Imperial College London

ProfessorAbbasDehghan

Faculty of MedicineSchool of Public Health

Professor in Molecular Epidemiology
 
 
 
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Contact

 

+44 (0)20 7594 3347a.dehghan CV

 
 
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Location

 

Sir Michael Uren HubWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Temprano-Sagrera:2022:10.1111/jth.15698,
author = {Temprano-Sagrera, G and Sitlani, CM and Bone, WP and Martin-Bornez, M and Voight, BF and Morrison, AC and Damrauer, SM and de, Vries PS and Smith, NL and Sabater-Lleal, M},
doi = {10.1111/jth.15698},
journal = {J Thromb Haemost},
pages = {1331--1349},
title = {Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations.},
url = {http://dx.doi.org/10.1111/jth.15698},
volume = {20},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - BACKGROUND: Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. OBJECTIVES: To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. METHODS: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10-9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). RESULTS: Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. CONCLUSIONS: The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.
AU - Temprano-Sagrera,G
AU - Sitlani,CM
AU - Bone,WP
AU - Martin-Bornez,M
AU - Voight,BF
AU - Morrison,AC
AU - Damrauer,SM
AU - de,Vries PS
AU - Smith,NL
AU - Sabater-Lleal,M
DO - 10.1111/jth.15698
EP - 1349
PY - 2022///
SP - 1331
TI - Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations.
T2 - J Thromb Haemost
UR - http://dx.doi.org/10.1111/jth.15698
UR - https://www.ncbi.nlm.nih.gov/pubmed/35285134
VL - 20
ER -