MMP-7: The Next Best Serum Biomarker for Biliary Atresia?

Proteomics Defines Plasma Biomarkers for the Early Diagnosis of Biliary Atresia

Early diagnosis of biliary atresia (BA) is crucial for improving the chances of survival and preserving the liver function of pediatric patients with BA. Herein, we performed proteomics analysis using data-independent acquisition (DIA) and parallel reaction monitoring (PRM) to explore potential biomarkers for the early diagnosis of BA compared to other non-BA jaundice cases. Consequently, we detected and validated differential protein expression in the plasma of patients with BA compared to the plasma of patients with intrahepatic cholestasis. Bioinformatics analysis revealed the enriched biological processes characteristic of BA by identifying the differential expression of specific proteins. Signaling pathway analysis revealed changes in the expression levels of proteins associated with an alteration in immunoglobulin levels, which is indicative of immune dysfunction in BA. The combination of polymeric immunoglobulin receptor expression and immunoglobulin lambda variable chain (IGL c2225_light_IGLV1-47_IGLJ2), as revealed via machine learning, provided a useful early diagnostic model for BA, with a sensitivity of 0.8, specificity of 1, accuracy of 0.89, and area under the curve value of 0.944. Thus, our study identified a possible effective plasma biomarker for the early diagnosis of BA and could help elucidate the underlying mechanisms of BA.

Accurate prediction of biliary atresia with an integrated model using MMP-7 levels and bile acids

BACKGROUND

Biliary atresia (BA) is a rare fatal liver disease in children, and the aim of this study was to develop a method to diagnose BA early.

METHODS

We determined serum levels of matrix metalloproteinase-7 (MMP-7), the results of 13 liver tests, and the levels of 20 bile acids, and integrated computational models were constructed to diagnose BA.

RESULTS

Our findings demonstrated that MMP-7 expression levels, as well as the results of four liver tests and levels of ten bile acids, were significantly different between 86 BA and 59 non-BA patients (P < 0.05). The computational prediction model revealed that MMP-7 levels alone had a higher predictive accuracy [area under the receiver operating characteristic curve (AUC) = 0.966, 95% confidence interval (CI): 0.942, 0.989] than liver test results and bile acid levels. The AUC was 0.890 (95% CI 0.837, 0.943) for liver test results and 0.825 (95% CI 0.758, 0.892) for bile acid levels. Furthermore, bile levels had a higher contribution to enhancing the predictive accuracy of MMP-7 levels (AUC = 0.976, 95% CI 0.953, 1.000) than liver test results. The AUC was 0.983 (95% CI 0.962, 1.000) for MMP-7 levels combined with liver test results and bile acid levels. In addition, we found that MMP-7 levels were highly correlated with gamma-glutamyl transferase levels and the liver fibrosis score.

CONCLUSION

The innovative integrated models based on a large number of indicators provide a noninvasive and cost-effective approach for accurately diagnosing BA in children. Video Abstract (MP4 142103 KB).

Serum matrix metalloproteinase-7 levels in infants with cholestasis and biliary atresia

Background

The aim of this study was to evaluate the serum level of matrix metalloproteinase 7 (MMP7) in infants with cholestasis and the diagnostic values of this biomarker to differentiate biliary atresia (BA) from other causes of cholestasis.

Methods

This multi-center study is conducted during 2 years in Mofid children’s hospital and Children’s Medical Center, Pediatrics Center of Excellence Tehran, Iran. 54 infants with cholestasis were enrolled in this study with a control group consists of 41 healthy infants with the same age. Serum samples were taken from all these patients to assess serum levels of MMP7, Gamma-glutamyl Transferase (GGT). For each biomarker, we calculated the sensitivity and specificity and other statistical characteristics.

Results

There were 89 subjects, 22 patients with BA, 32 patients with non-BA cholestasis and 41 subjects as control group. The mean serum MMP7 levels in BA, non-BA cholestasis and control group was 15.91 ng/ml ± 6.64, 4.73 ng/ml ± 2.59 and 0.49 ng/ml ± 0.33, respectively. The best cut-off point is calculated 7.8 ng/ml for MMP7 and 434.5 U/L for GGT. The area under curve (AUC) for these two markers are 0.988 ± 0.008 and 0.854 ± 0.052, respectively. The sensitivity and specificity of MMP7 to differentiate biliary atresia from nonbiliary atresia cholestasis in our study was 95.5% and 94.5%, respectively. The sensitivity and specificity of GGT was 77.3% and 77.8%, respectively. These results show that the MMP7 has more sensitivity and specificity in differentiation.

Conclusion

MMP7 demonstrated good accuracy to differentiate biliary atresia from other causes of cholestasis.

Neonatal Cholestasis: Updates on Diagnostics, Therapeutics, and Prevention

Cholestatic jaundice is a common presenting feature of hepatobiliary and/or metabolic dysfunction in the newborn and young infant. Timely detection of cholestasis, followed by rapid step-wise evaluation to determine the etiology, is crucial to identify those causes that are amenable to medical or surgical intervention and to optimize outcomes for all infants. In the past 2 decades, genetic etiologies have been elucidated for many cholestatic diseases, and next-generation sequencing, whole-exome sequencing, and whole-genome sequencing now allow for relatively rapid and cost-effective diagnosis of conditions not previously identifiable via standard blood tests and/or liver biopsy. Advances have also been made in our understanding of risk factors for parenteral nutrition-associated cholestasis/liver disease. New lipid emulsion formulations, coupled with preventive measures to decrease central line-associated bloodstream infections, have resulted in lower rates of cholestasis and liver disease in infants and children receiving long-term parental nutrition. Unfortunately, little progress has been made in determining the exact cause of biliary atresia. The median age at the time of the hepatoportoenterostomy procedure is still greater than 60 days; consequently, biliary atresia remains the primary indication for pediatric liver transplantation. Several emerging therapies may reduce the bile acid load to the liver and improve outcomes in some neonatal cholestatic disorders. The goal of this article is to review the etiologies, diagnostic algorithms, and current and future management strategies for infants with cholestasis.

Development and Assessment of Screening Nomogram for Biliary Atresia Based on Hepatobiliary Ultrasonographic Features

Objectives: Biliary atresia (BA) is a rare neonatal liver disease of which the early diagnosis remains a challenge for clinicians. Our center has established a nomogram diagnostic model based on clinical characteristics and liver function characteristics. We aim to develop and validate a nomogram that includes additional ultrasound and finds hepatobiliary abnormality with better BA early screening performance. Methods: In this single-center, retrospective cohort analysis, 1,001 neonatal obstructive jaundice (NOJ) patients between 2012 and 2015 were enrolled. Multivariable analysis was used to identify clinical characteristics, laboratory liver function characteristics, and ultrasonic features that may early screen BA. A nomogram was developed to predict the probability of BA using multiple logistic regression analysis. This nomogram was subsequently validated using another cohort of 501 NOJ patients between 2015 and 2017. Calibration curve analysis and decision curve analyses were performed to evaluate and interpret the nomogram's clinical benefits. Results: Gender, direct bilirubin (DB), alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), fasting gallbladder visibility, fasting gallbladder filling, and common bile duct visibility were found to have profound statistical significance between the BA and non-BA groups (P < 0.05). The significant features were used to build the nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) value of the novel nomogram (0.87) was superior to those of the former nomogram (0.83) and GGT alone (0.81) in the prediction of BA. The calibration curve revealed a close resemblance between the predicted and actual BA probabilities. Also, the net benefit from the decision curve analysis (DCA) of the nomogram (0.54) was superior to those of the former nomogram (0.49) and GGT alone (0.45) at 80% of threshold possibility. Conclusions: The nomogram has demonstrated better performance for BA screening by including additional information of the US finding, holding a promising future as a non-invasive method for BA patients.

Discovery of Candidate Stool Biomarker Proteins for Biliary Atresia Using Proteome Analysis by Data-Independent Acquisition Mass Spectrometry

Biliary atresia (BA) is a destructive inflammatory obliterative cholangiopathy of the neonate that affects various parts of the bile duct. If early diagnosis followed by Kasai portoenterostomy is not performed, progressive liver cirrhosis frequently leads to liver transplantation in the early stage of life. Therefore, prompt diagnosis is necessary for the rescue of BA patients. However, the prompt diagnosis of BA remains challenging because specific and reliable biomarkers for BA are currently unavailable. In this study, we discovered potential biomarkers for BA using deep proteome analysis by data-independent acquisition mass spectrometry (DIA–MS). Four patients with BA and three patients with neonatal cholestasis of other etiologies (non-BA) were recruited for stool proteome analysis. Among the 2110 host-derived proteins detected in their stools, 49 proteins were significantly higher in patients with BA and 54 proteins were significantly lower. These varying stool protein levels in infants with BA can provide potential biomarkers for BA. As demonstrated in this study, the deep proteome analysis of stools has great potential not only in detecting new stool biomarkers for BA but also in elucidating the pathophysiology of BA and other pediatric diseases, especially in the field of pediatric gastroenterology.

Matrix Metalloproteinases as Potential Biomarkers and Therapeutic Targets in Liver Diseases

Chronic liver diseases, characterized by an excessive accumulation of extracellular matrix (ECM) resulting in scar tissue formation, are a growing health problem causing increasing morbidity and mortality worldwide. Currently, therapeutic options for tissue fibrosis are severely limited, and organ transplantation is the only treatment for the end-stage liver diseases. During liver damage, injured hepatocytes release proinflammatory factors resulting in the recruitment and activation of immune cells that activate quiescent hepatic stellate cells (HSCs). Upon activation, HSCs transdifferentiate into highly proliferative, migratory, contractile and ECM-producing myofibroblasts. The disrupted balance between ECM deposition and degradation leads to the formation of scar tissue referred to as fibrosis. This balance can be restored either by reducing ECM deposition (by inhibition of HSCs activation and proliferation) or enhancing ECM degradation (by increased expression of matrix metalloproteinases (MMPs)). MMPs play an important role in ECM remodeling and represent an interesting target for therapeutic drug discovery. In this review, we present the current knowledge about ECM remodeling and role of the different MMPs in liver diseases. MMP expression patterns in different stages of liver diseases have also been reviewed to determine their role as biomarkers. Finally, we highlight MMPs as promising therapeutic targets for the resolution of liver diseases.

Diagnostic Value and Effectiveness of an Artificial Neural Network in Biliary Atresia

Objectives: Biliary atresia (BA) is a devastating pediatric liver disease. Early diagnosis is important for timely intervention and better prognosis. Using clinical parameters for non-invasive and efficient BA diagnosis, we aimed to establish an artificial neural network (ANN). Methods: A total of 2,384 obstructive jaundice patients from 2012 to 2017 and their 137 clinical parameters were screened for eligibility. A standard binary classification feed-forward ANN was employed. The network was trained and validated for accuracy. Gamma-glutamyl transpeptidase (GGT) level was used as an independent predictor and a comparison to assess the network effectiveness. Results: We included 46 parameters and 1,452 patients for ANN modeling. Total bilirubin, direct bilirubin, and GGT were the most significant indicators. The network consisted of an input layer, 3 hidden layers with 12 neurons each, and an output layer. The network showed good predictive property with a high area under curve (AUC) (0.967, sensitivity 97.2% and specificity 91.0%). Five-fold cross validation showed the mean accuracy for training data of 93.2% and for validation data of 88.6%. Conclusions: The high accuracy and efficiency demonstrated by the ANN model is promising in the noninvasive diagnosis of BA and could be considered as in a low-cost and independent expert diagnosis system.