ArticleScientific reports2022
Large-scale genetic correlation scanning and causal association between deep vein thrombosis and human blood metabolites.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 4 citations in OpenAlex.
- Diagnosis of deep vein thrombosis from γ-butylbetaine and L-carnitine in plasma and urine based on untargeted and targeted metabolomics.Scientific reports · 2025Article
- Mendelian randomization analysis of blood metabolites and immune cell mediators in relation to GVHD and relapse.BMC medicine · 2025Article
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7 authors at 4 institutions in 1 country.
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Abstract
Deep vein thrombosis (DVT) refers to the abnormal coagulation of blood in a deep vein. Recently, some studies have found that metabolites are related to the occurrence of DVT and may serve as new markers for the diagnosis of DVT. In this study, we used the GWAS summary dataset of blood metabolites and DVT to perform a large-scale genetic correlation scan of DVT and blood metabolites to explore the correlation between blood metabolites and DVT. We used GWAS summary data of DVT from the UK Biobank (UK Biobank fields: 20002) and GWAS summary data of blood metabolites from a previously published study (including 529 metabolites in plasma or serum from 7824 adults from two European population studies) for genetic correlation analysis. Then, we conducted a causal study between the screened blood metabolites and DVT by Mendelian randomization (MR) analysis. In the first stage, genetic correlation analysis identified 9 blood metabolites that demonstrated a suggestive association with DVT. These metabolites included Valine (correlation coefficient = 0.2440, P value = 0.0430), Carnitine (correlation coefficient = 0.1574, P value = 0.0146), Hydroxytryptophan (correlation coefficient = 0.2376, P value = 0.0360), and 1-stearoylglycerophosphoethanolamine (correlation coefficient = - 0.3850, P value = 0.0258). Then, based on the IVW MR model, we analysed the causal relationship between the screened blood metabolites and DVT and found that there was a suggestive causal relationship between Hydroxytryptophan (exposure) and DVT (outcome) (β = - 0.0378, se = 0.0163, P = 0.0204). Our study identified a set of candidate blood metabolites that showed a suggestive association with DVT. We hope that our findings will provide new insights into the pathogenesis and diagnosis of DVT in the future.
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