Proteomic insights into modifiable risk of venous thromboembolism and cardiovascular comorbidities.

Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden. Electronic address: shuai.yuan@ki.se. Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China. Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. Department of Gastroenterology, the Third Xiangya Hospital, Central South University, Changsha, China. Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden. Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK; Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden. Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden; Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. Electronic address: https://twitter.com/LarssonSC.

Journal of thrombosis and haemostasis : JTH. 2024;(3):738-748
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Abstract

BACKGROUND Venous thromboembolism (VTE) has been associated with several modifiable factors (MFs) and cardiovascular comorbidities. However, the mechanisms are largely unknown. OBJECTIVES We aimed to decipher proteomic pathways underlying the associations of VTE with MFs and cardiovascular comorbidities. METHODS A 2-stage network Mendelian randomization analysis was conducted to explore the associations between 15 MFs, 1151 blood proteins, and VTE using data from a genome-wide meta-analysis including 81 190 cases of VTE. We used protein data from 35 559 individuals as the discovery analysis, and from 2 independent studies including 10 708 and 54 219 participants as the replication analyses. Based on the identified proteins, we assessed the druggability and examined the cardiovascular pleiotropy. RESULTS The network Mendelian randomization analyses identified 10 MF-VTE, 86 MF-protein, and 34 protein-VTE associations. These associations were overall consistent in the replication analyses. Thirty-eight pathways with directionally consistent direct and indirect effects in the MF-protein-VTE pathway were identified. Low-density lipoprotein receptor-related protein 12 (LRP12: 34.3%-58.1%) and coagulation factor (F)XI (20.6%-39.6%) mediated most of the associations between 3 obesity indicators and VTE. Likewise, coagulation FXI mediated most of the smoking-VTE association (40%; 95% CI, 20%-60%) and insomnia-VTE association (27%; 95% CI, 5%-49%). Many VTE-associated proteins were highly druggable for thrombotic conditions. Five proteins (interleukin-6 receptor subunit alpha, LRP12, prothrombin, angiopoietin-1, and low-density lipoprotein receptor-related protein 4) were associated with VTE and its cardiovascular comorbidities. CONCLUSION This study suggests that coagulation FXI, a druggable target, is an important mediator of the associations of obesity, smoking, and insomnia with VTE risk.

Methodological quality

Publication Type : Meta-Analysis

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