Serum PAI-1 is a novel predictor for response to pegylated interferon-α-2b plus ribavirin therapy in chronic hepatitis C virus infection

Roles of Adipokines in Digestive Diseases: Markers of Inflammation, Metabolic Alteration and Disease Progression

Adipose tissue is a highly dynamic endocrine tissue and constitutes a central node in the interorgan crosstalk network through adipokines, which cause pleiotropic effects, including the modulation of angiogenesis, metabolism, and inflammation. Specifically, digestive cancers grow anatomically near adipose tissue. During their interaction with cancer cells, adipocytes are reprogrammed into cancer-associated adipocytes and secrete adipokines to affect tumor cells. Moreover, the liver is the central metabolic hub. Adipose tissue and the liver cooperatively regulate whole-body energy homeostasis via adipokines. Obesity, the excessive accumulation of adipose tissue due to hyperplasia and hypertrophy, is currently considered a global epidemic and is related to low-grade systemic inflammation characterized by altered adipokine regulation. Obesity-related digestive diseases, including gastroesophageal reflux disease, Barrett's esophagus, esophageal cancer, colon polyps and cancer, non-alcoholic fatty liver disease, viral hepatitis-related diseases, cholelithiasis, gallbladder cancer, cholangiocarcinoma, pancreatic cancer, and diabetes, might cause specific alterations in adipokine profiles. These patterns and associated bases potentially contribute to the identification of prognostic biomarkers and therapeutic approaches for the associated digestive diseases. This review highlights important findings about altered adipokine profiles relevant to digestive diseases, including hepatic, pancreatic, gastrointestinal, and biliary tract diseases, with a perspective on clinical implications and mechanistic explorations.

Link between plasminogen activator inhibitor-1 and cardiovascular risk in chronic hepatitis C after viral clearance

The pathophysiological implications of plasminogen activator inhibitor-1 (PAI-1) in HCV infection remain obscure. This prospective study evaluated 669 HCV patients, of whom 536 had completed a course of anti-HCV therapy and had pre-, peri- and post-therapy measurements of various profiles, including PAI-1 levels. Multivariate analysis demonstrated, before anti-HCV-therapy, platelet count and PAI-1-rs1799889 genotype were associated with PAI-1 levels. Among patients with a sustained virological response (SVR, n = 445), platelet count was associated with PAI-1 level at 24 weeks post-therapy. GEE analysis showed that PAI-1-rs-1799889 and interferon-λ3-rs12979860 genotypes affected PAI-1 levels early and late in therapy, respectively. At 24 weeks post-therapy, higher lipid, brain natriuretic peptide, homocysteine and PAI-1 levels and PAI-1 activity were noted only in SVR patients compared with pre-therapy levels. Within 24 weeks post-therapy, 2.2% of the SVR (mean age: 57.8 yr; 8 smoking males; the 2 females had pre-therapy hypercholesteremia or cardiovascular family history of disease) and 0% of the non-SVR patients experienced a new cardiovascular event. Platelet counts consistently correlated with PAI-1 levels regardless of HCV infection. PAI-1-rs-1799889 and interferon-λ3-rs12979860 genotypes mainly affected PAI-1 levels longitudinally. Within 24 weeks post-anti-HCV therapy, the SVR patients showed increasing PAI-1 levels with accelerating cardiovascular risk, especially the vulnerable cases.

Metabolic Dysregulation in Hepacivirus Infection of Common Marmosets (Callithrix jacchus)

Chronic hepatitis C has been associated with metabolic syndrome that includes insulin resistance, hepatic steatosis and obesity. These metabolic aberrations are risk factors for disease severity and treatment outcome in infected patients. Experimental infection of marmosets with GBV-B serves as a tangible, small animal model for human HCV infection, and while virology and pathology are well described, a full investigation of clinical disease and the metabolic milieu is lacking. In this study six marmosets were infected intravenously with GBV-B and changes in hematologic, serum biochemical and plasma metabolic measures were investigated over the duration of infection. Infected animals exhibited signs of lymphocytopenia, but platelet and RBC counts were generally stable or even increased. Although most animals showed a transient decline in blood glucose, infection resulted in several fold increases in plasma insulin, glucagon and glucagon-like peptide 1 (GLP-1). All infected animals experienced transient weight loss within the first 28 days of infection, but also became hypertriglyceridemic and had up to 10-fold increases in adipocytokines such as resistin and plasminogen activator inhibitor 1 (PAI-1). In liver, moderate to severe cytoplasmic changes associated with steatotic changes was observed microscopically at 168 days post infection. Collectively, these results suggest that GBV-B infection is accompanied by hematologic, biochemical and metabolic abnormalities that could lead to obesity, diabetes, thrombosis and atherosclerosis, even after virus has been cleared. Our findings mirror those found in HCV patients, suggesting that metabolic syndrome could be conserved among hepaciviruses, and both mechanistic and interventional studies for treating HCV-induced metabolic complications could be evaluated in this animal model.

Metabolic alterations and hepatitis C: From bench to bedside

In addition to causing cirrhosis and hepatocellular carcinoma, hepatitis C virus (HCV) is thought to cause hypolipidemia, hepatic steatosis, insulin resistance, metabolic syndrome, and diabetes. The viral life cycle of HCV depends on cholesterol metabolism in host cells. HCV core protein and nonstructural protein 5A perturb crucial lipid and glucose pathways, such as the sterol regulatory element-binding protein pathway and the protein kinase B/mammalian target of rapamycin/S6 kinase 1 pathway. Although several lines of transgenic mice expressing core or full HCV proteins exhibit hepatic steatosis and/or dyslipidemia, whether they completely reflect the metabolic alterations in humans with HCV infection remains unknown. Many cross-sectional studies have demonstrated increased prevalences of metabolic alterations and cardiovascular events in patients with chronic hepatitis C (CHC); however, conflicting results exist, primarily due to unavoidable individual variations. Utilizing anti-HCV therapy, most longitudinal cohort studies of CHC patients have demonstrated the favorable effects of viral clearance in attenuating metabolic alterations and cardiovascular risks. To determine the risks of HCV-associated metabolic alterations and associated complications in patients with CHC, it is necessary to adjust for crucial confounders, such as HCV genotype and host baseline glucose metabolism, for a long follow-up period after anti-HCV treatment. Adipose tissue is an important endocrine organ due to its release of adipocytokines, which regulate lipid and glucose metabolism. However, most data on HCV infection and adipocytokine alteration are inconclusive. A comprehensive overview of HCV-associated metabolic and adipocytokine alterations, from bench to bedside, is presented in this topic highlight.

Relevance of baseline viral genetic heterogeneity and host factors for treatment outcome prediction in hepatitis C virus 1b-infected patients

BACKGROUND

Only about 50% of patients chronically infected with HCV genotype 1 (HCV-1) respond to treatment with pegylated interferon-alfa and ribavirin (dual therapy), and protease inhibitors have to be administered together with these drugs increasing costs and side-effects. We aimed to develop a predictive model of treatment response based on a combination of baseline clinical and viral parameters.

METHODOLOGY

Seventy-four patients chronically infected with HCV-1b and treated with dual therapy were studied (53 retrospectively -training group-, and 21 prospectively -validation group-). Host and viral-related factors (viral load, and genetic variability in the E1-E2, core and Interferon Sensitivity Determining Region) were assessed. Multivariate discriminant analysis and decision tree analysis were used to develop predictive models on the training group, which were then validated in the validation group.

PRINCIPAL FINDINGS

A multivariate discriminant predictive model was generated including the following variables in decreasing order of significance: the number of viral variants in the E1-E2 region, an amino acid substitution pattern in the viral core region, the IL28B polymorphism, serum GGT and ALT levels, and viral load. Using this model treatment outcome was accurately predicted in the training group (AUROC = 0.9444; 96.3% specificity, 94.7% PPV, 75% sensitivity, 81% NPV), and the accuracy remained high in the validation group (AUROC = 0.8148, 88.9% specificity, 90.0% PPV, 75.0% sensitivity, 72.7% NPV). A second model was obtained by a decision tree analysis and showed a similarly high accuracy in the training group but a worse reproducibility in the validation group (AUROC = 0.9072 vs. 0.7361, respectively).

CONCLUSIONS AND SIGNIFICANCE

The baseline predictive models obtained including both host and viral variables had a high positive predictive value in our population of Spanish HCV-1b treatment naïve patients. Accurately identifying those patients that would respond to the dual therapy could help reducing implementation costs and additional side effects of new treatment regimens.