Gene expression changes in lymphocytes and monocytes from patients with traumatic brain injury: A prospective case-control study

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Although TBI can induce a decline in immune cell function, the detailed mechanisms remains to be elucidated. This study aimed to characterize the mechanism of immunosuppression caused by TBI using a comprehensive transcriptome analysis of immune cells. Methods Six patients with traumatic brain injury and acute subdural hematoma were admitted to our hospital. We focused on three major subsets of immune cells responsible for the immune response: CD4 + T cells, CD8 + T cells, and monocytes. We evaluated the changes in immune function after injury using comprehensive transcriptome analysis. Blood samples were collected immediately after admission and one week later, and the data were compared with those of healthy volunteers. Results CD4 + and CD8 + T cells decreased over seven days following injury, and a decrease in cell adhesion and endoplasmic reticulum function was observed. The results suggested that the process of protein synthesis from RNA was impaired and that overall cell function was reduced. Monocytes also showed a decrease in endoplasmic reticulum function, but classical and nonclassical monocyte subsets showed an increase in functions related to platelet activation and tissue repair. Conclusions Comprehensive transcriptome analysis confirmed a decrease in endoplasmic reticulum function in CD4 + T cells, CD8 + T cells, and monocytes. This study contributes to the further elucidation of the mechanisms of immunosuppression due to trauma. Health sciences/Diseases Biological sciences/Immunology traumatic brain injury lymphocyte immunity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background In the United States, approximately 2.8 million individuals sustain traumatic brain injuries (TBIs) each year. [ 1 ] Patients with severe TBI frequently develop nosocomial infections, including ventilator-associated pneumonia. [ 2 , 3 ] Therefore, clarifying the mechanism regulating the immune response in patients with TBI may help to improve treatment options. When tissue is injured due to trauma, various antigens and mediators are released. This reaction is sterile, and these factors interact with immune cells to initiate an inflammatory response. [ 4 ] This sort of inflammatory response is known as Systemic Inflammatory Response Syndrome (SIRS), and it is caused by the activation of the innate immune system. [ 5 , 6 ] A compensatory anti-inflammatory response syndrome (CARS) has also been described to occur simultaneously in response to trauma. CARS usually reflects autoimmune suppression caused by serious incidents such as sepsis, burns, and tissue damage. [ 7 ] Excessive or prolonged CARS can induce immunosuppression, which promotes secondary infection and organ dysfunction. [ 8 ] T cells play a major role in the modulation of immunosuppressive mechanisms. In particular, the reduction in CD4 + T cells and the increase in PD-1 expression in CD8 + T cells reflect immune fatigue. [ 7 ] Many studies have reported that T cell function is at its lowest level between a few days and a week after injury. This has been explained by the fact that the compensatory host reaction to strong inflammation is most clearly observed approximately one week after injury. [ 9 ] Besides T cells, monocytes and macrophages mediate immunosuppression, and a trauma-induced inflammasome dysfunction is possibly related to immunosuppression. [ 8 , 10 , 11 ] Furthermore, monocytes modulate immune function and, in the peripheral blood, there are three different monocyte subsets: classical, intermediate, and nonclassical, each of which has different functions that include phagocytosis and inflammation. In particular, non-classical monocytes are believed to have anti-inflammatory effects and to play a role in immunosuppression. [ 10 ] Conventionally, immunosuppression has been evaluated on the basis of changes in the number of immune cells and the amount of cytokine production. [ 12 ] However, the mechanisms and detailed pathology of the decline in functional immune cells remains to be characterized. Recent advances in genome analysis have facilitated comprehensive transcriptome analysis, [ 13 ] whereby trauma-induced changes in RNA expression have been identified. [ 14 , 15 ] Comprehensive transcriptome analysis can potentially provide novel insight into immunosuppressive mechanisms that could not previously be captured by studies focusing exclusively on cytokines or specific genes. Furthermore, functional changes can be monitored even when there is no change in cell numbers. The characterization of the underlying mechanisms and functional changes associated with immunosuppression may lead to treatments capable of preventing it and thus inhibiting secondary infections. Moreover, the monocyte subset known as nonclassical monocytes has anti-inflammatory effects, and elucidating changes in them may lead to the development of a treatment for immunosuppression. However, few transcriptome analyses of the response to TBI have been reported, and there are no available studies on the immune function of patients affected by TBI. In this study, we investigated three cell populations that modulate immune function: CD4 + T cells, CD8 + T cells, and monocytes. Furthermore, monocytes were divided into three subsets (classical, intermediate, and nonclassical), and the changes in each subpopulation within a week from admission, when immunosuppression is thought to occur, were compared. Functional changes in CD4 + T cells, CD8 + T cells, and monocytes were assessed through transcriptome analysis in patients with TBI. Methods Study design and participants We performed a prospective, observational, case-control, single-center study. The study protocol was approved by the Institutional Review Board of the University of Osaka hospital (Approval Number: 885) and complied with the principles of the Declaration of Helsinki. Written informed consent for the collection of blood samples and the use of clinical data was obtained from the patients or their relatives, and from healthy volunteers. In this study, we included patients with isolated TBI that were admitted to our hospital between August 2021 and April 2022 and required emergency neurosurgical surgery for acute subdural hematoma. We defined patients with isolated TBI as those who only presented an injury with an Abbreviated Injury Scale 98 (AIS-98) score equal or above 3 in the head and an AIS-98 score below 3 in areas other than the head. Patients who died within 7 days of admission were excluded from the study. The control population consisted of volunteers enrolled via public poster advertisements. Sample collection and clinical data Samples from the patients were collected at two time points: within 24 h of admission and on the 7th day after admission (Fig. 1 -a). Blood samples were stored at − 80°C until analysis. The clinical data collected by the investigators from the electronic medical records of the patients included age, sex, Glasgow Coma Scale (GCS) score at admission, site and AIS of whole-body trauma, Injury Severity Score (ISS), type of neurosurgical surgery, presence or absence of tracheotomy, duration of mechanical ventilation, presence or absence of nosocomial infection, and Glasgow Outcome Scale (GOS) score at discharge. The following blood parameters were determined from blood samples collected immediately after admission: fibrinogen, prothrombin time-international normalized ratio, activated partial thromboplastin time, fibrinogen degradation products, and D-dimer. Pneumonia, a nosocomial infection, was diagnosed as hospital-acquired pneumonia based on standard clinical and radiological imaging diagnoses. [ 16 ] Isolation of peripheral blood mononuclear cells Peripheral blood mononuclear cells (PBMCs) were isolated from fresh whole blood collected in heparin-coated tubes by density gradient centrifugation using Leucosep (Greiner Bio-One, Kremsmünster, Austria) according to the manufacturer’s instructions. Isolated PBMCs were divided in half and stored in CELLBANKER cell freezing medium (Nippon Zenyaku Kogyo Co. Ltd., Fukushima Japan) at − 80°C until use. [ 17 ] One half was sorted using fluorescence-activated cell sorting (FACS), and the number of cells in each subset was quantified. The other half was sorted into subsets, and RNA sequencing was performed (Fig. 1 -b). Fluorescence-activated cell sorting Two panels were used to identify subsets of CD4 + T cells, CD8 + T cells, and monocytes from PBMCs. First, DAPI was used to extract viable cells. Lymphocytes and CD3 + cells were extracted. Positive subsets for the CD4 and CD8 markers were defined as CD4 + and CD8 + T cells. Monocytes were extracted from the second panel. DAPI was used for the extraction of viable cells, and three subsets (classical, intermediate, and non-classical) were sorted according to their specific marker expression (CD14 + CD16-, CD14 + CD16+, and CD14lowCD16+, respectively). RNA sequencing and bioinformatics Total RNA was extracted from the sorted cells using QIAzol lysis reagent (Qiagen, Hilden, Germany) according to the manufacturer's protocol. The RNA quantity and integrity were assessed using a NanoDrop One spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Inc, Santa Clara, CA, USA). RNA sequencing (RNA-seq) libraries were prepared using a TruSeq stranded mRNA sample preparation kit (Illumina, San Diego, CA, USA) following the manufacturer's instructions. Whole-transcriptome sequencing was performed on an Illumina NovaSeq 6000 platform using a 101-base pair-end sequencing strategy. The reads were aligned to the human reference genome (hg19) using TopHat (version 2.1.1). Gene expression was quantified as fragments per kilobase of exon per million mapped fragments using Cufflinks (version 2.2.1). Differential gene expression analysis was conducted using the edgeR package (version 3.19) in R. [ 18 ] Gene Ontology were performed using ClusterProfiler (version 4.4.4). [ 19 ] Statistical analysis Summary data are presented as median (interquartile range [IQR]) for continuous variables and as number (%) for categorical variables. The Mann-Whitney U test was used to evaluate differences between the two groups for continuous variables, and the chi-squared test and Fisher's exact test were used for dichotomous variables. Statistical analysis was performed using commercially available statistical analysis software (JMP pro 16 software, SAS Institute Inc., Cary, NC, USA). A p value < 0.05 was considered statistically significant. Transcriptome analysis Transcriptome analysis was performed for each subpopulation (CD4 + T cells, CD8 + T cells, and monocytes) using PBMC samples from three patients (No. 1, 2, and 3). Transcriptome changes following trauma were evaluated by comparing samples collected within 24 h of hospitalization with those collected on hospitalization days 7 and 8. Next, we evaluated whether there were any differences with samples collected from healthy volunteers. We used PBMC samples from three patients (No. 4, 5, and 6) to further classify the monocytes into three subsets (classical, intermediate, and nonclassical), and performed transcriptome analysis for each subset. Results Participant characteristics Between August 2021 and April 2022, 31 patients with isolated TBI were admitted to our hospital. Of these, seven required emergency neural surgery for acute subdural hematoma. One patient died within 7 days of admission and was excluded from the analysis. Two healthy volunteers participated in the study. The backgrounds of the six patients included in the analysis are shown in Table 1 . The median age was 69 years, and three were men (50%). The type of neural surgery was as follows: trepanation in two cases, craniotomy in three cases, and craniectomy in one case. Tracheotomy was performed in three cases, and nosocomial infection occurred in five cases, all of which with a diagnosis of pneumonia. The median GOS at discharge was 3.5 (Table 1 ). The two healthy individuals were a 49-year-old man and a 60-year-old man with no underlying or ongoing disease. Samples from the first three consecutive cases with TBI (Pt. 1, 2, and 3) were used to retrieve CD4 + T cells, CD8 + T cells, and monocytes. Monocytes were further sorted into classical, intermediate, and nonclassical subpopulations using the samples collected from the next three cases (Pt. 4, 5, 6), and an additional analysis was performed. Table 1 Clinicodemographic characteristics of the participants Characteristic Patient No. Median (IQR) 1 2 3 4 5 6 Age, years 62 78 76 31 79 37 69 (35.5–78.3) Sex Female Male Male Male Female Female Admission GCS 3 3 6 6 6 3 4.5 (3–6) AIS-head 5 5 5 3 5 3 5 (3–5) ISS 29 25 25 10 26 9 25 (9.8–26.8) Fibrinogen*, mg/dL 261 361 249 200 211 177 230 (194.3–286.0) PT-INR* 1.11 1.08 1.03 1.01 1.1 0.97 1.1 (1.0–1.1) aPTT*, s 30 26 27 32 29 23 28 (25.3–30.5) FDP*, µg/mL 262.5 4.4 69.9 6.3 134.6 15.8 42.9 (5.8–166.6) D-dimer*, µg/mL 68.25 2.21 20.61 2.24 33.15 4.65 12.6 (2.2–41.9) Types of neurosurgical procedures Craniotomy Craniotomy Craniectomy Trepanation Craniotomy Trepanation Tracheostomy + + + - - - Blood products Fresh Frozen Plasma, units 14 4 10 4 8 4 6 (4–11) Red Cell Concentrate, units 8 4 2 0 2 0 2 (0–5) Platelet Concentrate, units 20 0 0 0 0 0 0 (0–5) Duration of ventilator use, days 13 7 9 8 3 9 8.5 (6–10) Types of nosocomial Pneumonia Pneumonia Pneumonia Pneumonia - Pneumonia GOS at discharge 3 2 2 4 4 4 3.5 (2–4) AIS: Abbreviated Injury Scale, aPTT: activated partial thromboplastin time, FDP: fibrinogen degradation products, GOS: Glasgow Outcome Scale, GCS: Glasgow Coma Scale, IQR: interquartile range, ISS: Injury Severity Score, PT-INR: prothrombin time-international normalized ratio *Parameters reported from blood sample collected at admission. [insert Table 1 here] Fluorescence-activated cell sorting results The proportion of CD4 + T cells among the total viable cells obtained from patients was 25.7% within 24 h of admission, which was similar to that obtained from healthy subjects (27.0%). However, this proportion decreased to 18.4% on days 7–8. In the CD8 + T cell subset, the percentage was 7.0% within 24 h of hospitalization and 4.6% on days 7–8, whereas the proportion in healthy volunteers was 17.4%. In the monocyte subset, the percentage was 3.2% in healthy individuals, 25.0% within 24 h of hospitalization, and 23.7% on days 7–8 (Table 2 ). Table 2 Ratio to live cells per subset (%) Subset Control Within 24 hours after admission 7–8 days after admission lymphocyte CD4+ 27.0 25.7 18.4 CD8+ 17.4 7.0 4.6 myeloid monocyte 3.2 25.0 23.7 [insert Table 2 here] Differences in transcriptome analysis for each fraction Comparing samples collected within 24 h of hospitalization with those collected on hospitalization days 7–8, the same trend was observed in all cell populations, including CD4 + T cells, CD8 + T cells, and monocytes. Compared with day 1, the upregulated genes on day 7 were related to cell adhesion and synapse organization. In contrast, the downregulated genes were related to RNA catabolism and the endoplasmic reticulum (Fig. 2 ). Next, we evaluated whether there were any differences with samples collected from healthy volunteers. The upregulated genes in CD4 + T cells were related to inflammatory responses, including control of inflammatory responses, apoptosis of white blood cells, and lymphocyte differentiation. Genes upregulated in CD8 + T cells were related to astrocyte development, control of inflammation, and neutrophils, and those upregulated in monocytes were related to neutrophil activation (Fig. 3 ). On Day 7, genes that were upregulated in CD4 + and CD8 + T cells compared to those in samples collected from healthy individuals were related to cell adhesion, whereas those that were downregulated were related to the endoplasmic reticulum (Fig. 4 ). The transcriptome analysis for both classical and nonclassical monocytes showed that the upregulated genes on day 7 compared to day 1 were related to platelet activation and coagulation. No genes were significantly upregulated or downregulated during this period in intermediate monocytes (Fig. 5 ). Discussion CD4 + T cells The response of CD4 + T cells is suppressed following trauma. [ 12 ] The Th1 type of immune response, in particular, is markedly reduced among the responses of CD4 + T cells. [ 20 , 21 ] Regulatory T cells protect the body by suppressing excessive Th1-type reactions. [ 9 ] In this study, the proportion of CD4 + T cells in viable cells isolated from patients on day 1 did not significantly differ from that of healthy individuals, whereas it decreased on day 7. In the transcriptome analysis, the upregulated genes on day 1 compared with those in healthy individuals were mostly related to inflammatory responses. On day 7, however, there were no significant differences between patients and healthy individuals in the expression of genes related to inflammatory responses, whereas those related to cell adhesion were enriched in patients. Thus, the function of CD4 + T cells changed between day 1 and day 7 in response to TBI. On day 1, these cells were responsible for inflammatory reactions, whereas functions related to cell adhesion became more prominent on day 7, and those related to the endoplasmic reticulum function showed the opposite trend. CD8 + T cells The characteristics of the changes in gene expression that occur in CD8 + T cells is response to TBI are unclear. In this study, FACS analysis showed that the proportion of CD8 + T cells on day 1 was lower than in that in healthy individuals, and decreased even further on day 7. The transcriptome analysis showed that, compared to those in healthy individuals, genes related to the development of astrocytes, regulation of inflammation, and neutrophils were enriched on day 1. Furthermore, genes related to cell adhesion and the endoplasmic reticulum were downregulated on day 7, as it had already been observed in the case of CD4 + T cells. Therefore, it is possible that CD8 + T cells may regulate on astrocyte and neutrophil function and be involved in the control of inflammation immediately after injury. However, after a week, the changes in RNA expression, such as a decrease in the expression of genes related to adhesion and RNA production, are likely to affect the immune capacity of the individual, in the same way as CD4 + T cells. Monocytes Monocytes play a role in innate immunity against infectious diseases, and it is thought that monocyte function often declines during severe infections. [ 22 ] In patients with trauma, it is thought that the expression of human leukocyte antigen (HLA)-DR on monocytes declines, and this has been associated to infections during the course of hospitalization. [ 10 ] The proportion of live cells was significantly higher than in healthy individuals, both on day 1 and day 7. There are few reports on the role of monocytes in trauma, and to the best of our knowledge, no transcriptome analysis for this specific case has been reported. In the analysis we conducted, upregulated genes on day 1 compared to those in healthy individuals were related to neutrophil activation. In addition, genes related to the endoplasmic reticulum were downregulated on day 7 compared to day 1, and to those in healthy individuals. Previous reports have suggested that monocyte function declines after injury. [ 10 ], Neutrophils are thought to be activated immediately following injury (day 1), and this has been associated with an increase in inflammation. However, by Day 7, genes associated with protein synthesis and the function of the endoplasmic reticulum had declined by day 7, as had the proportion of CD4 + and CD8 + T cells, suggesting that the function of the cells themselves is declining as a result. When monocytes were divided into three different subsets and transcriptome analysis was performed, genes related to platelet activation and coagulation were enriched in both classical and nonclassical monocytes on day 7 compared to day 1. In general, monocytes are activated by platelet activation and degranulation, which causes monocyte migration. Activated monocytes are also thought to promote angiogenesis and play a role in tissue repair. [ 23 ] Classical and nonclassical monocytes isolated from patients with TBI showed similar changes on day 7, suggesting that they may be involved in platelet degranulation and tissue repair. Summary In this study, we performed a transcriptome analysis of CD4 + T cells, CD8 + T cells, and monocytes, which are responsible for immunity, and evaluated changes in immune function in patients with TBI during the first seven days after injuty. On day 1, all these processes progressed in the direction of inflammatory activation. However, by day 7, cell adhesion had progressed in all cases and a decline in the function of the endoplasmic reticulum was confirmed, suggesting that RNA expression and protein synthesis in the cells had declined. Therefore, the changes observed by day 7 did not indicate changes in subset-specific immune function, but rather a decline in the function of the mechanisms necessary for maintaining the cells. In addition, the proportion of CD4 + and CD8 + T cells relative to the total number of cells decreased over the course of seven days. TBI is thought to affect peripheral immune responses due to brain damage, and it has been suggested that this may increase the risk of secondary damage to distant organs as well as that of infection. [ 8 ] All three of the cases analyzed in this study developed pneumonia, and secondary infections occurred during the course of the disease. It is thought that the cells responsible for immune protection against infection, including CD4 + T cells, CD8 + T cells, and monocytes, were unable to maintain their function by day 7, preventing the effective control of the infection. Furthermore, all monocyte subtypes were shown to play similar roles by day 7, with no difference in function between classical and non-classical subpopulations. This study revealed that changes in RNA expression play a role in peripheral immune function. Although the results of this study do not represent a major change in the current strategies used to treat trauma, they provide useful information to further elucidate the mechanisms of immunosuppression after trauma. In this study, the comparison was made with healthy individuals, not with patients affected by trauma but without a specific traumatic brain injury. Therefore, the results may not necessarily reflect changes caused by the brain injury itself, but rather by the general effect of suffering trauma. If the effects of brain injury are to be evaluated, it is necessary to make a comparison with cases affected by trauma but without a brain injury. In this study, we were able to capture broad changes occurring in CD4 + and CD8 + T cells. Each of them can be classified into many important subsets, such as regulatory T cells. Although discriminating between these subsets is important to characterize immune function in detail, this was not possible with our experimental setting because we could not isolate a sufficient number of cells for analysis from the blood samples. This limitation may be overcome by using new technologies such as single-cell sequencing. The results of this study may provide a platform for further elucidation of the pathology and treatment of patients with TBI. Limitations As this was a single-center study, the sample size was small and the analysis was exploratory. In addition, because this study only evaluated changes in patients with TBI, the results obtained cannot be considered specific to TBI. Furthermore, TBI can have different severities and hematoma morphologies, and its pathology is expected to differ. To reduce heterogeneity as much as possible among patients with TBI, we targeted patients with the same hematoma morphology and the same level of treatment invasiveness (neural surgery). We also targeted patients with acute subdural hematoma, which is considered more severe and has a higher mortality rate compared to other types of TBI. [ 24 ] Different results may be obtained for other types of TBI, such as acute epidural hematoma or diffuse axonal injury. Since the first blood sample was collected within 24 hours of admission, the condition of individual patients may have showed variations depending on the exact number of hours elapsed between injury and sample collection. Furthermore, the information obtained from transcriptome analysis only evaluates RNA expression at the time the sample was taken, and it is not possible to conclude whether it indicates the cause or result of the condition. Conclusions In patients with TBI, CD4 + T cells, CD8 + T cells, and monocytes showed impaired endoplasmic reticulum function in all cell populations seven days after the injury, suggesting that impaired cell function may have affected immune function. These findings may facilitate further elucidation of the mechanism of immunosuppression due to trauma. Abbreviations AIS-98, Abbreviated Injury Scale 98; CARS, compensatory anti-inflammatory response syndrome; GCS, Glasgow Coma Scale; GOS, Glasgow Outcome Scale; HLA, human leukocyte antigen; IQR, interquartile range; ISS, Injury Severity Score; PBMC, peripheral blood mononuclear cell; SIRS, systemic inflammatory response syndrome; TBI, traumatic brain injury Declarations Ethics approval and consent to participate: The study protocol was approved by the Institutional Review Board of the University of Osaka hospital (Approval Number: 885) and complied with the principles of the Declaration of Helsinki. Written informed consent for the collection of blood samples and the use of clinical data was obtained from the patients or their relatives, and from healthy volunteers. Consent for publication: Not applicable Availability of data and materials: All data generated or analyzed during this study are included in this published article. The raw data from this study were submitted to the Gene Expression Omnibus under accession numbers GSE285385 and GSE285386. Competing interests: The authors declare that they have no competing interests Funding: This study was supported by the General Insurance Association of Japan (grant to HI 2021, and HM 2023), a Grant-in-Aid for Scientific Research (C) from the Japan Society for the Promotion of Science (21K09017) to HI, and a Grant-in-Aid for Scientific Research (B) from the Japan Society for the Promotion of Science (23K27701) to HO. Authors' contributions: HI, MI, HM, HO, and DO were involved in the conception and design of the study. HI performed the literature review. HI and MI acquired the data and performed the analysis and interpretation. HI drafted the manuscript. HI, MI, HM, HO, and DO were involved in the critical revision of the manuscript. All authors contributed to the discussions, managed the study, and read and approved the final version of the manuscript. 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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-7118244","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":511219658,"identity":"207eaa92-007e-4de4-9582-3ddee670b2ec","order_by":0,"name":"Hiroshi Ito","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Ito","suffix":""},{"id":511219659,"identity":"39e7f804-afb7-46ca-9c37-2df5f94b80d9","order_by":1,"name":"Masakazu Ishikawa","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Masakazu","middleName":"","lastName":"Ishikawa","suffix":""},{"id":511219660,"identity":"72a830ae-e78d-499b-8c1e-69ba21d51730","order_by":2,"name":"Hisatake Matsumoto","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hisatake","middleName":"","lastName":"Matsumoto","suffix":""},{"id":511219661,"identity":"a8e3f339-d639-44f9-90ec-cd4df6fbe531","order_by":3,"name":"Hiroshi Ogura","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Ogura","suffix":""},{"id":511219662,"identity":"567fd35d-05e0-488c-81d0-336dbf44d152","order_by":4,"name":"Daisuke Okuzaki","email":"data:image/png;base64,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","orcid":"","institution":"Osaka University","correspondingAuthor":true,"prefix":"","firstName":"Daisuke","middleName":"","lastName":"Okuzaki","suffix":""},{"id":511219663,"identity":"b18289e2-1e4b-4fc1-b28d-41a760cbf20a","order_by":5,"name":"Jun Oda","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Oda","suffix":""}],"badges":[],"createdAt":"2025-07-14 07:38:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7118244/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7118244/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-39991-6","type":"published","date":"2026-02-15T15:58:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91076845,"identity":"065091c9-4f2e-43e7-a485-2f055d1899cf","added_by":"auto","created_at":"2025-09-11 11:12:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":153459,"visible":true,"origin":"","legend":"\u003cp\u003eWorkflow of our research\u003c/p\u003e\n\u003cp\u003e(a) Samples from the control population and the patients were collected. (b) One half of PBMCs was sorted using FACS, and the number of cells in each subset was quantified. The other half was sorted into subsets, and RNA sequencing was performed.\u003c/p\u003e\n\u003cp\u003ePBMCs, Peripheral blood mononuclear cells; FACS, fluorescence-activated cell sorting.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7118244/v1/6e5539adf79e25835228641a.png"},{"id":91076846,"identity":"cc859fa2-7277-4333-aee3-93eef537054c","added_by":"auto","created_at":"2025-09-11 11:12:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":327224,"visible":true,"origin":"","legend":"\u003cp\u003eDot plot of the GO terms (top five) that were significantly upregulated or downregulated in CD4+ T cells, CD8+ T cells, and monocytes (CD14+). The size of the dots represents the gene ratio, and the color represents the adjusted \u003cem\u003eP\u003c/em\u003e-value. “Up” and “Down” indicate upregulation and downregulation, respectively, in day 7 compared with day 1. GO, Gene Ontology; CD4+ T cells, cluster of differentiation 4+ T cells; CD8+ T cells, cluster of differentiation 8+ T cells.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7118244/v1/292c02df59ebf4e64f208c10.png"},{"id":91078658,"identity":"f4f74f1c-9b35-4512-9543-17ad622ad714","added_by":"auto","created_at":"2025-09-11 11:20:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":295112,"visible":true,"origin":"","legend":"\u003cp\u003eDot plot of GO terms (top five or top three) significantly upregulated or down regulated in CD4+ T cells, CD8+ T cells, and monocytes (CD14+). “Up” and “Down” indicate upregulation and downregulation, respectively, in each subset at day 1 compared with healthy individuals. GO, Gene Ontology; CD4+ T cells, cluster of differentiation 4+ T cells; CD8+ T cells, cluster of differentiation 8+ T cells.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7118244/v1/69a0fdbf3b97dd8fc52c40f9.png"},{"id":91078657,"identity":"5d3e5edf-0c30-48d1-b638-a4201a85210f","added_by":"auto","created_at":"2025-09-11 11:20:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":331387,"visible":true,"origin":"","legend":"\u003cp\u003eDot plot of GO terms (top five) significantly upregulated or down regulated in CD4+ T cells, CD8+ T cells, and monocytes (CD14+). “Up” and “Down” indicate upregulation and downregulation, respectively, in each subset at day 7 compared with healthy individuals. GO, Gene Ontology; CD4+ T cells, cluster of differentiation 4+ T cells; CD8+ T cells, cluster of differentiation 8+ T cells.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7118244/v1/ad9123f46d724f95cc7bd65f.png"},{"id":91078660,"identity":"aa76ba46-de5e-42e4-8d47-179614c3b2a3","added_by":"auto","created_at":"2025-09-11 11:20:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":327078,"visible":true,"origin":"","legend":"\u003cp\u003eDot plot of GO terms (top five) significantly upregulated or down regulated in classical (CM) and nonclassical (NM) monocytes. “Up” and “Down” indicate upregulation and downregulation, respectively, in each subset at day 7 compared with day 1. GO, Gene Ontology\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7118244/v1/a91a18f0b5a541d106a5c0a1.png"},{"id":102785334,"identity":"d58c4e83-eb7e-4a7a-92a1-034e03b2e7c1","added_by":"auto","created_at":"2026-02-16 16:05:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2054367,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7118244/v1/7ae31e87-5501-42b0-9c54-385cb74aab44.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Gene expression changes in lymphocytes and monocytes from patients with traumatic brain injury: A prospective case-control study","fulltext":[{"header":"Background","content":"\u003cp\u003eIn the United States, approximately 2.8\u0026nbsp;million individuals sustain traumatic brain injuries (TBIs) each year. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Patients with severe TBI frequently develop nosocomial infections, including ventilator-associated pneumonia. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] Therefore, clarifying the mechanism regulating the immune response in patients with TBI may help to improve treatment options. When tissue is injured due to trauma, various antigens and mediators are released. This reaction is sterile, and these factors interact with immune cells to initiate an inflammatory response. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] This sort of inflammatory response is known as Systemic Inflammatory Response Syndrome (SIRS), and it is caused by the activation of the innate immune system. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] A compensatory anti-inflammatory response syndrome (CARS) has also been described to occur simultaneously in response to trauma. CARS usually reflects autoimmune suppression caused by serious incidents such as sepsis, burns, and tissue damage. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] Excessive or prolonged CARS can induce immunosuppression, which promotes secondary infection and organ dysfunction. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] T cells play a major role in the modulation of immunosuppressive mechanisms. In particular, the reduction in CD4\u0026thinsp;+\u0026thinsp;T cells and the increase in PD-1 expression in CD8\u0026thinsp;+\u0026thinsp;T cells reflect immune fatigue. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] Many studies have reported that T cell function is at its lowest level between a few days and a week after injury. This has been explained by the fact that the compensatory host reaction to strong inflammation is most clearly observed approximately one week after injury. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] Besides T cells, monocytes and macrophages mediate immunosuppression, and a trauma-induced inflammasome dysfunction is possibly related to immunosuppression. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] Furthermore, monocytes modulate immune function and, in the peripheral blood, there are three different monocyte subsets: classical, intermediate, and nonclassical, each of which has different functions that include phagocytosis and inflammation. In particular, non-classical monocytes are believed to have anti-inflammatory effects and to play a role in immunosuppression. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eConventionally, immunosuppression has been evaluated on the basis of changes in the number of immune cells and the amount of cytokine production. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] However, the mechanisms and detailed pathology of the decline in functional immune cells remains to be characterized. Recent advances in genome analysis have facilitated comprehensive transcriptome analysis, [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] whereby trauma-induced changes in RNA expression have been identified. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] Comprehensive transcriptome analysis can potentially provide novel insight into immunosuppressive mechanisms that could not previously be captured by studies focusing exclusively on cytokines or specific genes. Furthermore, functional changes can be monitored even when there is no change in cell numbers. The characterization of the underlying mechanisms and functional changes associated with immunosuppression may lead to treatments capable of preventing it and thus inhibiting secondary infections. Moreover, the monocyte subset known as nonclassical monocytes has anti-inflammatory effects, and elucidating changes in them may lead to the development of a treatment for immunosuppression. However, few transcriptome analyses of the response to TBI have been reported, and there are no available studies on the immune function of patients affected by TBI.\u003c/p\u003e\u003cp\u003eIn this study, we investigated three cell populations that modulate immune function: CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes. Furthermore, monocytes were divided into three subsets (classical, intermediate, and nonclassical), and the changes in each subpopulation within a week from admission, when immunosuppression is thought to occur, were compared. Functional changes in CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes were assessed through transcriptome analysis in patients with TBI.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003eWe performed a prospective, observational, case-control, single-center study. The study protocol was approved by the Institutional Review Board of the University of Osaka hospital (Approval Number: 885) and complied with the principles of the Declaration of Helsinki. Written informed consent for the collection of blood samples and the use of clinical data was obtained from the patients or their relatives, and from healthy volunteers.\u003c/p\u003e\u003cp\u003eIn this study, we included patients with isolated TBI that were admitted to our hospital between August 2021 and April 2022 and required emergency neurosurgical surgery for acute subdural hematoma. We defined patients with isolated TBI as those who only presented an injury with an Abbreviated Injury Scale 98 (AIS-98) score equal or above 3 in the head and an AIS-98 score below 3 in areas other than the head. Patients who died within 7 days of admission were excluded from the study. The control population consisted of volunteers enrolled via public poster advertisements.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample collection and clinical data\u003c/h3\u003e\n\u003cp\u003eSamples from the patients were collected at two time points: within 24 h of admission and on the 7th day after admission (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-a). Blood samples were stored at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis. The clinical data collected by the investigators from the electronic medical records of the patients included age, sex, Glasgow Coma Scale (GCS) score at admission, site and AIS of whole-body trauma, Injury Severity Score (ISS), type of neurosurgical surgery, presence or absence of tracheotomy, duration of mechanical ventilation, presence or absence of nosocomial infection, and Glasgow Outcome Scale (GOS) score at discharge. The following blood parameters were determined from blood samples collected immediately after admission: fibrinogen, prothrombin time-international normalized ratio, activated partial thromboplastin time, fibrinogen degradation products, and D-dimer. Pneumonia, a nosocomial infection, was diagnosed as hospital-acquired pneumonia based on standard clinical and radiological imaging diagnoses. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eIsolation of peripheral blood mononuclear cells\u003c/h3\u003e\n\u003cp\u003ePeripheral blood mononuclear cells (PBMCs) were isolated from fresh whole blood collected in heparin-coated tubes by density gradient centrifugation using Leucosep (Greiner Bio-One, Kremsm\u0026uuml;nster, Austria) according to the manufacturer\u0026rsquo;s instructions. Isolated PBMCs were divided in half and stored in CELLBANKER cell freezing medium (Nippon Zenyaku Kogyo Co. Ltd., Fukushima Japan) at \u0026minus;\u0026thinsp;80\u0026deg;C until use. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] One half was sorted using \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003efluorescence-activated cell sorting\u003c/span\u003e (FACS), and the number of cells in each subset was quantified. The other half was sorted into subsets, and RNA sequencing was performed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-b).\u003c/p\u003e\n\u003ch3\u003eFluorescence-activated cell sorting\u003c/h3\u003e\n\u003cp\u003eTwo panels were used to identify subsets of CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes from PBMCs. First, DAPI was used to extract viable cells. Lymphocytes and CD3\u0026thinsp;+\u0026thinsp;cells were extracted. Positive subsets for the CD4 and CD8 markers were defined as CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells. Monocytes were extracted from the second panel. DAPI was used for the extraction of viable cells, and three subsets (classical, intermediate, and non-classical) were sorted according to their specific marker expression (CD14\u0026thinsp;+\u0026thinsp;CD16-, CD14\u0026thinsp;+\u0026thinsp;CD16+, and CD14lowCD16+, respectively).\u003c/p\u003e\n\u003ch3\u003eRNA sequencing and bioinformatics\u003c/h3\u003e\n\u003cp\u003eTotal RNA was extracted from the sorted cells using QIAzol lysis reagent (Qiagen, Hilden, Germany) according to the manufacturer's protocol. The RNA quantity and integrity were assessed using a NanoDrop One spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Inc, Santa Clara, CA, USA). RNA sequencing (RNA-seq) libraries were prepared using a TruSeq stranded mRNA sample preparation kit (Illumina, San Diego, CA, USA) following the manufacturer's instructions. Whole-transcriptome sequencing was performed on an Illumina NovaSeq 6000 platform using a 101-base pair-end sequencing strategy. The reads were aligned to the human reference genome (hg19) using TopHat (version 2.1.1). Gene expression was quantified as fragments per kilobase of exon per million mapped fragments using Cufflinks (version 2.2.1). Differential gene expression analysis was conducted using the edgeR package (version 3.19) in R. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] Gene Ontology were performed using ClusterProfiler (version 4.4.4). [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eSummary data are presented as median (interquartile range [IQR]) for continuous variables and as number (%) for categorical variables. The Mann-Whitney U test was used to evaluate differences between the two groups for continuous variables, and the chi-squared test and Fisher's exact test were used for dichotomous variables. Statistical analysis was performed using commercially available statistical analysis software (JMP pro 16 software, SAS Institute Inc., Cary, NC, USA). A \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTranscriptome analysis\u003c/h3\u003e\n\u003cp\u003eTranscriptome analysis was performed for each subpopulation (CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes) using PBMC samples from three patients (No. 1, 2, and 3). Transcriptome changes following trauma were evaluated by comparing samples collected within 24 h of hospitalization with those collected on hospitalization days 7 and 8. Next, we evaluated whether there were any differences with samples collected from healthy volunteers. We used PBMC samples from three patients (No. 4, 5, and 6) to further classify the monocytes into three subsets (classical, intermediate, and nonclassical), and performed transcriptome analysis for each subset.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eParticipant characteristics\u003c/h2\u003e\u003cp\u003eBetween August 2021 and April 2022, 31 patients with isolated TBI were admitted to our hospital. Of these, seven required emergency neural surgery for acute subdural hematoma. One patient died within 7 days of admission and was excluded from the analysis. Two healthy volunteers participated in the study. The backgrounds of the six patients included in the analysis are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median age was 69 years, and three were men (50%). The type of neural surgery was as follows: trepanation in two cases, craniotomy in three cases, and craniectomy in one case. Tracheotomy was performed in three cases, and nosocomial infection occurred in five cases, all of which with a diagnosis of pneumonia. The median GOS at discharge was 3.5 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The two healthy individuals were a 49-year-old man and a 60-year-old man with no underlying or ongoing disease. Samples from the first three consecutive cases with TBI (Pt. 1, 2, and 3) were used to retrieve CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes. Monocytes were further sorted into classical, intermediate, and nonclassical subpopulations using the samples collected from the next three cases (Pt. 4, 5, 6), and an additional analysis was performed.\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\u003eClinicodemographic characteristics of the participants\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e\u003cp\u003ePatient No.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e69 (35.5\u0026ndash;78.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdmission GCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.5 (3\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAIS-head\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5 (3\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eISS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e25 (9.8\u0026ndash;26.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFibrinogen*, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e261\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e361\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e230 (194.3\u0026ndash;286.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePT-INR*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.1 (1.0\u0026ndash;1.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eaPTT*, s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e28 (25.3\u0026ndash;30.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFDP*, \u0026micro;g/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e262.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e134.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e42.9 (5.8\u0026ndash;166.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD-dimer*, \u0026micro;g/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e33.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e12.6 (2.2\u0026ndash;41.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTypes of neurosurgical procedures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCraniotomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCraniotomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCraniectomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTrepanation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCraniotomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTrepanation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTracheostomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood products\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFresh Frozen Plasma, units\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6 (4\u0026ndash;11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRed Cell Concentrate, units\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2 (0\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlatelet Concentrate, units\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0 (0\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of ventilator use, days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8.5 (6\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTypes of nosocomial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePneumonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePneumonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePneumonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePneumonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePneumonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGOS at discharge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.5 (2\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eAIS: Abbreviated Injury Scale, aPTT: activated partial thromboplastin time, FDP: fibrinogen degradation products, GOS: Glasgow Outcome Scale, GCS: Glasgow Coma Scale, IQR: interquartile range, ISS: Injury Severity Score, PT-INR: prothrombin time-international normalized ratio\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e*Parameters reported from blood sample collected at admission.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eFluorescence-activated cell sorting results\u003c/h2\u003e\u003cp\u003eThe proportion of CD4\u0026thinsp;+\u0026thinsp;T cells among the total viable cells obtained from patients was 25.7% within 24 h of admission, which was similar to that obtained from healthy subjects (27.0%). However, this proportion decreased to 18.4% on days 7\u0026ndash;8. In the CD8\u0026thinsp;+\u0026thinsp;T cell subset, the percentage was 7.0% within 24 h of hospitalization and 4.6% on days 7\u0026ndash;8, whereas the proportion in healthy volunteers was 17.4%. In the monocyte subset, the percentage was 3.2% in healthy individuals, 25.0% within 24 h of hospitalization, and 23.7% on days 7\u0026ndash;8 (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\u003eRatio to live cells per subset (%)\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSubset\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWithin 24 hours after admission\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7\u0026ndash;8 days after admission\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003elymphocyte\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCD4+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCD8+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emyeloid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emonocyte\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e23.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eDifferences in transcriptome analysis for each fraction\u003c/h2\u003e\u003cp\u003eComparing samples collected within 24 h of hospitalization with those collected on hospitalization days 7\u0026ndash;8, the same trend was observed in all cell populations, including CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes. Compared with day 1, the upregulated genes on day 7 were related to cell adhesion and synapse organization. In contrast, the downregulated genes were related to RNA catabolism and the endoplasmic reticulum (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNext, we evaluated whether there were any differences with samples collected from healthy volunteers. The upregulated genes in CD4\u0026thinsp;+\u0026thinsp;T cells were related to inflammatory responses, including control of inflammatory responses, apoptosis of white blood cells, and lymphocyte differentiation. Genes upregulated in CD8\u0026thinsp;+\u0026thinsp;T cells were related to astrocyte development, control of inflammation, and neutrophils, and those upregulated in monocytes were related to neutrophil activation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOn Day 7, genes that were upregulated in CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells compared to those in samples collected from healthy individuals were related to cell adhesion, whereas those that were downregulated were related to the endoplasmic reticulum (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe transcriptome analysis for both classical and nonclassical monocytes showed that the upregulated genes on day 7 compared to day 1 were related to platelet activation and coagulation. No genes were significantly upregulated or downregulated during this period in intermediate monocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eCD4\u0026thinsp;+\u0026thinsp;T cells\u003c/h2\u003e\u003cp\u003eThe response of CD4\u0026thinsp;+\u0026thinsp;T cells is suppressed following trauma. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] The Th1 type of immune response, in particular, is markedly reduced among the responses of CD4\u0026thinsp;+\u0026thinsp;T cells. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] Regulatory T cells protect the body by suppressing excessive Th1-type reactions. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] In this study, the proportion of CD4\u0026thinsp;+\u0026thinsp;T cells in viable cells isolated from patients on day 1 did not significantly differ from that of healthy individuals, whereas it decreased on day 7.\u003c/p\u003e\u003cp\u003eIn the transcriptome analysis, the upregulated genes on day 1 compared with those in healthy individuals were mostly related to inflammatory responses. On day 7, however, there were no significant differences between patients and healthy individuals in the expression of genes related to inflammatory responses, whereas those related to cell adhesion were enriched in patients. Thus, the function of CD4\u0026thinsp;+\u0026thinsp;T cells changed between day 1 and day 7 in response to TBI. On day 1, these cells were responsible for inflammatory reactions, whereas functions related to cell adhesion became more prominent on day 7, and those related to the endoplasmic reticulum function showed the opposite trend.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eCD8\u0026thinsp;+\u0026thinsp;T cells\u003c/h2\u003e\u003cp\u003eThe characteristics of the changes in gene expression that occur in CD8\u0026thinsp;+\u0026thinsp;T cells is response to TBI are unclear. In this study, FACS analysis showed that the proportion of CD8\u0026thinsp;+\u0026thinsp;T cells on day 1 was lower than in that in healthy individuals, and decreased even further on day 7. The transcriptome analysis showed that, compared to those in healthy individuals, genes related to the development of astrocytes, regulation of inflammation, and neutrophils were enriched on day 1. Furthermore, genes related to cell adhesion and the endoplasmic reticulum were downregulated on day 7, as it had already been observed in the case of CD4\u0026thinsp;+\u0026thinsp;T cells. Therefore, it is possible that CD8\u0026thinsp;+\u0026thinsp;T cells may regulate on astrocyte and neutrophil function and be involved in the control of inflammation immediately after injury. However, after a week, the changes in RNA expression, such as a decrease in the expression of genes related to adhesion and RNA production, are likely to affect the immune capacity of the individual, in the same way as CD4\u0026thinsp;+\u0026thinsp;T cells.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eMonocytes\u003c/h2\u003e\u003cp\u003eMonocytes play a role in innate immunity against infectious diseases, and it is thought that monocyte function often declines during severe infections. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] In patients with trauma, it is thought that the expression of human leukocyte antigen (HLA)-DR on monocytes declines, and this has been associated to infections during the course of hospitalization. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] The proportion of live cells was significantly higher than in healthy individuals, both on day 1 and day 7.\u003c/p\u003e\u003cp\u003eThere are few reports on the role of monocytes in trauma, and to the best of our knowledge, no transcriptome analysis for this specific case has been reported. In the analysis we conducted, upregulated genes on day 1 compared to those in healthy individuals were related to neutrophil activation. In addition, genes related to the endoplasmic reticulum were downregulated on day 7 compared to day 1, and to those in healthy individuals. Previous reports have suggested that monocyte function declines after injury. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], Neutrophils are thought to be activated immediately following injury (day 1), and this has been associated with an increase in inflammation. However, by Day 7, genes associated with protein synthesis and the function of the endoplasmic reticulum had declined by day 7, as had the proportion of CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells, suggesting that the function of the cells themselves is declining as a result.\u003c/p\u003e\u003cp\u003eWhen monocytes were divided into three different subsets and transcriptome analysis was performed, genes related to platelet activation and coagulation were enriched in both classical and nonclassical monocytes on day 7 compared to day 1. In general, monocytes are activated by platelet activation and degranulation, which causes monocyte migration. Activated monocytes are also thought to promote angiogenesis and play a role in tissue repair. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Classical and nonclassical monocytes isolated from patients with TBI showed similar changes on day 7, suggesting that they may be involved in platelet degranulation and tissue repair.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eSummary\u003c/h2\u003e\u003cp\u003eIn this study, we performed a transcriptome analysis of CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes, which are responsible for immunity, and evaluated changes in immune function in patients with TBI during the first seven days after injuty. On day 1, all these processes progressed in the direction of inflammatory activation. However, by day 7, cell adhesion had progressed in all cases and a decline in the function of the endoplasmic reticulum was confirmed, suggesting that RNA expression and protein synthesis in the cells had declined. Therefore, the changes observed by day 7 did not indicate changes in subset-specific immune function, but rather a decline in the function of the mechanisms necessary for maintaining the cells. In addition, the proportion of CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells relative to the total number of cells decreased over the course of seven days.\u003c/p\u003e\u003cp\u003eTBI is thought to affect peripheral immune responses due to brain damage, and it has been suggested that this may increase the risk of secondary damage to distant organs as well as that of infection. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] All three of the cases analyzed in this study developed pneumonia, and secondary infections occurred during the course of the disease. It is thought that the cells responsible for immune protection against infection, including CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes, were unable to maintain their function by day 7, preventing the effective control of the infection. Furthermore, all monocyte subtypes were shown to play similar roles by day 7, with no difference in function between classical and non-classical subpopulations.\u003c/p\u003e\u003cp\u003eThis study revealed that changes in RNA expression play a role in peripheral immune function. Although the results of this study do not represent a major change in the current strategies used to treat trauma, they provide useful information to further elucidate the mechanisms of immunosuppression after trauma. In this study, the comparison was made with healthy individuals, not with patients affected by trauma but without a specific traumatic brain injury. Therefore, the results may not necessarily reflect changes caused by the brain injury itself, but rather by the general effect of suffering trauma. If the effects of brain injury are to be evaluated, it is necessary to make a comparison with cases affected by trauma but without a brain injury. In this study, we were able to capture broad changes occurring in CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells. Each of them can be classified into many important subsets, such as regulatory T cells. Although discriminating between these subsets is important to characterize immune function in detail, this was not possible with our experimental setting because we could not isolate a sufficient number of cells for analysis from the blood samples. This limitation may be overcome by using new technologies such as single-cell sequencing. The results of this study may provide a platform for further elucidation of the pathology and treatment of patients with TBI.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eAs this was a single-center study, the sample size was small and the analysis was exploratory. In addition, because this study only evaluated changes in patients with TBI, the results obtained cannot be considered specific to TBI. Furthermore, TBI can have different severities and hematoma morphologies, and its pathology is expected to differ. To reduce heterogeneity as much as possible among patients with TBI, we targeted patients with the same hematoma morphology and the same level of treatment invasiveness (neural surgery). We also targeted patients with acute subdural hematoma, which is considered more severe and has a higher mortality rate compared to other types of TBI. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] Different results may be obtained for other types of TBI, such as acute epidural hematoma or diffuse axonal injury. Since the first blood sample was collected within 24 hours of admission, the condition of individual patients may have showed variations depending on the exact number of hours elapsed between injury and sample collection. Furthermore, the information obtained from transcriptome analysis only evaluates RNA expression at the time the sample was taken, and it is not possible to conclude whether it indicates the cause or result of the condition.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn patients with TBI, CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes showed impaired endoplasmic reticulum function in all cell populations seven days after the injury, suggesting that impaired cell function may have affected immune function. These findings may facilitate further elucidation of the mechanism of immunosuppression due to trauma.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAIS-98, Abbreviated Injury Scale 98; CARS, compensatory anti-inflammatory response syndrome; GCS, Glasgow Coma Scale; GOS, Glasgow Outcome Scale; HLA, human leukocyte antigen; IQR, interquartile range; ISS, Injury Severity Score; PBMC, peripheral blood mononuclear cell; SIRS, systemic inflammatory response syndrome; TBI, traumatic brain injury\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThe study protocol was approved by the Institutional Review Board of the University of Osaka hospital (Approval Number: 885) and complied with the principles of the Declaration of Helsinki. Written informed consent for the collection of blood samples and the use of clinical data was obtained from the patients or their relatives, and from healthy volunteers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eAll data generated or analyzed during this study are included in this published article. The raw data from this study were submitted to the Gene Expression Omnibus under accession numbers GSE285385 and GSE285386.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis study was supported by the General Insurance Association of Japan (grant to HI 2021, and HM 2023), a Grant-in-Aid for Scientific Research (C) from the Japan Society for the Promotion of Science (21K09017) to HI, and a Grant-in-Aid for Scientific Research (B) from the Japan Society for the Promotion of Science (23K27701) to HO.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u0026nbsp;\u003c/strong\u003eHI, MI, HM, HO, and DO were involved in the conception and design of the study. HI performed the literature review. HI and MI acquired the data and performed the analysis and interpretation. HI drafted the manuscript. HI, MI, HM, HO, and DO were involved in the critical revision of the manuscript. All authors contributed to the discussions, managed the study, and read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe thank the Department of Medical Informatics, Osaka University Hospital, Osaka, Japan, for their cooperation in the collection of data from medical records. We also thank the medical staff who participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTaylor CA, Bell JM, Breiding MJ, Xu L. 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Dominance of T-helper 2-type cytokines after severe injury. \u003cem\u003eArch Surg\u003c/em\u003e 1996;131:1303\u0026ndash;8; discussion 8\u0026ndash;9. https://doi.org/10.1001/archsurg.1996.01430240057007.\u003c/li\u003e\n\u003cli\u003ePradhan K, Yi Z, Geng S, Li L. Development of exhausted memory monocytes and underlying mechanisms.\u003cem\u003e Front Immunol\u003c/em\u003e 2021;12:778830. https://doi.org/10.3389/fimmu.2021.778830.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez CE, Smith PC, Palma Alvarado VA. The influence of platelet-derived products on angiogenesis and tissue repair: a concise update. \u003cem\u003eFront Physiol \u003c/em\u003e2015;6:290. https://doi.org/10.3389/fphys.2015.00290.\u003c/li\u003e\n\u003cli\u003eKaribe H, Hayashi T, Hirano T, Kameyama M, Nakagawa A, Tominaga T. Surgical management of traumatic acute subdural hematoma in adults: a review. \u003cem\u003eNeurol Med Chir \u003c/em\u003e(Tokyo) 2014;54:887\u0026ndash;94. https://doi.org/10.2176/nmc.cr.2014-0204.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"traumatic brain injury, lymphocyte, immunity","lastPublishedDoi":"10.21203/rs.3.rs-7118244/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7118244/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eTraumatic brain injury (TBI) can alter various immune functions, including immunosuppression, and constitutes a risk factor for nosocomial infections and organ dysfunction. Although TBI can induce a decline in immune cell function, the detailed mechanisms remains to be elucidated. This study aimed to characterize the mechanism of immunosuppression caused by TBI using a comprehensive transcriptome analysis of immune cells.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eSix patients with traumatic brain injury and acute subdural hematoma were admitted to our hospital. We focused on three major subsets of immune cells responsible for the immune response: CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes. We evaluated the changes in immune function after injury using comprehensive transcriptome analysis. Blood samples were collected immediately after admission and one week later, and the data were compared with those of healthy volunteers.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells decreased over seven days following injury, and a decrease in cell adhesion and endoplasmic reticulum function was observed. The results suggested that the process of protein synthesis from RNA was impaired and that overall cell function was reduced. Monocytes also showed a decrease in endoplasmic reticulum function, but classical and nonclassical monocyte subsets showed an increase in functions related to platelet activation and tissue repair.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eComprehensive transcriptome analysis confirmed a decrease in endoplasmic reticulum function in CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, and monocytes. This study contributes to the further elucidation of the mechanisms of immunosuppression due to trauma.\u003c/p\u003e","manuscriptTitle":"Gene expression changes in lymphocytes and monocytes from patients with traumatic brain injury: A prospective case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 11:12:35","doi":"10.21203/rs.3.rs-7118244/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-17T12:12:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-16T10:02:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184483415357704003899934661284188994758","date":"2025-11-07T08:35:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-05T00:40:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226456184476594152787087612927127540568","date":"2025-10-28T01:18:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-04T12:14:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-04T02:43:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-02T10:03:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-27T06:46:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-27T06:43:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5dbd5578-a107-49d6-9ace-5ecbbb100ca5","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":54303925,"name":"Health sciences/Diseases"},{"id":54303926,"name":"Biological sciences/Immunology"}],"tags":[],"updatedAt":"2026-02-16T16:02:23+00:00","versionOfRecord":{"articleIdentity":"rs-7118244","link":"https://doi.org/10.1038/s41598-026-39991-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-02-15 15:58:18","publishedOnDateReadable":"February 15th, 2026"},"versionCreatedAt":"2025-09-11 11:12:35","video":"","vorDoi":"10.1038/s41598-026-39991-6","vorDoiUrl":"https://doi.org/10.1038/s41598-026-39991-6","workflowStages":[]},"version":"v1","identity":"rs-7118244","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7118244","identity":"rs-7118244","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}