Identification and Validation of Noninvasive Biomarkers of the Diagnosis and Severity of NASH in Type 2 Diabetics

Overview

Metabolic diseases of the liver are silent affections whose morbidity is important. About 70% of patients with type 2 diabetes (T2D) are concerned. Of these, 50% develop clinically significant lesions (including non-alcoholic steatohepatitis or NASH) as they are associated with an increased risk of complications; and 15% progress to severe fibrosis or cirrhosis. These diseases are slowly progressive and asymptomatic. Their pathophysiology is poorly known. Management is hampered by the absence of a specific diagnostic marker, the need for invasive diagnostic procedures (liver biopsy), and the lack of established treatment. QUID-NASH aims to develop a virtual liver biopsy in T2D participants, based on the identification of single or combined, multimodal, non-invasive biomarkers obtained by new quantitative imaging techniques (magnetic resonance and ultrafast ultrasound UFUS); and /or extensive clinical-biological phenotyping data; and/or data obtained by different omic approaches (metabolomics, targeted genetics, transcriptomics). Extracellular vesicle and immune cell profiling will complement these phenotyping data. This approach will also enable us to improve our understanding of pathophysiology (new signaling pathways, new therapeutic targets).

Metabolic diseases of the liver are silent affections whose morbidity is important. About 70% of patients with type 2 diabetes (T2D) are concerned. Of these, 50% develop clinically significant lesions (including non-alcoholic steatohepatitis or NASH) as they are associated with an increased risk of complications; and 15% progress to severe fibrosis or cirrhosis. These diseases are slowly progressive and asymptomatic. Their pathophysiology is poorly known. Management is hampered by the absence of a specific diagnostic marker, the need for invasive diagnostic procedures (liver biopsy), and the lack of established treatment. Non-invasive methods ("first-generation" tests) have recently seen significant growth: commercialization of FibroTest as a marker of fibrosis; FibroTest, Fibrometer and FibroScan, for the initial assessment of adult chronic hepatitis C; FibroTest, Fibrometer, and Enhanced Liver Fibrosis test (ELF-test) for diagnosis of metabolic liver disease and diagnosis of fibrosis; SteatoTest (APHP patent) for the diagnosis of steatosis. The ActiTest (APHP patent) is widely used in evaluating the necrotic-inflammatory activity of chronic viral hepatitis C and B. For the diagnosis of NASH alone the ActiTest is validated. The NashTest (APHP patent) is little used. Several biomarkers of imaging (liver ultrasound, FibroScan Controller Attenuated Parameter (CAP), elastography and nuclear magnetic resonance) are widely used for the diagnosis of steatosis. Two new "second generation" blood tests (APHP patents) are under development, Non Invasive Test-NASHr (NIT-NASHr), and NIT-A2F2. NIT-NASHr is a new combination of the components of SteatoTest and NASH-Test to assess the severity of NASH. NIT-A2F2 is a combination of NIT-NASHr and FibroTest for the diagnosis of clinically significant liver metabolic disease. These tests will be the subject in the project of a validation of their performances in the context of use (T2D without other liver disease). At the same time, significant progress has been made in integrating omic data to characterize various pathologies and to identify their mechanisms. The transcriptomics and metabolomics of body fluids are particularly promising for the construction of "third generation" tests. QUID-NASH aims to develop a virtual liver biopsy in T2D participants, based on the identification of single or combined, multimodal, non-invasive biomarkers obtained by new quantitative imaging techniques (magnetic resonance and ultrafast ultrasound UFUS); and / or extensive clinical-biological phenotyping data; and / or data obtained by different omic approaches (metabolomics, targeted genetics, transcriptomics). Extracellular vesicle and immune cell profiling will complement this data. This approach will also enable us to improve knowledge of the pathology (new signaling pathways, new therapeutic targets).