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Using Zebrafish Models to Study Epitranscriptomic Regulation of CNS Functions.
J Neurochem
January 2025
Suzhou Municipal Key Laboratory of Neurobiology and Cell Signaling, School of Science, Xi'an Jiaotong-Liverpool University, Suzhou, China.
Epitranscriptomic regulation of cell functions involves multiple post-transcriptional chemical modifications of coding and non-coding RNA that are increasingly recognized in studying human brain disorders. Although rodent models are presently widely used in neuroepitranscriptomic research, the zebrafish (Danio rerio) has emerged as a useful and promising alternative model species. Mounting evidence supports the importance of RNA modifications in zebrafish CNS function, providing additional insights into epitranscriptomic mechanisms underlying a wide range of brain disorders.
View Article and Find Full Text PDFThe interplay of sex and genotype in disease associations: a comprehensive network analysis in the UK Biobank.
Hum Genomics
January 2025
Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Richards Building B304, 3700 Hamilton Walk, Philadelphia, PA, 19104, USA.
Background: Disease comorbidities and longer-term complications, arising from biologically related associations across phenotypes, can lead to increased risk of severe health outcomes. Given that many diseases exhibit sex-specific differences in their genetics, our objective was to determine whether genotype-by-sex (GxS) interactions similarly influence cross-phenotype associations. Through comparison of sex-stratified disease-disease networks (DDNs)-where nodes represent diseases and edges represent their relationships-we investigate sex differences in patterns of polygenicity and pleiotropy between diseases.
View Article and Find Full Text PDFTreatment of gouty lumbar spinal stenosis: a case report and bioinformatics analysis.
BMC Musculoskelet Disord
January 2025
General Hospital of Ningxia Medical University, Ningxia, 750004, China.
The case of Lumbar spinal stenosis (LSS) combined with tophi due to gout is rarely reported. In the course of our clinic work, we encountered a young male patient who was diagnosed with a history of gout for 5 years and was targeted as LSS combined with gouty tophi, and we would like to share this case. In addition, in order to further investigate the deep mechanism of LSS associated with gout, we obtained the intersecting genes of the two diseases based on a machine learning approach by obtaining the dataset GSE113212 related to LSS from the Gene Expression Omnibus (GEO) database, and the genes related to gout from the human gene database.
View Article and Find Full Text PDFA multi-tissue longitudinal proteomics study to evaluate the suitability of post-mortem samples for pathophysiological research.
Commun Biol
January 2025
Cardio-Thoracic Translational Medicine (CTTM) Lab, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Recent developments in mass spectrometry-based proteomics have established it as a robust tool for system-wide analyses essential for pathophysiological research. While post-mortem samples are a critical source for these studies, our understanding of how body decomposition influences the proteome remains limited. Here, we have revisited published data and conducted a clinically relevant time-course experiment in mice, revealing organ-specific proteome regulation after death, with only a fraction of these changes linked to protein autolysis.
View Article and Find Full Text PDFEvidence of DNA methylation heterogeneity and epipolymorphism in kidney cancer tissue samples.
Oncogene
January 2025
Early Cancer Institute, Cancer Research UK Cambridge Centre, Cambridge Biomedical Campus, Cambridge, UK.
Clear cell renal cell carcinoma (ccRCC) is characterised by significant genetic heterogeneity, which has diagnostic and prognostic implications. Very limited evidence is available regarding DNA methylation heterogeneity. We therefore generate sequence level DNA methylation data on 136 multi-region tumour and normal kidney tissue from 18 ccRCC patients, along with matched whole exome sequencing (85 samples) and gene expression (47 samples) data on a subset of samples.
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