ATP9A
- Known as:
- ATP9A
- Catalog number:
- 002263A
- Product Quantity:
- 250ul
- Category:
- -
- Supplier:
- ABM
- Gene target:
- ATP9A
Related genes to: ATP9A
- Gene:
- ATP9A NIH gene
- Name:
- ATPase phospholipid transporting 9A (putative)
- Previous symbol:
- -
- Synonyms:
- KIAA0611, ATPIIA
- Chromosome:
- 20q13.2
- Locus Type:
- gene with protein product
- Date approved:
- 2000-09-25
- Date modifiied:
- 2016-06-28
Related products to: ATP9A
Related articles to: ATP9A
- The ATP9A gene encodes a P4-type ATPase involved in phospholipid translocation, essential for vesicular trafficking and neuronal development. Pathogenic ATP9A variants cause autosomal recessive neurodevelopmental disorders characterized by intellectual disability and microcephaly, yet the impact of missense variants remains poorly understood. - Source: PubMed
Publication date: 2026/01/28
Yavas CuneydAbuaisha AsmaaNekay EmirGezdirici AlperYilmaz Halil IbrahimAkbulut EkremArican Pinar - Fusion transcripts have been reported as biomarkers for several diseases; however, a fusion gene has not been reported in ophthalmic disease. To the best of our knowledge, the discovery of fusion transcript in Behcet's disease (BD), a noninfectious uveitis, is reported for the first time. We generated complete transcript data for BD subtape and discovered fusion transcripts specific to BD patients. - Source: PubMed
Publication date: 2026/01/24
Haridas KrishnaRajamanikkam YuvashreeThippanna MeghaNagarajan HemavathyBiswas JyotirmaySinnakaruppan Mathavan - Osteoarthritis (OA) involves a complex pathogenesis encompassing inflammation, metabolic dysregulation, and aberrant intercellular communication. Despite their crucial role as mediators of intercellular signaling, exosomes remain largely underexplored in OA. This study aims to investigate exosome-related genes (ERGs) and their roles in OA pathogenesis. Four OA-related gene expression datasets retrieved from GEO were harmonized using the ComBat algorithm to mitigate batch effects. Differentially expressed genes (DEGs) were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA). ERGs were screened utilizing the ExoCarta and Vesiclepedia databases. Core ERGs were prioritized using LASSO, random forest, and XGBoost algorithms. Predictive models were constructed and subsequently evaluated using SHAP analysis to ascertain feature importance. Additionally, pathway enrichment, immune infiltration, and molecular subtype identification were performed, followed by validation of core ERG expression via RT-qPCR in clinical samples. Integration of the four GEO datasets yielded 231 DEGs significantly enriched within OA-associated pathways (e.g., inflammation, immune cell migration, extracellular matrix remodeling). From a pool of 79 candidate ERGs, 10 core ERGs (EPB41L2, ISLR, HLA-DRB1, HLA-DRA, PGLYRP1, PTEN, TKT, CTNNB1, THSD4, ATP9A) were identified. Random forest models achieved impressive AUCs of 0.991, 1.0, and 0.935 in the training, validation, and external validation sets, respectively, demonstrating substantial clinical net benefit. SHAP analysis underscored CTNNB1 and PGLYRP1 as pivotal predictors. Core ERGs were intricately linked to immune regulation (e.g., M1 macrophage infiltration) and metabolic perturbations (e.g., fatty acid metabolism). Distinct molecular subtypes of OA were delineated based on ERG profiles, thereby revealing the inherent disease heterogeneity. RT-qPCR further corroborated the differential expression of core ERGs in clinical samples. This study comprehensively integrates exosome-related genomic data with advanced machine learning techniques to identify and validate 10 core ERGs associated with OA, thereby elucidating their pivotal roles in immunometabolic regulation. These seminal findings illuminate the intricate molecular heterogeneity of OA, concurrently offering promising novel biomarkers and therapeutic targets for early diagnosis and precision treatment. - Source: PubMed
Publication date: 2025/12/21
You ChuanfeiDai FurenDai BingzhuWu WeijunFang LeJia WeiminHan XuSu ZhiLi Jian - Metabolic dysregulation has been implicated in major depressive disorder (MDD). - Source: PubMed
Publication date: 2025/12/12
Fu LiBaranova AnchaCao HongbaoZhang Fuquan - Among mammalian P4-ATPase flippases, only ATP9A and ATP9B do not require the auxiliary subunit CDC50 protein. Whilst its yeast homolog, Neo1, is essential for cell survival, little is known about mammalian ATP9A. We present cryo-EM structures of human monomeric ATP9A at a resolution reaching 2.2 Å, in the outward-facing E2P state. Two distinguishable conformations were obtained from a single sample, one with its outward gate open and the other in its closed form. Unlike canonical gating observed for most P-type ATPases, which is driven by the movement of transmembrane (TM) helices 1 and 2 linked to the A domain, outward gating in ATP9A is achieved by the movement of TM6-10 helices, likely initiated by the unwinding of TM6. As a result, the volume of the phospholipid binding cavity in the open state surpasses that of other flippases, which could allow binding of phospholipids with larger hydrophilic headgroups than that of phosphatidylserine. ATP9A shows an ATPase activity that is significantly increased by the addition of phospholipids that retain the overall negative charge, including phosphatidylserine, phosphatidylinositol, and its phosphorylated species, compared with other electroneutral phospholipids. The observation of spontaneous binding of phosphorylated species of phosphatidylinositol in molecular simulation reinforces this fact. Our data provide mechanistic rationales for ATP9A gating, achieved by the rearrangement of the second half of the TM helices. Since TM4-TM10 is anchored by the CDC50 protein subunit in other flippases, the here-observed outward gating mechanism is unique to P4B-type flippases, which function as a monomer. - Source: PubMed
Publication date: 2025/08/26
Abe KazuhiroMarimuthu ParthibanQian YuhengGopalasingam Chai CGerle ChristophShigematsu HidekiTanaka KotaroKhandelia Himanshu