The Non-Invasive Biomarkers for Metabolic Liver Disease (NIMBLE) study is a comprehensive, multi-year collaborative effort to standardize, validate and advance the regulatory qualification of blood- and imaging-based biomarkers to diagnose and stage Metabolic dysfunction-associated steatohepatitis (MASH), previously known as nonalcoholic steatohepatitis (NASH). MASH is characterized by liver inflammation accompanied by simultaneous fat accumulation in the liver.
Provision of signed and dated informed consent form
Stated willingness to comply with all study procedures and availability for the duration of the study
Male or female, aged > 18 years and < 75 years
Known history or evidence of other forms of chronic liver disease other than MASLD/MASH including but not limited to viral hepatitis B or C, autoimmune liver disease, primary biliary cholangitis, primary sclerosing cholangitis, Wilson disease, hemochromatosis, drug-induced liver disease, conditions involving bile duct obstructions, liver cancer, past history of HCC or HCC treatment, listed for or history of liver transplantation, prior resection of liver, etc.
Current or past evidence of decompensated liver disease defined by overt ascites that is clinically obvious and requires diuretic therapy, overt encephalopathy requiring therapy or history of variceal hemorrhage
Circulating Alanine aminotransferase (ALT)> 5xULN
Ongoing or recent (within the last two years prior to screening) consumption of significantly greater than moderate amounts of alcohol.
This study will enroll participants with suspected or confirmed diagnosis of MASLD. Sex: Male and female participants Age: ≥ 18 and \< 75 years Population sample: Patients with a high probability of MASLD based on eligibility criteria (details under inclusion/exclusion criteria in Section 5.1) General health status: Patients with suspected or confirmed diagnosis of MASLD and no contraindications precluding participation in any study procedures. Geographic location: United States, multi-site
Cohort
Prospective
Not listed
Detection of At-Risk MASH
Evaluate the diagnostic performance of individual and combined biomarkers (e.g., NIS2+, ADAPT \[PRO-C3-based score\], MRI-AST (MAST) \[MRE + PDFF + AST\], FAST and Metabolomics-Advanced Steatohepatitis Fibrosis (MASEF) \[included in the OWLiver Test\]) for identifying at-risk MASH (MASH + MAS ≥4 + fibrosis stage ≥2).
Fibrosis Staging
Assess blood-based, imaging, and composite biomarkers (e.g., Enhanced Liver Fibrosis (ELF) Test, Liver Stiffness Measure (LSM) by VCTE, MRE, Agile 3+, Agile 4) for detecting clinically significant fibrosis (≥2), advanced fibrosis (≥3), and fibrosis stage 4 (cirrhosis, histologically defined).
Liver Fat Content Monitoring
Evaluate imaging-based biomarkers (e.g., MRI-PDFF, Hepatorenal Index, Controlled Attenuation Parameter (CAP)) for hepatic steatosis monitoring.
Diagnostic Enrichment
Identify biomarkers that enhance participant selection for clinical trials, focusing on populations with at-risk MASH, specific fibrosis stages, or steatosis.
Comparison to Fibrosis (FIB)-4 or other fibrosis-related standards
To compare the performance characteristics of one or more 1) blood-based biomarkers, 2) imaging-based biomarkers, 3) VCTE-based biomarkers and 4) multiparametric biomarkers to to FIB-4 or other fibrosis-related standards specific to the context of use (COU) for fibrosis in a population at risk for MASH with fibrosis.
Comparison to ALT or other activity-related standards.
To compare the performance characteristics of one or more 1) blood-based biomarkers, 2) imaging-based biomarkers, 3) VCTE-based biomarkers and 4) multiparametric biomarkers to ALT or other activity-related standards specific to the context of use (COU) of at-risk MASH in a population at risk for MASH with fibrosis.
Comparison to Histology.
To compare the performance characteristics of one or more 1) blood-based biomarkers, 2) imaging-based biomarkers, 3) VCTE-based biomarkers and 4) multiparametric biomarkers to histology standards to the context of use (COU) for steatosis in a population at risk for MASH with fibrosis.
AI-driven histology endpoints
a. Correlation of AI-based digital pathology results with traditional histological scoring systems (MAFLD Activity Score (MAS), fibrosis stages).
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