</td><td align="left" valign="top">.02</td><td align="left" valign="top">.39</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Nap during day</td><td align="left" valign="top">88</td><td align="left" valign="top">1.04 (0.74&#x2010;1.45)</td><td align="left" valign="top">.84</td><td align="left" valign="top">0.93 (0.55&#x2010;1.57)</td><td align="left" valign="top">.79</td><td align="left" valign="top">1.45 (0.46&#x2010;4.55)</td><td align="left" valign="top">.53</td><td align="left" valign="top">.45</td><td align="left" valign="top">.55</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Sleep duration</td><td align="left" valign="top">65</td><td align="left" valign="top">0.80 (0.57&#x2010;1.11)</td><td align="left" valign="top">.19</td><td align="left" valign="top">0.83 (0.50&#x2010;1.36)</td><td align="left" valign="top">.45</td><td align="left" valign="top">1.17 (0.32&#x2010;4.32)</td><td align="left" valign="top">.81</td><td align="left" valign="top">.27</td><td align="left" valign="top">.55</td></tr><tr><td align="left" valign="top" colspan="10">Physical and mental</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Unhealthy emotions</td><td align="left" valign="top">41</td><td align="left" valign="top">1.36 (0.67&#x2010;2.74)</td><td align="left" valign="top">.40</td><td align="left" valign="top">1.22 (0.45&#x2010;3.30)</td><td align="left" valign="top">.70</td><td align="left" valign="top">0.48 (0.01&#x2010;22.66)</td><td align="left" valign="top">.71</td><td align="left" valign="top">.81</td><td align="left" valign="top">.59</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Overall health rating</td><td align="left" valign="top">106</td><td align="left" valign="top">2.19 (1.61&#x2010;2.98)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.63 (1.09&#x2010;2.44)</td><td align="left" valign="top">.02</td><td align="left" valign="top">2.33 (0.49&#x2010;11.00)</td><td align="left" valign="top">.29</td><td align="left" valign="top">.02</td><td align="left" valign="top">.94</td></tr><tr><td align="left" valign="top">College or university</td><td align="left" valign="top">242</td><td align="left" valign="top">0.52 (0.40&#x2010;0.67)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">0.55 (0.37&#x2010;0.82)</td><td align="left" valign="top">.003</td><td align="left" valign="top">0.52 (0.18&#x2010;1.51)</td><td align="left" valign="top">.23</td><td align="left" valign="top">.85</td><td align="left" valign="top">.97</td></tr><tr><td align="left" valign="top" colspan="10">Blood lipid traits</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Triglycerides</td><td align="left" valign="top">38</td><td align="left" valign="top">1.00 (0.89&#x2010;1.13)</td><td align="left" valign="top">.94</td><td align="left" valign="top">1.02 (0.88&#x2010;1.18)</td><td align="left" valign="top">.80</td><td align="left" valign="top">1.14 (0.91&#x2010;1.42)</td><td align="left" valign="top">.25</td><td align="left" valign="top">.008</td><td align="left" valign="top">.20</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Total cholesterol</td><td align="left" valign="top">359</td><td align="left" valign="top">0.97 (0.89&#x2010;1.05)</td><td align="left" valign="top">.47</td><td align="left" valign="top">0.98 (0.87&#x2010;1.10)</td><td align="left" valign="top">.70</td><td align="left" valign="top">1.00 (0.88&#x2010;1.14)</td><td align="left" valign="top">.99</td><td align="left" valign="top">.02</td><td align="left" valign="top">.51</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>HDL&#x2010;c<sup><xref ref-type="table-fn" rid="table2fn5">e</xref></sup></td><td align="left" valign="top">91</td><td align="left" valign="top">0.91 (0.84&#x2010;0.98)</td><td align="left" valign="top">.02</td><td align="left" valign="top">0.89 (0.79&#x2010;0.99)</td><td align="left" valign="top">.04</td><td align="left" valign="top">0.86 (0.76&#x2010;0.98)</td><td align="left" valign="top">.02</td><td align="left" valign="top">.01</td><td align="left" valign="top">.33</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>LDL&#x2010;c<sup><xref ref-type="table-fn" rid="table2fn6">f</xref></sup></td><td align="left" valign="top">173</td><td align="left" valign="top">1.05 (0.97&#x2010;1.13)</td><td align="left" valign="top">.22</td><td align="left" valign="top">1.06 (0.93&#x2010;1.20)</td><td align="left" valign="top">.36</td><td align="left" valign="top">1.08 (0.97&#x2010;1.21)</td><td align="left" valign="top">.17</td><td align="left" valign="top">.39</td><td align="left" valign="top">.45</td></tr><tr><td align="left" valign="top" colspan="10">Obesity traits</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>BMI</td><td align="left" valign="top">432</td><td align="left" valign="top">1.50 (1.38&#x2010;1.63)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.47 (1.25&#x2010;1.72)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.47 (1.17&#x2010;1.85)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">.21</td><td align="left" valign="top">.85</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Waist circumference</td><td align="left" valign="top">357</td><td align="left" valign="top">1.70 (1.53&#x2010;1.89)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.64 (1.36&#x2010;1.98)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.52 (1.12&#x2010;2.05)</td><td align="left" valign="top">.008</td><td align="left" valign="top">.32</td><td align="left" valign="top">.43</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Whole body fat mass</td><td align="left" valign="top">412</td><td align="left" valign="top">1.50 (1.37&#x2010;1.64)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.51 (1.31&#x2010;1.75)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.50 (1.16&#x2010;1.93)</td><td align="left" valign="top">.002</td><td align="left" valign="top">.05</td><td align="left" valign="top">.99</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Trunk fat mass</td><td align="left" valign="top">399</td><td align="left" valign="top">1.48 (1.36&#x2010;1.62)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.51 (1.31&#x2010;1.75)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.02 (1.31&#x2010;1.68)</td><td align="left" valign="top">.03</td><td align="left" valign="top">.08</td><td align="left" valign="top">.29</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Arm fat mass (left)</td><td align="left" valign="top">402</td><td align="left" valign="top">1.57 (1.43&#x2010;1.71)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.52 (1.30&#x2010;1.77)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.57 (1.22&#x2010;2.00)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">.14</td><td align="left" valign="top">.99</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Leg fat mass (left)</td><td align="left" valign="top">397</td><td align="left" valign="top">1.69 (1.51-1.90)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.65 (1.37-1.99)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">1.34 (1.83-2.53)</td><td align="left" valign="top">&#x003C;.001</td><td align="left" valign="top">.11</td><td align="left" valign="top">.59</td></tr><tr><td align="left" valign="top" colspan="10">Metabolic syndrome</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>T2DM<sup><xref ref-type="table-fn" rid="table2fn7">g</xref></sup></td><td align="left" valign="top">148</td><td align="left" valign="top">1.03 (0.99&#x2010;1.07)</td><td align="left" valign="top">.16</td><td align="left" valign="top">1.05 (0.98&#x2010;1.11)</td><td align="left" valign="top">.14</td><td align="left" valign="top">1.07 (0.99&#x2010;1.15)</td><td align="left" valign="top">.11</td><td align="left" valign="top">.11</td><td align="left" valign="top">.31</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Hypertension</td><td align="left" valign="top">55</td><td align="left" valign="top">1.00 (0.94&#x2010;1.06)</td><td align="left" valign="top">.98</td><td align="left" valign="top">0.97 (0.90&#x2010;1.06)</td><td align="left" valign="top">.56</td><td align="left" valign="top">0.86 (0.70&#x2010;1.05)</td><td align="left" valign="top">.15</td><td align="left" valign="top">.52</td><td align="left" valign="top">.13</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Cardiovascular diseases</td><td align="left" valign="top">9</td><td align="left" valign="top">1.09 (0.91&#x2010;1.32)</td><td align="left" valign="top">.35</td><td align="left" valign="top">0.96 (0.75&#x2010;1.22)</td><td align="left" valign="top">.75</td><td align="left" valign="top">0.52 (0.21&#x2010;1.32)</td><td align="left" valign="top">.21</td><td align="left" valign="top">.66</td><td align="left" valign="top">.16</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Ischemic stroke</td><td align="left" valign="top">8</td><td align="left" valign="top">1.02 (0.88&#x2010;1.18)</td><td align="left" valign="top">.78</td><td align="left" valign="top">0.99 (0.82&#x2010;1.19)</td><td align="left" valign="top">.90</td><td align="left" valign="top">1.10 (0.37&#x2010;3.24)</td><td align="left" valign="top">.87</td><td align="left" valign="top">.81</td><td align="left" valign="top">.90</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Percent liver fat</td><td align="left" valign="top">10</td><td align="left" valign="top">1.02 (0.93&#x2010;1.11)</td><td align="left" valign="top">.66</td><td align="left" valign="top">1.02 (0.91&#x2010;1.13)</td><td align="left" valign="top">.76</td><td align="left" valign="top">0.96 (0.84&#x2010;1.10)</td><td align="left" valign="top">.59</td><td align="left" valign="top">.56</td><td align="left" valign="top">.30</td></tr></tbody></table><table-wrap-foot><fn id="table2fn1"><p><sup>a</sup>SNP: single-nucleotide polymorphism.</p></fn><fn id="table2fn2"><p><sup>b</sup>IVW: inverse variance weighted.</p></fn><fn id="table2fn3"><p><sup>c</sup>OR: odds ratio.</p></fn><fn id="table2fn4"><p><sup>d</sup>WM: weighted median.</p></fn><fn id="table2fn5"><p><sup>e</sup>HDL&#x2010;c: high&#x2010;density lipoprotein cholesterol.</p></fn><fn id="table2fn6"><p><sup>f</sup>LDL&#x2010;c: low-density lipoprotein cholesterol.</p></fn><fn id="table2fn7"><p><sup>g</sup>T2DM: type 2 diabetes mellitus.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s3-3"><title>Educational and Psychological Factors</title><p>Considering the investigation of educational and psychological factors, we found that genetically predicted higher overall health rating (OR 2.19, 95% CI 1.61&#x2010;2.98; <italic>P</italic>&#x003C;.001) was associated with an increased risk of sepsis (<xref ref-type="table" rid="table2">Table 2</xref>). Conversely, genetically predicted higher education attainment (individuals with a college or university degree; OR 0.52, 95% CI 0.40&#x2010;0.67; <italic>P</italic>&#x003C;.001) was associated with decreased risk of sepsis. Notably, no significant causal association was found between genetically driven unhealthy emotions and sepsis (<italic>P</italic>=.40). We did not find statistically significant results when investigating reverse causality validation (<italic>P</italic>&#x003E;.05).</p></sec><sec id="s3-4"><title>Metabolic Factors</title><p>We found an increased risk of sepsis associated with genetically predicted obesity. All fat mass&#x2013;related traits were significantly associated with an increased risk of sepsis. The odds of developing sepsis increased with every 1&#x2010;SD increment in the BMI (OR 1.50, 95% CI 1.38&#x2010;1.63; <italic>P</italic>&#x003C;.001), waist circumference (OR 1.70, 95% CI 1.53&#x2010;1.89; <italic>P</italic>&#x003C;.001), whole body fat mass (OR 1.50, 95% CI 1.37&#x2010;1.64; <italic>P</italic>&#x003C;.001), trunk fat mass (OR 1.48, 95% CI 1.36&#x2010;1.62; <italic>P</italic>&#x003C;.001), arm fat mass (left; OR 1.57, 95% CI 1.43&#x2010;1.71; <italic>P</italic>&#x003C;.001), and leg fat mass (left; OR 1.69, 95% CI 1.51&#x2010;1.90; <italic>P</italic>&#x003C;.001; <xref ref-type="table" rid="table2">Table 2</xref>). However, high-density lipoprotein cholesterol (HDL-C; OR 0.91, 95% CI 0.84&#x2010;0.98; <italic>P</italic>=.02) exhibited a protective effect against sepsis. In contrast, no significant causal association was observed between genetically predicted triglycerides, total cholesterol, low-density lipoprotein cholesterol, type 2 diabetes mellitus, hypertension, cardiovascular diseases, ischemic stroke, percent liver fat, and sepsis (all <italic>P</italic>&#x003E;.05).</p></sec><sec id="s3-5"><title>Reverse MR Analysis</title><p>To validate the reliability of the exposure-outcome causal direction, we performed reverse MR analysis by swapping the roles of the original exposure and outcome variables, and IVW analysis tests were conducted using the same set of SNPs. We did not find statistically significant results when investigating reverse causality validation (<italic>P</italic>&#x003E;.05).</p></sec><sec id="s3-6"><title>Multivariable MR Analysis</title><p>Considering the mutual influence of various obesity indicators, we conducted a multivariate MR analysis of BMI, waist circumference, whole body fat mass, trunk fat mass, arm fat mass (left), and leg fat mass (left). The results revealed that the waist circumference (OR 2.16, 95% CI 1.18&#x2010;3.96; <italic>P</italic>=.01) was an independent risk factor of sepsis (<xref ref-type="fig" rid="figure2">Figure 2</xref>).</p><fig position="float" id="figure2"><label>Figure 2.</label><caption><p>The association between obesity traits (BMI, waist circumference, whole body fat mass, trunk fat mass, arm fat mass, and leg fat mass) and sepsis by multivariable Mendelian randomization. Odds ratios (ORs) represent the associations with sepsis.</p></caption><graphic alt-version="no" mimetype="image" position="float" xlink:type="simple" xlink:href="i-jmr_v14i1e72244_fig02.png"/></fig></sec><sec id="s3-7"><title>Heterogeneity and Pleiotropy Test</title><p>Although some results displayed heterogeneity based on the Cochran <italic>Q</italic> test (<italic>P</italic>&#x003E;.05), the use of random-effects IVW as the primary outcome rendered this heterogeneity acceptable and did not undermine the validity of the MR estimates in this study (<xref ref-type="table" rid="table2">Table 2</xref>). In addition, the results were subjected to pleiotropy testing, demonstrating that those with significance did not exhibit pleiotropy. Therefore, assuming the absence of horizontal pleiotropy in this study is reasonable.</p></sec><sec id="s3-8"><title>Sensitivity Analysis</title><p>We conducted a sensitivity analysis using the MR-Egger intercept tests and the leave-one-out method. MR-Egger intercept tests showed no evidence of pleiotropy (<xref ref-type="table" rid="table2">Table 2</xref>). Using leave-one-out analysis, it is evident that nearly all lines align on one side of the y-axis, with minimal deviation beyond the axis. This consistency indicated the robustness of the results. The stable results shown in the MR visualization further corroborate the reliability of our study findings.</p></sec></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><p>In this bidirectional MR study, we investigated the association of lifestyle, educational and psychological, and metabolic factors with the risk of sepsis. Genetic variants such as smoking initiation, smoking frequency, and waist circumference were associated with an increased risk of sepsis, whereas light physical activity, higher education, and high levels of HDL-c were causally associated with a lower risk of sepsis (<xref ref-type="fig" rid="figure3">Figure 3</xref>).</p><fig position="float" id="figure3"><label>Figure 3.</label><caption><p>Association of modifiable lifestyle and metabolic factors with the risk of developing sepsis. HDL-C: high-density lipoprotein cholesterol; MR: Mendelian randomization.</p></caption><graphic alt-version="no" mimetype="image" position="float" xlink:type="simple" xlink:href="i-jmr_v14i1e72244_fig03.png"/></fig><p>Genetic variants such as smoking initiation, smoking frequency, and waist circumference were associated with an increased risk of sepsis, whereas light physical activity, higher education, and high levels of HDL-c were causally associated with a lower risk of sepsis.</p><p>Owing to the modifiable nature of lifestyle, the impact of lifestyle on diseases with high mortality, such as sepsis, has received increasing attention. Numerous observational studies have described an association between smoking, alcohol consumption, and the risk of various infectious diseases [<xref ref-type="bibr" rid="ref22">22</xref>,<xref ref-type="bibr" rid="ref30">30</xref>-<xref ref-type="bibr" rid="ref35">35</xref>]. However, establishing a causal link between lifestyle and sepsis remains challenging. This study aimed to explore the potential causal relationships between lifestyle factors and sepsis. The results showed that smoking initiation and a high frequency of smoking were associated with an increased risk of sepsis. Previous immunologic experiments reported that smoking has been associated with impaired phagocytic function and cytokine expression of T lymphocytes and macrophages in the respiratory tract or peripheral blood [<xref ref-type="bibr" rid="ref36">36</xref>-<xref ref-type="bibr" rid="ref38">38</xref>]. These studies collectively underscore the detrimental impact of smoking on the immune system. These findings provide a better understanding of the role of smoking in patients with sepsis. Therefore, healthy lifestyle modification is a preventive measure against sepsis; individuals should be advised to reduce smoking to reduce the risk of developing sepsis.</p><p>Physical exercise is a planned, purposeful action to maintain a healthy lifestyle and improve physical fitness (World Health Organization, 2010) [<xref ref-type="bibr" rid="ref39">39</xref>]. Furthermore, the evidence suggests that physical exercise affects multiple organ systems under various conditions [<xref ref-type="bibr" rid="ref40">40</xref>]. It has been found that inadequate exercise is associated with a doubled risk of sepsis-related mortality [<xref ref-type="bibr" rid="ref40">40</xref>]. Given that the incidence of sepsis is increasing, these results suggest that exercising could be immediately effective in reducing disease incidence. Currently, no MR analyses of the association between physical activity and sepsis are available. Our analysis confirmed that light physical activity is associated with a lower risk of sepsis.</p><p>The socioeconomic status affects health through environmental exposure, health behaviors, and lifestyle and has been shown to be positively related to health [<xref ref-type="bibr" rid="ref10">10</xref>,<xref ref-type="bibr" rid="ref41">41</xref>]. Education stands as the most potent indicator of socioeconomic status, exerting influence over lifestyle choices and access to health resources [<xref ref-type="bibr" rid="ref42">42</xref>]. Observational studies suggest an inverse association between educational attainment and sepsis risk. Wang et al [<xref ref-type="bibr" rid="ref43">43</xref>] reported significantly higher sepsis risk among individuals with lower education (hazard ratio 1.88, 95% CI 1.54&#x2010;2.29), though without controlling for comorbidities and other confounders. Another cohort study adjusting for socioeconomic factors still demonstrated a higher risk of sepsis-related intensive care unit admission in moderately educated versus highly educated individuals [<xref ref-type="bibr" rid="ref44">44</xref>]. It should be noted that these observational findings may be influenced by residual confounding and do not establish causality. This study found a negative correlation between genetically predicted educational levels and sepsis risk. Higher education may reduce sepsis risk through multiple pathways, including enhanced health literacy (eg, earlier recognition of infections), greater access to health care resources, and adoption of healthier behaviors (eg, smoking cessation and improved diet). These mechanisms could collectively mitigate exposure to risk factors and improve timely medical intervention.</p><p>In recent years, an increasing number of studies have focused on the impact of metabolic factors such as blood glucose, blood lipids, and obesity on various infectious diseases [<xref ref-type="bibr" rid="ref45">45</xref>-<xref ref-type="bibr" rid="ref49">49</xref>]. Previous studies have reported that high HDL-c levels are significantly associated with reduced sepsis risk and other sepsis-related outcomes [<xref ref-type="bibr" rid="ref50">50</xref>,<xref ref-type="bibr" rid="ref51">51</xref>]. Extremely low serum HDL-c levels (&#x2264;20 mg/dL) are associated with an increased risk of death, sepsis, and malignancy [<xref ref-type="bibr" rid="ref52">52</xref>]. However, observational clinical and epidemiologic studies have potential problems such as confounding, reverse causation, and unaccounted comorbidities. An MR study found that lower HDL-c levels were significantly associated with an increased risk of sepsis and related outcomes in infected patients [<xref ref-type="bibr" rid="ref53">53</xref>]. This is consistent with our findings. Our study found a genetic relationship between high HDL-c levels and low risk of sepsis. HDL-c might exert protective effects against sepsis via its anti-inflammatory and antioxidant properties, as well as its role in modulating endothelial function and neutralizing bacterial endotoxins [<xref ref-type="bibr" rid="ref54">54</xref>-<xref ref-type="bibr" rid="ref56">56</xref>].</p><p>In observational studies on the general population, a higher BMI has been associated with an increased incidence of mortality from bloodstream infections and sepsis [<xref ref-type="bibr" rid="ref57">57</xref>-<xref ref-type="bibr" rid="ref59">59</xref>]. This finding is confirmed in this study. We also found that BMI, arm fat mass, leg fat mass, whole body fat mass, waist circumference, and trunk fat mass were significantly associated with sepsis. However, using the multivariate factor analysis, only increased waist circumference was an independent risk factor for sepsis, which might be because other factors included the causes of increased waist circumference, suggesting that these factors might influence sepsis risk as a consequence of shared risk factor profiles.</p><p>This study had several limitations. First, the population limited to the European ancestry hampered the generalization of the findings to individuals of other ancestries, as genetic and environmental factors influencing sepsis risk may vary across ethnic groups (eg, differences in inflammatory responses or health care access). Further studies are required to assess the modifiable risk of sepsis in other races. Second, as with all MR studies, pleiotropy in an MR setting is challenging. Additionally, gene-environment interactions (eg, how lifestyle modifies genetic risk) and potential measurement errors in exposure variables were not fully addressed, which might have introduced bias. We performed various sensitivity analyses that made different assumptions regarding the underlying nature of pleiotropy. Most tests showed stable results. Future studies should incorporate multi-ancestry cohorts and explore gene-environment interplay to strengthen causal inference.</p><p>In conclusion, our combined MR analysis supports the causal roles of smoking, educational level, HDL-c level, physical condition, obesity, and physical activity in patients with sepsis. The findings of this study highlight actionable targets for sepsis prevention. For instance, smoking cessation programs, public health initiatives to promote physical activity, and interventions to improve HDL-c levels (eg, dietary modifications or pharmacotherapy) could be integrated into personalized preventive strategies for managing high-risk populations. Furthermore, educational campaigns targeting health literacy and early symptom recognition might reduce delays in seeking care, particularly among socioeconomically disadvantaged groups. Future research should prioritize replication in diverse populations, mechanistic studies to elucidate pathways (eg, HDL-c&#x2019;s immunomodulatory effects), and translational interventions targeting high-risk subgroups.</p></sec></body><back><ack><p>The authors would like to acknowledge the participants and investigators of the Integrative Epidemiology Unit OpenGWAS project used in this paper.</p></ack><notes><sec><title>Data Availability</title><p>Publicly available datasets were analyzed in this Mendelian randomization study. Genome-wide association study summary-level datasets were downloaded from the Integrative Epidemiology Unit OpenGWAS Project [<xref ref-type="bibr" rid="ref29">29</xref>]. Full details are provided in <xref ref-type="table" rid="table1">Table 1</xref>.</p></sec></notes><fn-group><fn fn-type="con"><p>Data curation: HL, JL</p><p>Formal analysis: HL, JL</p><p>Methodology: YC</p><p>Project administration: KX</p><p>Software: HL, JL</p><p>Supervision: XW, KX</p><p>Validation: GS, FW, QY</p><p>Visualization: HL, JL, WF</p><p>Writing&#x2013;original draft: HL, JL, YC, KX, XW, GS, FW, QY, WF</p><p>Writing&#x2013;review and editing: HL, JL, YC, KX, XW, GS, FW, QY, WF</p></fn><fn fn-type="conflict"><p>None declared.</p></fn></fn-group><glossary><title>Abbreviations</title><def-list><def-item><term id="abb1">GWAS</term><def><p>genome-wide association study</p></def></def-item><def-item><term id="abb2">HDL-C</term><def><p>high-density lipoprotein cholesterol</p></def></def-item><def-item><term id="abb3">IVW</term><def><p>inverse variance weighted</p></def></def-item><def-item><term id="abb4">MR</term><def><p>Mendelian randomization</p></def></def-item><def-item><term id="abb5">OR</term><def><p>odds ratio</p></def></def-item><def-item><term id="abb6">SNP</term><def><p>single-nucleotide polymorphism</p></def></def-item><def-item><term id="abb7">STROBE-MR</term><def><p>Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization</p></def></def-item></def-list></glossary><ref-list><title>References</title><ref id="ref1"><label>1</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Singer</surname><given-names>M</given-names> </name><name name-style="western"><surname>Deutschman</surname><given-names>CS</given-names> </name><name name-style="western"><surname>Seymour</surname><given-names>CW</given-names> </name><etal/></person-group><article-title>The third international consensus definitions for sepsis and septic shock (sepsis-3)</article-title><source>JAMA</source><year>2016</year><month>02</month><day>23</day><volume>315</volume><issue>8</issue><fpage>801</fpage><lpage>810</lpage><pub-id pub-id-type="doi">10.1001/jama.2016.0287</pub-id><pub-id pub-id-type="medline">26903338</pub-id></nlm-citation></ref><ref id="ref2"><label>2</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Rudd</surname><given-names>KE</given-names> </name><name name-style="western"><surname>Johnson</surname><given-names>SC</given-names> </name><name name-style="western"><surname>Agesa</surname><given-names>KM</given-names> </name><etal/></person-group><article-title>Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study</article-title><source>Lancet</source><year>2020</year><month>01</month><day>18</day><volume>395</volume><issue>10219</issue><fpage>200</fpage><lpage>211</lpage><pub-id pub-id-type="doi">10.1016/S0140-6736(19)32989-7</pub-id><pub-id pub-id-type="medline">31954465</pub-id></nlm-citation></ref><ref id="ref3"><label>3</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Xie</surname><given-names>J</given-names> </name><name name-style="western"><surname>Wang</surname><given-names>H</given-names> </name><name name-style="western"><surname>Kang</surname><given-names>Y</given-names> </name><etal/></person-group><article-title>The epidemiology of sepsis in Chinese ICUs: a national cross-sectional survey</article-title><source>Crit Care Med</source><year>2020</year><month>03</month><volume>48</volume><issue>3</issue><fpage>e209</fpage><lpage>e218</lpage><pub-id pub-id-type="doi">10.1097/CCM.0000000000004155</pub-id><pub-id pub-id-type="medline">31804299</pub-id></nlm-citation></ref><ref id="ref4"><label>4</label><nlm-citation citation-type="report"><article-title>Global report on the epidemiology and burden of sepsis: current evidence, identifying gaps and future directions</article-title><year>2020</year><access-date>2025-10-23</access-date><publisher-name>World Health Organization</publisher-name><comment><ext-link ext-link-type="uri" xlink:href="https://www.who.int/publications/i/item/%209789240010789">https://www.who.int/publications/i/item/ 9789240010789</ext-link></comment></nlm-citation></ref><ref id="ref5"><label>5</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Vincent</surname><given-names>JL</given-names> </name><name name-style="western"><surname>van der Poll</surname><given-names>T</given-names> </name><name name-style="western"><surname>Marshall</surname><given-names>JC</given-names> </name></person-group><article-title>The end of &#x201C;one size fits all&#x201D; sepsis therapies: toward an individualized approach</article-title><source>Biomedicines</source><year>2022</year><month>09</month><day>12</day><volume>10</volume><issue>9</issue><fpage>2260</fpage><pub-id pub-id-type="doi">10.3390/biomedicines10092260</pub-id><pub-id pub-id-type="medline">36140361</pub-id></nlm-citation></ref><ref id="ref6"><label>6</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Evans</surname><given-names>L</given-names> </name><name name-style="western"><surname>Rhodes</surname><given-names>A</given-names> </name><name name-style="western"><surname>Alhazzani</surname><given-names>W</given-names> </name><etal/></person-group><article-title>Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021</article-title><source>Intensive Care Med</source><year>2021</year><month>11</month><volume>47</volume><issue>11</issue><fpage>1181</fpage><lpage>1247</lpage><pub-id pub-id-type="doi">10.1007/s00134-021-06506-y</pub-id><pub-id pub-id-type="medline">34599691</pub-id></nlm-citation></ref><ref id="ref7"><label>7</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Vincent</surname><given-names>JL</given-names> </name></person-group><article-title>Emerging paradigms in sepsis</article-title><source>EBioMedicine</source><year>2022</year><month>12</month><volume>86</volume><fpage>104398</fpage><pub-id pub-id-type="doi">10.1016/j.ebiom.2022.104398</pub-id><pub-id pub-id-type="medline">36470835</pub-id></nlm-citation></ref><ref id="ref8"><label>8</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Rubio</surname><given-names>I</given-names> </name><name name-style="western"><surname>Osuchowski</surname><given-names>MF</given-names> </name><name name-style="western"><surname>Shankar-Hari</surname><given-names>M</given-names> </name><etal/></person-group><article-title>Current gaps in sepsis immunology: new opportunities for translational research</article-title><source>Lancet Infect Dis</source><year>2019</year><month>12</month><volume>19</volume><issue>12</issue><fpage>e422</fpage><lpage>e436</lpage><pub-id pub-id-type="doi">10.1016/S1473-3099(19)30567-5</pub-id></nlm-citation></ref><ref id="ref9"><label>9</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Wiewel</surname><given-names>MA</given-names> </name><name name-style="western"><surname>Harmon</surname><given-names>MB</given-names> </name><name name-style="western"><surname>van Vught</surname><given-names>LA</given-names> </name><etal/></person-group><article-title>Risk factors, host response and outcome of hypothermic sepsis</article-title><source>Crit Care</source><year>2016</year><month>10</month><day>14</day><volume>20</volume><issue>1</issue><fpage>328</fpage><pub-id pub-id-type="doi">10.1186/s13054-016-1510-3</pub-id><pub-id pub-id-type="medline">27737683</pub-id></nlm-citation></ref><ref id="ref10"><label>10</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Stensrud</surname><given-names>VH</given-names> </name><name name-style="western"><surname>Gustad</surname><given-names>LT</given-names> </name><name name-style="western"><surname>Dam&#x00E5;s</surname><given-names>JK</given-names> </name><name name-style="western"><surname>Sollig&#x00E5;rd</surname><given-names>E</given-names> </name><name name-style="western"><surname>Krokstad</surname><given-names>S</given-names> </name><name name-style="western"><surname>Nilsen</surname><given-names>TIL</given-names> </name></person-group><article-title>Direct and indirect effects of socioeconomic status on sepsis risk and mortality: a mediation analysis of the HUNT study</article-title><source>J Epidemiol Community Health</source><year>2023</year><month>03</month><volume>77</volume><issue>3</issue><fpage>168</fpage><lpage>174</lpage><pub-id pub-id-type="doi">10.1136/jech-2022-219825</pub-id><pub-id pub-id-type="medline">36707239</pub-id></nlm-citation></ref><ref id="ref11"><label>11</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Rose</surname><given-names>N</given-names> </name><name name-style="western"><surname>Matth&#x00E4;us-Kr&#x00E4;mer</surname><given-names>C</given-names> </name><name name-style="western"><surname>Schwarzkopf</surname><given-names>D</given-names> </name><etal/></person-group><article-title>Association between sepsis incidence and regional socioeconomic deprivation and health care capacity in Germany - an ecological study</article-title><source>BMC Public Health</source><year>2021</year><month>09</month><day>7</day><volume>21</volume><issue>1</issue><fpage>1636</fpage><pub-id pub-id-type="doi">10.1186/s12889-021-11629-4</pub-id><pub-id pub-id-type="medline">34493250</pub-id></nlm-citation></ref><ref id="ref12"><label>12</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Trevelin</surname><given-names>SC</given-names> </name><name name-style="western"><surname>Carlos</surname><given-names>D</given-names> </name><name name-style="western"><surname>Beretta</surname><given-names>M</given-names> </name><name name-style="western"><surname>da Silva</surname><given-names>JS</given-names> </name><name name-style="western"><surname>Cunha</surname><given-names>FQ</given-names> </name></person-group><article-title>Diabetes mellitus and sepsis: a challenging association</article-title><source>Shock</source><year>2017</year><month>03</month><volume>47</volume><issue>3</issue><fpage>276</fpage><lpage>287</lpage><pub-id pub-id-type="doi">10.1097/SHK.0000000000000778</pub-id><pub-id pub-id-type="medline">27787406</pub-id></nlm-citation></ref><ref id="ref13"><label>13</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Ahlberg</surname><given-names>CD</given-names> </name><name name-style="western"><surname>Wallam</surname><given-names>S</given-names> </name><name name-style="western"><surname>Tirba</surname><given-names>LA</given-names> </name><name name-style="western"><surname>Itumba</surname><given-names>SN</given-names> </name><name name-style="western"><surname>Gorman</surname><given-names>L</given-names> </name><name name-style="western"><surname>Galiatsatos</surname><given-names>P</given-names> </name></person-group><article-title>Linking Sepsis with chronic arterial hypertension, diabetes mellitus, and socioeconomic factors in the United States: a scoping review</article-title><source>J Crit Care</source><year>2023</year><month>10</month><volume>77</volume><fpage>154324</fpage><pub-id pub-id-type="doi">10.1016/j.jcrc.2023.154324</pub-id><pub-id pub-id-type="medline">37159971</pub-id></nlm-citation></ref><ref id="ref14"><label>14</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>St&#x00F6;sser</surname><given-names>S</given-names> </name><name name-style="western"><surname>Kleusch</surname><given-names>L</given-names> </name><name name-style="western"><surname>Schenk</surname><given-names>A</given-names> </name><name name-style="western"><surname>Schmid</surname><given-names>M</given-names> </name><name name-style="western"><surname>Petzold</surname><given-names>GC</given-names> </name></person-group><article-title>Derivation and validation of a screening tool for stroke-associated sepsis</article-title><source>Neurol Res Pract</source><year>2023</year><month>07</month><day>13</day><volume>5</volume><issue>1</issue><fpage>32</fpage><pub-id pub-id-type="doi">10.1186/s42466-023-00258-4</pub-id><pub-id pub-id-type="medline">37438794</pub-id></nlm-citation></ref><ref id="ref15"><label>15</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Hou</surname><given-names>J</given-names> </name><name name-style="western"><surname>Zhang</surname><given-names>J</given-names> </name><name name-style="western"><surname>Cui</surname><given-names>P</given-names> </name><etal/></person-group><article-title>TREM2 sustains macrophage-hepatocyte metabolic coordination in nonalcoholic fatty liver disease and sepsis</article-title><source>J Clin Invest</source><year>2021</year><month>02</month><day>15</day><volume>131</volume><issue>4</issue><fpage>e135197</fpage><pub-id pub-id-type="doi">10.1172/JCI135197</pub-id><pub-id pub-id-type="medline">33586673</pub-id></nlm-citation></ref><ref id="ref16"><label>16</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>You</surname><given-names>J</given-names> </name><name name-style="western"><surname>Bi</surname><given-names>X</given-names> </name><name name-style="western"><surname>Zhang</surname><given-names>K</given-names> </name><etal/></person-group><article-title>Causal associations between gut microbiota and sepsis: a two-sample Mendelian randomization study</article-title><source>Eur J Clin Invest</source><year>2023</year><month>11</month><volume>53</volume><issue>11</issue><fpage>e14064</fpage><pub-id pub-id-type="doi">10.1111/eci.14064</pub-id><pub-id pub-id-type="medline">37464539</pub-id></nlm-citation></ref><ref id="ref17"><label>17</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Wang</surname><given-names>GS</given-names> </name><name name-style="western"><surname>You</surname><given-names>KM</given-names> </name><name name-style="western"><surname>Jo</surname><given-names>YH</given-names> </name><etal/></person-group><article-title>Association of health insurance status with outcomes of sepsis in adult patients: a retrospective cohort study</article-title><source>Int J Environ Res Public Health</source><year>2021</year><month>05</month><day>27</day><volume>18</volume><issue>11</issue><fpage>5777</fpage><pub-id pub-id-type="doi">10.3390/ijerph18115777</pub-id><pub-id pub-id-type="medline">34072210</pub-id></nlm-citation></ref><ref id="ref18"><label>18</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Frydrych</surname><given-names>LM</given-names> </name><name name-style="western"><surname>Bian</surname><given-names>G</given-names> </name><name name-style="western"><surname>O&#x2019;Lone</surname><given-names>DE</given-names> </name><name name-style="western"><surname>Ward</surname><given-names>PA</given-names> </name><name name-style="western"><surname>Delano</surname><given-names>MJ</given-names> </name></person-group><article-title>Obesity and type 2 diabetes mellitus drive immune dysfunction, infection development, and sepsis mortality</article-title><source>J Leukoc Biol</source><year>2018</year><month>09</month><volume>104</volume><issue>3</issue><fpage>525</fpage><lpage>534</lpage><pub-id pub-id-type="doi">10.1002/JLB.5VMR0118-021RR</pub-id><pub-id pub-id-type="medline">30066958</pub-id></nlm-citation></ref><ref id="ref19"><label>19</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Davies</surname><given-names>NM</given-names> </name><name name-style="western"><surname>Holmes</surname><given-names>MV</given-names> </name><name name-style="western"><surname>Davey Smith</surname><given-names>G</given-names> </name></person-group><article-title>Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians</article-title><source>BMJ</source><year>2018</year><volume>362</volume><fpage>k601</fpage><pub-id pub-id-type="doi">10.1136/bmj.k601</pub-id></nlm-citation></ref><ref id="ref20"><label>20</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Lei</surname><given-names>P</given-names> </name><name name-style="western"><surname>Xu</surname><given-names>W</given-names> </name><name name-style="western"><surname>Wang</surname><given-names>C</given-names> </name><name name-style="western"><surname>Lin</surname><given-names>G</given-names> </name><name name-style="western"><surname>Yu</surname><given-names>S</given-names> </name><name name-style="western"><surname>Guo</surname><given-names>Y</given-names> </name></person-group><article-title>Mendelian randomization analysis reveals causal associations of polyunsaturated fatty acids with sepsis and mortality risk</article-title><source>Infect Dis Ther</source><year>2023</year><month>07</month><volume>12</volume><issue>7</issue><fpage>1797</fpage><lpage>1808</lpage><pub-id pub-id-type="doi">10.1007/s40121-023-00831-z</pub-id><pub-id pub-id-type="medline">37316614</pub-id></nlm-citation></ref><ref id="ref21"><label>21</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Wang</surname><given-names>J</given-names> </name><name name-style="western"><surname>Hu</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Zeng</surname><given-names>J</given-names> </name><etal/></person-group><article-title>Exploring the causality between body mass index and sepsis: a two-sample Mendelian randomization study</article-title><source>Int J Public Health</source><year>2023</year><volume>68</volume><fpage>1605548</fpage><pub-id pub-id-type="doi">10.3389/ijph.2023.1605548</pub-id><pub-id pub-id-type="medline">37205044</pub-id></nlm-citation></ref><ref id="ref22"><label>22</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Zhu</surname><given-names>H</given-names> </name><name name-style="western"><surname>Zhan</surname><given-names>X</given-names> </name><name name-style="western"><surname>Wang</surname><given-names>C</given-names> </name><etal/></person-group><article-title>Causal associations between tobacco, alcohol use and risk of infectious diseases: a Mendelian randomization study</article-title><source>Infect Dis Ther</source><year>2023</year><month>03</month><volume>12</volume><issue>3</issue><fpage>965</fpage><lpage>977</lpage><pub-id pub-id-type="doi">10.1007/s40121-023-00775-4</pub-id><pub-id pub-id-type="medline">36862322</pub-id></nlm-citation></ref><ref id="ref23"><label>23</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Hu</surname><given-names>J</given-names> </name><name name-style="western"><surname>Gan</surname><given-names>Q</given-names> </name><name name-style="western"><surname>Zhou</surname><given-names>D</given-names> </name><etal/></person-group><article-title>Evaluating the risk of sepsis attributing to obesity: a two-sample Mendelian randomization study</article-title><source>Postgrad Med J</source><year>2023</year><month>11</month><day>20</day><volume>99</volume><issue>1178</issue><fpage>1266</fpage><lpage>1271</lpage><pub-id pub-id-type="doi">10.1093/postmj/qgad072</pub-id><pub-id pub-id-type="medline">37681245</pub-id></nlm-citation></ref><ref id="ref24"><label>24</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Burgess</surname><given-names>S</given-names> </name><name name-style="western"><surname>Davey Smith</surname><given-names>G</given-names> </name><name name-style="western"><surname>Davies</surname><given-names>NM</given-names> </name><etal/></person-group><article-title>Guidelines for performing Mendelian randomization investigations: update for summer 2023</article-title><source>Wellcome Open Res</source><year>2019</year><volume>4</volume><fpage>186</fpage><pub-id pub-id-type="doi">10.12688/wellcomeopenres.15555.3</pub-id><pub-id pub-id-type="medline">32760811</pub-id></nlm-citation></ref><ref id="ref25"><label>25</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Thorkildsen</surname><given-names>MS</given-names> </name><name name-style="western"><surname>Gustad</surname><given-names>LT</given-names> </name><name name-style="western"><surname>Mohus</surname><given-names>RM</given-names> </name><etal/></person-group><article-title>Association of genetically predicted insomnia with risk of sepsis: a Mendelian randomization study</article-title><source>JAMA Psychiatry</source><year>2023</year><month>10</month><day>1</day><volume>80</volume><issue>10</issue><fpage>1061</fpage><lpage>1065</lpage><pub-id pub-id-type="doi">10.1001/jamapsychiatry.2023.2717</pub-id><pub-id pub-id-type="medline">37556136</pub-id></nlm-citation></ref><ref id="ref26"><label>26</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Ni</surname><given-names>F</given-names> </name><name name-style="western"><surname>Liu</surname><given-names>X</given-names> </name><name name-style="western"><surname>Wang</surname><given-names>S</given-names> </name></person-group><article-title>Impact of negative emotions and insomnia on sepsis: a mediation Mendelian randomization study</article-title><source>Comput Biol Med</source><year>2024</year><month>09</month><volume>180</volume><fpage>108858</fpage><pub-id pub-id-type="doi">10.1016/j.compbiomed.2024.108858</pub-id><pub-id pub-id-type="medline">39067155</pub-id></nlm-citation></ref><ref id="ref27"><label>27</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Shang</surname><given-names>W</given-names> </name><name name-style="western"><surname>Qian</surname><given-names>H</given-names> </name><name name-style="western"><surname>Zhang</surname><given-names>S</given-names> </name><etal/></person-group><article-title>Human blood metabolites and risk of sepsis: a Mendelian randomization investigation</article-title><source>Eur J Clin Invest</source><year>2024</year><month>04</month><volume>54</volume><issue>4</issue><fpage>e14145</fpage><pub-id pub-id-type="doi">10.1111/eci.14145</pub-id><pub-id pub-id-type="medline">38041600</pub-id></nlm-citation></ref><ref id="ref28"><label>28</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Zhu</surname><given-names>ZG</given-names> </name><name name-style="western"><surname>Ma</surname><given-names>JW</given-names> </name><name name-style="western"><surname>Ji</surname><given-names>DD</given-names> </name><name name-style="western"><surname>Li</surname><given-names>QQ</given-names> </name><name name-style="western"><surname>Diao</surname><given-names>XY</given-names> </name><name name-style="western"><surname>Bao</surname><given-names>J</given-names> </name></person-group><article-title>Mendelian randomization analysis identifies causal associations between serum lipidomic profile, amino acid biomarkers and sepsis</article-title><source>Heliyon</source><year>2024</year><month>06</month><day>30</day><volume>10</volume><issue>12</issue><fpage>e32779</fpage><pub-id pub-id-type="doi">10.1016/j.heliyon.2024.e32779</pub-id><pub-id pub-id-type="medline">38975226</pub-id></nlm-citation></ref><ref id="ref29"><label>29</label><nlm-citation citation-type="web"><article-title>OpenGWAS</article-title><access-date>2025-10-28</access-date><comment><ext-link ext-link-type="uri" xlink:href="https://opengwas.io/">https://opengwas.io/</ext-link></comment></nlm-citation></ref><ref id="ref30"><label>30</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>O&#x2019;Brien</surname><given-names>JM</given-names>  <suffix>Jr</suffix></name><name name-style="western"><surname>Lu</surname><given-names>B</given-names> </name><name name-style="western"><surname>Ali</surname><given-names>NA</given-names> </name><etal/></person-group><article-title>Alcohol dependence is independently associated with sepsis, septic shock, and hospital mortality among adult intensive care unit patients</article-title><source>Crit Care Med</source><year>2007</year><month>02</month><volume>35</volume><issue>2</issue><fpage>345</fpage><lpage>350</lpage><pub-id pub-id-type="doi">10.1097/01.CCM.0000254340.91644.B2</pub-id><pub-id pub-id-type="medline">17205003</pub-id></nlm-citation></ref><ref id="ref31"><label>31</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Bello</surname><given-names>S</given-names> </name><name name-style="western"><surname>Men&#x00E9;ndez</surname><given-names>R</given-names> </name><name name-style="western"><surname>Antoni</surname><given-names>T</given-names> </name><etal/></person-group><article-title>Tobacco smoking increases the risk for death from pneumococcal pneumonia</article-title><source>Chest</source><year>2014</year><month>10</month><volume>146</volume><issue>4</issue><fpage>1029</fpage><lpage>1037</lpage><pub-id pub-id-type="doi">10.1378/chest.13-2853</pub-id><pub-id pub-id-type="medline">24811098</pub-id></nlm-citation></ref><ref id="ref32"><label>32</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Gustot</surname><given-names>T</given-names> </name><name name-style="western"><surname>Fernandez</surname><given-names>J</given-names> </name><name name-style="western"><surname>Szabo</surname><given-names>G</given-names> </name><etal/></person-group><article-title>Sepsis in alcohol-related liver disease</article-title><source>J Hepatol</source><year>2017</year><month>11</month><volume>67</volume><issue>5</issue><fpage>1031</fpage><lpage>1050</lpage><pub-id pub-id-type="doi">10.1016/j.jhep.2017.06.013</pub-id><pub-id pub-id-type="medline">28647569</pub-id></nlm-citation></ref><ref id="ref33"><label>33</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Bukong</surname><given-names>TN</given-names> </name><name name-style="western"><surname>Cho</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Iracheta-Vellve</surname><given-names>A</given-names> </name><etal/></person-group><article-title>Abnormal neutrophil traps and impaired efferocytosis contribute to liver injury and sepsis severity after binge alcohol use</article-title><source>J Hepatol</source><year>2018</year><month>11</month><volume>69</volume><issue>5</issue><fpage>1145</fpage><lpage>1154</lpage><pub-id pub-id-type="doi">10.1016/j.jhep.2018.07.005</pub-id><pub-id pub-id-type="medline">30030149</pub-id></nlm-citation></ref><ref id="ref34"><label>34</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Moazed</surname><given-names>F</given-names> </name><name name-style="western"><surname>Hendrickson</surname><given-names>C</given-names> </name><name name-style="western"><surname>Jauregui</surname><given-names>A</given-names> </name><etal/></person-group><article-title>Cigarette smoke exposure and acute respiratory distress syndrome in sepsis: epidemiology, clinical features, and biologic markers</article-title><source>Am J Respir Crit Care Med</source><year>2022</year><month>04</month><day>15</day><volume>205</volume><issue>8</issue><fpage>927</fpage><lpage>935</lpage><pub-id pub-id-type="doi">10.1164/rccm.202105-1098OC</pub-id><pub-id pub-id-type="medline">35050845</pub-id></nlm-citation></ref><ref id="ref35"><label>35</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Sabaratnam</surname><given-names>R</given-names> </name><name name-style="western"><surname>Wojtaszewski</surname><given-names>JFP</given-names> </name><name name-style="western"><surname>H&#x00F8;jlund</surname><given-names>K</given-names> </name></person-group><article-title>Factors mediating exercise-induced organ crosstalk</article-title><source>Acta Physiol (Oxf)</source><year>2022</year><month>02</month><volume>234</volume><issue>2</issue><fpage>e13766</fpage><pub-id pub-id-type="doi">10.1111/apha.13766</pub-id><pub-id pub-id-type="medline">34981891</pub-id></nlm-citation></ref><ref id="ref36"><label>36</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Burton</surname><given-names>R</given-names> </name><name name-style="western"><surname>Fryers</surname><given-names>PT</given-names> </name><name name-style="western"><surname>Sharpe</surname><given-names>C</given-names> </name><etal/></person-group><article-title>The independent and joint risks of alcohol consumption, smoking, and excess weight on morbidity and mortality: a systematic review and meta-analysis exploring synergistic associations</article-title><source>Public Health</source><year>2024</year><month>01</month><volume>226</volume><fpage>39</fpage><lpage>52</lpage><pub-id pub-id-type="doi">10.1016/j.puhe.2023.10.035</pub-id><pub-id pub-id-type="medline">38000113</pub-id></nlm-citation></ref><ref id="ref37"><label>37</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Lee</surname><given-names>EH</given-names> </name><name name-style="western"><surname>Lee</surname><given-names>KH</given-names> </name><name name-style="western"><surname>Lee</surname><given-names>KN</given-names> </name><name name-style="western"><surname>Park</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Do Han</surname><given-names>K</given-names> </name><name name-style="western"><surname>Han</surname><given-names>SH</given-names> </name></person-group><article-title>The relation between cigarette smoking and development of sepsis: a 10-year follow-up study of four million adults from the national health screening program</article-title><source>J Epidemiol Glob Health</source><year>2024</year><month>06</month><volume>14</volume><issue>2</issue><fpage>444</fpage><lpage>452</lpage><pub-id pub-id-type="doi">10.1007/s44197-024-00197-6</pub-id><pub-id pub-id-type="medline">38372892</pub-id></nlm-citation></ref><ref id="ref38"><label>38</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Elisia</surname><given-names>I</given-names> </name><name name-style="western"><surname>Lam</surname><given-names>V</given-names> </name><name name-style="western"><surname>Cho</surname><given-names>B</given-names> </name><etal/></person-group><article-title>The effect of smoking on chronic inflammation, immune function and blood cell composition</article-title><source>Sci Rep</source><year>2020</year><month>11</month><day>10</day><volume>10</volume><issue>1</issue><fpage>19480</fpage><pub-id pub-id-type="doi">10.1038/s41598-020-76556-7</pub-id><pub-id pub-id-type="medline">33173057</pub-id></nlm-citation></ref><ref id="ref39"><label>39</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Ye</surname><given-names>KX</given-names> </name><name name-style="western"><surname>Sun</surname><given-names>L</given-names> </name><name name-style="western"><surname>Wang</surname><given-names>L</given-names> </name><etal/></person-group><article-title>The role of lifestyle factors in cognitive health and dementia in oldest-old: a systematic review</article-title><source>Neurosci Biobehav Rev</source><year>2023</year><month>09</month><volume>152</volume><fpage>105286</fpage><pub-id pub-id-type="doi">10.1016/j.neubiorev.2023.105286</pub-id><pub-id pub-id-type="medline">37321363</pub-id></nlm-citation></ref><ref id="ref40"><label>40</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Williams</surname><given-names>PT</given-names> </name></person-group><article-title>Inadequate exercise as a risk factor for sepsis mortality</article-title><source>PLoS One</source><year>2013</year><volume>8</volume><issue>12</issue><fpage>e79344</fpage><pub-id pub-id-type="doi">10.1371/journal.pone.0079344</pub-id><pub-id pub-id-type="medline">24324580</pub-id></nlm-citation></ref><ref id="ref41"><label>41</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Minejima</surname><given-names>E</given-names> </name><name name-style="western"><surname>Wong-Beringer</surname><given-names>A</given-names> </name></person-group><article-title>Impact of socioeconomic status and race on sepsis epidemiology and outcomes</article-title><source>J Appl Lab Med</source><year>2021</year><month>01</month><day>12</day><volume>6</volume><issue>1</issue><fpage>194</fpage><lpage>209</lpage><pub-id pub-id-type="doi">10.1093/jalm/jfaa151</pub-id><pub-id pub-id-type="medline">33241269</pub-id></nlm-citation></ref><ref id="ref42"><label>42</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Rosengren</surname><given-names>A</given-names> </name><name name-style="western"><surname>Smyth</surname><given-names>A</given-names> </name><name name-style="western"><surname>Rangarajan</surname><given-names>S</given-names> </name><etal/></person-group><article-title>Socioeconomic status and risk of cardiovascular disease in 20 low-income, middle-income, and high-income countries: the Prospective Urban Rural Epidemiologic (PURE) study</article-title><source>Lancet Glob Health</source><year>2019</year><month>06</month><volume>7</volume><issue>6</issue><fpage>e748</fpage><lpage>e760</lpage><pub-id pub-id-type="doi">10.1016/S2214-109X(19)30045-2</pub-id><pub-id pub-id-type="medline">31028013</pub-id></nlm-citation></ref><ref id="ref43"><label>43</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Wang</surname><given-names>HE</given-names> </name><name name-style="western"><surname>Shapiro</surname><given-names>NI</given-names> </name><name name-style="western"><surname>Griffin</surname><given-names>R</given-names> </name><name name-style="western"><surname>Safford</surname><given-names>MM</given-names> </name><name name-style="western"><surname>Judd</surname><given-names>S</given-names> </name><name name-style="western"><surname>Howard</surname><given-names>G</given-names> </name></person-group><article-title>Chronic medical conditions and risk of sepsis</article-title><source>PLoS One</source><year>2012</year><volume>7</volume><issue>10</issue><fpage>e48307</fpage><pub-id pub-id-type="doi">10.1371/journal.pone.0048307</pub-id><pub-id pub-id-type="medline">23118977</pub-id></nlm-citation></ref><ref id="ref44"><label>44</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Storm</surname><given-names>L</given-names> </name><name name-style="western"><surname>Schnegelsberg</surname><given-names>A</given-names> </name><name name-style="western"><surname>Mackenhauer</surname><given-names>J</given-names> </name><name name-style="western"><surname>Andersen</surname><given-names>LW</given-names> </name><name name-style="western"><surname>Jessen</surname><given-names>MK</given-names> </name><name name-style="western"><surname>Kirkegaard</surname><given-names>H</given-names> </name></person-group><article-title>Socioeconomic status and risk of intensive care unit admission with sepsis</article-title><source>Acta Anaesthesiol Scand</source><year>2018</year><month>08</month><volume>62</volume><issue>7</issue><fpage>983</fpage><lpage>992</lpage><pub-id pub-id-type="doi">10.1111/aas.13114</pub-id><pub-id pub-id-type="medline">29569230</pub-id></nlm-citation></ref><ref id="ref45"><label>45</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Madsen</surname><given-names>CM</given-names> </name><name name-style="western"><surname>Varbo</surname><given-names>A</given-names> </name><name name-style="western"><surname>Tybj&#x00E6;rg-Hansen</surname><given-names>A</given-names> </name><name name-style="western"><surname>Frikke-Schmidt</surname><given-names>R</given-names> </name><name name-style="western"><surname>Nordestgaard</surname><given-names>BG</given-names> </name></person-group><article-title>U-shaped relationship of HDL and risk of infectious disease: two prospective population-based cohort studies</article-title><source>Eur Heart J</source><year>2018</year><month>04</month><day>7</day><volume>39</volume><issue>14</issue><fpage>1181</fpage><lpage>1190</lpage><pub-id pub-id-type="doi">10.1093/eurheartj/ehx665</pub-id><pub-id pub-id-type="medline">29228167</pub-id></nlm-citation></ref><ref id="ref46"><label>46</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Meng</surname><given-names>J</given-names> </name><name name-style="western"><surname>Li</surname><given-names>X</given-names> </name><name name-style="western"><surname>Xiao</surname><given-names>Y</given-names> </name><etal/></person-group><article-title>Intensive or liberal glucose control in intensive care units for septic patients? A meta-analysis of randomized controlled trials</article-title><source>Diabetes Metab Syndr</source><year>2024</year><month>05</month><volume>18</volume><issue>5</issue><fpage>103045</fpage><pub-id pub-id-type="doi">10.1016/j.dsx.2024.103045</pub-id><pub-id pub-id-type="medline">38796958</pub-id></nlm-citation></ref><ref id="ref47"><label>47</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Liu</surname><given-names>P</given-names> </name><name name-style="western"><surname>Meng</surname><given-names>J</given-names> </name><name name-style="western"><surname>Tang</surname><given-names>H</given-names> </name><etal/></person-group><article-title>Association between bariatric surgery and outcomes of total joint arthroplasty: a meta-analysis</article-title><source>Int J Surg</source><year>2025</year><volume>111</volume><issue>1</issue><fpage>1541</fpage><lpage>1546</lpage><pub-id pub-id-type="doi">10.1097/JS9.0000000000002002</pub-id></nlm-citation></ref><ref id="ref48"><label>48</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Meng</surname><given-names>J</given-names> </name><name name-style="western"><surname>Li</surname><given-names>X</given-names> </name><name name-style="western"><surname>Liu</surname><given-names>W</given-names> </name><etal/></person-group><article-title>The role of vitamin D in the prevention and treatment of SARS-CoV-2 infection: a meta-analysis of randomized controlled trials</article-title><source>Clin Nutr</source><year>2023</year><month>11</month><volume>42</volume><issue>11</issue><fpage>2198</fpage><lpage>2206</lpage><pub-id pub-id-type="doi">10.1016/j.clnu.2023.09.008</pub-id><pub-id pub-id-type="medline">37802017</pub-id></nlm-citation></ref><ref id="ref49"><label>49</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Meng</surname><given-names>J</given-names> </name><name name-style="western"><surname>Li</surname><given-names>X</given-names> </name><name name-style="western"><surname>Xiong</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Wu</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Liu</surname><given-names>P</given-names> </name><name name-style="western"><surname>Gao</surname><given-names>S</given-names> </name></person-group><article-title>The role of vitamin D in the prevention and treatment of tuberculosis: a meta-analysis of randomized controlled trials</article-title><source>Infection</source><year>2025</year><month>06</month><volume>53</volume><issue>3</issue><fpage>1129</fpage><lpage>1140</lpage><pub-id pub-id-type="doi">10.1007/s15010-024-02446-z</pub-id></nlm-citation></ref><ref id="ref50"><label>50</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Scalsky</surname><given-names>RJ</given-names> </name><name name-style="western"><surname>Chen</surname><given-names>YJ</given-names> </name><name name-style="western"><surname>Desai</surname><given-names>K</given-names> </name><name name-style="western"><surname>O&#x2019;Connell</surname><given-names>JR</given-names> </name><name name-style="western"><surname>Perry</surname><given-names>JA</given-names> </name><name name-style="western"><surname>Hong</surname><given-names>CC</given-names> </name></person-group><article-title>Baseline cardiometabolic profiles and SARS-CoV-2 infection in the UK Biobank</article-title><source>PLoS ONE</source><year>2021</year><volume>16</volume><issue>4</issue><fpage>e0248602</fpage><pub-id pub-id-type="doi">10.1371/journal.pone.0248602</pub-id></nlm-citation></ref><ref id="ref51"><label>51</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Shor</surname><given-names>R</given-names> </name><name name-style="western"><surname>Wainstein</surname><given-names>J</given-names> </name><name name-style="western"><surname>Oz</surname><given-names>D</given-names> </name><etal/></person-group><article-title>Low HDL levels and the risk of death, sepsis and malignancy</article-title><source>Clin Res Cardiol</source><year>2008</year><month>04</month><volume>97</volume><issue>4</issue><fpage>227</fpage><lpage>233</lpage><pub-id pub-id-type="doi">10.1007/s00392-007-0611-z</pub-id></nlm-citation></ref><ref id="ref52"><label>52</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Liu</surname><given-names>G</given-names> </name><name name-style="western"><surname>Jiang</surname><given-names>L</given-names> </name><name name-style="western"><surname>Kerchberger</surname><given-names>VE</given-names> </name><etal/></person-group><article-title>The relationship between high density lipoprotein cholesterol and sepsis: a clinical and genetic approach</article-title><source>Clinical Translational Sci</source><year>2023</year><month>03</month><volume>16</volume><issue>3</issue><fpage>489</fpage><lpage>501</lpage><pub-id pub-id-type="doi">10.1111/cts.13462</pub-id></nlm-citation></ref><ref id="ref53"><label>53</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Twig</surname><given-names>G</given-names> </name><name name-style="western"><surname>Geva</surname><given-names>N</given-names> </name><name name-style="western"><surname>Levine</surname><given-names>H</given-names> </name><etal/></person-group><article-title>Body mass index and infectious disease mortality in midlife in a cohort of 2.3 million adolescents</article-title><source>Int J Obes (Lond)</source><year>2018</year><month>04</month><volume>42</volume><issue>4</issue><fpage>801</fpage><lpage>807</lpage><pub-id pub-id-type="doi">10.1038/ijo.2017.263</pub-id><pub-id pub-id-type="medline">29081504</pub-id></nlm-citation></ref><ref id="ref54"><label>54</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Hamilton</surname><given-names>F</given-names> </name><name name-style="western"><surname>Pedersen</surname><given-names>KM</given-names> </name><name name-style="western"><surname>Ghazal</surname><given-names>P</given-names> </name><name name-style="western"><surname>Nordestgaard</surname><given-names>BG</given-names> </name><name name-style="western"><surname>Smith</surname><given-names>GD</given-names> </name></person-group><article-title>Low levels of small HDL particles predict but do not influence risk of sepsis</article-title><source>Crit Care</source><year>2023</year><month>10</month><day>9</day><volume>27</volume><issue>1</issue><fpage>389</fpage><pub-id pub-id-type="doi">10.1186/s13054-023-04589-1</pub-id><pub-id pub-id-type="medline">37814277</pub-id></nlm-citation></ref><ref id="ref55"><label>55</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Taylor</surname><given-names>R</given-names> </name><name name-style="western"><surname>Zhang</surname><given-names>C</given-names> </name><name name-style="western"><surname>George</surname><given-names>D</given-names> </name><etal/></person-group><article-title>Low circulatory levels of total cholesterol, HDL-C and LDL-C are associated with death of patients with sepsis and critical illness: systematic review, meta-analysis, and perspective of observational studies</article-title><source>EBioMedicine</source><year>2024</year><month>02</month><volume>100</volume><fpage>104981</fpage><pub-id pub-id-type="doi">10.1016/j.ebiom.2024.104981</pub-id><pub-id pub-id-type="medline">38290288</pub-id></nlm-citation></ref><ref id="ref56"><label>56</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Zou</surname><given-names>G</given-names> </name><name name-style="western"><surname>Zhu</surname><given-names>Q</given-names> </name><name name-style="western"><surname>Ren</surname><given-names>B</given-names> </name><etal/></person-group><article-title>HDL-associated lipoproteins: potential prognostic biomarkers for gram-negative sepsis</article-title><source>J Inflamm Res</source><year>2022</year><volume>15</volume><fpage>1117</fpage><lpage>1131</lpage><pub-id pub-id-type="doi">10.2147/JIR.S350737</pub-id><pub-id pub-id-type="medline">35210815</pub-id></nlm-citation></ref><ref id="ref57"><label>57</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Weng</surname><given-names>L</given-names> </name><name name-style="western"><surname>Fan</surname><given-names>J</given-names> </name><name name-style="western"><surname>Yu</surname><given-names>C</given-names> </name><etal/></person-group><article-title>Body-mass index and long-term risk of sepsis-related mortality: a population-based cohort study of 0.5 million Chinese adults</article-title><source>Crit Care</source><year>2020</year><month>08</month><day>31</day><volume>24</volume><issue>1</issue><fpage>534</fpage><pub-id pub-id-type="doi">10.1186/s13054-020-03229-2</pub-id><pub-id pub-id-type="medline">32867859</pub-id></nlm-citation></ref><ref id="ref58"><label>58</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Paulsen</surname><given-names>J</given-names> </name><name name-style="western"><surname>Askim</surname><given-names>&#x00C5;</given-names> </name><name name-style="western"><surname>Mohus</surname><given-names>RM</given-names> </name><etal/></person-group><article-title>Associations of obesity and lifestyle with the risk and mortality of bloodstream infection in a general population: a 15-year follow-up of 64&#x2009;027 individuals in the HUNT Study</article-title><source>Int J Epidemiol</source><year>2017</year><month>10</month><day>1</day><volume>46</volume><issue>5</issue><fpage>1573</fpage><lpage>1581</lpage><pub-id pub-id-type="doi">10.1093/ije/dyx091</pub-id><pub-id pub-id-type="medline">28637260</pub-id></nlm-citation></ref><ref id="ref59"><label>59</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Winter-Jensen</surname><given-names>M</given-names> </name><name name-style="western"><surname>Afzal</surname><given-names>S</given-names> </name><name name-style="western"><surname>Jess</surname><given-names>T</given-names> </name><name name-style="western"><surname>Nordestgaard</surname><given-names>BG</given-names> </name><name name-style="western"><surname>Allin</surname><given-names>KH</given-names> </name></person-group><article-title>Body mass index and risk of infections: a Mendelian randomization study of 101,447 individuals</article-title><source>Eur J Epidemiol</source><year>2020</year><month>04</month><volume>35</volume><issue>4</issue><fpage>347</fpage><lpage>354</lpage><pub-id pub-id-type="doi">10.1007/s10654-020-00630-7</pub-id><pub-id pub-id-type="medline">32307655</pub-id></nlm-citation></ref></ref-list><app-group><supplementary-material id="app1"><label>Checklist 1</label><p>STROBE-MR checklist.</p><media xlink:href="i-jmr_v14i1e72244_app1.docx" xlink:title="DOCX File, 31 KB"/></supplementary-material></app-group></back></article>