CC BY-NC-ND 4.0 · Thromb Haemost 2019; 119(07): 1072-1083
DOI: 10.1055/s-0039-1687879
Coagulation and Fibrinolysis
Georg Thieme Verlag KG Stuttgart · New York

Hemostatic Genes Exhibit a High Degree of Allele-Specific Regulation in Liver

1   Department of Laboratory Medicine, Institute of Biomedicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
,
Lena Hansson
2   Novo Nordisk, Oxford, United Kingdom
3   Science For Life Laboratory (SciLifeLab), Stockholm, Sweden
,
Sofia Klasson
1   Department of Laboratory Medicine, Institute of Biomedicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
,
Marcela Davila Lopez
4   Bioinformatics Core Facility, University of Gothenburg, Gothenburg, Sweden
,
Christina Jern
1   Department of Laboratory Medicine, Institute of Biomedicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
,
Tara M. Stanne
1   Department of Laboratory Medicine, Institute of Biomedicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
› Author Affiliations
Funding This study was supported by the Swedish Heart and Lung Foundation (20160316), the Swedish Research Council (2018-02543), the Swedish Stroke Association, the Swedish state under the agreement between the Swedish government and the county councils (the ALF-agreement, ALFGBG-42), the Swedish Foundation for Strategic Research (RIF14–0081), the Rune and Ulla Amlövs Foundation for Neurologic Research, the John and Brit Wennerström Foundation for Neurologic Research, the Marcus Borgströms Foundation for Neurologic Research, and the Nilsson-Ehle Endowments.
Further Information

Publication History

17 January 2019

11 March 2019

Publication Date:
29 April 2019 (online)

Abstract

Objective Elucidating the genetic basis underlying hepatic hemostatic gene expression variability may contribute to unraveling genetic factors contributing to thrombotic or bleeding disorders. We aimed to identify novel cis-regulatory variants involved in regulating hemostatic genes by analyzing allele-specific expression (ASE) in human liver samples.

Study Design Biopsies of human liver tissue and blood were collected from adults undergoing liver surgery at the Sahlgrenska University Hospital (n = 20). Genomic deoxyribonucleic acid (gDNA) and total ribonucleic acid (RNA) were isolated. A targeted approach was used to enrich and sequence 35 hemostatic genes for single nucleotide polymorphism (SNP) analysis (gDNAseq) and construct individualized genomes for transcript alignment. The allelic ratio of transcripts from targeted RNAseq was determined via ASE analysis. Public expression quantitative trait loci (eQTL) and genome-wide association study (GWAS) data were used to assess novelty and importance of the ASE SNPs (and proxies, r 2 ≥ 0.8) for relevant traits/diseases.

Results Sixty percent of the genes studied showed allelic imbalance across 53 SNPs. Of these, 7 SNPs were previously validated in liver eQTL studies. For 32 with eQTLs in other cell/tissue types, this is the first time genotype-specific expression is demonstrated in liver, and for 14 ASE SNPs, this is the first ever reported genotype–expression association. A total of 29 ASE SNPs were previously associated with the respective plasma protein levels and 17 ASE SNPs to other relevant GWAS traits including venous thromboembolism, coronary artery disease, and stroke.

Conclusion Our study provides a comprehensive ASE analysis of hemostatic genes and insights into the regulation of hemostatic genes in human liver.

Authors' Contributions

T.M.S. and C.J. conceived the research design of the present study. C.J. was responsible for sample contribution, M.O.L. and S.K. isolated gDNA and RNA and M.O.L. prepared sequencing libraries. M.O.L., L.H., and M.D.L. performed statistical analyses. M.O.L., L.H., S.K., and M.D.L. drafted the figures. M.O.L., C.J., and T.M.S. interpreted the data. M.O.L. and T.M.S. drafted the manuscript. L.H., M.D.L., and C.J. intellectually reviewed the manuscript. All authors contributed to the last revision process and approved the version to be published.


 
  • References

  • 1 de Vries PS, Chasman DI, Sabater-Lleal M. , et al. A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration. Hum Mol Genet 2016; 25 (02) 358-370
  • 2 Smith NL, Chen MH, Dehghan A. , et al; Wellcome Trust Case Control Consortium. Novel associations of multiple genetic loci with plasma levels of factor VII, factor VIII, and von Willebrand factor: the CHARGE (Cohorts for Heart and Aging Research in Genome Epidemiology) Consortium. Circulation 2010; 121 (12) 1382-1392
  • 3 van Loon J, Dehghan A, Weihong T. , et al. Genome-wide association studies identify genetic loci for low von Willebrand factor levels. Eur J Hum Genet 2016; 24 (07) 1035-1040
  • 4 Huang J, Huffman JE, Yamakuchi M. , et al; Cohorts for Heart and Aging Research in Genome Epidemiology (CHARGE) Consortium Neurology Working Group; CARDIoGRAM Consortium; CHARGE Consortium Hemostatic Factor Working Group. Genome-wide association study for circulating tissue plasminogen activator levels and functional follow-up implicates endothelial STXBP5 and STX2. Arterioscler Thromb Vasc Biol 2014; 34 (05) 1093-1101
  • 5 Stanne TM, Olsson M, Lorentzen E. , et al. A genome-wide study of common and rare genetic variants associated with circulating thrombin activatable fibrinolysis inhibitor. Thromb Haemost 2018; 118 (02) 298-308
  • 6 Dehghan A, Bis JC, White CC. , et al. Genome-wide association study for incident myocardial infarction and coronary heart disease in prospective cohort studies: the CHARGE Consortium. PLoS One 2016; 11 (03) e0144997
  • 7 Klarin D, Emdin CA, Natarajan P, Conrad MF, Kathiresan S. ; INVENT Consortium. Genetic analysis of venous thromboembolism in UK Biobank identifies the ZFPM2 locus and implicates obesity as a causal risk factor. Circ Cardiovasc Genet 2017; 10 (02) 10
  • 8 Malik R, Chauhan G, Traylor M. , et al; AFGen Consortium; Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium; International Genomics of Blood Pressure (iGEN-BP) Consortium; INVENT Consortium; STARNET; BioBank Japan Cooperative Hospital Group; COMPASS Consortium; EPIC-CVD Consortium; EPIC-InterAct Consortium; International Stroke Genetics Consortium (ISGC); METASTROKE Consortium; Neurology Working Group of the CHARGE Consortium; NINDS Stroke Genetics Network (SiGN); UK Young Lacunar DNA Study; MEGASTROKE Consortium; MEGASTROKE Consortium. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet 2018; 50 (04) 524-537
  • 9 Falcone GJ, Woo D. Genetics of spontaneous intracerebral hemorrhage. Stroke 2017; 48 (12) 3420-3424
  • 10 Konkle BA, Johnsen JM, Wheeler M, Watson C, Skinner M, Pierce GF. ; My Life Our Future programme. Genotypes, phenotypes and whole genome sequence: approaches from the My Life Our Future haemophilia project. Haemophilia 2018; 24 (Suppl. 06) 87-94
  • 11 Consortium G. ; GTEx Consortium. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 2015; 348 (6235): 648-660
  • 12 Innocenti F, Cooper GM, Stanaway IB. , et al. Identification, replication, and functional fine-mapping of expression quantitative trait loci in primary human liver tissue. PLoS Genet 2011; 7 (05) e1002078
  • 13 Spielman RS, Bastone LA, Burdick JT, Morley M, Ewens WJ, Cheung VG. Common genetic variants account for differences in gene expression among ethnic groups. Nat Genet 2007; 39 (02) 226-231
  • 14 Pickrell JK, Marioni JC, Pai AA. , et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 2010; 464 (7289): 768-772
  • 15 Campino S, Forton J, Raj S. , et al. Validating discovered Cis-acting regulatory genetic variants: application of an allele specific expression approach to HapMap populations. PLoS One 2008; 3 (12) e4105
  • 16 Mercer TR, Clark MB, Crawford J. , et al. Targeted sequencing for gene discovery and quantification using RNA CaptureSeq. Nat Protoc 2014; 9 (05) 989-1009
  • 17 Dimas AS, Deutsch S, Stranger BE. , et al. Common regulatory variation impacts gene expression in a cell type-dependent manner. Science 2009; 325 (5945): 1246-1250
  • 18 Castel SE, Levy-Moonshine A, Mohammadi P, Banks E, Lappalainen T. Tools and best practices for data processing in allelic expression analysis. Genome Biol 2015; 16: 195
  • 19 Ward LD, Kellis M. HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease. Nucleic Acids Res 2016; 44 (D1): D877-D881
  • 20 Kundaje A, Meuleman W, Ernst J. , et al; Roadmap Epigenomics Consortium. Integrative analysis of 111 reference human epigenomes. Nature 2015; 518 (7539): 317-330
  • 21 Kumar S, Ambrosini G, Bucher P. SNP2TFBS - a database of regulatory SNPs affecting predicted transcription factor binding site affinity. Nucleic Acids Res 2017; 45 (D1): D139-D144
  • 22 Staley JR, Blackshaw J, Kamat MA. , et al. PhenoScanner: a database of human genotype-phenotype associations. Bioinformatics 2016; 32 (20) 3207-3209
  • 23 Battle A, Brown CD, Engelhardt BE, Montgomery SB. ; GTEx Consortium; Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group; Statistical Methods groups—Analysis Working Group; Enhancing GTEx (eGTEx) groups; NIH Common Fund; NIH/NCI; NIH/NHGRI; NIH/NIMH; NIH/NIDA; Biospecimen Collection Source Site—NDRI; Biospecimen Collection Source Site—RPCI; Biospecimen Core Resource—VARI; Brain Bank Repository—University of Miami Brain Endowment Bank; Leidos Biomedical—Project Management; ELSI Study; Genome Browser Data Integration &Visualization—EBI; Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz; Lead analysts; Laboratory, Data Analysis &Coordinating Center (LDACC); NIH program management; Biospecimen collection; Pathology; eQTL manuscript working group. Genetic effects on gene expression across human tissues. Nature 2017; 550 (7675): 204-213
  • 24 Eicher JD, Landowski C, Stackhouse B. , et al. GRASP v2.0: an update on the Genome-Wide Repository of Associations between SNPs and phenotypes. Nucleic Acids Res 2015; 43 (Database issue): D799-D804
  • 25 Franzén O, Ermel R, Cohain A. , et al. Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases. Science 2016; 353 (6301): 827-830
  • 26 Jood K, Ladenvall C, Rosengren A, Blomstrand C, Jern C. Family history in ischemic stroke before 70 years of age: the Sahlgrenska Academy Study on Ischemic Stroke. Stroke 2005; 36 (07) 1383-1387
  • 27 Jood K, Ladenvall P, Tjärnlund-Wolf A. , et al. Fibrinolytic gene polymorphism and ischemic stroke. Stroke 2005; 36 (10) 2077-2081
  • 28 Söderholm M, Almgren P, Jood K. , et al. Exome array analysis of ischaemic stroke: results from a southern Swedish study. Eur J Neurol 2016; 23 (12) 1722-1728
  • 29 Danik JS, Paré G, Chasman DI. , et al. Novel loci, including those related to Crohn disease, psoriasis, and inflammation, identified in a genome-wide association study of fibrinogen in 17 686 women: the Women's Genome Health Study. Circ Cardiovasc Genet 2009; 2 (02) 134-141
  • 30 Lovely RS, Yang Q, Massaro JM. , et al. Assessment of genetic determinants of the association of γ′ fibrinogen in relation to cardiovascular disease. Arterioscler Thromb Vasc Biol 2011; 31 (10) 2345-2352
  • 31 Wassel CL, Lange LA, Keating BJ. , et al. Association of genomic loci from a cardiovascular gene SNP array with fibrinogen levels in European Americans and African-Americans from six cohort studies: the Candidate Gene Association Resource (CARe). Blood 2011; 117 (01) 268-275
  • 32 Williams FM, Carter AM, Hysi PG. , et al; EuroCLOT Investigators; Wellcome Trust Case Control Consortium 2; MOnica Risk, Genetics, Archiving and Monograph; MetaStroke; International Stroke Genetics Consortium. Ischemic stroke is associated with the ABO locus: the EuroCLOT study. Ann Neurol 2013; 73 (01) 16-31
  • 33 Tang W, Teichert M, Chasman DI. , et al. A genome-wide association study for venous thromboembolism: the extended Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Genet Epidemiol 2013; 37 (05) 512-521
  • 34 van der Harst P, Verweij N. Identification of 64 novel genetic loci provides an expanded view on the genetic architecture of coronary artery disease. Circ Res 2018; 122 (03) 433-443
  • 35 Tang W, Schwienbacher C, Lopez LM. , et al. Genetic associations for activated partial thromboplastin time and prothrombin time, their gene expression profiles, and risk of coronary artery disease. Am J Hum Genet 2012; 91 (01) 152-162
  • 36 Thanassoulis G, Campbell CY, Owens DS. , et al; CHARGE Extracoronary Calcium Working Group. Genetic associations with valvular calcification and aortic stenosis. N Engl J Med 2013; 368 (06) 503-512
  • 37 Zhang ZY, Wang ZY, Dong NZ, Bai X, Zhang W, Ruan CG. A case of deficiency of plasma plasminogen activator inhibitor-1 related to Ala15Thr mutation in its signal peptide. Blood Coagul Fibrinolysis 2005; 16 (01) 79-84
  • 38 Morange PE, Saut N, Alessi MC. , et al. Association of plasminogen activator inhibitor (PAI)-1 (SERPINE1) SNPs with myocardial infarction, plasma PAI-1, and metabolic parameters: the HIFMECH study. Arterioscler Thromb Vasc Biol 2007; 27 (10) 2250-2257
  • 39 AlShaikh FS, Finan RR, Almawi AW, Mustafa FE, Almawi WY. Association of the R67X and W303X non-sense polymorphisms in the protein Z-dependent protease inhibitor gene with idiopathic recurrent miscarriage. Mol Hum Reprod 2012; 18 (03) 156-160
  • 40 Van de Water N, Tan T, Ashton F. , et al. Mutations within the protein Z-dependent protease inhibitor gene are associated with venous thromboembolic disease: a new form of thrombophilia. Br J Haematol 2004; 127 (02) 190-194
  • 41 Dentali F, Gianni M, Lussana F, Squizzato A, Cattaneo M, Ageno W. Polymorphisms of the Z protein protease inhibitor and risk of venous thromboembolism: a meta-analysis. Br J Haematol 2008; 143 (02) 284-287
  • 42 Kukurba KR, Zhang R, Li X. , et al. Allelic expression of deleterious protein-coding variants across human tissues. PLoS Genet 2014; 10 (05) e1004304
  • 43 Roldán V, Corral J, Marín F, Pineda J, Vicente V, González-Conejero R. Synergistic association between hypercholesterolemia and the C46T factor XII polymorphism for developing premature myocardial infarction. Thromb Haemost 2005; 94 (06) 1294-1299
  • 44 del Río-Espínola A, Fernández-Cadenas I, Giralt D. , et al; GRECOS Investigators. A predictive clinical-genetic model of tissue plasminogen activator response in acute ischemic stroke. Ann Neurol 2012; 72 (05) 716-729
  • 45 Santamaría A, Martínez-Rubio A, Mateo J, Tirado I, Soria JM, Fontcuberta J. Homozygosity of the T allele of the 46 C-->T polymorphism in the F12 gene is a risk factor for acute coronary artery disease in the Spanish population. Haematologica 2004; 89 (07) 878-879
  • 46 Santamaría A, Mateo J, Tirado I. , et al. Homozygosity of the T allele of the 46 C->T polymorphism in the F12 gene is a risk factor for ischemic stroke in the Spanish population. Stroke 2004; 35 (08) 1795-1799
  • 47 Cochery-Nouvellon E, Mercier E, Lissalde-Lavigne G. , et al. Homozygosity for the C46T polymorphism of the F12 gene is a risk factor for venous thrombosis during the first pregnancy. J Thromb Haemost 2007; 5 (04) 700-707
  • 48 Hardison RC, Oeltjen J, Miller W. Long human-mouse sequence alignments reveal novel regulatory elements: a reason to sequence the mouse genome. Genome Res 1997; 7 (10) 959-966
  • 49 Schalkwyk LC, Meaburn EL, Smith R. , et al. Allelic skewing of DNA methylation is widespread across the genome. Am J Hum Genet 2010; 86 (02) 196-212