ReviewMetabolomic profiling for drug-induced liver injury with autoantibodies
Introduction
Drug induced liver injury (DILI) refers to the disease caused by drugs or their metabolites and / or liver allergic reaction to drugs and metabolites [1]. DILI is more common in women, and most patients are acute, self-healing, and negative in autoantibodies [2]. However, clinically, some patients with DILI can be accompanied by autoantibody [3]. Some DILI with autoantibodies had serological and histological characteristics of classical autoimmune hepatitis (AIH) [2], [4]. For example, Ynto S. de Boer et al. [3] reported that nearly half of patients with liver injury caused by tetracycline and furantoin had serological characteristics similar to AIH. In DILI induced by clomiphene, serum IgG increased significantly in 80 % of patients, and anti-nucleic antibody (ANA) or anti-smooth muscle antibody (ASMA) was positive in 60 % of patients [5]. DILI induced by immune checkpoint inhibitors is also accompanied by autoantibodies [6]. In addition to DILI with autoantibodies, bleomycin can also cause systemic sclerosis, which is also an autoimmune disease [7]. Besides, the classic histological characteristics of AIH, such as interface hepatitis, infiltration of plasma cells, lymphocytes and eosinophils in portal area, central lobular necrosis and so on, can also appear in DILI patients [8], [9].
To describe these DILI, some blended terms such as “autoimmune-like” DILI (AL-DILI)[2], “AIH DILI” [10] and so on came up. Albert J. Czaja called DILI with autoantibodies as drug-induced liver injury with autoimmune characteristics [11]. The clinical phenotype of AIH can be mimicked by some DILI with autoantibodies, or vice versa [2], [10]. Weiler-Normann and Schramm [12] proposed to divide the relationship between AIH and DILI into three combination types: AIH with DILI, drug induced AIH and immune mediated DILI in 2011. In a long term follow-up study of 685 patients with DILI, 23 patients had been hospitalized for liver disease and 5 of these were diagnosed with AIH after a mean of 5.8 years [13]. These patients need to take immunosuppressant for a long time to maintain the normal function of the body. Although some DILI with autoantibodies have similar serological and histological characteristics of classic AIH, and similar treatment response as AIH, the difference from AIH is that they have no recurrence after stopping immunosuppressive treatment [8], [11], [14], [15]. In addition, some DILI with autoantibodies did not respond to glucocorticoids [16], [17]. Their liver function can gradually recover when the offending drugs are stopped. Based on these situations, some clinicians or scholars tend to carry out glucocorticoid therapy only for those DILI patients with significant autoimmune signature [11], [18]. While for DILI without autoantibodies, it is generally considered that glucocorticoids therapy is not necessary. If glucocorticoids therapy is wrongly used, the risks outweigh the benefits for these patients [19]. Unfortunately, the current screening of those DILI patients with significant autoimmune signature is only empiric fashion of clinicians [18], [20].
Above observation suggest that although these DILI are accompanied by autoantibodies, there may be significant internal variation among them. In other words, we argue that DILI patients with autoantibodies may not be a community of same pathogenesis, and the pathologic mechanism of some patients may be similar to that of AIH patients or DILI patients without autoantibodies. Therefore, it is necessary to systematically characterize DILI with autoantibodies by holistic omics, so as to better understand the internal variation of these patients.
Metabolomics is a phenotypic method for studying metabolites, small molecule substrates, and intermediary metabolites which can directly reflect the potential biochemical activities and states of tissues or cells [21]. It is a powerful method to explore specific biomarkers of different liver diseases [22], and it is also very helpful to the diagnosis, treatment and prognosis of diseases [23]. Therefore, in this study, metabolomics was used to classify the metabolic variation of DILI with autoantibodies, in order to provide reference for clinical screening of DILI with significant autoimmune characteristics, so as to solve the current situation that clinicians can only empirically screen such patients.
Section snippets
Study design
Biobanked serum samples of patients with AIH or DILI hospitalized in the Fifth Medical Center of Chinese PLA General Hospital from January 31, 2015 to May 19, 2017 were collected, and baseline demographic and clinical data were obtained, regardless of age and gender. All cases were reassessed by two intermediate doctors. According to the diagnostic scoring system of AIH revised by the International Autoimmune Hepatitis Group (IAIHG) in 1999, AIH cases without glucocorticoid treatment and score
Demographic and clinical characteristics of the study Cohort
The demography and clinical characteristics among AIH, DILIAb+, and DILIAb- were presented in Table 1. There was no significant difference in the mean ages among AIH (49.3; 95 %CI: 47.6, 51.0), DILIAb+ (47.4; 95 %CI: 47.8, 50.0), and DILIAb-(47.9; 95 %CI: 45.1, 50.6). Female was dominant in all three groups. The levels of AST/ALT, IgG, Pt, γ- Globulin and the proportion of ascites gradually decreased in AIH, DILIAb+, and DILIAb-. The levels of ALT, CHE, TC, TG, ALB, WBC and PLT in DILIAb+ were
Discussion
Some DILIAb+ samples have serological and histological characteristics similar to classical AIH, which is easy to be confused in clinical diagnosis. It has shown that some DILI can progress to AIH with the extension of time [13]. When using glucocorticoids to treat DILI clinically, it is suggested paying attention to the selection of indications and screening DILI with significant autoimmune characteristics for treatment [30]. In this study, we found that DILIAb+ may be was not a community of
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by National Natural Science Foundation of China (Nos. 82074112, 81630100 and 82104702), National Science and Technology Major Project (No. 2015ZX09501-004-001-008) and Project of China PLA General Hospital (Nos. 2019-JQPY-003 and 2019MBD-023)
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These authors contributed equally to this work.