Plasma protein and venous thromboembolism: prospective cohort and mendelian randomisation analyses

Author:

Yuan Shuai1ORCID,Titova Olga E.2,Zhang Ke34,Gou Wanglong34,Schillemans Tessa1,Natarajan Pradeep567,Chen Jie8,Li Xue8,Åkesson Agneta1,Bruzelius Maria910,Klarin Derek1112,Damrauer Scott M.1314,Larsson Susanna C.12

Affiliation:

1. Unit of Cardiovascular and Nutritional Epidemiology Institute of Environmental Medicine, Karolinska Institute Stockholm Sweden

2. Unit of Medical Epidemiology, Department of Surgical Sciences Uppsala University Uppsala Sweden

3. Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences Westlake University Hangzhou China

4. Westlake Intelligent Biomarker Discovery Lab Westlake Laboratory of Life Sciences and Biomedicine Hangzhou China

5. Program in Medical and Population Genetics and the Cardiovascular Disease Initiative Broad Institute of MIT and Harvard Cambridge Massachusetts USA

6. Department of Medicine Harvard Medical School Boston Massachusetts USA

7. Cardiovascular Research Center Massachusetts General Hospital Boston Massachusetts USA

8. 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

9. Department of Medicine, Solna Karolinska Institute Stockholm Sweden

10. Coagulation Unit, Department of Hematology Karolinska University Hospital Stockholm Sweden

11. VA Palo Alto Healthcare System Palo Alto California USA

12. Department of Surgery Stanford University School of Medicine Palo Alto California USA

13. Corporal Michael Crescenz Veterans Affairs Medical Center Philadelphia Pennsylvania USA

14. Department of Surgery, Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA

Abstract

SummaryWe conducted cohort and Mendelian randomisation (MR) analyses to examine the associations of circulating proteins with risk of venous thromboembolism (VTE) to provide evidence basis for disease prevention and drug development. Cohort analysis was performed in 11 803 participants without baseline VTE. Cox regression was used to estimate the associations between 257 proteins and VTE risk. A machine‐learning model was constructed to compare the importance of identified proteins and traditional risk factors. Genetic association data on VTE were obtained from a genome‐wide meta‐analysis (26 066 cases and 624 053 controls) and FinnGen (14 454 cases and 294 700 controls). The cohort analysis, including 353 incident VTE cases diagnosed during a 6.6‐year follow‐up, identified 21 proteins associated with VTE risk after false discovery rate correction. The machine‐learning model indicated that body mass index and von Willebrand factor (vWF) made the same as well as most of the contributions to the overall model prediction. MR analysis found that genetically predicted levels of vWF, SERPINE1 (plasminogen activator inhibitor 1, known as PAI‐1), EPHB4 (ephrin type‐B receptor 4), TYRO3 (tyrosine‐protein kinase receptor TYRO3), TNFRSF11A (tumour necrosis factor receptor superfamily member 11A), and BOC (brother of CDO) were causally associated with VTE risk.

Funder

Forskningsrådet om Hälsa, Arbetsliv och Välfärd

Hjärt-Lungfonden

Karolinska Institutet

Vetenskapsrådet

U.S. Department of Veterans Affairs

Publisher

Wiley

Subject

Hematology

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