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Abstract

Background

Neutrophil extracellular traps (NETs) are extracellular reticular structures released from activated neutrophils. This study investigated the relationships among NET constituents—cell-free DNA (cfDNA), histone H3, and high-mobility group box 1 (HMGB1) protein—as well as deoxyribonuclease (DNase), and the severity of organ dysfunction and coagulopathy in patients with sepsis.

Methods

In this exploratory retrospective study, we analyzed serum samples that were collected prospectively and clinical data of 58 adult patients with sepsis admitted to the Emergency and Critical Care Center of Hokkaido University Hospital between September 2019 and October 2021. Participants were divided into high and low cfDNA groups based on the median cfDNA level upon arrival. NET components and DNase activity were measured using fluorescence assays and enzyme-linked immunosorbent assay (ELISA).

Results

The high cfDNA group demonstrated significantly elevated Sequential Organ Failure Assessment (SOFA) and disseminated intravascular coagulation (DIC) scores, greater leukocytosis, and more pronounced coagulopathy compared to the low cfDNA group. Serum cfDNA, histone H3, and HMGB1 levels were positively correlated and increased with DIC severity. However, serum DNase activity did not differ significantly between groups, nor did it correlate with NET components, DIC scores, or organ dysfunction severity.

Conclusions

In patients with severe sepsis, elevated levels of NET components were associated with poor clinical outcomes, reflecting enhanced NET formation. However, DNase activity did not influence NET levels or clinical severity. These findings suggest that NET components may serve as useful biomarkers of sepsis severity, while DNase activity appears unrelated to clinical outcomes in this context.

Keywords

deoxyribonuclease neutrophil extracellular traps cell-free DNA histones high mobility group box 1 sepsis

Background

Sepsis and Neutrophil Extracellular Trap (NET) Formation

Sepsis is a critical condition characterized by a dysregulated host response to severe infections, often resulting in life-threatening organ dysfunction and coagulopathy.¹ Once a systemic immune response is evoked along with neutrophil activation, neutrophils release NETs,² which are composed of neutrophil-derived cell-free DNA (cfDNA), histones, high mobility group box 1 (HMGB1), and neutrophil cytoplasmic proteins such as proteases.³

Roles of NET Components: cfDNA, Histones, HMGB1

NETs play a key role in the host defense mechanism against infections; however, when overproduced or persistent, they can exacerbate sepsis and cause multiple organ dysfunction.⁴ Elevated plasma cfDNA is associated with poor clinical outcomes, such as sepsis severity and organ dysfunction.^2,3 Moreover, all NET components display pro-coagulant properties in the vascular compartment and surrounding tissues. NETs promote vascular thrombosis by activating platelet adhesion and aggregation.⁴ Extracellular histones, released in response to inflammatory challenges, contribute to endothelial dysfunction, organ failure, and cell death during sepsis.⁵ HMGB1 stimulates cells of the innate immune system and complement system, leading to vascular endothelial cell and organ damage and immunoparesis.⁶ Excessive NET formation can damage the microcirculation, promote immunothrombosis, and lead to disseminated intravascular coagulation (DIC), as they facilitate thrombogenesis by serving as a thrombotic scaffold.^7,8

Deoxyribonuclease (DNase) Biology and Gaps in Current Knowledge

The DNA is subsequently degraded by a DNase. In systemic lupus erythematosus (SLE), DNase activity in the bloodstream is reduced, leading to impaired degradation of NETs.^9,10 The compromised clearance of NETs contributes substantively to SLE pathogenesis by extending the exposure duration of autoantigens and elevating levels of SLE-associated autoantibodies.^11,12 Reduced serum DNase I activity has been reported to have pathogenic consequences in inflammatory bowel diseases.¹³ Furthermore, DNase activity is lower than normal in asthma.¹⁴ However, the clinical relevance of DNase activity, its interaction with cfDNA, and clinical outcomes in severe acute conditions, such as sepsis, remain poorly understood. We hypothesized that in sepsis, decreased DNase activity leads to the accumulation of NET components, thereby promoting excessive coagulation activation and subsequent organ failure. Therefore, we evaluated the relationships among NET components, DNase activity, organ dysfunction, and DIC in patients with sepsis.

Methods

Participant Inclusion and Exclusion

Our study enrolled patients diagnosed with sepsis according to the definition established by the sepsis-3 task force in 2016.¹ This exploratory retrospective study was conducted at the Emergency and Critical Care Centre of Hokkaido University Hospital. Patients with sepsis admitted to the Emergency and Critical Care Center of the Emergency Department of Hokkaido University Hospital between September 2019 and October 2021 were included in this study. Their serum samples were collected prospectively. Eligibility criteria included the following: (1) age ≥20 years at the time of comprehensive consent acquisition and (2) consent to participate or non-objection to study inclusion. The exclusion criteria were as follows: (1) cardiac arrest before admission or (2) fungal or virus-induced sepsis to ensure a more homogeneous study population; the pathogenic mechanisms underlying bacterial, viral, and fungal sepsis differ, and these variations could potentially influence the study outcomes.

Clinical and Laboratory Data

Patient characteristics (age, sex, and diagnosis), laboratory parameters (hematological, biochemical, and coagulation profiles), Sequential Organ Failure Assessment (SOFA) scores,¹⁵ DIC scores,¹⁶ and discharge outcomes were obtained from the medical records.

Blood Sample Collection and Analysis

Serum samples were collected within the first 5 days after arrival at the emergency department and were stored at −80 °C until measurements were performed. The timing of serum collection was defined based on arrival at the emergency department as follows: the day of arrival at the emergency department was designated as Day 1, the following morning as Day 2, and the subsequent morning as Day 3. Cell-free DNA levels in serum samples were quantified as previously described.¹⁷ Briefly, serum samples were mixed with SytoxGreen (2 µM; Molecular Probes, Eugene, OR). Fluorescence intensity was analyzed using a SpectraMax iD3 (Molecular Devices Japan, Tokyo, Japan) with 488 nm excitation and 528 nm emission. Serum histone H3 levels were measured using an enzyme-linked immunosorbent assay (ELISA) at Shino-Test Corporation (Tokyo, Japan), as described previously.¹⁸ Serum HMGB1 levels were measured using an HMGB1 ELISA Kit (Shino-Test Corporation), according to the manufacturer's instructions.

DNase activity was measured using a single radial enzyme diffusion assay, as described previously.^19,20 Salmon testis DNA (55 µg/mL; Sigma-Aldrich) was dissolved in a buffer containing 20 mM Tris-HCl pH 7.8, 10 mM MnCl₂, 2 mM CaCl₂, and 2 µM SytoxGreen). The DNA solution was heated at 55 °C for 10 min and mixed with an equal volume of 0.2% agarose GP-36 (Nacalai Tesque, Inc., Kyoto, Japan). The mixture was poured into 24-well plates and incubated at room temperature until solidification. Four microliters of serum samples were injected into wells. Gels were incubated for 4 h at 37 °C. Circular dark zones were observed using an all-in-one fluorescence microscope BZ-X710 (KEYENCE, Osaka, Japan). DNase activity was calculated by measuring the diameter of the dark circles based on a standard curve of known DNase activity.

Statistical Analysis

Continuous variables are expressed as medians (interquartile ranges) and categorical variables are presented as numbers (percentages). Based on the median value of cfDNA concentration upon arrival, patients were divided into two groups: high and low cfDNA groups. Continuous and categorical variables were compared between the two groups using the Mann–Whitney U test and chi-squared test, respectively. A mixed-effects model for repeated measures was employed to compare longitudinal changes between the two groups, accounting for both fixed and random effects. The fixed effects included group, time, and the interaction between group and time. A random intercept was included to account for the within-subject correlation. Time was treated as a continuous variable. No special handling was applied to the missing data points. The significance of the group differences over time was assessed using an interaction term. Spearman's rank correlation analysis was used to evaluate the relationship between the two variables, and the Jonckheere-Terpstra test for trends was used to evaluate the relationship between DIC severity and the variables. To evaluate relationships between the biomarkers and DIC/in-hospital mortality, logistic regression analyses were used. All statistical analyses and calculations were performed using SPSS software (version 26, SPSS Inc., Chicago, IL, USA) and EZR (version 1.68, Saitama Medical Center, Jichi Medical University, Saitama, Japan),¹⁵ which is a graphical user interface for R (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was defined as a two-sided p-value of <.05.

Results

During the observation period, 58 patients with sepsis were evaluated. Among these, 45 presented with septic shock. The median cfDNA concentration upon arrival at the emergency department was 2.97 μg/mL. Based on this median value, patients were divided into two groups: high and low cfDNA groups.

Table 1 summarizes the demographic and clinical characteristics of patients in the two groups. The SOFA score, DIC score, and frequency of DIC-related complications were higher in the high cfDNA group than in the low cfDNA group (p = .012, .001, and .004, respectively). Table 2 presents the results of the laboratory tests on arrival at the emergency department for the two groups. The high cfDNA group was characterized by more severe leukocytosis (p = .005) and coagulation abnormalities, such as low platelet counts (p = .027), prolonged prothrombin time (p = .009), and higher D-dimer levels, than the low cfDNA group (p = .044).

Table 1.

Demographic and Clinical Characteristics of the Patients.

	Low cfDNA Group	igh cfDNA Group	P value
	n = 29	n = 29
Age, years	78 (67-85)	77 (65-83)	.762
Male, m (%)	10 (34.5%)	16 (55.2%)	.113
Infection site
Respiratory	12 (41.4%)	7 (24.1%)	.231
Abdominal	8 (27.6%)	6 (20.7%)
Urinary tract	3 (10.3%)	9 (31.0%)
Soft tissue	6 (20.7%)	6 (20.7%)
Other	0 (0.0%)	1 (3.4%)
Severity on admission to the intensive care unit
SOFA score	7 (4-10)	9 (7-13)	.012
SIRS score	3 (2-4)	3 (3-3.5)	.777
DIC complication	8 (27.6%)	19 (65.5%)	.004
DIC score	2 (1-4)	4 (3-7)	.001

Abbreviations: SOFA, sequential organ failure assessment; SIRS, systemic inflammatory response syndrome; DIC, disseminated intravascular coagulation.

Table 2.

Laboratory Test Results on Arrival at the Emergency Department.

	Normal Range	Low cfDNA Group	High cfDNA Group	P value
		n = 29	n = 29
White blood cell count, ×10⁹/L	3.3–8.6	6.6 (3.5-14.2)	15.7 (6.5-21.4)	.005
Hemoglobin, g/dL	11.6–14.8	12.1 (11-13.1)	11.1 (9.4-12.8)	.035
Platelet count, ×10⁹/L	158–348	196 (135-250)	124 (58-215)	.027
Prothrombin time, sec	9.5–12.0	14 (12.95-15.3)	17.4 (13.9-22.75)	.009
Fibrinogen, mg/dL	200–400	439 (311-643.5)	328.5 (259-511)	.062
Antithrombin, %	80–130	71 (62-80.5)	56 (51-65.5)	.001
FDP, μg/mL	<5.0	13.4 (7.7-24.9)	23 (10.7-66.1)	.078
D-dimer, μg/mL	<1.00	5.57 (3.1-15.12)	11.52 (6.28-37.235)	.044
Albumin, g/dL	>3.9	2.7 (2.4-3.1)	2.3 (1.7-2.7)	.006
Total bilirubin, mg/dL	0.4–1.5	0.7 (0.6-1.3)	1.1 (0.8-1.5)	.083
AST, U/L	13–30	30 (25-52)	81 (48-185)	.001
ALT, U/L	7–23	24 (18-36)	47 (24-75)	.013
LDH, U/L	124–222	224 (192-273)	377 (307-513)	<.001
Creatine kinase, U/L	41–153	115 (68-245)	384 (53-1332)	.137
Amylase, IU/L	44–132	74 (48-143)	49.5 (28-86)	.061
BUN, mg/dL	8–21	26 (18-42)	35 (24-73)	.036
Creatinine, mg/dL	0.45–1.07	1.34 (0.96-1.77)	1.9 (1.29-3.31)	.016
Na, mEq/L	136–143	138 (135-141)	139 (135-142)	.575
K, mEq/L	3.5–5.0	4.1 (3.7-4.5)	4.1 (3.5-5)	.785
Cl, mEq/L	98–108	103 (100-107)	104 (95-108)	1.000
C–reactive protein, mg/dL	0.–0.14	10.63 (2.31-18.92)	13.68 (8.34-22.43)	.234

Abbreviations: FDP, fibrinogen/fibrin degradation products; AST, aspartate aminotransferase; ALT, alanine aminotransferase; LDH, lactate dehydrogenase; BUN, blood urea nitrogen.

Figure 1 illustrates the quantified levels of the primary NET components, including cfDNA, histone H3, and HMGB1, in both groups. The cfDNA and HMGB1 levels were significantly higher in the high cfDNA group during the observation period (p for group effects = .014 and .031, respectively). However, histone H3 levels were not significantly different between the two groups (p for group effect = .887).

Figure 1.

Comparison of cfDNA, HMGB1, and histone H3 between the high and low cfDNA groups. Levels of cfDNA and HMGB1 were significantly higher in the high cfDNA group at all time points. Histone H3 levels were not significantly different between the two groups. Day 1 represents the day of arrival. The horizontal axis represents the timing of sample collection, whereas the vertical axes indicate the concentrations of each NET marker.

Figure 2 shows the SOFA and DIC scores of both groups from day 1 to day 5. Both the SOFA and DIC scores were consistently higher in the high cfDNA group than in the low cfDNA group during the observation period (p for group effect < .001 and p < .001, respectively). Both SOFA and DIC scores gradually decreased from day 1 to day 5 in both groups (p for time effect = .003 and .002, respectively). Furthermore, although changes in DIC scores from days 1 to 5 did not differ between the two groups, changes in SOFA scores were statistically different (p = .038). Both the prothrombin time and antithrombin activity in the high cfDNA group were worse than those in the low cfDNA group during the observation period (p for group effect = .004 and p < .001, respectively). Furthermore, the changes in antithrombin activity from day 1 to day 5 were significantly different between the two groups (p < .001). As shown in Figure 3, cfDNA, HMGB1, and histone H3 levels gradually increased with increasing DIC scores (p < .001, p = .031, and p = .003, respectively).

Figure 2.

Comparison of SOFA and DIC scores, as well as coagulation parameter levels between the high and low cfDNA groups. Both SOFA and DIC scores were consistently higher in the high cfDNA group than in the low cfDNA group. Both scores exhibited a continuous downward trend during the observational period. Both prothrombin time and antithrombin activity were significantly impaired in the high cfDNA group compared to the low cfDNA group. In addition, the change in antithrombin activity exhibited a statistically significant difference between the two groups over the five-day period. The horizontal axis represents the timing of sample collection, whereas the vertical axes indicate the level of each score and the concentrations of the coagulation-fibrinolysis system markers.

Figure 3.

Comparison of cfDNA, HMGB1, and histone H3 levels in relation to the DIC score. All three variables gradually increased with increasing DIC scores. The horizontal axis represents the DIC score of all the patients, whereas the vertical axes indicate the concentrations of each NET marker.

Relationships among cfDNA, HMGB1, histone H3, and DNase activity are shown in Figure 4. As shown in Figure 4, cfDNA, histone H3, and HMGB1 levels were positively correlated with each other. However, DNase activity did not demonstrate a clear association with any of these three variables. Furthermore, Figure 5A shows no significant difference in DNase activity between the high and low cfDNA groups throughout the observation period. Additionally, DNase activity did not appear to vary according to the DIC score, as illustrated in Figure 5B. The effects of DNase activity, HMGB1, histone H3, and cfDNA—treated as continuous variables—on DIC and in-hospital mortality were also examined, and no statistically significant associations were identified (Supplemental Table).

Figure 4.

Relationships among cfDNA, HMGB1, and histone H3 and dNase activity. Although cfDNA, histone H3, and HMGB1 demonstrated mutually positive correlations, DNase activity did not show a distinct relationship with any of these three variables. Each horizontal and vertical axis represents the level of the corresponding marker.

Figure 5.

Comparison of dNase activity between the high and low cfDNA groups. (A) No significant differences in the DNase activity were observed between high and low cfDNA groups. The horizontal axis represents the timing of sample collection, whereas the vertical axis indicates the DNase activity. (B) Furthermore, DNase activity did not change with increasing DIC scores. The horizontal axis represents the DIC score of all the patients, whereas the vertical axis indicates the DNase activity.

Discussion

The present study revealed that HMGB1 levels were considerably elevated in the high cfDNA group. In addition, cfDNA, histone H3, and HMGB1 were positively correlated, suggesting a strong release of NETs. Moreover, both DIC and SOFA scores were consistently higher in the high cfDNA group. This may be attributed to the accelerated release of NETs, which leads to platelet and coagulation activation, thereby contributing to the development of DIC and multiple organ failure. However, contrary to our initial hypothesis, DNase activity was not clearly associated with DIC severity or cfDNA levels.

Sepsis was defined by the Sepsis-3 conference in 2016 as a “life-threatening organ dysfunction caused by a deregulated host response to infection.”^1,21 Excessive NET formation has been observed in sepsis,^2,22,23 and cfDNA, histone H3, and HMGB1 have been detected in the systemic circulation as NET components.³ In a previous study, higher cfDNA concentrations were detected in patients with sepsis than in healthy controls, and these levels correlated with sepsis severity and organ dysfunction.² HMGB1 has been reported to be elevated in patients with sepsis,^24–26 and several animal studies have demonstrated that targeting HMBG1 improves outcomes in sepsis.^26–30 Additionally, histone levels were significantly increased in patients with sepsis and, as in murine models, appeared to cause cellular injury in a Toll-like receptor 4-dependent manner.³¹ Moreover, an increase in these NET components is known to activate platelets and the coagulation cascade, thereby increasing mortality in patients with sepsis.³² Similar to previous studies, our experiments demonstrated that cfDNA, histone H3, and HMGB1 were positively correlated with each other, and their concentrations were elevated with higher DIC scores. These results suggest that sepsis-induced excessive NET formation contributes to the development of DIC.

The effective removal of cfDNA is crucial for tissue homeostasis, preventing inflammation, and avoiding the presentation of autoantigens.^4,33 NETs are cleaved and degraded by DNases, such as DNase 1 and DNase 1-like 3, and intravascular NETs form clots that obstruct blood vessels and cause organ damage in the absence of such DNases in animal studies.^4,19,34 Sohrabipour et al reported that the plasma antigen levels of DNase 1 are significantly lower in patients with sepsis than in healthy controls.³⁵ Aramburu et al reported that approximately 30% of patients with coronavirus disease 2019 (COVID-19) pneumonia and 60% of patients with sepsis exhibited reduced DNase activity in their plasma samples compared to a group of healthy individuals.³⁶ Aramburu et al investigated the association between DNase activity and COVID-19 mortality and found that individuals with low plasma DNase activity exhibited a 4.2-fold increase in mortality and lower lung function recovery among patients with severe COVID-19.³⁶ Our initial hypothesis was that, in sepsis, a decrease in DNase activity would result in elevated cfDNA levels and the development of DIC and multiple organ dysfunction. However, the present findings demonstrated no statistically significant difference in DNase activity between the two groups. Unlike previous studies,^35,36 the present study compared critically ill patients admitted to the intensive care unit (ICU); thus, the absence of a detectable difference in DNase activity may be attributable to the uniformly severe clinical status of the cohort. Some methodological issues might also be associated with the outcomes. The first possible explanation relates to the timing of blood sample collection. Our study population consisted of patients with sepsis, and the progression from infection to sepsis generally occurs over time. Therefore, the samples in our study may have been obtained later in the disease course compared with previous reports. The second potential factor concerns the methodology of the DNase assay. Currently, no gold-standard method exists for measuring DNase activity, and variations in assay techniques may influence the results. In our study, we assessed the overall ability of serum samples to degrade cfDNA. Notably, no association was observed between DNase antigen levels and circulating cfDNA levels, which is consistent with a previous report.³⁵

DNase may play a pivotal role in the pathogenesis of conditions other than sepsis. Skiljevic et al reported that DNase 1 activity in patients with SLE is lower than that in healthy controls³⁷ and that DNase activity is associated with asthma. Charbit et al reported that low DNase activity in the airways is associated with more severe asthma.¹⁴ A potential association may exist between DNase activity and various inflammatory diseases that extend beyond sepsis.

This study has some limitations. First, it was conducted at a single center with a relatively small sample size, which may limit the statistical power of the analysis. Second, the study population was limited to critically ill patients admitted to the ICU. Third, because of the retrospective design and the selection of patients based on their availability of stored samples, the possibility of selection bias cannot be excluded. Therefore, the findings may not be generalizable to non-severe cases, and the results may differ if patients with less severe conditions are included. Further large-scale studies are needed to confirm the relationships among NET constituents, DNase activity, and the severity of organ dysfunction and coagulopathy in patients with sepsis.

Conclusion

In the present study, cfDNA, histone H3, and HMGB1 levels were positively correlated with each other, and their levels increased in parallel with higher DIC scores and greater severity of organ dysfunction. However, DNase activity was not significantly associated with these three variables. Furthermore, DNase activity did not correlate with DIC scores or the severity of organ failure. In the context of severe sepsis, although serum levels of NET components, such as cfDNA, histone H3, and HMGB1, may correlate with the severity of DIC and organ dysfunction, DNase activity does not appear to be associated with the severity of these clinical manifestations.

Supplemental Material

sj-docx-1-cat-10.1177_10760296261416912 - Supplemental material for Neutrophil Extracellular Traps and DNase Activity in Sepsis: Associations with Coagulopathy and Organ Dysfunction

Supplemental material, sj-docx-1-cat-10.1177_10760296261416912 for Neutrophil Extracellular Traps and DNase Activity in Sepsis: Associations with Coagulopathy and Organ Dysfunction by Yuki Munekata, MD, Mineji Hayakawa, MD, PhD, Akane Shinkai, BHSc, and Takashi Ito, MD, PhD in Clinical and Applied Thrombosis/Hemostasis

Footnotes

ORCID iDs

Yuki Munekata

Mineji Hayakawa

Takashi Ito

Ethical Considerations

The study was approved by the Institutional Review Boards of the Ethics Committees of Hokkaido University Hospital and Kumamoto University and was conducted in compliance with the Helsinki Declaration. This study utilized prospectively preserved blood samples under comprehensive consent agreements and retrospectively collected clinical data.

Consent to Participate

Not applicable.

Consent for Publication

Not applicable to this study of anonymized data.

Competing Interests

None of the authors has any competing interests to declare.

Authors’ Contributions

Yuki Munekata (YM) and Mineji Hayakawa (MH) contributed equally to this work and should be considered co-first authors. YM drafted the manuscript. MH contributed to the design of the study, collected data, performed statistical analysis, and drafted the manuscript. Akane Shinkai (AS) and Takashi Ito (TI) contributed to the measurement of MH and TI and supervised the present study. All authors have revised the manuscript for important intellectual content and approved the final version of the manuscript and its submission for publication. All authors have read and approved the final version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Availability of Data and Materials

The datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable request.

Supplemental Material

Supplemental material for this article is available online.

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