Peer-review started: May 7, 2015
First decision: August 11, 2015
Revised: November 23, 2015
Accepted: December 17, 2015
Article in press: December 18, 2015
Published online: January 8, 2016
Processing time: 252 Days and 13.7 Hours
Metabonomics has recently been widely used to discover the pathogenesis and find potential metabolic markers with high sensitivity and specificity. Furthermore, it develops new diagnosis and treatment methods, increases early phase diagnosis rates of certain diseases and provides a new basis for targeted therapy. This review mainly analyzes the research progress of the metabonomics of hepatitis B virus (HBV)-related hepatic diseases, hoping to discover some potential metabolic markers for identification of HBV-related hepatic diseases from other etiologies and for HBV-related hepatitis, liver cirrhosis and hepatocellular carcinoma. This can contribute to early discovery, diagnosis and treatment, eventually increasing the survival rate of HBV-related hepatic diseases.
Core tip: This review mainly analyzes the research progress of the metabonomics of hepatitis B virus (HBV)-related hepatic diseases, hoping to discover some potential metabolic markers which can distinguish HBV-related hepatic diseases from other etiologies and discover potential metabolic markers of HBV-related hepatitis, liver cirrhosis and hepatocellular carcinoma, which can contribute to early discovery, diagnosis and treatment.
- Citation: Hou Q, Duan ZJ. Metabonomic window into hepatitis B virus-related hepatic diseases. World J Hepatol 2016; 8(1): 1-8
- URL: https://www.wjgnet.com/1948-5182/full/v8/i1/1.htm
- DOI: https://dx.doi.org/10.4254/wjh.v8.i1.1
The main function of the liver is the synthesis and metabolism of various proteins, polysaccharides and fats and the detoxification of the body’s normal metabolic wastes, such as uric acid, drugs and chemical products[1,2]. There are many hepatic diseases that threaten health. However, because of a lack of effective early diagnosis methods, a large number of the diseases are in the middle to late stages when detected, which seriously affects the prognosis. Therefore, it is important to find tumor markers with high sensitivity and specificity as well as to elucidate the pathogenesis.
Metabonomics, a branch of systematic biology, is a recent newly developing subject. It aims to explore biological systems, like the changes in metabolites of the cells, tissues and certain organisms in the environment of exogenous stimulations, especially studying metabolites weighing less than 1000. Metabonomics integrates gene regulation, post-transcriptional regulation and the interaction of the pathways together, which makes different metabolites manifest significant biological phenotypes through the stages of the cell directly. Compared to the vast information in genomics, transcriptomics and proteomics, there is more information about apparent learning[3]. Thus, metabonomics has recently been widely used to discover the pathogenesis, finding potential metabolic markers with high sensitivity and specificity and exploring new diagnosis and treatment methods in order to increase early phase diagnosis rates of certain diseases and provide a new basis for targeted therapy[4].
The morbidity of hepatocellular carcinoma (HCC) ranks 5th and its mortality ranks 3rd as a malignancy worldwide[5]. The incidence in southeast Asia and Africa is especially high, about 20 per 100000 population[6]. HCC has many risks with HBC as the primary one, causing 780000 death yearly[7]. The evolutionary progress of chronic hepatic disease is from chronic hepatitis B (CHB), hepatitis B virus (HBV)-related cirrhosis to HBV-related HCC. Nowadays, liver biopsy is the golden criteria in differentiating hepatic fibrosis, liver cirrhosis (LC) and HCC but cannot be used universally because of the invasiveness. Abdominal ultrasound is still the first screening method for hepatic diseases. It is widely used clinically because it is noninvasive and cheap. However, its sensitivity is affected by the machine, operators and different states of the disease. The sensitivity of diagnosing early cirrhosis is especially low, only 32% to 65% in HCC[8,9]. However, as a widely used clinical serum biomarker for HCC, alpha fetoprotein shows no increase in 80% of small HCC and its overall sensitivity is just 70%[8-11]. Some liver fibrosis indexes, such as hyaluronic acid, procollagen type III, procollagen type IV and laminin, can indicate early hepatic cirrhosis by analyzing the proliferation and degeneration of hepatic fibrosis. However, its sensitivity and specificity remain unknown[12]. As an essential metabolic organ, any organic disease of the liver will lead to changes in the whole body’s metabolism, causing widespread concern for medical staff. Research on the relationship between hepatic diseases and metabonomics has been increasing yearly. This review mainly analyzes the research progress of the metabonomics of HBV-related hepatic diseases, hoping to discover some potential metabolic markers for identification of HBV-related hepatic diseases from other etiologies and for HBV-related hepatitis, LC and HCC. It can contribute to early discovery, diagnosis and treatment, eventually increasing the survival rate of HBV-related hepatic diseases.
Chronic HBV infection is a global problem, mainly in developing countries and especially in southeast Asia and Africa. About 600000 people die of acute or chronic HBV infection each year[13]. Chronic HBV infection can result in hepatitis, hepatic fibrosis and even LC and HCC. Presently, the main treatment methods for chronic HBV infection are interferon treatment[14-16], nucleotide analogue treatment[17-19], immune treatment[20-22], etc. Although they can reduce the transformation from CHB to LC and HCC, their cure rates still need to improve. In the meantime, the pathogenic pathway of chronic HBV infection is still unclear. In the metabonomic study of patients with chronic HBV infection, some metabolites with a significant difference were found, which may provide some basis for discovering a pathogenic pathway and ideas for new targeted therapy.
As shown in Table 1, there are 2 studies concerning CHB. Zhou et al[23] analyzed the metabolites in serum from CHB patients and a control group by liquid chromatography-mass spectrometry (LC-MS) and discovered 12 metabolites with a difference that were involved in fatty acids, amino acids, bile acids and energy metabolism and other pathways[24]. To date, there are still few metabonomic studies about CHB so it is a research domain that needs to be expanded. Autoimmune hepatitis (AIH) is an inflammatory reaction of the liver caused by autoantibodies. Early diagnosis can result in successful treatment. However, due to the unknown pathogenesis, the diagnostic rate is low and the prognosis cannot be estimated. Wang et al[25] studied metabonomic characteristics of AIH by nuclear magnetic resonance (NMR) for the first time, providing a basis for researching the pathogenesis of AIH and discovering potential metabolic markers further. About 11% of patients with nonalcoholic steatohepatitis (NASH) will develop LC after 15 years and 7% will develop HCC through LC or directly after 6.5 years[26]. The metabolic changes of NASH refer to the metabolism of fatty acids, carbohydrates and bile acids[27-29]. The metabonomic research for chronic hepatitis C has discovered that the up-regulation of AKR1B10 expression in urine leads to abnormal glucose metabolism[30]. In studies about acute alcoholic hepatitis, Rachakonda et al[31] detected metabolites that were distinctly different from those in alcoholic LC that were involved in the metabolic process of fatty acids, bile acids, proteins and carbohydrates.
LC is the terminal stage of chronic liver diseases (CLD), with a high morbidity worldwide. Chronic HBV infection is an important pathogenic factor of LC[32] and the evolution of HBV-related LC is a gradual progress[33]. Due to a lack of specific diagnostic methods, the incidence rate of LC is 3.7 per 100 person-years in HBV carriers[34] and the 5 years survival rate of decompensated LC patients is only 14% to 35%[35,36], while 70% to 90% of HBV-related HCC developed from decompensated LC[37,38]. To date, there are still few valuable markers for early diagnosis of HBV-related LC and it is especially important to detect potential biomarkers with a higher sensitivity and specificity.
Table 2 shows 5 studies regarding the metabonomics of HBV-related LC, 4 of them based on serum and 1 based on urine. According to the Child-Pugh scores, all the LC patients were classified into three groups, A, B and C. Wang et al[39] carried out a urinary metabonomic study on the different stages of HBV-related LC and healthy controls using a gas chromatography-mass spectrometer (GC-MS) and ultra performance liquid chromatography time-of-flight mass spectrometry. They found metabolites with a significant difference in the three groups of LC, which may be potential metabolic markers in different stages of LC, providing a basis for the estimate of progress. Differently from the other three studies, Xue et al[40] chose patients with CHB as a control group and found nine metabolites with an obvious difference in total. The study also further verified the distinguishing ability by SAS software, showing that five out of twenty LC patients in Child-Pugh A were misdiagnosed as patients with CHB due to the small sample size. Zhou et al[23] and Yin et al[41] analyzed the metabolites in the serum of a HBV-related LC group and healthy control group by LC-MS and NMR, with both methods discovering metabolites with differences[42]. Among these five articles, only one used hepatitis B patients as a control group and the others chose healthy volunteers. In these present studies, we still lack research that uses CHB patients as a control group. The identification sensitivity of potential metabolic markers in patients with early HBV-related LC and patients with CHB found in present studies should be further discussed.
| Ref. | Year | Species | Tissue | Platform | Up-regulated | Down-regulated |
| Liu et al[42] | 2013 | Human | Serum | NMR | L-phenylalanine, C16 sphinganine, alpha-CEHC, LysoPC (18:1), linoelaidic acid, PC (18:4/20:1), bilirubin | L-carnitine, decanoyl-L-carnitine, phytosphingosine, 3α, 6α, 7α, 12α-tetrahydroxy-5β-cholan-24-oic acid PC (14:1/14:1), LysoPC (16:0) |
| LC 42 | LC-MS | |||||
| N 18 | ||||||
| LC/N | ||||||
| Wang et al[39] | 2012 | Human | Urine | GC-MS | Prolile, citrate, aconitate, 3,4-dihydroxyphenylacetate, taurohyocholate, glycocholate, glycoursodeoxycholate | Threonine, hippurate, 2-aminobutyrate, cis-aconitate, pyroglutamate, alpha-hydroxyisobutyrate, 3-hydroxyisovalerate, alpha-hydroxyhippurate, estrone |
| LC 63 | UPLC-TOFMS | |||||
| N 31 | ||||||
| LC/N | ||||||
| Zhou et al[23] | 2012 | Human | Serum | LC-MS | GCA, GCDCA, CN | Tryptophan, LysoPC (20:5), LysoPC (0:0/14:0), LysoPC (22:6), LysoPC (14:0/0:0), LysoPE (20:4), C10-CN, C10:1-CN, C8-CN, C6-CN |
| CIR 30 | ||||||
| N 30 | ||||||
| CIR/N | ||||||
| Yin et al[41] | 2009 | Human | Serum | RRLC | Taurocholic acid fragment, GCA, bilirubin, TCDCA fragment, GCDCA, oleic acid fragment, taurocholic acid fragment, carnitine fragment, L-acetylcarnitine | Hypoxanthine, lysoPC C18:2, LPC C18:3, LPC C16:1, LPC C18:0, Hypoxanthine fragment, inosine, taurine, 6-methylnicotinic acid |
| LC25 N25 | ||||||
| LC/N | ||||||
| Xue et al[40] | 2009 | HBV infected human | Serum | GC-MS | Acetic acid, hexanoic acid, 1-naphthalenamine, butanoic acid | Sorbitol, D-Lactic acid, phosphoric acid, D-glucitol, glucose |
| LC20 non-LC 20 | ||||||
| LC/non-LC |
Primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC) are two diseases relevant to metabolic disorders of bile acid. Due to the insidious onset and lack of effective diagnostic methods with high specificity, patients are usually in an advanced stage when diagnosed[43]. Trottier et al[44] analyzed the metabolic changes of 17 bile acids in patients with these two diseases by LC-MS. Compared to healthy volunteers, the primary bile acid in serum in the two diseases increased significantly, which may be associated with impairment of the enterohepatic circulation. Compared with PBC, the levels of secondary bile acid in the PSC group decreased obviously. It suggests that PBC is only relevant to the impairment of the extrahepatic bile duct, while PSC involves both the intrahepatic and extrahepatic bile duct. Furthermore, Bell et al[45] also drew similar conclusions by LC-MS. Acute-on-chronic liver failure (ACLF) is acute liver failure resulting from the acute deterioration of liver function on the basis of CLD, which can be accompanied by multiple organ failure at the same time. Due to its yearly increasing incidence and high mortality rate, ACLF is receiving more and more attention from the medical profession[46]. Amathieu et al[47,48] studied the metabonomic characteristics of LC patients with and without ACLF and detected obvious differences in the metabolic features of the two groups. Nie et al[49] discovered 17 potential markers by comparing HBV-related ACLF with HBV-related LC in Child-Pugh A and 11 of them had improved survival after treatment, which has implications for the early diagnosis and prognosis assessment of ACLF. Lian et al[50] researched metabolic differences in alcoholic LC and HBV-related LC by LC-MS and found that oleamide and myristamide increased significantly in patients with alcoholic LC but decreased distinctly in patients with HBV-related LC, which indicated that they both could be used as specific metabolic markers to distinguish alcoholic LC from HBV-related LC. By GC-MS and LC-MS, Fitian AI, Soga et al[24] and Fitian et al[51] found that some bile acids and dicarboxylic acids increased in hepatitis C virus (HCV)-related LC. Also, γ-glutamyl dipeptides were mentioned in both studies and there was thought to be some expressed differences in different types of hepatic diseases. Therefore, it can be used as a potential metabolic marker to differentiate various hepatic diseases. So far, metabonomics of various hepatic diseases is still in the primary stages, lacking the metabolomic difference analysis comparing the diverse types of hepatic diseases. Therefore, the field of metabonomics of hepatic diseases needs further research.
In China, over 80% of HCC cases resulted from chronic HBV infection, an evolutionary progress from CHB to LC and eventually to HCC[32,33]. To improve the diagnostic rate for early HCC, potential biomarkers with high specificity which can be adopted to screen the HBV-related LC need to be explored. Some metabolites which are specifically expressed in HBV-related HCC may provide a new horizon for the targeted treatment of HCC in the future.
In Table 3, 4 studies from China exploring metabolomics of HBV-related HCC are shown, complying with the regional differences of HCC. The potential metabolic markers found in these studies involve the metabolism pathways of fatty, amino and bile acids, energy and so on. Liu et al[52] researched the metabolomic characteristics of liver tissue in 10 patients with liver carcinoma by LC-MS. Based on the comparison of the central area of the tumor and distant tissue, 14 metabolites were found with obvious differences and 9 of them[53-55] have also been mentioned in other studies. However, beta-sitosterol, quinaldic acid, arachidyl carnitine, tetradecanal and oleamide have rarely been mentioned, possibly because the levels of these 5 metabolites are too low in serum to be detected. It indicates that although metabolic profiling of tissue cannot reflect the changes of systemic metabolism in the human body, it could actually reflect the changes of metabolic characteristics of certain tissues or organs. Li et al[56] compared the metabolomic characteristics of HBV infected HCC host cells HepG2.2.15 with HCC host cell HepG2 by NMR and found that 11 metabolites were obviously different. N-acetyl glucosamine kinase had a significantly increased expression in HepG2.2.15 and was involved in the hexosamine biosynthesis pathway, which demonstrated that the hexosamine biosynthesis pathway was activated in HBV infected cells, providing a new thought for studying targeted therapy for HBV infection in the future. Zhou et al[23] and Yin et al[41] analyzed the metabolites of HBV-related HCC and normal bodies by LC-MS and found some potential biomarkers of metabolism involved in the metabolism of fatty acid, phosphoric acid, amino acid and glucose. Both studies found that the expression of glycochenodeoxycholic acid, lysophosphatidylcholine and glycocholic acid were significantly different in patients with HCC.
| Ref. | Year | Species | Tissue | Platform | Up-regulated | Down-regulated |
| Li et al[56] | 2015 | Human | Liver | NMR | Fructose-bisphosphatealdolase, glucose-6-phosphate isomerase, alpha-enolase, citrate synthase | 4-hydroxyphenylpyruvate dioxygenase |
| Hepatoblastoma cell line | Host cell | Phosphoglycerate kinase 1 | Fumarylacetoacetase | |||
| HepG2.2.15/HepG2 | Triosephosphate isomerase | |||||
| Sussinate dehydrogenase | ||||||
| Malate dehydrogenase | ||||||
| Liu et al[52] | 2013 | Human | Liver | UPLC-MS | Sitosterol-beta, L-phenylalanine, LysoPC [18:2 (9Z, 12Z)], quinaldic acid glycerophosphocholine, LysoPC (18:0) | Arachidyl carnitine |
| HCC 10 | LysoPE (18:0/0:0), chenodeoxycholic acid glycine conjugate | Tetradecanal | ||||
| Central/distant | LysoPE [18:3 (9Z, 12Z, 15Z)/0:0] | Oleamide | ||||
| LysoPC [22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)] M | ||||||
| LysoPC [20:4 (5Z, 8Z, 11Z, 14Z)] | ||||||
| Zhou et al[23] | 2012 | Human | Serum | LC-MS | GCA, GCDCA, C16:1-CN | Tryptophan, C10:1-CN, C8-CN, C10-CN, |
| HCC 30 N 30 | C6-CN, LysoPC (20:5) | |||||
| HCC/N | LysoPC (0:0/14:0), LysoPC (20:3), LysoPC (14:0/0:0) | |||||
| Yin et al[41] | 2009 | Human | Serum | LC-MS | Taurocholic acid, GCA, bilirubin, TCDCA, GCDCA, oleic acid, taurocholic acid, carnitine, L-acetylcarnitine | Hypoxanthine, phytosphingosine, dihydrosphingosine, LPC C18:2, LPC C18:3, LPC C16:1, LPC C18:0 phytosphingosine, inosine, hypoxanthine, taurine, 6-methylnicotinic acid |
| HCC 24 N 25 | ||||||
| HCC/N |
Besides the infection with HBV, infection with HCV, the addition of alcohol and steatohepatitis are also important pathogenic factors in HCC. We found 3 studies regarding HCV-related HCC[51,57,58] from the United States. Compared to the research of HBV-related HCC, other body fluid samples were added, as well as serum, containing metabolomic characteristics of HCV-related HCC and LC. Bowers et al[57] analyzed the metabolomic characteristics in serum and urine from HCV-related HCC and chronic hepatitis C patients by LC-MS. Fitian et al[51] and Baniasadi et al[58] also studied the diversity of serum metabolomics in patients with HCV-related HCC and LC, resulting in some potential metabolic markers with significant differences being detected. There are increasing numbers of people addicted to alcohol with the speeding pace of modern society and about 1/3 of HCC cases result from alcohol worldwide[59]. Nahon et al[60] analyzed the metabolic changes of alcoholic LC and HCC by NMR and discovered that the metabolites in a group of alcoholic LC without HCC were apparently different from that of alcoholic LC with large HCC. Glutamine decreased greatly, while metabolites such as glutamate and glycoprotein increased sharply. It indicated that glutamine degradation and glycolysis might be the main metabolic pathway of energy in hepatoma cells. With the improvement of living standards and the changes in lifestyle, the incidence of non-alcoholic fatty liver disease is increasing yearly and is currently up to 30% in developed countries[61,62]. Excessive deposition of fat in the liver can cause NASH, liver fibrosis, LC and even HCC[63]. Beyoğlu et al[64] specifically analyzed the research about non-alcoholic HCC in their review. Most of the research used healthy people as the control group, while a small part used patients with LC. The potential metabolic markers detected were involved in the metabolic processes of fatty acids, bile acids and so on. There are some differences between the metabolic markers found in this research and in the research on HBV-related HCC. More research is needed to find the pathogenesis in order to provide the basis for targeted treatment of HCC of different etiologies in the future.
Metabonomics is still in the beginning and developing stage but it has drawn wide attention from the medical community. There are some short comings in its analysis technology and data analysis methods which require further completion and improvement. At present, metabonomics is just applied to common diseases. In our review, there are some obvious metabonomic differences between HBV-related hepatic diseases and other liver diseases, which have some research value and may provide evidence for detecting specific markers and elucidating the pathogenesis of HBV-related hepatic diseases. With the continuous development of medical technology, the prospect of metabonomics is immeasurable. It is expected to develop and enhance clinical diagnosis and treatment in the future, with genomics, transcriptomics and proteomics.
P- Reviewer: Ito H S- Editor: Ji FF L- Editor: Roemmele A E- Editor: Liu SQ
| 1. | Zámbó V, Simon-Szabó L, Szelényi P, Kereszturi E, Bánhegyi G, Csala M. Lipotoxicity in the liver. World J Hepatol. 2013;5:550-557. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 124] [Cited by in F6Publishing: 129] [Article Influence: 11.7] [Reference Citation Analysis (0)] |
| 2. | Yang WS, Va P, Bray F, Gao S, Gao J, Li HL, Xiang YB. The role of pre-existing diabetes mellitus on hepatocellular carcinoma occurrence and prognosis: a meta-analysis of prospective cohort studies. PLoS One. 2011;6:e27326. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 83] [Cited by in F6Publishing: 100] [Article Influence: 7.7] [Reference Citation Analysis (0)] |
| 3. | Fitzpatrick M, Young SP. Metabolomics--a novel window into inflammatory disease. Swiss Med Wkly. 2013;143:w13743. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 16] [Cited by in F6Publishing: 35] [Article Influence: 3.2] [Reference Citation Analysis (0)] |
| 4. | Friedrich N. Metabolomics in diabetes research. J Endocrinol. 2012;215:29-42. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 103] [Cited by in F6Publishing: 97] [Article Influence: 8.1] [Reference Citation Analysis (0)] |
| 5. | Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61:69-90. [PubMed] [Cited in This Article: ] |
| 6. | Han YF, Zhao J, Ma LY, Yin JH, Chang WJ, Zhang HW, Cao GW. Factors predicting occurrence and prognosis of hepatitis-B-virus-related hepatocellular carcinoma. World J Gastroenterol. 2011;17:4258-4270. [PubMed] [DOI] [Cited in This Article: ] [Cited by in CrossRef: 57] [Cited by in F6Publishing: 65] [Article Influence: 5.0] [Reference Citation Analysis (0)] |
| 7. | Churin Y, Roderfeld M, Roeb E. Hepatitis B virus large surface protein: function and fame. Hepatobiliary Surg Nutr. 2015;4:1-10. [PubMed] [DOI] [Cited in This Article: ] [Cited by in F6Publishing: 23] [Reference Citation Analysis (0)] |
| 8. | Singal AG, Conjeevaram HS, Volk ML, Fu S, Fontana RJ, Askari F, Su GL, Lok AS, Marrero JA. Effectiveness of hepatocellular carcinoma surveillance in patients with cirrhosis. Cancer Epidemiol Biomarkers Prev. 2012;21:793-799. [PubMed] [Cited in This Article: ] |
| 9. | Singal A, Volk ML, Waljee A, Salgia R, Higgins P, Rogers MA, Marrero JA. Meta-analysis: surveillance with ultrasound for early-stage hepatocellular carcinoma in patients with cirrhosis. Aliment Pharmacol Ther. 2009;30:37-47. [PubMed] [Cited in This Article: ] |
| 10. | Soper R, Himmelreich U, Painter D, Somorjai RL, Lean CL, Dolenko B, Mountford CE, Russell P. Pathology of hepatocellular carcinoma and its precursors using proton magnetic resonance spectroscopy and a statistical classification strategy. Pathology. 2002;34:417-422. [PubMed] [Cited in This Article: ] |
| 11. | Saffroy R, Pham P, Reffas M, Takka M, Lemoine A, Debuire B. New perspectives and strategy research biomarkers for hepatocellular carcinoma. Clin Chem Lab Med. 2007;45:1169-1179. [PubMed] [Cited in This Article: ] |
| 12. | Zhu C, Cao H, Zhou X, Dong C, Luo J, Zhang C, Liu J, Ling Y. Meta-analysis of the clinical value of danshen injection and huangqi injection in liver cirrhosis. Evid Based Complement Alternat Med. 2013;2013:842824. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 0.9] [Reference Citation Analysis (0)] |
| 13. | Yu R, Fan R, Hou J. Chronic hepatitis B virus infection: epidemiology, prevention, and treatment in China. Front Med. 2014;8:135-144. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 34] [Cited by in F6Publishing: 39] [Article Influence: 3.9] [Reference Citation Analysis (0)] |
| 14. | Sonneveld MJ, Rijckborst V, Zeuzem S, Heathcote EJ, Simon K, Senturk H, Pas SD, Hansen BE, Janssen HL. Presence of precore and core promoter mutants limits the probability of response to peginterferon in hepatitis B e antigen-positive chronic hepatitis B. Hepatology. 2012;56:67-75. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 64] [Cited by in F6Publishing: 62] [Article Influence: 5.2] [Reference Citation Analysis (0)] |
| 15. | Sonneveld MJ, Hansen BE, Piratvisuth T, Jia JD, Zeuzem S, Gane E, Liaw YF, Xie Q, Heathcote EJ, Chan HL. Response-guided peginterferon therapy in hepatitis B e antigen-positive chronic hepatitis B using serum hepatitis B surface antigen levels. Hepatology. 2013;58:872-880. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 178] [Cited by in F6Publishing: 172] [Article Influence: 15.6] [Reference Citation Analysis (1)] |
| 16. | Lampertico P, Viganò M, Di Costanzo GG, Sagnelli E, Fasano M, Di Marco V, Boninsegna S, Farci P, Fargion S, Giuberti T. Randomised study comparing 48 and 96 weeks peginterferon α-2a therapy in genotype D HBeAg-negative chronic hepatitis B. Gut. 2013;62:290-298. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 90] [Cited by in F6Publishing: 94] [Article Influence: 8.5] [Reference Citation Analysis (0)] |
| 17. | Kitrinos KM, Corsa A, Liu Y, Flaherty J, Snow-Lampart A, Marcellin P, Borroto-Esoda K, Miller MD. No detectable resistance to tenofovir disoproxil fumarate after 6 years of therapy in patients with chronic hepatitis B. Hepatology. 2014;59:434-442. [PubMed] [Cited in This Article: ] |
| 18. | Marcellin P, Gane E, Buti M, Afdhal N, Sievert W, Jacobson IM, Washington MK, Germanidis G, Flaherty JF, Aguilar Schall R. Regression of cirrhosis during treatment with tenofovir disoproxil fumarate for chronic hepatitis B: a 5-year open-label follow-up study. Lancet. 2013;381:468-475. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 1228] [Cited by in F6Publishing: 1292] [Article Influence: 117.5] [Reference Citation Analysis (0)] |
| 19. | Tenney DJ, Rose RE, Baldick CJ, Pokornowski KA, Eggers BJ, Fang J, Wichroski MJ, Xu D, Yang J, Wilber RB. Long-term monitoring shows hepatitis B virus resistance to entecavir in nucleoside-naïve patients is rare through 5 years of therapy. Hepatology. 2009;49:1503-1514. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 615] [Cited by in F6Publishing: 600] [Article Influence: 40.0] [Reference Citation Analysis (0)] |
| 20. | Hakim MS, Spaan M, Janssen HL, Boonstra A. Inhibitory receptor molecules in chronic hepatitis B and C infections: novel targets for immunotherapy? Rev Med Virol. 2014;24:125-138. [PubMed] [Cited in This Article: ] |
| 21. | Wang L, Zou ZQ, Liu CX, Liu XZ. Immunotherapeutic interventions in chronic hepatitis B virus infection: a review. J Immunol Methods. 2014;407:1-8. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 21] [Cited by in F6Publishing: 21] [Article Influence: 2.1] [Reference Citation Analysis (0)] |
| 22. | Atanley E, van Drunen Littel-van den Hurk S. Future considerations for dendritic cell immunotherapy against chronic viral infections. Expert Rev Clin Immunol. 2014;10:801-813. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 0.7] [Reference Citation Analysis (0)] |
| 23. | Zhou L, Wang Q, Yin P, Xing W, Wu Z, Chen S, Lu X, Zhang Y, Lin X, Xu G. Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases. Anal Bioanal Chem. 2012;403:203-213. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 106] [Cited by in F6Publishing: 125] [Article Influence: 10.4] [Reference Citation Analysis (0)] |
| 24. | Soga T, Sugimoto M, Honma M, Mori M, Igarashi K, Kashikura K, Ikeda S, Hirayama A, Yamamoto T, Yoshida H. Serum metabolomics reveals γ-glutamyl dipeptides as biomarkers for discrimination among different forms of liver disease. J Hepatol. 2011;55:896-905. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 184] [Cited by in F6Publishing: 180] [Article Influence: 13.8] [Reference Citation Analysis (0)] |
| 25. | Wang JB, Pu SB, Sun Y, Li ZF, Niu M, Yan XZ, Zhao YL, Wang LF, Qin XM, Ma ZJ. Metabolomic Profiling of Autoimmune Hepatitis: The Diagnostic Utility of Nuclear Magnetic Resonance Spectroscopy. J Proteome Res. 2014;Epub ahead of print. [PubMed] [Cited in This Article: ] |
| 26. | Torres DM, Williams CD, Harrison SA. Features, diagnosis, and treatment of nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2012;10:837-858. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 182] [Cited by in F6Publishing: 182] [Article Influence: 15.2] [Reference Citation Analysis (0)] |
| 27. | Kalhan SC, Guo L, Edmison J, Dasarathy S, McCullough AJ, Hanson RW, Milburn M. Plasma metabolomic profile in nonalcoholic fatty liver disease. Metabolism. 2011;60:404-413. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 358] [Cited by in F6Publishing: 406] [Article Influence: 31.2] [Reference Citation Analysis (0)] |
| 28. | Barr J, Vázquez-Chantada M, Alonso C, Pérez-Cormenzana M, Mayo R, Galán A, Caballería J, Martín-Duce A, Tran A, Wagner C. Liquid chromatography-mass spectrometry-based parallel metabolic profiling of human and mouse model serum reveals putative biomarkers associated with the progression of nonalcoholic fatty liver disease. J Proteome Res. 2010;9:4501-4512. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 118] [Cited by in F6Publishing: 126] [Article Influence: 9.7] [Reference Citation Analysis (0)] |
| 29. | Li H, Wang L, Yan X, Liu Q, Yu C, Wei H, Li Y, Zhang X, He F, Jiang Y. A proton nuclear magnetic resonance metabonomics approach for biomarker discovery in nonalcoholic fatty liver disease. J Proteome Res. 2011;10:2797-2806. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 51] [Cited by in F6Publishing: 49] [Article Influence: 3.8] [Reference Citation Analysis (0)] |
| 30. | Semmo N, Weber T, Idle JR, Beyoğlu D. Metabolomics reveals that aldose reductase activity due to AKR1B10 is upregulated in hepatitis C virus infection. J Viral Hepat. 2015;22:617-624. [PubMed] [Cited in This Article: ] |
| 31. | Rachakonda V, Gabbert C, Raina A, Bell LN, Cooper S, Malik S, Behari J. Serum metabolomic profiling in acute alcoholic hepatitis identifies multiple dysregulated pathways. PLoS One. 2014;9:e113860. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 39] [Cited by in F6Publishing: 45] [Article Influence: 4.5] [Reference Citation Analysis (0)] |
| 32. | Patel M, Shariff MI, Ladep NG, Thillainayagam AV, Thomas HC, Khan SA, Taylor-Robinson SD. Hepatocellular carcinoma: diagnostics and screening. J Eval Clin Pract. 2012;18:335-342. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 33] [Cited by in F6Publishing: 38] [Article Influence: 3.2] [Reference Citation Analysis (0)] |
| 33. | Ott JJ, Stevens GA, Groeger J, Wiersma ST. Global epidemiology of hepatitis B virus infection: new estimates of age-specific HBsAg seroprevalence and endemicity. Vaccine. 2012;30:2212-2219. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 1217] [Cited by in F6Publishing: 1284] [Article Influence: 107.0] [Reference Citation Analysis (0)] |
| 34. | Qi SW, Tu ZG, Peng WJ, Wang LX, Ou-Yang X, Cai AJ, Dai Y. ¹H NMR-based serum metabolic profiling in compensated and decompensated cirrhosis. World J Gastroenterol. 2012;18:285-290. [PubMed] [DOI] [Cited in This Article: ] [Cited by in CrossRef: 28] [Cited by in F6Publishing: 34] [Article Influence: 2.8] [Reference Citation Analysis (0)] |
| 35. | Fattovich G, Bortolotti F, Donato F. Natural history of chronic hepatitis B: special emphasis on disease progression and prognostic factors. J Hepatol. 2008;48:335-352. [PubMed] [Cited in This Article: ] |
| 36. | Peng CY, Chien RN, Liaw YF. Hepatitis B virus-related decompensated liver cirrhosis: benefits of antiviral therapy. J Hepatol. 2012;57:442-450. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 149] [Cited by in F6Publishing: 150] [Article Influence: 12.5] [Reference Citation Analysis (0)] |
| 37. | Yang JD, Kim WR, Coelho R, Mettler TA, Benson JT, Sanderson SO, Therneau TM, Kim B, Roberts LR. Cirrhosis is present in most patients with hepatitis B and hepatocellular carcinoma. Clin Gastroenterol Hepatol. 2011;9:64-70. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 171] [Cited by in F6Publishing: 184] [Article Influence: 14.2] [Reference Citation Analysis (0)] |
| 38. | Mittal S, El-Serag HB. Epidemiology of hepatocellular carcinoma: consider the population. J Clin Gastroenterol. 2013;47 Suppl:S2-S6. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 770] [Cited by in F6Publishing: 853] [Article Influence: 77.5] [Reference Citation Analysis (0)] |
| 39. | Wang X, Wang X, Xie G, Zhou M, Yu H, Lin Y, Du G, Luo G, Jia W, Liu P. Urinary metabolite variation is associated with pathological progression of the post-hepatitis B cirrhosis patients. J Proteome Res. 2012;11:3838-3847. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 17] [Cited by in F6Publishing: 17] [Article Influence: 1.4] [Reference Citation Analysis (0)] |
| 40. | Xue R, Dong L, Wu H, Liu T, Wang J, Shen X. Gas chromatography/mass spectrometry screening of serum metabolomic biomarkers in hepatitis B virus infected cirrhosis patients. Clin Chem Lab Med. 2009;47:305-310. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 16] [Cited by in F6Publishing: 20] [Article Influence: 1.3] [Reference Citation Analysis (0)] |
| 41. | Yin P, Wan D, Zhao C, Chen J, Zhao X, Wang W, Lu X, Yang S, Gu J, Xu G. A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry. Mol Biosyst. 2009;5:868-876. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 173] [Cited by in F6Publishing: 179] [Article Influence: 11.9] [Reference Citation Analysis (0)] |
| 42. | Liu Y, Hong Z, Tan G, Dong X, Yang G, Zhao L, Chen X, Zhu Z, Lou Z, Qian B. NMR and LC/MS-based global metabolomics to identify serum biomarkers differentiating hepatocellular carcinoma from liver cirrhosis. Int J Cancer. 2014;135:658-668. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 82] [Cited by in F6Publishing: 97] [Article Influence: 9.7] [Reference Citation Analysis (0)] |
| 43. | Tabibian JH, Talwalkar JA, Lindor KD. Role of the microbiota and antibiotics in primary sclerosing cholangitis. Biomed Res Int. 2013;2013:389537. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 72] [Cited by in F6Publishing: 66] [Article Influence: 6.0] [Reference Citation Analysis (0)] |
| 44. | Trottier J, Białek A, Caron P, Straka RJ, Heathcote J, Milkiewicz P, Barbier O. Metabolomic profiling of 17 bile acids in serum from patients with primary biliary cirrhosis and primary sclerosing cholangitis: a pilot study. Dig Liver Dis. 2012;44:303-310. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 96] [Cited by in F6Publishing: 115] [Article Influence: 9.6] [Reference Citation Analysis (0)] |
| 45. | Bell LN, Wulff J, Comerford M, Vuppalanchi R, Chalasani N. Serum metabolic signatures of primary biliary cirrhosis and primary sclerosing cholangitis. Liver Int. 2015;35:263-274. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 43] [Cited by in F6Publishing: 58] [Article Influence: 6.4] [Reference Citation Analysis (0)] |
| 46. | Jalan R, Gines P, Olson JC, Mookerjee RP, Moreau R, Garcia-Tsao G, Arroyo V, Kamath PS. Acute-on chronic liver failure. J Hepatol. 2012;57:1336-1348. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 447] [Cited by in F6Publishing: 441] [Article Influence: 36.8] [Reference Citation Analysis (1)] |
| 47. | Amathieu R, Nahon P, Triba M, Bouchemal N, Trinchet JC, Beaugrand M, Dhonneur G, Le Moyec L. Metabolomic approach by 1H NMR spectroscopy of serum for the assessment of chronic liver failure in patients with cirrhosis. J Proteome Res. 2011;10:3239-3245. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 44] [Cited by in F6Publishing: 46] [Article Influence: 3.5] [Reference Citation Analysis (1)] |
| 48. | Amathieu R, Triba MN, Nahon P, Bouchemal N, Kamoun W, Haouache H, Trinchet JC, Savarin P, Le Moyec L, Dhonneur G. Serum 1H-NMR metabolomic fingerprints of acute-on-chronic liver failure in intensive care unit patients with alcoholic cirrhosis. PLoS One. 2014;9:e89230. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 37] [Cited by in F6Publishing: 40] [Article Influence: 4.0] [Reference Citation Analysis (0)] |
| 49. | Nie CY, Han T, Zhang L, Li Y, Liu H, Xiao SX, Li Y, Kang H, Liu SY. Cross-sectional and dynamic change of serum metabolite profiling for Hepatitis B-related acute-on-chronic liver failure by UPLC/MS. J Viral Hepat. 2014;21:53-63. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 19] [Cited by in F6Publishing: 22] [Article Influence: 2.2] [Reference Citation Analysis (0)] |
| 50. | Lian JS, Liu W, Hao SR, Guo YZ, Huang HJ, Chen DY, Xie Q, Pan XP, Xu W, Yuan WX. A serum metabonomic study on the difference between alcohol- and HBV-induced liver cirrhosis by ultraperformance liquid chromatography coupled to mass spectrometry plus quadrupole time-of-flight mass spectrometry. Chin Med J (Engl). 2011;124:1367-1373. [PubMed] [Cited in This Article: ] |
| 51. | Fitian AI, Nelson DR, Liu C, Xu Y, Ararat M, Cabrera R. Integrated metabolomic profiling of hepatocellular carcinoma in hepatitis C cirrhosis through GC/MS and UPLC/MS-MS. Liver Int. 2014;34:1428-1444. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 71] [Cited by in F6Publishing: 85] [Article Influence: 8.5] [Reference Citation Analysis (0)] |
| 52. | Liu SY, Zhang RL, Kang H, Fan ZJ, Du Z. Human liver tissue metabolic profiling research on hepatitis B virus-related hepatocellular carcinoma. World J Gastroenterol. 2013;19:3423-3432. [PubMed] [DOI] [Cited in This Article: ] [Cited by in CrossRef: 38] [Cited by in F6Publishing: 34] [Article Influence: 3.1] [Reference Citation Analysis (0)] |
| 53. | Tan Y, Yin P, Tang L, Xing W, Huang Q, Cao D, Zhao X, Wang W, Lu X, Xu Z. Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis. Mol Cell Proteomics. 2012;11:M111.010694. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 92] [Cited by in F6Publishing: 113] [Article Influence: 8.7] [Reference Citation Analysis (0)] |
| 54. | Chen F, Xue J, Zhou L, Wu S, Chen Z. Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method. Anal Bioanal Chem. 2011;401:1899-1904. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 69] [Cited by in F6Publishing: 69] [Article Influence: 5.3] [Reference Citation Analysis (0)] |
| 55. | Chen T, Xie G, Wang X, Fan J, Qiu Y, Zheng X, Qi X, Cao Y, Su M, Wang X. Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma. Mol Cell Proteomics. 2011;10:M110.004945. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 171] [Cited by in F6Publishing: 239] [Article Influence: 18.4] [Reference Citation Analysis (0)] |
| 56. | Li H, Zhu W, Zhang L, Lei H, Wu X, Guo L, Chen X, Wang Y, Tang H. The metabolic responses to hepatitis B virus infection shed new light on pathogenesis and targets for treatment. Sci Rep. 2015;5:8421. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 86] [Cited by in F6Publishing: 100] [Article Influence: 11.1] [Reference Citation Analysis (0)] |
| 57. | Bowers J, Hughes E, Skill N, Maluccio M, Raftery D. Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS. J Chromatogr B Analyt Technol Biomed Life Sci. 2014;966:154-162. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 17] [Cited by in F6Publishing: 19] [Article Influence: 1.9] [Reference Citation Analysis (0)] |
| 58. | Baniasadi H, Gowda GA, Gu H, Zeng A, Zhuang S, Skill N, Maluccio M, Raftery D. Targeted metabolic profiling of hepatocellular carcinoma and hepatitis C using LC-MS/MS. Electrophoresis. 2013;34:2910-2917. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 16] [Cited by in F6Publishing: 35] [Article Influence: 3.2] [Reference Citation Analysis (0)] |
| 59. | French SW. Epigenetic events in liver cancer resulting from alcoholic liver disease. Alcohol Res. 2013;35:57-67. [PubMed] [Cited in This Article: ] |
| 60. | Nahon P, Amathieu R, Triba MN, Bouchemal N, Nault JC, Ziol M, Seror O, Dhonneur G, Trinchet JC, Beaugrand M. Identification of serum proton NMR metabolomic fingerprints associated with hepatocellular carcinoma in patients with alcoholic cirrhosis. Clin Cancer Res. 2012;18:6714-6722. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 54] [Cited by in F6Publishing: 60] [Article Influence: 5.0] [Reference Citation Analysis (0)] |
| 61. | Vernon G, Baranova A, Younossi ZM. Systematic review: the epidemiology and natural history of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in adults. Aliment Pharmacol Ther. 2011;34:274-285. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 2065] [Cited by in F6Publishing: 2221] [Article Influence: 170.8] [Reference Citation Analysis (0)] |
| 62. | Patel NS, Peterson MR, Lin GY, Feldstein A, Schnabl B, Bettencourt R, Seki E, Sirlin CB, Loomba R. Insulin Resistance Increases MRI-Estimated Pancreatic Fat in Nonalcoholic Fatty Liver Disease and Normal Controls. Gastroenterol Res Pract. 2013;2013:498296. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 33] [Cited by in F6Publishing: 44] [Article Influence: 4.0] [Reference Citation Analysis (0)] |
| 63. | Karandish M, Tamimi M, Shayesteh AA, Haghighizadeh MH, Jalali MT. The effect of magnesium supplementation and weight loss on liver enzymes in patients with nonalcoholic fatty liver disease. J Res Med Sci. 2013;18:573-579. [PubMed] [Cited in This Article: ] |
| 64. | Beyoğlu D, Idle JR. The metabolomic window into hepatobiliary disease. J Hepatol. 2013;59:842-858. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 157] [Cited by in F6Publishing: 171] [Article Influence: 15.5] [Reference Citation Analysis (0)] |