High-Fat Diet Induces Pre-Diabetes and Distinct Sex-Specific Metabolic Alterations in Negr1-Deficient Mice

Depression-Associated Negr1 Gene-Deficiency Induces Alterations in the Monoaminergic Neurotransmission Enhancing Time-Dependent Sensitization to Amphetamine in Male Mice

In GWAS studies, the neural adhesion molecule encoding the neuronal growth regulator 1 (NEGR1) gene has been consistently linked with both depression and obesity. Although the linkage between NEGR1 and depression is the strongest, evidence also suggests the involvement of NEGR1 in a wide spectrum of psychiatric conditions. Here we show the expression of NEGR1 both in tyrosine- and tryptophan hydroxylase-positive cells. Negr1^-/- mice show a time-dependent increase in behavioral sensitization to amphetamine associated with increased dopamine release in both the dorsal and ventral striatum. Upregulation of transcripts encoding dopamine and serotonin transporters and higher levels of several monoamines and their metabolites was evident in distinct brain areas of Negr1^-/- mice. Chronic (23 days) escitalopram-induced reduction of serotonin and dopamine turnover is enhanced in Negr1^-/- mice, and escitalopram rescued reduced weight of hippocampi in Negr1^-/- mice. The current study is the first to show alterations in the brain monoaminergic systems in Negr1-deficient mice, suggesting that monoaminergic neural circuits contribute to both depressive and obesity-related phenotypes linked to the human NEGR1 gene.

Impact of a High-Fat Diet on the Metabolomics Profile of 129S6 and C57BL6 Mouse Strains

Different inbred mouse strains vary substantially in their behavior and metabolic phenotype under physiological and pathological conditions. The purpose of this study was to extend the knowledge of distinct coping strategies under challenging events in two differently adapting mouse strains: C57BL/6NTac (Bl6) and 129S6/SvEvTac (129Sv). Thus, we aimed to investigate possible similarities and differences in the body weight change, behavior, and several metabolic variables in Bl6 and 129Sv strains in response to high-fat diet (HFD) using the AbsoluteIDQ p180 kit. We found that 9 weeks of HFD induced a significant body weight gain in 129Sv, but not in Bl6 mice. Besides that, 129Sv mice displayed anxiety-like behavior in the open-field test. Metabolite profiling revealed that 129Sv mice had higher levels of circulating branched-chain amino acids, which were even more amplified by HFD. HFD also induced a decrease in glycine, spermidine, and t4-OH-proline levels in 129Sv mice. Although acylcarnitines (ACs) dominated in baseline conditions in 129Sv strain, this strain had a significantly stronger AC-reducing effect of HFD. Moreover, 129Sv mice had higher levels of lipids in baseline conditions, but HFD caused more pronounced alterations in lipid profile in Bl6 mice. Taken together, our results show that the Bl6 line is better adapted to abundant fat intake.

Special Issue: Emerging Paradigms in Insulin Resistance

This Biomedicines Special Issue was designed to attract articles that focused on different facets of biology relating to insulin resistance, defined as reduced cellular and organismal response to the insulin hormone, and its underlying mechanisms [...]

Anti-Obesity and Anti-Adipogenic Effects of Administration of Arginyl-Fructose-Enriched Jeju Barley (Hordeum vulgare L.) Extract in C57BL/6 Mice and in 3T3-L1 Preadipocytes Models

In our previous study, we reported that arginyl-fructose (AF), one of the Amadori rearrangement compounds (ARCs) produced by the heat processing of Korean ginseng can reduce carbohydrate absorption by inhibiting intestinal carbohydrate hydrolyzing enzymes in both in vitro and in vivo animal models. This reduced absorption of carbohydrate might be helpful to control body weight gain due to excessive carbohydrate consumption and support induced calorie restriction. However, the weight management effect, except for the effect due to anti-hyperglycemic action, along with the potential mechanism of action have not yet been determined. Therefore, the efforts of this study are to investigate and understand the possible weight management effect and mechanism action of AF-enriched barley extracts (BEE). More specifically, the effect of BEE on lipid accumulation and adipogenic gene expression, body weight gain, body weight, plasma lipids, body fat mass, and lipid deposition were evaluated using C57BL/6 mice and 3T3-L1 preadipocytes models. The formation of lipid droplets in the 3T3-L1 treated with BEE (500 and 750 µg/mL) was significantly blocked (p < 0.05 and p < 0.01, respectively). Male C57BL/6 mice were fed a high-fat diet (30% fat) for 8 weeks with BEE (0.3 g/kg-body weight). Compared to the high fat diet control (HFD) group, the cells treated with BEE significantly decreased in intracellular lipid accumulation with concomitant decreases in the expression of key transcription factors, peroxisome proliferator-activated receptor gamma (PPARγ), CCAAT/enhancer-binding protein alpha (CEBP/α), the mRNA expression of downstream lipogenic target genes such as fatty acid binding protein 4 (FABP4), fatty acid synthase (FAS), and sterol regulatory element-binding protein 1c (SREBP-1c). Supplementation of BEE effectively lowered the body weight gain, visceral fat accumulation, and plasma lipid concentrations. Compared to the HFD group, BEE significantly suppressed body weight gain (16.06 ± 2.44 g vs. 9.40 ± 1.39 g, p < 0.01) and increased serum adiponectin levels, significantly, 1.6-folder higher than the control group. These results indicate that AF-enriched barley extracts may prevent diet-induced weight gain and the anti-obesity effect is mediated in part by inhibiting adipogenesis and increasing adiponectin level.

Risk prediction of diabetes and pre-diabetes based on physical examination data

Diabetes is a metabolic disorder caused by insufficient insulin secretion and insulin secretion disorders. From health to diabetes, there are generally three stages: health, pre-diabetes and type 2 diabetes. Early diagnosis of diabetes is the most effective way to prevent and control diabetes and its complications. In this work, we collected the physical examination data from Beijing Physical Examination Center from January 2006 to December 2017, and divided the population into three groups according to the WHO (1999) Diabetes Diagnostic Standards: normal fasting plasma glucose (NFG) (FPG < 6.1 mmol/L), mildly impaired fasting plasma glucose (IFG) (6.1 mmol/L ≤ FPG < 7.0 mmol/L) and type 2 diabetes (T2DM) (FPG > 7.0 mmol/L). Finally, we obtained1,221,598 NFG samples, 285,965 IFG samples and 387,076 T2DM samples, with a total of 15 physical examination indexes. Furthermore, taking eXtreme Gradient Boosting (XGBoost), random forest (RF), Logistic Regression (LR), and Fully connected neural network (FCN) as classifiers, four models were constructed to distinguish NFG, IFG and T2DM. The comparison results show that XGBoost has the best performance, with AUC (macro) of 0.7874 and AUC (micro) of 0.8633. In addition, based on the XGBoost classifier, three binary classification models were also established to discriminate NFG from IFG, NFG from T2DM, IFG from T2DM. On the independent dataset, the AUCs were 0.7808, 0.8687, 0.7067, respectively. Finally, we analyzed the importance of the features and identified the risk factors associated with diabetes.