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Obesity is an expanding global public health problem and a leading cause of metabolic disorders. The hepatokine Fetuin B participates in regulating insulin resistance, glucose metabolism and liver steatosis. However, the mechanism underlying Fetuin B activation remains unclear. Our previous population-based study demonstrated a significant association between serum Fetuin B and body fat mass in an obese population, which indicates its potential in mediating obesity-related metabolic disorders. In the present study, we further revealed a significant correlation between Fetuin B and leptin, the classic adipokine released by expanding adipose tissue, in this obese population. Consistently, elevated Fetuin B and leptin levels were confirmed in diet-induced obese mice. Furthermore, an in vitro study demonstrated that the leptin signalling pathway directly activated the transcription and expression of Fetuin B in primary hepatocytes and AML12 cells in a STAT3-dependent manner. STAT3 binds to the response elements on FetuB promoter to directly activate FetuB transcription. Finally, the mediating effect of Fetuin B in insulin resistance induced by leptin was confirmed according to mediation analysis in this obese population. Therefore, our study identifies leptin-STAT3 as an upstream signalling pathway that activates Fetuin B and provides new insights into the pathogenic mechanisms of obesity-related metabolic disorders., (© 2022. The Author(s).)

Background: There are emerging studies suggesting that non-alcoholic fatty liver disease (NAFLD) is a heterogeneous disease with multiple etiologies and molecular phenotypes. Fibrosis is the key process in NAFLD progression. In this study, we aimed to explore molecular phenotypes of NAFLD with a particular focus on the fibrosis phenotype and also aimed to explore the changes of macrophage subsets in the fibrosis subset of NAFLD. Methods: To assess the transcriptomic alterations of key factors in NAFLD and fibrosis progression, we included 14 different transcriptomic datasets of liver tissues. In addition, two single-cell RNA sequencing (scRNA-seq) datasets were included to construct transcriptomic signatures that could represent specific cells. To explore the molecular subsets of fibrosis in NAFLD based on the transcriptomic features, we used a high-quality RNA-sequencing (RNA-seq) dataset of liver tissues from patients with NAFLD. Non-negative matrix factorization (NMF) was used to analyze the molecular subsets of NAFLD based on the gene set variation analysis (GSVA) enrichment scores of key molecule features in liver tissues. Results: The key transcriptomic signatures on NAFLD including non-alcoholic steatohepatitis (NASH) signature, fibrosis signature, non-alcoholic fatty liver (NAFL) signature, liver aging signature and TGF-β signature were constructed by liver transcriptome datasets. We analyzed two liver scRNA-seq datasets and constructed cell type-specific transcriptomic signatures based on the genes that were highly expressed in each cell subset. We analyzed the molecular subsets of NAFLD by NMF and categorized four main subsets of NAFLD. Cluster 4 subset is mainly characterized by liver fibrosis. Patients with Cluster 4 subset have more advanced liver fibrosis than patients with other subsets, or may have a high risk of liver fibrosis progression. Furthermore, we identified two key monocyte-macrophage subsets which were both significantly correlated with the progression of liver fibrosis in NAFLD patients. Conclusion: Our study revealed the molecular subtypes of NAFLD by integrating key information from transcriptomic expression profiling and liver microenvironment, and identified a novel and distinct fibrosis subset of NAFLD. The fibrosis subset is significantly correlated with the profibrotic macrophages and M2 macrophage subset. These two liver macrophage subsets may be important players in the progression of liver fibrosis of NAFLD patients. [ABSTRACT FROM AUTHOR]

Background: There is no evidence available on the association of Fetuin-B with chronic kidney disease (CKD), and mechanisms linking nonalcoholic fatty liver disease (NAFLD) to CKD are not fully understood. We aimed to explore the independent associations and potential mechanisms of Fetuin-B and NAFLD with CKD. Methods: A cross-sectional study of 1,072 Chinese adults who underwent serum Fetuin-B test and hepatic ultrasonography scanning was conducted in Xiamen, China. CKD was defined as estimated glomerular filtration rate < 60 mL/min/1.73 m2 and/or the presence of albuminuria. Results: Subjects with CKD showed significantly higher prevalence of NAFLD (69.5 vs. 57.2%, p < 0.001) and serum Fetuin-B levels (4.32 ± 1.45 vs. 4.05 ± 1.36 µg/mL, p = 0.007) than their controls. Increased serum Fetuin-B was also significantly associated with increased levels of fasting insulin and homeostasis model assessment – insulin resistance (both p values < 0.05). NAFLD and higher serum Fetuin-B were significantly associated with increased risk of CKD, and the unadjusted ORs (95% CIs) were 1.701 (1.256–2.303, p = 0.001) and 1.213 (1.053–1.399, p = 0.008, per SD increase of Fetuin-B), respectively. With adjustment for potential confounding factors, including metabolic/insulin resistance syndrome, NAFLD but not serum Fetuin-B was still significantly associated with increased risk of CKD, and the adjusted ORs (95% CIs) were 1.820 (1.327–2.496, p < 0.001) and 1.116 (0.959–1.298, p = 0.153, per SD increase of Fetuin-B), respectively. Conclusions: Fetuin-B might link NAFLD to CKD via inducing insulin resistance, and NAFLD contributes independently to the pathogenesis of CKD via multiple mechanisms besides of metabolic/insulin resistance syndrome. [ABSTRACT FROM AUTHOR]

Objective Laboratory models suggested that Fetuin-B impaired insulin action in myotubes and hepatocytes and caused glucose intolerance in mice. We aimed to explore the independent associations and pathways among serum Fetuin-B, nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D). Methods A cross-sectional study of 1318 obese adults who underwent serum Fetuin-B test and hepatic ultrasonography scanning was conducted in Xiamen, China. Multivariable logistic regression was used to calculate adjusted odds ratio (OR) and 95% confidence intervals (CI) of serum Fetuin-B level and NAFLD for T2D in different models with adjustment for potential confounders. Structural equation modeling (SEM) was used to examine the paths among NAFLD, serum Fetuin-B, metabolic/insulin resistance syndrome and T2D. Results Subjects with T2D or NAFLD showed significantly increased serum Fetuin-B levels compared to their controls (4.25 ± 1.35 vs. 4.08 ± 1.38 µg/ml for diabetes; and 4.26 ± 1.41 vs. 4.07 ± 1.33 µg/ml for NAFLD; both p-values < 0.05). NAFLD and higher serum Fetuin-B were significantly associated with higher risk of T2D with adjustment for sociodemographic and lifestyle habits; and the adjusted ORs (95%CIs) were 2.90 (2.17–3.87, p < 0.001) and 1.16 (1.01–1.32, p = 0.032), respectively. With further adjustment for metabolic/insulin resistance syndrome (BMI, systolic and diastolic BP, triglyceride, total cholesterol, HDL- and LDL-cholesterol, HOMA-IR and serum uric acid), NAFLD but not serum Fetuin-B was significantly associated with increased risk of T2D (ORs (95%CIs): 1.58 (1.12–2.21, p = 0.009) and 1.07 (0.92–1.23, p = 0.384), respectively). A one pathway model by using SEM fitted well (χ 2  = 497.92, p < 0.001; CFI = 0.965; TLI = 0.926; and RMSEA = 0.097) and showed that NAFLD increased serum Fetuin-B and elevated Fetuin-B increased fasting insulin level, which in turn induced insulin resistance and T2D. Besides, NAFLD increased the risk of T2D directly in addition to its indirect effects of inducing metabolic/insulin resistance syndrome which in turn increased the risk of T2D. Conclusions Fetuin-B links NAFLD to T2D via inducing insulin resistance, and NAFLD contributes to the pathogenesis of T2D via multiple mechanisms. [ABSTRACT FROM AUTHOR]