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Browsing by Subject "Arteriovenous malformations"
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Item Identification and validation of a novel pathogenic variant in GDF2 (BMP9) responsible for hereditary hemorrhagic telangiectasia and pulmonary arteriovenous malformations(Wiley, 2022) Balachandar, Srimmitha; Graves, Tamara J.; Shimonty, Anika; Kerr, Katie; Kilner, Jill; Xiao, Sihao; Slade, Richard; Sroya, Manveer; Alikian, Mary; Curetean, Emanuel; Thomas, Ellen; McConnell, Vivienne P. M.; McKee, Shane; Boardman-Pretty, Freya; Devereau, Andrew; Fowler, Tom A.; Caulfield, Mark J.; Alton, Eric W.; Ferguson, Teena; Redhead, Julian; McKnight, Amy J.; Thomas, Geraldine A.; Genomics England Research Consortium; Aldred, Micheala A.; Shovlin, Claire L.; Medicine, School of MedicineHereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant multisystemic vascular dysplasia, characterized by arteriovenous malformations (AVMs), mucocutaneous telangiectasia and nosebleeds. HHT is caused by a heterozygous null allele in ACVRL1, ENG, or SMAD4, which encode proteins mediating bone morphogenetic protein (BMP) signaling. Several missense and stop-gain variants identified in GDF2 (encoding BMP9) have been reported to cause a vascular anomaly syndrome similar to HHT, however none of these patients met diagnostic criteria for HHT. HHT families from UK NHS Genomic Medicine Centres were recruited to the Genomics England 100,000 Genomes Project. Whole genome sequencing and tiering protocols identified a novel, heterozygous GDF2 sequence variant in all three affected members of one HHT family who had previously screened negative for ACVRL1, ENG, and SMAD4. All three had nosebleeds and typical HHT telangiectasia, and the proband also had severe pulmonary AVMs from childhood. In vitro studies showed the mutant construct expressed the proprotein but lacked active mature BMP9 dimer, suggesting the mutation disrupts correct cleavage of the protein. Plasma BMP9 levels in the patients were significantly lower than controls. In conclusion, we propose that this heterozygous GDF2 variant is a rare cause of HHT associated with pulmonary AVMs.Item Untargeted plasma metabolome identifies biomarkers in patients with extracranial arteriovenous malformations(Frontiers Media, 2023-09-01) Fan, Xueqiang; Gao, Xixi; Deng, Yisen; Ma, Bo; Liu, Jingwen; Zhang, Zhaohua; Zhang, Dingkai; Yang, Yuguang; Wang, Cheng; He, Bin; Nie, Qiangqiang; Ye, Zhidong; Liu, Peng; Wen, Jianyan; Pediatrics, School of MedicineObjective: This study aimed to investigate the plasma metabolic profile of patients with extracranial arteriovenous malformations (AVM). Method: Plasma samples were collected from 32 AVM patients and 30 healthy controls (HC). Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) was employed to analyze the metabolic profiles of both groups. Metabolic pathway enrichment analysis was performed through Kyoto Encyclopedia of Genes and Genomes (KEGG) database and MetaboAnalyst. Additionally, machine learning algorithms such as Least Absolute Shrinkage and Selection Operator (LASSO) and random forest (RF) were conducted to screen characteristic metabolites. The effectiveness of the serum biomarkers for AVM was evaluated using a receiver-operating characteristics (ROC) curve. Result: In total, 184 differential metabolites were screened in this study, with 110 metabolites in positive ion mode and 74 metabolites in negative mode. Lipids and lipid-like molecules were the predominant metabolites detected in both positive and negative ion modes. Several significant metabolic pathways were enriched in AVMs, including lipid metabolism, amino acid metabolism, carbohydrate metabolism, and protein translation. Through machine learning algorithms, nine metabolites were identify as characteristic metabolites, including hydroxy-proline, L-2-Amino-4-methylenepentanedioic acid, piperettine, 20-hydroxy-PGF2a, 2,2,4,4-tetramethyl-6-(1-oxobutyl)-1,3,5-cyclohexanetrione, DL-tryptophan, 9-oxoODE, alpha-Linolenic acid, and dihydrojasmonic acid. Conclusion: Patients with extracranial AVMs exhibited significantly altered metabolic patterns compared to healthy controls, which could be identified using plasma metabolomics. These findings suggest that metabolomic profiling can aid in the understanding of AVM pathophysiology and potentially inform clinical diagnosis and treatment.