Perez-Diaz-Del-Campo Nuria, Riezu-Boj Jose I, Marin-Alejandre Bertha Araceli, Monreal J Ignacio, Elorz Mariana, Herrero José Ignacio, Benito-Boillos Alberto, Milagro Fermín I, Tur Josep A, Abete Itziar, Zulet M Angeles, Martinez J Alfredo
Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy and Nutrition, University of Navarra, 31008 Pamplona, Spain.
Centre for Nutrition Research, Faculty of Pharmacy and Nutrition, University of Navarra, 31008 Pamplona, Spain.
Diagnostics (Basel). 2021 Jun 13;11(6):1083. doi: 10.3390/diagnostics11061083.
Non-alcoholic fatty liver disease (NAFLD) affects 25% of the global population. The pathogenesis of NAFLD is complex; available data reveal that genetics and ascribed interactions with environmental factors may play an important role in the development of this morbid condition. The purpose of this investigation was to assess genetic and non-genetic determinants putatively involved in the onset and progression of NAFLD after a 6-month weight loss nutritional treatment. A group of 86 overweight/obese subjects with NAFLD from the Fatty Liver in Obesity (FLiO) study were enrolled and metabolically evaluated at baseline and after 6 months. A pre-designed panel of 95 genetic variants related to obesity and weight loss was applied and analyzed. Three genetic risk scores (GRS) concerning the improvement on hepatic health evaluated by minimally invasive methods such as the fatty liver index (FLI) (GRS), lipidomic-OWLiver-test (GRS) and magnetic resonance imaging (MRI) (GRS), were derived by adding the risk alleles genotypes. Body composition, liver injury-related markers and dietary intake were also monitored. Overall, 23 SNPs were independently associated with the change in FLI, 16 SNPs with OWLiver-test and 8 SNPs with MRI, which were specific for every diagnosis tool. After adjusting for gender, age and other related predictors (insulin resistance, inflammatory biomarkers and dietary intake at baseline) the calculated GRS, GRS and GRS were major contributors of the improvement in hepatic status Thus, fitted linear regression models showed a variance of 53% (adj. R = 0.53) in hepatic functionality (FLI), 16% (adj. R = 0.16) in lipidomic metabolism (OWLiver-test) and 34% (adj. R = 0.34) in liver fat content (MRI). These results demonstrate that three different genetic scores can be useful for the personalized management of NAFLD, whose treatment must rely on specific dietary recommendations guided by the measurement of specific genetic biomarkers.
非酒精性脂肪性肝病（NAFLD）影响着全球25%的人口。NAFLD的发病机制复杂；现有数据表明，遗传因素以及与环境因素的既定相互作用可能在这种疾病状态的发展中起重要作用。本研究的目的是评估在为期6个月的减重营养治疗后，可能与NAFLD的发生和进展相关的遗传和非遗传决定因素。对来自肥胖症脂肪肝（FLiO）研究的86名患有NAFLD的超重/肥胖受试者进行了招募，并在基线和6个月后进行了代谢评估。应用并分析了一组预先设计的与肥胖和减重相关的95个基因变异。通过将风险等位基因基因型相加，得出了三个关于肝脏健康改善情况的遗传风险评分（GRS），这些改善情况通过脂肪肝指数（FLI）（GRS）、脂质组学-OWLiver检测（GRS）和磁共振成像（MRI）（GRS）等微创方法进行评估。还监测了身体成分、肝脏损伤相关标志物和饮食摄入情况。总体而言，23个单核苷酸多态性（SNP）与FLI的变化独立相关，16个SNP与OWLiver检测相关，8个SNP与MRI相关，这些对于每种诊断工具都是特异性的。在对性别、年龄和其他相关预测因素（胰岛素抵抗、炎症生物标志物和基线饮食摄入）进行调整后，计算得出的GRS、GRS和GRS是肝脏状态改善的主要贡献因素。因此，拟合线性回归模型显示，肝脏功能（FLI）的方差为53%（调整后R = 0.53），脂质组学代谢（OWLiver检测）的方差为16%（调整后R = 0.16），肝脏脂肪含量（MRI）的方差为34%（调整后R = 0.34）。这些结果表明，三种不同的遗传评分可用于NAFLD的个性化管理，其治疗必须依赖于由特定遗传生物标志物测量所指导的特定饮食建议。
