Identification of unique venous thromboembolism-susceptibility variants in African-Americans

Summary

To identify novel single nucleotide polymorphisms (SNPs) associated with venous thromboembolism (VTE) in African-Americans (AAs), we performed a genome-wide association study (GWAS) of VTE in AAs using the Electronic Medical Records and Genomics (eMERGE) Network, comprised of seven sites each with DNA biobanks (total ~39,200 unique DNA samples) with genome-wide SNP data (imputed to 1000 Genomes Project cosmopolitan reference panel) and linked to electronic health records (EHRs). Using a validated EHR-driven phenotype extraction algorithm, we identified VTE cases and controls and tested for an association between each SNP and VTE using unconditional logistic regression, adjusted for age, sex, stroke, site-platform combination and sickle cell risk genotype. Among 393 AA VTE cases and 4,941 AA controls, three intragenic SNPs reached genome-wide significance: LEMD3 rs138916004 (OR=3.2; p=1.3E-08), LY86 rs3804476 (OR=1.8; p=2E-08) and LOC100130298 rs142143628 (OR=4.5; p=4.4E-08); all three SNPs validated using internal cross-validation, parametric bootstrap and meta-analysis methods. LEMD3 rs138916004 and LOC100130298 rs142143628 are only present in Africans (1000G data). LEMD3 showed a significant differential expression in both NCBI Gene Expression Omnibus (GEO) and the Mayo Clinic gene expression data, LOC100130298 showed a significant differential expression only in the GEO expression data, and LY86 showed a significant differential expression only in the Mayo expression data. LEMD3 encodes for an antagonist of TGF-β-induced cell proliferation arrest. LY86 encodes for MD-1 which down-regulates the pro-inflammatory response to lipopolysaccharide; LY86 variation was previously associated with VTE in white women; LOC100130298 is a non-coding RNA gene with unknown regulatory activity in gene expression and epigenetics.

Supplementary Material to this article is available online at www.thrombosis-online.com.

Keywords

Genetic variation - venous thromboembolism - African Americans - association analyses

• References

• 1 Heit JA, Cunningham JM, Petterson TM. et al. Genetic variation within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways as risk factors for venous thromboembolism. J Thromb Haemost 2011; 9: 1133-1142
• 2 Huang W, Goldberg RJ, Anderson FA. et al. Secular trends in occurrence of acute venous thromboembolism: the Worcester VTE study (1985 2009). Am J Med 2014; 127: 829-839 e5
• 3 Koton S, Schneider AL, Rosamond WD. et al. Stroke incidence and mortality trends in US communities, 1987 to 2011. J Am Med Assoc 2014; 312: 259-268
• 4 White RH, Keenan CR. Effects of race and ethnicity on the incidence of venous thromboembolism. Thromb Res 2009; 123 (04) Suppl S11-S17
• 5 Larsen TB, Sorensen HT, Skytthe A. et al. Major genetic susceptibility for venous thromboembolism in men: a study of Danish twins. Epidemiology 2003; 14: 328-332
• 6 Heit JA, Phelps MA, Ward SA. et al. Familial segregation of venous thromboembolism. J Thromb Haemost 2004; 2: 731-736
• 7 Zöller B, Ohlsson H, Sundquist J. et al. Familial risk of venous thromboembolism in first-, second- and third-degree relatives: a nationwide family study in Sweden. Thromb Haemost 2013; 109: 458-463
• 8 Germain M, Chasman DI, de Haan H. et al. Meta-analysis of 65,734 individuals identifies TSPAN15 and SLC44A2 as two susceptibility loci for venous thromboembolism. Amer J Hum Gen 2015; 96: 532-542
• 9 Dilley A, Austin H, Hooper WC. et al. Prevalence of the prothrombin 20210 G-to-A variant in blacks: infants, patients with venous thrombosis, patients with myocardial infarction, and control subjects. J Lab Clin Med 1998; 132: 452-455
• 10 Austin H, Key NS, Benson JM. et al. Sickle cell trait and the risk of venous thromboembolism among blacks. Blood 2007; 110: 908-912
• 11 Austin H, De Staercke C, Lally C. et al. New gene variants associated with venous thrombosis: a replication study in White and Black Americans. J Thromb Haemost 2011; 9: 489-495
• 12 Hernandez W, Gamazon ER, Smithberger E. et al. Novel genetic predictors of venous thromboembolism risk in African Americans. Blood 2016; 127: 1923-1929
• 13 Rees DC, Cox M, Clegg JB. World distribution of factor V Leiden. Lancet 1995; 346: 1133-1134
• 14 Dilley A, Austin H, Hooper WC. et al. Relation of three genetic traits to venous thrombosis in an African-American population. Am J Epidemiol 1998; 147: 30-35
• 15 Genome-Wide Studies in Biorepositories with Electronic Medical Record Data (U01) 2007 [cited; National Human Genome Research Institute RFA Announcement] Available from:. http: //grants.nih.gov/grants/guide/rfa-files/RFA-HG-07-005.html
• 16 McCarty CA, Chisholm RL, Chute CG. et al. The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC Med Genomics 2011; 4: 13
• 17 Gottesman O, Kuivaniemi H, Tromp G. et al. The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future. Genet Med 2013; 15: 761-771
• 18 Pathak J, Wang J, Kashyap S. et al. Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience. J Am Med Inform Assoc 2011; 18: 376-386
• 19 McPeek Hinz ER, Bastarache L, Denny JC. A natural language processing algorithm to define a venous thromboembolism phenotype. Association of Moving Image Archivists Conference; 2013 November 2013; Richmond, VA. 2013: p. 975-983
• 20 Turner S, Armstrong LL, Bradford Y. et al. Quality control procedures for genome-wide association studiesCurr Protoc Hum Genet 2011; Chapter 1: Unit1 19.
• 21 Zuvich RL, Armstrong LL, Bielinski SJ. et al. Pitfalls of merging GWAS data: lessons learned in the eMERGE network and quality control procedures to maintain high data quality. Genetic Epidemiol 2011; 35: 887-898
• 22 Denny JC, Crawford DC, Ritchie MD. et al. Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studies. Amer J Hum Gen 2011; 89: 529-542
• 23 Ritchie MD, Denny JC, Crawford DC. et al. Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record. Amer J Hum Gen 2010; 86: 560-572
• 24 Heit JA. Epidemiology of venous thromboembolism. Nat Rev Cardiol 2015; 12: 464-474
• 25 Howie B, Marchini J, Stephens M. Genotype imputation with thousands of genomes. G3 (Bethesda) 2011; 1: 457-470
• 26 Delaneau O, Zagury JF, Marchini J. Improved whole-chromosome phasing for disease and population genetic studies. Nat Methods 2013; 10: 5-6
• 27 Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 2009; 5: e1000529
• 28 Purcell S, Neale B, Todd-Brown K. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Amer J Hum Gen 2007; 81: 559-575
• 29 Patterson N, Price AL, Reich D. Population structure and eigenanalysis. PLoS Genet 2006; 2: e190
• 30 Price AL, Patterson NJ, Plenge RM. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 2006; 38: 904-909
• 31 Panagiotou OA, Ioannidis JP. What should the genome-wide significance threshold be? Empirical replication of borderline genetic associations. Intern J Epidemiol 2012; 41: 273-286
• 32 Buzkova, Lumley, Rice. Permutation and parametric bootstrap tests for gene-gene and gene-environment interactions. Ann Hum Gen. 2011; 75: 36-45
• 33 R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2013
• 34 Lewis DA, Suchindran S, Beckman MG. et al. Whole blood gene expression profiles distinguish clinical phenotypes of venous thromboembolism. Thromb Res 2015; 135: 659-665
• 35 Cunningham JM, Oberg AL, Borralho PM. et al. Evaluation of a new high-dimensional miRNA profiling platform. BMC Med Genomics 2009; 2: 57
• 36 Mahoney DW, Therneau TM, Anderson SK. et al. Quality assessment metrics for whole genome gene expression profiling of paraffin embedded samples. BMC Res Notes 2013; 6: 33
• 37 Gagnon-Bartsch JA, Speed TP. Using control genes to correct for unwanted variation in microarray data. Biostatistics 2012; 13: 539-552
• 38 Smyth GK. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 2004; 3: Article3
• 39 Lin F, Blake DL, Callebaut I. et al. MAN1, an inner nuclear membrane protein that shares the LEM domain with lamina-associated polypeptide 2 and emerin. J Biol Chem 2000; 275: 4840-4847
• 40 Lin F, Morrison JM, Wu W. et al. MAN1, an integral protein of the inner nuclear membrane, binds Smad2 and Smad3 and antagonizes transforming growth factor-beta signaling. Human Mol Gen 2005; 14: 437-445
• 41 Bourgeois B, Gilquin B, Tellier-Lebegue C. et al. Inhibition of TGF-beta signaling at the nuclear envelope: characterisation of interactions between MAN1, Smad2 and Smad3, and PPM1A. Sci Signal 2013; 6: ra49.
• 42 Horbelt D, Denkis A, Knaus P. A portrait of Transforming Growth Factor beta superfamily signalling: Background matters. Int J Biochem Cell Biol 2012; 44: 469-474
• 43 Ashfaque M, Sundquist K, Wang X. et al. Transforming growth factor (TGF)-levels and unprovoked recurrent venous thromboembolism. J Thromb Thrombolysis 2014; 38: 348-354
• 44 Tracz MJ, Juncos JP, Grande JP. et al. Induction of heme oxygenase-1 is a beneficial response in a murine model of venous thrombosis. Am J Pathol 2008; 173: 1882-1890
• 45 Mustafa S, Weltermann A, Fritsche R. et al. Genetic variation in heme oxygenase 1 (HMOX1) and the risk of recurrent venous thromboembolism. J Vasc Surg 2008; 47: 566-570
• 46 Kim HJ, Kim PK, Bae SM. et al. Transforming growth factor-beta-induced protein (TGFBIp/beta ig-h3) activates platelets and promotes thrombogenesis. Blood 2009; 114: 5206-5215
• 47 Smeeth L, Cook C, Thomas S. et al. Risk of deep vein thrombosis and pulmonary embolism after acute infection in a community setting. Lancet 2006; 367: 1075-1079
• 48 Reitsma P, Rosendaal F. Activation of innate immunity in patients with venous thrombosis: the Leiden Thrombophilia Study. J Thromb Haemost 2004; 2: 619-622
• 49 Heit JA, Armasu SM, Asmann YW. et al. A genome-wide association study of venous thromboembolism identifies risk variants in chromosomes 1q24.2 and 9q. J Thromb Haemost 2012; 10: 1521-1531
• 50 Heller R, Bogomolov M, Benjamini Y. Deciding whether follow-up studies have replicated findings in a preliminary large-scale omics study. Proc Nat Acad Sci USA 2014; 111: 16262-16267