Murine neuronatin deficiency is associated with a hypervariable food intake and bimodal obesity

Circulating Neuronatin Levels Are Positively Associated with BMI and Body Fat Mass but Not with Psychological Parameters

Human genetic studies have associated Neuronatin gene variants with anorexia nervosa (AN) and obesity. Studies on the expression of the Neuronatin gene product, a proteolipid, are lacking. We investigated the relationship between circulating Neuronatin, body mass index (BMI), body composition (BC), physical activity (PA), and psychometric outcomes in patients with AN, normal weight, and obesity. Plasma Neuronatin was measured by ELISA in (1) 79 subjects of five BMI categories (AN/BMI < 17.5 kg/m2; normal weight/BMI 18.5-25 kg/m2; obesity/BMI 30-40 kg/m2; obesity/BMI 40-50 kg/m2; obesity/BMI > 50 kg/m2) with assessment of BC (bioimpedance analysis; BIA); (2) 49 women with AN (BMI 14.5 ± 1.8 kg/m2) with measurements of BC (BIA) and PA (accelerometry); (3) 79 women with obesity (BMI 48.8 ± 7.8 kg/m2) with measurements of anxiety (GAD-7), stress (PSQ-20), depression (PHQ-9) and eating behavior (EDI-2). Overall, a positive correlation was found between Neuronatin and BMI (p = 0.006) as well as total fat mass (FM; p = 0.036). In AN, Neuronatin did not correlate with BMI, FM, or PA (p > 0.05); no correlations were found between Neuronatin and psychometric outcomes in obesity (p > 0.05). The findings suggest an FM-dependent peripheral Neuronatin expression. The decreased Neuronatin expression in AN provides evidence that Neuronatin is implicated in the pathogenesis of eating disorders.

In Silico Identification of Key Genes and Immune Infiltration Characteristics in Epicardial Adipose Tissue from Patients with Coronary Artery Disease

Background

The present study is aimed at identifying the differentially expressed genes (DEGs) and relevant biological processes and pathways associated with epicardial adipose tissue (EAT) from patients with coronary artery disease (CAD). We also explored potential biomarkers using two machine-learning algorithms and calculated the immune cell infiltration in EAT.

Materials and Methods

Three datasets (GSE120774, GSE64554, and GSE24425) were obtained from the Gene Expression Omnibus (GEO) database. The GSE120774 dataset was used to evaluate DEGs between EAT of CAD patients and the control group. Functional enrichment analyses were conducted to study associated biological functions and mechanisms using the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA). After this, the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) were performed to identify the feature genes related to CAD. The expression level of the feature genes was validated in GSE64554 and GSE24425. Finally, we calculated the immune cell infiltration and evaluated the correlation between the feature genes and immune cells using CIBERSORT.

Results

We identified a total of 130 upregulated and 107 downregulated genes in GSE120774. Functional enrichment analysis revealed that DEGs are associated with several pathways, including the calcium signaling pathway, complement and coagulation cascades, ferroptosis, fluid shear stress and atherosclerosis, lipid and atherosclerosis, and regulation of lipolysis in adipocytes. TCF21, CDH19, XG, and NNAT were identified as feature genes and validated in the GSE64554 and GSE24425 datasets. Immune cell infiltration analysis showed plasma cells are significantly more numerous in EAT than in the control group (p = 0.001), whereas macrophage M0 (p = 0.024) and resting mast cells (p = 0.036) were significantly less numerous. TCF21, CDH19, XG, and NNAT were correlated with immune cells, including plasma cells, M0 macrophages, and resting mast cells.

Conclusion

TCF21, CDH19, XG, and NNAT might serve as feature genes for CAD, providing new insights for future research on the pathogenesis of cardiovascular diseases.

Neuroendocrine microRNAs linked to energy homeostasis: future therapeutic potential

The brain orchestrates whole-body metabolism through an intricate system involving interneuronal crosstalk and communication. Specifically, a key player in this complex circuitry is the hypothalamus that controls feeding behaviour, energy expenditure, body weight and metabolism, whereby hypothalamic neurons sense and respond to circulating hormones, nutrients, and chemicals. Dysregulation of these neurons contributes to the development of metabolic disorders, such as obesity and type 2 diabetes. The involvement of hypothalamic microRNAs, post-transcriptional regulators of gene expression, in the central regulation of energy homeostasis has become increasingly apparent, although not completely delineated. This review summarizes current evidence demonstrating the regulation of feeding-related neuropeptides by brain-derived microRNAs as well as the regulation of specific miRNAs by nutrients and other peripheral signals. Moreover, the involvement of microRNAs in the central nervous system control of insulin, leptin, and estrogen signal transduction is examined. Finally, the therapeutic and diagnostic potential of microRNAs for metabolic disorders will be discussed and the regulation of brain-derived microRNAs by nutrients and other peripheral signals is considered. Demonstrating a critical role of microRNAs in hypothalamic regulation of energy homeostasis is an innovative route to uncover novel biomarkers and therapeutic candidates for metabolic disorders.

Independent phenotypic plasticity axes define distinct obesity sub-types

Studies in genetically 'identical' individuals indicate that as much as 50% of complex trait variation cannot be traced to genetics or to the environment. The mechanisms that generate this 'unexplained' phenotypic variation (UPV) remain largely unknown. Here, we identify neuronatin (NNAT) as a conserved factor that buffers against UPV. We find that Nnat deficiency in isogenic mice triggers the emergence of a bi-stable polyphenism, where littermates emerge into adulthood either 'normal' or 'overgrown'. Mechanistically, this is mediated by an insulin-dependent overgrowth that arises from histone deacetylase (HDAC)-dependent β-cell hyperproliferation. A multi-dimensional analysis of monozygotic twin discordance reveals the existence of two patterns of human UPV, one of which (Type B) phenocopies the NNAT-buffered polyphenism identified in mice. Specifically, Type-B monozygotic co-twins exhibit coordinated increases in fat and lean mass across the body; decreased NNAT expression; increased HDAC-responsive gene signatures; and clinical outcomes linked to insulinemia. Critically, the Type-B UPV signature stratifies both childhood and adult cohorts into four metabolic states, including two phenotypically and molecularly distinct types of obesity.

Mechanisms Driving Palmitate-Mediated Neuronal Dysregulation in the Hypothalamus

The hypothalamus maintains whole-body homeostasis by integrating information from circulating hormones, nutrients and signaling molecules. Distinct neuronal subpopulations that express and secrete unique neuropeptides execute the individual functions of the hypothalamus, including, but not limited to, the regulation of energy homeostasis, reproduction and circadian rhythms. Alterations at the hypothalamic level can lead to a myriad of diseases, such as type 2 diabetes mellitus, obesity, and infertility. The excessive consumption of saturated fatty acids can induce neuroinflammation, endoplasmic reticulum stress, and resistance to peripheral signals, ultimately leading to hyperphagia, obesity, impaired reproductive function and disturbed circadian rhythms. This review focuses on the how the changes in the underlying molecular mechanisms caused by palmitate exposure, the most commonly consumed saturated fatty acid, and the potential involvement of microRNAs, a class of non-coding RNA molecules that regulate gene expression post-transcriptionally, can result in detrimental alterations in protein expression and content. Studying the involvement of microRNAs in hypothalamic function holds immense potential, as these molecular markers are quickly proving to be valuable tools in the diagnosis and treatment of metabolic disease.