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All issues Volume 29 / No 1 (February 2024) Wuhan Univ. J. Nat. Sci., 29 1 (2024) 85-94 Full HTML
Open Access
Issue
Wuhan Univ. J. Nat. Sci.
Volume 29, Number 1, February 2024
Page(s) 85 - 94
DOI https://doi.org/10.1051/wujns/2024291085
Published online 15 March 2024

© Wuhan University 2023

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

0 Introduction

Septic shock patients frequently suffer from severe and circulatory cellular metabolism disorders that cause high mortality[1]. Upon detection of inflammatory signals, the host immune system primarily generates an innate response with a relative feed-forward amplification of this response and other immune response pathways. The feed-forward mechanism means that the transcription of upstream genes simultaneously activates miRNA expression to regulate target gene expression[2, 3]. high mobility group box-1 (HMGB1), a macromolecular substance restricted to the cell nucleus, is released into the bloodstream of patients with sepsis and circulates at an elevated level[4, 5]. HMGB1 is regarded as an alarmin that promotes the production of inflammatory mediators with a tardive and biphasic pattern[6]. This indicates that extracellular HMGB1 is involved in the initial activation of systemic inflammatory response and participates in the enduring immunosuppression that causes mortality in the later stage of sepsis[7, 8]. The early source of HMGB1 is derived from platelet aggregation, and the later source is derived from injured tissue. These lines of evidence demonstrate that HMGB1 is essential in integrating the inflammatory response to cell injuries[9-12]. These results suggest that HMGB1 is a late-released and critical mediator of fatality in sepsis.

To attenuate the inflammatory response, the immune system can switch a pro-inflammatory process into the resolution phase[13, 14]. Several primary anti-inflammatory reactions that inhibit the pro-inflammatory response include the inhibitory miRNAs[15], suppressor of cytokine signaling (SOCS) proteins[16], and hypo-thalamic-pituitary endocrine axis[17], which inhibit the expressions of pro-inflammatory genes[14]. In eukaryotes, miRNAs approximately constitute 1%-2% of the known genes and negatively regulate gene translation by targeting mRNAs[18, 19]. It has been proved that the changes in miRNAs expression profile are related to the onset, progress, and response to treatment of diseases, indicating that they have potential values in diagnostic, prognostic, and predictive indicators in clinics. Recent studies have proved the association of miRNAs with the development of sepsis. It has been determined that gene-specific reprogramming through a miRNA-dependent mechanism can independently suppress the transcription and translation of proinflammatory genes[20, 21]. MiR-146 may play a crucial role in developing sepsis by suppressing the production of inflammatory cytokines[22]. In addition, miR-146b can reduce the expressions of inflammatory cytokines in endothelial cells[23] and improve sepsis-induced myocardial injury in mice[24]. Exceptionally, HMGB1 can be significantly downregulated by miR-146 in lipopolysaccharide (LPS) induced sepsis by targeting the key members to inhibit the inflammatory response[25]. Clinical studies suggest that miR-146a and miR-146b levels are associated with disease severity, and they might be potential biomarkers for ARDS prevention and prognosis in sepsis[26, 27]. However, the roles of miRNAs and their target genes in sepsis are urgent to be illuminated.

As of now, sepsis continues to be a leading cause of morbidity and mortality in patients[28]. Despite this, only a limited number of agents have been validated for effectively treating sepsis. Genes exert their influence through networks of co-expressed genes with similar or opposite biological functions[29]. Therefore, in many instances, the interaction of the host's genetic expressions and regulations determines the approach to treating the disease. In an effort to shed light on the role of specific genes and miRNAs in sepsis, we conducted this cohort study to investigate the potential gene HMGB1 and its associated regulatory miR-146b in context of septic shock.

1 Materials and Methods

1.1 Participants

In this study, 96 patients who suffered from septic shock were admitted to the intensive care unit (ICU) between January and December 2021 in Tongji Hospital (Wuhan, Hubei, China). Furthermore, 22 healthy controls were collected with matched gender and age. The study was approved by the Ethics Committee of Tongji Hospital (NO. TJ-IRB20211252).

1.2 Diagnosis and Treatment

The clinical criteria for diagnosis of septic, exclusive criteria of patients, the measurements of sepsis-related organ failure assessment (SOFA), and the acute physiology, age, chronic health evaluation II (APACHE-II) scores have been detailed in our prior study[30].

1.3 Sample Collection and Detection

Collecting samples and detecting serum HMGB1 and miR-146b mRNA levels at baseline (Day 0) and on Day 3, Day 5, and Day 7 in the ICU were referred to our previous study[30]. The primers utilized for quantitative RT-PCR were listed as follows (5'-3'):

HMGB1-Forward: TAACTAAACATGGGCAAAGGAG,

HMGB1-Reverse: TAGCAGACATGGTCTTCCAC;

miR-146b-Forward: TGACCC ATCCTG GGCCTCAA,

miR-146b-Reverse: CCAGTGGGCAAGATGTGGGCC;

β-actin-Forward: GCACCACACCTTCTACAATGAG,

β-actin-Reverse: GGTCTCAAACATGATCTGGGTC;

U6-Forward: CTCGCTTCGGCAGCACATATACTA,

U6-Reverse: AACGCTTCACGAATTTGCGT.

1.4 Statistical Analysis

All statistical analyses were determined with GraphPad Prism 7.0 Software (GraphPad Software, San Diego, CA). Nonparametric statistical tests were used for data analysis. Mann-Whitney U test, one-way ANOVA, the post hoc test (using Tukey-Kramer's method), receiver operating characteristic (ROC) curve, and the Spearman rank correlation coefficient were performed for statistical comparisons. Data are shown as mean ± SEM. P-value<0.05 indicats statistical significance.

2 Results

2.1 Clinical Characteristics of the Septic Shock Patients

Patients' baseline information, including age, gender, disease severity scores, and clinical parameters are presented in Table 1. The demographics of the patient cohort were displayed by the age distribution [55(47-78) years] and the gender difference (65/31, male/female). The healthy controls were 16/6 (male/female) with a median age of 50 years old. Statistical tests show that there are no differences in age (P=0.13) and gender (P=0.800) between patients and healthy controls (Table 1).

The primary endpoint in this patient cohort was 28 days. This cohort was comprised of 75 survivors and 21 non-survivors, resulting in a rate of 28-day mortality of 21.9%. Statistical analysis of biochemical indices shows that the mean RBC (red blood cell) (P=0.013), PLT(platelet) (P<0.001), ALB (albumin) (P=0.02) and fibrinogen (P<0.001) were significantly elevated in survivors than that in non-survivors, while mean PCT (Procalcitonin) (P<0.001), CRP (C-reactive protein) (P=0.007), serum creatinine (Scr)(P=0.023), lactate and prothrombin time (PT) (P<0.001) were significantly decreased in survivors. Meanwhile, the mean SOFA and APACHE II score, which are commonly used in clinics to evaluate the severity of sepsis patients and predict the prognosis, were significantly lower in survivors (P<0.001, respectively).

Moreover, the time of ICU stay was longer in survivors (P<0.001). The detailed information on baseline and clinical characteristics of healthy controls and patients with septic shock is presented in Table 2.

Table 1

Clinical characteristics of septic patients and healthy controls

Table 2

Infection localization of septic shock

2.2 Expressions of HMGB1 and miR-146b in Septic Shock Patients and Healthy Controls

During time series analysis, the expressions of HMGB1 and miR-146b in baseline (Day 0), Day 3, Day 5, and Day 7 significantly differed between septic shock patients and healthy controls (Fig. 1). The HMGB1 expression was significantly elevated, while the miR-146b level was obviously decreased in septic shock patients.

thumbnail Fig. 1

Significant increase of HMGB1 levels (a) and significant decrease of miR-146b levels (b) in septic shock patients

***P< 0.001; HCs: healthy controls

2.3 Downward Trend of HMGB1 and Upward Trend of miR-146b over Time

To investigate the changing trend of HMGB1 and miR-146b further, consecutive time series analyses were performed among subgroups. Compared with the baseline, HMGB1 was significantly decreased on Day 3, Day 5, and Day 7 (Fig. 2(a), P=0.003, P<0.001 and P<0.001, respectively). However, miR-146b was significantly elevated compared to the baseline on Day 5 and Day 7 (Fig. 2(b), P<0.001 and P=0.006, respectively). Besides, miR-146b on Day 7 was slightly lower than that on Day 5, but no statistical difference was observed (P=0.52). Collectively, our results revealed that after standard treatment, the serum HMGB1 level showed a downward trend, and miR-146b displayed an upward trend with time in septic shock patients.

thumbnail Fig. 2

The downward trend of HMGB1 (a) and the upward trend of miR-146b (b) over time

**P<0.01, ***P<0.001

2.4 HMGB1, miR-146b, SOFA, and APACHE II Scores Indicate Illness Severity and Prognosis

The 96 septic shock patients who suffered from the 28-day challenge were composed of 75 survivors and 21 deaths. The mortality rate is 21.9%. Differences in baseline HMGB1 and miR-146b levels and clinical measurements of SOFA and APACHE II scores between survivors and non-survivors were compared (Fig. 3). At admission, the mean HMGB1 and the baseline SOFA and APACHE II scores were significantly decreased in survivors (Table 1, Fig. 3(a), Fig. 3(c), and Fig. 3(d), P<0.001, respectively). At the same time, the miR-146b was significantly elevated in survivors (Table 1, Fig.3(b), P<0.001).

thumbnail Fig. 3

Correlation of septic shock with HMGB1 level (a), miR-146b(b), SOFA(c), and APACHE II scores (d)

***P<0.001

2.5 HMGB1 and miR-146b Predict Outcomes of Septic Shock

Figure 4 shows the ROC curves for predicting 28-day mortality based on baseline parameters in septic shock patients. The area under the curve (AUC) values (AUC, P value) of the relative parameters were 0.67 (P=0.02) for HMGB1, 0.66 (P=0.03) for miR-146b , 0.72 (P=0.002) for SOFA score, and 0.73 (P=0.001) for APACHE II score, respectively.

thumbnail Fig. 4

ROC curves of four predictors (HMGB1, miR-146b, SOFA, and APACHE II scores) for mortality

The AUC values (with P value) of HMGB1, miR-146b, SOFA, and APACHE II scores were 0.67 (P=0.02), 0.66 (P=0.03), 0.72 (P=0.002), and 0.73 (P=0.001), respectively

2.6 Correlation Between miR-146b and HMGB1 in Patients with Septic Shock

Correlation analysis indicated that the serum miR-146b expression might be negatively associated with HMGB1 level. However, no statistical significance was detected between miR-146b and HMGB1 expressions at any time point, including Day 0 (baseline) (r=-0.21, P=0.32), Day 3 (r=-0.14, P=0.18), Day 5 (r=-0.15, P=0.16), and Day 7(r=-0.09, P=0.34).

3 Discussion

Although retrospective, this study investigated the relative expressions, dynamic tendencies, and the correlation of HMGB1 and miR-146b in septic shock patients for the first time. HMGB1 is considered a delayed-acting mediator in sepsis since it is extracellularly released 8-12 hours after the primary response of macrophages[31]. In a study of septic patients, significant expression of serum HMGB1 was detected 24 hours after the onset of sepsis and persisted until 96 hours, suggesting that HMGB1 is not released until sepsis is well established 24 hours later and sustains the pathological progression of sepsis[32]. An earlier prospective study of septic patients has validated that HMGB1 is a late and downstream inflammatory mediator in sepsis[33]. However, in a previous multicenter trial, no correlation was observed between plasma HMGB1 levels and disease severity, including APACHE II and SOFA scores[34]. In another prospective study, plasma and sputum HMGB1 levels did not correlate with disease severity[35]. A possible explanation is that the concentration of HMGB1 was determined with Western blotting analysis in these studies.

The National Heart, Lung, and Blood Institute (NHLBI) has proposed a unified concept of sepsis as a severe syndrome of endothelial dysfunction. Intravascular or extravascular microbial infections cause it and eventually lead to multiple organ failure, which suggests the central role of endothelial dysfunction in the pathogenesis of sepsis[36]. Therefore, endothelial dysfunction has been considered a predominant hallmark of sepsis. The stability of endothelial cells and integrity of the endothelial barrier can regulate anticoagulant and anti-inflammatory properties in the bloodstream[37, 38]. In response to pathogenic infections, chemokines can recruit neutrophils to infection sites for microbe clearance, and elevated endothelial adhesion molecules and loosened endothelial barrier promote cell penetration to infection sites. However, increased endothelial permeability subsequently causes microvascular leakage, leading to vascular hypotension and shock[39, 40]. Though HMGB1 releases relatively later than acute phase cytokines[41], it orchestrates excessive inflammation response to induce significant endothelial dysfunction or blood coagulation[4, 5]. Besides, circulating HMGB1 can promptly bind to LPS and instruct intracellular translocation of LPS via the receptor for advanced glycation end products (RAGE). The internalization of the HMGB1-LPS complex becomes an essential step in the inflammasome response to LPS[12]. These results indicate that HMGB1 performs as a late-phase mediator of inflammation that drives the progression of sepsis, suggesting it is the potential target for the diagnostics and therapeutics of sepsis[42].

The regulatory mechanism of miRNAs on HMGB1 is unclear. miRNAs are post-transcriptional regulators of gene translation that are involved in pathologies[43, 44],ischemia-reperfusion injury[45, 46], and inflamma-tion-related diseases[47, 48], especially sepsis[49-51]. Both miR-146a and miR-146b are negative regulators of inflammatory gene expression in various cells[23, 52-55]. Validated targeted inflammation genes of miR-146 family are COX-2[56], IRAK1[52], TRAF6[57], IL-1β, IL-6[58], IL-17A[59] and NF-κB[23]. Moreover, HMGB1 might elicit miR-146b expression in turn[60]. Since sepsis is a heterogeneous syndrome involving numerous genes, a single gene's contribution is hard to determine with univariate tests[20]. Likewise, since expressions of miRNAs and the target genes can reciprocally regulate to form feedback loops, the role of miR-146 in sepsis or other inflammation diseases also needs to be illuminated. However, increasing studies have shown that transcriptome methods can be used to analyze potential gene networks that theoretically regulate the occurrence and development of sepsis due to the reciprocal regulation between miRNAs and target genes[61, 62].

Up to now, extensive studies on the negative regulation of inflammatory cytokines (e.g., CRP, TNF-α, IL-1b, IL-6, IL-17) and disease severity (e.g., APACHE II and SOFA scores) by miR-146 in septic patients have been carried out. In one study of 108 sepsis patients, the miR-146 relative level was higher than healthy controls[26]. However, in another study of 104 septic patients, miR-146b was decreased compared to healthy controls[27]. Although the measurement of miR-146 was controversial, miR-146 has attracted extensive attention from clinicians. However, there are two defects in these studies. Firstly, the dynamic trend of miR-146b was not elucidated. Secondly, the possible downstream target gene of miR-146b was not investigated. Nevertheless, these findings emphasize the critical role of miR-146b in regulating inflammation and sepsis.

To investigate the potential regulatory role of miR-146 on HMGB1, we employed quantitative RT-PCR to evaluate the transcriptional level of genes. In comparison to healthy controls, septic shock patients exhibited a notable increase in the mRNA level of HMGB1, accompanied by a significant decrease in the expression of miR-146b. Compared with non-survivors, HMGB1 levels and the baseline SOFA and APACHE II scores were significantly reduced, whereas the mean miR-146b level was significantly elevated in survivors. During time series analysis, HMGB1 levels presented a downward trend, but miR-146b levels displayed an upward trend. Our study showed higher mortality was associated with higher HMGB1 mRNA but lower miR-146b levels, SOFA and APACHE II scores. To evaluate the predictive efficiency of 28-day mortality risk, ROC curves were generated based on the baseline parameters of HMGB1, miR-146b, SOFA, and APACHE II scores. Although ROC curves showed favorable predictive values of HMGB1 and miR-146b, respectively, they were not superior to SOFA and APACHE II scores.

Furthermore, correlation analysis showed that the serum miR-146b level might be negatively associated with the HMGB1 level. However, no significant correlation was found between HMGB1 and miR-146b levels at any time within the first week after admission to ICU. The potential pathophysiological explanation is that persistent septic shock leads to profound endothelial dysfunction and severe reduction in white blood cells, eventually resulting in prolonged immunosuppression. Another aspect that should be mentioned is that CRRT (continuous renal replacement therapy) has been widely applied in clinical therapy for severe sepsis, which may result in sample errors and statistical biases. In spite of these, the levels of HMGB1 and miR-146b can also reflect the direct mechanistic correlations between the host immune response and the feed-forward amplification response, which ultimately contribute to the pathogenesis of sepsis. The above results suggest that HMGB1 and miR-146b may be valuable and convenient indicators for disease severity and predictors for mortality. However, considering patient characteristics, etiology, and intervention variations, more reliable biomarkers for sepsis should be established and evaluated.

It should be noted that there are some limitations in this study. Firstly, the HMGB1 and miR-146b measurements for an extended period were not recorded. Secondly, a verification cohort was not collected to validate the correlation of miR-146b with HMGB1. Thirdly, the relatively small sample of patients might result in statistical bias. Thus, further studies will be conducted in future studies. Overall, validated indicative and predictive biomarkers are very important for clinicians to manage sepsis. Therefore, reliable indicators to evaluate endothelial function, disease severity, and treatment effectiveness should be increased for optimal application.

4 Conclusion

Our findings indicated that a majority of septic shock patients exhibited markedly elevated levels of HMGB1, coupled with notably reduced levels of miR-146b. Furthermore, our study demonstrated that the expression of miR-146b was down-regulated with time, and it may negatively regulate the expression of HMGB1. HMGB1 is a late mediator of inflammation, and miR-146b is a negative regulator of inflammation; both are critical clinical biomarkers reflecting disease severity and predictive mortality indicators in patients with sepsis.

References

  1. Dugar S, Choudhary C, Duggal A. Sepsis and septic shock: Guideline-based management[J]. Cleveland Clinic Journal of Medicine, 2020, 87(1): 53-64. [CrossRef] [PubMed] [Google Scholar]
  2. Shao Y, Saredy J, Yang W Y, et al. Vascular endothelial cells and innate immunity[J]. Arteriosclerosis, Thrombosis, and Vascular Biology, 2020, 40(6): e138-e152. [Google Scholar]
  3. Claser C, Nguee S Y T, Balachander A, et al. Lung endothelial cell antigen cross-presentation to CD8+T cells drives malaria-associated lung injury[J]. Nature Communications, 2019, 10(1): 4241. [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  4. Gould T J, Lysov Z, Liaw P C. Extracellular DNA and histones: Double-edged swords in immunothrombosis[J]. Journal of Thrombosis and Haemostasis, 2015, 13(Suppl 1): S82-S91. [CrossRef] [PubMed] [Google Scholar]
  5. Yang X, Li L, Liu J, et al. Extracellular histones induce tissue factor expression in vascular endothelial cells via TLR and activation of NF-κB and AP-1[J]. Thrombosis Research, 2016, 137: 211-218. [CrossRef] [PubMed] [Google Scholar]
  6. Kim S, Kim S Y, Pribis J P, et al. Signaling of high mobility group box 1 (HMGB1) through toll-like receptor 4 in macrophages requires CD14[J]. Molecular Medicine, 2013, 19: 88-98. [CrossRef] [PubMed] [Google Scholar]
  7. Grégoire M, Tadié J M, Uhel F, et al. Frontline Science: HMGB1 induces neutrophil dysfunction in experimental sepsis and in patients who survive septic shock[J]. Journal of Leukocyte Biology, 2017, 101(6): 1281-1287. [CrossRef] [PubMed] [Google Scholar]
  8. Barnay-Verdier S, Borde C, Fattoum L, et al. Emergence of antibodies endowed with proteolytic activity against High-mobility group box 1 protein (HMGB1) in patients surviving septic shock[J]. Cell Immunology, 2020, 347: 104020. [CrossRef] [Google Scholar]
  9. Andersson U, Tracey K J. HMGB1 is a therapeutic target for sterile inflammation and infection[J]. Annual Review of Immunology, 2011, 29: 139-162. [Google Scholar]
  10. Tsung A, Tohme S, Billiar T R. High-mobility group box-1 in sterile inflammation[J]. Journal of Internal Medicine, 2014, 276(5): 425-443. [Google Scholar]
  11. Yang H, Wang H, Chavan S S, et al. High mobility group box protein 1 (HMGB1): The prototypical endogenous danger molecule[J]. Molecular Medicine (Cambridge, Mass), 2015, 21(Suppl 1): S6-S12. [CrossRef] [PubMed] [Google Scholar]
  12. Deng M, Tang Y, Li W, et al. The endotoxin delivery protein HMGB1 mediates caspase-11-dependent lethality in sepsis[J]. Immunity, 2018, 49(4): 740-753e7. [CrossRef] [PubMed] [Google Scholar]
  13. Serhan C N. Treating inflammation and infection in the 21st century: New hints from decoding resolution mediators and mechanisms[J]. FASEB Journal, 2017, 31(4): 1273-1288. [CrossRef] [PubMed] [Google Scholar]
  14. VanPatten S, Al-Abed Y. High mobility group box-1 (HMGb1): Current wisdom and advancement as a potential drug target[J]. Journal of Medicinal Chemistry, 2018, 61(12): 5093-5107. [CrossRef] [PubMed] [Google Scholar]
  15. Pan Y, Wang D, Liu F. miR-146b suppresses LPS-induced M1 macrophage polarization via inhibiting the FGL2-activated NF-kappaB/MAPK signaling pathway in inflammatory bowel disease[J]. Clinics (Sao Paulo), 2022, 77: 100069. [CrossRef] [PubMed] [Google Scholar]
  16. Sobah M L, Liongue C, Ward A C. SOCS proteins in immunity, inflammatory diseases, and immune-related cancer[J]. Frontiers in Medicine (Lausanne), 2021, 8: 727987. [CrossRef] [Google Scholar]
  17. Ramírez L A, Pérez-Padilla E A, García-Oscos F, et al. A new theory of depression based on the serotonin/kynurenine relationship and the hypothalamicpituitary-adrenal axis[J]. Biomedica, 2018, 38(3): 437-450. [CrossRef] [PubMed] [Google Scholar]
  18. Tong L, Tang C, Cai C, et al. Upregulation of the microRNA rno-miR-146b-5p may be involved in the development of intestinal injury through inhibition of Kruppel-like factor 4 in intestinal sepsis[J]. Bioengineered, 2020, 11(1): 1334-1349. [CrossRef] [PubMed] [Google Scholar]
  19. Iorio M V, Croce C M. microRNA dysregulation in cancer: Diagnostics, monitoring and therapeutics. A comprehensive review[J]. EMBO Molecular Medicine, 2012, 4(3): 143-159. [CrossRef] [PubMed] [Google Scholar]
  20. Zhang Z, Chen L, Xu P, et al. Gene correlation network analysis to identify regulatory factors in sepsis[J]. Journal of Translational Medicine, 2020, 18(1): 381. [CrossRef] [PubMed] [Google Scholar]
  21. Zheng Y, Peng L, He Z, et al. Identification of differentially expressed genes, transcription factors, microRNAs and pathways in neutrophils of sepsis patients through bioinformatics analysis[J]. Cellular and Molecular Biology (Noisy-Le-Grand, France), 2022, 67(5): 405-420. [CrossRef] [PubMed] [Google Scholar]
  22. Comer B S, Camoretti-Mercado B, Kogut P C, et al. microRNA-146a and microRNA-146b expression and anti-inflammatory function in human airway smooth muscle[J]. American Journal of Physiology Lung Cellular and Molecular Physiology, 2014, 307(9): L727-L734. [CrossRef] [PubMed] [Google Scholar]
  23. Gao N, Dong L. MicroRNA-146 regulates the inflammatory cytokines expression in vascular endothelial cells during sepsis[J]. Pharmazie, 2017, 72(11): 700-704. [PubMed] [Google Scholar]
  24. Wang X, Yu Y. MiR-146b protect against sepsis induced mice myocardial injury through inhibition of Notch1[J]. Journal of Molecular Histology, 2018, 49(4): 411-417. [Google Scholar]
  25. Kanaan Z, Barnett R, Gardner S, et al. Differential microRNA (miRNA) expression could explain microbial tolerance in a novel chronic peritonitis model[J]. Innate Immunity, 2013, 19(2): 203-212. [CrossRef] [PubMed] [Google Scholar]
  26. Chen L, Yu L, Zhang R, et al. Correlation of microRNA-146a/b with disease risk, biochemical indices, inflammatory cytokines, overall disease severity, and prognosis of sepsis[J]. Medicine (Baltimore), 2020, 99(22): e19754. [CrossRef] [PubMed] [Google Scholar]
  27. Chen W, Liu L, Yang J, et al. MicroRNA-146b correlates with decreased acute respiratory distress syndrome risk, reduced disease severity, and lower 28-day mortality in sepsis patients[J]. Journal of Clinical Laboratory Analysis, 2020, 34(12): e23510. [CrossRef] [Google Scholar]
  28. Coopersmith C M, de Backer D, Deutschman C S, et al. Surviving sepsis campaign: Research priorities for sepsis and septic shock[J]. Intensive Care Medicine, 2018, 44(9): 1400-1426. [CrossRef] [PubMed] [Google Scholar]
  29. Singer M, Deutschman C S, Seymour C W, et al. The third international consensus definitions for sepsis and septic shock (sepsis-3)[J]. Metabolites, 2016, 315(8): 801-810. [Google Scholar]
  30. Feng J, Wang L, Feng Y, et al. Serum levels of angiopoietin 2 mRNA in the mortality outcome prediction of septic shock[J]. Experimental and Therapeutic Medicine, 2022, 23(5): 362. [CrossRef] [PubMed] [Google Scholar]
  31. Andersson U, Tracey K J. HMGB1 in sepsis[J]. Scandinavian Journal of Infectious Diseases, 2003, 35(9): 577-584. [CrossRef] [PubMed] [Google Scholar]
  32. Zheng Y J, Xu W P, Ding G, et al. Expression of HMGB1 in septic serum induces vascular endothelial hyperpermeability[J]. Molecular Medicine Reports, 2016, 13(1): 513-521. [CrossRef] [PubMed] [Google Scholar]
  33. Sundén-Cullberg J, Norrby-Teglund A, Rouhiainen A, et al. Persistent elevation of high mobility group box-1 protein (HMGB1) in patients with severe sepsis and septic shock[J]. Critical Care Medicine, 2005, 33(3): 564-573. [CrossRef] [PubMed] [Google Scholar]
  34. Unterwalder N, Meisel C, Savvatis K, et al. High-mobility group box-1 protein serum levels do not reflect monocytic function in patients with sepsis-induced immunosuppression[J]. Mediators of Inflammation, 2010, 2010: 745724. [CrossRef] [Google Scholar]
  35. Alpkvist H, Athlin S, Molling P, et al. High HMGB1 levels in sputum are related to pneumococcal bacteraemia but not to disease severity in community-acquired pneumonia[J]. Scientific Reports, 2018, 8(1): 13428. [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  36. Goldenberg N M, Steinberg B E, Slutsky A S, et al. Broken barriers: A new take on sepsis pathogenesis[J]. Science Translational Medicine, 2011, 3(88): 88ps25. [CrossRef] [PubMed] [Google Scholar]
  37. Joffre J, Hellman J, Ince C, et al. Endothelial responses in sepsis[J]. Am J Respir Crit Care Med, 2020, 202(3): 361-370. [Google Scholar]
  38. Vincent J L, Ince C, Pickkers P. Endothelial dysfunction: A therapeutic target in bacterial sepsis?[J]. Expert Opinion on Therapeutic Targets, 2021, 25(9): 733-748. [CrossRef] [PubMed] [Google Scholar]
  39. Zhang Y Y, Ning B T. Signaling pathways and intervention therapies in sepsis[J]. Signal Transduction and Targeted Therapy, 2021, 6(1): 407. [CrossRef] [PubMed] [Google Scholar]
  40. Pool R, Gomez H, Kellum J A. Mechanisms of organ dysfunction in sepsis[J]. Critical Care Clinics, 2018, 34(1): 63-80. [CrossRef] [PubMed] [Google Scholar]
  41. Nakamura T, Sato E, Fujiwara N, et al. Suppression of high-mobility group box-1 and receptor for advanced glycation end-product axis by polymyxin B-immobilized fiber hemoperfusion in septic shock patients[J]. Chemistry (Weinheim an Der Bergstrasse, Germany), 2011, 26(6): 546-549. [NASA ADS] [Google Scholar]
  42. Lee W, Kwon O K, Han M S, et al. Role of moesin in HMGB1-stimulated severe inflammatory responses[J]. Thromb Haemost, 2015, 114(2): 350-363. [CrossRef] [PubMed] [Google Scholar]
  43. Hill M, Tran N. miRNA interplay: Mechanisms and consequences in cancer[J]. Disease Models & Mechanisms, 2021, 14(4): dmm047662. [CrossRef] [PubMed] [Google Scholar]
  44. Ali Syeda Z, Langden S S S, Munkhzul C, et al. Regulatory mechanism of microRNA expression in cancer[J]. International Journal of Molecular Sciences, 2020, 21(5): E1723. [Google Scholar]
  45. Huang Y, Wang H, Wang Y, et al. Regulation and mechanism of miR-146 on renal ischemia reperfusion injury[J]. Pharmazie, 2018, 73(1): 29-34. [PubMed] [Google Scholar]
  46. Ghafouri-Fard S, Shoorei H, Taheri M. Non-coding RNAs participate in the ischemia-reperfusion injury[J]. Biomed Pharmacother, 2020, 129: 110419. [Google Scholar]
  47. Zhong L, Simard M J, Huot J. Endothelial microRNAs regulating the NF-kappaB pathway and cell adhesion molecules during inflammation[J]. FASEB J, 2018, 32(8): 4070-4084. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  48. Olivieri F, Prattichizzo F, Giuliani A, et al. miR-21 and miR-146a: The microRNAs of inflammaging and age-related diseases[J]. Ageing Research Reviews, 2021, 70: 101374. [CrossRef] [PubMed] [Google Scholar]
  49. Vergadi E, Vaporidi K, Tsatsanis C. Regulation of endotoxin tolerance and compensatory anti-inflammatory response syndrome by non-coding RNAs[J]. Frontiers in Immunology, 2018, 9: 2705. [CrossRef] [PubMed] [Google Scholar]
  50. Benz F, Roy S, Trautwein C, et al. Circulating microRNAs as biomarkers for sepsis[J]. International Journal of Molecular Sciences, 2016, 17(1): E78. [Google Scholar]
  51. Dang C P, Leelahavanichkul A. Over-expression of miR-223 induces M2 macrophage through glycolysis alteration and attenuates LPS-induced sepsis mouse model, the cell-based therapy in sepsis[J]. PLoS One, 2020, 15(7): e0236038. [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  52. Gao M, Wang X, Zhang X, et al. Attenuation of cardiac dysfunction in polymicrobial sepsis by microRNA-146a is mediated via targeting of IRAK1 and TRAF6 expression[J]. Journal of Immunology, 2015, 195(2): 672-682. [Google Scholar]
  53. Laura B, Ferguson D A, McCall C E, et al. microRNA-146a and RBM4 form a negative feed-forward loop that disrupts cytokine mRNA translation following TLR4 responses in human THP-1 monocytes[J]. Immunology and Cell Biology, 2013, 91(8): 532-540. [CrossRef] [PubMed] [Google Scholar]
  54. Cheng H S, Sivachandran N, Lau A, et al. microRNA-146 represses endothelial activation by inhibiting proinflamma-tory pathways[J]. EMBO Molecular Medicine, 2013, 5(7): 1017-1034. [CrossRef] [PubMed] [Google Scholar]
  55. Wang Q, Li D, Han Y, et al. MicroRNA-146 protects A549 and H1975 cells from LPS-induced apoptosis and inflammation injury[J]. Journal of Biosciences, 2017, 42(4): 637-645. [CrossRef] [PubMed] [Google Scholar]
  56. Huang X, Zhu Z, Guo X, et al. The roles of microRNAs in the pathogenesis of chronic obstructive pulmonary disease[J]. International Immunopharmacology, 2019, 67: 335-347. [CrossRef] [PubMed] [Google Scholar]
  57. An R, Feng J, Xi C, et al. miR-146a attenuates sepsis-induced myocardial dysfunction by suppressing IRAK1 and TRAF6 via targeting ErbB4 expression[J]. Oxidative Medicine and Cellular Longevity, 2018, 2018: 7163057. [PubMed] [Google Scholar]
  58. Feng J, Zhu Y, Chen L, et al. Clinical significance of microRNA-146a in patients with ulcerative colitis[J]. Ann Clin Lab Sci, 2020, 50(4): 463-467. [PubMed] [Google Scholar]
  59. Li N, Wang J, Yu W, et al. MicroRNA146a inhibits the inflammatory responses induced by interleukin17A during the infection of helicobacter pylori[J]. Mol Med Rep 2019, 19(2): 1388-1395. [PubMed] [Google Scholar]
  60. Ge S, Wu X, Xiong Y, et al. HMGB1 inhibits HNF1A to modulate liver fibrogenesis via p65/miR-146b signaling[J]. DNA and Cell Biology, 2020, 39(9): 1711-1722. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  61. Li Y, Zhang F, Cong Y, et al. Identification of potential genes and miRNAs associated with sepsis based on microarray analysis[J]. Mol Med Rep, 2018, 17(5): 6227-6234. [PubMed] [Google Scholar]
  62. Chen W, Ma X, Zhang P, et al. MiR-212-3p inhibits LPS-induced inflammatory response through targeting HMGB1 in murine macrophages[J]. Exp Cell Res, 2017, 350(2): 318-326. [CrossRef] [PubMed] [Google Scholar]

All Tables

Table 1

Clinical characteristics of septic patients and healthy controls

In the text
Table 2

Infection localization of septic shock

In the text

All Figures

thumbnail Fig. 1

Significant increase of HMGB1 levels (a) and significant decrease of miR-146b levels (b) in septic shock patients

***P< 0.001; HCs: healthy controls
In the text
thumbnail Fig. 2

The downward trend of HMGB1 (a) and the upward trend of miR-146b (b) over time

**P<0.01, ***P<0.001
In the text
thumbnail Fig. 3

Correlation of septic shock with HMGB1 level (a), miR-146b(b), SOFA(c), and APACHE II scores (d)

***P<0.001
In the text
thumbnail Fig. 4

ROC curves of four predictors (HMGB1, miR-146b, SOFA, and APACHE II scores) for mortality

The AUC values (with P value) of HMGB1, miR-146b, SOFA, and APACHE II scores were 0.67 (P=0.02), 0.66 (P=0.03), 0.72 (P=0.002), and 0.73 (P=0.001), respectively
In the text

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