Comparison of Non-Invasive Clinical Algorithms for Liver Fibrosis in Patients With Chronic Hepatitis B to Reduce the Need for Liver Biopsy: Application of Enhanced Liver Fibrosis and Mac-2 Binding Protein Glycosylation Isomer
2022; 42(2): 249-257
Ann Lab Med 2021; 41(1): 16-24
Published online January 1, 2021 https://doi.org/10.3343/alm.2021.41.1.16
Copyright © Korean Society for Laboratory Medicine.
Nobuharu Tamaki , M.D., Ph.D.1,2, Masayuki Kurosaki , M.D., Ph.D.1, Rohit Loomba , M.D., M.H.S.2, and Namiki Izumi, M.D., Ph.D.1
1Department of Gastroenterology and Hepatology, Musashino Red Cross Hospital, Tokyo, Japan; 2NAFLD Research Center, Division of Medicine, University of California, San Diego, La Jolla, California, USA
Correspondence to: Namiki Izumi, M.D., Ph.D.
Department of Gastroenterology and Hepatology, Musashino Red Cross Hospital, 1-26-1 Kyonan-cho, Musashino-shi, Tokyo 180-8610, Japan
Tel: +81-422-32-3111
Fax: +81-422-32-9551
E-mail: izumi012@musashino.jrc.or.jp
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
An accurate evaluation of liver fibrosis is clinically important in chronic liver diseases. Mac-2 binding protein glycosylation isomer (M2BPGi) is a novel serum marker for liver fibrosis. In this review, we discuss the role of M2BPGi in diagnosing liver fibrosis in chronic hepatitis B and C, chronic hepatitis C after sustained virologic response (SVR), and nonalcoholic fatty liver disease (NAFLD). M2BPGi predicts not only liver fibrosis but also the hepatocellular carcinoma (HCC) development and prognosis in patients with chronic hepatitis B and C, chronic hepatitis C after SVR, NAFLD, and other chronic liver diseases. M2BPGi can also be used to evaluate liver function and prognosis in patients with cirrhosis. M2BPGi levels vary depending on the etiology and the presence or absence of treatment. Therefore, the threshold of M2BPGi for diagnosing liver fibrosis and predicting HCC development has to be adjusted according to the background and treatment status.
Keywords: Mac-2 binding protein glycosylation isomer, Liver fibrosis, Threshold, Hepatocellular carcinoma, Chronic hepatitis C, Chronic hepatitis B, Sustained virologic response, Nonalcoholic fatty liver disease
Liver fibrosis correlates with hepatocarcinogenesis and prognosis in chronic liver diseases; hence, an accurate evaluation of liver fibrosis is extremely important [1]. Although liver biopsy is currently the gold standard for liver fibrosis evaluation, it has many drawbacks, such as risk of complications and difficulty in repeated evaluation [2]. Therefore, various methods for the evaluation of noninvasive liver fibrosis have been developed recently, including elastography using magnetic resonance imaging or ultrasonography [3–11]. Although elastography has a high diagnostic ability for not only liver fibrosis but also liver steatosis [12, 13] and is widely used, it has a number of drawbacks, such as the requirement of expensive equipment, limited available facilities, and equipment incompatibility. Blood tests are also widely used to evaluate liver fibrosis and prognosis in patients with chronic hepatitis, and a two-step screening strategy to detect advanced fibrosis patients in a large population has been suggested [10, 14–17]. In the first-line screening, serum biomarkers are used to exclude patients with low risk of advanced fibrosis, and, in the second-line screening, patients with advanced fibrosis are identified by elastography. Recent advances in the non-invasive assessment of liver fibrosis based on serum biomarkers and imaging have been summarized in reviews [10, 18].
In Japan, serum Mac-2 binding protein (M2BP) glycosylation isomer (M2BPGi) was identified in 2013 and clinically applied as a diagnostic marker for liver fibrosis; it is now widely used, mainly in Asia [19–21]. The clinical use of M2BPGi has rapidly increased in recent years, because it can be easily measured in the serum, and M2BPGi measurement has been used to assess liver fibrosis and carcinogenesis risk in chronic liver diseases [20, 22–26].
In this review, we summarize the current knowledge on the utility of M2BPGi in diagnosing liver fibrosis in chronic hepatitis B and C, nonalcoholic fatty liver disease (NAFLD), and other liver diseases, and as a carcinogenic risk factor.
M2BP, a secreted glycoprotein present in the extracellular matrix, is associated with cell adhesion and correlates with liver fibrosis [27]. Recent advances in glycoproteomics have revealed that specific glycan structures of M2BP change as liver fibrosis progresses [28]. The concept of M2BPGi measurement involves the evaluation of liver fibrosis by measuring M2BP with an altered glycan structure. The change in the M2BP glycan structure was detected using the lectin
where [M2BPGi]sample is the M2BPGi level in the serum sample, PC is the positive control, and NC is the negative control. The PC was supplied as a calibration solution preliminarily standardized to yield a COI value of 1.0.
The pathophysiological role of M2BPGi is not completely elucidated. Hepatic stellate cells (HSCs) are the source of M2BPGi, and the M2BPGi secreted from HSCs induces Mac-2 expression in Kupffer cells, which in turn activates HSCs and increases alpha-smooth muscle actin expression [30]. These findings indicated that M2BPGi plays an important role in the progression of liver fibrosis and M2BPGi levels are associated with the fibrosis stage.
M2BPGi was developed as a biomarker using the serum of chronic hepatitis C patients and is now widely used for diagnosing liver fibrosis in chronic hepatitis C [19, 31–38]. Numerous studies have compared the diagnostic accuracy of M2BPGi with that of liver biopsy in identifying liver fibrosis stage. The mean COI values of M2BPGi in histological fibrosis stages 1, 2, 3, and 4 are 0.88–2.23, 1.81–3.86, 2.3–3.53, and 3.12–7.86, respectively (Table 1) [31–38]. In all cases, M2BPGi levels significantly increased as liver fibrosis progressed, which confirmed the utility of M2BPGi for diagnosing liver fibrosis in chronic hepatitis C. Liver fibrosis is a risk factor for carcinogenesis in chronic hepatitis C. Therefore, M2BPGi predicts the development of hepatocellular carcinoma (HCC). In studies on carcinogenesis, M2BPGi ≥4.0 indicated a high risk of HCC development (Table 2) [31, 32].
Another advantage of M2BPGi is that it can be measured easily and repeatedly. An increase in M2BPGi levels over time was associated with HCC risk [32, 39]. High M2BPGi levels also correlate with the prognosis of chronic hepatitis C [36]. A meta-analysis confirmed the utility of M2BPGi in diagnosing fibrosis and predicting HCC risk [21].
In recent studies, several patients achieved SVR with direct-acting antiviral (DAA) treatment [40–43]; hence, we discuss the role of M2BPGi in relation to SVR. M2BPGi not only strongly correlates with liver fibrosis but also weakly correlates with inflammation and alanine transaminase (ALT) [34, 36, 44]. Therefore, M2BPGi decreases rapidly during DAA treatment according to the improvement of inflammation or ALT level [45, 46]. M2BPGi also increases during acute liver injury [47]. The threshold of M2BPGi for predicting HCC development after SVR should be adjusted because of the improved inflammation. In studies examining the risk of HCC development after SVR, M2BPGi at SVR of 1.0–2.0, which was lower than that during continuous infection with hepatitis C virus, indicated a carcinogenic risk (Table 2) [48–51].
M2BPGi levels in patients with chronic hepatitis B increase as liver fibrosis progresses. The mean M2BPGi COI values in histological fibrosis stages 1, 2, 3, and 4 are 0.26–0.9, 0.34–1.36, 0.57–1.65, and 1.21–3.1, respectively (Table 1) [52–58]. M2BPGi was significantly lower in patients with chronic hepatitis B than in those with chronic hepatitis C [59]. Therefore, it is necessary to adjust the threshold of M2BPGi for liver fibrosis diagnosis, considering its etiology.
In cross-sectional studies examining the association of M2BPGi with HCC, M2BPGi level was significantly higher in patients with HCC than in those without HCC [60, 61]. When the presence or absence of HCC was evaluated after the fibrosis stages were adjusted, no difference in M2BPGi levels was found [58], which was considered to reflect its carcinogenic potential due to fibrosis progression. Longitudinal observational studies have reported that patients with M2BPGi level ≥0.71–2.0 have a high risk of HCC development (Table 2) [53, 58, 62–69]. In considering the risk of carcinogenesis, the presence or absence of treatment should be considered. M2BPGi level decreases with nucleotide/nucleoside analogue (NA) treatment [53, 56]. Therefore, it is necessary to reduce the threshold when evaluating M2BPGi level during NA treatment, because M2BPGi level decreases with improvement in fibrosis and inflammation. M2BPGi level ≥1.2 during NA treatment is associated with carcinogenesis and prognosis of chronic hepatitis B [60, 61], and the threshold tends to be lower than in treatment-naive cases. On the contrary, another study showed that the M2BPGi level during NA treatment is not associated with carcinogenesis [70], and further verification is needed in this regard.
The utility of M2BPGi for diagnosing liver fibrosis in NAFLD has been reported. The mean M2BPGi COI values in histological fibrosis stages 1, 2, 3, and 4 were 0.62–0.71, 0.7–1.17, 1.2–1.57, and 1.6–2.96, respectively, and M2BPGi levels increased with the progression of liver fibrosis (Table 1) [71–75]. M2BPGi level has a higher diagnostic accuracy for fibrosis than FIB-4 or NAFLD fibrosis score [71]. The threshold of M2BPGi for predicting F3–4 according to these reports was 0.83–1.23 and that for predicting F4 was 1.26–1.46 [71–75]. In a report comparing the threshold of M2BPGi for diagnosing liver fibrosis between chronic hepatitis C and NAFLD, the threshold for predicting F3–4 in NAFLD was lower than that for predicting F3–4 in chronic hepatitis C; hence, it is necessary to consider the underlying liver disease when interpreting the M2BPGi results for the diagnosis of liver fibrosis [76]. Although FIB-4 is used for diagnosing liver fibrosis in NAFLD, its diagnostic accuracy is not enough, unless the threshold is adjusted according to age [77]. In a study comparing M2BPGi level and FIB-4, the optimal threshold of FIB-4 increased with age, whereas that of M2BPGi remained unchanged; this finding indicated that M2BPGi has a high potential for advanced fibrosis screening in large populations [78]. In a report examining its association with carcinogenesis (an M2BPGi level of 1.255 as the threshold), a higher level indicated an increased risk of subsequent carcinogenesis [79]. Other reports have also suggested that M2BPGi level is associated with carcinogenesis and liver-related complications [80]. Recently, it was reported that M2BPGi level is useful for predicting advanced fibrosis in health checkups [81].
M2BPGi level increases when compensated cirrhosis develops to decompensated cirrhosis [82–84]. Therefore, in patients with cirrhosis, high M2BPGi levels indicate a poor prognosis [82, 85, 86]. M2BPGi is reportedly useful as a predictive marker for liver failure and complications after hepatectomy or transcatheter arterial chemoembolization [82, 87–91]. Thus, M2BPGi level reflects not only liver fibrosis but also liver function. M2BPGi level is also associated with recurrence and prognosis after hepatectomy and can be used for follow-up after HCC therapy [92–94]. Sarcopenia has recently attracted attention as a complication of cirrhosis. M2BPGi level is correlated with muscle mass and is useful as a predictive marker for sarcopenia [95, 96]. Thus, M2BPGi level is useful in patients with cirrhosis as it correlates with cirrhosis complications and prognosis.
M2BPGi level is useful for diagnosing liver fibrosis in autoimmune hepatitis [97, 98], primary biliary cholangitis [99, 100], biliary atresia [101, 102], and primary sclerosing cholangitis [103], in addition to viral hepatitis and NAFLD; but relevant studies are limited in number and need validation.
The clinical utility of M2BPGi in chronic liver diseases is shown in Fig. 1. M2BPGi levels increase as the disease progresses. M2BPGi can be used to assess disease status, such as that of liver fibrosis [31–38, 52–58, 71–75], HCC risk [31, 32, 36, 48–51, 53, 58, 62–69, 79, 104], HCC recurrence risk [92–94], liver function [82, 87–91], and prognosis of chronic liver diseases [82–86], with progression of the disease. In one relevant meta-analysis, the sensitivities and specificities for predicting significant fibrosis (≥F2), advanced fibrosis (≥F3), and cirrhosis were 0.690, 0.764, and 0.818 and 0.778, 0.758, and 0.839, respectively [21]. The hazard ratios for HCC development and overall survival were 5.946 and 1.068, respectively. The study included different etiologies, and the results indicated that the diagnostic accuracy differs depending on the etiology [21]. In the future, a meta-analysis needs to be performed separately for each etiology. Nearly all studies cited in this article reported the utility of M2BPGi; however, publication bias may exist, and further investigation is required. Furthermore, the clinical utility of M2BPGi in patients with alcoholic liver diseases or liver transplantation has not been sufficiently investigated and requires further investigation [105].
M2BPGi is useful for diagnosing liver fibrosis in chronic hepatitis B and C, chronic hepatitis C after SVR, and NAFLD and for predicting HCC risk in these diseases. It is also useful for evaluating liver function in patients with cirrhosis, predicting complications and prognosis. It should be noted that M2BPGi levels vary depending on the etiology of the disease and the presence or absence of treatment.
Clinical utility of M2BPGi in chronic liver diseases. The M2BPGi levels increase as the disease progresses from minimal liver fibrosis to decompensated cirrhosis. M2BPGi can be used to assess disease status, such as liver fibrosis, HCC risk, HCC recurrence risk, liver function, and prognosis of chronic liver diseases, with the progression of the disease.
Abbreviations: M2BPGi, Mac-2 binding protein glycosylation isomer; HCC, hepatocellular carcinoma.
Thresholds of M2BPGi in liver fibrosis
Reference | Etiology | Mean value of M2BPGi | Threshold for diagnosing fibrosis stage | ||||||
---|---|---|---|---|---|---|---|---|---|
F0 | F1 | F2 | F3 | F4 | ≥F2 | ≥F3 | F4 | ||
Yamasaki, | HCV | 1.3 | 2.2 | 3.3 | 5.2 | ||||
Tamaki, | HCV | 0.81 | 1.82 | 2.31 | 7.5 | ||||
Ura, | HCV | 1.6 | 3.86 | 3.53 | 3.12 | 2.14 | 2.17 | ||
Huang, | HCV | 2.23 | 3.45 | 3.48 | 3.77 | 1.61 | 1.42 | 2.67 | |
Fujita, | HCV | 1.26 | 1.81 | 4.03 | 7.86 | 2.19 | |||
Inoue, | HCV | 2.3 | 6.9 | ||||||
Nakamura, | HCV | 1.7 (F1–2) | 5.1 (F3–4) | ||||||
Xu, | HCV | 0.88 | 1.70 (F2–3) | 5.68 | 0.95 | 1.35 | |||
0.88–2.23 | 1.81–3.86 | 2.3–3.53 | 3.12–7.86 | ||||||
Ishii, | HBV | 0.9 | 1.4 | 1.6 | 3.1 | 1.4 | 1.4 | 1.9 | |
Ichikawa, | HBV | 0.75 | 1.14 | 1.03 | 1.64 | 0.94 | 1.26 | 1.26 | |
Yeh, | HBV | 0.64 | 1.36 | 1.65 | 2.7 | 1.35 | 1.54 | 1.67 | |
Jekarl, | HBV | 0.68 | 0.87 | 1.65 | 0.7 | 0.7 | |||
Mak, | HBV | 0.26 | 0.34 | 0.57 | 1.21 | 0.25 | 0.45 | 0.96 | |
Wei, | HBV | 0.88 | 1.17 (F2–3) | 1.92 | 1.12 | 1.83 | |||
Jun, | HBV | 0.80 (F1–3) | 2.67 | ||||||
0.26–0.9 | 0.34–1.36 | 0.57–1.65 | 1.21–3.1 | ||||||
Abe, | NAFLD | 0.57 | 0.7 | 1.02 | 1.57 | 2.96 | 0.94 | 1.46 | |
Ogawa, | NAFLD | 0.43 | 0.62 | 0.92 | 1.12 | 2.94 | 0.83 | 0.83 | 1.26 |
Nishikawa, | NAFLD | 0.7 | 0.7 | 1.2 | 1.6 | 1.1 | 1.6 | ||
Atsukawa, | NAFLD | 0.71 | 1.17 | 1.36 | 1.98 | 1.23 | 1.37 | ||
Alkhouri, | NAFLD | 0.66 (F0–1) | 1.2 (F2–3) | 2.4 | |||||
0.62–0.71 | 0.7–1.17 | 1.2–1.57 | 1.6–2.96 |
Thresholds of M2BPGi in HCC development
Reference | Etiology | Treatment status | Threshold of M2BPGi for HCC risk | HR (95% CI) |
---|---|---|---|---|
Yamasaki, | HCV | ≥4 | 8.3 (1.8–38) | |
Tamaki, | HCV | ≥4.2 | 4.1 (1.1–15) | |
≥0.3 increase/yr | 5.5 (1.5–19) | |||
Inoue, | HCV | ≥4 (mortality risk) | ||
Sasaki, | HCV SVR | ≥2.0 | 5.7 (1.7–20) | |
Nagata, | HCV SVR | ≥1.8 | 2.0 (1.4–2.4) | |
Yasui, | HCV SVR | ≥1.75 | 6.0 (1.8–19) | |
Akuta, | HCV SVR | ≥1.0 | 4.9 (1.4–18) | |
Ichikawa, | HBV | Naive | ≥0.71 | 8.3 (1.0–67) |
Jun, | HBV | Naive | Each 1 increase | 1.1 (1.05–1.18) |
Liu, | HBV | Naive | ≥2.0 (1–2 yr HCC) | 7.4 (2.4–23) |
Kim, | HBV | Naive | ≥1.8 | 1.5 (1.1–2.1) |
Mak, | HBV | NA treatment | ≥1.15 before NA treatment | 1.2 (1.04–1.5) |
Kawaguchi, | HBV | NA treatment | ≥1.2 after NA treatment | 10.5 (3.0–38) |
Shinkai, | HBV | NA treatment | ≥1.2 after NA treatment | 5.0 (1.7–15) |
Su, | HBV | NA treatment | Each 1 increase after NA treatment | 1.6 (1.2–2.1) |
Heo, | HBV | Naive/NA treatment | ≥1.8 | 11.5 (1.4–97) |
Mak, | HBV | Naive/NA treatment | ≥0.68 | 4.7 (1.3–17) |
Kawanaka, | NAFLD | ≥1.255 | 1.7 (1.1–2.3) |