Katherine Martin1,2,3, Anas Hatab4,5, Varinder S Athwal4,5,6, Elliot Jokl4,5, Karen Piper Hanley7,8. 1. Wellcome Centre for Cell-Matrix Research, Faculty of Biology, Medicine & Health, Manchester Academic Health Science Centre, University of Manchester, Oxford Road M13 9PT, Manchester, UK. katherine.martin@manchester.ac.uk. 2. Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine & Health, Manchester Academic Health Science Centre, University of Manchester, Oxford Road, Manchester, UK. katherine.martin@manchester.ac.uk. 3. Manchester University NHS Foundation Trust, Oxford Road M13 9PT, Manchester, UK. katherine.martin@manchester.ac.uk. 4. Wellcome Centre for Cell-Matrix Research, Faculty of Biology, Medicine & Health, Manchester Academic Health Science Centre, University of Manchester, Oxford Road M13 9PT, Manchester, UK. 5. Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine & Health, Manchester Academic Health Science Centre, University of Manchester, Oxford Road, Manchester, UK. 6. Manchester University NHS Foundation Trust, Oxford Road M13 9PT, Manchester, UK. 7. Wellcome Centre for Cell-Matrix Research, Faculty of Biology, Medicine & Health, Manchester Academic Health Science Centre, University of Manchester, Oxford Road M13 9PT, Manchester, UK. karen.piperhanley@manchester.ac.uk. 8. Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine & Health, Manchester Academic Health Science Centre, University of Manchester, Oxford Road, Manchester, UK. karen.piperhanley@manchester.ac.uk.
Abstract
PURPOSE OF REVIEW: Non-alcoholic fatty liver disease (NAFLD) is a major and increasing health burden, with the potential to overwhelm hepatology services. However, only a minority of patients develop advanced liver disease. The challenge is early identification of patients at risk of progression. This review aims to summarize current knowledge on the genetic predisposition to NAFLD, and its implications for prognostication and risk stratification. RECENT FINDINGS: PNPLA3-I148M is the most robustly associated genetic variant with NAFLD. Recently, variants in TM6SF2, MBOAT7, GCKR and HSD17B13 have also been implicated. NAFLD is a complex disease, and any one genetic variant alone is insufficient for risk stratification, but combining multiple genetic variants with other parameters is a promising strategy. It is anticipated that, in the near future, analysis of data from large-scale prospective cohorts will reveal NAFLD subtypes and enable the development of prognostic models. This will facilitate risk stratification of patients, enabling optimisation of resources to effectively manage the NAFLD epidemic.
PURPOSE OF REVIEW: Non-alcoholic fatty liver disease (NAFLD) is a major and increasing health burden, with the potential to overwhelm hepatology services. However, only a minority ofpatients develop advanced liver disease. The challenge is early identification ofpatients at risk of progression. This review aims to summarize current knowledge on the genetic predisposition to NAFLD, and its implications for prognostication and risk stratification. RECENT FINDINGS:PNPLA3-I148M is the most robustly associated genetic variant with NAFLD. Recently, variants in TM6SF2, MBOAT7, GCKR and HSD17B13 have also been implicated. NAFLD is a complex disease, and any one genetic variant alone is insufficient for risk stratification, but combining multiple genetic variants with other parameters is a promising strategy. It is anticipated that, in the near future, analysis of data from large-scale prospective cohorts will reveal NAFLD subtypes and enable the development of prognostic models. This will facilitate risk stratification ofpatients, enabling optimisation of resources to effectively manage the NAFLD epidemic.
Authors: Kerry L Donnelly; Coleman I Smith; Sarah J Schwarzenberg; Jose Jessurun; Mark D Boldt; Elizabeth J Parks Journal: J Clin Invest Date: 2005-05 Impact factor: 14.808
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Authors: Mauy Frujuello Mana; Maria Cândida R Parisi; Maria Lucia Correa-Giannella; Arnaldo Moura Neto; Ademar Yamanaka; Marlone Cunha-Silva; Ana Mercedes Cavaleiro; Cristina Rodrigues Dos Santos; Célia Regina Pavan; Tiago Sevá-Pereira; Sergio S J Dertkigil; Daniel F Mazo Journal: Molecules Date: 2022-05-17 Impact factor: 4.927