EPHX1 Antibody
- Known as:
- EPHX1 Antibody
- Catalog number:
- csb-pa007734la01hu
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- CusAb
- Gene target:
- EPHX1 Antibody
Related genes to: EPHX1 Antibody
- Gene:
- EPHX1 NIH gene
- Name:
- epoxide hydrolase 1
- Previous symbol:
- EPHX
- Synonyms:
- -
- Chromosome:
- 1q42.12
- Locus Type:
- gene with protein product
- Date approved:
- 1988-08-09
- Date modifiied:
- 2016-10-05
Related products to: EPHX1 Antibody
Related articles to: EPHX1 Antibody
- Ulcerative colitis (UC) is associated with gut microbial dysbiosis, but the host molecular alterations potentially linked to microbially derived metabolites remain incompletely understood. We integrated Mendelian randomization (MR), microbial metabolite annotation, computational target prediction, colonic transcriptomics, network analysis, and machine learning. MiBioGen microbiome GWAS data were used as exposures and FinnGen Release 12 ULCERENTER as the outcome. Metabolites linked to MR-prioritized taxa were retrieved from GutMGene, and human targets were predicted using SwissTargetPrediction and SEA. UC-related genes were defined by integrating differential expression analysis and WGCNA and then intersected with predicted metabolite targets. MR prioritized one family and eight genera showing nominal genetically supported associations with UC, but none remained significant after Benjamini-Hochberg FDR correction. Three prioritized genera were linked to 15 microbe-metabolite records, corresponding to 13 unique metabolites; nine were retained for target prediction, yielding 277 unique predicted human targets. Transcriptomic analysis identified 1,530 DEGs and a 312-gene MEgrey60 module, with 273 overlapping genes, producing 1,569 unique UC-related genes. Their intersection with the 277 predicted targets yielded 47 candidate genes. Enrichment analyses highlighted mainly metabolic and lipid-related processes. Random Forest showed the highest mean AUC across the two independent external benchmarking cohorts, and SHAP prioritized EPHX1, HSD17B2, IGFBP5, and MMP10. IBDome analysis showed inflammation-associated expression differences in these genes. This study provides a genomics-informed, hypothesis-generating framework that prioritizes candidate microbe-metabolite-host relationships in UC for future experimental validation. - Source: PubMed
Publication date: 2026/09/04
Yan JingrenDing Shun - Grilled food toxicants 4-hydroxynonenal (4-HNE), benzo[a]pyrene (BaP), and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) pose health risks, including non-alcoholic steatohepatitis (NASH) and hepatocellular carcinoma (HCC). However, their synergistic molecular mechanisms in driving NASH to NASH-HCC progression remain unclear. We employed network toxicology (CTD, GeneCards), bioinformatics analysis of the GSE164760 dataset, machine learning (LASSO, SVM-RFE, Random Forest), SHAP interpretability analysis, immune infiltration profiling (CIBERSORT), miRNA-TF-mRNA network construction, and molecular docking to identify core genes and elucidate mechanisms. Toxicity prediction confirmed significant hepatotoxicity for all three compounds. Intersection analysis identified 8 key genes (InterGenes) enriched in oxidant detoxification, fatty acid metabolism, and chemical carcinogenesis pathways. Machine learning refined this to 6 CoreGenes (). SHAP analysis revealed that high expression of ALB, TF, GSTA1 and CYP2E1, together with low expression of GPX3 and EPHX1, correlated with increased progression risk. A CoreGenes-based diagnostic nomogram achieved exceptional performance (AUC = 0.967). Immune infiltration analysis revealed significant shifts in regulatory T cells and M2 macrophages during progression. Molecular docking confirmed strong binding affinities between the toxicants and CoreGenes proteins (e.g., BaP-GSTA1: -10.7 kcal/mol). Functional enrichment implicated dysregulated fatty acid metabolism, PPAR, and TGF-beta signaling. This study identifies GSTA1, EPHX1, CYP2E1, GPX3, ALB, and TF as pivotal biomarkers and mediators through which 4-HNE, BaP, and PhIP synergistically promote NASH-HCC progression via oxidative stress, metabolic dysfunction and remodeling of the immune microenvironment. The CoreGenes signature and multi-gene model provide a powerful tool for risk assessment and early intervention. - Source: PubMed
Publication date: 2026/08/31
Qin BingbingZhang YeLi NaLi JingLuo YuehuaTang XiZhou RuishengCui TianqiTang Ying - Hydrolytic drug-metabolizing enzymes (hydrolases) are essential for the metabolism of many therapeutic agents; however, comprehensive data on their tissue distribution and interspecies variability remain limited. To address this knowledge gap, the primary objective of this study was to quantify the abundance of drug metabolism-relevant hydrolases (e.g., CES1/2, PON1/2/3, BPHL, APEH, CMBL, EPHX1/2, DPP4, and AADAC) across liver, intestine, and kidney tissues in humans, rats, mice, dogs, and monkeys using a comprehensive global proteomics approach. Further, we present here qualitative and quantitative differences in intertissue and interspecies variability among 182 detected hydrolases. Humans exhibited the greatest variability of hydrolases across tissues, with marked qualitative and quantitative differences in protein abundance observed between species. Orthology analysis highlighted substantial sequence conservation in monkeys but greater divergence in rodents and dogs. Overall, these findings could provide critical quantitative data to inform animal model selection and improve the translation of preclinical drug metabolism studies to humans for drugs that are majorly metabolized by hydrolases. - Source: PubMed
Publication date: 2026/06/24
Subash SandhyaAhire DeepakJones Robert SMa BinTian YuWang TingKhojasteh S CyrusMurray Bernard PStresser David MTaub MitchellPrasad Bhagwat - Herb-Drug Interactions (HDIs) are a major clinical concern, as they may alter drug efficacy or cause toxicity. This study evaluated the potential HDIs of Echinacea purpurea, Thymus vulgaris, and Salvia officinalis by assessing their effects on Drug-Metabolizing Enzyme (DME) gene expression in rats. - Source: PubMed
Publication date: 2026/05/22
Ahmed Shahira HNaguib Mohamed MSeoudi Dina MEl-Sayed Wael M - BackgroundAlzheimer's disease (AD) involves interactions among genetic, environmental, and lifestyle factors, yet the contribution of environmental exposures to cognitive decline and biomarker changes remains unclear. Detoxification genes such as EPHX1 may influence susceptibility to environmental neurotoxicants.ObjectiveTo evaluate associations between environmental risk, cognitive outcomes, and AD biomarkers, and to examine potential contributions of detoxification genes.MethodsWe analyzed 5101 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) across four study phases. Environmental exposure was summarized using a composite Environmental Risk Score (ERS) derived from Rural-Urban Continuum Codes, Rural-Urban Commuting Area codes, Risk-Screening Environmental Indicators, and occupational exposure. Cognitive outcomes included Mini-Mental State Examination, Clinical Dementia Rating, Montreal Cognitive Assessment, Neuropsychological Test Battery, Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Executive Dysfunction Cognitive Assessment. Biomarkers included PET amyloid/tau, MRI hippocampal volume, and cerebrospinal fluid amyloid-β, tau, and neurofilament light chain. Multivariable regression models adjusted for sociodemographic factors and ε4 carrier status.ResultsERS was significantly associated with CDR (β = -1.13E-07; 95% CI -1.98E-07, -2.75E-08; p = 0.00956) but not with other cognitive measures. EPHX1 showed a significant main effect on ADAS-Cog (β = 0.479; 95% CI 0.0305, 0.927; p = 0.0356). ERS × gene interaction terms were not significant. ERS was not associated with amyloid PET SUVR.ConclusionsEnvironmental risk showed limited associations with AD-related outcomes, while EPHX1 demonstrated a significant main effect on cognitive performance. Longitudinal studies are needed to clarify mechanisms linking environmental exposure and AD. - Source: PubMed
Publication date: 2026/05/25
Kanani KhushiRamakrishnan PrevenaNeupane SnabuMisra ManaliBalmer-Brown KaitlynnHalteman SarahWarrick Tia