Steroid metabolic process

About: Steroid metabolic process is a research topic. Over the lifetime, 40 publications have been published within this topic receiving 752 citations.

Roles of transforming growth factor-β1 and OB-cadherin in porcine cardiac valve myofibroblast differentiation

Abstract: Calcific aortic stenosis is a common disease, and some of its early causes are the activation and differentiation of resident fibroblasts to myofibroblasts in response to transforming growth factor β1 (TGF-β1). The aim of this study was to understand how TGF-β1 and its downstream effector, OB-cadherin [cadherin 11 (CDH11)], regulate porcine myofibroblast phenotypes. Based on whole-genome microarrays, 95 and 107 genes are up- and down-regulated at both the early (8 h) and the late (24 h) time points of TGF-β1 treatment. Gene functions related to cell adhesion, skeletal system development, and extracellular matrix are up-regulated by TGF-β1, whereas oxidation-reduction and steroid metabolic process are down-regulated. Notably, one of the cell adhesion molecules, CDH11, is up-regulated by ∼2-fold through both the Smad2/3 and the ERK pathways elicited by TGF-β1. CDH11 mediates cell-cell contacts in both valvular fibroblasts and myofibroblasts. Knockdown of CDH11 by small interfering RNA increases the myofibroblast phenotype, including an ∼2-fold increase in α-smooth muscle actin (α-SMA) expression and stress fiber formation. In contrast, increased binding of CDH11 through antibody treatment inhibits α-SMA expression. This study presents gene functional changes in response to TGF-β1 at the systems level and supports an inhibitory role of CDH11 in myofibroblast differentiation.

Connecting gene expression data from connectivity map and in silico target predictions for small molecule mechanism-of-action analysis

Abstract: Integrating gene expression profiles with certain proteins can improve our understanding of the fundamental mechanisms in protein–ligand binding. This paper spotlights the integration of gene expression data and target prediction scores, providing insight into mechanism of action (MoA). Compounds are clustered based upon the similarity of their predicted protein targets and each cluster is linked to gene sets using Linear Models for Microarray Data. MLP analysis is used to generate gene sets based upon their biological processes and a qualitative search is performed on the homogeneous target-based compound clusters to identify pathways. Genes and proteins were linked through pathways for 6 of the 8 MCF7 and 6 of the 11 PC3 clusters. Three compound clusters are studied; (i) the target-driven cluster involving HSP90 inhibitors, geldanamycin and tanespimycin induces differential expression for HSP90-related genes and overlap with pathway response to unfolded protein. Gene expression results are in agreement with target prediction and pathway annotations add information to enable understanding of MoA. (ii) The antipsychotic cluster shows differential expression for genes LDLR and INSIG-1 and is predicted to target CYP2D6. Pathway steroid metabolic process links the protein and respective genes, hypothesizing the MoA for antipsychotics. A sub-cluster (verepamil and dexverepamil), although sharing similar protein targets with the antipsychotic drug cluster, has a lower intensity of expression profile on related genes, indicating that this method distinguishes close sub-clusters and suggests differences in their MoA. Lastly, (iii) the thiazolidinediones drug cluster predicted peroxisome proliferator activated receptor (PPAR) PPAR-alpha, PPAR-gamma, acyl CoA desaturase and significant differential expression of genes ANGPTL4, FABP4 and PRKCD. The targets and genes are linked via PPAR signalling pathway and induction of apoptosis, generating a hypothesis for the MoA of thiazolidinediones. Our analysis show one or more underlying MoA for compounds and were well-substantiated with literature.

Collagen peptide ingestion alters lipid metabolism-related gene expression and the unfolded protein response in mouse liver.

Abstract: Ingestion of collagen peptide (CP) elicits beneficial effects on the body, including improvement in blood lipid profiles, but the underlying mechanisms remain unclear. The purpose of this study was to investigate the effects of CP ingestion on the liver, which controls lipid metabolism in the body. Male BALB/cCrSlc mice were bred with the AIN-93M diet containing 14 % casein or the AIN-93M-based low-protein diet containing 10 % casein or a diet containing 6 % casein+4 % CP for 10 weeks (n 12/group). Total, free and esterified cholesterol levels in the blood decreased in the CP group. DNA microarray analysis of the liver revealed that expressions of genes related to lipid metabolic processes such as the PPAR signalling pathway and fatty acid metabolism increased in the CP group compared with the 10 % casein group. The expressions of several genes involved in steroid metabolic process, including Cyp7a1 and Cyp8b1, were decreased, despite being targets of transcriptional regulation by PPAR. These data suggest that lipid metabolism in the liver is altered by CP ingestion, and the decrease in blood cholesterol levels in the CP group is not due to enhancement of the steroid metabolic process. On the other hand, expressions of genes related to the unfolded protein response (UPR) significantly decreased at the mRNA level, suggesting that CP ingestion lowers endoplasmic reticulum stress. Indeed, protein levels of phosphorylated inositol-requiring enzyme 1 decreased after CP ingestion. Taken together, CP affects the broader pathways in the liver - not only lipid metabolism but also UPR.

Expression Profile of Genes Regulating Steroid Biosynthesis and Metabolism in Human Ovarian Granulosa Cells-A Primary Culture Approach.

Abstract: Because of the deep involvement of granulosa cells in the processes surrounding the cycles of menstruation and reproduction, there is a great need for a deeper understanding of the ways in which they function during the various stages of those cycles. One of the main ways in which the granulosa cells influence the numerous sex associated processes is hormonal interaction. Expression of steroid sex hormones influences a range of both primary and secondary sexual characteristics, as well as regulate the processes of oogenesis, folliculogenesis, ovulation, and pregnancy. Understanding of the exact molecular mechanisms underlying those processes could not only provide us with deep insight into the regulation of the reproductive cycle, but also create new clinical advantages in detection and treatment of various diseases associated with sex hormone abnormalities. We have used the microarray approach validated by RT-qPCR, to analyze the patterns of gene expression in primary cultures of human granulosa cells at days 1, 7, 15, and 30 of said cultures. We have especially focused on genes belonging to ontology groups associated with steroid biosynthesis and metabolism, namely “Regulation of steroid biosynthesis process” and “Regulation of steroid metabolic process”. Eleven genes have been chosen, as they exhibited major change under a culture condition. Out of those, ten genes, namely STAR, SCAP, POR, SREBF1, GFI1, SEC14L2, STARD4, INSIG1, DHCR7, and IL1B, belong to both groups. Patterns of expression of those genes were analyzed, along with brief description of their functions. That analysis helped us achieve a better understanding of the exact molecular processes underlying steroid biosynthesis and metabolism in human granulosa cells.

Pathway analysis of genome-wide association studies for Parkinson's disease.

Abstract: The study was done to identify the candidate causal single nucleotide polymorphisms (SNPs) and candidate causal mechanisms that contribute to Parkinson’s disease (PD) susceptibility and to generate a SNP to ene to pathway hypothesis using an analytical pathway-based approach. We used a PD genome-wide association study (GWAS) meta-analysis data of the genotypes of 2,525,705 SNPs in 4,238 PD cases and 4,239 controls. Identify candidate Causal SNPs and Pathways (ICSNPathway) analysis was applied to the PD GWAS dataset. The first stage involved the pre-selection of candidate causal SNPs by linkage disequilibrium analysis and the functional SNP annotation of the most significant SNPs found. The second stage involved the annotation of biological mechanisms for the pre-selected candidate causal SNPs using improved-gene set enrichment analysis. ICSNPathway analysis identified three candidate SNPs, two genes, twenty-one pathways, and three hypothetical biological mechanisms: (1) rs17651549 to microtubule-associated protein tau (MAPT) to protein domain specific binding (nominal p < 0.001, false discovery rate (FDR) < 0.001), neurogenesis (nominal p < 0.001, FDR < 0.001), regulation of neurogenesis (nominal p < 0.001, FDR = 0.001), positive regulation of axonogenesis (nominal p < 0.001, FDR = 0.001), regulation of protein polymerization (nominal p < 0.001, FDR = 0.004), negative regulation of organelle organization (nominal p < 0.001, FDR = 0.004), hsa01510 (nominal p < 0.001, FDR = 0.005), neuron differentiation (nominal p < 0.001, FDR = 0.009), and axonogenesis (nominal p < 0.001, FDR = 0.009); (2) rs10445337 to MAPT to protein domain specific binding (nominal p < 0.001, FDR < 0.001), neurogenesis (nominal p < 0.001, FDR < 0.001), regulation of neurogenesis (nominal p < 0.001, FDR = 0.001), and positive regulation of axonogenesis (nominal p < 0.001, FDR = 0.001); (3) rs9938550 to HSD3B7 to hsa00363 (nominal p < 0.001, FDR = 0.004), bile acid metabolic process (nominal p = 0.005, FDR = 0.019), and steroid metabolic process (nominal p = 0.010, FDR = 0.039). By applying the ICSNPathway analysis to PD GWAS meta-analysis data, three candidate SNPs, two genes (MAPT and HSD3B7), and 21 pathways involving protein domain specific binding and neurogenesis were identified, which may contribute to PD susceptibility.