1. Department of Nutrition, Food Science and Physiology. Centre for Nutrition Research. School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.
2. Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain.
3. CIBERobn, Physiopathology of Obesity and Nutrition. Instituto de Salud Carlos III. Madrid, Spain.
4. Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.
5. Liver Unit, Clinica Universidad de Navarra, Pamplona, Spain.
6. Clinical Chemistry Department, Clínica Universidad de Navarra, Pamplona, Spain.
7. Department of Internal Medicine, Clínica Universidad de Navarra, Pamplona, Navarra, Spain.
8. Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain.
9. Department of Gastroenterology, Complejo Hospitalario de Navarra, Pamplona, Spain.
10. Research Group on Community Nutrition and Oxidative Stress. University of Balearic Islands. Palma de Mallorca. Spain.
11. School of Biological Sciences, Dublin Institute of Technology, Dublin, Republic of Ireland.
12. IMDEA FOOD. Madrid.
Introduction: Non-alcoholic fatty liver disease (NAFLD) may progress to steatohepatitis, cirrhosis and complicated hepatocellular carcinoma with defined differential symptoms and manifestations.
Objective: To evaluate the fatty liver status by several validated approaches and to compare imaging techniques, lipidomic and routine blood markers with magnetic resonance imaging in adults subjects with non-alcoholic fatty liver disease.
Materials and methods: A total of 127 overweight/obese with NAFLD, were parallelly assessed by Magnetic Resonance Imaging (MRI), ultrasonography, transient elastography and a validated metabolomic designed test to diagnose NAFLD in this cross-sectional study. Body composition (DXA), hepatic related biochemical measurements as well as the Fatty Liver Index (FLI) were evaluated. This study was registered as FLiO: Fatty Liver in Obesity study; NCT03183193.
Results: The subjects with more severe liver disease were found to have worse metabolic parameters. Positive associations between MRI with inflammatory and insulin biomarkers were found. A linear regression model including ALT, RBP4 and HOMA-IR was able to explain 40.9% of the variability in fat content by MRI. In ROC analyses a combination panel formed of ALT, HOMA-IR and RBP4 followed by ultrasonography, ALT and metabolomic test showed the major predictive ability (77.3%, 74.6%, 74.3% and 71.1%, respectively) for liver fat content.
Conclusions: A panel combination including routine blood markers linked to insulin resistance showed highest associations with MRI considered as a gold standard for determining liver fat content. This combination of tests can facilitate the diagnosis of early stages of non-alcoholic liver disease thereby avoiding other invasive and expensive methods.
Keywords: MRI, liver fat content, ultrasound, ROC, FibroScan, NAFLD.