Ask about this productRelated genes to: HSD11B1 antibody
- Gene:
- HSD11B1 NIH gene
- Name:
- hydroxysteroid 11-beta dehydrogenase 1
- Previous symbol:
- HSD11B, HSD11
- Synonyms:
- SDR26C1
- Chromosome:
- 1q32.2
- Locus Type:
- gene with protein product
- Date approved:
- 1991-11-14
- Date modifiied:
- 2016-10-05
Related products to: HSD11B1 antibody
Related articles to: HSD11B1 antibody
- This study aimed to elucidate the mechanism of San Jie Tong Mai Formula (SJTMF) against atherosclerosis (AS), a leading cause of cardiovascular morbidity. Using ApoE mouse models, we demonstrated that SJTMF significantly inhibits AS plaque progression. Through an integrated network pharmacology and proteomics strategy, five core bioactive components were identified: beta-sitosterol, naringenin, luteolin, isorhamnetin, and 3beta-hydroxy-24-methylene-8-lanostene-21-oic acid. Concurrently, proteomics revealed 129 AS-related proteins that were differentially expressed. Molecular docking confirmed high-affinity binding interactions between these components and the key target Hsd11b1, with their binding energies all below -5 kcal/mol. Mechanistic investigations further revealed that SJTMF may regulate Hsd11b1-mediated glucocorticoid metabolism. This regulation contributes to significant amelioration of both dyslipidemia and vascular inflammation, thereby suppressing AS development. Collectively, this work demonstrates, for the first time, the innovative mechanism by which a traditional Chinese medicine formula exerts anti-AS effects through multi-component synergistic regulation of the Hsd11b1 target, offering new insights for therapeutic intervention. - Source: PubMed
Publication date: 2026/04/17
Han HuizeLi HongyuZhou ZhilinLiu AidongZhong CongboSun Ye - Depression remains a leading cause of global disability, with early-life stress (ELS) representing one of its most potent and well-replicated risk factors. This chapter synthesizes evidence linking childhood adversity-including abuse, neglect, and loss-to persistent dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis. A key mechanism is the imbalance between mineralocorticoid (MR) and glucocorticoid receptors (GR), resulting in altered cortisol rhythms, impaired stress recovery, and increased susceptibility to recurrent and treatment-resistant depression. Converging neuroimaging, molecular, and epigenetic data reveals that ELS induces lasting changes in MR/GR signaling, including methylation and HSD11B1 polymorphisms, which biologically embed risk across the lifespan. Translational tools such as the prednisolone suppression test (PST) and cortisol awakening response (CAR) have emerged as promising biomarkers for patient stratification, treatment prediction, and suicide risk assessment. Future directions highlight the potential of biomarker-guided psychiatry, integrating endocrine, genetic, epigenetic, neuroimaging, and immune data to inform mechanism-based interventions-such as MR/GR agonists and antagonists, including an epigenetic approach-aimed at mitigating the enduring impact of childhood adversity and advancing precision mental health care. - Source: PubMed
Juruena Mario F - Bone and skeletal muscles are vital to human health, and diseases related to these tissues can place significant stress on patients, families, and society. The key enzyme regulating glucocorticoid metabolism, 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1), is encoded by the gene and can convert inactive cortisone into active cortisol. Recent studies have shown that 11β-HSD1 is a key enzyme in the pathogenesis of bone and skeletal muscle, with its function being strictly context-dependent. 11β-HSD1 inhibits osteoblast differentiation and activates osteoclast formation, contributing to glucocorticoid-induced osteoporosis (GIOP). 11β-HSD1 accelerates skeletal muscle atrophy by disrupting the stability of muscle proteins. It plays a dual role in anti-inflammation and bone protection, participating in polyarthritis; 11β-HSD1 also contributes to bone loss and anti-inflammation in rheumatoid arthritis (RA) through multiple pathways. Clarifying the context-specific mechanisms of 11β-HSD1 in bone and skeletal muscle diseases is critical for clinical translation. This review systematically summarizes the role of 11β-HSD1 in bone and skeletal muscle diseases, outlines its potential as a disease-specific therapeutic target, and provides new insights for precise treatment of these diseases. - Source: PubMed
Publication date: 2026/03/15
Huo LiyueSui WeiWang ShangZhu WeiYang YanweiZhang XiaolinZhang YubeiWang Xuefeng - Atopic dermatitis (AD) is a common chronic inflammatory skin condition affecting humans and animals, including dogs. The underlying mechanisms in both species are intricate and varied, yet they demonstrate notable similarities. Although numerous transcriptome profiles have been analyzed separately for each species, comparative studies are relatively scarce. We performed a meta-analysis of gene expression datasets from the affected skin of dogs and humans. Enrichment analysis of commonly shared differentially expressed genes (DEGs) derived from two canine datasets revealed an IL-27-mediated signaling pathway. Furthermore, after examining two published GEO datasets from humans and two from canines, we identified fifteen conserved DEGs across all datasets (p < 0.05). The enrichment assessment of the upregulated genes indicated that S100A8 and S100A9 are associated with the Th17 signaling pathway, while FHL1 and STAT1 are linked to JAK-STAT signaling pathways. CCL13, identified as a Th2-related chemokine, displayed increased expression in both canine and human AD. Consequently, these proteins may serve as potential biomarkers and therapeutic targets for AD in both species. Additionally, three gene products-HSD11B1, IL-34, and NELL2-showed different expression patterns in humans and dogs with AD, suggesting that specific genes may have distinct roles in the pathogenesis of AD across species. - Source: PubMed
Publication date: 2026/04/16
Wang YuRichmond Jillian MAlmela Ramon M - phytochemicals were predicted to target insulin resistance proteins using a modified network pharmacology and molecular docking approach. Two hundred ninety phytochemicals with their aglycones, acetylase and myrosinase degradation products were compiled from literature and phytochemical databases. Nine protein targets were identified from the intersection of gene lists with high relevance to insulin resistance from GeneCards and DisGeNET and the target genes predicted by reverse screening using Swiss Target Prediction: protein-tyrosine phosphatase 1B (PTPN1), 11-beta-hydroxysteroid dehydrogenase 1 (HSD11B1), peroxisome proliferator-activated receptor α (PPARα), peroxisome proliferator-activated receptor γ (PPARγ), PI3-kinase p85-alpha subunit (PIK3R1), insulin receptor (INSR), tumor necrosis factor α (TNF-α), endothelial nitric oxide synthase (eNOS) and hepatic lipase (LIPC). Binding affinities of phytochemicals with the targets were predicted using Autodock Vina. The predicted binding affinities were classified according to calculated thresholds using receiver operating characteristic (ROC) calculations of binding affinities of: (a) binders (annotated drugs and other molecules with known interaction with each target), and (b) decoys (molecules not expected to bind to a specific target). In addition, ubiquitous phytochemicals were filtered out to differentiate the effect on insulin resistance of from that of other plants. The resulting phytochemical-protein interaction network was visualized using Cytoscape. All mentioned targets, except hepatic lipase, were key targets based on various network centrality measures. Previous studies on murine models have shown that isothiocyanate-rich extracts ameliorate insulin resistance. Using our approach, the following phytochemicals, with predicted moderate bioavailability, high GI absorption, and probable binding with insulin resistance targets, are recommended for further or validation for insulin resistance activity: boldione (a steroid); aurantiamide acetate and aurantiamide (peptide derivatives); O-ethyl-[(3,4-dihydroxyphenyl)methyl] carbamothioate and O-methyl-N-[(4-hydroxyphenyl)methyl] carbamothioate (thiocarbamates); 4α,6α-dihydroxyeudesman-8β,12-olide (a sesquiterpenoid); sanleng acid and tianshic acid (fatty acid derivatives); 2',5,5',7-tetrahydroxyflavone; 2',3,5,7-tetrahydroxyflavone; and 6-hydroxykaempferol (flavonoids). By combining network centrality measures of targets, using ROC-derived thresholds for docking energies, and considering ubiquity of phytochemicals, our refined network pharmacology approach may aid in discovering key bioactive phytochemicals as potential chemical markers for standardization and differentiation of an herbal drug. - Source: PubMed
Publication date: 2026/03/10
Santos-Enriquez Armi KatrinaDayrit Fabian Mde Jesus Armando JeromeRojas Nina Rosario L