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. 2022 Oct 18;146(16):1225-1242.
doi: 10.1161/CIRCULATIONAHA.122.059675. Epub 2022 Sep 26.

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors

Florian Thibord #  1   2 Derek Klarin #  3   4 Jennifer A Brody  5 Ming-Huei Chen  1   2 Michael G Levin  6 Daniel I Chasman  7   8 Ellen L Goode  9 Kristian Hveem  10 Maris Teder-Laving  11 Angel Martinez-Perez  12 Dylan Aïssi  13   14 Delphine Daian-Bacq  15   16 Kaoru Ito  17 Pradeep Natarajan  18   19   20 Pamela L Lutsey  21 Girish N Nadkarni  22   23   24 Paul S de Vries  25 Gabriel Cuellar-Partida  26 Brooke N Wolford  27 Jack W Pattee  28   29 Charles Kooperberg  30 Sigrid K Braekkan  31   32 Ruifang Li-GaoNoemie Saut  33 Corriene Sept  34 Marine Germain  13   14   16 Renae L Judy  35   36 Kerri L Wiggins  5 Darae Ko  2   37 Christopher J O'Donnell  18   38 Kent D Taylor  39 Franco Giulianini  7 Mariza De Andrade  9 Therese H Nøst  10 Anne Boland  15   16 Jean-Philippe Empana  40   41 Satoshi Koyama  17   19   20 Thomas Gilliland  18   19   20 Ron Do  22   23   42 Jennifer E Huffman  43 Xin Wang  26 Wei Zhou  44 Jose Manuel Soria  12 Juan Carlos Souto  12   45 Nathan Pankratz  46 Jeffery Haessler  30 Kristian Hindberg  31 Frits R Rosendaal  36 Constance Turman  34 Robert Olaso  15   16 Rachel L Kember  47 Traci M Bartz  48 Julie A Lynch  49 Susan R Heckbert  50 Sebastian M Armasu  9 Ben Brumpton  10 David M Smadja  51   52 Xavier Jouven  53   54 Issei Komuro  55 Katharine R Clapham  56   18   20 Ruth J F Loos  22 Cristen J Willer  27 Maria Sabater-Lleal  12   57 James S Pankow  21 Alexander P Reiner  30   50 Vania M Morelli  31   32 Paul M Ridker  7   8 Astrid van Hylckama Vlieg  36 Jean-François Deleuze  15   16   58 Peter Kraft  34 Daniel J Rader  6   59 Global Biobank Meta-Analysis Initiative; Estonian Biobank Research Team; 23andMe Research Team; Biobank Japan; CHARGE Hemostasis Working GroupKyung Min Lee  60 Bruce M Psaty  5   61   50 Anne Heidi Skogholt  10 Joseph Emmerich  62   63 Pierre Suchon  33   64 Stephen S Rich  65 Ha My T Vy  22   23 Weihong Tang  21 Rebecca D Jackson  66 John-Bjarne Hansen  31   32 Pierre-Emmanuel Morange  33   64 Christopher Kabrhel  67   68 David-Alexandre Trégouët #  13   14   16 Scott M Damrauer #  35   59   69 Andrew D Johnson #  1   2 Nicholas L Smith #  50   70   71
Affiliations

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors

Florian Thibord et al. Circulation. .

Abstract

Background: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources.

Methods: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations.

Results: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis.

Conclusions: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

Keywords: genetics; genome-wide association study; meta-analysis; venous thromboembolism; venous thrombosis.

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Conflict of interest statement

Conflict of Interest Disclosures

B.M.P. serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. P.M.R. has received investigator initiated research grant support for unrelated projects from NHLBI, Operation Warp Speed, Novartis, Kowa, Amarin, and Pfizer; and has served as a consultant on unrelated issues to Novo Nordisk, Flame, Agepha, Uppton, Novartis, Jansen, Health Outlook, Civi Biopharm, Alnylam, and SOCAR. P.N. reports investigator-initated grants from Amgen, Apple, AstraZeneca, Boston Scientific, and Novartis, personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Foresite Labs, Novartis, Roche / Genentech, is a co-founder of TenSixteen Bio, is a scientific advisory board member of Esperion Therapeutics, geneXwell, and TenSixteen Bio, and spousal employment at Vertex, all unrelated to the present work. D.C. has received research funding for unrelated projects from Pfizer. D.Ko initiated research grant from Boston Scientific, Consulting fee from Eagle Pharmaceutical, both unrelated to the current work. C.J.O. is employed by Novartis Institute of Biomedical Research. G.C-P. and X.W. are employed by and hold stock or stock options in 23andMe, Inc. The spouse of C.J.W. works at Regeneron Pharmaceuticals. K.R.C. reports fees from Tectonics Therapeutics. R.L-G. is contractor of Metabolon, Inc. R.D. reported receiving grants from AstraZeneca, grants and non-financial support from Goldfinch Bio, being a scientific co-founder, consultant and equity holder for Pensieve Health (pending), and being a consultant for Variant Bio, all not related to this work. D.Klarin is a scientific advisor and received consulting fees from Bitterroot Bio, Inc unrelated to the current research. S.M.D. receives research support from RenalytixAI and personal consulting fees from Calico Labs, outside the scope of the current research. S.M.D. is named as a co-inventor on a Government-owned US Patent application related to the use of genetic risk prediction for venous thromboembolic disease filed by the US Department of Veterans Affairs in accordance with Federal regulatory requirements. All other authors had nothing to disclose.

Figures

Figure 1:
Figure 1:. Analyses Workflow
Workflow of genetic analyses conducted for this study.
Figure 2:
Figure 2:. Genetic loci associated with VTE
This figure presents the 135 loci significantly associated with VTE identified across all 4 meta-analyses: the Discovery (in red), the overall meta-analysis (in green), the analysis restricted to individuals of European ancestry (in purple), African ancestry (in orange) and Hispanic ancestry (in blue). Novel loci are represented with circles and known loci with diamonds. Loci with replication evidence are indicated with a red ‘*’.
Figure 3:
Figure 3:. Genetic risk score analysis
Distribution of the GRS in VTE cases (in green) and controls (in purple) as a density plot (A) and a boxplot (B). (C) Presentation of the VTE risk as odds ratios and associated 95% confidence intervals (y-axis) for different percentiles ranges of the GRS score (x-axis) relative to the middle range (45–55%).
Figure 4:
Figure 4:. Significant associations of protein QTL Mendelian Randomization
23 proteins significantly associated with VTE, out of 1,216 plasma protein analyzed, using the combined VTE summary statistics.
Figure 5:
Figure 5:. VTE genetic loci shared with hemostatic factors and blood traits
(A) Number of VTE loci shared with each of the 10 hemostatic factors investigated. Loci with shared variants that had an opposite effect direction between the trait and VTE are indicated in orange, while those that had the same effect direction are presented in blue. Loci with multiple independent shared variants and conflictual effect directions are indicated in gray. (B) Same analysis with complete blood count traits: PLT (platelet count), MPV (mean platelet volume), RBC (red blood cell count), MCV (mean corpuscular volume), HCT (hematocrit), MCH (mean corpuscular hemoglobin), MCHC (MCH concentration), HGB (hemoglobin concentration), RDW (red cell distribution width), WBC (white blood cell count), MONO (monocyte count), NEU (neutrophil count), EOS (eosinophil count), BASO (basophil count), LYM (lymphocyte count).
Figure 6:
Figure 6:. PheWAS traits sharing at least 10 loci with VTE
This figure presents the pheWAS traits sharing at least 10 loci with VTE. Shape and color represent one of 5 categories: Complete Blood Count (CBC) traits, lipid traits, liver enzyme, height and weight traits, or other (if the trait did not fit in one of the aforementioned categories). The x-axis indicates the number of loci shared between VTE and the pheWAS trait, while the y-axis indicates the proportion of loci where the direction of effect was the same between the pheWAS trait and VTE. As a result, traits close to 100% have the same direction of effect than VTE at most shared loci, while traits close to 0% have an opposite direction than VTE at most shared loci.

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