KCNV2 Antibody (C-term) Blocking Peptides
- Known as:
- KCNV2 Antibody (C-terminus) Blocking Peptides
- Catalog number:
- BP13082b
- Product Quantity:
- 0.1 mg
- Category:
- -
- Supplier:
- Abgen
- Gene target:
- KCNV2 Antibody (C-term) Blocking Peptides
Ask about this productRelated genes to: KCNV2 Antibody (C-term) Blocking Peptides
- Gene:
- KCNV2 NIH gene
- Name:
- potassium voltage-gated channel modifier subfamily V member 2
- Previous symbol:
- -
- Synonyms:
- Kv8.2
- Chromosome:
- 9p24.2
- Locus Type:
- gene with protein product
- Date approved:
- 2002-11-20
- Date modifiied:
- 2016-02-04
Related products to: KCNV2 Antibody (C-term) Blocking Peptides
Related articles to: KCNV2 Antibody (C-term) Blocking Peptides
- Cone dystrophy with supernormal rod responses (CDSRR) is a rare autosomal recessive hereditary retinal dystrophy caused by biallelic variants. Accurate prevalence data remain limited because current estimates rely on clinically ascertained cases. This study aimed to estimate its population prevalence by integrating curated variant evidence and large-scale population genomics resources. The key methodological feature of this study is a multi-tiered pathogenicity framework combined with estimation of a biologically plausible prevalence range: Known pathogenic variants define conservative estimates, whereas probably pathogenic variants and strong variants of uncertain significance define broader estimates. Allele frequencies were analyzed in 807,162 individuals from the gnomAD database and 144,127 Russian genomes from GDB and EvogenDB. A Bayesian framework was applied to calculate disease prevalence from aggregated carrier frequencies across predefined variant tiers. Conservative estimates based on known pathogenic variants, were 1 in 343,926 globally and 1 in 1,911,347 in Russia. Including broader tiers increased estimates to 1 in 14,620 and 1 in 32,764, respectively. Compared to previous clinically ascertained prevalence of 1 in 865,000, these estimates define a wider biologically plausible prevalence range and are consistent with possible clinical underascertainment. This tier-based approach accounts for uncertainty in variant classification when estimating rare disease prevalence. - Source: PubMed
Publication date: 2026/06/30
Rozhkova Anastasiia VRutkovskaya Ekaterina AKadyshev Vitaly VEsibov Anton AAlsalloum AlmaqdadKuznetsova Ekaterina SKrupinova Julia AMityaeva Olga NShefer Kristina KBoiko Ernest VSagaydak Olesya VDoroshchuk Natalya AMakarova Maria VWoroncow MaryBogdanov Viktor PVolchkov Pavel Y - The electronegative electroretinogram (ERG)-in which the dark-adapted bright-flash b-wave amplitude falls below the a-wave (b: a ratio < 1.0)-localizes dysfunction to the inner retina or photoreceptor-bipolar synapse. In inherited retinal disease (IRD), this waveform has been associated with a restricted set of genetic etiologies, but the evidence has not been systematically synthesized. - Source: PubMed
Publication date: 2026/05/09
Taha IbrahimHuraibat KhalilAl-Labadi Liana - Photoreceptors are highly energy-demanding neurons, and disruption of photoreceptor signaling remodels retinal metabolism and contributes to degeneration, yet the pathways underlying these changes remain incompletely defined. Kv8.2 knockout (KO) mice, a model of KCNV2 retinopathy, exhibit impaired photoreceptor ion homeostasis and slow rod degeneration, providing an opportunity to investigate metabolic adaptation during progressive dysfunction. Untargeted metabolomic profiling was performed on retinas from wildtype (WT) and Kv8.2 KO mice at 1 and 13 months of age. Principal component analysis revealed distinct profiles for aged Kv8.2 KO retinas compared with aged WT and young groups, while young WT and KO retinas were metabolically similar. The major changes in aged Kv8.2 KO retinas compared to aged WT were reduced nucleobases and nucleosides while the amino acids homocysteine, methionine, and serine were elevated. These are signature metabolites in one-carbon metabolism, a metabolic hub influencing nucleotide metabolism, epigenic regulation, and anti-oxidant defense. Supervised modeling showed that these one-carbon-related changes emerge early and progress with age in Kv8.2 KO retinas. Together, these findings implicate altered one-carbon metabolism as a key mechanism in photoreceptor vulnerability and adaptation in slow retinal degeneration. - Source: PubMed
Kruth KarinaBaker Sheila A - encodes Kv8.2, an electrically silent voltage-gated potassium channel subunit that is expressed in photoreceptors. Disease-causing variants in cause a monogenic disorder which is classified clinically as cone dystrophy with supernormal rod response (CDSRR). Here, we generated -deficient human retinal organoids as a tool for gene therapy vector potency assessment. The organoids were derived from two separate sources: by generating IPSCs from patient blood and by gene editing of a control cell line. Eight gene therapy vectors were assessed in retinal organoids; Kv8.2 protein levels and its in situ interactions with potassium channel binding partners were quantitatively assessed. We show significant enhancements in vector potency and specificity by transgene codon optimisation and the use of the photoreceptor-specific rhodopsin kinase (RK) promoter, respectively. Single-cell RNA sequencing was performed in transduced retinal organoids to assess the performance of the AAV vectors at single-cell resolution. -deficient photoreceptors had an upregulation in genes associated with apoptosis, oxidative stress, and hypoxia pathways which were partially restored in AAV- transduced photoreceptors. These data show how human retinal organoids can be used to evaluate AAV gene therapy vector potency in vitro in a physiologically relevant model for the selection of lead therapeutic candidates and to help minimise the use of animals in preclinical development. - Source: PubMed
Publication date: 2025/12/31
Busson Sophie LNaeem ArifaFerrara SilviaSarcar ShilpitaAdefila-Ideozu ToyinWells SarahEl Alami SophiaBoot JamesSladen Paul EMichaelides MichelGeorgiadis AnastasiosLane Amelia - - Source: PubMed
Fatihoğlu Özlem UralBozkurt Oflaz AyşeÖzkan ÖzlemTaylan Şekeroğlu HandeSaatci Ali Osman