SerpinD1 _ HC2 Antibody
- Known as:
- SerpinD1 _ HC2 Antibody
- Catalog number:
- 10295-RP01
- Product Quantity:
- 200
- Category:
- -
- Supplier:
- Smart Serology
- Gene target:
- SerpinD1 _ HC2 Antibody
Related genes to: SerpinD1 _ HC2 Antibody
- Gene:
- SERPIND1 NIH gene
- Name:
- serpin family D member 1
- Previous symbol:
- HCF2
- Synonyms:
- HC-II, HLS2, HC2, D22S673
- Chromosome:
- 22q11.21
- Locus Type:
- gene with protein product
- Date approved:
- 1988-05-31
- Date modifiied:
- 2019-04-23
Related products to: SerpinD1 _ HC2 Antibody
Related articles to: SerpinD1 _ HC2 Antibody
- Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder with incompletely elucidated underlying biological mechanisms. Circulating proteins serve as an intermediate molecular layer linking genetic variation to downstream biological processes. This study aimed to systematically investigate the causal associations between the plasma proteome and ASD risk, followed by multi-omic and clinical validation. - Source: PubMed
Publication date: 2026/04/24
Wang LihongLiu TianciYu LianhuLiu ZhiyueChe ChaoYu XiaoxiaoCai ZhifengCao Aihua - Patients with Hepatitis B Virus-related liver failure are highly vulnerable to secondary infections (SI), yet early predictive tools remain limited. In this work, we aim to develop and validate a plasma proteomics-based model for early SI risk assessment. In a prospective multicenter study, 114 patients are enrolled in the discovery cohort, 60 each in two validation cohorts. Untargeted proteomics is used to identify SI-related proteins, followed by Minimum Redundancy Maximum Relevance based feature selection and logistic regression modeling. Targeted proteomics and ELISA are applied for external validation. Inflammatory and coagulation pathway dysregulation is strongly associated with SI. A final model including Lysozyme (LYZ), Calmodulin 1 (CALM1), Serpin Family D Member 1 (SERPIND1), Dermatopontin (DPT), total bilirubin, and AST show excellent discrimination (area under the receiver operating characteristic curve (AUROC) 0.980 in discovery; 0.873 in validation), outperforming C-reactive protein (CRP), white blood cell (WBC), and Neutrophil percentage (NE%). It also predicts 28-day mortality better than Chronic Liver Failure-Consortium Acute-on-Chronic Liver Failure score (CLIF-C ACLF) and Model for End-Stage Liver Disease (MELD). ELISA measurements in validation cohort 2 yield consistent trends, and an ELISA-based model achieve an AUROC of 0.883. This proteomics-derived model reliably identifies patients at high SI risk and supports early clinical intervention. - Source: PubMed
Publication date: 2026/03/03
Xiong FeixiangZheng JianmingChen JiajiaWu LinhuanJiang YuyongLu LianheZhou TongZhou YangWu TongSun YaminJin RonghuaHou Yixin - Lung squamous cell carcinoma (LUSC) has a poor prognosis due to the lack of effective targeted therapies, and its incidence has increased dramatically in recent years, creating an urgent need for new prognostic markers. Given that tumor immune and metabolic heterogeneity can influence LUSC prognosis, this study aimed to construct a novel predictive model based on immune-related and metabolism-related genes for prognostic stratification in LUSC. Transcriptomic as well as clinical data of 502 and 43 LUSC cases were downloaded from The Cancer Genome Atlas Program (TCGA) and the Gene Expression Omnibus (GEO) databases. Core LUSC subtype genes were identified using nonnegative matrix factorization (NMF), and a prognostic risk model was subsequently constructed by applying machine learning, LASSO regression, and multivariate Cox regression. Based on this model, patients were stratified into low-risk and high-risk subgroups with distinct expression profiles and significant survival differences. Gene-Set Enrichment Analysis of the marker genes revealed that immune pathways were active in the high-risk group, whereas metabolic pathways were prominent in the low-risk group. The two groups also differed in tumor mutation burden and response to clinical therapy. High expression levels of NRTN, CYP2C18, TSLP, MIOX, and RORB and low expression levels of HBEGF, SERPIND1, PTGIS, and LBP were correlated with high survival rates. Immunohistochemical validation in 42 patients confirmed the expression patterns of the identified genetic markers, which were stronger in tumor tissues than in adjacent normal tissues. In conclusion, six immune-related and three metabolism-related genes were identified as prognostic markers of LUSC, with their expression levels significantly associated with the survival rate. The resulting model demonstrates strong predictive power and is expected to help guide treatment strategy decisions. - Source: PubMed
Xue HaoyuanLi HongweiHan SongyanZhang XiaqinLiu TongBu PengLiang Hua - The glymphatic system plays a key role in brain waste clearance, but its genetic regulation remains poorly understood. Diffusion Tensor Image Analysis along the Perivascular Space (DTI-ALPS) index is a non-invasive imaging biomarker to asses glymphatic system activity. We integrated mean DTI-ALPS genome-wide association study (GWAS) data from 31,021 individuals of European ancestry with GTEx v8 multi-tissue eQTL data to perform transcriptome-wide association studies (TWAS) using Unified Test for Molecular Signature (UTMOST) and Functional Summary-based Imputation (FUSION). Gene-level associations were further validated by Multi-marker Analysis of Genomic Annotation (MAGMA). Causal inference was conducted using cis-Mendelian randomization (cis-MR) and summary-data-based Mendelian randomization (SMR), while colocalization was applied to provide evidence of strong associations between two traits within a single genetic region, thereby ensuring the stability of the MR conclusions. TWAS identified 17 candidate genes (AGBL5-IT1, CENPA, CGREF1, DNAJC5G, EMILIN1, GCAT, KHK, MAPRE3, OTOF, PLCL1, PREB, RBM43, RFTN2, SERPIND1, SNAP29, TRIOBP, and UCN), among which six protein-coding genes (TRIOBP, MAPRE3, EMILIN1, KHK, GCAT, and CGREF1) were further validated by MAGMA. Cis-MR provided evidence for the causal effects of these six genes, while colocalization supported that the MR conclusions were stable for four of them (TRIOBP, MAPRE3, EMILIN1, and GCAT). Finally, SMR identified three genes (TRIOBP, GCAT, and MAPRE3) that showed consistent and robust associations with DTI-ALPS across multiple tissues. These findings provide statistical evidence for genetic regulation of glymphatic function. - Source: PubMed
Publication date: 2025/12/05
Zhu XiaoyangWang ShengjieZhang ShuaiqiLiu ZhiyuanWang NaWang ShuYang Nixia - : Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare disease, in which multiple genetic and environmental factors may contribute. This study aimed to identify potential genetic determinants in patients with CTEPH and to compare their occurrence to a control group, which included patients with pulmonary embolism who had not developed CTEPH. : Tier 1 and 2 genes related to coagulation, fibrinolysis and platelet disorders-as recommended by the International Society on Thrombosis and Haemostasis-and genes associated with vascular conditions were analyzed in n = 15 patients with CTEPH and n = 17 controls using next-generation sequencing. Non-synonymous, rare variants were collected and interpreted. : As expected, no single gene or variant was consistently present among CTEPH patients. Instead, individuals carried different mutations and combinations of variants. We identified several variants that were not found in the control group. Candidate variants were detected in , , , , , , , , , , , , , , , , , , , and We did not detect exclusive variants in , , and although they were suggested as candidates in previous studies. Elevated factor VIII and von Willebrand factor in CTEPH could not be explained by mutations in and . : Our study supports the hypothesis of heterogeneous genetic background in CTEPH, involving multiple pathways such as coagulation, altered fibrinolysis and impaired angiogenesis. These results provide a basis for more detailed investigations into specific genes and variants potentially associated with CTEPH in larger cohorts. - Source: PubMed
Publication date: 2025/11/06
Bereczky ZsuzsannaKolodzey GáborBorsos SaroltaBalogh LászlóBiró Petra ErzsébetMolnár ÉvaRázsó KatalinPéter AndreaBarta JuditSzűk Tibor