The relationship between visceral obesity and hepatic steatosis measured by controlled attenuation parameter

<div><p>Background</p><p>Nonalcoholic fatty liver disease (NAFLD) is closely related with obesity. However, obese subjects, generally represented by high BMI, do not always develop NAFLD. A number of possible causes of NAFLD have been studied, but the exact mechanism has not yet been elucidated.</p><p>Methods</p><p>A total of 304 consecutive subjects who underwent general health examinations including abdominal ultrasonography, transient elastography and abdominal fat computed tomography were prospectively enrolled. Significant steatosis was diagnosed by ultrasonography and controlled attenuation parameter (CAP) assessed by transient elastography.</p><p>Results</p><p>Visceral fat area (VFA) was significantly related to hepatic steatosis assessed by CAP, whereas body mass index (BMI) was related to CAP only in univariate analysis. In multiple logistic regression analysis, VFA (odds ratio [OR], 1.010; 95% confidence interval [CI], 1.001–1.019; <i>P</i> = 0.028) and triglycerides (TG) (OR, 1.006; 95% CI, 1.001–1.011; <i>P</i> = 0.022) were independent risk factors for significant hepatic steatosis. The risk of significant hepatic steatosis was higher in patients with higher VFA: the OR was 4.838 (<i>P</i><0.001; 95% CI, 2.912–8.039) for 1002 and 7.474 (<i>P</i><0.001; 95% CI, 2.462–22.693) for VFA >200 cm², compared to patients with a VFA ≤100 cm².</p><p>Conclusions</p><p>Our data demonstrated that VFA and TG is significantly related to hepatic steatosis assessed by CAP not BMI. This finding suggests that surveillance for subjects with NAFLD should incorporate an indicator of visceral obesity, and not simply rely on BMI.</p></div

Areas under the receiver operating characteristic curves of the predictive power of hepatic steatosis.

<p>Areas under the receiver operating characteristic curves of the predictive power of hepatic steatosis.</p

The relationship between visceral obesity and hepatic steatosis measured by controlled attenuation parameter - Fig 2

<p>(A) Controlled attenuation parameter (CAP) score distribution in patients with visceral fat area (VFA) <100 cm², 100≤VFA<200 cm², and VFA ≥200 cm². The median CAP score increased with increasing VFA. (B) Liver stiffness (LS) value distribution in patients with visceral fat area (VFA) <100 cm², 100≤VFA<200 cm², and VFA ≥200 cm². The median LS value increased with increasing VFA.</p

Discrimination of Nonalcoholic Steatohepatitis Using Transient Elastography in Patients with Nonalcoholic Fatty Liver Disease

<div><p>Background/aims</p><p>The accuracy of noninvasive markers to discriminate nonalcoholic steatohepatitis (NASH) is unsatisfactory. We investigated whether transient elastography (TE) could discriminate patients with NASH from those with nonalcoholic fatty liver disease (NAFLD).</p><p>Methods</p><p>The patients suspected of NAFLD who underwent liver biopsy and concomitant TE were recruited from five tertiary centers between November 2011 and December 2013.</p><p>Results</p><p>The study population (n = 183) exhibited a mean age of 40.6 years and male predominance (n = 111, 60.7%). Of the study participants, 89 (48.6%) had non-NASH and 94 (51.4%) had NASH. The controlled attenuation parameter (CAP) and liver stiffness (LS) were significantly correlated with the degrees of steatosis (r = 0.656, <i>P</i><0.001) and fibrosis (r = 0.714, <i>P</i><0.001), respectively. The optimal cut-off values for steatosis were 247 dB/m for S1, 280 dB/m for S2, and 300 dB/m for S3. Based on the independent predictors derived from multivariate analysis [<i>P</i> = 0.044, odds ratio (OR) 4.133, 95% confidence interval (CI) 1.037–16.470 for <u><i>C</i></u>AP>250 dB/m; <i>P</i> = 0.013, OR 3.399, 95% CI 1.295–8.291 for <u><i>L</i></u>S>7.0 kPa; and <i>P</i><0.001, OR 7.557, 95% CI 2.997–19.059 for <u><i>A</i></u>lanine aminotransferase>60 IU/L], we developed a novel CLA model for discriminating patients with NASH. The CLA model showed good discriminatory capability, with an area under the receiver operating characteristic curve (AUROC) of 0.812 (95% CI 0.724–0.880). To assess discriminatory power, the AUROCs, as determined by the bootstrap method, remained largely unchanged between iterations, with an average value of 0.833 (95% CI 0.740–0.893).</p><p>Conclusion</p><p>This novel TE-based CLA model showed acceptable accuracy in discriminating NASH from simple steatosis. However, further studies are required for external validation.</p></div

Independent risk factors for significant hepatic steatosis.

<p>Independent risk factors for significant hepatic steatosis.</p

Comparison of patients with and without significant hepatic steatosis.

<p>Comparison of patients with and without significant hepatic steatosis.</p

Diagnostic performance of LS for assessing liver fibrosis in patients with NAFLD

<p>Diagnostic performance of LS for assessing liver fibrosis in patients with NAFLD</p

The distribution of LS and CAP values according to histologic fibrosis and steatosis grade.

<p>The bar lines mean the range of each grade of steatosis and fibrosis. LS, liver stiffness; CAP, controlled attenuation parameter.</p

CLA score and corresponding NASH prevalence.

<p>CLA score and corresponding NASH prevalence.</p

Additional file 1 of Inhibition of Dickkopf-1 enhances the anti-tumor efficacy of sorafenib via inhibition of the PI3K/Akt and Wnt/β-catenin pathways in hepatocellular carcinoma

Additional file 1: Supplementary Figure 1. The effects of LEN, WAY or their combination treatment on cell viability or colony formation in HCC cells. Supplementary Figure 2. Combination effects of SOR + WAY treatment on tumor progression in xenograft mouse model. Supplementary Figure 3. SOR + WAY treatment regulates PI3K/Akt and Wnt/β-catenin pathways in HCC. Supplementary Figure 4. The combination effects of SOR + WAY treatment under condition of PI3K activation. Supplementary Figure 5. Correlation between DKK1 expression and immune cell infiltration. Supplementary Table 1. Primary and secondary anti-bodies used in this study. Supplementary Table 2. Primer sequences used in the qRT-PCR