Three Different Genetic Risk Scores Based on Fatty Liver Index, Magnetic Resonance Imaging and Lipidomic for a Nutrigenetic Personalized Management of NAFLD: The Fatty Liver in Obesity Study.
Nuria Pérez Diaz Del CampoJosé-Ignacio Riezu-BojBertha Araceli Marin-AlejandreJ Ignacio MonrealMariana ElorzJosé Ignacio HerreroAlberto Benito-BoillosFermin Ignacio MilagroJosep Antonio TurJosé Alfredo MartínezMaría de Los Ángeles ZuletJosé Alfredo Martínez HernándezPublished in: Diagnostics (Basel, Switzerland) (2021)
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) (GRSFLI), lipidomic-OWLiver®-test (GRSOWL) and magnetic resonance imaging (MRI) (GRSMRI), 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 GRSFLI, GRSOWL and GRSMRI were major contributors of the improvement in hepatic status. Thus, fitted linear regression models showed a variance of 53% (adj. R2 = 0.53) in hepatic functionality (FLI), 16% (adj. R2 = 0.16) in lipidomic metabolism (OWLiver®-test) and 34% (adj. R2 = 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.
Keyphrases
- weight loss
- genome wide
- magnetic resonance imaging
- insulin resistance
- bariatric surgery
- body composition
- metabolic syndrome
- contrast enhanced
- liver injury
- roux en y gastric bypass
- type diabetes
- adipose tissue
- copy number
- drug induced
- gastric bypass
- dna methylation
- weight gain
- diffusion weighted imaging
- high fat diet induced
- minimally invasive
- computed tomography
- mental health
- obese patients
- magnetic resonance
- resistance training
- polycystic ovary syndrome
- public health
- machine learning
- physical activity
- body mass index
- skeletal muscle
- combination therapy
- smoking cessation
- robot assisted