Metabolomics Study Of Hepatitis B Virus-induced Acute-on-chronic Liver Failure Treated With Artificial Liver Support System

According to the report of WHO,2 billion people have been infected by HBV globally, of whom 350 million is chronic HBV infection. about I million people die of HBV infection induced liver failure, liver cihhrosis and HCC each year. In China, chronic HBV infection by now is about 93 million, of whom about 20 million is chronic HBV hepatitis patients. End stage liver diseases induced by various causes each year is about 8 million, and 500 thousand of whom died of liver diseases. During liver failure, there are cumulations of a lot of endogenous substances, such as bilirubin, ammonium, glutamine, lactate, aromatic amino acids, free fatty acid, phonel, mercaptans, benzodiazepines and proinflammatory cytokines. Liver failure is a severe sympotom with very poor prognosis for the reason of massive necrosis of hepatocytes, the motality of intensive medicine care is as high as 60%-80%. The standard treatment of acute liver failure is orthotopic liver transplantation, however, because of limited donor livers, lots of patients died while waiting on the transplantation list. Artificial liver support system (ALSS) is an unique and effective liver failure cure plan, and profoundly decreases the motality of liver failure patients. With ALSS, recovery rate of acute, subacute severe hepatitis improved from 20% to 80%, chronic severe hepatitis from 5.6% to 48.4%. Nevertheless, clinically patients with similar biochemical indices had very different outcome, some recovery while others die. To date, there is still no satisfing predictive index. ALSS cause tremendous changes at the metabolites level, however, there is no study on the effect of ALSS at the metabolomic level yet. This study applies ultraperformance liquid chromotography- mass spectromatry technique to study the difference of plasma metabolite between different outcomes of acute on chronic HBV induced liver failure patients and between before and after the ALSS treatment.50 AOCLF patients were recruited each of whom accepted at least 2 sessions of ALSS (a total of 296 sessions), and the serum was analysed by UPLC Q-TOF MS. Normalization, PCA and OPLS analysis were performed by Masslynx and Simca P software.An metabolomic OPLS model was constucted using Simca-P+12.0 for prognosis of ACOLF. This model was based on the samples collected right before the first ALSS treatment rather than later ones because of comparable model efficacy and earlier time point. The concordance statistics of our model was 0.968 (95% CI [0.951.0.985]) which is superior to that of the MELD score (0.737,95% CI [0.578,0.896]). Three categories of markers were identified:lysophosphatidylcholine, primary fatty acid amides and conjugated bile acids. Lysophosphatidylcholine and conjugated bile acids were protect factors of living and primary fatty acid amides were risk factors. The cut-off point of predictive value from our model was greater than or equal to 0.196, which was the best discriminant of recovery and non-recovery group, with sensitivity 95% and specificity 87%. Our metabolomic model based on plasma UPLC-MS profile analysis provided not only excellent discrimination and prediction of the prognosis of HBV induced acute-on-chronic liver failure but also early and precise warning of liver transplantation.The serum metabolomic change due to ALSS treatment of ACOLF is analysed. PCA plot indicated almost identical metabolic track after ALSS. OPLS model descriminated the treatment effect perfectly and p value of the model by CV-ANOVA test was 8.7×10-10.8 biomarkers were identified according to the descending order of VIP. In PCA plot, prognosis was the main grouping factor, while the change according to ALSS was mainly showed on the y axies (the 2nd PC), indicating the status of patients is another deciding factor of prognosis besides ALSS. Among the most different substances, LPC level elevated through the treatment, GCDCA level decreased though the treatment. This effect was constant in consective three ALSS treatments. This result clarified the effect of ALSS in improving the internal environment on small molecule level; at the same time, the dynamic processes of biomarkers during multi-ALSS treatment were analysed. Also, we analysed the corelations between these dynamic changes of bimarkers and the pronosis.