Human Apolipoprotein H ELISA, APOH
- Known as:
- Human Apolipoprotein H Enzyme-linked immunosorbent assay test, APOH
- Catalog number:
- E01A0521
- Product Quantity:
- 96 Tests/kit
- Category:
- -
- Supplier:
- BGene
- Gene target:
- Human Apolipoprotein ELISA APOH
Related genes to: Human Apolipoprotein H ELISA, APOH
- Gene:
- APOH NIH gene
- Name:
- apolipoprotein H
- Previous symbol:
- B2G1
- Synonyms:
- BG
- Chromosome:
- 17q24.2
- Locus Type:
- gene with protein product
- Date approved:
- 1987-09-11
- Date modifiied:
- 2015-12-17
Related products to: Human Apolipoprotein H ELISA, APOH
Related articles to: Human Apolipoprotein H ELISA, APOH
- Cannabidiol (CBD) is increasingly being used in veterinary medicine; however, its systemic molecular effects in dogs remain poorly characterized. This study employed label-free quantitative proteomics to compare the serum proteomic responses of healthy dogs ( = 18) after 30 days of oral CBD delivery via three distinct matrices: hemp by-product feed pellets (F), CBD-infused oil (O), and semi-solid treat (SN). The verified chronic doses differed among the groups. Multivariate analysis revealed distinct formulation-specific proteomic signatures, with the F group clustered separately from the O and SN groups. Despite dose and matrix variations, all groups shared a core metabolic response characterized by downregulation of apolipoproteins (APOA4, APOC3, APOC1, and APOH) and upregulation of hemoglobin subunits (HBA and HBB), indicating CBD-mediated modulation of lipid metabolism and redox homeostasis. The high-exposure groups (O, SN) uniquely exhibited upregulation of proteins involved in vascular integrity and tissue scaffolding (e.g., TGFB1, PDGFRB, and VWF), while the SN group also showed induction of immunomodulatory and cytoprotective markers, such as clusterin (CLU). These findings demonstrate that the CBD delivery matrix critically influences systemic bioavailability and the scope of proteomic remodeling. Although all formulations engage core metabolic pathways, high-bioavailability formats induce additional signatures suggestive of vascular stabilization and stress resilience, providing a molecular rationale for optimizing CBD-based therapeutic formulations in canine medicine. - Source: PubMed
Publication date: 2026/05/13
Theerapan WutthiwongLimsuwan SasithornRattanasrisomporn JatupornPloypetch SekkarinTansakul Natthasit - Immune checkpoint inhibitors like pembrolizumab exhibit variable efficacy in metastatic gastric cancer (GC). This study aimed to identify molecular drivers of pembrolizumab response, explore mechanisms of immune checkpoint inhibitors (ICIs) efficacy, and develop a prognostic signature. Transcriptomic analysis of pembrolizumab-treated GC (TIGER database) identified 165 response-associated differentially expressed genes (DEGs). Functional annotation and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) revealed that responder-upregulated genes (R-DEGs) were enriched in immune activation pathways and mainly localized to CD8 + T/NK cells. In contrast, non-responder-upregulated genes (D-DEGs) were linked to extracellular matrix (ECM) remodeling and mainly expressed in fibroblasts/endothelial cells. CellChat analysis demonstrated that key DEGs mediate immune-stromal crosstalk via MHC-I and collagen/laminin signaling. A prognostic signature (Lasso-StepCox[forward] Riskscore; LSR: APOD, APOH, BATF2, GJA1, MAGED1, SLC5A1, SLCO2A1, VWF, VCAN) was derived and validated in four independent GC cohorts from the GEO and Cancer Genome Atlas (TCGA) database. Multi-omics analyses showed that LSR-high tumors exhibited aggressive clinicopathological features, increased stromal components, reduced cytotoxic immune infiltration, diminished tumor mutational burden (TMB), and poorer prognosis. Immunohistochemistry (IHC) and spatial transcriptomics in GC showed that stromal VWF/VCAN expression correlates with reduced CD8⁺ T cell granzyme B expression, suggesting T cell dysfunction. High VWF expression in GC predicted poor survival, and a combined VWF/VCAN score showed enhanced prognostic stratification. This study highlights stromal-immune crosstalk as a driver of pembrolizumab resistance and provides a signature as a clinical tool for prognosis and personalized therapy in metastatic GC. - Source: PubMed
Publication date: 2026/04/23
Zhang FanZhang QingqingShao ShuaiLi XiaoboCheng YiCao XuYu XiaotangGao Zhengming - The search for new biomarkers that allow an early diagnosis in sepsis has become a necessity in medicine. This study aims to identify protein biomarkers that differentiate sepsis from non-infectious systemic inflammatory response syndrome (NISIRS), addressing the need for early sepsis diagnosis. - Source: PubMed
Publication date: 2026/04/24
Ruiz-Sanmartín AdolfoRibas VicentSuñol DavidChiscano-Camón LuisMartín LauraBajaña IvánBastida JulianaLarrosa NievesGonzález Juan JoséCarrasco María DoloresCanela NúriaFerrer RicardRuiz-Rodríguez Juan Carlos - Developing reliable biomarkers capable of differentiating Parkinson's disease from other neurological conditions is crucial for both patient care and research. In this study, we leveraged recent advances in high-throughput proteomic technology and machine learning to develop candidate biomarkers for Parkinson's disease. Using the Olink Explore 3072 assay, we obtained plasma proteomic profiles from 698 study participants, comprising Parkinson's disease cases (n = 149), neurologically healthy controls (n = 230), and participants with other neurological conditions (n = 319). The study cohort was split into Training Set (n = 560) and Test Set (n = 138). We conducted differential protein abundance analysis and pathway enrichment analysis, and subsequently applied the Boruta algorithm to identify differentially abundant proteins that are predictive of Parkinson's disease. To create a diagnostic biomarker panel, we trained a stacking ensemble machine learning (ML) model on the Training Set (n = 118 Parkinson's patients, n = 184 healthy controls, and n = 258 individuals with other neurological disorders) using eleven proteins (APOH, ARG1, CCN1, CXCL1, CXCL8, DDC, GRAP2, IL1RAP, OSM, PRL, and SPRY2) as model features. We used the Shapley Additive Explanations (SHAP) framework and network analysis to evaluate predictive importance and biological relevance of each protein in the ML model. The model demonstrated high accuracy in the held-out Test Set (n = 138) and three external cohorts-the UK Biobank (n = 43,969), the Parkinson's Disease Biomarkers Program (n = 138), and the Parkinson's Progression Markers Initiative (n = 385), with areas under the receiver operating characteristic curve of 0.939, 0.789, 0.909, 0.816, respectively. Additionally, network and pathway analyses helped interpret the model, revealing activity related to inflammatory mediators, ErbB signaling, T-cell receptor signaling, and lipid metabolism. Our findings highlight the potential of plasma protein biomarkers to improve Parkinson's disease diagnosis and deepen biological understanding of this complex neurological disorder. Our model demonstrates high specificity and reliability across multiple independent cohorts, indicating the significant potential of proteomics-based biomarkers and the clinical utility of ML-supported diagnosis in Parkinson's disease care. The model also helps to elucidate potential novel risk factors and pathways associated with Parkinson's disease. - Source: PubMed
Publication date: 2026/04/22
Adewale BoluwatifeChia RuthMoaddel RuinLandeck NatalieRasheed MemoonaAlba CamilleReho PaoloVasta RosarioCalvo AndreaMoglia CristinaCanosa AntonioManera UmbertoSnyder AllisonLee Yi-JungGrassano MaurizioGao ChristineZhu MinBrunetti MauraCasale FedericoArvind Kumar Dawson Ted MRosenthal Liana SHall Anna JPantelyat Alexander YDing JinhuiGibbs J RaphaelEgan Josephine MCandia JuliánTanaka ToshikoFerrucci LuigiChiò AdrianoNarendra Derek PKwan Justin YEhrlich Debra JDalgard Clifton LTraynor Bryan JScholz Sonja W - Recurrent pregnancy loss (RPL) remains a devastating outcome for many women, with up to 40–60% of cases classified as unexplained despite extensive clinical workup. During pregnancy, extracellular vesicles (EVs) from the placenta enters into maternal circulation and plays a vital role in completion of a successful pregnancy. Profiling of EVs cargo proteins offers a promising avenue for the pathophysiology of RPL, with the potential to revolutionize diagnosis, prognosis, and treatment strategies. Blood samples were collected from 5 pregnant women with history of RPL and 5 gestational aged-matched healthy pregnant controls. EVs were extracted from plasma and characterized for their size, morphology, number and presence of surface markers. Further, liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis of EV protein was performed to identify differentially expressed proteins (DEPs). In total 508 proteins with unique peptides were identified. Among these 330 proteins were differentially expressed between patients and controls, out of which 94 were significantly expressed ( < 0.05). Based on the expression pattern, 25 proteins were upregulated (log2FC > 1, < 0.05) and 69 were downregulated. GO enrichment and KEGG pathway enrichment indicated involvement of pathways such as innate immune response, neutrophil degranulation, complement cascade regulation and intrinsic pathway of fibrin clot formation. Protein-protein interaction analysis identified 10 hub proteins (,,,,,,,,,) potentially implicated in RPL pathophysiology. While preliminary, this study provides molecular insights into EV-associated proteins in RPL and highlights potential biomarkers for future validation. - Source: PubMed
Publication date: 2026/04/09
Bhardwaj ChitraSrivastava PriyankaBhadoriya Ravi Pratap SinghRohilla MinakshiKaur AnupriyaPanigrahi InushaChopra Seema