Spatially Distinct Immunothrombotic Signatures in Patients with Pneumonia-Related Acute Respiratory Distress Syndrome: Insights from Lung Alveolar and Blood Circulation Profiles

doi:10.21203/rs.3.rs-3337664/v1

Background

The role of immunothrombosis in the pathogenesis of pulmonary acute respiratory distress syndrome (ARDS) is increasingly recognized, but its implications in extrapulmonary complications remain inadequately understood. This study aimed to compare the immunothrombotic signatures in patients with pneumonia-related ARDS (p-ARDS) at both pulmonary and systemic levels and to assess their clinical relevance.

Methods

This prospective observational study included consecutive patients with p-ARDS admitted to the intensive care unit between July and November 2022. Concurrently hospitalized patients with common pneumonia in the general ward were included as controls. Paired bronchoalveolar lavage fluid (BALF) and serum samples were utilized to quantify 15 biomarkers and characterize pulmonary and systemic immunothrombotic signatures, respectively. The clinical relevance of these biomarkers was explored using Spearman correlation, receiver operating characteristic, and binary logistic regression analyses.

Results

A total of 23 patients with p-ARDS and 10 pneumonia controls were included for analysis. Among the p-ARDS cohort, 10 out of 23 patients experienced mortality within 28 days of admission. Our results revealed significant signatures of pulmonary inflammation and systemic endothelial injury in patients with p-ARDS, in comparison to the pneumonia controls. Specially, BALF IL-6 showed a negative correlation with PaO₂/FiO₂ ratio (Spearman r = − 0.67, P < 0.001), while serum a disintegrin and metalloproteinase with thrombospondin type 1 motif, 13 (ADAMTS-13) and soluble thrombomodulin (TM) exhibited close correlations with SOFA and DIC score. The combination of BALF IL-6 and serum TM showed promise in distinguishing p-ARDS from common pneumonia (area under the curve [AUC] = 0.955; 95% confidence interval [CI]: 0.895 − 1.000). Furthermore, BALF H3cit was significantly associated with 28-day mortality, even after adjusting for the SOFA score upon admission (odds ratio [OR] = 6.71; 95% CI: 1.05 − 42.44; P = 0.043).

Conclusions

This preliminary investigation revealed compartment-specific differences in the immunothrombotic signature between patients with p-ARDS and those with pneumonia alone. These findings provide insights into the pathophysiology underlying p-ARDS and its complications, with potential to facilitate the development of precision medicine approaches for its clinical management.

Acute respiratory distress syndrome (ARDS)

Bronchoalveolar lavage fluid

Coagulation

Immunothrombosis

Inflammation

Pneumonia

The respiratory tract is inherently vulnerable to infection due to continuous exposure to airborne pathogens. Pneumonia is a common respiratory infection that affects people of all ages worldwide. Although most patients respond well to appropriate treatment, older adults with preexisting chronic medical conditions are at an increased risk of developing complications that may result in respiratory failure or fatality [1]. Acute respiratory distress syndrome (ARDS), a life-threatening condition, can arise as a complication of various pulmonary and extrapulmonary diseases, with pneumonia being one of the leading causes [2]. Pneumonia-related ARDS (p-ARDS) accounts for approximately 30–50% of all cases of ARDS in adults [3, 4], with associated mortality rates ranging from 30–50% [3, 5]. While several risk factors, including advanced age, the presence of preexisting chronic medical conditions, immunocompromised status, and infection with multidrug-resistant pathogens, have been demonstrated to be associated with the progression from pneumonia to ARDS, the definitive mechanisms driving this clinical course remain incompletely understood [6].

Immunothrombosis, also known as thromboinflammation, refers to the complex interplay between the immune and coagulation systems in response to infection or injury. It encompasses a multifaceted process wherein activated immune cells, such as macrophages and neutrophils, release a diverse array of proinflammatory and procoagulant factors. These factors subsequently trigger the activation of platelets and endothelial cells, initiating the coagulation cascade and resulting in the formation of fibrin clots at the inflamed endothelial surface. The primary physiological function of this process is to encapsulate the pathogen and restrict its dissemination, thereby serving as an innate defense mechanism against infection [7]. However, in certain instances, it can also lead to the development of thrombotic complications and contribute to organ damage [8].

The role of immunothrombosis in the pathogenesis of pneumonia and its related ARDS has been well-established in last decade and further highlighted during the recent COVID-19 pandemic [9–11]. Extensive experimental and clinical evidence suggest that inflammatory and thrombotic processes deeply modulate the complex ARDS pathophysiology. A range of biological phenotypes, including platelet activation, endothelial injury, neutrophil extracellular traps, and thrombi formation have been consistently identified in bronchoalveolar lavage fluid (BALF) samples and injured lung tissues obtained from animal models and ARDS patients [12–15]. Nonetheless, the observation that patients with p-ARDS frequently experience complications such as systemic thromboembolism and extrapulmonary organs injury [2, 16] suggests that dysregulated immunothrombosis may extend beyond the local lung environment and into the systemic circulation, thereby further exacerbating the risk of mortality associated with this condition.

Investigating the immunothrombotic biomarker profiles at both lung local and systemic levels is crucial for better understanding the complex pathophysiology of p-ARDS and facilitating the development of precision medicine approaches for its effective clinical management. In this study, we conducted a quantitative analysis of a comprehensive panel of biomarkers in paired BALF and serum samples obtained from patients with p-ARDS and pneumonia controls. The objectives of this investigation were: (1) to characterize and compare the immunothrombotic signatures in the alveolar compartments and systemic circulation of patients with p-ARDS and those with pneumonia alone, and (2) to explore the potential association between these biomarkers and clinical variables and outcomes.

Study Design, patients and control subjects

This prospective, single-center, observational study was conducted at the Department of Respiratory and Critical Care Medicine, Second Hospital of Tianjin Medical University, China. The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Second Hospital of Tianjin Medical University, with informed consent being waived due to the utilization of clinical residual samples and the absence of any additional risks to the patients (approval number [KY2021K089]). Stringent measures were implemented throughout the study to ensure the preservation of patient privacy and confidentiality.

Between July and November 2022, we consecutively included adult patients diagnosed with p-ARDS based on the Berlin criteria [17] who were admitted to the intensive care unit (ICU). The inclusion criteria, partially adapted from Bendib's study [18], were as follows: (1) respiratory support received for less than 72 hours; (2) PaO₂/FiO₂ ratio ≤ 300 mmHg with positive-end expiratory pressure (PEEP) or continuous positive airway pressure ≥ 5 cm H₂O; (3) bilateral lung infiltrates observed on chest imaging; (4) lung infection diagnosed within 7 days prior to ICU admission; (5) bronchoscopy with bronchoalveolar lavage (BAL) performed within 72 hours of admission for clinical purposes.

For comparison purposes, we included a cohort of patients admitted to the general respiratory ward with common pneumonia who did not require intubation or mechanical ventilation. These patients also underwent bronchoscopy with BAL for clinical purposes and served as control subjects. Pneumonia was defined as the presence of new abnormal infiltration or opacity on chest radiography accompanied by respiratory symptoms or fever.

To identify specific immunothrombotic signatures related to pulmonary infections, we excluded patients and controls who had any of the following conditions: (1) acute non-pulmonary infections (e.g., urinary tract infection, skin and soft tissue infections, etc.); (2) interstitial lung disease or other autoimmune disorders; (3) hematological or solid malignancies; (4) new-onset thrombotic events (e.g., venous thromboembolism, stroke, myocardial infarction, etc.); or (5) major surgery/trauma within the past three months.

Data collection

Demographic, clinical, laboratory, treatment, outcome information, and co-morbidities of both cohorts were extracted from electronic medical records by two independent researchers. Within 24 hours of admission to the ICU, Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Failure Assessment (SOFA), and Disseminated Intravascular Coagulation (DIC) scores [19] were computed for patients with p-ARDS. The severity of ARDS was assessed according to the Berlin criteria [17]. Patients with p-ARDS were monitored for a duration of 30 days following ICU admission. The 28-day mortality was documented as primary outcome.

Sample collection

Residual BALF and serum specimens from p-ARDS patients and pneumonia controls, who underwent bronchoscopy with BAL procedure and had blood drawn within 72 hours of admission for clinical purposes, were utilized in this study. The residual specimens were prospectively collected from the clinical laboratory at the Second Hospital of Tianjin Medical University throughout the designated study period. The time interval from sampling to storage of residual samples was less than 4 hours.

The common indication for performing bronchoscopy with BAL procedure was clinically suspected lung infection, with no identification of causative pathogens in tracheal aspirate or sputum examination. The BAL procedure followed a previously established protocol [20]. Briefly, using 60mL of sterile saline solution (37℃) as the lavage solution and 20 mL administered via bronchoscopy each time to recover the lavage fluid by suction. The retrieved fluid (~ 20mL) was immediately transported to clinical laboratory for microbiology examination. Subsequently, the residual BALF was obtained and subjected to centrifugation (1000 g, 10 mins) at 4 ℃ to remove mucus and cells. The resulting supernatants were aliquoted and stored at − 80°C until batch measurement. In cases where patients underwent multiple BAL procedures, the initial BALF sample was used for analyses.

Routine blood tests were performed daily as part of standard care for both cohorts. On the day of BAL, a blood sample was subjected to centrifugation (1000 g, 10 min) at 4 ℃ to isolated serum for routine laboratory analyses. The residual serum was then obtained and stored at − 80°C for research purpose.

Immunothrombotic biomarkers measurement

A total of 15 immunothrombotic biomarkers, including cytokines/chemokines [(interleukin (IL)-1β, IL-6, IL-8, tumor necrosis factor (TNF)-α], endothelial injury/coagulation-related biomarkers [von Willebrand Factor (vWF)-A2, soluble thrombomodulin (TM), a disintegrin and metalloproteinase with thrombospondin type 1 motif, 13 (ADAMTS-13)], alveolar epithelium injury biomarker [surfactant protein (SP)-D], as well as platelet [p-selectin/CD-62P, platelet factor 4 (PF4)/C-X-C Motif Chemokine Ligand 4 (CXCL4), thrombopoietin (TPO)] and neutrophil [myeloperoxidase (MPO), proteinase 3 (PR3), S100A8, citrullinated histone H3 (H3cit)] activation biomarkers, were quantified in paired BALF and serum samples. The concentration of H3cit was measured using an ELISA kit (#501620, clone 11D3, Cayman Chemical, Ann Arbor, MI, USA). The other 14 biomarkers were quantified at distance using Luminex®multiplex bead-based technology (R&D Systems, Minneapolis, MN, USA) and a Bio-Plex 200® instrument (BioRad, Hercules, CA, USA), according to the manufacturers’ protocols. Results were expressed in fluorescence intensities and concentrations (pg/mL).

Statistical analysis

Continuous variables were presented as median [1st–3rd quartiles] or mean ± standard deviation (SD), and compared using the unpaired Student t-test or the Mann–Whitney U test, as appropriate. Qualitative variables were expressed as numbers and percentages and compared with the χ² or Fisher exact tests, as recommended. Receiver operating characteristic (ROC) analysis was utilized to assess the discriminatory ability of individual biomarkers in distinguishing between p-ARDS and pneumonia. The Spearman method was employed to evaluate correlations between biomarkers and clinical variables in patients with p-ARDS. Binary logistic regression analysis was performed to determine the prognostic value of interested biomarkers for patients with p-ARDS. Statistical significance was defined as a p value < 0.05. Statistical analyses were conducted using SPSS 22.0 (IBM Corporation, Armonk, NY), GraphPad Prism 9.3 (GraphPad Software, Inc., San Diego, CA, USA) and R software (version 4.2.1).

Patients’ characteristics, clinical features, and laboratory findings

During the study period, a total of 42 patients with p-ARDS and 31 patients with common pneumonia were admitted to the ICU and general respiratory ward, respectively. Among them, 30 p-ARDS patients and 12 pneumonia controls met the predefined inclusion criteria. Seven p-ARDS patients and 2 controls were excluded due to the presence of exclusion criteria. Ultimately, a total of 23 patients with p-ARDS and 10 pneumonia controls were included in the final analysis (Supplementary file 1: Fig. S1). According to the Berlin criteria, the p-ARDS cohort comprised 10 individuals classified as mild, 9 as moderate, and 4 as severe cases.

Table 1 presents demographic, laboratory, and clinical data, while Supplementary file 1: Table S1 detailed microbiological examination results. No significant difference in pathogenic spectrum was found between the two groups, with bacterial infections being most common. Demographic characteristics and comorbidities were also similar in both cohorts. Patients diagnosed with p-ARDS exhibited significant elevations in white blood cell counts, procalcitonin levels, and D-dimer levels, alongside decreased serum albumin concentrations upon admission. As anticipated, patients with p-ARDS had higher APACHE II, SOFA, and DIC scores, indicating a greater severity of illness and the presence of extrapulmonary injuries. Despite the implementation of intensive respiratory support, anti-inflammatory treatment, and antithrombotic therapy, a total of 10 out of 23 p-ARDS patients succumbed within 28 days following admission.

Table 1

Characteristics and outcomes of included patients and control subjects
Characteristic	p-ARDS (n = 23)	Pneumonia (n = 10)	P value^*
Demographics
Age (year)	71 ± 12	65 ± 10	0.148
Male	16 (69.5)	5 (50.0)	0.283
Smoking	8 (34.8)	3 (30.0)	0.792
Comorbidities
Diabetes	10 (43.5)	3 (30.0)	0.473
Hypertension	10 (43.5)	4 (40.0)	0.855
Chronic renal insufficiency	5 (21.7)	2 (20.0)	0.911
Admission Laboratory findings
WBC (×10⁹/L)	12.1 (8.5 − 14.8)	6.4 (4.3 − 9.6)	0.015
Hemoglobin (g/L)	118.7 ± 25.2	113.5 ± 22.3	0.574
Platelet (×10⁹/L)	200 (114 − 233)	231 (189 − 328)	0.196
Albumin (g/L)	29.9 ± 5.1	36.1 ± 4.5	0.002
Bilirubin (µmol/L)	15.5 (9.3 − 22.3)	9.9 (7.4 − 19.4)	0.137
Creatinine (µmol/L)	90.9 (61.2 − 191.2)	68.5 (54.9 − 91.5)	0.153
C-reactive protein (mg/L)	70.4 (18.3 − 116.0)	40.0 (8.6 − 67.8)	0.258
Procalcitonin (ng/mL)	3.81 (0.59 − 30.38)	0.08 (0.06–0.73)	0.002
D-dimer (µg/mL)	2.68 (1.45 − 5.02)	0.88 (0.49 − 1.55)	0.006
PaO₂/FiO₂ ratios (mm Hg)	183.6 ± 17.2
Time from admission to 1st BALF sampling (day)	2.1 ± 0.7	2.1 ± 0.9	0.965
ARDS severity			0.054
Mild (PaO₂/FiO₂ ≤ 300 mm Hg)	10 (43.5)
Moderate (PaO₂/FiO₂ ≤ 200 mm Hg)	9 (39.1)
Severe(PaO₂/FiO₂ ≤ 100 mm Hg)	4 (17.4)
Admission Clinical Scores
APACHE II	28.6 ± 7.6
SOFA	10.4 ± 2.1
DIC score^†	2.2 ± 0.7
Clinical outcomes
28-d mortality	10 (43.5)	0 (0.0)	0.015
Hospital length of stay (day)	14 (8 − 19)	13 (9 − 25)	0.754
Respiratory supports
Invasive mechanical ventilation	21 (91.3)
Mechanical ventilation duration (hour)	244 (110 − 350)
ECMO	1 (4.3)
Vasopressors	17 (73.9)
Specific therapies
Antiplatelet agents	3 (13.0)	2 (20.0)	0.614
Heparin/LMWH	17 (73.9)	3 (30.0)	0.026
Corticosteroid	14 (60.9)	2 (20.0)	0.034
Data were presented as either mean ± SD, median with interquartile range (IQR) or number with percentage (%). APACHE II: Acute Physiologic Assessment and Chronic Health Evaluation II; DIC: Disseminated Intravascular Coagulation; ECMO: Extracorporeal Membrane Oxygenation; LWMH: Low Molecular-Weight Heparin; SOFA: Sequential Organ Failure Assessment.
^*: Unpaired Student t test or the Mann–Whitney U test for continuous variables and χ² or Fisher exact test for categorical variables.
^†: The DIC score was computed according to the International Society on Thrombosis and Haemostasis (ISTH) criteria¹⁹, excluding the Fibrinogen Degradation Product (FDP)/D-dimer item due to inadequate FDP measurements.

Spatially distinct immunothrombotic signatures in p-ARDS compared to pneumonia

Biomarkers previously associated with inflammatory and coagulation pathways implicated in the pathophysiology of ARDS were quantified in paired BALF and serum samples obtained in average two days after admission and compared with those of controls. As expected, patients with p-ARDS showed significantly higher concentrations of most investigated biomarkers compared to pneumonia controls. The raw data of biomarker concentrations are presented in Supplementary file 1: Fig. S2, while Fig. 1 provides a visual representation of the Z-score standardized values. Specifically, Fig. 1A illustrates higher levels of inflammatory cytokines (IL-1β, IL-6, IL-8, and TNF-α), as well as markers of neutrophil (S100A8, PR3, and H3cit) and platelet (PF4 and P-selectin) activation, and epithelial damage (SP-D) within the alveolar compartments of p-ARDS patients. In contrast, coagulation-related factors such as soluble TM exhibited increased levels in serum samples of p-ARDS patients, while ADAMTS-13 showed a significant decrease (Fig. 1B).

To further explore the distribution of these biomarkers between the alveolar and blood compartments, we computed the BALF-to-serum concentration ratios. Figure 2A shows that some biomarkers exhibited BALF-to-serum ratios close to 1, indicating no concentration gradient between the alveolar and blood compartments. However, ratios greater than one were observed for SP-D, S100A8, IL-8, IL-6, and IL-1β. Notably, the BALF-to-serum ratios of IL-1β, IL-6, TNF-α, S100A8, and SP-D were significantly higher in patients with p-ARDS compared to those with common pneumonia, suggesting a potential association between the extent of concentration gradient and illness severity. In contrast to the inflammatory biomarkers, the ratios of coagulation/endothelial injury biomarkers between BALF and serum were consistently less than one (Fig. 2B). Comparison based on diseases revealed higher ratios of ADAMTS-13, PF4, and P-selectin in p-ARDS patients compared to pneumonia controls, while the ratio of TM was significantly lower.

In summary, these results suggest the presence of compartment-specific immunothrombotic signatures in patients with p-ARDS. Specifically, the inflammatory biomarkers tend to compartmentalize within the alveolar environment, while coagulation/endothelial injury biomarkers exhibit more pronounced fluctuations in the systemic circulation.

Combination of BALF and serum biomarkers discriminated p-ARDS from pneumonia

We next evaluated the performance of BALF and serum biomarkers in discriminating p-ARDS from pneumonia using ROC analysis. Supplementary file 1: Table S2 presents the results, showing that serum TM and BALF IL-6 were the top two variables in distinguishing between the two conditions, with area under curves (AUC) of 0.861 (95% confidence intervals [CI]: 0.734 − 0.988; P = 0.001) and 0.830 (95%CI: 0.668 − 0.995; P = 0.003), respectively. Furthermore, the combination of these two biomarkers yielded an increased AUC of 0.913 (95%CI: 0.816 − 1.000; P < 0.001), as shown in Fig. 3.

Association of immunothrombotic biomarkers with clinical measures and outcomes

We further investigated the clinical relevance of these biomarkers in the p-ARDS cohort. First, a Spearman correlation matrix was constructed to examine the associations among the biomarkers, clinical scores, and laboratory findings (Fig. 4 and Supplementary file 1: Table S3). BALF IL-6 and PF4 exhibited negative correlations with the severity of respiratory failure (PaO₂/FiO₂ ratio), while serum ADAMTS-13 and TM displayed stronger associations with SOFA, DIC scores, and blood platelet counts (see Fig. 4). Additionally, BALF H3cit showed a positive correlation trend with lung local inflammation (BALF IL-6 and PF4), systemic damage (SOFA) and coagulopathy (DIC score), although statistical significance were not achieved. A subsequent exploratory analysis assessing the prognostic value of these biomarkers revealed that only BALF H3cit was significantly associated with 28-d mortality, even after adjusting for admission SOFA (OR = 6.71;95% CIs: 1.05 − 42.44; P = 0.043), see Table 2. It is important to note that the statistical power of this observation was limited due to the small sample size and validation in future studies is necessary.

Table 2

Association of interested biomarkers with 28-d mortality among patients with p-ARDS
			Univariable analysis		Multivariable analysis
	Decease (n = 10)	Survivals (n = 13)	OR (95%CI)	P value	OR (95%CI) ^*	P value
IL-1β	3.41 (3.10, 3.59)	3.01 (2.40, 3.72)	3.02 (0.70, 13.05)	0.139
IL-6	2.93 (2.14,3.30)	2.59 (2.27, 2.80)	3.33 (0.49, 22.52)	0.217
IL-8	3.76 (3.73, 3.83)	3.78 (3.67, 3.80)	23.60 (0.02, 25154)	0.374
TNFα	1.85 (1.57, 2.04)	1.75 (1.27, 1.91)	11.69 (0.50, 272.36)	0.126
PF4	3.18 (3.06, 3.36)	3.15 (2.65, 3.49)	1.59 (0.15, 16.64)	0.696
P-selectin	3.15 (3.00, 3.21)	3.14 (3.01, 3.26)	0.74 (0.01, 77.42)	0.899
S100A8	3.45 (3.16, 3.82)	3.14 (2.84, 3.68)	3.79 (0.52, 27.84)	0.190
H3cit	4.49 (4.09, 4.73)	3.22 (2.51, 3.93)	5.73 (1.23, 26.61)	0.026	6.71 (1.05, 42.44)	0.043
SP-D	4.55 (4.11, 4.78)	4.26 (4.06, 4.60)	2.56 (0.31, 21.06)	0.381
s-ADAMTS-13	5.66 (5.42, 5.82)	5.94 (5.53, 6.00)	0.05 (0.00, 1.98)	0.109
s-TM	4.05 (3.87, 4.37)	3.96 (3.83, 4.16)	7.85 (0.26, 235.3)	0.235
s-MPO	5.29 (5.16, 5.38)	5.22 (5.12, 5.40)	2.19 (0.01, 393.3)	0.767
s-H3cit	4.23 (3.85, 4.53)	4.06 (3.85, 4.46)	1.27 (0.16, 10.19)	0.818
Data were presented as log10 transformed median with interquartile range of concentrations (pg/mL). ^*: Odds ratio and 95% confidence intervals adjusted for SOFA. The prefix “s-” denotes serum, for instance s-ADAMTS-13 refers to ADAMTS-13 present in the serum. For abbreviations see legend to Fig. 1.

In the present study, we conducted an analysis of 23 p-ARDS patients and 10 pneumonia controls, with a focus on comparing their immunothrombotic biomarker profiles in matched BALF and blood samples. The utilization of control patients with common pneumonia instead of healthy controls is an important aspect of this study, as it allows for a more relevant and realistic comparison between p-ARDS patients and pneumonia controls, both of whom have an underlying lung infection. Our main findings include: (1) We observed compartment-specific differences in immunothrombotic signatures between patients with p-ARDS and those with common pneumonia. Specifically, inflammatory responses were primarily localized within the alveolar compartments, while coagulation/endothelial injury biomarkers exhibit more pronounced fluctuations in the systemic circulation. (2) The combination of BALF IL-6 and serum TM showed potential for distinguishing p-ARDS from pneumonia. (3) BALF IL-6 was found to have a negative correlation with the PaO₂/FiO₂ ratio, while BALF H3cit was associated with 28-day mortality in p-ARDS patients.

The respiratory and circulatory systems interconnect within lung tissues through the alveolar-capillary barrier, which serves as a critical physical and functional partition enabling efficient gas exchange. However, conditions such as lung injury and ARDS can disrupt the integrity of this barrier, leading to its rupture and the subsequent infiltration of fluid and inflammatory cells into the alveoli [2]. Although cell counts on BALF were not conducted in our study, we did detect abundant cell marker proteins in the alveolar compartment of patients with p-ARDS. Specifically, we found significant levels of markers associated with neutrophil activation, such as S100A8 and PR3 [21, 22], as well as H3cit, a marker of neutrophil extracellular traps [23]. These levels were comparable to or even higher than those observed in the serum (refer to Fig. S2 F-H). Furthermore, we observed a positive correlation between PF4 and H3cit in BALF obtained from patients with p-ARDS, although this correlation did not reach statistical significance (see Fig. 4). Additionally, BALF H3cit was found to be significantly associated with 28-d mortality in patients with p-ARDS, even after adjusting for admission SOFA. These findings are in line with previous studies that highlighted the cross-talk between platelet and neutrophil in the pathogenesis of ARDS [12, 24].

The current study supports recent literature documenting significant intra-alveolar inflammation in patients with ARDS triggered by either pulmonary or extrapulmonary factors [25, 26]. A parallel analysis of BALF and serum samples showed that the inflammatory biomarkers are mainly concentrated in the alveolar microenvironment, with no significant enrichment observed in systemic circulation. Consistently, the BALF-to-serum ratios of inflammatory biomarkers in patients with p-ARDS were found to be significantly higher than those in control patients with common pneumonia. Such alveolar compartmentalization of inflammation can primarily be explained by the production of these inflammatory biomarkers within the lung system itself [25]. Additionally, this observation may also be attributed to the deposition of fibrin triggered by inflammation in inflamed alveoli, commonly known as hyaline membrane formation [27]. This local fibrin deposition may, in turn, confines the inflammatory response within the alveolar compartments, thereby limiting the spread of injury or infection to the systemic circulation [28, 29]. Consequently, targeting BALF rather than blood inflammatory indicators may offer a more effective approach for guiding lung targeted anti-inflammatory therapy for patients with p-ARDS.

Enhanced alveolar procoagulant activity, mediated by the tissue factor-VIIa pathway, and consequent intra-alveolar fibrin deposition has been extensively elucidated in previous research [27–29]. In this study, our focus was on quantifying the biomarkers associated with endothelial injury (TM, vWF) and subsequent platelet-vessel wall interaction (ADAMTS-13, P-selectin) pathway, which bridge inflammation and thrombosis as a unified mechanism implicated in ARDS pathogenesis [8, 9]. Elevated serum soluble TM levels has been increasing linked to endothelial damage and dysfunction, a known phenotype underlying the pathogenesis of ARDS [30]. Our research validated this relationship, and intriguingly, our results propose that increased soluble TM levels are more prominent in the bloodstream relative to alveolar compartments. ADAMTS-13 is a metalloprotease that cleaves large vWF to prevent excessive platelet adhesion to damaged blood vessels, thus maintaining normal blood flow [31]. Decreased ADAMTS-13 coupled with increased vWF activity has been observed in sepsis and its related coagulopathy [32]. The current study observed significantly lower levels of serum ADAMTS-13 in patients with p-ARDS, yet no marked difference was found for vWF. This may be attributed to the employed measurement method in this study, focusing on protein quantification rather than activity assessment [33]. Taken together, these results indicate that patients with p-ARDS complicated with more pronounced systemic endothelial injury than pneumonia controls, which can, at least partially, explain the link between lung local injury and extrapulmonary organ failures and systemic coagulopathy complicating the clinical course of ARDS.

Currently, the diagnosis and severity stratification of ARDS are primarily based on clinical criteria and PaO₂/FiO₂ ratio, which serves as an objective metric for assessing the severity of respiratory failure. However, a significant limitation of these criteria is their exclusive focus on functional impairment, without considering the underlying pathophysiology [34]. This presents a challenge in identifying individuals at risk during the early stages of ARDS. Our study has revealed a spatial discrete immunothrombotic signature in patients with p-ARDS, characterized by inflammation confined within alveolar compartments and systemic disturbance of endothelial homeostasis. In line with this observation, we found a negative correlation between BALF IL-6 and PaO₂/FiO₂ ratio, while serum biomarkers ADAMTS-13 and TM were closely correlated with extrapulmonary organ damage (SOFA score) and systemic coagulopathy (DIC score), as previously reported [32, 35]. Furthermore, the combination of BALF IL-6 and serum TM demonstrates promising potential in distinguishing p-ARDS from common pneumonia. These findings suggests that the biomarker profile in BALF has the potential to complement information obtained from blood samples, thereby providing a more comprehensive understanding of the immunothrombosis landscape underlying ARDS and facilitating the development of a biomarker-based approach for ARDS diagnosis and severity stratification.

Several limitations should be acknowledged in our study. Firstly, the statistical power of our analysis was limited due to the relatively small sample size. Therefore, further validation using larger sample sizes is necessary to confirm our findings. Secondly, the p-ARDS and pneumonia control groups were derived from different populations, which may introduce potential confounding factors. Although we observed no significant differences in demographic characteristics and past medical history between the two groups, the ability to infer the progression from pneumonia to ARDS pathology is somewhat limited. Thirdly, our findings are specific to pneumonia-related ARDS and may not be generalizable to extrapulmonary ARDS, such as sepsis-induced ARDS. Future research should include a broader range of etiologies to enable a comparative analysis.

This preliminary investigation, although limited in size, revealed increased and spatially distinct immunothrombotic signatures in patients with p-ARDS compared to those with pneumonia alone. The immuno-inflammatory responses were found to be compartmentalized within the pulmonary microenvironment, while disruptions in endothelial homeostasis were more pronounced in the systemic circulation. Importantly, these findings are in line with recent studies documenting discordance between ARDS subtypes characterized by plasma-based inflammatory and coagulation markers and those defined by alveolar biomarker profiles [36, 37]. Therefore, a comprehensive analysis of both blood and BALF immunothrombotic biomarker profiles may provide valuable insights into the intricate pathophysiology underlying these diseases, with potential to facilitate the advancement of precision medicine approaches for their clinical management.

ADAMTS-13 A disintegrin and metalloproteinase with thrombospondin type 1 motif, 13

APACHE II Acute physiology and chronic health evaluation II

ARDS Acute respiratory distress syndrome

BAL Bronchoalveolar lavage;

BALF Bronchoalveolar lavage fluid

CXCL4 C-X-C motif chemokine ligand 4

DIC Disseminated intravascular coagulation

H3cit Citrullinated histone H3

IL Interleukin

MPO Myeloperoxidase

p-ARDS Pneumonia-induced acute respiratory distress syndrome

PCI Percutaneous coronary intervention

PF4 Platelet factor 4

PR3 Proteinase 3

SOFA Sequential organ failure assessment

SP-D Surfactant protein-D

TM Thrombomodulin

TNF-α Tumor necrosis factor-α

TPO Thrombopoietin

vWF-A2 von willebrandfactor-A2

Acknowledgments

Not applicable.

Author contributions

X-LZ and Z-YL designed the study, with X-LZ, Y-RL, YS, D-YL, and Z-QZ collecting BALF and serum specimens and performing measurements. XW, and J-YW acquired patient information and evaluated clinical data. X-LZ and L-YG conducted statistical analyses, drafted the manuscript, and Z-YL reviewed and revised it. All authors gave final approval and agreed to be accountable for all aspects of the work ensuring integrity and accuracy.

Funding

This work was supported by the Tianjin Health Science and Technology Project (KJ20092),Tianjin High-level Selection and Training Project “Young Medical Pioneers”project [2018(19)], and Scientific Research Project of Integrated Traditional Chinese and Western Medicine of Tianjin Health Committee (2021207).

Availability of data and materials

The datasets generated and analyzed during this study are available from the corresponding authors upon reasonable request.

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Second Hospital of Tianjin Medical University, with informed consent being waived due to the utilization of clinical residual samples and the absence of any additional risks to the patients (approval number [KY2021K089]). Stringent measures were implemented throughout the study to ensure the preservation of patient privacy and confidentiality.

Consent for publication

Not applicable

Competing interests

All co-authors declare that they have no competing interests.

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No competing interests reported.

Supplementaryfile.docx

Spatially Distinct Immunothrombotic Signatures in Patients with Pneumonia-Related Acute Respiratory Distress Syndrome: Insights from Lung Alveolar and Blood Circulation Profiles

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Introduction

Methods

Study Design, patients and control subjects

Data collection

Sample collection

Immunothrombotic biomarkers measurement

Statistical analysis

Results

Patients’ characteristics, clinical features, and laboratory findings

Spatially distinct immunothrombotic signatures in p-ARDS compared to pneumonia

Combination of BALF and serum biomarkers discriminated p-ARDS from pneumonia

Association of immunothrombotic biomarkers with clinical measures and outcomes

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1