Genome-wide association study-driven identification of thrombomodulin and factor V as the best biomarker combination for deep vein thrombosis
Abstract Deep vein thrombosis (DVT) is a clinically significant condition characterized by the formation of thrombi in deep venous structures, leading to high morbidity and potential mortality. Identifying reliable biomarkers for DVT risk prediction remains challenging due to the intricate genetic a...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BioMed Central
2025-05-01
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| Series: | Genomics & Informatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44342-025-00047-2 |
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| Summary: | Abstract Deep vein thrombosis (DVT) is a clinically significant condition characterized by the formation of thrombi in deep venous structures, leading to high morbidity and potential mortality. Identifying reliable biomarkers for DVT risk prediction remains challenging due to the intricate genetic and molecular mechanisms underlying the disease. This study aims to investigate the best biomarker for DVT. Our study utilized genome-wide association studies (GWAS) findings coupled with a functional annotation scoring system to identify and prioritize genetic markers with strong associations to DVT. Furthermore, gene expression levels were analyzed to determine the most promising genetic markers. Several databases were utilized, including the GWAS Catalog, HaploReg 4.2, WebGestalt, Enrichr, and the GTEx Portal. Through the comprehensive analysis, we found 5 potential biomarkers and highlighted thrombomodulin (THBD) and Factor V (F5) as the best blood-based biomarkers. THBD and F5 genes were selected based on their elevated expression levels in blood and the presence of eQTLs. Functionally, THBD modulates coagulation via protein C activation, while F5 is pivotal in thrombin formation and clot stabilization, underscoring their mechanistic relevance to DVT pathogenesis, and rendering them suitable for non-invasive clinical assessment. Our findings emphasize the potential of genetic biomarkers to transform DVT risk assessment and support advancements in precision medicine for thrombotic disorders. |
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| ISSN: | 2234-0742 |