{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Zhang K"],"funding":["National Natural Science Foundation of China","National Natural Science Foundation of China (National Science Foundation of China)"],"pagination":["7831"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11380666"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(1)"],"pubmed_abstract":["Deep vein thrombosis (DVT) is a leading cause of morbidity and mortality after trauma. Here, we integrate plasma metabolomics and proteomics to evaluate the metabolic alterations and their function in up to 680 individuals with and without DVT after trauma (pt-DVT). We identify 28 metabolites and 2 clinical parameter clusters associated with pt-DVT. Then, we develop a panel of 9 metabolites (hexadecanedioic acid, pyruvic acid, L-Carnitine, serotonin, PE(P-18:1(11Z)/18:2(9Z,12Z)), 3-Hydroxycapric acid, 5,6-DHET, 3-Methoxybenzenepropanoic acid and pentanenitrile) that can predict pt-DVT with high performance, which can be verified in an independent cohort. Furthermore, the integration analysis of metabolomics and proteomics data indicates that the upregulation of glycolysis/gluconeogenesis-T"],"journal":["Nature communications"],"pubmed_title":["Integrated landscape of plasma metabolism and proteome of patients with post-traumatic deep vein thrombosis."],"pmcid":["PMC11380666"],"funding_grant_id":["32170616"],"pubmed_authors":["Tang SH","Zhang K","Li D","Guo Y","Yang N","Liang Y","Tian D","Wu H","Chen JB","Zou Y","Rong Y","Wang P","Dong SS","Huang W","Zhang Y","Yang TL","Liu C","Xue H"],"additional_accession":[]},"is_claimable":false,"name":"Integrated landscape of plasma metabolism and proteome of patients with post-traumatic deep vein thrombosis.","description":"Deep vein thrombosis (DVT) is a leading cause of morbidity and mortality after trauma. Here, we integrate plasma metabolomics and proteomics to evaluate the metabolic alterations and their function in up to 680 individuals with and without DVT after trauma (pt-DVT). We identify 28 metabolites and 2 clinical parameter clusters associated with pt-DVT. Then, we develop a panel of 9 metabolites (hexadecanedioic acid, pyruvic acid, L-Carnitine, serotonin, PE(P-18:1(11Z)/18:2(9Z,12Z)), 3-Hydroxycapric acid, 5,6-DHET, 3-Methoxybenzenepropanoic acid and pentanenitrile) that can predict pt-DVT with high performance, which can be verified in an independent cohort. Furthermore, the integration analysis of metabolomics and proteomics data indicates that the upregulation of glycolysis/gluconeogenesis-T","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Sep","modification":"2026-05-27T22:26:35.998Z","creation":"2025-02-19T02:33:57.762Z"},"accession":"S-EPMC11380666","cross_references":{"pubmed":["39244606"],"doi":["10.1038/s41467-024-52262-0"]}}