Urinary Metabolic Biomarker and Pathway Study of Hepatitis B Virus Infected Patients Based on UPLC-MS System

Wang X (2013) Urinary Metabolic Biomarker and Pathway Study of Hepatitis B Virus Infected Patients Based on UPLC-MS System. PLoS ONE 8(5): e64381. doi:10.1371/journal.pone.0064381 Urinary Metabolic Biomarker and Pathway Study of Hepatitis B Virus Infected Patients Based on UPLC-MS System Aihua Zhang 0 Hui Sun 0 Ying Han 0 Guangli Yan 0 Xijun Wang 0 Anand S. Mehta, Drexel University College of Medicine, United States of America 0 National TCM Key Lab of Serum Pharmacochemistry, Key Lab of Chinmedomics, Heilongjiang University of Chinese Medicine, and Key Pharmacometabolomics Platform of Chinese Medicines , Harbin , China Hepatitis B virus (HBV) is the fatal consequence of chronic hepatitis, and lack of biomarkers has been a long standing bottleneck in the clinical diagnosis. Metabolomics concerns with comprehensive analysis of small molecules and provides a powerful approach to discover biomarkers in biological systems. Here, we present metabolomics analysis applying ultraperformance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry. (UPLC-Q-TOFHDMS) to determine metabolite alterations in HBV patients. Most important permutations are elaborated using multivariate statistical analysis and network analysis that was used to select the metabolites for the noninvasive diagnosis of HBV. In this study, the total 11 urinary differential metabolites were identified and contributed to HBV progress involving several key metabolic pathways by using pathway analysis with MetPA, which are promising biomarker candidates for diagnostic research. More importantly, of 11 altered metabolites, 4 metabolite markers were effective for the diagnosis of human HBV, achieved a satisfactory accuracy, sensitivity and specificity, respectively. It demonstrates that metabolomics has the potential as a non-invasive tool to evaluate the potential of these metabolites in the early diagnosis of HBV patients. These findings may be promising to yield a valuable insight into the pathophysiology of HBV and to advance the approaches of diagnosis, treatment, and prevention. - Funding: This work was supported by grants from the Key Program of Natural Science Foundation of State (Grant No. 90709019), the National Specific Program on the Subject of Public Welfare (Grant No. 200807014), National Key Subject of Drug Innovation (Grant No. 2009ZX09502-005), and National Program on Key Basic Research Project of China (Grant No. 2005CB523406). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Hepatitis B continues to be a worldwide clinical problem with approximately 360 million people chronically infected [1]. In China, about 120 million people are carriers of HBV, accounts for 30% of hepatic cirrhosis globally [2]. During a five-year period, 10%20% of patients with chronic hepatitis develop cirrhosis [3]. Cirrhosis precedes most cases of hepatocellular carcinoma (HCC), with 70%90% of HCC developing from a background of chronic liver cirrhosis [4]. These data clearly indicate the critical importance of early diagnosis of hepatic cirrhosis. Although liver biopsy (LB) is currently recommended as the gold standard method of staging fibrosis in patients with chronic HBV, it has several disadvantages such as poor patient compliance, sampling error, limited usefulness for dynamic surveillance and follow-up. Therefore, a reliable, noninvasive diagnostic system to predict and assess treatment and prognosis of liver cirrhosis is needed. Among them, metabolomics analysis is a powerful tool to advance the diagnosis, treatment, and prevention of human diseases [5,6]. The field of metabolomics continues to grow rapidly over the last decade and has been proven to be a powerful technology in predicting and explaining complex phenotypes in diverse biological systems, might be the sole technology capable of detecting complex, biologically essential changes [7]. Metabolomics involves the establishment of relationships between phenotype and a metabolic signature, which are key aspects of biological function. Recent developments have suggested that understanding changes in metabolite profiles will confer a high degree of predictive accuracy in terms of understanding the fundamental mechanisms resulting in perturbations of the metabolic state [811]. As such, metabolomics is fast becoming an important discovery tool for new diagnostic and prognostic biomarkers. It is envisioned that this will provide new avenues towards preventive medicine and prognostic strategies for tailored therapeutic and personalized nutrition management. The development of metabolomics approaches and the new generation of biomarker patterns will provide the opportunity to associate complex metabolic regulations to disease [1215]. It is hoped that the information derived from metabolite profiling will make it possible to suggest individualized therapies that more effectively treat disease. Metabolomics has been used to characterize metabolic signatures for various diseases including depression, cancers, diabetes, Parkinsons disease and Alzheimers Disease [16]. Traditional markers of classical clinical chemistry and histopathology method are not region-specific and only increase significantly after substantial disease injury [1719]. Therefore, more early markers of disease are eagerly needed. Incidence of HBV is rising at a rapid rate and the sensitivity and specificity of the clinical diagnosis of HBV is quite low [20]. However, sensitivity of current diagnostic markers is relatively low, difficult to get outcome immediately and not particularly effective in separating cases of HBV from other non-HBV disorders. Fortunately, the rapid development of metabolomics technology platforms has been used to explore the particular metabolites, potentially diagnostic and prognostic biomarkers for deep understanding the essence of HBV. This paper was designed to investigate a comprehensive metabolome of patients HBVinduced cirrhosis by UPLC-Q-TOF-HDMS combined with pattern recognition methods to identify urine biomarkers for HBV, explore the diagnostic possibilities, and enhance the understanding of its mechanisms. Materials and Methods Ethical Statement Signed and informed consent was obtained from each participant, and the project was approved by the ethics committee of Heilongjiang University of Chinese Medicine, and was conducted according to the Declaration of Helsinki Principles. Subjects Patients were collected from Hospital of Heilongjiang University of Chinese Medicine, China. HBV (n = 13) patients and healthy volunteers (n = 11) were recruited in this study. The outcomes of Health Survey Questionnaire in patients with HBV and the normal controls were assessed, and the related clinical information including gender, age, body mass index, basic syndromes of di (...truncated)