The Serum Concentrations of Hedgehog-Interacting Protein, a Novel Biomarker, Were Decreased in Overweight or Obese Subjects

The identification of key genes and pathways in polycystic ovary syndrome by bioinformatics analysis of next-generation sequencing data

Background

Polycystic ovary syndrome (PCOS) is a reproductive endocrine disorder. The specific molecular mechanism of PCOS remains unclear. The aim of this study was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of PCOS.

Methods

The next-generation sequencing (NGS) dataset GSE199225 was downloaded from the gene expression omnibus (GEO) database and NGS dataset analyzed is obtained from in vitro culture of PCOS patients’ muscle cells and muscle cells of healthy lean control women. Differentially expressed gene (DEG) analysis was performed using DESeq2. The g:Profiler was utilized to analyze the gene ontology (GO) and REACTOME pathways of the differentially expressed genes. A protein–protein interaction (PPI) network was constructed and module analysis was performed using HiPPIE and cytoscape. The miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed. The hub genes were validated by using receiver operating characteristic (ROC) curve analysis.

Results

We have identified 957 DEG in total, including 478 upregulated genes and 479 downregulated gene. GO terms and REACTOME pathways illustrated that DEG were significantly enriched in regulation of molecular function, developmental process, interferon signaling and platelet activation, signaling, and aggregation. The top 5 upregulated hub genes including HSPA5, PLK1, RIN3, DBN1, and CCDC85B and top 5 downregulated hub genes including DISC1, AR, MTUS2, LYN, and TCF4 might be associated with PCOS. The hub gens of HSPA5 and KMT2A, together with corresponding predicted miRNAs (e.g., hsa-mir-34b-5p and hsa-mir-378a-5p), and HSPA5 and TCF4 together with corresponding predicted TF (e.g., RCOR3 and TEAD4) were found to be significantly correlated with PCOS.

Conclusions

These study uses of bioinformatics analysis of NGS data to obtain hub genes and key signaling pathways related to PCOS and its associated complications. Also provides novel ideas for finding biomarkers and treatment methods for PCOS and its associated complications.

Serum Concentrations of Cartilage Intermediate Layer Protein 2 Were Higher in Overweight and Obese Subjects

Background

Cartilage intermediate layer protein 2 (CILP2) is associated with a variety of plasma lipoproteins and lipid traits. However, the correlation between CILP2 and obesity remains unknown. The aim of this study was to investigate the relationship between circulating CILP2 levels and obesity based on body mass index (BMI).

Methods

A total of 252 subjects were divided into three groups: normal weight (n = 124), overweight (n = 94), and obese (n = 34). Metabolic parameters were measured in a fasting state. Serum CILP2 concentration was tested by enzyme-linked immunosorbent assay. Multivariate linear regression analysis was used to explore the relationship between CILP2 and obesity. We also conducted bioinformatics analysis to further explore the genes and signaling pathways related to CILP2.

Results

The concentrations of serum CILP2 in the overweight and obese groups were significantly higher than that in the normal weight group. In multiple linear regression analysis, BMI was positively correlated with CILP2 concentration after controlling gender and age. Being overweight and obese were independently correlated with CILP2 concentration after adjusting for gender, age, SBP, DBP, FBG, 2-hour OGTT blood glucose (2h-BG), fasting blood insulin (FIns), TG, TC, HDL-C, LDL-C, and FFA. Bioinformatics analysis showed that the genes related to CILP2 are primarily associated with lipid metabolism and insulin resistance.

Conclusion

We speculate that CILP2 may attribute to metabolic disorders in obesity.

Hepatic Hedgehog Signaling Participates in the Crosstalk between Liver and Adipose Tissue in Mice by Regulating FGF21

The Hedgehog signaling pathway regulates many processes during embryogenesis and the homeostasis of adult organs. Recent data suggest that central metabolic processes and signaling cascades in the liver are controlled by the Hedgehog pathway and that changes in hepatic Hedgehog activity also affect peripheral tissues, such as the reproductive organs in females. Here, we show that hepatocyte-specific deletion of the Hedgehog pathway is associated with the dramatic expansion of adipose tissue in mice, the overall phenotype of which does not correspond to the classical outcome of insulin resistance-associated diabetes type 2 obesity. Rather, we show that alterations in the Hedgehog signaling pathway in the liver lead to a metabolic phenotype that is resembling metabolically healthy obesity. Mechanistically, we identified an indirect influence on the hepatic secretion of the fibroblast growth factor 21, which is regulated by a series of signaling cascades that are directly transcriptionally linked to the activity of the Hedgehog transcription factor GLI1. The results of this study impressively show that the metabolic balance of the entire organism is maintained via the activity of morphogenic signaling pathways, such as the Hedgehog cascade. Obviously, several pathways are orchestrated to facilitate liver metabolic status to peripheral organs, such as adipose tissue.