Ask about this productRelated genes to: ZNF597 antibody
- Gene:
- ZNF597 NIH gene
- Name:
- zinc finger protein 597
- Previous symbol:
- -
- Synonyms:
- FLJ33071, HIT-4
- Chromosome:
- 16p13.3
- Locus Type:
- gene with protein product
- Date approved:
- 2004-03-01
- Date modifiied:
- 2019-04-23
Related products to: ZNF597 antibody
Related articles to: ZNF597 antibody
- Uniparental disomies (UPDs) are among the causes of imprinting disorders. Specific phenotypes of most causative UPDs have been described. Here, we describe the case of a 2-year-old female patient who presented a syndromic phenotype. Chromosomal microarray analysis revealed UPD of the whole chromosome 16. Microsatellite analysis demonstrated paternal origin of the UPD and its isodisomic pattern (UPiD (16) pat). Mosaic trisomy 16 was not detected using the FISH method. Whole-exome sequencing revealed no pathogenetic genetic variants sufficient to explain the syndromic phenotype nor unmasked pathogenic recessive genetic variants on chromosome 16. Whole-genome trio DNA sequencing revealed no additional candidate pathogenic genetic variants to those detected by whole-exome sequencing, including miRNAs and lncRNAs. Imprinting disorders at 6q24.2, 7p12.2, 7q32.2, 11p15.5, 14q32.2, 15q11.2, and 20q13.32, as well as multilocus imprinting disturbances (MLIDs), were excluded by Methylation-Specific Multiplex Ligation-Dependent Probe Amplification (MS-MLPA). At the same time, we detected abnormal hypermethylation of the transcription start site differentially methylated region (TSS-DMR), accompanied by hypomethylation of the neighbouring :3' DMR. Both DMRs were normally imprinted, and the DNA alterations in our patient with UPD (16) pat are opposite to those previously described for maternal uniparental disomy (UPD (16) mat). To date, several cases of UPD (16) pat have been reported. Our case report describes the syndromic phenotype of a patient with paternal uniparental disomy of chromosome 16 in contrast to the previously described patients with a normal phenotype or with abnormal phenotypes caused by acquired homozygosity of pathogenic variants at autosomal recessive genes located on this chromosome. Reporting such observations will help systematize data on the phenotypes of imprinting disorders on chromosome 16. - Source: PubMed
Publication date: 2025/09/02
Panchenko ElizavetaSemenova NataliaSereda OlgaGuseva DariaMarkova ZhannaShilova NadezhdaSimonova OlgaSmirnov AntonPustoshilov DmitryKhalilova ArinaUdalova VasilisaKanivets IlyaZaletaev DmitryStrelnikov VladimirKutsev Sergey - Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer's disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics. - Source: PubMed
Publication date: 2025/07/22
Bracher-Smith MatthewMelograna FedericoUlm BrittanyBellenguez CélineGrenier-Boley BenjaminDuroux DianeNevado Alejo JHolmans PeterTijms Betty MHulsman Marcde Rojas ItziarCampos-Martin Rafaelder Lee Sven vanCastillo AtahualpaKüçükali FahriPeters OliverSchneider AnjaDichgans MartinRujescu DanScherbaum NorbertDeckert JürgenRiedel-Heller SteffiHausner LucreziaMolina-Porcel LauraDüzel EmrahGrimmer TimoWiltfang JensHeilmann-Heimbach StefanieMoebus SusanneTegos ThomasScarmeas NikolaosDols-Icardo OriolMoreno FerminPérez-Tur JordiBullido María JPastor PauSánchez-Valle RaquelÁlvarez VictoriaBoada MercèGarcía-González PabloPuerta RaquelMir PabloReal Luis MPiñol-Ripoll GerardGarcía-Alberca Jose MaríaRodriguez-Rodriguez EloySoininen HilkkaHeikkinen Samide Mendonça AlexandreMehrabian ShimaTraykov LatchezarHort JakubVyhnalek MartinSandau NicolaiThomassen Jesper QvistPijnenburg Yolande A LHolstege Hennevan Swieten JohnRamakers InezVerhey FransScheltens PhilipGraff CarolinePapenberg GoranGiedraitis VilmantasWilliams JulieAmouyel PhilippeBoland AnneDeleuze Jean-FrançoisNicolas GaelDufouil CarolePasquier FlorenceHanon OlivierDebette StéphanieGrünblatt EdnaPopp JuliusGhidoni RobertaGalimberti DanielaArosio BeatriceMecocci PatriziaSolfrizzi VincenzoParnetti LucillaSquassina AlessioTremolizzo LucioBorroni BarbaraWagner MichaelNacmias BenedettaSpallazzi MarcoSeripa DavideRainero InnocenzoDaniele AntonioPiras FabrizioMasullo CarloRossi GiacominaJessen FrankKehoe PatrickMagda TsolakiSánchez-Juan PascualSleegers KristelIngelsson MartinHiltunen MikkoSims Rebeccavan der Flier WiesjeAndreassen Ole ARuiz AgustínRamirez Alfredo Frikke-Schmidt RuthAmin NajafRoshchupkin GennadyLambert Jean-CharlesVan Steen Kristelvan Duijn CorneliaEscott-Price Valentina - The reproduction process in domestic animals is one of the most important challenges of animal husbandry. Fertility is an important trait that contributes to herd profitability and can be improved by genomic information. One of the best ways to investigate the association between single nucleotide polymorphisms (SNPs) and phenotypic performance is the genome-wide association study (GWAS). The aim of our study was to identify the genomic regions affecting reproductive traits, interval between first and last insemination (IFL), days open (DO), days from calving to first service (DFS), number of services per conception (NSPC), age at first calving (AFC) and age at first insemination (AFI) using SNP chip data in Iranian Holstein cows. - Source: PubMed
Publication date: 2025/07/11
Maddahi NargesSadeghi MostafaMiraee Ashtiani Seyed RezaKholghi MunaJalil Sarghale Ali - Osteosarcoma is the most common malignant bone tumor that seriously threatens the lives of teenagers and children. Zinc finger (ZNF) protein genes encode the largest transcription factor family in the human genome. Aberrant expressions of ZNF protein genes widely occur in osteosarcoma, and these genes are therefore attractive biomarker candidates for prognosis prediction. In this study, we conducted a comprehensive analysis of ZNF protein genes in osteosarcoma and identified prognosis-related ZNF protein genes. Then, we constructed a prognostic signature based on seven prognosis-related ZNF protein genes and stratified patients into high- and low-risk groups. The seven genes included , , , , , , and . After validation of the prognostic signature in internal and external cohorts, we constructed a nomogram including clinical features such as sex and age and the relative risk score based on the risk signature. Functional enrichment analysis of the risk-related differentially expressed genes revealed that the prognostic signature was closely associated with immune-related biological processes and signaling pathways. Moreover, we found significant differences between the high- and low-risk groups for the scores of diverse immune cell subpopulations, including CD8 T cells, neutrophils, Th1 cells, and TILs. Regarding immune function, APC co-inhibition, HLA, inflammation promotion, para-inflammation, T-cell co-inhibition, and the type I IFN response were significantly different between the high- and low-risk groups. Of the seven ZNF protein genes, lower expressions of , , , , and were correlated with a high risk, while higher expressions of and were associated with a high risk. The Kaplan-Meier survival analysis suggested that lower expressions of , , and and the higher expression of were associated with worse overall survival in osteosarcoma. In conclusion, our ZNF protein gene-based signature was a novel and clinically useful prognostic biomarker for osteosarcoma patients. - Source: PubMed
Publication date: 2022/02/25
Sun XiangranZheng DiGuo Weichun - , encoding a zinc-finger protein, is the human-specific maternally expressed imprinted gene located on 16p13.3. The parent-of-origin expression of is regulated by the :TSS-DMR, of which only the paternal allele acquires methylation during postimplantation period. Overexpression of may contribute to some of the phenotypes associated with maternal uniparental disomy of chromosome 16 (UPD(16)mat), and some patients with UPD(16)mat presenting with Silver-Russell syndrome (SRS) phenotype have recently been reported. - Source: PubMed
Publication date: 2020/06/23
Yamazawa KazukiInoue TakanobuSakemi YoshihiroNakashima ToshinoriYamashita HironoriKhono KadukiFujita HidekiEnomoto KeisukeNakabayashi KazuhikoHata KenichiroNakashima MoekoMatsunaga TatsuoNakamura AkieMatsubara KeikoOgata TsutomuKagami Masayo