© Borgis - New Medicine 2/2014, s. 57-62
*Tomasz Kryczka1, Piotr Małkowski2 , Dorota Zarębska-Michaluk3, Wiesław Kryczka3, 4
The perspectives of the use of metabolomics measures in viral hepatitis
1Department of Medical Biology, Medical University of Warsaw, Warsaw, Poland
Head of Department: Gabriela Olędzka, PhD, DSc
2Department of Surgical & Transplant Nursing, Medical University of Warsaw, Warsaw, Poland
Head of Department: prof. Piotr Małkowski, MD, PhD, DSc
3Department of Infectious Diseases, Provincial Hospital of Kielce, Poland
Head of Department: Wiesław Kryczka, MD, PhD, DSc
4The Faculty of Health Sciences, Jan Kochanowski University (JKU) in Kielce, Poland
Head of the Faculty: Wiesław Kryczka, MD, PhD, DSc
Metabolomics is one of the ‘-omic’ sciences - beside genomics, transcriptomics and proteomics - belonging to systems biology. It represents an emerging and powerful discipline that provides an explanation of accurate small molecule fingerprints related to the disease. It is an interdisciplinary field of science, which combines analytical chemistry, new technology platforms, mass spectrometry, and NMR spectroscopy with a sophisticated data analysis. In this review we highlight the importance of metabolomics as a potential tool for uncovering metabolic changes in HBV and HCV infections of the liver and for discovering novel biomarkers to improve diagnosis, management and prognosis of the liver diseases.
CHRONIC VIRAL HEPATITIS
The hepatitis B virus (HBV) infection is still one of the most challenging public health burdens although a safe and effective vaccine has been available since the 80’s. It is estimated that nearly one third of the global population has serological evidence of the past or present HBV infection. Approximately 350 million people worldwide are chronically infected with HBV, of whom 1 million die every year of HBV-related liver consequences (1).
The hepatitis C virus (HCV) infection is a leading cause of liver disease worldwide. More than 170 million people are chronically infected with HCV globally and approximately 20% of them develop cirrhosis over a period of 20 years. Patients with established cirrhosis are at high risk for decompensation and development of hepatocellular carcinoma; it is estimated that 350 000 deaths occur every year as a result of these severe complications of the HCV infection (2).
These data clearly indicate a crucial importance of an early and accurate diagnosis of liver diseases. Diagnosing liver diseases and assessing the severity of liver injury include biochemical markers, such as activity of serum transaminases (aspartate transaminase AST, alanine transaminase ALT), γ-glutamyl transpeptidase (γ-GTP), alkaline phosphatase (ALP), as well as protrombin time, serum albumin concentration and blood counts (3). Then, patients are subjected to diagnostic imaging, such as ultrasound and computed tomography (CT). In respect to all patients presenting increased aminotransferase levels, with chronic liver diseases of unclear etiology and with the history of enhanced risk of hepatitis virus transmission HBV and HCV, the diagnostics should be performed.
The diagnosis of HBV infection based on the detection of series serological markers of HBV, such as hepatitis B surface antigen (HBsAg) and antibody (anti-HBs), hepatitis Be antigen (HBeAg) and antibody (anti-HBe) and antibody for hepatitis core antigen (anti-HBc) by serologic assays (radioimmunoassays RIA or enzyme-linked immunoassay EIA). Polymerase chain reaction (PCR) assays allow to directly determine the hepatitis B virus DNA (HBVDNA) in serum (4).
For a diagnosis of the hepatitis C, serologic and nucleic acid-based molecular assays are also available. In clinical practice antibodies against HCV epitopes are detected by 3rd generation EIA test with a high specificity and sensitivity of more than 99%. Positive serologic results require a confirmation by molecular tests for detection of HCVRNA to differentiate between the chronic hepatitis C and a resolved HCV infection. HCVRNA measurement is routinely performed using PCR. HCV is heterogeneous and until recently six genotypes (1-6) and multiple (a, b, c, d...) subtypes have been characterized. Since HCVRNA was detected, genotyping and HCV RNA load assessment by molecular nucleic acid-based tests is mandatory in every patient who considers antiviral therapy. It determines the treatment duration, a ribavirin (RBV) dose and even success rate (5).
Finally, a liver biopsy is recommended to evaluate the severity of liver diseases for patients with chronic hepatitis. Currently used scoring systems assessed histologic lesions using two separate scores, one for the necroinflammatory stage and the other for the stage of fibrosis (6). Although a liver biopsy remains the reference method for determination of liver fibrosis, it has several disadvantages such as poor patient compliance, sampling error, limited usefulness for dynamic surveillance and follow-up. Alternative non-invasive methods can now be used to assess a disease severity. Liver stiffness measurement and panels of biomarkers of fibrosis can be performed instead of liver biopsy at a safe level of predictability (4, 5).
All patients with HBsAg positive chronic hepatitis should be considered for antiviral therapy. The decision of treatment initiation is based on the HBVDNA serum level, ALT activity and the severity of liver disease. Two drug classes are available for the treatment of chronic HBV infection, the immune modulator interferon α (recombinant or pegylated pegIFN) and nucleoside or nucleotide analogs. Analogs act as reverse transcriptase inhibitors of the HBV polymerase. Currently, the nucleoside analogs lamivudine (LMV), telbivudine (LdT), entecavir (ETV) and nucleotide analogs adefovir dipivoxil (ADV), tenofovir disoproxil (TDF) are also available (4).
The goal of antiviral therapy of chronic HCV infection is to cure hepatitis C by a sustained virus eradication. It is defined as a negative serum HCVRNA six months after the end of the treatment (sustained virological response SVR). The current therapy recommendation is based on HCV genotype and a viral load before and during the treatment. Standard antiviral regimen consisted of pegIFNα and RBV results in SVR in 40 to 50% patients infected with genotype 1 or 4 and 80% of those infected with genotype 2 or 3 (7). The outcome of a double therapy depends also on host factors, such as age, race, BMI, and a stage of liver fibrosis (8). Recent efforts to improve the rate of SVR have been focused on oral direct-acting antiviral agents. Within this class of drugs, telaprevir and boceprevir are currently available for treating patients infected with genotype 1, with a higher success rate compared to a standard therapy (9).
PLACE OF METABOLOMICS AMONG -OMICS.
With advances in technology and the ability to collect and process enormous amounts of data, the progress of life sciences has seen a change from a reductionist approach towards that provided by systems biology, that is, measuring biological aspects of a whole system and its interaction with its surroundings, rather than targeting one single part of it. In today’s research world, -omics techniques such as proteomics, transcriptomics, genomics and metabolomics have become an integral part of systems biology. However, metabolomics is a window that offers a perspective distinct from the lenses of genomics, transcriptomics, and proteomics (10-13).
Metabolomics, an emerging and powerful discipline, reveals homeostatic imbalances in biological systems, and has the capability of providing comprehensive information. It enables the parallel assessment of the levels of a broad range of endogenous and exogenous metabolites, and has been shown to have a great impact on the investigation of physiological status, diagnosing diseases, discovering biomarkers, and identifying perturbed pathways due to disease or treatment. Metabolomics adopts a „top-down” strategy to reflect the function of organisms from terminal symptoms of metabolic network in a holistic context. It can provide a panoramic view of abundance changes of endogenous metabolites in monitoring cellular responses to perturbations (e.g. diseases or drug treatments) (11, 14-18).
Assessing the origin of metabolomics brings us far back to the history of bioanalytical sciences before the terms „metabolome”, „metabonomics”, and „metabolomics” were finally accepted by the scientific community. Both terms, metabonomics and metabolomics, describe in a broad manner the study of the metabolome, which was first defined as a collective set of metabolites produced or present in a biosystem. The most often cited definition of metabonomics is the one proposed by Nicholson et al.: ‘Metabonomics is defined as the quantitative measurement of the dynamic multi-parametric metabolic response of living systems to pathophysiological stimuli or genetic modification’ (19). For metabolomics a very similar definition is often used: ‘The study of the quantitative complement of metabolites in a biological system and changes in metabolite concentrations or fluxes related to genetic or environmental perturbations. Studies are typically holistic in nature though targeted studies are also encompassed in the term metabolomics’ (20). Then, metabolomics is the study of metabolic changes in biological systems and provides ‘the small molecule fingerprints’ related to the disease. Importantly, metabolomics’ approaches have developed in many areas of biomedical research and recently demonstrated significant potential for example in toxicology studies, nutritional effects, metabolic consequences of genetic modifications, inborn errors of metabolism, diabetes, cancer diagnostics, physiology, diagnostics, functional genomics, pharmacology, toxicology, nutrition and diagnosing of neurological diseases, and etc (example ref.: 10, 11, 15, 16, 18, 20-29).
Metabolomics in its practice combines high-throughput analytical chemistry, typically, methodologies based upon mass spectrometry or nuclear magnetic resonance spectroscopy, with multivariate data analysis. There is no single analytical technique that is suited to the precise and accurate identification and quantification of all the metabolites in question. Regardless of the analytical set up, metabolomics studies can be divided into two different types: targeted and non-targeted approaches, depending on at which stage the metabolite identification is performed during the data processing. Non-targeted metabolomics is used for global metabolome analysis, that is, a comprehensive analysis of all the measurable analytes in a sample. In a targeted metabolomics strategy, predefined metabolite-specific signals (by selected reaction monitoring (SRM) by tandem mass spectrometry (MS/MS), or selected ion recording (SIR) by GC-MS) are often used to determine precisely and accurately relative abundancies and concentrations of a limited number of pre-known and expected endogenous metabolites (15, 16).