title: Non-invasive biomarkers for monitoring the fibrogenic process in liver: a short survey.
abstract: The clinical course of chronic liver diseases is significantly dependent on the progression rate and the extent of fibrosis, i.e. the non-structured replacement of necrotic parenchyma by extracellular matrix. Fibrogenesis, i.e. the development of fibrosis can be regarded as an unlimited wound healing process, which is based on matrix (connective tissue) synthesis in activated hepatic stellate cells, fibroblasts (fibrocytes), hepatocytes and biliary epithelial cells, which are converted to matrix-producing (myo-)fibroblasts by a process defined as epithelial-mesenchymal transition. Blood (non-invasive) biomarkers of fibrogenesis and fibrosis can be divided into class I and class II analytes. Class I biomarkers are those single tests, which are based on the pathophysiology of fibrosis, whereas class II biomarkers are mostly multiparametric algorithms, which have been statistically evaluated with regard to the detection and activity of ongoing fibrosis. Currently available markers fulfil the criteria of ideal clinical-chemical tests only partially, but increased understanding of the complex pathogenesis of fibrosis offers additional ways for pathophysiologically well based serum (plasma) biomarkers. They include TGF-beta-driven marker proteins, bone marrow-derived cells (fibrocytes), and cytokines, which govern pro- and anti-fibrotic activities. Proteomic and glycomic approaches of serum are under investigation to set up specific protein or carbohydrate profiles in patients with liver fibrosis. These and other novel parameters will supplement or eventually replace liver biopsy/histology, high resolution imaging analysis, and elastography for the detection and monitoring of patients at risk of developing liver fibrosis.
authors.forename: Axel-M
authors.initials: AM
authors.lastname: Gressner
authors.forename: Chun-Fang
authors.initials: CF
authors.lastname: Gao
authors.forename: Olav-A
authors.initials: OA
authors.lastname: Gressner
mesh_terms: D015415:Biomarkers / Q000378:metabolism*; D055513:Connective Tissue Growth Factor / Q000378:metabolism; D003937:Diagnosis, Differential; D005109:Extracellular Matrix / Q000378:metabolism; D006801:Humans; D008103:Liver Cirrhosis / Q000378:metabolism / Q000473:pathology; D008107:Liver Diseases / Q000378:metabolism / Q000473:pathology
chemical_list: D015415:Biomarkers; D055513:Connective Tissue Growth Factor