Elevated endothelial dysfunction-related biomarker levels indicate the severity and predict sepsis incidence

Sepsis-associated endothelial glycocalyx damage: a review of animal models, clinical evidence, and molecular mechanisms

In the mammalian cardiovascular system, endothelial glycocalyx is a gel-like layer that covers the luminal surface of endothelial cells (ECs) and plays crucial roles in vascular homeostasis, permeability and leukocyte adhesion. Degradation of this structure occurs early in sepsis and becomes accordingly dysfunctional. In severe cases, it is not self-regulated by the organism. However, the relationship between the glycocalyx and the occurrence and development of sepsis remains poorly understood. One possibility is that thinned glycocalyx promotes leukocyte recognition and adhesion, thereby facilitating the elimination of pathogens from infected areas. This may represent a protective mechanism developed by the organism during through evolutionary processes. However, if the damage persists and disrupts the dynamic balance of the microcirculation, interstitial edema or organ failure can occur. Thus, we asked the questions, what is the precise composition and structure of the glycocalyx? How is it degraded? What animal models are available to study the relationship between the glycocalyx and sepsis? What glycocalyx biomarkers are found in the blood of patients with sepsis? To determine whether sepsis can be treated by interfering with the glycocalyx, this study provides a systematic summary and discussion of the latest progress in addressing these questions.

Hepatic conditioning results in better lung endothelial cell preservation under hypoxic environment in vitro

BACKGROUND

as we look to extend ex vivo lung perfusion times (EVLP) to improve preservation, the metabolic activity of the lungs will require support from other organ functions. Active functional liver support, including detoxification, synthesis, and regulation, can improve lung preservation during EVLP. This study aimed to demonstrate the effects of hepatic conditioning of the EVLP perfusate on lung endothelium, via the receptor of advanced glycation end-products (RAGE)-nuclear-factor-κB (NF-κB) signaling in vitro.

METHODS

we performed in vitro experiments using human lung microvascular endothelial cells (HLMVECs), human hepatocytes, and perfusate (Steen solution). Four experimental groups: 1) fresh Steen (negative controls, NC), 2) EVLP'ed Steen control, this solution collected after 12 h of EVLP of human lungs, 3) hepatocyte conditioned EVLP'ed Steen (Hep-cond.), and 4) a RAGE inhibitor added in EVLP'ed Steen (RAGE inhibitor). HLMVECs were incubated in each testing condition and exposed to hypoxia (1% O2/8% CO2) for 24 h. Media were collected to investigate NF-κB signaling and endothelial glycocalyx damage.

RESULTS

HLMVECs incubated under hypoxia in EVLP'ed Steen showed significantly upregulated NF-κB signal and endothelial damage denoted by increased glycosaminoglycans and matrix metalloproteinase-2 activity among the groups. The Hep-cond. solution significantly attenuated those findings, while the RAGE inhibitor attenuated the NF-κB signal but not endothelial glycocalyx damage.

CONCLUSION

Our study demonstrates that hepatic function incorporated into EVLP can ameliorate pulmonary endothelial cells injury under hypoxic normothermic perfusion exposure. Our data supports the concept of incorporating other organ functions into an organ perfusion platform, to enhance lung graft preservation.

Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients

Background

Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population. This study compared the performance of traditional logistic regression and machine learning models in predicting adult sepsis mortality.

Objective

To develop an optimum model for predicting the mortality of adult sepsis patients based on comparing traditional logistic regression and machine learning methodology.

Methods

Retrospective analysis was conducted on 606 adult sepsis inpatients at our medical center between January 2020 and December 2022, who were randomly divided into training and validation sets in a 7:3 ratio. Traditional logistic regression and machine learning methods were employed to assess the predictive ability of mortality in adult sepsis. Univariate analysis identified independent risk factors for the logistic regression model, while Least Absolute Shrinkage and Selection Operator (LASSO) regression facilitated variable shrinkage and selection for the machine learning model. Among various machine learning models, which included Bagged Tree, Boost Tree, Decision Tree, LightGBM, Naïve Bayes, Nearest Neighbors, Support Vector Machine (SVM), and Random Forest (RF), the one with the maximum area under the curve (AUC) was chosen for model construction. Model validation and comparison with the Sequential Organ Failure Assessment (SOFA) and the Acute Physiology and Chronic Health Evaluation (APACHE) scores were performed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the validation set.

Results

Univariate analysis was employed to assess 17 variables, namely gender, history of coronary heart disease (CHD), systolic pressure, white blood cell (WBC), neutrophil count (NEUT), lymphocyte count (LYMP), lactic acid, neutrophil-to-lymphocyte ratio (NLR), red blood cell distribution width (RDW), interleukin-6 (IL-6), prothrombin time (PT), international normalized ratio (INR), fibrinogen (FBI), D-dimer, aspartate aminotransferase (AST), total bilirubin (Tbil), and lung infection. Significant differences (p < 0.05) between the survival and non-survival groups were observed for these variables. Utilizing stepwise regression with the "backward" method, independent risk factors, including systolic pressure, lactic acid, NLR, RDW, IL-6, PT, and Tbil, were identified. These factors were then incorporated into a logistic regression model, chosen based on the minimum Akaike Information Criterion (AIC) value (98.65). Machine learning techniques were also applied, and the RF model, demonstrating the maximum Area Under the Curve (AUC) of 0.999, was selected. LASSO regression, employing the lambda.1SE criteria, identified systolic pressure, lactic acid, NEUT, RDW, IL6, INR, and Tbil as variables for constructing the RF model, validated through ten-fold cross-validation. For model validation and comparison with traditional logistic models, SOFA, and APACHE scoring.

Conclusion

Based on deep machine learning principles, the RF model demonstrates advantages over traditional logistic regression models in predicting adult sepsis prognosis. The RF model holds significant potential for clinical surveillance and interventions to enhance outcomes for sepsis patients.

Soluble Proteoglycans and Proteoglycan Fragments as Biomarkers of Pathological Extracellular Matrix Remodeling

Proteoglycans and their proteolytic fragments diffuse into biological fluids such as plasma, serum, urine, or synovial fluid, where they can be detected by antibodies or mass-spectrometry. Neopeptides generated by the proteolysis of proteoglycans are recognized by specific neoepitope antibodies and can act as a proxy for the activity of certain proteases. Proteoglycan and proteoglycan fragments can be potentially used as prognostic, diagnostic, or theragnostic biomarkers for several diseases characterized by dysregulated extracellular matrix remodeling such as osteoarthritis, rheumatoid arthritis, atherosclerosis, thoracic aortic aneurysms, central nervous system disorders, viral infections, and cancer. Here, we review the main mechanisms accounting for the presence of soluble proteoglycans and their fragments in biological fluids, their potential application as diagnostic, prognostic, or theragnostic biomarkers, and highlight challenges and opportunities ahead of their clinical translation.

Immunological alterations in the endothelial barrier: a new predictive and therapeutic paradigm for sepsis

INTRODUCTION

Despite the fact incidence and mortality vary widely among regions, sepsis remains a major cause of morbidity and cost worldwide. The importance of the endothelial barrier in sepsis and infectious diseases is increasingly recognized; however, the underlying pathophysiology of the endothelial barrier in sepsis remains poorly understood.

AREAS COVERED

Here we review the advances in basic and clinical research for relevant papers in PubMed database. We attempt to provide an updated overview of immunological alterations in endothelial dysfunction, discussing the central role of endothelial barrier involved in sepsis to provide new predictive and therapeutic paradigm for sepsis.

EXPERT OPINION

Given its physiological and immunological functions in infectious diseases, the endothelial barrier has been dramatically altered in sepsis, suggesting that endothelial dysfunction may play a critical role in the pathogenesis of sepsis. Although many reliable biomarkers have been investigated to monitor endothelial activation and injury in an attempt to find diagnostic and therapeutic tools, there are no specific therapies to treat sepsis due to its complex pathophysiology. Since sepsis is initiated by both hyperinflammation and immunoparalysis occurring simultaneously, a 'one-treatment-fits-all' strategy for sepsis-induced immune injury and immunoparalysis is bound to fail, and an individualized 'precision medicine' approach is required.

Fluid bolus increases plasma hyaluronan concentration compared to follow-up strategy without a bolus in oliguric intensive care unit patients

Fluid therapy is a fundamental part of supportive therapy in critical care. However, it is also a suspected risk for endothelial glycocalyx degradation which is associated with poor clinical outcomes. This secondary analysis of RESPONSE randomized trial compares the effect of follow-up strategy (FU) on endothelial biomarkers to that of 500 ml crystalloid fluid bolus (FB) in oliguric, hemodynamically optimized intensive care unit (ICU) patients. 130 adult subjects were enrolled in two Finnish ICUs from January 2017 to November 2020. Blood and urine samples of 63 patients in FU group and 67 patients in FB group were collected before and after the intervention and analyzed using enzyme-linked immunosorbent assays. Single fluid bolus, given after median of 3887 ml (interquartile range 2842; 5359 ml) resuscitation fluids in the preceding 24 h, increased plasma hyaluronan concentration compared to the follow-up strategy (difference in medians 29.2 ng/ml with 95% CI [14.5ng/ml; 55.5ng/ml], P < 0.001). No treatment effect was detected in the plasma levels of syndecan-1, , angiopoietin-2, angiopoietin receptors Tie2 and Tie1, or in soluble thrombomodulin in the adjusted median regression analysis. The increase in hyaluronan was independent of its simultaneous renal clearance but correlated moderately with the increase in endothelium-specific Tie1. The follow-up strategy did not show consistent endothelium-sparing effect but protected against hyaluronan increase. The mechanisms and consequences of hyaluronan fluctuations need further clarification. Trial registration: clinicaltrials.gov, NCT02860572. Registered 1 August 2016, https://www.clinicaltrials.gov/study/NCT02860572?term=NCT02860572&rank=1.

Assessment of soluble thrombomodulin and soluble endoglin as endothelial dysfunction biomarkers in seriously ill surgical septic patients: correlation with organ dysfunction and disease severity

BACKGROUND

Sepsis, a complex condition characterized by dysregulated immune response and organ dysfunction, is a leading cause of mortality in ICU patients. Current diagnostic and prognostic approaches primarily rely on non-specific biomarkers and illness severity scores, despite early endothelial activation being a key feature of sepsis. This study aimed to evaluate the levels of soluble thrombomodulin and soluble endoglin in seriously ill surgical septic patients and explore their association with organ dysfunction and disease severity.

METHODOLOGY

A case control study was conducted from March 2022 to November 2022, involving seriously ill septic surgical patients. Baseline clinical and laboratory data were collected within 24 h of admission to the Surgical Intensive Care Unit. This included information such as age, sex, hemodynamic parameters, blood chemistry, SOFA score, qSOFA score, and APACHE-II score. A proforma was filled out to record these details. The outcome of each patient was noted at the time of discharge.

RESULTS

The study found significantly elevated levels of soluble thrombomodulin and soluble endoglin in seriously ill surgical septic patients. The RTqPCR analysis revealed a positive correlation between soluble thrombomodulin and soluble endoglin levels with the qSOFA score, as well as, there was a positive association between RTqPCR soluble thrombomodulin and the SOFA score. These findings indicate a correlation between these biomarkers and organ dysfunction and disease severity.

CONCLUSION

The study concludes that elevated levels of soluble thrombomodulin and soluble endoglin can serve as endothelial biomarkers for early diagnosis and prognostication in seriously ill surgical septic patients.

Syndecan-1 levels predict septic shock in critically ill patients with COVID-19

BACKGROUND

The clinical picture of coronavirus disease 2019 (COVID-19)-associated sepsis is similar to that of sepsis of other aetiologies. The present study aims to analyse the role of syndecan-1 (SDC-1) as a potential predictor of septic shock in critically ill patients with COVID-19.

METHODS

This is a prospective study of 86 critically ill patients due to COVID-19 infection. Patients were followed until day 28 of hospitalization. Vascular biomarkers, such as vascular cell adhesion protein-1, SDC-1, angiopoietin-1 and angiopoietin-2, were quantified upon admission and associated with the need for vasopressors in the first 7 d of hospitalization.

RESULTS

A total of 86 patients with COVID-19 (mean age 60±16 y; 51 men [59%]) were evaluated. Thirty-six (42%) patients died during hospitalization and 50 (58%) survived. The group receiving vasopressors had higher levels of D-dimer (2.46 ng/ml [interquartile range {IQR} 0.6-6.1] vs 1.01 ng/ml [IQR 0.62-2.6], p=0.019) and lactate dehydrogenase (929±382 U/l vs 766±312 U/l, p=0.048). The frequency of deaths during hospitalization was higher in the group that received vasoactive amines in the first 24 h in the intensive care unit (70% vs 30%, p=0.002). SDC-1 levels were independently associated with the need for vasoactive amines, and admission values >269 ng/ml (95% CI 0.524 to 0.758, p=0.024) were able to predict the need for vasopressors during the 7 d following admission.

CONCLUSIONS

Syndecan-1 levels predict septic shock in critically ill patients with COVID-19.

Application of an artificial intelligence for quantitative analysis of endothelial capillary beds in vitro

BACKGROUND

The use of endothelial cell cultures has become fundamental to study angiogenesis. Recent advances in artificial intelligences (AI) offer opportunities to develop automated assessment methods in medical research, analyzing larger datasets.

OBJECTIVE

The aim of this study was to compare the application of AI with a manual method to morphometrically quantify in vitro angiogenesis.

METHODS

Co-cultures of human microvascular endothelial cells and fibroblasts were incubated mimicking endothelial capillary-beds. An AI-software was trained for segmentation of endothelial capillaries on anti-CD31-labeled light microscope crops. Number of capillaries and branches and average capillary diameter were measured by the AI and manually on 115 crops.

RESULTS

The crops were analyzed faster by the AI than manually (3 minutes vs 1 hour per crop). Using the AI, systematically more capillaries (mean 48/mm2 vs 27/mm2) and branches (mean 23/mm2 vs 11/mm2) were counted than manually. Both methods had a strong linear relationship in counting capillaries and branches (r-capillaries = 0.88, r-branches = 0.89). No correlation was found for measurements of the diameter (r-diameter = 0.15).

CONCLUSIONS

The present AI reduces the time required for quantitative analysis of angiogenesis on large datasets, and correlates well with manual analysis.

Organotypic heterogeneity in microvascular endothelial cell responses in sepsis-a molecular treasure trove and pharmacological Gordian knot

In the last decades, it has become evident that endothelial cells (ECs) in the microvasculature play an important role in the pathophysiology of sepsis-associated multiple organ dysfunction syndrome (MODS). Studies on how ECs orchestrate leukocyte recruitment, control microvascular integrity and permeability, and regulate the haemostatic balance have provided a wealth of knowledge and potential molecular targets that could be considered for pharmacological intervention in sepsis. Yet, this information has not been translated into effective treatments. As MODS affects specific vascular beds, (organotypic) endothelial heterogeneity may be an important contributing factor to this lack of success. On the other hand, given the involvement of ECs in sepsis, this heterogeneity could also be leveraged for therapeutic gain to target specific sites of the vasculature given its full accessibility to drugs. In this review, we describe current knowledge that defines heterogeneity of organ-specific microvascular ECs at the molecular level and elaborate on studies that have reported EC responses across organ systems in sepsis patients and animal models of sepsis. We discuss hypothesis-driven, single-molecule studies that have formed the basis of our understanding of endothelial cell engagement in sepsis pathophysiology, and include recent studies employing high-throughput technologies. The latter deliver comprehensive data sets to describe molecular signatures for organotypic ECs that could lead to new hypotheses and form the foundation for rational pharmacological intervention and biomarker panel development. Particularly results from single cell RNA sequencing and spatial transcriptomics studies are eagerly awaited as they are expected to unveil the full spatiotemporal signature of EC responses to sepsis. With increasing awareness of the existence of distinct sepsis subphenotypes, and the need to develop new drug regimen and companion diagnostics, a better understanding of the molecular pathways exploited by ECs in sepsis pathophysiology will be a cornerstone to halt the detrimental processes that lead to MODS.

[Application Value of Novel Coagulation Markers in Predicting Postoperarative Complications in the Early Stage After Liver Transplantation]

Objective

To investigate the relationship between thrombin-antithrombin complex (TAT), plasmin-α 2-plasmininhibitor complex (PIC), soluble thrombomodulin (sTM), and tissue plasminogen activator-inhibitor complex (tPAIC) and postoperative complications in the early stage after liver transplantation (LT).

Methods

We analyzed the perioperative clinical data, including plasma TAT, PIC, sTM, and tPAIC, of 130 post-LT patients admitted to the intensive care unit (ICU), West China Hospital, Sichuan University between December 2021 and November 2022. Patients were divided into two groups, a complication group and a non-complication group, according to whether they experienced complications of Clavien-Dindo (CD) grade Ⅲb and above within 30 days after the surgery. Univariate analysis and binary multivariate logistic regression models were used to determine the risk factors for complications within 30 days post-LT.

Results

The incidence of complications of CD grade Ⅲb and above within 30 days post-LT was 33.1% (43/130). Patients in the complication group had significantly higher scores for the Model for End-Stage Liver Disease (MELD), operative time, intraoperative red blood cell transfusion volume, intraoperative plasma transfusion volume, and plasma TAT, PIC, sTM and tPAIC measured at the time of admission to ICU after the operation than those in the non-complication group did (all P<0.05). Logistic regression showed that for every single U of red blood cells transfused during the transplant surgery, the probabilities of complications within 30 days post-LT increased by 15.1% (95% confidence interval [ C I]: 1.070-1.239, P<0.001) and for the increase of every single TU/mL of plasma sTM measured upon post-LT admission to ICU, the probabilities of complications increased by 13.7% (95% CI: 1.060-1.220, P<0.001).

Conclusion

Plasma sTM measured upon admission to ICU after LT is an independent risk factor for complications within 30 days post-LT, and additional assessment of sTM may help predict complications in the early stage post-LT.

Association Between Endothelial Activation and Stress Index and 28-Day Mortality in Septic ICU patients: a Retrospective Cohort Study

Background: Endothelial Activation and Stress Index (EASIX) is a reliable alternative biomarker of endothelial dysfunction. Because endothelial activation is involved in sepsis pathophysiology, we aimed to investigate the association between EASIX and prognosis in septic patients. Methods: Data were extracted from the Medical Information Mart for Intensive Care (MIMIC) IV database. EASIX scores were calculated using the formula: lactate dehydrogenase (U/L) × creatinine (mg/dL)/platelet count (109/L). Patients were grouped into tertiles according to log2 transformed EASIX. The primary and secondary outcomes were 28-day and 90-day mortality. Cox proportional hazards models, Kaplan-Meier curves, restricted cubic spline curves, and subgroup analyses were conducted to evaluate the association between EASIX and prognosis in septic patients. Results: A total of 7504 patients were included. Multivariable Cox proportional hazards analyses showed that higher log2-EASIX was associated with increased risk of 28-day mortality (HR, 1.10; 95% CI, 1.07-1.13; P < 0.001). Compared with tertile 1, the tertile 2 and 3 groups had higher risk of 28-day mortality [HR (95% CI) 1.24 (1.09-1.41); HR (95% CI) 1.51 (1.31-1.74)]; P for trend < 0.001). Similar results were found for 90-day mortality. Kaplan-Meier curves showed that patients with higher EASIX had lower 28-day and 90-day survival rates. A linear relationship was found between log2-EASIX and 28-day and 90-day mortality. Conclusion: High EASIX was significantly associated with an increased risk of 28-day and 90-day all-cause mortality in patients with sepsis.

Circulating Syndecan-1 Levels Are Associated with Chronological Coagulofibrinolytic Responses and the Development of Disseminated Intravascular Coagulation (DIC) after Trauma: A Retrospective Observational Study

BACKGROUND

The purpose of this study was to evaluate the association between endotheliopathy represented by high levels of circulating syndecan-1 (SDC-1) and coagulofibrinolytic responses due to trauma, which can lead to disseminated intravascular coagulation (DIC).

METHODS

We retrospectively evaluated 48 eligible trauma patients immediately admitted to our hospital and assessed SDC-1 and coagulofibrinolytic parameters for 7 days after admission. We compared the longitudinal changes of coagulofibrinolytic parameters and SDC-1 levels between two groups (high and low SDC-1) according to median SDC-1 value on admission.

RESULTS

The median circulating SDC-1 level was 99.6 (61.1-214.3) ng/mL on admission, and levels remained high until 7 days after admission. Coagulofibrinolytic responses assessed by biomarkers immediately after trauma were correlated with SDC-1 elevation (thrombin-antithrombin complex, TAT: r = 0.352, p = 0.001; antithrombin, AT: r = -0.301, p < 0.001; plasmin-α₂-plasmin inhibitor complex, PIC: r = 0.503, p = 0.035; tissue plasminogen activator, tPA: r = 0.630, p < 0.001). Sustained SDC-1 elevation was associated with intense and prolonged coagulation activation, impairment of anticoagulation, and fibrinolytic activation followed by inhibition of fibrinolysis, which are the primary responses associated with development of DIC in the acute phase of trauma. Elevation of circulating SDC-1 level was also associated with consumption coagulopathy and the need for transfusion, which revealed a significant association between high SDC-1 levels and the development of DIC after trauma (area under the curve, AUC = 0.845, cut-off value = 130.38 ng/mL, p = 0.001).

CONCLUSIONS

High circulating levels of syndecan-1 were associated with intense and prolonged coagulation activation, impairment of anticoagulation, fibrinolytic activation, and consumption coagulopathy after trauma. Endotheliopathy represented by SDC-1 elevation was associated with trauma induced coagulopathy, which can lead to the development of DIC.

Serum Thrombomodulin Level Can Predict Mortality in Patients With Sepsis?

Background

Thrombomodulin (TM) is a type-1 trans-membrane glycoprotein on endothelial cells which is known to be involved in various biochemical pathways. TM can be detected in biological fluids such as blood and urine under many forms. Soluble thrombomodulin (sTM), consist of various particles of TM, is the predominant agent which is created by enzymatic or chemical catalysis of the whole protein under divergent conditions. TM plays a vital role in protein C system and is crucial in the pathogenesis of Sepsis.

Objective

To identify the serum level of soluble thrombomodulin (sTM) in groups of patients: sepsis and septic shock including their survival and fatal in-hospital outcome; and validate the death prediction of serum sTM in patients with sepsis.

Methods

This prospective observational study was conducted in 63 patients who were diagnosed with sepsis, septic shock according to Sepsis 3 criteria at the ICU Department of Hue Central Hospital, Vietnam, from 3/2022 to 3/2023.

Results

Twenty participants developed septic shock (31.7%), morality within 28-days was 19 patients (30.2%), 22 patients complicated with acute kidney injury that necessitated renal replacement therapy (34.9%), 30 patients required mechanical ventilation (47.6%), the median length of ICU stay was 8 (3-28) days. Serum level of lactate and creatinine were significantly higher in septic shock group compared with sepsis and survival group (p<0.05). The median sTM level in septic shock group and fatal group were 4.68(3.38-6.46) ng/mL and 4.68 (1.69-6.46) ng/mL, respectively. These results were significantly higher than sepsis group [3.62 (1.51-1.94) ng/mL] and survival group [3.73 (1.51-5.9) ng/mL] (p<0.05). The death predictive power of DIC score, APACHE II score, creatinine, sTM and SOFA presented with AUC values of 0.723, 0.726, 0.777, 0.803 and 0.807, respectively. There were no significant difference of serum level IL-6 and PCT between survival and fatal group. The median DIC score in fatal group was 7 (3-7), which was significantly higher than survival group 4 (2-7) (p= 0.001).

Conclusion

Sepsis is a common diagnosis among ICU settings which links the critically ill patients to higher complications and mortalities. Serum level of sTM in septic shock and fatal groups were significantly higher than sepsis and survival groups. sTM is a reliable marker and should be used in predict severity and mortality in sepsis patients.

Syndecan-1: A Novel Diagnostic and Therapeutic Target in Liver Diseases

Syndecan-1 (SDC-1), known as a coreceptor of various growth factors or an integrin binding partner, regulates various cell behaviours. Under certain pathological conditions, SDC-1 is shed from the cell surface and plays a protective or pathogenic role in various diseases. In the liver, SDC-1 is highly expressed in hepatocytes, where it is localized on the basolateral surface. It is critical to the cellular and molecular functions of hepatocytes, including their attachment to hepatitis viruses. Previous studies have reported that SDC-1 may function as a novel and promising diagnostic and therapeutic marker for various liver diseases, such as drug-induced liver injury, liver fibrosis, and liver cancer. In this review, we summarize related research and highlight the mechanisms by which SDC-1 participates in the pathogenesis of liver diseases, as well as its potential diagnostic and therapeutic applications. This review is expected to lay the foundation for further therapeutic strategies to target SDC-1 in liver diseases.