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NASH Diagnostics™ panel and its comparison to APRI and ELF/OELF tests in morbidly obese cohort

Zobair Younossi, Aybike Biredinc, Sandy Page, Maria Stepanova, Michael Estep, Yun Fang, Arian Afendi, Hazem Elariny, Z. Goodman, Vikas Chandhoke, Ancha Baranova

This work is based on our previous study "A biomarker panel for non-alcoholic steatohepatitis (NASH) and NASH-related fibrosis" published in Obesity Surgery in 2011

This is a collaborative project between

School of Systems Biology, College of Science,George Mason University, Fairfax, VA

Translational Reseach Institute, Inova Hospital, VA

As the importance of non-alcoholic fatty liver disease (NAFLD) is being increasingly appreciated, it is also becoming important to distinguish its subtypes. At one end of the NAFLD spectrum is simple steatosis, and at the other end are nonalcoholic steatohepatitis (NASH), NASH-related cirrhosis and hepatocellular carcinoma. The distinction between NASH and steatosis alone is important because of their differential risks for potential for progression. While simple steatosis is relatively benign, NASH can progress to cirrhosis. Even in 2007, the only method to accurately establish the diagnosis of NASH or to stage the liver disease is through a liver biopsy using strict pathologic criteria. Despite significant improvements, liver biopsy remains invasive and costly, associated with potentially important complications occurring in approximately 0.5% of cases. Additionally, histologic lesions of NASH may not be evenly distributed throughout the liver parenchyma, leading to potentially sampling errors. If biopsy has inadequate length or fragmented, making the correct diagnosis becomes even more challenging.
Among the experimental alternatives to the liver biopsy are non-invasive panels of biomarkers or scoring system including both serum tests and clinical parameters, e.g. age or body mass index. Recently, two markers of apoptosis and necrosis were suggested as markers of NASH: cleaved and uncleaved forms of cytokeratin 18 apotosis. Additionally, adipocytokines secreted by White Adipose Tissue of patients with visceral obesity, have been shown to play an important role in the pathogenesis of NASH. In our previous study we developed a panel of biomarkers, NASH Diagnostics™, consisting of two adipokines and two biomarkers of cellular death. This panel predicts the presence of NASH potentially decreasing the number of required biopsies. NASH Diagnostics™ needs to be extensively validated and cross-compared with other existing predictive assays in various cohorts of the patients with NAFLD. After careful validation, this panel of biomarkers may become very useful in the clinical management of these patients.
A significant portion of patients with NAFLD subsequently develop other liver pathology, including fibrosis which is a progenitor and the key histologic predictor of liver cirrhosis. The connection between NASH and fibrosis may reside in the role of inflammation in the development of both diseases. The relationship between NASH and hepatic fibrosis is so intertwined that some propose to use serum hepatic fibrosis markers as auxillary component for the diagnosis of NASH. Several serum markers of fibrosis have been developed, particularly, aspartate transaminase platelet ratio index (APRI), Original European Liver Fibrosis (OELF) panel that contain age, hyaluronic acid, amino-terminal propeptide of type III collagen, and tissue inhibitor of matrix metalloproteinase 1 and its simplified version ELF that does not include age. Some, but not all of the serum markers of fibrosis were tested in the cohorts of the patients with NAFLD in order to predict the presence of the fibrotic changes. Given an urgent need for the development, optimization and validation of the serum based non-invasive diagnostic biomarkers for NASH, it is important to evaluate the components of the fibrosis predicting panels as the potential source for an improvement of NASH diagnostics.

This study examines the performance of a new biomarker panel for NASH and NASH-related fibrosis with a combination of clinical and laboratory variables.

Enrolled patients had biopsy-proven NAFLD. Clinical data, laboratory data, and serum samples were collected at the time of biopsy. Fasting serum was assayed for adiponectin, resistin, glucose, M30, M65, Tissue inhibitor of metalloproteinases-1 (Timp-1), ProCollagen 3 N-terminal peptide (PIIINP), and hyaluronic acid (HA). Regression models predictive of NASH, NASH-related fibrosis, and NASH-related advanced fibrosis were designed and cross-validated.

Of the 79 enrolled NAFLD patients, 40 had biopsy-proven NASH and 39 had non-NASH NAFLD. Clinical and laboratory data were from this cohort were used to develop a NAFLD Diagnostic Panel that includes three models (models for NASH, NASH-related fibrosis, and NASH-related advanced fibrosis). The model for predicting NASH includes diabetes, gender, BMI, triglycerides, M30 (apoptosis), and M65-M30 (necrosis) [AUC: 0.81, 95% CI, 0.70-0.89, 300 p value <9E 301 (-06)]. The NASH-related fibrosis prediction model includes the same predictors [AUC: 0.80, 95% CI 0.68-0.88, 307 p value <0.00014]. Finally, the NASH-related advanced fibrosis model includes type 2 diabetes, serum triglycerides, Timp-1, and AST [AUC: 0.81, 95% CI, 0.70-0.89; p value, 0.000062].

This NAFLD Diagnostic Panel based on a clinical and laboratory data has good performance characteristics and is easy to use. This biomarker panel could become useful in the management of patients with NAFLD.

This work is a continuation of our previous study published in Obes Surg. 2008 Nov;18(11):1430-7.

Comment in: Obes Surg. 2008 Nov;18(11):1507-8; author reply 1509-10.

A novel diagnostic biomarker panel for obesity-related nonalcoholic steatohepatitis (NASH).

Younossi ZM, Jarrar M, Nugent C, Randhawa M, Afendy M, Stepanova M, Rafiq N, Goodman Z, Chandhoke V, Baranova A.

BACKGROUND: Within the spectrum of nonalcoholic fatty liver disease (NAFLD), only patients with nonalcoholic steatohepatitis (NASH) show convincing evidence for progression. To date, liver biopsy remains the gold standard for the diagnosis of NASH; however, liver biopsy is expensive and associated with a small risk, emphasizing the urgent need for noninvasive diagnostic biomarkers. Recent findings suggest a role for apoptosis and adipocytokines in the pathogenesis of NASH. The aim of this study was to develop a noninvasive diagnostic biomarker for NASH. METHODS: The study included 101 patients with liver biopsies who were tested with enzyme-linked immunosorbent assay (ELISA)-based assays. Of these, 69 were included in the biomarker development set and 32 were included in the biomarker validation set. Clinical data and serum samples were collected at the time of biopsy. Fasting serum samples were assayed for adiponectin, resistin, insulin, glucose, TNF-alpha, IL-6, IL-8, cytokeratin CK-18 (M65 antigen), and caspase-cleaved CK-18 (M30 antigen). RESULTS: Data analysis revealed that the levels of M30 antigen (cleaved CK-18) predicted histological NASH with 70% sensitivity and 83.7% specificity and area under the curve (AUC) = 0.711, p < 10(-4), whereas the predictive value of the levels of intact CK-18 (M65) was higher (63.6% sensitivity and 89.4% specificity and AUC = 0.814, p < 10(-4)). Histological NASH could be predicted by a combination of Cleaved CK-18, a product of the subtraction of Cleaved CK-18 level from intact CK-18 level, serum adiponectin, and serum resistin with a sensitivity of 95.45% sensitivity, specificity of 70.21%, and AUC of 0.908 (p < 10(-4)). Blinded validation of this model confirmed its reliability for separating NASH from simple steatosis. CONCLUSIONS: Four ELISA-based tests were combined to form a simple diagnostic biomarker for NASH.

Figure 1. CK-18 neoepitope (M30 antigen) levels are significantly increased in the serum of NASH patients in comparison to patients with Simple Steatosis and Controls. On this scatter plot, each dot represents one subject, and dashed line represents the mean value for each group.

Table1. Results of the blinded validation of NASH Diagnostics™  model predicting NASH. AUC (Area Under the Curve) of this model is 0.732 with 95% confidence interval of (0.546 – 0.872).