Non-Alcoholic Fatty Liver Disease, Non-Alcoholic Steatohepatitis
Conditions
Brief summary
Researchers are assessing the prevalence of Non-alcoholic Fatty Liver Disease (NAFLD) and Nonalcoholic Steatohepatitis (NASH) in the population and assembling a well-characterized cohort of adults with NAFLD and NASH to validate models of NAFLD diagnosis and determine long-term outcomes.
Detailed description
Non-Alcoholic Fatty Liver Disease (NAFLD) is the most common cause of chronic liver disease in the world and a major public health issue in the US. Recent information on the prevalence of NAFLD in general and Non-Alcoholic Steatohepatitis (NASH) with fibrosis in particular is very scarce. Such information is crucial for defining the epidemiology of NAFLD, identifying risk factors for advanced fibrosis and longitudinal outcomes. This study will enroll a random sample of adults from Olmsted County, Minnesota, to validate machine learning models for NAFLD diagnosis and disease severity. These data would be fundamental for the development of screening strategies in the community, which are urgently needed for early diagnosis of liver fibrosis and therapeutic interventions before cirrhosis develops.
Interventions
Combines MRI imaging with sound waves to create a visual map (elastogram) showing the stiffness of body tissues.
Clinical blood tests with a focus on liver function parameters and diabetes
If indicated per MRE results a biopsy will be taken of the liver.
If indicated per MRE results a fibroscan will be performed of the liver.
Sponsors
Study design
Intervention model description
We will invite adult Olmsted County residents with research authorization, identified based on a random search of the Rochester Epidemiology Project database. We plan to accrue 800 participants. Based on literature estimates, approximately 25-30% of adults will be at risk for NAFLD due to overweight/obese status. Participants will undergo tests for NAFLD screening: blood tests, Magnetic Resonance Imaging/Elastography and electrocardiogram. Those identified with fatty liver will undergo Transient elastography and liver biopsy for disease severity assessment. These results will be used to validate a machine learning model of NAFLD diagnosis and liver disease severity which uses the participants clinical and laboratory data (noninvasive electronic health records). The cohort will be followed for 5 years, when they will return for repeat imaging and blood tests to monitor for incident NAFLD, liver disease progression and outcomes.
Eligibility
Inclusion criteria
* Olmsted County residents at the time of search * Age 18 or older * No personal history of NAFLD diagnosis (administrative codes)
Exclusion criteria
* Alcohol in excess (more than 20 gm per week in women and 30 gm per week in men) * Currently pregnant * Have contraindications to MRI (MRI incompatible implanted devices, severe claustrophobia)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Prevalence of NAFLD and NASH in the population | 5 years | Number of subjects with NAFLD and NASH determined by the MRE |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Long-term health outcomes | 5 years | Number of participants to experience the development of NAFLD, NASH, NASH cirrhosis complications, liver transplant, cardiovascular events, cancers or death |
Countries
United States
Contacts
Mayo Clinic