Abdominal Fat and Metabolic Health Markers but Not PNPLA3 Genotype Predicts Liver Fat Accumulation in Response to Excess Intake of Energy and Saturated Fat in Healthy Individuals

• Main Authors: Fredrik Rosqvist, Marju Orho-Melander, Joel Kullberg, David Iggman, Hans-Erik Johansson, Jonathan Cedernaes, Håkan Ahlström, Ulf Risérus
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2020-12-01
• Series: Frontiers in Nutrition
• Subjects: liver fat; saturated fat; overfeeding; NAFLD; fatty acids
• Online Access: https://www.frontiersin.org/articles/10.3389/fnut.2020.606004/full

Background: Saturated fat (SFA) has consistently been shown to increase liver fat, but the response appears variable at the individual level. Phenotypic and genotypic characteristics have been demonstrated to modify the hypercholesterolemic effect of SFA but it is unclear which characteristics that predict liver fat accumulation in response to a hypercaloric diet high in SFA.Objective: To identify predictors of liver fat accumulation in response to an increased intake of SFA.Design: We pooled our two previously conducted double-blind randomized trials (LIPOGAIN and LIPOGAIN-2, clinicaltrials.gov NCT01427140 and NCT02211612) and used data from the n = 49 metabolically healthy men (n = 32) and women (n = 17) randomized to a hypercaloric diet through addition of SFA-rich muffins for 7–8 weeks. Associations between clinical and metabolic variables at baseline and changes in liver fat during the intervention were analyzed using Spearman rank correlation. Linear regression was used to generate a prediction model.Results: Liver fat increased by 33% (IQR 5.4–82.7%; P < 0.0001) in response to excess energy intake and this was not associated (r = 0.17, P = 0.23) with the increase in body weight (1.9 kg; IQR 1.1–2.9 kg). Liver fat accumulation was similar (P = 0.28) in carriers (33%, IQR 14–79%) and non-carriers (33%, IQR −11 to +87%) of the PNPLA3-I148M variant. Baseline visceral and liver fat content, as well as levels of the liver enzyme γ-glutamyl transferase (GT), were the strongest positive predictors of liver fat accumulation—in contrast, adiponectin and the fatty acid 17:0 in adipose tissue were the only negative predictors in univariate analyses. A regression model based on eight clinical and metabolic variables could explain 81% of the variation in liver fat accumulation.Conclusion: Our results suggest there exists a highly inter-individual variation in the accumulation of liver fat in metabolically healthy men and women, in response to an increased energy intake from SFA and carbohydrates that occurs over circa 2 months. This marked variability in liver fat accumulation could largely be predicted by a set of clinical (e.g., GT and BMI) and metabolic (e.g., fatty acids, HOMA-IR, and adiponectin) variables assessed at baseline.