Early expression of PD-L1 on monocyte is a predictor for severity in older adult sepsis

Early expression of PD-L1 on monocyte is a predictor for severity in older adult sepsis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Early expression of PD-L1 on monocyte is a predictor for severity in older adult sepsis Qian Gao, Beibei Liu, Li Yang, Tiecheng Yang, Shubin Guo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8975708/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Objective To evaluate the early expression of programmed cell death receptor ligand-1 (PD-L1) on different subtype of monocyte and investigate their relation in term the severity of sepsis in the older adult population. Methods Eighty sepsis patients in older adult and 40 age and sex matched healthy controls were included in this study. The flow cytometry method was used to measure the monocyte subsets and PD-L1 expression on different subsets of monocyte. Results PD-L1 expression on M1 monocyte was lower in septic shock group compared to patients without shock [1.19% (0.69%, 2.42%) vs. 1.96% (0.65%, 4.10%), p = 0.012]. PD-L1 expression on M1 monocyte (OR = 0.542, CI: 0.324, 0.907, p = 0.020) still exhibited significant effect in predicating septic shock in logistic regression analysis. The aera under the curve (AUC) from the receiver operating characteristic curve displayed that the of PD-L1 expression on M1 monocyte for predicting septic shock was 0.689 (p = 0.006). The AUC for the combined analysis of PD-L1 expression on M1 monocytes and the sequential organ failure assessment score was 0.826 (p < 0.001). Conclusion The PD-L1 expression on M1 monocyte could be a new predictor for the severity of sepsis and provided a new therapeutic breakthrough for sepsis in older adult population. Health sciences/Biomarkers Health sciences/Diseases Biological sciences/Immunology Health sciences/Medical research sepsis sepsis shock monocyte subsets PD-L1 aging Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Sepsis represents a life-threatening infectious condition accompanied by varying degrees of organ dysfunction, arising from a complex interplay between the host's pro-inflammatory and anti-inflammatory responses( 1 ). Monocytes isolated from sepsis patients display a reduced ability to secrete pro-inflammatory mediators, including interleukin (IL)-1α, IL-6, and tumour necrosis factor (TNF)-α. In contrast, the production of anti-inflammatory cytokines such as IL-10 and IL-1 receptor antagonist—remains unimpaired or even elevated, a key hallmark of sepsis-associated immunosuppression( 2 , 3 ). Human peripheral blood monocytes constitute a heterogeneous cell population, which can be categorized into three distinct subtypes based on the expression patterns of CD14 (a lipopolysaccharide receptor) and CD16 (the FcγIII receptor) on their cell membranes( 4 , 5 ). According to this classification system, monocytes are divided into: "classical monocytes" with high CD14 expression and no CD16 expression (CD14 + + CD16−); "intermediate monocytes" that co-express both receptors (CD14 + + CD16+); and "nonclassical monocytes" characterized by predominant CD16 expression (CD14 + CD16++)( 4 ). Previous studies have indicated that the immunosuppressive phase of sepsis is typified by increased anti-inflammatory cytokine synthesis and decreased expression of human leukocyte antigen-DR (HLA-DR)( 6 ). Additionally, programmed cell death receptor-1 (PD-1) and its ligand PD-L1 co-inhibitory receptor molecules exert crucial regulatory effects on sepsis-induced immunosuppression ( 7 ). The global aging population is expanding at an alarming rate, and the immune system of older adult individuals exhibits distinct functional characteristics compared to that of young adults. Notably, most prior investigations into sepsis and monocyte function failed to stratify patients by age, resulting in a paucity of knowledge regarding monocyte behavior in older adult sepsis patients. In line with recommendations that novel biomarkers should be utilized in conjunction with conventional indicators ( 4 ), this study compared PD-L1 expression levels on the surface of the three major monocyte subtypes to gain deeper insights into this cell population in older adult Chinese sepsis patients. Materials and methods 2.1 Study subjects and healthy controls The participants recruited for this study presented to the emergency departments (EDs) of two distinct hospitals, which reported annual ED visit volumes of roughly 250,000 and 200,000 cases, respectively. Eligible subjects were all aged 65 years or older and diagnosed with sepsis in accordance with the 2016 International Sepsis-3 Diagnostic Criteria ( 8 ). For the sake of clinical standardization, organ dysfunction was defined as an elevation of the Sequential Organ Failure Assessment (SOFA) score by no less than 2 points. Clinically, septic shock was identified by the necessity of vasopressor administration to sustain a mean arterial pressure of ≥ 65 mmHg, accompanied by a plasma lactate concentration exceeding 2 mmol/L (> 18 mg/dL), in the absence of hypovolemia. The exclusion criteria included the following: mortality within 48 hours after sepsis onset; sepsis-related manifestations emerging more than 72 hours prior to hospital admission; presence of congenital or acquired immunodeficiency disorders; chronic administration of corticosteroids or other immunosuppressive agents; comorbidities of human immunodeficiency virus (HIV) infection or malignant neoplasms; positive findings on coronavirus disease 2019 (COVID-19) antigen and/or nucleic acid detection assays; and refusal of study participation. The healthy control group was recruited from the physical examination centre of the two participating hospitals. Individuals with coronary heart disease, diabetes mellitus, hypertension, other severe systemic diseases affecting the heart, brain, lungs, liver or kidneys, or those who declined study participation were excluded from the control group. 2.2 Data collection Venous blood specimens were obtained from enrolled patients within 24 hours of meeting the diagnostic criteria for sepsis. The baseline clinical characteristics of patients, encompassing age, gender, and results of laboratory tests, were systematically documented following the onset of sepsis. The SOFA score was determined on the basis of relevant clinical findings and demographic data. The 28-day clinical outcome (survival or mortality) was ascertained during the scheduled follow-up period. For healthy control subjects, blood samples were procured at the time of their attendance at the physical examination centre. This study was performed in adherence to the principles of the Declaration of Helsinki and was approved by the institutional review boards of the two participating hospitals (ethics approval number: 2021 − 686, sjtkyll-lx-2020( 8 )). Written informed consent was provided by all study participants prior to their enrolments. 2.3 Flow cytometry Whole blood analyses were conducted within 2 hours of collecting peripheral blood into ethylenediaminetetraacetic acid (EDTA)-anticoagulated tubes, using human-specific monoclonal antibodies targeting CD45 (Clone HI30), CD14 (Clone M5E2), CD16 (Clone 3G8), and CD274 (Clone MIH1), alongside isotype-matched control antibodies. All antibodies were pre-titered and optimized based on the conjugated fluorophore. Cells were stained on ice in the dark for 30 minutes and subsequently washed twice. A minimum of 10,000 monocyte events were acquired using a BD FACS Aria II flow cytometer. Monocyte gating was performed based on forward scatter, side scatter, and positive expression of CD14 and CD16, with gating thresholds calibrated against isotype-matched control staining. Single-cell gating was achieved by plotting forward scatter area (FSC-A) versus forward scatter height (FSC-H). Results were expressed as percentages and mean fluorescence intensities. Data analysis was carried out using FlowJo software (Version 10.0.8; Tree Star, Ashland, OR, USA). 2.5 Statistical analysis Normally distributed data are expressed as mean ± standard deviation, and non-normally distributed data as median (interquartile range). Baseline characteristics of the patient cohort and healthy controls were compared using independent-samples t-tests, Mann-Whitney U tests, and chi-square tests, as deemed appropriate. Among group comparisons of monocyte subset proportions and PD-L1 expression levels on distinct monocyte subsets were performed using the Mann-Whitney U test. Binary logistic regression analysis was employed to identify variables independently associated with severity in sepsis patients. The area under curve (AUC) of the receiver operating characteristic (ROC) curve was calculated to assess the predictive efficacy of relevant parameters for sepsis shock in this sepsis population. All statistical tests were two-tailed, with statistical significance established at a P value < 0.05. All data analyses were conducted using SPSS software (Version 27.0). Results 3.1 Patient clinical baseline characteristics A total of 80 patients were enrolled in this study following the screening of 146 Han Chinese patients aged ≥ 65 years with sepsis between October 2021 and October 2022 (Fig. 1 ). Based on disease severity, these 80 patients were further categorized into two subgroups: 27 cases with septic shock and 53 cases with uncomplicated sepsis (without shock). Forty sex-, age-, and race-matched healthy volunteers were recruited from a routine health check-up center for inclusion in the present study. Detailed demographic and clinical characteristics of the enrolled patients are summarized in Table 1 . Elevated SOFA scores in patients with septic shock reflected a more severe disease phenotype. Moreover, the 28-day mortality rate was notably higher in the septic shock subgroup compared with the non-shock sepsis subgroup. Although concentrations of conventional clinical inflammatory biomarkers (i.e., PCT and CRP) were numerically elevated in the septic shock cohort relative to the non-shock cohort, these differences did not reach statistical significance in our study. Furthermore, no statistically significant intergroup differences were observed in terms of age, sex distribution, peripheral blood leukocyte count, or monocyte count. Table 1 Baseline characteristics of all the enrollments Sepsis with older adult Septic shock Septic (n = 27) (n = 53) P value Controls (n = 40) Age (yrs) Male, n (%) WBC (ⅹ10^9/L) M (ⅹ10^9/L) MP (%) PCT (ng/ml) CRP (mg/L) ESR (mm/h) SOFA score 28-day mortality 80.00±8.38 17(60.7) 11.86(6.92,16.36) 0.43(0.23,0.61) 4.60(2.03,6.78) 18.73±41.44 141.25±90.52 52.00±32.79 12.17±1.49 9(33.3) 81.10±8.59 26(50) 11.61(7.24,17.62) 0.46(0.33,0.76) 4.50(2.20,6.15) 13.50±24.00 120.59±77.48 53.38±32.88 6.33±2.46 3(5.66) 0.085 0.512 0.526 0.410 0.438 0.076 0.094 0.135 0.001 0.003 76±5.75 24(40) / / / / / / / Data are expressed as mean ± SD, median (Q1, Q3), number (%); WBC white blood cell count; M blood monocyte count; MP blood monocyte percentage; PCT procalcitonin; CRP C reactive protein; ESR erythrocyte sedimentation rate; SOFA sequential organ failure assessment; 3.2 PD-L1 expression on different monocyte subtypes between groups Peripheral blood monocyte subsets were categorized as M1(CD14 + + CD16−), M2 (CD14 + + CD16+), and M3 (CD14 + CD16++) based on the surface expression of CD14 and CD16 molecules. We found that the percentage of M1 monocyte was higher in septic shock group and in 28-day death group comparing to septic group and 28-day survival group, respectively [68.8% (50.7%, 77.8%) vs. 40.8% (19.7%, 70.7%), p = 0.011; 70.9% (49.4%,76.9%) vs 54.3% (22.2%, 74.7%), P = 0.038] (Fig. 2 A). The proportion of M3 monocytes was significantly higher in sepsis patients than in healthy controls [3.2% (1.6%, 5.8%) vs. 1.8% (0.8%, 4.5%); p = 0.034] (Fig. 2 C). There were no disparity among the other groups on the three subsets monocyte nevertheless. PD-L1 expression on M1 monocyte was lower in septic shock group compared to septic group [1.19% (0.69%, 2.42%) vs. 1.96% (0.65%, 4.10%), p = 0.012]. But, PD-L1 expression on M1 monocyte among patients and controls group, 28-day survival and 28-day death group shown no significant differences. The PD-L1 expression on M2, M3 monocyte also exhibited no significant differences. Detailed data were presented in Fig. 3 . 3.3 The association between PD-L1 expression on M1 monocyte and septic shock in patients with older adult population In the univariate analyses, we have shown that the proportion of M1 monocyte, PD-L1 expression on M1 monocyte exhibited significant difference between the septic shock group and that without shock group. In the following multivariate logistic regression analysis, PD-L1 expression on M1 monocyte (β = -0.612, OR = 0.542, CI: 0.324, 0.907, p = 0.020) and SOFA score (β = 1.366, OR = 3.919, CI: 1.893, 8.114, p = 0.000) still exhibited significant effect in predicating septic shock. While, we had not found any significant effect for predicating septic shock with the percentage of M1 monocyte (Table 2 ). Table 2 Logistic Regression-Based Analysis of Independent Determinants of Septic Shock variable β SE Wald P value Odds ratio 95% confidence interval for EXP(B) Lower limit Upper limit M1 monocyte PD-L1 expression on M1 monocyte SOFA constant 0.018 -0.612 1.366 -12.097 0.020 0.263 0.371 3.461 0.844 5.429 13.537 12.216 0.358 0.020 0.000 0.000 1.019 0.542 3.919 0.000 0.979 1.060 0.324 0.907 1.893 8.114 PD-L1 programmed cell death receptor ligand-1; M1 CD14 + + CD16 − monocyte; SOFA sequential organ failure assessment; The ROC curve analysis demonstrated that the AUC value for PD-L1 expression on M1 monocytes in predicting septic shock was 0.689 (p = 0.006), whereas the AUC value corresponding to SOFA score was 0.781 (p < 0.001). Furthermore, the AUC derived from the combination of PD-L1 expression percentage on M1 monocytes and the SOFA score reached 0.826 (p < 0.001), a value superior to that of either individual parameter. Detailed data pertaining to these ROC curve analyses are depicted in Fig. 4 . Discussion Impaired pro-inflammatory cytokine release capacity of monocytes from patients with sepsis in response to endotoxin (lipopolysaccharide, LPS), other Toll-like receptor (TLR) agonists, and various other bacterial compounds constitutes a key hallmark of the immune dysfunction associated with sepsis ( 2 , 3 ). CD14 + + CD16 − monocytes represent the dominant subset in healthy individuals( 8 ). The majority of evidence indicates that these cells exhibit a pro-inflammatory phenotype, attributable to their robust capacity to secrete pro-inflammatory cytokines in response to microbial challenge( 9 ). Studies had shown that the proportion of classical monocytes (CD14 + + CD16−) exhibited a decreased tendency in the older adult population( 10 ). Transcriptomic analysis further suggested that CD14 + + CD16 − monocytes exhibit age-associated decline in proliferative capacity( 11 ). At present, it was generally believed that immune function was impaired with the increasing of age. Immunosenescence was associated with aging which was charactered with immune dysfunction and gradual deterioration of the immune system( 12 ). Senescent cells are capable of secreting copious amounts of proinflammatory cytokines, which initiate inflammatory responses and remodel the tissue microenvironment( 13 ). Accumulating evidence indicates that senescent cells persist and accumulate without efficient immune surveillance and clearance during the aging process, thereby exacerbating inflammatory states and contributing to the development of multiple age-related disorders.( 14 , 15 ). The PD-1/PD-L1 signaling pathway playd a critical role in autoimmune diseases, infectious diseases, tumor immunity, and drug resistance mechanisms( 16 ). PD-L1 was up expressed in natural aging( 17 ). The senescence-associated secretory phenotype, characterized by the secretion of a large amount of proinflammatory cytokines, chemokines induced the PD-L1 upregulation by several mechanism such as NF-kB and p38 MAPK pathways( 2 , 18 , 19 ). The upregulating PD-L1 may create an overall immunosuppressive environment that inhibited immune-mediated clearance of damaged cell( 20 ), therefore worsen the sepsis. And report shown that senescence and aging were associated with upregulation of PD-L1( 17 ). This can explain why older adult sepsis patients who had elevated expression of PD-L1 on CD14 + + CD16 − monocytes were prone to have adverse outcomes, such as septic shock in our study. Aging status secreted a large array of inflammatory cytokines that triggered inflammation response and altered tissue microenvironment( 13 ). Study showed that the anti-PD-L1 therapy markedly decreased the level of pro and anti-inflammatory cytokines such as interleukin-6 and interleukin-10 in sepsis mice and the survival rate of sepsis model mice was significantly improved by anti-PD-L1 antibody treatment( 16 ). These was not only a new predictive indicator for the early prognosis of older adult patients with sepsis, but also provided a new inspiration for the early treatment of sepsis in older adult patients. Limitations The present study has certain limitations that warrant acknowledgment. First, the relatively small sample size may restrict the generalizability of the findings, as the results might not fully reflect the broader older adult sepsis population. Accordingly, future investigations should expand the sample size to enhance statistical power and improve external validity. Second, the current study focused on the prognostic significance of early-phase PD-L1 expression on monocytes in older adult sepsis patients. Notably, additional data regarding the dynamic alterations in monocyte PD-L1 expression over time are needed to better mirror the real-world clinical course of sepsis in this the older adult group. Conclusions Monocytes and their various subtypes, as important immune cells, have long been regarded as playing a crucial role in the development of sepsis. This is the first study to investigate the association between early PD-L1 expression on monocyte subsets and prognosis in older adult Chinese Han patients with sepsis. As population aging intensifies, the early diagnosis of sepsis in older adult patients presents a major clinical challenge for clinicians worldwide. PD-L1 expression on monocyte subsets may serve as a novel prognostic biomarker for sepsis in the older adult patients and offer new insights to inform the development of targeted therapeutic strategies. Abbreviations PD-L1 programmed cell death receptor ligand-1 AUC aera under the curve ROC receiver operating characteristic IL interleukin TNF tumor necrosis factor PD-1 programmed cell death receptor-1 ED emergency department SOFA sequential organ failure assessment HIV human immunodeficiency virus COVID-19 coronavirus disease 2019 EDTA ethylenediaminetetraacetic acid PCT procalcitonin CRP C reactive protein ESR erythrocyte sedimentation rate Declarations Conflict of Interest All authors declare no financial or non-financial competing interests. Funding: This work was supported by Research Open Project of Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation (2020XFN-KFKT-01) Author Contribution QG and TCY designed the study. BBL acquired the data. QG and LY performed the analysis and interpretation of data. QG and BBL wrote the manuscript. TCY and SBG revised the manuscript. Acknowledgement: We are grateful to Melissa Crawford, PhD, of Liwen Bianji (Edanz) ( www.liwenbianji.cn/ ), for her professional English language editing of the draft version of this manuscript. Data Availability The data that support the findings of this study are available from ResMan (http:// www. medre sman. org. cn/ login. aspx) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of ResMan. References Hotchkiss RS, Monneret G, Payen D. Sepsis-induced immunosuppression: from cellular dysfunctions to immunotherapy. Nat Rev Immunol. 2013;13(12):862–74. http://dx.doi.org/10.1038/nri3552 Cavaillon JM, Adib-Conquy M. Bench-to-bedside review: endotoxin tolerance as a model of leukocyte reprogramming in sepsis. Crit Care. 2006;10(5):233. http://dx.doi.org/10.1186/cc5055 Biswas SK, Lopez-Collazo E. 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Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 12 May, 2026 Reviewers agreed at journal 27 Apr, 2026 Reviewers invited by journal 27 Apr, 2026 Editor assigned by journal 18 Mar, 2026 Submission checks completed at journal 01 Mar, 2026 First submitted to journal 26 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8975708","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":630519620,"identity":"4d5400ee-2825-47f0-92dd-170130e7bd5d","order_by":0,"name":"Qian Gao","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Gao","suffix":""},{"id":630519621,"identity":"ac4c024c-ee52-42d4-b3f4-af65c06ce1f1","order_by":1,"name":"Beibei Liu","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Beibei","middleName":"","lastName":"Liu","suffix":""},{"id":630519622,"identity":"e8a868a0-1b30-4d8e-9ade-1751a3d1dcfc","order_by":2,"name":"Li Yang","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Yang","suffix":""},{"id":630519623,"identity":"e6fd5d75-2b12-410b-8f23-fd4d35a56e7e","order_by":3,"name":"Tiecheng Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIie3RMUvEMBTA8ZQHuSVp15Qb9CMECsGhtB/EpVLoVOUm6dChINTxVkc/QsEvUHlwLtWuN9xQl8PhhsqB42FVxFuacxTMj4zvD8kLIYbxF8Hn+WL12S5wALDTFWw/AdHUsXtNE6lNyF5CeFlbVcuOhS4JJ3C/nWWroHp4xBe3XIGHjEiS+6fjF6Px9KZZx1VzkZzMnta2Ql53ZJGcF6MJU8BLjGWdKikuARTakbQK1CTOG/DdkLQbJRkF6+6KSaFPhjFeYCCXqdexEq0KDiVIvSlbYOQuN2pYchILHJYcad4ymePzluUY2m3qvfaZHzhzxK7P/dHk29ltTejPd0QHxj+ERwWB/heDhmEY/9A7inpbIi9TmFsAAAAASUVORK5CYII=","orcid":"","institution":"Capital Medical University","correspondingAuthor":true,"prefix":"","firstName":"Tiecheng","middleName":"","lastName":"Yang","suffix":""},{"id":630519624,"identity":"4290e593-0f8f-4650-b157-351c3f0714e7","order_by":4,"name":"Shubin Guo","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shubin","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2026-02-26 09:08:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8975708/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8975708/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108940444,"identity":"035584d2-1741-4dd9-b9af-7b8dab04e77d","added_by":"auto","created_at":"2026-05-11 05:13:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":226724,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram depicting the enrolment of patients and controls, with detailed reasons for exclusion provided.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8975708/v1/922fba06f187b48e865ebc8b.png"},{"id":108977213,"identity":"ebf16652-633b-4954-987b-9ce5f6befe1c","added_by":"auto","created_at":"2026-05-11 11:30:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":150887,"visible":true,"origin":"","legend":"\u003cp\u003ePeripheral blood monocyte subsets distribution in different comparison groups. Panels 2a, 2b, and 2c illustrate MO1 (CD14++CD16−), MO2 (CD14++CD16+), and MO3 (CD14+CD16++) monocytes, respectively, in the following comparison groups: patients vs. controls, septic shock vs. sepsis without shock, and 28-day survival and 28-day death groups. Percentage of M1 monocyte was significant different among septic shock and sepsis without shock, 28-day survival and 28-day death groups [68.8 % (50.7 %, 77.8 %) vs. 40.8 % (19.7 %, 70.7 %), p = 0.011; 70.9% (49.4%,76.9%) vs 54.3% (22.2%, 74.7%), P=0.038]. Percentage of M3 monocytes was significantly higher in sepsis patients than in healthy controls [3.2% (1.6%, 5.8%) vs. 1.8% (0.8%, 4.5%); p = 0.034]. No significant differences were observed in other comparison groups.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8975708/v1/ed3a8b50aa65e2da211773fa.png"},{"id":108940445,"identity":"58d997af-bd1d-4b1f-a344-9e122bf686e5","added_by":"auto","created_at":"2026-05-11 05:13:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":276319,"visible":true,"origin":"","legend":"\u003cp\u003ePD-L1 expression on M1 monocyte in different comparison groups: patients vs. controls, septic shock vs. sepsis without shock [1.19% (0.69%, 2.42%) vs. 1.96% (0.65%, 4.10%), p = 0.012.], and 28-day survival and 28-day death.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8975708/v1/abf1c884ceb0b605df60bfc7.png"},{"id":108940447,"identity":"47aaeda7-99b3-488c-8569-324b240f4430","added_by":"auto","created_at":"2026-05-11 05:13:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":65669,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curve for predicting septic shock in all sepsis patients. Area under the curve (AUC) values: the percentage of PD-L1 expression on M1 monocytes (red line) was 0.689 (p = 0.006); SOFA score (yellow line) was 0.781 (p \u0026lt; 0.001); the combination of PD-L1 expression percentage on M1 monocytes and the SOFA score (green line) was 0.826 (p \u0026lt; 0.001)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8975708/v1/eb512ab1ed9b8fce21cb6d2f.png"},{"id":108979716,"identity":"9b48aa2f-dfd5-49b9-ac95-243c96053e3b","added_by":"auto","created_at":"2026-05-11 12:00:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":887286,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8975708/v1/93cfd7c1-e828-4bb3-ac32-9c1a869c50cc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Early expression of PD-L1 on monocyte is a predictor for severity in older adult sepsis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSepsis represents a life-threatening infectious condition accompanied by varying degrees of organ dysfunction, arising from a complex interplay between the host's pro-inflammatory and anti-inflammatory responses(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Monocytes isolated from sepsis patients display a reduced ability to secrete pro-inflammatory mediators, including interleukin (IL)-1α, IL-6, and tumour necrosis factor (TNF)-α. In contrast, the production of anti-inflammatory cytokines such as IL-10 and IL-1 receptor antagonist\u0026mdash;remains unimpaired or even elevated, a key hallmark of sepsis-associated immunosuppression(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Human peripheral blood monocytes constitute a heterogeneous cell population, which can be categorized into three distinct subtypes based on the expression patterns of CD14 (a lipopolysaccharide receptor) and CD16 (the FcγIII receptor) on their cell membranes(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). According to this classification system, monocytes are divided into: \"classical monocytes\" with high CD14 expression and no CD16 expression (CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16\u0026minus;); \"intermediate monocytes\" that co-express both receptors (CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16+); and \"nonclassical monocytes\" characterized by predominant CD16 expression (CD14\u0026thinsp;+\u0026thinsp;CD16++)(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Previous studies have indicated that the immunosuppressive phase of sepsis is typified by increased anti-inflammatory cytokine synthesis and decreased expression of human leukocyte antigen-DR (HLA-DR)(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Additionally, programmed cell death receptor-1 (PD-1) and its ligand PD-L1 co-inhibitory receptor molecules exert crucial regulatory effects on sepsis-induced immunosuppression (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe global aging population is expanding at an alarming rate, and the immune system of older adult individuals exhibits distinct functional characteristics compared to that of young adults. Notably, most prior investigations into sepsis and monocyte function failed to stratify patients by age, resulting in a paucity of knowledge regarding monocyte behavior in older adult sepsis patients. In line with recommendations that novel biomarkers should be utilized in conjunction with conventional indicators (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), this study compared PD-L1 expression levels on the surface of the three major monocyte subtypes to gain deeper insights into this cell population in older adult Chinese sepsis patients.\u003c/p\u003e"},{"header":"Materials and methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study subjects and healthy controls\u003c/h2\u003e \u003cp\u003eThe participants recruited for this study presented to the emergency departments (EDs) of two distinct hospitals, which reported annual ED visit volumes of roughly 250,000 and 200,000 cases, respectively. Eligible subjects were all aged 65 years or older and diagnosed with sepsis in accordance with the 2016 International Sepsis-3 Diagnostic Criteria (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). For the sake of clinical standardization, organ dysfunction was defined as an elevation of the Sequential Organ Failure Assessment (SOFA) score by no less than 2 points. Clinically, septic shock was identified by the necessity of vasopressor administration to sustain a mean arterial pressure of \u0026ge;\u0026thinsp;65 mmHg, accompanied by a plasma lactate concentration exceeding 2 mmol/L (\u0026gt;\u0026thinsp;18 mg/dL), in the absence of hypovolemia. The exclusion criteria included the following: mortality within 48 hours after sepsis onset; sepsis-related manifestations emerging more than 72 hours prior to hospital admission; presence of congenital or acquired immunodeficiency disorders; chronic administration of corticosteroids or other immunosuppressive agents; comorbidities of human immunodeficiency virus (HIV) infection or malignant neoplasms; positive findings on coronavirus disease 2019 (COVID-19) antigen and/or nucleic acid detection assays; and refusal of study participation.\u003c/p\u003e \u003cp\u003eThe healthy control group was recruited from the physical examination centre of the two participating hospitals. Individuals with coronary heart disease, diabetes mellitus, hypertension, other severe systemic diseases affecting the heart, brain, lungs, liver or kidneys, or those who declined study participation were excluded from the control group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data collection\u003c/h2\u003e \u003cp\u003eVenous blood specimens were obtained from enrolled patients within 24 hours of meeting the diagnostic criteria for sepsis. The baseline clinical characteristics of patients, encompassing age, gender, and results of laboratory tests, were systematically documented following the onset of sepsis. The SOFA score was determined on the basis of relevant clinical findings and demographic data. The 28-day clinical outcome (survival or mortality) was ascertained during the scheduled follow-up period. For healthy control subjects, blood samples were procured at the time of their attendance at the physical examination centre. This study was performed in adherence to the principles of the Declaration of Helsinki and was approved by the institutional review boards of the two participating hospitals (ethics approval number: 2021\u0026thinsp;\u0026minus;\u0026thinsp;686, sjtkyll-lx-2020(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)). Written informed consent was provided by all study participants prior to their enrolments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Flow cytometry\u003c/h2\u003e \u003cp\u003eWhole blood analyses were conducted within 2 hours of collecting peripheral blood into ethylenediaminetetraacetic acid (EDTA)-anticoagulated tubes, using human-specific monoclonal antibodies targeting CD45 (Clone HI30), CD14 (Clone M5E2), CD16 (Clone 3G8), and CD274 (Clone MIH1), alongside isotype-matched control antibodies. All antibodies were pre-titered and optimized based on the conjugated fluorophore. Cells were stained on ice in the dark for 30 minutes and subsequently washed twice. A minimum of 10,000 monocyte events were acquired using a BD FACS Aria II flow cytometer. Monocyte gating was performed based on forward scatter, side scatter, and positive expression of CD14 and CD16, with gating thresholds calibrated against isotype-matched control staining. Single-cell gating was achieved by plotting forward scatter area (FSC-A) versus forward scatter height (FSC-H). Results were expressed as percentages and mean fluorescence intensities. Data analysis was carried out using FlowJo software (Version 10.0.8; Tree Star, Ashland, OR, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eNormally distributed data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and non-normally distributed data as median (interquartile range). Baseline characteristics of the patient cohort and healthy controls were compared using independent-samples t-tests, Mann-Whitney U tests, and chi-square tests, as deemed appropriate. Among group comparisons of monocyte subset proportions and PD-L1 expression levels on distinct monocyte subsets were performed using the Mann-Whitney U test. Binary logistic regression analysis was employed to identify variables independently associated with severity in sepsis patients. The area under curve (AUC) of the receiver operating characteristic (ROC) curve was calculated to assess the predictive efficacy of relevant parameters for sepsis shock in this sepsis population. All statistical tests were two-tailed, with statistical significance established at a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All data analyses were conducted using SPSS software (Version 27.0).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Patient clinical baseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 80 patients were enrolled in this study following the screening of 146 Han Chinese patients aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years with sepsis between October 2021 and October 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Based on disease severity, these 80 patients were further categorized into two subgroups: 27 cases with septic shock and 53 cases with uncomplicated sepsis (without shock). Forty sex-, age-, and race-matched healthy volunteers were recruited from a routine health check-up center for inclusion in the present study. Detailed demographic and clinical characteristics of the enrolled patients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Elevated SOFA scores in patients with septic shock reflected a more severe disease phenotype. Moreover, the 28-day mortality rate was notably higher in the septic shock subgroup compared with the non-shock sepsis subgroup. Although concentrations of conventional clinical inflammatory biomarkers (i.e., PCT and CRP) were numerically elevated in the septic shock cohort relative to the non-shock cohort, these differences did not reach statistical significance in our study. Furthermore, no statistically significant intergroup differences were observed in terms of age, sex distribution, peripheral blood leukocyte count, or monocyte count.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of all the enrollments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSepsis with older adult\u003c/p\u003e \u003cp\u003eSeptic shock Septic\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;27) (n\u0026thinsp;=\u0026thinsp;53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (yrs)\u003c/p\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003cp\u003eWBC (ⅹ10^9/L)\u003c/p\u003e \u003cp\u003eM (ⅹ10^9/L)\u003c/p\u003e \u003cp\u003eMP (%)\u003c/p\u003e \u003cp\u003ePCT (ng/ml)\u003c/p\u003e \u003cp\u003eCRP (mg/L)\u003c/p\u003e \u003cp\u003eESR (mm/h)\u003c/p\u003e \u003cp\u003eSOFA score\u003c/p\u003e \u003cp\u003e28-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.00\u0026plusmn;8.38\u003c/p\u003e \u003cp\u003e17(60.7)\u003c/p\u003e \u003cp\u003e11.86(6.92,16.36)\u003c/p\u003e \u003cp\u003e0.43(0.23,0.61)\u003c/p\u003e \u003cp\u003e4.60(2.03,6.78)\u003c/p\u003e \u003cp\u003e18.73\u0026plusmn;41.44\u003c/p\u003e \u003cp\u003e141.25\u0026plusmn;90.52\u003c/p\u003e \u003cp\u003e52.00\u0026plusmn;32.79\u003c/p\u003e \u003cp\u003e12.17\u0026plusmn;1.49\u003c/p\u003e \u003cp\u003e9(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.10\u0026plusmn;8.59\u003c/p\u003e \u003cp\u003e26(50)\u003c/p\u003e \u003cp\u003e11.61(7.24,17.62)\u003c/p\u003e \u003cp\u003e0.46(0.33,0.76)\u003c/p\u003e \u003cp\u003e4.50(2.20,6.15)\u003c/p\u003e \u003cp\u003e13.50\u0026plusmn;24.00\u003c/p\u003e \u003cp\u003e120.59\u0026plusmn;77.48\u003c/p\u003e \u003cp\u003e53.38\u0026plusmn;32.88\u003c/p\u003e \u003cp\u003e6.33\u0026plusmn;2.46\u003c/p\u003e \u003cp\u003e3(5.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003cp\u003e0.512\u003c/p\u003e \u003cp\u003e0.526\u003c/p\u003e \u003cp\u003e0.410\u003c/p\u003e \u003cp\u003e0.438\u003c/p\u003e \u003cp\u003e0.076\u003c/p\u003e \u003cp\u003e0.094\u003c/p\u003e \u003cp\u003e0.135\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76\u0026plusmn;5.75\u003c/p\u003e \u003cp\u003e24(40)\u003c/p\u003e \u003cp\u003e/\u003c/p\u003e \u003cp\u003e/\u003c/p\u003e \u003cp\u003e/\u003c/p\u003e \u003cp\u003e/\u003c/p\u003e \u003cp\u003e/\u003c/p\u003e \u003cp\u003e/\u003c/p\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, median (Q1, Q3), number (%); WBC white blood\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003ecell count; M blood monocyte count; MP blood monocyte percentage; PCT procalcitonin; CRP C reactive protein; ESR erythrocyte sedimentation rate; SOFA sequential organ failure assessment;\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 PD-L1 expression on different monocyte subtypes between groups\u003c/h2\u003e \u003cp\u003ePeripheral blood monocyte subsets were categorized as M1(CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16\u0026minus;), M2 (CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16+), and M3 (CD14\u0026thinsp;+\u0026thinsp;CD16++) based on the surface expression of CD14 and CD16 molecules. We found that the percentage of M1 monocyte was higher in septic shock group and in 28-day death group comparing to septic group and 28-day survival group, respectively [68.8% (50.7%, 77.8%) vs. 40.8% (19.7%, 70.7%), p\u0026thinsp;=\u0026thinsp;0.011; 70.9% (49.4%,76.9%) vs 54.3% (22.2%, 74.7%), P\u0026thinsp;=\u0026thinsp;0.038] (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The proportion of M3 monocytes was significantly higher in sepsis patients than in healthy controls [3.2% (1.6%, 5.8%) vs. 1.8% (0.8%, 4.5%); p\u0026thinsp;=\u0026thinsp;0.034] (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). There were no disparity among the other groups on the three subsets monocyte nevertheless.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePD-L1 expression on M1 monocyte was lower in septic shock group compared to septic group [1.19% (0.69%, 2.42%) vs. 1.96% (0.65%, 4.10%), p\u0026thinsp;=\u0026thinsp;0.012]. But, PD-L1 expression on M1 monocyte among patients and controls group, 28-day survival and 28-day death group shown no significant differences. The PD-L1 expression on M2, M3 monocyte also exhibited no significant differences. Detailed data were presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.3 The association between PD-L1 expression on M1 monocyte and septic shock in patients with older adult population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the univariate analyses, we have shown that the proportion of M1 monocyte, PD-L1 expression on M1 monocyte exhibited significant difference between the septic shock group and that without shock group. In the following multivariate logistic regression analysis, PD-L1 expression on M1 monocyte (β = -0.612, OR\u0026thinsp;=\u0026thinsp;0.542, CI: 0.324, 0.907, p\u0026thinsp;=\u0026thinsp;0.020) and SOFA score (β\u0026thinsp;=\u0026thinsp;1.366, OR\u0026thinsp;=\u0026thinsp;3.919, CI: 1.893, 8.114, p\u0026thinsp;=\u0026thinsp;0.000) still exhibited significant effect in predicating septic shock. While, we had not found any significant effect for predicating septic shock with the percentage of M1 monocyte (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic Regression-Based Analysis of Independent Determinants of Septic Shock\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003evariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% confidence interval for EXP(B)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLower limit Upper limit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM1 monocyte\u003c/p\u003e \u003cp\u003ePD-L1 expression on M1 monocyte\u003c/p\u003e \u003cp\u003eSOFA\u003c/p\u003e \u003cp\u003econstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003cp\u003e-0.612\u003c/p\u003e \u003cp\u003e1.366\u003c/p\u003e \u003cp\u003e-12.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003cp\u003e0.263\u003c/p\u003e \u003cp\u003e0.371\u003c/p\u003e \u003cp\u003e3.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003cp\u003e5.429\u003c/p\u003e \u003cp\u003e13.537\u003c/p\u003e \u003cp\u003e12.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003cp\u003e0.020\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003cp\u003e0.542\u003c/p\u003e \u003cp\u003e3.919\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.979 1.060\u003c/p\u003e \u003cp\u003e0.324 0.907\u003c/p\u003e \u003cp\u003e1.893 8.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ePD-L1 programmed cell death receptor ligand-1; M1 CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16\u0026thinsp;\u0026minus;\u0026thinsp;monocyte; SOFA sequential organ failure assessment;\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe ROC curve analysis demonstrated that the AUC value for PD-L1 expression on M1 monocytes in predicting septic shock was 0.689 (p\u0026thinsp;=\u0026thinsp;0.006), whereas the AUC value corresponding to SOFA score was 0.781 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, the AUC derived from the combination of PD-L1 expression percentage on M1 monocytes and the SOFA score reached 0.826 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), a value superior to that of either individual parameter. Detailed data pertaining to these ROC curve analyses are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eImpaired pro-inflammatory cytokine release capacity of monocytes from patients with sepsis in response to endotoxin (lipopolysaccharide, LPS), other Toll-like receptor (TLR) agonists, and various other bacterial compounds constitutes a key hallmark of the immune dysfunction associated with sepsis (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16\u0026thinsp;\u0026minus;\u0026thinsp;monocytes represent the dominant subset in healthy individuals(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The majority of evidence indicates that these cells exhibit a pro-inflammatory phenotype, attributable to their robust capacity to secrete pro-inflammatory cytokines in response to microbial challenge(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Studies had shown that the proportion of classical monocytes (CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16\u0026minus;) exhibited a decreased tendency in the older adult population(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Transcriptomic analysis further suggested that CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16\u0026thinsp;\u0026minus;\u0026thinsp;monocytes exhibit age-associated decline in proliferative capacity(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). At present, it was generally believed that immune function was impaired with the increasing of age. Immunosenescence was associated with aging which was charactered with immune dysfunction and gradual deterioration of the immune system(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Senescent cells are capable of secreting copious amounts of proinflammatory cytokines, which initiate inflammatory responses and remodel the tissue microenvironment(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Accumulating evidence indicates that senescent cells persist and accumulate without efficient immune surveillance and clearance during the aging process, thereby exacerbating inflammatory states and contributing to the development of multiple age-related disorders.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe PD-1/PD-L1 signaling pathway playd a critical role in autoimmune diseases, infectious diseases, tumor immunity, and drug resistance mechanisms(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). PD-L1 was up expressed in natural aging(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The senescence-associated secretory phenotype, characterized by the secretion of a large amount of proinflammatory cytokines, chemokines induced the PD-L1 upregulation by several mechanism such as NF-kB and p38 MAPK pathways(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The upregulating PD-L1 may create an overall immunosuppressive environment that inhibited immune-mediated clearance of damaged cell(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), therefore worsen the sepsis. And report shown that senescence and aging were associated with upregulation of PD-L1(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). This can explain why older adult sepsis patients who had elevated expression of PD-L1 on CD14\u0026thinsp;+\u0026thinsp;+\u0026thinsp;CD16\u0026thinsp;\u0026minus;\u0026thinsp;monocytes were prone to have adverse outcomes, such as septic shock in our study. Aging status secreted a large array of inflammatory cytokines that triggered inflammation response and altered tissue microenvironment(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Study showed that the anti-PD-L1 therapy markedly decreased the level of pro and anti-inflammatory cytokines such as interleukin-6 and interleukin-10 in sepsis mice and the survival rate of sepsis model mice was significantly improved by anti-PD-L1 antibody treatment(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). These was not only a new predictive indicator for the early prognosis of older adult patients with sepsis, but also provided a new inspiration for the early treatment of sepsis in older adult patients.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eThe present study has certain limitations that warrant acknowledgment. First, the relatively small sample size may restrict the generalizability of the findings, as the results might not fully reflect the broader older adult sepsis population. Accordingly, future investigations should expand the sample size to enhance statistical power and improve external validity. Second, the current study focused on the prognostic significance of early-phase PD-L1 expression on monocytes in older adult sepsis patients. Notably, additional data regarding the dynamic alterations in monocyte PD-L1 expression over time are needed to better mirror the real-world clinical course of sepsis in this the older adult group.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMonocytes and their various subtypes, as important immune cells, have long been regarded as playing a crucial role in the development of sepsis. This is the first study to investigate the association between early PD-L1 expression on monocyte subsets and prognosis in older adult Chinese Han patients with sepsis. As population aging intensifies, the early diagnosis of sepsis in older adult patients presents a major clinical challenge for clinicians worldwide. PD-L1 expression on monocyte subsets may serve as a novel prognostic biomarker for sepsis in the older adult patients and offer new insights to inform the development of targeted therapeutic strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePD-L1 programmed cell death receptor ligand-1\u003c/p\u003e\n\u003cp\u003eAUC aera under the curve\u003c/p\u003e\n\u003cp\u003eROC receiver operating characteristic\u003c/p\u003e\n\u003cp\u003eIL interleukin\u003c/p\u003e\n\u003cp\u003eTNF tumor necrosis factor\u003c/p\u003e\n\u003cp\u003ePD-1 programmed cell death receptor-1\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eED emergency department\u003c/p\u003e\n\u003cp\u003eSOFA sequential organ failure assessment\u003c/p\u003e\n\u003cp\u003eHIV human immunodeficiency virus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCOVID-19 coronavirus disease 2019\u003c/p\u003e\n\u003cp\u003eEDTA ethylenediaminetetraacetic acid\u003c/p\u003e\n\u003cp\u003ePCT procalcitonin\u003c/p\u003e\n\u003cp\u003eCRP C reactive protein\u003c/p\u003e\n\u003cp\u003eESR erythrocyte sedimentation rate\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003eAll authors declare no financial or non-financial competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by Research Open Project of Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation (2020XFN-KFKT-01)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eQG and TCY designed the study. BBL acquired the data. QG and LY performed the analysis and interpretation of data. QG and BBL wrote the manuscript. TCY and SBG revised the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement:\u003c/h2\u003e \u003cp\u003eWe are grateful to Melissa Crawford, PhD, of Liwen Bianji (Edanz) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.liwenbianji.cn/\u003c/span\u003e\u003cspan address=\"http://www.liwenbianji.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), for her professional English language editing of the draft version of this manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from ResMan (http:// www. medre sman. org. cn/ login. aspx) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of ResMan.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHotchkiss RS, Monneret G, Payen D. Sepsis-induced immunosuppression: from cellular dysfunctions to immunotherapy. Nat Rev Immunol. 2013;13(12):862\u0026ndash;74.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/nri3552\u003c/span\u003e\u003cspan address=\"10.1038/nri3552\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCavaillon JM, Adib-Conquy M. Bench-to-bedside review: endotoxin tolerance as a model of leukocyte reprogramming in sepsis. 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Nature. 2019;566(7742):73\u0026ndash;8.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41586-018-0784-9\u003c/span\u003e\u003cspan address=\"10.1038/s41586-018-0784-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-aging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Aging](https://www.nature.com/npjamd/)","snPcode":"41514","submissionUrl":"https://submission.springernature.com/new-submission/41514/3","title":"npj Aging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"sepsis, sepsis shock, monocyte subsets, PD-L1, aging","lastPublishedDoi":"10.21203/rs.3.rs-8975708/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8975708/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo evaluate the early expression of programmed cell death receptor ligand-1 (PD-L1) on different subtype of monocyte and investigate their relation in term the severity of sepsis in the older adult population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eEighty sepsis patients in older adult and 40 age and sex matched healthy controls were included in this study. The flow cytometry method was used to measure the monocyte subsets and PD-L1 expression on different subsets of monocyte.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePD-L1 expression on M1 monocyte was lower in septic shock group compared to patients without shock [1.19% (0.69%, 2.42%) vs. 1.96% (0.65%, 4.10%), p\u0026thinsp;=\u0026thinsp;0.012]. PD-L1 expression on M1 monocyte (OR\u0026thinsp;=\u0026thinsp;0.542, CI: 0.324, 0.907, p\u0026thinsp;=\u0026thinsp;0.020) still exhibited significant effect in predicating septic shock in logistic regression analysis. The aera under the curve (AUC) from the receiver operating characteristic curve displayed that the of PD-L1 expression on M1 monocyte for predicting septic shock was 0.689 (p\u0026thinsp;=\u0026thinsp;0.006). The AUC for the combined analysis of PD-L1 expression on M1 monocytes and the sequential organ failure assessment score was 0.826 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe PD-L1 expression on M1 monocyte could be a new predictor for the severity of sepsis and provided a new therapeutic breakthrough for sepsis in older adult population.\u003c/p\u003e","manuscriptTitle":"Early expression of PD-L1 on monocyte is a predictor for severity in older adult sepsis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 05:13:03","doi":"10.21203/rs.3.rs-8975708/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-12T15:03:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18590138377343213894930497635282647366","date":"2026-04-27T16:52:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-27T16:49:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-18T16:27:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-02T04:27:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Aging","date":"2026-02-26T08:52:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-aging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Aging](https://www.nature.com/npjamd/)","snPcode":"41514","submissionUrl":"https://submission.springernature.com/new-submission/41514/3","title":"npj Aging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"00b217a2-fbbe-4f65-a43d-aadcce3b074a","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-12T15:03:56+00:00","index":20,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67109886,"name":"Health sciences/Biomarkers"},{"id":67109887,"name":"Health sciences/Diseases"},{"id":67109888,"name":"Biological sciences/Immunology"},{"id":67109889,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-05-11T05:13:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 05:13:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8975708","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8975708","identity":"rs-8975708","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}