The incidence of non-alcoholic fatty liver disease (NAFLD) is rising. It is a common and often under-appreciated comorbidity in patients with obesity, insulin resistance, diabetes, metabolic syndrome, and cardiovascular disease. These patients are likely to be on multiple medications for prolonged periods. Drug uptake, distribution, metabolism, transport, and excretion change over time in patients with fatty liver.
The progression of NAFLD to NASH leads to changes in excretion and toxicity of drugs that are typically well-tolerated.
Liver biopsy remains the gold standard for the accurate diagnosis and definition of staging and grading relating to chronic liver disease. Liver biopsy provides information on the degree of fibrosis, inflammation, necrosis, and steatosis, and quantifies the amount of iron and copper in the parenchyma. Various grading systems are then used to evaluate the degree and stage of the disease and choose an appropriate management regime (Caviglia et al., 2014). The accurate assessment of chronic liver disease and its progression into fibrosis, cirrhosis, and hepatocellular carcinoma has been a continuing challenge. Non-invasive biomarkers in accessible fluids that correlate with type and extent of liver tissue damage and prognosis are of great interest to clinicians.
Insulin resistance and metabolic syndrome
Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are referred to as fatty liver. Fatty liver is strongly associated with insulin resistance, diabetes mellitus, dyslipidemia, and hypertension, summarily known as metabolic syndrome. Adiponectines adiponectin, leptin, resistin, and visfatin are the most relevant indicators of metabolic syndrome. Hepatocellular apoptosis is one of the typical features of NASH. The laboratory clues include the increase in the messenger RNA expression of the adiponectin receptor (ApoR2). Inverse correlation between adiponectin and bile acids exists in NASH.
Proteohormone leptin that regulates food intake and energy expenditure reflects the total amount of body fat and is one of the indicators of insulin resistance. Ghrelin, a peptide produced by the stomach, influences insulin secretion and glucose and lipid metabolism. Ghrelin and retinol-binding protein 4 (RBP4) can also serve as indicators of insulin resistance. As such, adiponectines are useful biomarkers of metabolic syndrome, NAFLD, and its progression to NASH (Neuman, Cohen and Nanau, 2014).
Diagnosis of fatty liver (NAFLD and NASH)
Non-invasive tests and imaging have an increasing role in the diagnosis of NAFLD/NASH. BAAT score considers body mass index (BMI), age at liver biopsy, ALT, and serum triglycerides. It is used to identify patients who would most benefit from liver biopsy (Neuman et al., 2016).
Clinical parameters standardly evaluated in NAFLD/NASH patients include body mass index or waist circumference. Biochemical parameters include transaminase levels, gamma-glutamyl transferase, cholesterol, triglycerides, glucose, and C-peptide. Diagnostic indicators of insulin resistance in NASH are cytokines tumor necrosis factor (TNF) α and interleukin (IL)-6, CC-chemokine ligand-2 (chemo-attractant protein-1) and C-reactive protein (hs-CRP).
Complementary information can be gained from markers of cell death and mitochondrial dysfunction. These biomarkers include apolipoprotein A1 and B, leptin, adiponectin, free fatty acids, ghrelin, and cytokeratins. Initial stages of the disease only show minimum elevations in transaminases, ALP, and GGT. These biomarkers have to be evaluated in the context of other risk factors (Neuman, Cohen and Nanau, 2014).
Alcoholic liver disease (ALD)
Alcohol is one of the significant sources of oxidative stress. Alcoholic liver disease (ALD) develops as the consequence of oxidative stress associated with alcohol metabolism, glutathione depletion, abnormal metabolism of methionine, malnutrition, the release of intestinal endotoxins, and subsequent activation of Kupffer cells. Progression to the fatty liver through lipoperoxidation affects more than 90% of heavy drinkers. In about 30%, the disease progresses to fibrosis and cirrhosis (Gao and Bataller, 2011). Oxidative stress, one of the NAFLD risk factors, is detected by elevated plasma reactive carbonyl species levels and is assessed based on the balance of SOD2 antioxidant enzyme and cytochrome from the p450 family CYP2E1.
Free fatty acids are lipotoxic. The biological mechanism involved is the downregulation of mitochondrial beta-oxidation. Consequently, the accumulation of ceramides and diacylglycerol occurs (Neuman, Cohen and Nanau, 2014).
Liver biopsy and venous pressure gradient (HVPG) are the best measurements of disease severity. It also sheds light on the risk of complications such as bleeding, infections, ascites, encephalopathy and hepatocellular carcinoma. Additional options include transient elastography (Fibroscan), real-time shear wave elastography and MR elastography that can assess the whole liver and avoid sampling error (Karsdal et al., 2014).
Diagnostic performance of biomarkers
The most commonly used indirect serum markers are platelet count, coagulation factors, and transaminases. Direct markers reflect matrix turnover and include products of matrix synthesis or degradation. The most relevant markers include TNF-β, collagens (procollagen I C terminal, procollagen Ⅲ N terminal, procollagen Ⅳ C peptide and N peptide and collagen Ⅳ), tenascin, undulin, matrix metalloproteinases, urinary desmosine and hydroxylysypyridinoline (Chrostek, 2014).
The diagnostic performance of indirect non-invasive markers of liver fibrosis is evaluated by calculating the area under the receiver operating characteristic curve (AUROC). The plot shows the sensitivity and specificity of the tests (Schiavon, 2014). Commercially available plots include FibroTest (median AUROC in ALD 0.83), FibrometerA (0.83), Hepascore (0.83), Forns (0.38), APRI (0.59), FIB-4 (0.70), hyaluronic acid (0.79) and the algorithm combining PI, α-2 macroglobulin and hyaluronic acid (0.96). FibroTest, FibrometerA, and Hepascore showed the highest diagnostic accuracy, with prognostic values comparable to biopsy (Chrostek, 2014).
Chronic viral hepatitis
Hepatitis B (HBV)
The choice of antiviral therapy depends on stage and grade of the disease depending on serum ALT, HBV DNA, hepatitis B e antigen (HBeAg) status, and the level of hepatic necro-inflammation and fibrosis. Novel approaches include a variety of imaging techniques such as transient elastography, ultrasonography, computed tomography, and magnetic resonance imaging. No single marker can accurately measure fibrosis in HBV patients. Practitioners use a wide range of algorithms and combinations. The most relevant markers, according to Zeng et al., are platelet count, AST, and ALT, globin, serum HBsAg, ceruloplasmin, red blood cell distribution width, IL-2R, TGF-α and serum Golgi protein 73 (Zeng et al., 2016). Serum biomarkers used in HBV include haptoglobin, α-2 macroglobulin, apolipoprotein A1, GGT, total bilirubin, gamma globulin, AST, ALT, platelets, cholesterol, INR, albumin and bilirubin. Batteries of these tests are available commercially as Fibrotest, APRI, FIB-4, Forn’s, GUCI and Hui’s. Some of the diagnostic algorithms were developed as a measure of response to treatment (Branchi, 2014).
Hepatitis C (HCV)
Indirect serum biomarkers of liver fibrosis include routine liver function tests such as AST, ALT, GGT, platelet count, bilirubin, haptoglobin, apolipoprotein A1, and α-2 macroglobulin. The most common models for fibrosis estimation in hepatitis C are the AST/ALT ratio, AST-to-Platelet Ratio Index – APRI (median AUROC in HCV 0.77) and FIB-4 (0.74), Forns index (0.76) and Fibroindex (0.76) (Schiavon, 2014).
Fibrosis
Chronic liver diseases such as the progressive form of hepatitis C, NASH, autoimmune hepatitis, and primary biliary cirrhosis represent a significant risk of liver fibrosis. Non-invasive markers of NAFLD-induced fibrosis that correlate with high-risk of liver complications and death include NAFLD fibrosis score, AST/platelet ratio index, FIB-4 score, and BARD score. These markers are valuable when ruling out fibrosis in patients who would not benefit from liver biopsy (Neuman, Cohen, and Nanau, 2014). The NAFLD Fibrosis Score is designed to rule out advanced fibrosis based on age, hyperglycemia, BMI, platelet count, albumin, and AST/ALT ratio. Commercially available algorithms designed for staging and grading of the disease include Fib-4, FibroTest, NashTest, and SteatoTest (Neuman et al., 2016). Non-invasive direct biomarkers of liver fibrinogenesis indicate deposition or removal of extracellular matrix in the liver, while indirect markers reflect changes in processes induced by fibrosis. Direct markers include glycoproteins hyaluronic acid and laminin, collagens (type IV, type III and N-terminal peptide), matrix metalloproteinases, and cytokines TNF α and TGF β, in addition to standard liver function tests such as platelet count, alanine transaminases (ALT and AST), and AST-to-platelets ratio (APRI).
More sophisticated tests include Fibrotest (Bio-predictive), Forn’s index, and Hepascore (PathWest), in addition to imaging methods such as ultrasound-based elastography (Caviglia et al., 2014).
Stiffness is another indicator of liver fibrosis; however, obesity often prevents proper interpretation of the results. The use of transient elastography (FibroScan) XL probe, acoustic radiation force impulse (ARFI), proton magnetic resonance imaging (MRI), two-dimensional magnetic resonance elastography (2D MRI), and novel 3D MRI can further assist grading and staging of liver fibrosis (Neuman et al., 2016).
Metabolomics and proteomics in NAFLD/NASH
Additional markers can be identified using metabolomics and proteomics techniques. Metabolomics analysis shows an association of NAFLD with elevated glycocholate, taurocholate and glyco-cheno-deoxycholate as well as homocysteine and total cysteine and lower plasma glutathione. In NASH and steatosis, plasma levels of long-chain fatty acids and cysteine-glutathione were lower while the levels of several glutamyl dipeptides, free carnitine, butyrylcarnitine and methylbutyrylcarnitine were increased. Proteomic analysis shows that metabolic profile correlates with level of obesity. Proteins upregulated in NAFLD include afamin, apolipoprotein E, CD5 molecule-like, complement C3, insulin-like growth factorbinding protein 3, vitamin D-binding protein and lymphocyte cytosolic protein. Proteins upregulated in NASH are apolipoprotein E, catalase, CD5 molecule-like, lymphocyte cytosolic protein 1 and vitamin D-binding protein. Additional variants of metabolic and proteomic profile can be found in different ethnic groups (Neuman, Cohen and Nanau, 2014).
Inflammatory markers
Cytokines imbalance lead to liver injury through lipotoxicity and signaling processes. Lipopolysaccharides absorbed from the gut is transferred from the portal vein to the liver depends on gut microbiota. Inflammatory markers present in NAFLD/NASH include TNF-α, interleukin (IL)-6 and IL-8, matrix metalloproteinases and high-sensitivity C-reactive protein (hsCRP). Elevated levels of hyaluronic acid indicate advanced fibrosis and steatosis (Neuman et al., 2016).
Cell death markers
The most relevant markers of apoptosis are cytokeratin (CK)-18. The protein’s fragments can be detected in peripheral blood by immunoassay. The M30 assay, M65 and M65ED detect total cell death with varying range of sensitivity and specificity. Fibrosis patterns can be evaluated by immunostaining technique CK-7 that serves as an indicator of the number of hepatic progenitor cells and ductular reaction. Significantly higher caspase activity can be observed in patients with NASH (Neuman, Cohen and Nanau, 2014). Review of 15 studies in NASH patients shows that CK-18 fragments including M30 and M65 can be used to distinguish NASH from simple steatosis and assess disease progression. The levels of a liver-secret-hormone FGF-21 are significantly higher in patients with NAFLD, suggesting its potential value in the diagnosis of NAFLD/NASH. More data is needed to establish reference points and cut of values. These markers are not yet widely used in clinical practice due to technical and accuracy issues (He et al., 2017)
Cirrhosis
Patients with ALD or other chronic liver conditions often present only in final stages when they experience symptoms of bleeding and ascites. Identification of those at risk of fast progression can prevent and treat complications. Remodeling processes in cirrhotic liver lead to a release of a wide range of intracellular and extracellular proteins in the bloodstream. Neo-epitope based markers represent a unique fingerprint of this process and reflect the turnover of fibrotic tissue. Degradation products of type I collagen are used as indicators of bone resorption, multiple myeloma, and liver fibrosis. The diagnostic marker for liver fibrosis is PIIINP, a pro-peptide of type III collagen, which is cleaved off the pro-collagen during formation of mature collagen. PIIINP can be detected using monoclonal antibodies embedded into ELISA. A fragment of type III collagen (C3M) is a biomarker of inflammation-induced soft tissue turnover. Protein fingerprints have to be carefully interpreted in clinical context of full clinical picture (Karsdal et al., 2014).
Hepatocellular carcinoma (HCC)
High-risk factors for the development of HCC is chronic liver disease caused by HCV and HBV infection, chronic alcohol abuse, NAFLD/NASH, and progression to fibrosis, cirrhosis and eventually cancer. HCC tops the list of cancer-related mortality due to late diagnosis and limited treatment options for advanced stages of the disease. The most widely used biomarker for HCC is alphafetoprotein (AFP) that lacks the necessary sensitivity and specificity. Currently, advanced radiological surveillance methods are recommended for patients with chronic liver disease to detect HCC at time when tumor resection, ablation, transarterial chemoembolization and liver transplant are still possible (Kimhofer et al., 2015).
HCC biomarkers
Emerging biomarkers for HCC include the identification of proteins, peptides and metabolites in accessible bodily fluids, notably des-carboxy prothrombin, squamous cell carcinoma antigen–immunoglobulin M complexes, and chromogranin A. Bile acids (glycochenodeoxycholic acid, glycocholic acid, CA, and deoxycholic acid) are extensively studied as indicators of hepatic decompensation and a major source of oxidative stress.
Lysophosphatidylcholines (C16:0, LPC C18:0, and LPC C18:2) decrease in patients with HCC compared to cirrhosis. Metabolic changes affect also the synthesis and degradation of aminoacids, observable as a drop in branched chain aminoacids (leucine, isoleucine, and valine) and the increase in aromatic amino acids (tyrosine, phenylalanine, tryptophan and histidine). Creatinine and trimethylamine-N-oxide (TMAO) also drop in HCC patients. The best model appears to be scanning of the whole serum protein fraction using LC-MS (100% sensitivity and 100% specificity) and its reduced version based on scanning canavaninosuccinate and AFP (96.4% and 100%). Other promising biomarkers are propionylcarnitine and betaine, haptoglobin and fucosylated haemopexin. The full clinical picture has to be considered because biochemical markers of a minor tumor on extensively cirrhotic liver differ substantially from a large tumor on the background of mild cirrhosis (Kimhofer et al., 2015).
Validation of biomarkers
There is an increasing need for classification of biomarkers to facilitate their use and interpretation. Non-invasive markers of fibrosis are validated against the gold standard tool, which is a liver biopsy. However, equivocal results can be expected in about a third of biopsy specimens. (Duarte-Rojo, Altamirano and Feld, 2012). The osteoarthritis (OA) Biomarkers Network, funded by the US National Institutes of Health (NIH), proposed the BIPED approach to classification of biomarkers. The classification takes into account burden of disease, and investigative, prognostic and diagnostic attributes in addition to the efficacy of the intervention. Similarly, in liver fibrosis, an imprecise gold standard makes the validation of non-invasive markers challenging (Karsdal et al., 2014). Non-invasive biomarkers may, in fact, better reflect the true progression of the disease than a liver biopsy and must be assessed in longitudinal studies for predictive value in clinical outcomes (Duarte-Rojo, Altamirano and Feld, 2012).
Conclusion
Many critical gaps still exist for the evaluation of chronic liver disease and its progression. Non-invasive biomarkers are being developed to detect progression of liver damage, select appropriate treatment strategies, and measure response to treatment. Biomarkers also help avoid liver biopsy in patients in whom advanced stages of the liver disease can be excluded and who would not benefit from the additional information provided by the procedure. A reference library of normal values of various tests in different population subgroups, including ethnic groups and patients with comorbidities, needs to be developed to make these new tests useful in clinical practice. Validation of biomarkers remains a major challenge, making their utilization in establishing safety profiles of medications in patients with NAFLD/NASH especially challenging.
References
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