Association of Dietary Patterns with MRI Markers of Hepatic Inflammation and Fibrosis in the MAST4HEALTH Study

Athina I. Amanatidou, Andriana C. Kaliora, Charalampia Amerikanou, Stefan Stojanoski, Natasa Milosevic, Chara Vezou, Mirjana Beribaka, Rajarshi Banerjee, Ioanna-Panagiota Kalafati, Ilias Smyrnioudis, Mary Jo Kurth, Aimo Kannt, M. Pilar Francino, Sophie Visvikis-Siest, Panos Deloukas, Carlos Llorens, Fernando Marascio, Natasa Milic, Milica Medic-Stojanoska, Amalia Gastaldelli, Maria Giovanna Trivella and George V. Dedoussis
Additional contact information
Athina I. Amanatidou: Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece
Andriana C. Kaliora: Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece
Charalampia Amerikanou: Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece
Stefan Stojanoski: Center for Diagnostic Imaging, Oncology Institute of Vojvodine, 21204 Sremska Kamenica, Serbia
Natasa Milosevic: Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia
Chara Vezou: Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece
Mirjana Beribaka: Department of Biology, Faculty of Technology Zvornik, University of East Sarajevo, 75400 Zvornik, Bosnia and Herzegovina
Rajarshi Banerjee: Perspectum Ltd., Oxford OX4 2LL, UK
Ioanna-Panagiota Kalafati: Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece
Ilias Smyrnioudis: Chios Mastic Gum Growers Association, 82100 Chios, Greece
Mary Jo Kurth: Clinical Studies Group, Randox Laboratories Ltd., Crumlin BT29 4RN, UK
Aimo Kannt: Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, 60596 Frankfurt, Germany
M. Pilar Francino: Area de Genòmica i Salut, Fundació per al Foment de la Investigació Sanitá ria I Biomèdica de la Comunitat Valenciana (FISABIO-Salut Pú blica), 46020 Valencia, Spain
Sophie Visvikis-Siest: INSERM UMR U1122, IGE-PCV, Faculté de Pharmacie, Université de Lorraine, 30 Rue Lionnois, 54000 Nancy, France
Panos Deloukas: William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
Carlos Llorens: Biotechvana, Parc Científic, Universitat de València, Paterna, 46010 Valencia, Spain
Fernando Marascio: Intervideo Web Service, 88100 Catanzaro, Italy
Natasa Milic: Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia
Milica Medic-Stojanoska: Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia
Amalia Gastaldelli: Institute of Clinical Physiology National Research Council, 56124 Pisa, Italy
Maria Giovanna Trivella: Institute of Clinical Physiology National Research Council, 56124 Pisa, Italy
George V. Dedoussis: Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece

IJERPH, 2022, vol. 19, issue 2, 1-13

Abstract: Whereas the etiology of non-alcoholic fatty liver disease (NAFLD) is complex, the role of nutrition as a causing and preventive factor is not fully explored. The aim of this study is to associate dietary patterns with magnetic resonance imaging (MRI) parameters in a European population (Greece, Italy, and Serbia) affected by NAFLD. For the first time, iron-corrected T1 (cT1), proton density fat fraction (PDFF), and the liver inflammation fibrosis score (LIF) were examined in relation to diet. A total of 97 obese patients with NAFLD from the MAST4HEALTH study were included in the analysis. A validated semi-quantitative food frequency questionnaire (FFQ) was used to assess the quality of diet and food combinations. Other variables investigated include anthropometric measurements, total type 2 diabetes risk, physical activity level (PAL), and smoking status. Principal component analysis (PCA) was performed to identify dietary patterns. Six dietary patterns were identified, namely “High-Sugar”, “Prudent”, “Western”, “High-Fat and Salt”, “Plant-Based”, and “Low-Fat Dairy and Poultry”. The “Western” pattern was positively associated with cT1 in the unadjusted model (beta: 0.020, p -value: 0.025) and even after adjusting for age, sex, body mass index (BMI), PAL, smoking, the center of the study, and the other five dietary patterns (beta: 0.024, p -value: 0.020). On the contrary, compared with low-intake patients, those with medium intake of the “Low-Fat Dairy and Poultry” pattern were associated with lower values of cT1, PDFF, and LIF. However, patients with a “Low-Fat Dairy and Poultry” dietary pattern were negatively associated with MRI parameters (cT1: beta: −0.052, p -value: 0.046, PDFF: beta: −0.448, p -value: 0.030, LIF: beta: −0.408, p -value: 0.025). Our findings indicate several associations between MRI parameters and dietary patterns in NAFLD patients, highlighting the importance of diet in NAFLD.

Keywords: NAFLD; NASH; MRI; dietary patterns; MAST4HEALTH (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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