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

Author

Listed:
  • 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
    Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, 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
    CIBER en Epidemiología y Salud Pú blica, 28029 Madrid, 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
    Centre for Genomic Health, Life Sciences, Queen Mary University of London, London E1 2AD, 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
    Clinic for Endocrinology, Diabetes and Metabolic Diseases, Clinical Centre of Vojvodina, 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
    ASST Grande Ospedale Metropolitano Niguarda, 20162 Milan, Italy)

  • George V. Dedoussis

    (Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece)

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.

Suggested Citation

  • Athina I. Amanatidou & Andriana C. Kaliora & Charalampia Amerikanou & Stefan Stojanoski & Natasa Milosevic & Chara Vezou & Mirjana Beribaka & Rajarshi Banerjee & Ioanna-Panagiota Kalafati & Ilias Smyr, 2022. "Association of Dietary Patterns with MRI Markers of Hepatic Inflammation and Fibrosis in the MAST4HEALTH Study," IJERPH, MDPI, vol. 19(2), pages 1-13, January.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:2:p:971-:d:725765
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    Keywords

    NAFLD; NASH; MRI; dietary patterns; MAST4HEALTH;
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