Identification of TAT, PIC, tPAIC, and TM complex as biomarkers for prognosis and early evaluation of non-severe pneumonia and severe pneumonia diagnosis

doi:10.21203/rs.3.rs-3924460/v1

Download PDF

Research Article

Identification of TAT, PIC, tPAIC, and TM complex as biomarkers for prognosis and early evaluation of non-severe pneumonia and severe pneumonia diagnosis

https://doi.org/10.21203/rs.3.rs-3924460/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background

Pneumonia is a major health problem and the most important causes of mortality in all age groups worldwide. We investigated new automation technology to detect plasma biomarkers, including thrombinantithrombin complex (TAT), α2-plasmininhibitor- plasmin complex (PIC), soluble thrombomodulin (sTM), and tissue plasminogen activator-inhibitor complex (tPAIC), and evaluated their diagnostic performance and prognostic value for severe pneumonia patients.

Methods

We collected 414 patients date with pneumonia. sTM, t-PAI·C, TAT, PIC were measured by qualitative chemiluminescence immunoassay performed on HISCL analyzers. Other laboratory tests were evaluated on the day of non-severe pneumonia and severe pneumonia diagnosis.

Results

There were significant differences in sTM, t-PAI·C, TAT, PIC (P < 0.0001), WBC (P = 0.023), PCT (P = 0.007) and IL-6 (P = 0.002) between the severe pneumonia and non-severe pneumonia groups, Logistic regression analysis showed that sTM (P = 0.001), t-PAI·C(P = 0.001), TAT(P = 0.022), PIC(P = 0.000) and APTT (P = 0.013) were independent risk factors for severe pneumonia. Logistic regression analysis showed that t-PAI·C(P = 0.006)was an independent risk factor for hospital mortality in severe pneumonia.The AUC of sTM combined with t-PAI·C, TAT and PIC on diagnosis of patients with severe pneumonia was 0.868 (95%CI: 0.837,0.899).Kaplan-Meier survival analysis with a log-rank test showed the in-hospital death rate of severe pneumonia was higher in the high TAT(≥ 5.58 ng/ mL) level than in group with low TAT(< 5.58 ng/ mL)level (log rank < 0.029). The same trend with high t-PAI·C was also found in severe pneumonia patients(log rank < 0.021).

Conclusions

Novel coagulation markers might be potential molecular markers for diagnosing and evaluating prognosis of severe pneumonia.

Severe pneumonia

Thrombinantithrombin complex

α2-plasmininhibitor- plasmin complex

Soluble thrombomodulin

Tissue plasminogen activator-inhibitor complex

Pneumonia is a common acute respiratory infection that affects the alveoli and distal bronchial tree of the lungs.Children of < 5 years of age and adults of > 70 years of age are the populations most affected by pneumonia, according to the 2019 GBD study[1].At the global level, lower respiratory tract infections, including pneumonia, are the fourth most common cause of death[2].Systemic coagulation abnormalities, including clotting activation and inhibition of anticoagulant factors, have been observed not only in sepsis but also in pneumonia[3–5].

The pathogenesis of the pneumonia-induced coagulopathy has not yet been fully elucidated, but the mechanisms may overlap in some part to those of bacteria-induced septic coagulopathy/DIC. The excess production of proinflammatory cytokines, increased levels of damage-associated molecular patterns, the stimulation of cell-death mechanisms and vascular endothelial damage are the major causes of coagulation disorder in any severe infection[6–8].Since conventional or classical coagulation laboratory tests (CCTs) cannot detect activation of the early rising coagulation system or the inhibition of the fibrinolytic system, coagulation markers that accurately reflect the coagulation status of patients with severe pneumonia are sorely needed.Soluble thrombomod-ulin (sTM), thrombin-antithrombin complex (TAT), α2-plasmininhibitor -plasmin complex (PIC), and tissue plasminogen activator inhibitor complex (t-PAI·C) have been useful in a variety of diseases[9];however, there is little research on sTM, TAT, PIC, or t-PAI·C to distinguish between severe and non severe pneumonia.

In this study, we analyzed the coagulation status of patients with pneumonia by determining sTM, TAT, PIC, and t-PAI·C combined with CCTs, and assessed their values in the diagnosis of severe pneumonia and the outcome of it.

Subjects

The study initially enrolled 414 patients with pneumonia in Henan Provincial People's Hospital between December 2022 and April 2023.This was a single-center prospective study in which patients were diagnosed as having pneumonia.Pneumonia and severe pneumonia were diagnosed in accordance with the Infectious Diseases Society of America/American Thoracic Society Consensus Guidelines on the Management of Community-Acquired Pneumonia in Adults[10]. This study was approved by the Ethics Committee of Henan Provincial People's Hospital(2022-15,2022.3.1).

Patients

Demographic and clinical characteristics were collected from the electronic medical record system. Data collection of laboratory results were defined by the results of at admission (within 24 h after admission). The exclusion criteria included 1) patients with congenital coagulation dysfunction; 2) long-term use of anticoagulant drugs (heparin, antithrombin, etc); 3) undergoing blood purification and establishment of in vitro life support, and requiring systemic heparin anticoagulant therapy; and 4) the guardian refusing to sign an informed consent form.

Twenty-four healthy individuals (14 male and 10 female) who attended the hospital for a physical examination during the same time period were recruited as controls. The subjects in the control group were included only if they had normal biochemical indices in all routine examinations and no organic diseases.

Laboratory Test Methods

The novel coagulation markers sTM, TAT, PIC, and t-PAI·C were determined using matching reagents by a chemiluminescence method on a Sysmex HISCL-5000 chemiluminescence immunoassay analyzer (Sysmex Corporation, Japan). CCTs were assessed using a CS-5100 coagulation analyzer from the Sysmex Company in Japan (Sysmex Corporation, Japan).The timing of coagulation markers measurement was when the patients was admitted to hospital to diagnose pneumonia or severe pneumonia.

Statistical Methods

Data with normal distribution are presented as the mean ± standard deviation, and data without normal distribution are presented as median (M) and inter-quartile range (P25 and P75).Categorical variables were expressed as frequency rates with percentages. Continuous variables were compared using the independent samples T-test (normal distribution) ,the Mann-Whitney U-test (non-normal distribution)and chi-square test (categorical variables).Logistic regression analysis was used to analyze the independent risk factors of severe pneumonia and mortality outcome due to severe pneumonia following discharge. Kaplan-Meier survival analysis with a log-rank test was performed to estimate the cumulative survival rate of groups with high or low TAT and t-PAI·C level. We implemented the area under the ROC curve (AU-ROC) method to evaluate the sensitivity and specificity of sTM, TAT, and PIC, and t-PAI·C without or combined with CCTs, to predict the mortality outcome of severe pneumonia following discharge.Statistical analyses were performed by SPSS 17.0(SPSS, Chicago, IL, USA) and p-value of < 0.05 was considered statistically significant.

Primary outcomes in the non-severe pneumonia group and severe pneumonia group are shown in Table S1.Patients in severe pneumonia group were significantly higher levels of blood urea( BUN), white blood cell (WBC), C-Reactive Protein (CRP), procalcitonin (PCT), Interle ukin-6 (IL-6), duration in ICU and lower survival rate than the participants in non-severe pneumonia group. Other characteristics like sex, age, Alanine aminotransferase (ALT), total bilirubin(TBIL) and the history of underlying diseases showed no significance between two groups(Table S1).

There were significant differences in sTM,TAT,PIC and t-PAI·C in healthy people, non-severe pneumonia and severe pneumonia groups (P < 0.0001) (Table S2, Fig. 1).There were significant differences in Plt, PT, INR, APTT, FDP, and D-dimer between the two groups (P < 0.001) (Table S3).

Logistic regression analysis of sTM, TAT, PIC and t-PAI·C combined with CCTs in predicting severe pneumonia. Multivariate logistic regression analysis showed that sTM(P = 0.001), TAT(P = 0.022), PIC(P = 0.000), t-PAI·C(P = 0.001) and APTT(P = 0.013) were independent risk factors for severe pneumonia(Table S4).

Receiver operator characteristic (ROC) curve were shown in Fig. 2 to analyze the prognostic value and predicting severe pneumonia.The area under the curve (AUC) of independent and combined with sTM, TAT, PIC,t-PAI·C for severe pneumonia were 0.779 (95%CI 0.734,0.823, P < 0.001), 0.802 (95%CI 0.758,0.845, P < 0.001),0.804(95%CI 0.762,0.845, P < 0.001),0.755(95%CI 0.708,0.802, P < 0.001) and 0.868(95%CI 0.837, 0.899, P < 0.001) (Table S5, Fig. 2A).AUC of other indicators for severe pneumonia were shown in Fig. 2B.

Comparison of outcomes due to death at discharge: 134 severe pneumonia patients survived and 60 died at discharge.There were significant differences in TAT and t-PAI·C between the two groups (P < 0.05) Fig. 3 ,Table S6).

Logistic regression analysis of TAT and t-PAI·C combined with CCTs in predicting mortality outcome due to severe pneumonia. Multivariate logistic regression analysis showed that t-PAI·C(P = 0.006) was an independent risk factor for mortality outcome due to severe pneumonia(Table S7).

AUC of independent and combined with TAT and t-PAI·C for death of severe pneumonia were 0.614 (95%CI 0.532,0.695, P = 0.012), 0.643 (95%CI 0.550,0.718, P = 0.003) and 0.656(95%CI 0.573,0.738, P = 0.001) (Table S8, Fig. 4).

Baseline characteristics of severe pneumonia patients were divided into two groups by low and high TAT levels (TAT < 5.85 ng/mL and TAT ≥ 5.85 ng/ mL) according to the cut-off value determined in the ROC curve (Fig. 4).Cumulative survival rate curves between two groups categorized by TAT cut-off value were shown in Fig. 5A. During follow-up, the in-hospital death rate was higher in the high TAT level than in group with low TAT level (log rank < 0.029). The same trend with high t-PAI·C was also found in patients with severe pneumonia(log rank < 0.021)(Fig. 5B).

Pneumonia remains one of the most important causes of mortality. it is the first cause of respiratory death all over the world, excluding lung cancer[11].Studying hospital admissions for moderate to severe pneumonia has been one way to understand the characteristics and the impact of this disease[12, 13].Although it has been reported that the diagnosis of pneumonia relies on symptoms, clinical features and radiology, those cannot effectively distinguish severe pneumonia. Thus, this study is intended to seek potential molecular markers for diagnosing and evaluating prognosis of severe pneumonia.

In this study,we observed significantly elevated sTM,TAT,PIC and t-PAI·C expressions in severe pneumonia groups compared with healthy and non-severe pneumonia. sTM, a transmem -brane glycoprotein, is abundant on all endothelial surfaces[14].TAT directly reflects the activation of the coagulation system and can be used as a marker of coagulation initiation[15]. The half-life of activated plasmin is very short; and plasmin reacts rapidly with fibrinolytic system α2 plasmin inhibitor to combine 1:1 and thereby form PIC, which then reflects the early rise in plasmin and measurement of which can be used to evaluate the degree of fibrinolytic activation in vivo[16]. In addition, the fibrinolytic system is principally mediated by plasminogen activator inhibitor-1 (PAI-1) and PIC, and thrombin activator fibrinolysis inhibitor (TAFI) leads to fibrinolytic inhibition. PAI-1 forms t-PAI·C by combining with tissue plasminogen activator (t-PA) to inactivate it, thereby inhibiting the dissolution of fibrin[17].The emergence of t-PAI·C can provide an early indication of the occurrence of fibrinolytic inhibition, and is closely related to endothelial cell injury[18]. Interestingly, this study revealed that sTM, TAT, PIC, t-PAI·C and APTT were independent risk factors for severe pneumonia.Pneumonia is an infection of the lung causing exudative fluid to accumulate in the pulmonary parenchyma, compromising respiratory function.Pneumonia is by far the most common cause of sepsis[19, 20], which has been defined by an international task force as organ dysfunction due to a dysregulated host response to infection that is severe enough to be life threatening[21]. Pneumonia is distinguished from other forms of sepsis by the location; when the infection causing dysregulated host response is in the lungs, then it is pneumonia.Sepsis leads to endothelial cell damage, activation of the procoagulant system, and inhibition of anticoagulant substances such as antithrombin (AT), protein C (PC), and TFPI. In addition, alveolar macrophages ,lung epithelial cells, neutrophils and so on can undergo dramatic transcriptional remodeling ,such as NF-κB and STAT3 signal pathway ,in response to infection or infectious stimuli, and such activity is elicited by both pathogen- and host-derived mediators, as enabled by a wide gamut of receptors for pathogen-associated molecular patterns (PAMPs), damage-associated molecular patterns (DAMPs), cytokines, and other immunomodulatory agents[22–25]. Thus, IL-6, CRP and CCTs highly expressed in severe pneumonia. However, AUC of independent and combined with sTM, TAT, PIC, t-PAI·C is better than IL-6 and other indicators for severe pneumonia. These results suggest that sTM, TAT, PIC and t-PAI·C could be an imminent value for diagnostics in severe pneumonia.

Besides the effect of novel coagulation markers on diagnosing severe pneumonia, we also elucidated that novel coagulation markers predict mortality from severe pneumonia.It is well documented that sTM, TAT, PIC, and t-PAI·C can be utilized to evaluate the changes in coagulation status from the critical environments of many pathophysiological mechanisms that underly Sepsis-induced coagulopathy(SIC)— including endothelial cell injury, early-coagulation activation, and fibrinolytic- system inhibition. TAT,PIC,and t-PAI·C be detected in sepsis-related DIC to evaluate the status of coagulation disorders[26]. Moreover, sTM,TAT,PIC and t-PAI·C have been reported to be the clinical value of in diagnosis and outcome of pediatrics sepsis and pSIC[27].In this study we observed remarkably elevated expression of TAT and t-PAI·C in non-survival group,whereas logistic regression analysis revealed t-PAI·C was an independent risk factor for mortality outcome due to severe pneumonia.Interestingly,the higher TAT and t-PAI·C level, the higher in-hospital death rate.The plasma level of t-PAI·C is known to be related with organ failure, and sTM can reflect poor clinical outcomes[28]. PIC, however, is not a significant prognostic factor[29]. As for TAT, some reports showed that TAT levels were significantly higher in patients with poor outcomes than those without[30].The molecular markers differ among patients with different underlying diseases.These data showed that TAT and t-PAI·C could be as biomarkers for the prediction of prognosis and early evaluation of severe pneumonia.

In summary,we have elucidated the role of novel coagulation markers sTM,TAT,PIC and t-PAI·C in diagnosing and predicting the prognosis of severe pneumonia patients. Importantly, both high expression of TAT and t-PAI·C were associated with in-hospital death in patients with severe pneumonia.These findings indicate that novel coagulation markers might be potential molecular markers for diagnosing and evaluating prognosis of severe pneumonia.

Thrombinantithrombin complex

TAT

α2-plasmininhibitor- plasmin complex

PIC

Soluble thrombomodulin

sTM

Tissue plasminogen activator-inhibitor complex

tPAIC

Classical coagulation laboratory tests

CCTs

white blood cell

WBC

C-reactive protein

CRP

Procalcitonin

PCT

Interleukin-6

IL-6

Activated partial thromboplastin time

APTT

Prothrombin time

Area under curve

AUC

Receiver operating characteristic curve

ROC

Thrombin activator fibrinolysis inhibitor

TAFI

All authors have notinstitutional email addresses ,those email addresses are commonly used by the authors.

Ethical Approval

This study was approved by the Ethics Committee of Henan Provincial People's Hospital(2022-15,2022.3.1),and was conducted in accordance with the Helsinki Declaration.All patients and volunteers involved in this study provided informed consent.

Funding

This work was supported by the Provincial Natural Science Foundation of Henan (No.232300421278).

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary files.

Conflicting Interests

The author(s) have no conflicts of interest.

Author Contributions

Yanru Fan designed the subject and writen this paper; Rufei Ma and Biao Hu collected clinical data of patients and performed same experiments;Yuan Zhang and Yanru Fan was responsible for the statistics data;Gang Li and Yujing Zhang revised manuscript;Lan Gao designed the subject.All authors have approved the submitted version of the manuscript and agreed to be accountable for any part of the work.

Notation of prior abstract publication/presentation

Not published in any journal

Acknowledgement

The authors wish to thank Sysmex Corporation for their support.

Global burden. of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet (London, England) 2020;396:1204–22.
Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Volume 380. London, England: Lancet; 2012. pp. 2095–128.
Vail GM, Xie YJ, Haney DJ, Barnes CJ. Biomarkers of thrombosis, fibrinolysis, and inflammation in patients with severe sepsis due to community-acquired pneumonia with and without Streptococcus pneumoniae. Infection. 2009;37:358–64.
Fourrier F, Chopin C, Goudemand J, Hendrycx S, Caron C, Rime A, et al. Septic shock, multiple organ failure, and disseminated intravascular coagulation. Compared patterns of antithrombin III, protein C, and protein S deficiencies. Chest. 1992;101:816–23.
Schultz MJ, Millo J, Levi M, Hack CE, Weverling GJ, Garrard CS, et al. Local activation of coagulation and inhibition of fibrinolysis in the lung during ventilator associated pneumonia. Thorax. 2004;59:130–5.
Subramaniam S, Kothari H, Bosmann M. Tissue factor in COVID-19-associated coagulopathy. Thromb Res. 2022;220:35–47.
Yang X, Cheng X, Tang Y, Qiu X, Wang Z, Fu G, et al. The role of type 1 interferons in coagulation induced by gram-negative bacteria. Blood. 2020;135:1087–100.
Iba T, Connors JM, Nagaoka I, Levy JH. Recent advances in the research and management of sepsis-associated DIC. Int J Hematol. 2021;113:24–33.
Zhou K, Zhang J, Zheng ZR, Zhou YZ, Zhou X, Wang LD, et al. Diagnostic and Prognostic Value of TAT, PIC, TM, and t-PAIC in Malignant Tumor Patients With Venous Thrombosis. Clin Appl thrombosis/hemostasis: official J Int Acad Clin Appl Thrombosis/Hemostasis. 2020;26:1076029620971041.
Mandell LA, Wunderink RG, Anzueto A, Bartlett JG, Campbell GD, Dean NC, et al. Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect diseases: official publication Infect Dis Soc Am. 2007;44(Suppl 2):27–72.
Mandell LA, Niederman MS. Aspiration Pneumonia. The New England journal of medicine 2019;380:651 – 63.
Froes F. [Morbidity and mortality of community-acquired pneumonia in adults in Portugal]. Acta Med Port. 2013;26:644–5.
Froes F, Diniz A, Mesquita M, Serrado M, Nunes B. Hospital admissions of adults with community-acquired pneumonia in Portugal between 2000 and 2009. Eur Respir J. 2013;41:1141–6.
Mochizuki L, Sano H, Honkura N, Masumoto K, Urano T, Suzuki Y. Visualization of Domain- and Concentration-Dependent Impact of Thrombomodulin on Differential Regulation of Coagulation and Fibrinolysis. 2023;123:16–26.
Asanuma K, Nakamura T, Hagi T, Okamoto T, Kita K, Nakamura K, et al. Significance of coagulation and fibrinolysis markers for benign and malignant soft tissue tumors. BMC Cancer. 2021;21:364.
Li S, Qian Y, Pei Y, Wu K, Lu S. Coagulation and Fibrinolysis Biomarkers as Potential Indicators for the Diagnosis and Classification of Ovarian Hyperstimulation Syndrome. Front Med. 2021;8:720342.
Van De Craen B, Declerck PJ, Gils A. The Biochemistry, Physiology and Pathological roles of PAI-1 and the requirements for PAI-1 inhibition in vivo. Thromb Res. 2012;130:576–85.
Zhang J, Xue M, Chen Y, Liu C, Kuang Z, Mu S, et al. Identification of soluble thrombomodulin and tissue plasminogen activator-inhibitor complex as biomarkers for prognosis and early evaluation of septic shock and sepsis-induced disseminated intravascular coagulation. Annals Palliat Med. 2021;10:10170–84.
Hespanhol V, Bárbara C. Pneumonia mortality, comorbidities matter? Pulmonology. 2020;26:123–9.
Violi F, Cangemi R, Calvieri C. Pneumonia, thrombosis and vascular disease. J Thromb haemostasis: JTH. 2014;12:1391–400.
Miyashita N. Atypical pneumonia: Pathophysiology, diagnosis, and treatment. Respiratory Invest. 2022;60:56–67.
Kamata H, Yamamoto K, Wasserman GA, Zabinski MC, Yuen CK, Lung WY, et al. Epithelial Cell-Derived Secreted and Transmembrane 1a Signals to Activated Neutrophils during Pneumococcal Pneumonia. Am J Respir Cell Mol Biol. 2016;55:407–18.
Quinton LJ, Mizgerd JP. NF-κB and STAT3 signaling hubs for lung innate immunity. Cell Tissue Res. 2011;343:153–65.
Sinha M, Lowell CA. Immune Defense Protein Expression in Highly Purified Mouse Lung Epithelial Cells. Am J Respir Cell Mol Biol. 2016;54:802–13.
Whitsett JA, Alenghat T. Respiratory epithelial cells orchestrate pulmonary innate immunity. Nat Immunol. 2015;16:27–35.
Mei H, Jiang Y, Luo L, Huang R, Su L, Hou M, et al. Evaluation the combined diagnostic value of TAT, PIC, tPAIC, and sTM in disseminated intravascular coagulation: A multi-center prospective observational study. Thromb Res. 2019;173:20–6.
Li J, Zhou J, Ren H, Teng T, Li B, Wang Y, et al. Clinical Efficacy of Soluble Thrombomodulin, Tissue Plasminogen Activator Inhibitor complex, Thrombin-Antithrombin complex, α2-Plasmininhibito - Plasmin complex in Pediatric Sepsis. Clin Appl Thromb Hemost. 2022;28:10760296221102929.
Zhao X, Yang S, Lei R, Duan Q, Li J, Meng J, et al. Clinical study on the feasibility of new thrombus markers in predicting massive cerebral infarction. Front Neurol. 2022;13:942887.
Lin SM, Wang YM, Lin HC, Lee KY, Huang CD, Liu CY, et al. Serum thrombomodulin level relates to the clinical course of disseminated intravascular coagulation, multiorgan dysfunction syndrome, and mortality in patients with sepsis. Crit Care Med. 2008;36:683–9.
Hatada T, Wada H, Nobori T, Okabayashi K, Maruyama K, Abe Y, et al. Plasma concentrations and importance of High Mobility Group Box protein in the prognosis of organ failure in patients with disseminated intravascular coagulation. Thromb Haemost. 2005;94:975–9.

No competing interests reported.

supplementdata.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Identification of TAT, PIC, tPAIC, and TM complex as biomarkers for prognosis and early evaluation of non-severe pneumonia and severe pneumonia diagnosis

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Introduction

Methods

Subjects

Patients

Laboratory Test Methods

Statistical Methods

Results

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1