Abstract

Previous genetic studies of venous thromboembolism (VTE) have been largely limited to common variants, leaving the genetic determinants relatively incomplete. We performed an exome-wide association study of VTE among 14,723 cases and 334,315 controls. Fourteen known and four novel genes (SRSF6, PHPT1, CGN, and MAP3K2) were identified through protein-coding variants, with broad replication in the FinnGen cohort. Most genes we discovered exhibited the potential to predict future VTE events in longitudinal analysis. Notably, we provide evidence for the additive contribution of rare coding variants to known genome-wide polygenic risk in shaping VTE risk. The identified genes were enriched in pathways affecting coagulation and platelet activation, along with liver-specific expression. The pleiotropic effects of these genes indicated the potential involvement of coagulation factors, blood cell traits, liver function, and immunometabolic processes in VTE pathogenesis. In conclusion, our study unveils the valuable contribution of protein-coding variants in VTE etiology and sheds new light on its risk stratification.

Here, the authors perform a large exome-wide study for venous thromboembolism and identify 18 potential risk genes, including 4 new genes, revealing a significant role of rare coding variants, and offering insights into genetic risk factors.

Details

Title
Genetic associations of protein-coding variants in venous thromboembolism
Author
He, Xiao-Yu 1 ; Wu, Bang-Sheng 1 ; Yang, Liu 1 ; Guo, Yu 1 ; Deng, Yue-Ting 1   VIAFID ORCID Logo  ; Li, Ze-Yu 2 ; Fei, Chen-Jie 1 ; Liu, Wei-Shi 1 ; Ge, Yi-Jun 1   VIAFID ORCID Logo  ; Kang, Jujiao 2   VIAFID ORCID Logo  ; Feng, Jianfeng 3   VIAFID ORCID Logo  ; Cheng, Wei 4   VIAFID ORCID Logo  ; Dong, Qiang 1   VIAFID ORCID Logo  ; Yu, Jin-Tai 1   VIAFID ORCID Logo 

1  Fudan University, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443) 
2  Fudan University, Institute of Science and Technology for Brain-Inspired Intelligence, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443) 
3  Fudan University, Institute of Science and Technology for Brain-Inspired Intelligence, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); University of Warwick, Department of Computer Science, Coventry, UK (GRID:grid.7372.1) (ISNI:0000 0000 8809 1613) 
4  Fudan University, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Fudan University, Institute of Science and Technology for Brain-Inspired Intelligence, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); University of Warwick, Department of Computer Science, Coventry, UK (GRID:grid.7372.1) (ISNI:0000 0000 8809 1613) 
Pages
2819
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41467-024-47178-8
ProQuest document ID
3028036389
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.