Ask about this productRelated genes to: KIF5C antibody
- Gene:
- KIF5C NIH gene
- Name:
- kinesin family member 5C
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 2q23.1-q23.2
- Locus Type:
- gene with protein product
- Date approved:
- 1998-08-24
- Date modifiied:
- 2018-02-13
Related products to: KIF5C antibody
Related articles to: KIF5C antibody
- Distinct, recurrent missense variants in KIF5C have previously been described in a small number of patients with cortical dysplasia and severe intellectual disability. We aimed to further characterize the phenotype associated with KIF5C variants, including truncating variants. - Source: PubMed
Publication date: 2026/03/11
Kulosik LuiseSchanze InaZacher PiaAl-Awam Bashayer SSrinivasan Varunvenkat MGowda Vykuntaraju KKrey IlonaFuchs AlexanderGoldenberg AliceSaugier-Veber PascaleHashemi-Gorji FarzadYassaee Vahid RezaZenker MartinSticht HeinrichJamra Rami AbouNeuser Sonja - Alzheimer's disease (AD) is a common neurodegenerative disorder in the elderly population, and early screening can effectively delay the progression of the disease. Mild cognitive impairment (MCI) occurs prior to the onset of AD; however, the accuracy of existing MCI-to-AD prediction methods remains relatively low. Additionally, small sample sizes and high feature dimensions often lead to model overfitting, highlighting the need for effective early screening approaches. To address the aforementioned issues, this study integrated non-paired multi-modal features-including clinical indicators from the ADNI database, blood biomarkers, brain region volume features extracted from MRI, and genetic biomarkers from the GEO database-and proposed a gender-corrected random matching strategy. The Random Forest algorithm was adopted to evaluate this strategy, analyze feature importance, and compare the performance of 9 machine learning algorithms based on the top 40 ranked features. The predictive performance of multi-modal data was superior to that of single-modal data, and the proposed strategy achieved favorable results in early AD screening. 16 specific genetic features (e.g., IFI27, EDF1, RAP2A, KIF5C, SERPINA3, FBXW7, IFITM1, ISG15, PSMB3, APOE4, KCNB1, PSPH, HMGN2, S100A13, IFIT3, and CALM1) and 6 brain region volume features ranked high in terms of importance. When validated using paired datasets from ADNI across the 9 algorithms, ensemble learning models demonstrated significantly stronger fitting capabilities. The non-paired multi-modal fusion approach not only expands the sample size but also enhances the generalization ability and robustness of the model. This provides a theoretical basis for the application of this strategy in the field of small-sample medical research. - Source: PubMed
Publication date: 2026/03/06
Zhang ZhihaoZhang RuixiaYang WenzhongLv KeWu MiaoXu Lianghui - Improving feed efficiency in cattle is increasingly important for both environmental and economic reasons. Although feed efficiency traits are under considerable genetic control, with an average moderate heritability estimate of 0.33, genetic evaluations are limited by the difficulties in measuring feed intake and the lack of records from most commercial herds. Most genetic evaluations rely on small numbers of records from research farms, resulting in under-represented genetic variation and pronounced sampling errors in heritability estimates. To enhance the discovery of genetic mechanisms underlying feed efficiency and to address measurement limitations and the under-representation of genetic variation, we used joint phenotypic and genotypic measurements from two distinct herds for GWAS and in-depth genomic analysis. By applying this approach, our exploratory analysis discovered fourteen significant markers with effects on residual feed intake (RFI) ranging from -1.41 to 1.44 kg/day. Quantitative trait loci (QTLs) enrichment analysis specifically pointed to traits that contributed to RFI, including dry matter intake (DMI), body weight (BW), and protein yield. Gene enrichment analysis, which was largely biased by a local cluster of vomeronasal receptor genes within a single ~ 500 kb region on BTA18, suggested three sets of genes of interest: a vomeronasal pheromone receptor cluster (VN1R1 and four additional response to pheromone genes on BTA18), genes linked to social and behavioral responses (EPC2 on BTA2; SYN3 on BTA5), and fat metabolism-related genes (KIF5C on BTA2; SV2B on BTA21). Of these candidate genes, likely functional amino acid (AA) variations were observed in the VN1R1 putative protein (314 AA) after screening a sample of 27 Israeli Holstein genomes. These functional variations included two truncation mutations that could encode 89 and 239 AA polypeptides. Consistent with these findings, whole-genome sequence data analysis of RFI-characterized Irish bulls identified a significant association between the 89 AA truncation and high RFI, further validating our results and indicating that although such variation was common, the presence of an intact VN1R1 receptor was associated with a beneficial effect on feed efficiency. Moreover, the 89 AA truncation was observed in diverse cattle breeds, including American, Israeli, Irish, and New Zealand Holstein. These findings are compatible with feed efficiency, a complex trait governed by neural (behavioral) and metabolic components. Further characterization of these factors would allow genetic selection to reduce feed costs and environmental footprints. - Source: PubMed
Publication date: 2026/02/05
Shirak AndreyYang LiuBhowmik NayanBen-Meir Yehoshav AShabtay ArielCohen-Zinder MiriBaldwin Vi Ransom LSeroussi EyalLiu George EGershoni Moran - Isocitrate dehydrogenase wild-type (IDH wild-type) gliomas represents the most aggressive subtype of diffuse gliomas, characterized by therapeutic resistance and dismal prognosis. Despite advances in molecular classification, reliable prognostic biomarkers for these tumors remain limited, particularly for recurrent disease. This study aims to identify gene expression signatures associated with survival outcomes in recurrent IDH wild-type gliomas, with the goal of improving patient stratification and potential therapeutic targeting. - Source: PubMed
Publication date: 2025/11/20
Liu YangHuse JasonKannan Kasthuri - KIF5C, a kinesin-1 motor protein critical for neuronal cargo transport, has been clinically associated with developmental delay and intellectual disability (DD/ID), although its pathogenic mechanisms are yet to be elucidated. Building on our prior identification of a de novo heterozygous KIF5C variant in a patient with DD/ID, a conditional knock-in mouse model was constructed to determine disease pathogenesis. The mutant mice exhibited core clinical phenotypes, including growth retardation, microcephaly, and deficits in social and spatial memory. Electrophysiological recordings revealed a decreased frequency of miniature excitatory postsynaptic currents, impaired long-term potentiation, and altered presynaptic vesicle release probability. Mechanistically, hippocampal neurons displayed decreased mature dendritic spines and impaired axonal mitochondrial transport, collectively contributing to diminished excitatory neurotransmission. Nonetheless, the overexpression of KIF5C in hippocampal CA1 neurons enhanced memory performance and excitatory synaptic transmission in the mutant mice. Overall, these findings establish that KIF5C dysfunction disrupts dendritic spine maturation at the postsynaptic terminal, axonal mitochondrial transport, and presynaptic vesicle release. Thus, a critical cellular mechanism underlying DD/ID pathogenesis has been identified in this research, opening novel therapeutic avenues. - Source: PubMed
Publication date: 2025/11/17
Wang XiaojunYe LuyuBanerjee SantasreeFeng JiabinLiao TailinWang ZiyiQin JialeLuo JianhongYang WeiXu JunyuLi Chen