Ask about this productRelated genes to: IFNA13 Blocking Peptide
- Gene:
- IFNA1 NIH gene
- Name:
- interferon alpha 1
- Previous symbol:
- -
- Synonyms:
- IFNA@, IFL, IFN, IFN-ALPHA, IFNA13, IFN-alphaD
- Chromosome:
- 9p21.3
- Locus Type:
- gene with protein product
- Date approved:
- 1993-01-14
- Date modifiied:
- 2016-10-05
- Gene:
- IFNA13 NIH gene
- Name:
- interferon alpha 13
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 9p21.3
- Locus Type:
- gene with protein product
- Date approved:
- 1993-01-14
- Date modifiied:
- 2016-10-05
Related products to: IFNA13 Blocking Peptide
Related articles to: IFNA13 Blocking Peptide
- Inflammatory bowel diseases (IBD), including Crohn's disease (CD), ulcerative colitis (UC), and IBD-unclassified (IBD-U), are chronic inflammatory disorders of the gastrointestinal tract. Current methods for classification and longitudinal monitoring are invasive, expensive, and often delayed, limiting timely diagnosis and management. This study reports the first application of high-dimensional salivary proteomics integrated with interpretable artificial intelligence/machine learning (AI/ML) to define a minimal protein signature for pediatric IBD classification with the goal of informing therapeutic decision-making. - Source: PubMed
Publication date: 2025/10/17
Rupp Brittany TReyna JoaquinGiunta AllyWeaver TheresaChason KellyLiu JinzeGulati Ajay SByrd Kevin M - Chimeric antigen receptor T-cell (CAR-T) immunotherapy, a novel approach for treating blood cancer, is associated with the production of cytokine release syndrome (CRS), which poses significant safety concerns for patients. Currently, there is limited knowledge regarding CRS-related cytokines and the intricate relationship between cytokines and cells. Therefore, it is imperative to explore a reliable and efficient computational method to identify cytokines associated with CRS. In this study, we propose Meta-DHGNN, a directed and heterogeneous graph neural network analysis method based on meta-learning. The proposed method integrates both directed and heterogeneous algorithms, while the meta-learning module effectively addresses the issue of limited data availability. This approach enables comprehensive analysis of the cytokine network and accurate prediction of CRS-related cytokines. Firstly, to tackle the challenge posed by small datasets, a pre-training phase is conducted using the meta-learning module. Consequently, the directed algorithm constructs an adjacency matrix that accurately captures potential relationships in a more realistic manner. Ultimately, the heterogeneous algorithm employs meta-photographs and multi-head attention mechanisms to enhance the realism and accuracy of predicting cytokine information associated with positive labels. Our experimental verification on the dataset demonstrates that Meta-DHGNN achieves favorable outcomes. Furthermore, based on the predicted results, we have explored the multifaceted formation mechanism of CRS in CAR-T therapy from various perspectives and identified several cytokines, such as IFNG (IFN-γ), IFNA1, IFNB1, IFNA13, IFNA2, IFNAR1, IFNAR2, IFNGR1 and IFNGR2 that have been relatively overlooked in previous studies but potentially play pivotal roles. The significance of Meta-DHGNN lies in its ability to analyze directed and heterogeneous networks in biology effectively while also facilitating CRS risk prediction in CAR-T therapy. - Source: PubMed
Wei ZhenyuZhao ChengkuiZhang MinXu JiayuXu NanWu ShiweiXin XiaohuiYu LeiFeng Weixing - In systemic lupus erythematosus (SLE), the relevance of non-hematopoietic sources of type I interferon in human autoimmunity has recently been recognized. Particularly, type I interferon production precedes autoimmunity in early skin lesions related to SLE. However, the relevance of intrarenal type I interferon expression has not been shown in lupus nephritis. From transcriptome array datasets, median-centered log mRNA expression levels of IFNα (, , , , , , , , , , , , and ), IFNω (), and IFNβ () in lupus nephritis were extracted specifically from microdissected tubulointerstitial ( = 32) and glomerular compartments ( = 32). We found an association between proteinuria and tubulointerstitial expression of type I interferon ( = 0.0142), while all others were not significantly associated. By contrast, no such correlation was observed between proteinuria and any type I interferon expression in the glomerular compartment in lupus nephritis. Interestingly, there was no difference between female and male patients ( = 0.8237) and no association between type I interferon expression and kidney function or lupus nephritis progression. Finally, we identified distinct molecular signatures involved in transcriptional regulation (GLI protein-regulated transcription, IRF7 activation, and HSF1-dependent transactivation) and receptor signaling (BMP signaling and GPCR ligand binding) in association with tubulointerstitial expression of type I interferon in the kidney. In summary, this transcriptome array-based approach links proteinuria to the tubulointerstitial expression of type I interferon in lupus nephritis. Because type I interferon receptor subunit I antagonism has recently been investigated in active SLE, the current study further emphasizes the role of type I interferons in lupus nephritis and might also be of relevance for mechanistic studies. - Source: PubMed
Publication date: 2023/06/25
Korsten PeterTampe Björn - Uveitis is considered the most frequent extra-articular manifestation of Ankylosing Spondylitis (AS). Genetic factors play an important role in the pathogenesis of AS with uveitis. In this study, we investigated susceptibility genes of AS concomitant with uveitis. - Source: PubMed
Publication date: 2020/09/29
Liu JingjingLi HaiboLan TingWang Weina - Interferon (IFN) signaling has been suggested to play an important role in colorectal carcinogenesis. Our study aimed to examine potentially functional genetic variants in interferon regulatory factor 3 (IRF3), IRF5, IRF7, type I and type II IFN and their receptor genes with respect to colorectal cancer (CRC) risk and clinical outcome. Altogether 74 single nucleotide polymorphisms (SNPs) were covered by the 34 SNPs genotyped in a hospital-based case-control study of 1327 CRC cases and 758 healthy controls from the Czech Republic. We also analyzed these SNPs in relation to overall survival and event-free survival in a subgroup of 483 patients. Seven SNPs in IFNA1, IFNA13, IFNA21, IFNK, IFNAR1 and IFNGR1 were associated with CRC risk. After multiple testing correction, the associations with the SNPs rs2856968 (IFNAR1) and rs2234711 (IFNGR1) remained formally significant (P = 0.0015 and P<0.0001, respectively). Multivariable survival analyses showed that the SNP rs6475526 (IFNA7/IFNA14) was associated with overall survival of the patients (P = 0.041 and event-free survival among patients without distant metastasis at the time of diagnosis, P = 0.034). The hazard ratios (HRs) for rs6475526 remained statistically significant even after adjustment for age, gender, grade and stage (P = 0.029 and P = 0.036, respectively), suggesting that rs6475526 is an independent prognostic marker for CRC. Our data suggest that genetic variation in the IFN signaling pathway genes may play a role in the etiology and survival of CRC and further studies are warranted. - Source: PubMed
Publication date: 2014/10/28
Lu ShunPardini BarbaraCheng BowangNaccarati AlessioHuhn StefanieVymetalkova VeronikaVodickova LudmilaBuchler ThomasHemminki KariVodicka PavelFörsti Asta