Fibrosis Hepatic fibrosis is a scarring process in which the extracellular matrix encapsulates the region of the liver parenchyma that has suffered an inflammatory insult. Fibrosis develops in almost all patients with chronic hepatopathy, although varying degrees depending on the type of stimulus that generated it and factors related to the host. Fibrosis is a dynamic pathological event, which is reversible in the early stages.
The composition of scar tissue is independent of the type of insult that led to fibrosis and involves the presence of macromolecules present in the normal extracellular matrix, including collagen of type I, III, V and IX, fibronectin, laminin, and elastin. The transition to a fibrotic tissue involves a significant change in matrix composition, with at least a three to tenfold increase in collagen, glycoproteins, proteoglycans, and glycosaminoglycans. These changes in the composition of the extracellular matrix result in the replacement of the normal low-density matrix of the subendothelial space by the interstitial matrix, with important consequences for the function of hepatocytes, stellate cells, and endothelial cells. When the processes of cell proliferation, deposition of the extracellular matrix, regeneration of the hepatic parenchyma, and inflammation occur in a contextual and, above all, uncontrolled manner, a state of fibrosis is established that can progress into cirrhosis (Fig. 1). Recently, the knowledge of the molecular mechanisms leading to fibrosis has aroused great scientific interest due to the potential of devel oping therapies aimed at stopping the progression of fibrosis.
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style=height:495px; width:684px />
Fig1. Schematic representation of the mechanisms leading to hepatic fibrosis. (Copyright EDISES 2021. Reproduced with permission)
Diagnostic Investigations
 The diagnostic approach to liver fibrosis includes biochemical, imaging, and histopathological evaluations, which are of little help if considered in isolation. Histopathological investigations represent the gold standard for the diagnosis and classification of fibrosis.
Noninvasive, serological, and imaging investigations (mainly hepatic elastometry) are performed to monitor any fibrosis progression.
Many biomarkers have been proposed for predicting fibrosis severity, with variable results. Generally, bio markers of hepatic fibrosis reflect matrix turnover, but not the extent of deposition of its components. Therefore, they may increase significantly when a relevant inflammatory state occurs, regardless of the degree of extracellular matrix deposition. None of the biomarkers available today are specific for hepatic fibrosis, and inflammatory states at other sites may contribute to increased circulating levels.
Serological markers can be distinguished into:
• Indirect markers reflecting changes in liver function.
• Direct markers of fibrosis, or biomarkers reflecting the turnover of the extracellular matrix. Indirect markers include all serological tests, which are indicative of an alteration in liver function, namely AST, ALT, platelet count, basic coagulation parameters (PT and INR), GGT, total bilirubin, α2-macroglobulin, and α2-globulins (mainly haptoglobin). Since these tests, individually, provide rather limited clinical information about the presence or absence of fibrosis, several panels have been proposed that combine these tests in various ways to increase their diagnostic accuracy. The APRI (AST to Platelet Ratio Index) and the Hepascore are the best known.
The APRI is calculated using the serum AST concentration, its upper reference limit (URL) used in the laboratory, and platelet count (PLT) according to the following formula:
APRI = [ ( AST / LSR ) / PLT ] X 100
The clinical validity of APRI was evaluated primarily in patients with hepatitis C and hepatopathy alcoholic. In patients with hepatitis C, it has been shown that a cutoff of 0.7 is associated with a sensitivity of 77% and a specificity of 72% in predicting significant fibrosis, while a cutoff of 1.0 is associated with a sensitivity of 76% and a specificity of 72% in predicting cirrhosis.
The Hepascore is an index calculated based on total bilirubin, GGT, hyaluronic acid, α2-macroglobulin, age, and sex.
The clinical evidence on the use of these scoring systems, although encouraging, is not sufficient to date to consider their use in clinical routine.
Direct markers of liver fibrosis include biomarkers of collagen synthesis or degradation, extracellular matrix glycoproteins, proteoglycans, and glycosaminoglycans. They can be summarily distinguished into biomarkers associated with extracellular matrix deposition, biomarkers associated with extracellular matrix degradation, and cytokines and chemokines associated with fibrogenesis (Table 1).
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style=height:347px; width:684px />
Table1. Main biomarkers of fibrogenesis and hepatic fibrinolysis
Serum levels of N-terminal procollagen type III peptide (PIIINP) increase in acute and chronic hepatopathies. They correlate with transaminase and bilirubin levels in cirrhotic patients and histological degree of fibrosis and inflammation in patients with alcoholic hepatopathy, viral hepatitis, and primary biliary cirrhosis. N-terminal procollagen type I pep tide (PINP) levels increase in patients with cirrhosis; however, this marker is less accurate than procollagen III-derived peptides in predicting the severity of fibrosis and the presence of hepatitis. Extracellular matrix degradation is primarily mediated by metalloproteinases (MMPs). These enzymes are synthesized intracellularly and secreted as proenzymes. Their activation requires proteolytic cutting mediated by cell surface enzymes. Finally, their action is inhibited by tissue inhibitors of metalloproteinases (TIMPs). It has been proposed that the degradation of the hepatic extracellular matrix by MMPs, or the loss of its regulation, is a pathophysiological event in liver fibrosis. Inflammation plays a relevant role in the pathogenesis of fibrosis, and many cytokines and other mediators of inflammation have been directly associated with the processes of cell proliferation and extracellular matrix deposition. For example, TGF-β is among the most potent stimulators of extracellular matrix production by hepatic stellate cells.
In general, evidence on the clinical use of direct labelers has often remained isolated and has not led to definitive conclusions on their use in clinical routine.