Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors

Abstract

Venous thromboembolism (VTE) is a complex disease with environmental and genetic determinants. We present new cross-ancestry meta-analyzed genome-wide association study (GWAS) results from 30 studies, with replication of novel loci and their characterization through in silico genomic interrogations. In our initial genetic discovery effort that included 55,330 participants with VTE (47,822 European, 6,320 African, and 1,188 Hispanic ancestry), we identified 48 novel associations of which 34 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. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein QTL Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 novel GWAS loci provided insights to biological pathways contributing to VTE, indicating that some loci may contribute to VTE through well-characterized coagulation pathways while others provide 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. In summary, these findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of antithrombosis treatments with reduced risk of bleeds.

Shared genetic etiology and causality between COVID-19 and venous thromboembolism: evidence from genome-wide cross trait analysis and bi-directional Mendelian randomization study

“…Figure 3 displays the Manhattan plots of these results. In line with previous studies, 3-6,15,16 we identified ABO gene and FUT2 gene, which contributed to both VTE and COVID-19. Notably, we identified seven novel genes which have not been reported yet, including LINC00970 , and six protein-coding genes ( TSPAN15, ADAMTS13, F5, DNAJB4, SLC39A8 and OBSCN) .…”

Elevated plasma Complement Factor H Regulating Protein 5 is associated with venous thromboembolism and COVID-19 severity

“…The rs10737681 we identify with genome wide association with CFHR5 levels maps between the CFHR4 and CFHR1 genes (Figure 4B). Of note, the CFHR2 locus has just been identified as a novel susceptibility locus for VTE in the recently published international effort on VTE genetics [21]. The lead SNP at this locus is rs143410348, which is in moderate LD with the rs10737681 (r 2 = 0.38 in FARIVE) that here we found associated with CFHR5 plasma levels.…”

“…Risk scores based on clinical risk factors and D-dimer levels have been developed for recurrence prediction [12][13][14][15][16][17][18], but none are routinely integrated into clinical practice. In addition to the genetic variants currently used in clinical assessment of hereditary thrombophilia (e.g., Factor V Leiden, prothrombin mutation) there are other more recently discovered common gene variants that contribute to VTE risk [19][20][21]. However, even when these are also incorporated into risk scores, they still lack sufficient precision for VTE prediction on an individual basis [22,23].…”

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

“…Second, even though 257 cardiovascular and metabolic proteins were included in the analysis, the study by no means examined all circulating proteins in relation to VTE, which indicated that other important VTE-related proteins might be overlooked. 58 Third, compared to mass spectrometry methods, the Olink protein immunoassay was not able to profile different protein isoforms or posttranslational modifications. However, this method with moderate-tohigh specificity and high throughput efficiently measured the absolute quantifications of proteins in a large sample.…”