Prediction of treatment efficacy and risk of relapse for autoimmune hepatitis – PRETERRAH

Autoimmune hepatitis (AIH) is a rare chronic liver disease characterized by elevated serum aminotransferases, elevated IgG or gamma globulins, autoantibodies, and interface hepatitis on liver histology. The aim of the immunosuppression (IS) treatment is the achievement of a rapid, complete biochemical response within the first 6 months. After 2 or 3 years, attempts should be made to stop IS in order to avoid its long-term deleterious effects. Unfortunately, this is an ideal course of action, far from the reality for many patients. 15% of patients do not respond to the treatment within the first 4 weeks, and around 35% have an insufficient biochemical response within the first 6 months. These events of poor disease control entail an increased risk of liver failure, liver transplantation, and death. Among those who reach a state of remission (2 years of complete response) and in whom treatment discontinuation is attempted, the relapse rate is close to 60%.
The recent 2019 AASLD AIH guidelines cited prognostic and therapeutic biomarkers as a significant unmet need in AIH. We aim to obtain precise predictive models based on simple biomarker tests, to stratify patients and to adapt their treatment and follow-up. They would help increase the proportion of patients in remission, and later on, they would help identify those in whom complete treatment withdrawal has a good chance of success.
The objective is to answer three questions associated with clinical needs:
A) What are the markers at the time of diagnosis (baseline), predictive of non-response to treatment at 4 weeks?
B) What are the baseline markers predictive of insufficient biological response at 6 months?
C) After 2 years of complete remission, can we predict the risk of relapse, based on data collected before treatment discontinuation?
Until now, clinical and biochemical data collected at diagnosis and during follow-up do not in themselves robustly predict response to treatment. Our recent studies have demonstrated the importance of the lymphocyte response in AIH pathogenesis. In the DISTAL project (ANR 2019-23), we described the cellular and molecular signature of autoreactive CD4 T cells in the blood of AIH patients by flow cytometry and transcriptomic approaches. Both in the liver and in circulating blood, we have highlighted several lymphocyte markers associated with the pathology. In preliminary studies, we also show by multiplex immunofluorescence on liver biopsies the presence of tertiary lymphoid structures, with an enrichment of CD4 T cell subsets compatible with a pathogenic role.
We hypothesize that by analyzing lymphocyte markers through omics techniques in biopsies, serum, and PBMCs, and integrating these findings with standard biological and clinical markers, we can identify distinct patient response to treatment, and relapse risk, profiles.
The project relies on the multicentric BIO-MAI-FOIE biobank and associated database, dedicated to autoimmune liver diseases. Two cohorts will be constituted to answer the questions. It is divided into three work packages: WP1 : Acquisition and processing of clinical, biological and histological data for the identification of “classical” biomarkers ; WP2 : Acquisition and processing of omic data for the identification of innovative biomarkers : multiplex immunofluorescence on biopsies, single cell RNAseq on CD3+ T cells, and spectral flow cytometry on PBMC; WP3 : Implementation of personalized predictive scores routinely usable in the clinics.
By the end of this project, personalized predictive scores for each of the three questions will be established, based on the biomarkers identified in this discovery phase. They will be patented and a validation step on an independent European cohort of AIH patients will be the next step toward their clinical application.