Nutrigenomics analysis reveals that copper deficiency and dietary sucrose up-regulate inflammation, fibrosis and lipogenic pathways in a mature rat model of nonalcoholic fatty liver disease

Abstract

Nonalcoholic fatty liver disease (NAFLD) prevalence is increasing worldwide, with the affected US population estimated near 30%. Diet is a recognized risk factor in the NAFLD spectrum, which includes nonalcoholic steatohepatitis (NASH) and fibrosis. Low hepatic copper (Cu) was recently linked to clinical NAFLD/NASH severity. Simple sugar consumption including sucrose and fructose is implicated in NAFLD, while consumption of these macronutrients also decreases liver Cu levels. Though dietary sugar and low Cu are implicated in NAFLD, transcript-level responses that connect diet and pathology are not established. We have developed a mature rat model of NAFLD induced by dietary Cu deficiency, human-relevant high sucrose intake (30% w/w) or both factors in combination. Compared to the control diet with adequate Cu and 10% (w/w) sucrose, rats fed either high-sucrose or low-Cu diet had increased hepatic expression of genes involved in inflammation and fibrogenesis, including hepatic stellate cell activation, while the combination of diet factors also increased ATP citrate lyase and fatty acid synthase gene transcription (fold change > 2, P < 0.02). Low dietary Cu decreased hepatic and serum Cu (P ≤ 0.05), promoted lipid peroxidation and induced NAFLD-like histopathology, while the combined factors also induced fasting hepatic insulin resistance and liver damage. Neither low Cu nor 30% sucrose in the diet led to enhanced weight gain. Taken together, transcript profiles, histological and biochemical data indicate that low Cu and high sucrose promote hepatic gene expression and physiological responses associated with NAFLD and NASH, even in the absence of obesity or severe steatosis.

Keywords: Copper; Fibrosis; Inflammation; Liver; Nonalcoholic steatohepatitis; Steatosis.

Figure 1. Relationships of transcript profiles and quantitative RT-PCR analysis of selected transcripts

A. Venn diagram indicating overlap of transcripts and numbers in categories for CuD/30%, CuA/30% and CuD/10% compared to control CuA/10% diet. B. Mean fold change (2^−ΔΔCt) for CuD/30%, CuA/30% and CuD/10% compared to CuA/10% with SEM is shown (n=3 per treatment).

Figure 2. CuD or high sucrose initiates transcript expression associated with inflammation

Cytokines and chemokines qPCR array showing the number of transcripts with fold change >1.5 up or down compared to CuA/10% diet.

Figure 3. Dietary CuD influences hepatic pathology and steatosis

A) Representative ORO and H&E images of hepatic tissue with indicated diet (20X objective). CuD diets evidenced significant increases in lipid staining. B) White arrowheads indicate possible Mallory-Denk bodies (20X objective, digital zoom 2X). C) Digital image analysis of ORO stained lipid accumulation by % area, evaluated by ANOVA followed by Dunnett’s multiple comparison test. Data (columns) represent means +SEM (n=6). D) CARS imaging confirms lipid accumulation in 30%/CuD liver compared to 30%/CuA liver.

Figure 4. Dietary CuD alters circulating triglyceride levels, but not fatty acids or weight gain

A. Serum triglyceride concentration by dietary Cu content, 10% and 30% sucrose are grouped. B. Serum palmitic acid concentration. C. Serum oleic acid concentration. D. Weight change after 12 weeks ad lib feeding purified diets.

Figure 5. CuD and sucrose influence Cu and Fe status

Mean + SEM (n=5–6) for hepatic Cu (A) and Fe (B) and serum Cu (C) and Fe (D). Significant differences between treatments are indicated by asterisks (P ≤0.05).

Figure 6. Individual and synergistic effects of CuD and sucrose on insulin resistance and oxidative stress

A) Serum glucose; B) serum insulin; C) modified HOMA-IR evaluating insulin resistance: dotted and dashed lines indicate validated HOMA-IR values for normal and insulin-resistant Wistar rats [42]. D–E) Levels of D) hepatic and E) serum malondialdehyde (MDA) as assessed by TBARS assay. F) Serum ALT level. Mean + S.E.M. (n=5–6) is indicated in A–F. Asterisks indicated significance of data vs. control: *P<0.05, **P< 0.01.