Sexual dimorphism during LPS-induced systemic inflammation

Sexual dimorphism during LPS-induced systemic inflammation | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Sexual dimorphism during LPS-induced systemic inflammation Aron Jansen , Niklas Bruse , Nicole Waalders , Dirk van Lier , Guus Leijte , Jelle Gerretsen , Bas Adriaansen , Teun van Herwaarden , Peter Pickkers , Matthijs Kox doi: https://doi.org/10.1101/2025.02.04.25321661 Aron Jansen 1 Department of Intensive Care Medicine, Radboud university medical center , Nijmegen, The Netherlands MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Niklas Bruse 1 Department of Intensive Care Medicine, Radboud university medical center , Nijmegen, The Netherlands MSc Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nicole Waalders 1 Department of Intensive Care Medicine, Radboud university medical center , Nijmegen, The Netherlands MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dirk van Lier 1 Department of Intensive Care Medicine, Radboud university medical center , Nijmegen, The Netherlands MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Guus Leijte 1 Department of Intensive Care Medicine, Radboud university medical center , Nijmegen, The Netherlands MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jelle Gerretsen 1 Department of Intensive Care Medicine, Radboud university medical center , Nijmegen, The Netherlands BSc Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bas Adriaansen 2 Department of Laboratory Medicine, Radboud university medical center , Nijmegen, The Netherlands MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Teun van Herwaarden 2 Department of Laboratory Medicine, Radboud university medical center , Nijmegen, The Netherlands PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peter Pickkers 1 Department of Intensive Care Medicine, Radboud university medical center , Nijmegen, The Netherlands MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Matthijs Kox 1 Department of Intensive Care Medicine, Radboud university medical center , Nijmegen, The Netherlands PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: matthijs.kox{at}radboudumc.nl Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Incidence and outcomes of systemic inflammatory diseases, such as sepsis, differ between men and women, but the underlying mechanisms remain unclear. We examined systemic inflammatory responses in 56 male and 54 female healthy volunteers challenged with 1 ng/kg bacterial lipopolysaccharide (LPS) twice, with an interval of one week. Sex hormones, inflammatory markers, and monocyte RNA expression were determined. Women exhibited higher levels of several proinflammatory mediators than men during the first LPS challenge (TNF +45%, p=0.002; IL-6 +43%, p=0.0009; IP-10 +58%, p<0.0001; G-CSF +60%, p=0.02). Among women, use of hormonal contraceptives was associated with a more pronounced pro-inflammatory response (TNF +60%, p=0.001; IL-8 +30%, p=0.008; IP-10 +37%, p<0.0001). Endogenous concentrations of estrogens and testosterone inversely correlated with the extent of cytokine responses in women, while estrone positively correlated with these responses among men. The magnitude of endotoxin tolerance, exemplified by a significantly blunted cytokine response upon the second LPS challenge, was similar between the sexes, as were monocyte RNA expression patterns. In conclusion, our data indicate that there is considerable sexual dimorphism in systemic inflammation and implicate an important role for sex hormones in regulating immunity. Introduction Sepsis, defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection 1 , represents a global health care burden to hospitals and to intensive care units (ICUs) in particular. Despite significant advances in supportive care, sepsis mortality rates remain alarmingly high and its incidence continues to rise 2 – 5 . In fact, sepsis was recently identified as the leading cause of death worldwide, with an estimated 11 million fatalities annually 6 . Unfortunately, over the last decades a plethora of negative sepsis studies have failed to yield effective therapies, and as of today supportive care and source control remain the cornerstone of treatment 7 – 23 . One of the primary challenges in managing sepsis is its remarkable heterogeneity, with diverse pathophysiological manifestations across patients. These can include both hyperinflammation, characterized by an overwhelming release of proinflammatory mediators, hemodynamic shock and organ failure as well as immune suppression, marked by excessive anti-inflammatory responses that compromise immune function and increase susceptibility to secondary infections 24 , 25 . In this light, a solid understanding of the factors that drive these differential disease manifestations is of paramount importance for the development of personalized treatment approaches. One such factor may be biological sex. Demographic data consistently show that the incidence and outcomes of sepsis differ considerably between men and women, with women generally experiencing more favorable outcomes, including lower ICU admission rates and mortality 26 – 29 . These sex-specific differences in outcomes are not unique to sepsis, but also hold true for other infectious and systemic inflammatory conditions, such as COVID-19, which affects men more severely than women 30 – 32 . In contrast, auto-immune diseases such as multiple sclerosis and rheumatoid arthritis are more prevalent among women 33 . These observations suggest that sex-related differences in immune responses may play a significant role, yet robust in vivo human data are limited. In this study, we investigate how biological sex influences the immune response in a large cohort of healthy volunteers undergoing repeated experimental endotoxemia, a model that mimics many aspects of both the hyperinflammatory and immunoparalytic phenotypes of sepsis 34 , 35 . Results Safety and subject characteristics All subjects (female n= 54, male n=56) received LPS twice, with an interval of two weeks ( Figure 1A ). All procedures and symptoms associated with the experimental endotoxemia protocol were well tolerated by all subjects, and no (serious) adverse events occurred during the study. To explore potential effects of sex hormones on the response to LPS, female participants were subdivided into two groups based on the use of hormonal contraceptives (HC). Only women who used hormonal contraceptives with a systemic route of administration, such as oral, intramuscular, subcutaneous or transcutaneous contraceptives, were assigned to the HC+ group, whereas intrauterine devices (IUDs) were considered non-systemic contraceptives. Twenty-four female participants were assigned to the HC+ group, leaving 30 women in the HC-group. Baseline demographic characteristics of the study cohort are displayed in Figure 1B and reveal no relevant differences between groups. Download figure Open in new tab Figure 1. A: Schematic representation of the study protocol. B: Demographic characteristics of the study cohort. Data are represented as mean ± SEM. HC = hormonal contraceptives. Plasma cytokines The first LPS challenge resulted in a profound increase in all measured inflammatory cytokines in all subjects ( Figure 2 and Supplementary Figure 1 ). Compared to men, women (HC+ and HC-combined) exhibited markedly higher plasma concentrations of proinflammatory cytokines tumor necrosis factor (TNF; 45% higher geometric mean area under curve [AUC] values, p=0.002), interleukin (IL)-6 (+43%, p=0.009), interferon gamma induced protein (IP)-10 (+58%, p<0.0001), and granulocyte colony stimulating factor (G-CSF; +60%, p=0.02), whereas macrophage inflammatory protein (MIP)-1α and monocyte chemoattractant protein (MCP)-1 were not different (+14%, p=0.12 and -4%, p=0.38, respectively). Concentrations of the archetypal anti-inflammatory cytokine IL-10 (+0%, p=0.99) were similar between sexes, whereas the increase in IL-1 receptor antagonist (Ra), another anti-inflammatory cytokine, was more pronounced in women (+95%, p<0.0001). Download figure Open in new tab Figure 2. Cytokine time-concentration during the first (D0) and second (D7) LPS challenge, and magnitude of endotoxin tolerance (expressed as the log2 fold change in area under the curve between the two LPS challenge days). Cytokine concentrations are displayed as geometric mean with 95% confidence intervals, whereas tolerance is depicted as jitter plots with the crossbar indicating the mean. These differences in cytokine responses were also present upon the second challenge, for instance reflected by more pronounced increases in TNF (+25% p=0.03), IL-6 (+51% p=0.004) and IP-10 (+112% p<0.0001) in women compared with men, whereas IL-10 again showed no differences ( Figure 2 and Supplementary Figure 1 ). Furthermore, in both men and women, cytokine responses upon the second challenge were severely blunted as compared to the first challenge (p<0.0001 for all cytokines Figure 2 and Supplementary Figure 1 ). This phenomenon, known as endotoxin tolerance, was similar in magnitude between sexes for all cytokines ( Figure 2 and Supplementary Figure 1 ) . Clinical and hematological parameters Both LPS challenges led to a transient decrease in blood pressure and an increase in heart rate, body temperature and symptom scores ( Supplementary Figure 2 ). The LPS-induced maximum decrease in mean arterial pressure (MAP) was more pronounced in women during both challenges (both p<0.0001, Supplementary Figure 2 ), whereas the compensatory increase in heart rate did not differ between sexes during both challenges (p=0.98 and p=0.22, respectively, Supplementary Figure 2 ). Although the fever response was less pronounced in women than in men upon the first challenge, no differences were observed upon the second LPS challenge (p<0.001 and p=0.11, respectively, Supplementary Figure 2 ). Men and women displayed similar symptom scores over time upon the first challenge (p=0.23), although women exhibited higher scores during the second challenge (p<0.0001, Supplementary Figure 2 ). Moreover, peak scores of several individual symptoms such as headache, nausea and general malaise were higher in women during the first LPS challenge, whereas shivering and general malaise were also more pronounced in women upon the second LPS challenge ( Supplementary Figure 3 ). Baseline hemoglobin concentrations and platelet numbers differed significantly between men and women; however, the LPS-induced changes in these parameters over time were similar during both challenges ( Supplementary Figure 4 ). In contrast, circulating leukocyte numbers decreased more strongly in women (p<0.0001 for both challenges, Supplementary Figure 4 ), primarily due to a greater reduction in neutrophil counts (p<0.0001 and p=0.0001 during the first and second LPS challenge, respectively, Supplementary Figure 4 ). While the decrease in circulating monocyte counts following LPS administration was comparable between sexes, the monocyte repopulation was notably delayed in women during both challenges (p<0.0001 and p=0.005, respectively, Supplementary Figure 4 ). Influence of hormonal contraceptives Although women in the HC-group still exhibited significantly higher concentrations of several cytokines than men ( Figure 3A and Supplementary Figure 5 ), the cytokine responses were particularly more pronounced among women of the HC+ group. During both the first and second LPS challenge, use of HC was associated with a more pronounced increase of proinflammatory cytokines TNF (+60%, p=0.001 and +49%, p=0.04, respectively) and IP-10 (+37%, p<0.0001 and +37%, p=0.04, respectively) compared to women in the HC-group ( Figure 3A and Supplementary Figure 5 ) . Although differences in the IL-10 response did not reach statistical significance upon the first challenge (+41%, p=0.07), HC use was associated with significantly higher concentrations of IL-10 upon the second challenge (+48%, p<0.0001, Figure 3A and Supplementary Figure 5 ). Moreover, increases of IL-8, IL-1Ra and G-CSF were also more pronounced in the HC+ group ( Figure 3A and Supplementary Figure 5 ). No relationship between HC use and the magnitude of endotoxin tolerance was observed ( Figure 3A and Supplementary Figure 5 ). Download figure Open in new tab Figure 3. A: Heatmap depicting cytokine responses during the two LPS challenges (day 0 and day 7) and magnitude of endotoxin tolerance. Cytokine responses are displayed as Z-scaled geometric mean area under the curve and endotoxin tolerance is depicted as mean log2 fold change between the two LPS challenges. B: Differences in baseline concentrations of sex hormones. ♀ + = HC+ women, ♀ - = HC-women, ♂ = men; ns = not significant; ** = p<0.01; *** = p<0.001; **** = p<0.0001. C: Pearson correlations between sex hormone concentrations and area under the curve cytokine responses upon the first LPS challenge (day 0). Correlation coefficients are indicated by color and significant correlations are marked with an asterisk. Although HC use was not related to differences in MAP and heart rate trajectories over time upon the first challenge (p=0.39 and p=0.69 compared to the HC-group, respectively, Supplementary Figure 6 ), the decrease in MAP was more pronounced in the HC+ group upon the second challenge, whereas the compensatory increase in heart rate was less apparent (both p<0.0001, Supplementary Figure 6 ). During both LPS challenges, the fever response was substantially less pronounced in the HC+ group compared to the HC-group (p=0.0006 and p<0.0001, respectively, Supplementary Figure 6 ). Although the between-group difference in composite symptom score progression over time did not reach statistical significance during both challenges (p=0.053 and p=0.055, respectively, Supplementary Figure 6 ), women in the HC+ group did report higher peak scores of individual symptoms such as general malaise and headache upon the first LPS challenge. However, no such differences between the HC+ and HC-group were observed upon the second challenge ( Supplementary Figure 7 ). Role of sex hormones As expected, sex hormone concentrations determined at baseline differed substantially between men and women. For instance, compared to men, women of the HC-group exhibited significantly higher concentrations of estradiol and estrone (p<0.0001 and p=0.0001, respectively, Figure 3B ), whereas testosterone concentrations were lower (p<0.0001, Figure 3B ). Differences in progesterone did not reach statistical significance (p=0.06, Figure 3B ). Use of HC was associated with suppression of endogenous estrogens, resulting in lower concentrations of estradiol and estrone (p<0.0001 and p=0.001 compared to the HC-group, respectively, Figure 3B ). Testosterone concentrations were also lower in the HC+ group (p=0.0002, Figure 3B ) than in the HC-group, and a trend towards lower progesterone concentrations was observed (p=0.06, Figure 3B ). Correlations between sex hormone concentrations and cytokine responses during the first LPS challenge were determined among men and women separately to preclude group-based effects. Among men, estrone concentrations positively correlated with IL-6, IL-10 and G-CSF responses, although no significant relationships between estradiol and any of the cytokines were present ( Figure 3C ). In women, concentrations of the estrogens estrone and estradiol correlated inversely with TNF, IL-8, G-CSF, and IP-10 responses ( Figure 3C and Supplementary Figure 8 ). No associations between testosterone concentrations and cytokine responses were found among men ( Figure 3C and Supplementary Figure 8 ). In contrast, testosterone concentrations were inversely correlated with several pro-inflammatory cytokines in women (TNF, G-CSF, and IP-10, Figure 3C and Supplementary Figure 8 ). No relationships between progesterone concentrations and cytokine responses were found among both men and women. Monocyte RNA expression To investigate sex-specific differences in RNA expression, monocytes were isolated at baseline (T0) and four hours following the first LPS administration (T4), and RNA sequencing was performed ( Figure 1A ). After filtering genes with low counts across all samples, 14,564 genes remained for downstream analysis. An exploratory principal component analysis revealed that the first component (PC1) was mainly dependent on the timepoint (and thus driven by LPS administration), accounting for 39% of the observed variance in this dataset. PC2 accounted for 14% of the observed variance and was mainly driven by sex ( Figure 4A ). Differential expression analysis between samples obtained at T0 and T4 revealed that LPS administration resulted in more than 11,000 differentially expressed genes across men and women ( Figure 4B ). With an overlap of 90.5% in upregulated genes and 88.4% in downregulated genes, the monocyte transcriptomic response to LPS administration proved highly similar between the two sexes ( Figures 4B and 4C ). Next, the 20 most upregulated and downregulated genes were selected based on their log2 fold change and their expression levels on T4 were plotted in a heatmap, again displaying great similarity between men and women ( Figure 4D ). Finally, genes which were differentially expressed between men and women on T4 were explored using Reactome pathway analysis ( Figure 4E ). Several gene sets associated with hemostasis, signal transduction, developmental biology, reproduction, chromatin organization, and DNA localization were significantly more enriched in female subjects, whereas gene sets related to protein localization were less enriched in women. However, no significant differences in pathways associated with the immune system and cellular responses to stimuli were observed. Download figure Open in new tab Figure 4. A: Principal component analysis of the variance in gene expression in monocytes isolated at baseline (T0) and four hours (T4) after the first LPS challenge (day 0). B: Venn-diagrams displaying the overlap in significantly upregulated and downregulated genes between male and female subjects. C: Volcano-plots of differentially expressed genes between monocytes isolated at T0 and T4 for male and female participants. D: Heatmap depicting normalized counts per million (CPM) at T4 of the top 20 upregulated and downregulated genes in all subjects of the study cohort. E: Bar-plot displaying differences in gene-set enrichment between male and female subjects (Reactome analysis). Nested enrichment scores (NES) are indicated by color, and non-significantly enriched terms are displayed in grey. Discussion Sepsis and numerous other inflammatory diseases exhibit distinct incidence rates and outcome statistics among men and women, suggesting the presence of sexual dimorphism in immunity. Although the origins of these differences have been extensively investigated in preclinical (animal) models and in vitro studies, comprehensive in vivo data from human subjects remain limited. In the present work, we demonstrate that women mount a more pronounced proinflammatory response to intravenous administration of bacterial LPS than men. Furthermore, our findings indicate that hormonal contraceptive use is strongly associated with the magnitude of the immune response, highlighting a significant influence of sex hormones in regulation of the immune response. Finally, our study signifies that despite these marked sex-based differences in the magnitude of the LPS-induced immune response, monocyte RNA expression patterns were largely similar between male and female participants. Our results are in agreement with previous endotoxemia studies that also reported a more pronounced proinflammatory response in women 29 , 36 – 38 . However, neither the role of sex hormones and hormonal contraceptives, nor transcriptomic responses had been studied to date. The use of hormonal contraceptives was associated with more pronounced cytokine responses. In line, estrone concentrations were correlated with stronger cytokine responses in men. In contrast, estrogens were inversely related to cytokine responses among women. Perhaps counterintuitively, this may actually support the pro-inflammatory effects of estrogens found in men, as hormonal contraceptives used by a large proportion of women in our cohort strongly suppress endogenous estrogens, which our data clearly show as well. The effects of estrogens on immune function are not uncontested in literature 39 and appear to be concentration-dependent: low or physiological concentrations (such as those evoked by hormonal contraceptive use) tend to promote inflammation in animal and in vitro studies, while higher concentrations (such as observed during pregnancy) are generally thought to be anti-inflammatory 39 , 40 . The putative proinflammatory effects of hormonal contraceptives are further supported by clinical studies reporting elevated levels of C-reactive protein and other acute phase proteins in young women using oral contraceptives 41 , 42 . Additionally, the use of hormonal contraceptives has been linked to an increased susceptibility to several autoimmune diseases, including multiple sclerosis, Crohn’s disease, and lupus 43 . Based on these effects, one might hypothesize that hormonal contraceptives could have therapeutic potential in managing sepsis-induced immune suppression. However, since our study found no impact of hormonal contraceptives on the development of endotoxin tolerance, our results do not directly support this hypothesis. Testosterone concentrations were inversely correlated with several proinflammatory cytokines in female participants, supporting a broader body of literature that suggests an anti-inflammatory role of androgens 39 . Although no such correlations were observed in male subjects, this may be attributed to a threshold effect, given that our study comprised a highly homogeneous group of young, healthy volunteers with high testosterone levels. This may have obscured evidencing relationships between testosterone and immune function among men. This hypothesis is consistent with findings from a study in male COVID-19 patients, where inverse correlations between testosterone concentrations and several proinflammatory cytokines were found 44 . The transcriptomic responses of monocytes upon an LPS challenge were largely similar between men and women, only differing in magnitude rather than specific molecular pathways. These results align with a clinical cohort study of sepsis patients, which also reported an 80% overlap in leukocyte gene expression between male and female patients 45 . It appears plausible that the apparent lack of a genomic substrate for the observed differences in cytokine production reflects the highly conserved nature of host defense pathways. Our study has several strengths. Unlike immunological studies in sepsis patients, which are often confounded by factors such as age, medical history, medication use, disease severity and source of infection, the experimental endotoxemia model offers a highly standardized and reproducible framework to investigate systemic inflammation in humans in vivo . Furthermore, while experimental endotoxemia studies are often constrained by small sample sizes due to their cost and labor-intensive nature, we included over 100 participants, enabling a more comprehensive exploration of the factors underlying immunological differences between male and female participants. However, although the homogeneity of our study population is a benefit in terms of confounding factors, it clearly also represents a limitation, as results from our study may not be generalizable to populations with broader demographic diversity. Moreover, the inflammatory response induced by experimental endotoxemia is relatively acute and transient, which may limit its translatability to diseases and conditions characterized by sustained systemic inflammation. Nevertheless, previous work has shown that many hallmarks of the immune response in sepsis, including hyperinflammatory and immunosuppressive mechanisms, are also present in the endotoxemia model 35 . Finally, RNA sequencing was only performed in monocytes and it cannot be excluded that differential transcriptomic responses between men and women are present in other immune cells, such as lymphocytes, neutrophils, tissue-resident macrophages, or endothelial cells. In conclusion, we demonstrate that women mount a markedly more pronounced proinflammatory response during experimental endotoxemia than men, that the observed differences in cytokine production do not arise from distinct underlying molecular pathways, and that responses are strongly influenced by sex hormones, supporting an important immunoregulatory role for these mediators. Methods Subjects After approval of the local ethics committee (Medical Ethical Committee Oost-Nederland; reference no. NL68166.091.18), 56 male and 54 female healthy volunteers between 18-35 years old were recruited for the endotoxemia study. All subjects provided written informed consent and were included after medical history, physical examination, routine laboratory tests, and a 12-lead electrocardiogram did not reveal any abnormalities. Smoking, use of any medication (with exception of contraceptives), previous participation in experimental human endotoxemia, or signs of acute illness within two weeks prior to the start of the study were exclusion criteria. All study procedures were performed in compliance with the declaration of Helsinki, including the latest revisions. Study design We performed a prospective experimental cohort study, the design of which is depicted in Figure 1A . All subjects were intravenously challenged with bacterial lipopolysaccharide (LPS) twice, on study days zero and seven. The first challenge served to induce a systemic inflammatory response and the development of endotoxin tolerance. The second challenge served to quantify the degree of endotoxin tolerance, which is reflected by a blunted cytokine response upon the second challenge as compared to the first challenge 35 , 46 – 48 . To gain insight into the effects of contraceptives on the immune response, questionnaires regarding contraceptive methods were sent out to all participants prior to the first LPS challenge. In female participants, pregnancy was excluded prior to LPS administration on both days by using a human chorionic gonadotropin (hCG) urine dipstick test. Other than that, there were no differences in the protocol between female and male participants. Experimental endotoxemia Experimental endotoxemia procedures were performed as described extensively elsewhere 34 . In short: during both LPS challenge days, subjects were admitted to the research unit of the Intensive Care Department of the Radboud university medical center for 8 hours. Subjects had to refrain from alcohol and caffeine (24 hours), and food and drinks (12 hours) prior to LPS administration. Upon admission, subjects were weighed to determine the total dose of LPS to be administered (1 ng/kg bodyweight). An intravenous cannula was placed in an antebrachial vein to administer fluids and LPS. A radial artery catheter (BD Infusion Therapy Systems, Sandy, USA) was placed under ultrasound guidance to allow serial blood sampling and continuous monitoring and collection of hemodynamic data. Prior to LPS administration, prehydration fluids (1.5 liters of 2.5% glucose / 0.45% sodium chloride in 45 minutes) were administered to reduce the risk of vasovagal responses 49 . Thereafter, a bolus of 1 ng/kg LPS ( E. coli Type O113 , Lot no. 94332B1; List Biological Laboratories, Campbell, USA) was administered. Hydration fluids (2.5% glucose / 0.45% sodium chloride) were administered at a rate of 150 mL/h continuously throughout the experiment. Clinical parameters During hospitalization, heart rate and intra-arterial blood pressure were continuously monitored using a 4-lead electrocardiogram (M50 Monitor, Philips, Eindhoven, the Netherlands), and a radial artery pressure transducer (Edward Lifesciences, Irvine, USA) connected to the Philips monitor, respectively. Hemodynamic data were sampled every 5 seconds using in-house developed software. Every 30 minutes, core temperature was measured with a tympanic thermometer (FirstTemp Genius 2, Covidien, Dublin, Ireland). Flu-like symptoms (headache, nausea, cold shivers, muscle and back pain) were scored using a numeric six-point Likert scale (0 = no symptoms, 5 = worst ever experienced) whereas general malaise was scored on an eleven-point Likert scale (0 = no symptoms, 10 = worst ever experienced). A total composite symptom score was then calculated as the sum of all previous elements, resulting in a total symptom score ranging from 0 to 35. Sex hormone measurements Sex hormone profiles were assessed at baseline (before the first LPS challenge). To this end, blood samples were collected in serum clot activator tubes and allowed to clot for 30 minutes. Tubes were subsequently centrifuged (10 min, 2000g, 4°C) and serum was stored at -80°C until analysis. Concentrations of testosterone, progesterone, estrone and estradiol were determined batchwise using liquid chromatography – mass spectrometry (LC-MS). Cytokine measurements For plasma cytokines, EDTA-anticoagulated blood was centrifuged (10 min, 2000g, 4°C) directly after withdrawal and plasma was stored at -80°C until analysis. Concentrations of tumor necrosis factor (TNF), interleukin (IL)-1 receptor antagonist (Ra), IL-6, IL-8, IL-10, macrophage inflammatory protein (MIP)-1α, monocyte chemoattractant protein (MCP)-1, granulocyte colony stimulating factor (G-CSF) and interferon-γ induced protein (IP)-10 were determined batchwise using a simultaneous Luminex assay (Milliplex, Millipore, Billerica, USA). RNA sequencing Classical monocytes (CD14+CD16-) were isolated at baseline (T0) and four hours after LPS administration (T4). To this end, PBMCs were first isolated as described above. Subsequently, classical monocytes were isolated by immunomagnetic negative selection using a monocyte isolation kit (EasySepTM Human Monocyte Isolation Kit, STEMCELL Technologies, Cologne, Germany) and RNA was isolated using the RNeasy kit (Qiagen, Hilden, Germany) as per the manufacturer’s instructions. Sequencing of the isolated samples was performed by BGI Genomics (Shenzhen, China) using their proprietary DNBseq TM platform. Using a pipeline developed in-house by the Center for Molecular and Biomolecular Informatics (CMBI) of Radboud university medical center, the resulting paired-end reads (.fastQ files) were trimmed using Trim Galore! v0.4.5 to remove low-quality bases and adapters, quality checked using MultiQC and subsequently mapped against the GRCh38 reference transcriptome using STAR v2.6.0a 50 – 52 . Gene counts were quantified using HTSeq v0.11.0, resulting in gene counts for 58,740 genes 53 . Genes with low counts across all samples were filtered using the default ‘filterByExpr()’ function from edgeR v4.0.2 54 . Next, differential expression analysis between samples obtained at T0 and T4 was performed using DESeq2 v1.42.0. Finally, to further explore potential between-sex differences in the transcriptomic response to LPS, pathway analysis was performed on differentially expressed genes between male and female subjects on T4 using ReactomePA v1.46.0 55 . Statistical analysis Distribution of data was tested for normality using Shapiro-Wilk’s test, and data with a non-Gaussian distribution were log-transformed prior to statistical testing. Data with a Gaussian distribution are presented as mean ± standard error (SEM), and non-parametric data as geometric mean (95%-confidence interval) or median [interquartile range]. The area under the time-concentration curve (AUC) was used as an integral measure of cytokine responses over time during each LPS challenge day. In the text, percentage difference in cytokine AUCs are reported to illustrate differences in responses to LPS. The degree of endotoxin tolerance was calculated per cytokine as the log2 fold change in AUC between the two LPS challenges. Differences in baseline characteristics were analyzed using unpaired student’s t-tests. Repeated measures two-way analysis of variance (ANOVA, time*group interaction term) was used to analyze between-group differences over time within the same LPS challenge day. Within-group differences between the two LPS challenge days were compared using paired student’s t-tests. Pearson’s correlation analysis was used. A two-tailed p-value <0.05 was considered statistically significant, and results were corrected for multiple testing using the false discovery rate according to Benjamini and Hochberg where applicable 56 . All statistical analyses were performed using GraphPad Prism version 8 (GraphPad Software, San Diego, USA) and R version 4.3.2 (The R Foundation for Statistical Computing, Vienna, Austria). Data Availability All data produced in the present study are available upon reasonable request to the authors Supplementary Figures Download figure Open in new tab Supplementary Figure 1. Cytokine time-concentration curves during the first (D0) and second (D7) LPS challenge, and magnitude of endotoxin tolerance (expressed as the log2 fold change in area under the curve between the two LPS challenge days). Cytokine concentrations are displayed as geometric mean with 95% confidence intervals, whereas tolerance is depicted in jitter plots with the crossbar indicating the mean. Download figure Open in new tab Supplementary Figure 2. LPS-induced changes over time in blood pressure, heart rate, body temperature and composite symptom scores during the first (D0) and second (D7) LPS challenge. Blood pressure, heart rate and temperature are displayed as mean ± SEM, whereas symptom scores are displayed as median and interquartile range. MAP = mean arterial pressure; mmHg = millimeters of mercury; bpm = beats per minute; °C = degrees Celsius. Download figure Open in new tab Supplementary Figure 3. Differences in peak scores of individual symptoms and composite symptom score during the first (day 0) and second (day 7) LPS challenge. Data displayed as jitter plots with the crossbar indicating the median. CSS = composite symptom score. ns = not significant; * = p≤0.05; ** = p<0.01. Download figure Open in new tab Supplementary Figure 4. Time-concentration curves of hemocytometry parameters during the first (D0) and second (D7) LPS challenge. Data displayed as mean ± SEM. Download figure Open in new tab Supplementary Figure 5. Cytokine time-concentration curves on during the first (D0) and second (D7) LPS challenge, and magnitude of endotoxin tolerance (expressed as the log2 fold change in area under the curve between the two LPS challenge days). Cytokine concentrations are displayed as geometric mean with 95% confidence intervals, whereas tolerance is depicted in jitter plots with the crossbar indicating the mean. ♀ + = HC+ women; ♀ - = HC-women; ♂ = men; ns = not significant. Download figure Open in new tab Supplementary Figure 6. LPS-induced changes over time in blood pressure, heart rate, body temperature and composite symptom scores during the first (D0) and second (D7) LPS challenge. Blood pressure, heart rate and temperature are displayed as mean ± SEM, whereas symptom scores are displayed as median and interquartile range. MAP = mean arterial pressure; mmHg = millimeters of mercury; bpm = beats per minute; °C = degrees Celsius; ♀ + = HC+ women; ♀ - = HC-women; ♂ = men. Download figure Open in new tab Supplementary Figure 7. Differences in peak scores of individual symptoms and composite symptom score during the first (day 0) and second (day 7) LPS challenge. Data displayed as jitter plots with the crossbar indicating the median. CSS = composite symptom score. ns = not significant; * = p≤0.05; ** = p<0.01; ♀ + = HC+ women; ♀ - = HC-women; ♂ = men. Download figure Open in new tab Supplementary Figure 8. Scatterplots displaying Pearson correlations between baseline sex hormone concentrations and area under the curve (AUC) of inflammatory cytokines during the first LPS challenge. References ↵ Singer , M. et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)Consensus Definitions for Sepsis and Septic ShockConsensus Definitions for Sepsis and Septic Shock . Jama 315 , 801 – 810 ( 2016 ). doi: 10.1001/jama.2016.0287 OpenUrl CrossRef PubMed ↵ Luhr , R. , Cao , Y. , Söderquist , B. & Cajander , S. Trends in sepsis mortality over time in randomised sepsis trials: a systematic literature review and meta-analysis of mortality in the control arm, 2002–2016 . Critical Care 23 , 241 ( 2019 ). doi: 10.1186/s13054-019-2528-0 OpenUrl CrossRef PubMed Fleischmann , C. et al. Assessment of Global Incidence and Mortality of Hospital-treated Sepsis. Current Estimates and Limitations . American Journal of Respiratory and Critical Care Medicine 193 , 259 – 272 ( 2016 ). doi: 10.1164/rccm.201504-0781OC OpenUrl CrossRef PubMed Angus , D. C. et al. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care . Crit Care Med 29 , 1303 – 1310 ( 2001 ). OpenUrl CrossRef PubMed Web of Science ↵ Gaieski , D. F. , Edwards , J. M. , Kallan , M. J. & Carr , B. G . Benchmarking the Incidence and Mortality of Severe Sepsis in the United States* . Critical Care Medicine 41 , 1167 – 1174 ( 2013 ). doi: 10.1097/CCM.0b013e31827c09f8 OpenUrl CrossRef PubMed Web of Science ↵ Rudd , K. E. et al. Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study . Lancet (London, England) 395 , 200 – 211 ( 2020 ). doi: 10.1016/S0140-6736(19)32989-7 OpenUrl CrossRef PubMed ↵ Annane , D. et al. Corticosteroids in the treatment of severe sepsis and septic shock in adults: a systematic review . Jama 301 , 2362 – 2375 ( 2009 ). doi: 10.1001/jama.2009.815 OpenUrl CrossRef PubMed Web of Science Warren , B. L. et al. Caring for the critically ill patient. High-dose antithrombin III in severe sepsis: a randomized controlled trial . Jama 286 , 1869 – 1878 ( 2001 ). doi: 10.1001/jama.286.15.1869 OpenUrl CrossRef PubMed Web of Science Abraham , E. et al. Efficacy and safety of tifacogin (recombinant tissue factor pathway inhibitor) in severe sepsis: a randomized controlled trial . Jama 290 , 238 – 247 ( 2003 ). doi: 10.1001/jama.290.2.238 OpenUrl CrossRef PubMed Web of Science Rice , T. W. et al. A randomized, double-blind, placebo-controlled trial of TAK-242 for the treatment of severe sepsis . Crit Care Med 38 , 1685 – 1694 ( 2010 ). doi: 10.1097/CCM.0b013e3181e7c5c9 OpenUrl CrossRef PubMed Web of Science Angus , D. C. et al. E5 murine monoclonal antiendotoxin antibody in gram-negative sepsis: a randomized controlled trial. E5 Study Investigators . Jama 283 , 1723 – 1730 ( 2000 ). doi: 10.1001/jama.283.13.1723 OpenUrl CrossRef PubMed Web of Science Opal , S. M. et al. Confirmatory interleukin-1 receptor antagonist trial in severe sepsis: a phase III, randomized, double-blind, placebo-controlled, multicenter trial. The Interleukin-1 Receptor Antagonist Sepsis Investigator Group . Crit Care Med 25 , 1115 – 1124 ( 1997 ). doi: 10.1097/00003246-199707000-00010 OpenUrl CrossRef PubMed Web of Science Abraham , E. et al. Lenercept (p55 tumor necrosis factor receptor fusion protein) in severe sepsis and early septic shock: a randomized, double-blind, placebo-controlled, multicenter phase III trial with 1,342 patients . Crit Care Med 29 , 503 – 510 ( 2001 ). doi: 10.1097/00003246-200103000-00006 OpenUrl CrossRef PubMed Web of Science Abraham , E. et al. Double-blind randomised controlled trial of monoclonal antibody to human tumour necrosis factor in treatment of septic shock. NORASEPT II Study Group. Lancet (London , England ) 351 , 929 – 933 ( 1998 ). OpenUrl Cohen , J. & Carlet , J . INTERSEPT: an international, multicenter, placebo-controlled trial of monoclonal antibody to human tumor necrosis factor-alpha in patients with sepsis. International Sepsis Trial Study Group . Crit Care Med 24 , 1431 – 1440 ( 1996 ). doi: 10.1097/00003246-199609000-00002 OpenUrl CrossRef PubMed Web of Science Abraham , E. et al. Efficacy and safety of monoclonal antibody to human tumor necrosis factor alpha in patients with sepsis syndrome . A randomized, controlled, double-blind, multicenter clinical trial. TNF-alpha MAb Sepsis Study Group. Jama 273 , 934 – 941 ( 1995 ). OpenUrl Root , R. K. et al. Multicenter, double-blind, placebo-controlled study of the use of filgrastim in patients hospitalized with pneumonia and severe sepsis . Crit Care Med 31 , 367 – 373 ( 2003 ). doi: 10.1097/01.Ccm.0000048629.32625.5d OpenUrl CrossRef PubMed Web of Science McCloskey , R. V. , Straube , R. C. , Sanders , C. , Smith , S. M. & Smith , C. R . Treatment of septic shock with human monoclonal antibody HA-1A . A randomized, double-blind, placebo-controlled trial. CHESS Trial Study Group. Ann Intern Med 121 , 1 – 5 ( 1994 ). doi: 10.7326/0003-4819-121-1-199407010-00001 OpenUrl CrossRef PubMed Web of Science Cavaillon , J.-M. , Singer , M. & Skirecki , T . Sepsis therapies: learning from 30 years of failure of translational research to propose new leads . EMBO Molecular Medicine 12 , e10128 ( 2020 ). doi: 10.15252/emmm.201810128 OpenUrl CrossRef PubMed Barrot , L. et al. Liberal or Conservative Oxygen Therapy for Acute Respiratory Distress Syndrome . New England Journal of Medicine 382 , 999 – 1008 ( 2020 ). doi: 10.1056/NEJMoa1916431 OpenUrl CrossRef PubMed Moskowitz , A. et al. Effect of Ascorbic Acid, Corticosteroids, and Thiamine on Organ Injury in Septic Shock: The ACTS Randomized Clinical Trial . Jama 324 , 642 – 650 ( 2020 ). doi: 10.1001/jama.2020.11946 OpenUrl CrossRef PubMed Fujii , T. et al. Effect of Vitamin C, Hydrocortisone, and Thiamine vs Hydrocortisone Alone on Time Alive and Free of Vasopressor Support Among Patients With Septic Shock: The VITAMINS Randomized Clinical Trial . Jama 323 , 423 – 431 ( 2020 ). doi: 10.1001/jama.2019.22176 OpenUrl CrossRef PubMed ↵ Dellinger , R. P. et al. Effect of Targeted Polymyxin B Hemoperfusion on 28-Day Mortality in Patients With Septic Shock and Elevated Endotoxin Level: The EUPHRATES Randomized Clinical Trial . Jama 320 , 1455 – 1463 ( 2018 ). doi: 10.1001/jama.2018.14618 OpenUrl CrossRef PubMed ↵ van der Poll , T. , van de Veerdonk , F. L. , Scicluna , B. P. & Netea , M. G . The immunopathology of sepsis and potential therapeutic targets . Nat Rev Immunol 17 , 407 – 420 ( 2017 ). doi: 10.1038/nri.2017.36 OpenUrl CrossRef PubMed ↵ Angus , D. C. & van der Poll , T. Severe sepsis and septic shock . N Engl J Med 369 , 840 – 851 ( 2013 ). doi: 10.1056/NEJMra1208623 OpenUrl CrossRef PubMed Web of Science ↵ Antequera , A. et al. Sex as a prognostic factor for mortality in critically ill adults with sepsis: a systematic review and meta-analysis . BMJ Open 11 , e048982 ( 2021 ). doi: 10.1136/bmjopen-2021-048982 OpenUrl Abstract / FREE Full Text Zhang , M. Q. et al. Sex- and Gender-Dependent Differences in Clinical and Preclinical Sepsis . Shock (Augusta, Ga.) 56 , 178 – 187 ( 2021 ). doi: 10.1097/SHK.0000000000001717 OpenUrl CrossRef PubMed Schröder , J. , Kahlke , V. , Staubach , K.-H. , Zabel , P. & Stüber , F . Gender Differences in Human Sepsis . Archives of Surgery 133 , 1200 – 1205 ( 1998 ). doi: 10.1001/archsurg.133.11.1200 OpenUrl CrossRef PubMed Web of Science ↵ Ferguson , J. F. et al. Race and gender variation in response to evoked inflammation . J Transl Med 11 , 63 – 63 ( 2013 ). doi: 10.1186/1479-5876-11-63 OpenUrl CrossRef PubMed ↵ Ya’qoub , L. , Elgendy , I. Y. & Pepine , C. J . Sex and gender differences in COVID-19: More to be learned! American Heart Journal Plus: Cardiology Research and Practice 3 , 100011 ( 2021 ). doi: 10.1016/j.ahjo.2021.100011 OpenUrl CrossRef Viveiros , A. et al. Sex differences in COVID-19: candidate pathways, genetics of ACE2, and sex hormones . Am J Physiol Heart Circ Physiol 320 , H296 – h304 ( 2021 ). doi: 10.1152/ajpheart.00755.2020 OpenUrl CrossRef PubMed ↵ Williamson , E. J. et al. Factors associated with COVID-19-related death using OpenSAFELY . Nature 584 , 430 – 436 ( 2020 ). doi: 10.1038/s41586-020-2521-4 OpenUrl CrossRef PubMed ↵ Ngo , S. T. , Steyn , F. J. & McCombe , P. A . Gender differences in autoimmune disease . Frontiers in Neuroendocrinology 35 , 347 – 369 ( 2014 ). doi: 10.1016/j.yfrne.2014.04.004 OpenUrl CrossRef PubMed ↵ van Lier , D. , Geven , C. , Leijte , G. P. & Pickkers , P . Experimental human endotoxemia as a model of systemic inflammation . Biochimie 159 , 99 – 106 ( 2019 ). doi: 10.1016/j.biochi.2018.06.014 OpenUrl CrossRef PubMed ↵ Keramati , F. et al. Systemic inflammation impairs human myelopoiesis and interferon I responses . medRxiv , 2022.2010.2006.22280312 ( 2022 ). doi: 10.1101/2022.10.06.22280312 OpenUrl Abstract / FREE Full Text ↵ Engler , H. et al. Men and women differ in inflammatory and neuroendocrine responses to endotoxin but not in the severity of sickness symptoms . Brain Behav Immun 52 , 18 – 26 ( 2016 ). doi: 10.1016/j.bbi.2015.08.013 OpenUrl CrossRef PubMed van Eijk , L. T. et al. Gender differences in the innate immune response and vascular reactivity following the administration of endotoxin to human volunteers . Crit Care Med 35 , 1464 – 1469 ( 2007 ). doi: 10.1097/01.Ccm.0000266534.14262.E8 OpenUrl CrossRef PubMed Web of Science ↵ Wegner , A. et al. Sex differences in the pro-inflammatory cytokine response to endotoxin unfold in vivo but not ex vivo in healthy humans . Innate Immunity 23 , 432 – 439 ( 2017 ). doi: 10.1177/1753425917707026 OpenUrl CrossRef PubMed ↵ Shepherd , R. , Cheung , A. S. , Pang , K. , Saffery , R. & Novakovic , B . Sexual Dimorphism in Innate Immunity: The Role of Sex Hormones and Epigenetics . Frontiers in Immunology 11 ( 2021 ). doi: 10.3389/fimmu.2020.604000 OpenUrl CrossRef ↵ Klein , S. L. & Flanagan , K. L . Sex differences in immune responses . Nature Reviews Immunology 16 , 626 – 638 ( 2016 ). doi: 10.1038/nri.2016.90 OpenUrl CrossRef PubMed ↵ Kluft , C. , Leuven , J. A. , Helmerhorst , F. M. & Krans , H. M . Pro-inflammatory effects of oestrogens during use of oral contraceptives and hormone replacement treatment . Vascul Pharmacol 39 , 149 – 154 ( 2002 ). doi: 10.1016/s1537-1891(02)00304-x OpenUrl CrossRef PubMed Web of Science ↵ van Rooijen , M. et al. Treatment with combined oral contraceptives induces a rise in serum C-reactive protein in the absence of a general inflammatory response . J Thromb Haemost 4 , 77 – 82 ( 2006 ). doi: 10.1111/j.1538-7836.2005.01690.x OpenUrl CrossRef PubMed Web of Science ↵ Williams , W. V . Hormonal contraception and the development of autoimmunity: A review of the literature . Linacre Q 84 , 275 – 295 ( 2017 ). doi: 10.1080/00243639.2017.1360065 OpenUrl CrossRef PubMed ↵ Dhindsa , S. et al. Association of Circulating Sex Hormones With Inflammation and Disease Severity in Patients With COVID-19 . JAMA Network Open 4 , e2111398 – e2111398 ( 2021 ). doi: 10.1001/jamanetworkopen.2021.11398 OpenUrl CrossRef ↵ van Vught , L. A. et al. Association of Gender With Outcome and Host Response in Critically Ill Sepsis Patients . Crit Care Med 45 , 1854 – 1862 ( 2017 ). doi: 10.1097/ccm.0000000000002649 OpenUrl CrossRef PubMed ↵ Kox , M. et al. Differential ex vivo and in vivo endotoxin tolerance kinetics following human endotoxemia . Crit Care Med 39 , 1866 – 1870 ( 2011 ). doi: 10.1097/CCM.0b013e3182190d5d OpenUrl CrossRef PubMed Web of Science Leijte , G. P. et al. Treatment With Acetylsalicylic Acid Reverses Endotoxin Tolerance in Humans In Vivo: A Randomized Placebo-Controlled Study . Crit Care Med 47 , 508 – 516 ( 2019 ). doi: 10.1097/ccm.0000000000003630 OpenUrl CrossRef PubMed ↵ Leentjens , J. et al. Reversal of immunoparalysis in humans in vivo: a double-blind, placebo-controlled, randomized pilot study . Am J Respir Crit Care Med 186 , 838 – 845 ( 2012 ). doi: 10.1164/rccm.201204-0645OC OpenUrl CrossRef PubMed Web of Science ↵ van Eijk , L. T. , Pickkers , P. , Smits , P. , Bouw , M. P. & van der Hoeven , J. G . Severe vagal response after endotoxin administration in humans . Intensive Care Med 30 , 2279 – 2281 ( 2004 ). doi: 10.1007/s00134-004-2477-0 OpenUrl CrossRef PubMed Web of Science ↵ Dobin , A. et al. STAR: ultrafast universal RNA-seq aligner . Bioinformatics 29 , 15 – 21 ( 2012 ). doi: 10.1093/bioinformatics/bts635 OpenUrl CrossRef PubMed Web of Science Ewels , P. , Magnusson , M. , Lundin , S. & Käller , M . MultiQC: summarize analysis results for multiple tools and samples in a single report . Bioinformatics 32 , 3047 – 3048 ( 2016 ). doi: 10.1093/bioinformatics/btw354 OpenUrl CrossRef PubMed ↵ Krueger , F. et al. FelixKrueger/TrimGalore: v0.6.10 . Zenodo ( 2023 ). doi: 10.5281/zenodo.5127898 OpenUrl CrossRef ↵ Anders , S. , Pyl , P. T. & Huber , W . HTSeq—a Python framework to work with high-throughput sequencing data . Bioinformatics 31 , 166 – 169 ( 2014 ). doi: 10.1093/bioinformatics/btu638 OpenUrl CrossRef PubMed Web of Science ↵ Robinson , M. D. , McCarthy , D. J. & Smyth , G. K . edgeR: a Bioconductor package for differential expression analysis of digital gene expression data . Bioinformatics 26 , 139 – 140 ( 2009 ). doi: 10.1093/bioinformatics/btp616 OpenUrl CrossRef PubMed Web of Science ↵ Yu , G. & He , Q.-Y . ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization . Molecular BioSystems 12 , 477 – 479 ( 2016 ). doi: 10.1039/C5MB00663E OpenUrl CrossRef PubMed ↵ Benjamini , Y. & Hochberg , Y . Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing . Journal of the Royal Statistical Society: Series B (Methodological ) 57 , 289 – 300 ( 1995 ). doi: 10.1111/j.2517-6161.1995.tb02031.x OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted February 11, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. 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