The Protein C anticoagulant pathway regulates blood coagulation by preventing the inadequate formation of thrombi. It has two main plasma components: protein C and protein S. Individuals with protein C or protein S deficiency present a dramatically increased incidence of thromboembolic disorders. Here, we present the results of a genome-wide association study (GWAS) for protein C and protein S plasma levels in a set of extended pedigrees from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) Project. A total number of 397 individuals from 21 families were typed for 307,984 SNPs using the Infinium® 317 k Beadchip (Illumina). Protein C and protein S (free, functional and total) plasma levels were determined with biochemical assays for all participants. Association with phenotypes was investigated through variance component analysis. After correcting for multiple testing, two SNPs for protein C plasma levels (rs867186 and rs8119351) and another two for free protein S plasma levels (rs1413885 and rs1570868) remained significant on a genome-wide level, located in and around the PROCR and the DNAJC6 genomic regions respectively. No SNPs were significantly associated with functional or total protein S plasma levels, although rs1413885 from DNAJC6 showed suggestive association with the functional protein S phenotype, possibly indicating that this locus plays an important role in protein S metabolism. Our results provide evidence that PROCR and DNAJC6 might play a role in protein C and free protein S plasma levels in the population studied, warranting further investigation on the role of these loci in the etiology of venous thromboembolism and other thrombotic diseases.
Citation: Athanasiadis G, Buil A, Souto JC, Borrell M, López S, Martinez-Perez A, et al. (2011) A Genome-Wide Association Study of the Protein C Anticoagulant Pathway. PLoS ONE 6(12): e29168. https://doi.org/10.1371/journal.pone.0029168
Editor: Marie-Pierre Dubé, Universite de Montreal, Canada
Received: July 28, 2011; Accepted: November 22, 2011; Published: December 28, 2011
Copyright: © 2011 Athanasiadis et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was partially supported by grant 2 R01 HL070751-05 from the American National Institutes of Health; grants PI-08/0420, PI-08/0756 and RECAVA-RD06/0014 from the “Instituto de Salud Carlos III” of the Spanish “Ministerio de Ciencia e Innovación” (MICINN); and grants SAF2005/04738 and SAF2008/01859 (MICINN). JMS was supported by the “Programa d'Estabilització d'Investigadors de la Direcció d'Estrategia I Coordinació del Departament de Salut” (Generalitat de Catalunya), SL was supported by the programa “Sara Borell” from Fondo Investigación Sanitaria and GA by the “Subprograma Nacional de Contratación e Incorporación de Investigadores Juan de la Cierva” (MICINN). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
The protein C anticoagulant pathway is an important physiological mechanism that regulates blood coagulation. It prevents the inadequate formation of thrombi and has two main plasma components: protein C and protein S.
Protein C (PC) is a vitamin K-dependent serine protease, which acts as an anticoagulant by inactivating activated Factors V (FVa) and VIII (FVIIIa). PC is activated by the thrombin/thrombomodulin complex on the surface of endothelial cells, where it binds with endothelial PC receptor (EPCR) , . EPCR also circulates in a soluble form (sEPCR) with similar affinity to both PC and activated PC (APC). Moreover, sEPCR acts as an inhibitor of APC .
Protein S (PS) is also a vitamin K-dependent anticoagulant plasma protein. It has no enzymatic activity, but acts as a cofactor to activated PC in the inactivation of FVa and FVIIIa. Moreover, PS is a cofactor for tissue factor pathway inhibitor (TFPI) for inhibiting FXa . PS circulates either as a free molecule (fPS; ∼40% of the total PS) or as a complex with the C4b-binding protein (C4BP-PS; ∼60% of the total PS) . Until recently, it was thought that only fPS had cofactor activity; however, now there is growing evidence that the C4BP-PS complex participates directly in FVa and FVIIIa inactivation .
Individuals with PC or PS deficiency present a dramatically increased incidence of thromboembolic disorders . Many of the mutations that cause these deficiencies are located in and around the structural genes of PC and PS (PROC and PROS1 respectively) –. However, a high proportion of families with PC or PS deficiency have no mutations in these genes . Moreover, several polymorphisms in the promoter of the PROC gene account for a mere ∼6% of the quantitative variation of PC levels . These observations suggest that the genetic mechanisms underlying PC and PS plasma levels are still largely unknown and that more loci, other than the two structural genes, are involved in the variability of these traits.
A genome-wide linkage analysis using the data from the family-based GAIT Project was performed to find novel loci affecting PC and PS plasma levels , . The analysis showed that genotypic variation in the PROC and PROS1 genomic regions is not a primary determinant of the quantitative variation of PC and PS plasma levels. Rather, PC levels showed significant linkage with chromosomal region 16q23. This region contains a candidate gene, NQO1 coding for NAD(P)H:dehydrogenase quinone 1, involved in vitamin K metabolism . In addition, there was strong evidence of linkage between chromosomal region 1q32 and fPS plasma levels. Interestingly, this region contains the genes that code for the α and β chains of the C4b-binding protein (C4BPA and C4BPB) . Moreover, using a tagSNP approach, the Cardiovascular Health Study (CHS) reported that polymorphism rs867186 from the gene that codes for EPCR (PROCR) was associated with higher levels of circulating PC antigen and that polymorphism rs1878672 from the IL10 gene was associated with higher fPS levels .
More recently, a genome-wide association scan for loci affecting PC plasma levels in a large sample of patients and controls of European descent identified three novel loci (GCKR, EDEM2 and BAZ1B), together with two already known (PROC and PROCR) . In addition, a genome-wide linkage analysis reported that a quantitative trait locus in chromosomal region 20q11 (including genes FOXA2, THBD and PROCR) influences PC levels in one extended family from the GENES study , . A subsequent study revealed that PROCR haplotype 3 and a SNP from FOXA2 (rs1055080) were associated with PC levels in this family, but only PROCR haplotype 3 was associated also with plasma levels in healthy individuals .
The top (i.e., showing the most significant associations) SNPs from the five genes found in the aforementioned genome-wide association scan explained only a fraction (28.2%) of the variance in PC plasma levels . Since previous studies postulated that ∼50% of the phenotypic variation in PC plasma levels is caused by the additive effect of genes  the discovery of more loci is tenable. Bearing this in mind, we carried out the first GWAS that encompasses the two main components of the protein C anticoagulant pathway (PC and functional, free and total PS levels). The objective of this work was to search for SNPs that influence PC and PS plasma levels and potentially increase the risk of venous thrombosis. We were successful in identifying such loci.
The Institutional Review Board of the Hospital de la Santa Creu i Sant Pau approved all protocols used in the GAIT Project and participants gave their informed consent, in compliance with the Declaration of Helsinki.
The GAIT Project: a brief description
The GAIT Project included 397 individuals from 21 extended Spanish families (mean pedigree size = 19) –. Twelve of these families were selected on the basis of a proband with idiopathic thrombophilia, whereas the remaining nine families were selected randomly. Age ranged from <1 to 88 years (mean = 37.7) and male to female sex ratio was 0.85.
PC plasma concentrations were measured by a biochemical analyzer (CPA Coulter, Coulter Corp) using chromogenic methods from Chromogenix. Functional PS (funcPS) was assayed with the STA automated coagulometer (Boehringer Mannheim) and determined with a Diagnostica Stago kit. fPS and total protein S (free+C4b–bound) were assayed with an ELISA-based commercial kit (Diagnostica Stago). To reduce experimental error, each assay was performed twice and the average value was calculated for each participant. Intra- and inter-assay coefficients of variation were between 2% and 6%.
Genotypic determinations and data cleaning
A genome-wide set of 307,984 SNPs was typed in all of the participants using the Infinium® 317 k Beadchip on the Illumina platform (San Diego, CA, USA). Genotype imputation was performed with Merlin  to avoid missing values and all genotypes were checked for Mendelian inconsistencies. In addition, any SNP with call rate<95%, MAF<0.025 or failing to fit Hardy-Weinberg proportions taking into account multiple testing (p<5×10−7) was removed from the study. In total, 24,547 SNPs failed to pass the data cleaning criteria, leaving a set of 283,437 SNPs for further analysis.
Association with phenotypes was investigated through variance component analysis that takes into account the family relationships among individuals. The quantitative phenotype (y) was modeled as a linear function of the genetic effect of a SNP (snp), the polygenic effect (g) and a random environmental deviation (e):
The covariance among phenotypic values (Ω) was modeled using the kinship coefficient matrix (Φ) derived from the family structure:whereby and are the variances of the polygenic and environmental effects and I is the identity matrix.
The analysis was performed with the SOLAR v4.0 statistical package . Variance component methods present considerable advantages when combined with extended families for the localization of QTLs, as it is now clear that large complex pedigrees have substantially more power per sampled individual than smaller families do –. All plasma phenotypes (PC fPS, funcPS and total PS) were log-transformed and adjusted for age and sex. Measured genotype analysis was used for testing association, assuming an additive genetic model . Finally, the Benjamini – Hochberg (B-H) adjustment  was applied to the p-values using the p.adjust function in R and assuming a 10% false discovery rate.
PC, fPS, funcPS and total PS plasma levels in the GAIT sample have been comprehensively described elsewhere , . In brief, PC plasma levels ranged from 37% to 198% those of healthy donors, with a mean value of 118.3% (standard deviation = 19.5%) adjusted for age and gender. In addition, fPS plasma levels ranged from 54% to 166% those of healthy donors and the mean age-adjusted fPS value was 109.4% for men (standard deviation = 21.3%) and 89.2% for women (standard deviation = 18.0%). Finally, mean funcPS and total PS plasma levels were 96.5% (range: 30%–188%; standard deviation = 21.7%) and 101.5% (range: 60%–176%; standard deviation = 20.7%) those of healthy donors respectively.
Table 1 shows the top SNP associations for each of the four phenotypes (PC, funcPS, fPS and total PS plasma levels). In all plasma phenotypes, association statistics followed the expected χ2 distribution under the null hypothesis of no association (Figure 1). From the 283,437 SNPs that were tested, two SNPs for the PC plasma levels (rs867186 and rs8119351) and another two for the fPS plasma levels (rs1413885 and rs1570868) remained significant on a genome-wide level, after applying the B-H adjustment.
Each plot represents one of the four plasma phenotypes (PC, fPS, funcPS and total PS). The red lines (y = x) correspond to equal theoretical and experimental distributions.
Polymorphism rs867186 is located in the PROCR gene and is responsible for a non-synonymous substitution in the amino acid chain of EPCR (S219G), whereas polymorphism rs8119351 is intergenic, located at ∼10 Kbp upstream from rs867186, with no apparent function. Each copy of minor allele from rs867186 (G) and rs8119351 (A) seems to increase PC plasma levels by 0.845 and 0.812 standard deviations and to explain 10.27% and 9.56% of the variance in PC plasma levels respectively (Table 2). However, these observations are not independent as both SNPs belong to the same LD block (D′ = 0.99; r2 = 0.91; p = 6.74×10−15). On the other hand, both significant SNPs for the fPS plasma levels (rs1413885 and rs1570868) are intronic, located in the DNAJC6 gene, and have no known function. In this case, each copy of minor allele from rs1413885 (C) and rs1570868 (T) seems to increase fPS plasma levels by 0.428 and 0.415 standard deviations and to explain 6.24% and 7.53% of the variance in fPS plasma levels respectively (Table 2). Again, these observations are not completely independent as the two SNPs present significant LD (D′ = 0.78; r2 = 0.44; p = 1.36×10−14). It is also important to note that two more SNPs from the DNAJC6 genomic region (rs12086738 and rs2375699) also showed suggestive association with fPS plasma levels (Table 1).
Although none of the SNPs were significantly associated with funcPS or total PS plasma levels (Table 1), one of the significant SNPs for fPS (rs1413885) also ranked among the top hits for funcPS (p = 2.82×10−05), suggesting that DNAJC6 might be involved in the PS metabolism. Finally, it is also worth noting that four out of five top hits for total PS levels were from the same genomic region (PPP2R3A). Although none of these SNPs rose to genome-wide significance levels (p-values between 10−06 and 10−05) they deserve special attention.
The aim of this study was to shed more light on the genetic mechanisms underlying the protein C anticoagulant pathway through a GWAS of the plasma levels of PC, fPS, funcPS and total PS; these levels are strongly involved in the development of thromboembolic disorders.
We were able to detect associations between two tightly linked SNPs from the PROCR genomic region (coding for EPCR) and PC plasma levels, also found in previous studies , , , . In this respect, these particular results of ours stand as an independent replication from a family-based perspective. EPCR is an endothelial cell-specific transmembrane protein that is involved in the protein C anticoagulant pathway by enhancing the activation rate of PC , . Increased levels of sEPCR have been associated with an increased risk of thrombotic events , . From the two most significant SNPs we found in the PROCR gene, rs867186 is more likely to play a causative role in determining the PC plasma levels, as it is located in exon 4 of the PROCR gene and leads to an amino acid change (S219G). More importantly, previous studies have associated S219G with increased risk of venous thromboembolism , ; moreover, a haplotype including S219G has been associated with increased risk of venous thromboembolism in carriers of (i) Factor V Leiden ; (ii) the G20210A mutation in the prothrombin gene ; and (iii) other dysfunctional PC variants . It has been proposed that S219G either affects the binding properties of sEPCR or enhances its secretion from the endothelial surface leading to alterations of circulating PC .
In addition, we were able also to detect significant associations between two SNPs from a novel candidate gene (DNAJC6) and fPS plasma levels, as well as suggestive associations between another two SNPs from DNAJC6 and the same trait. Interestingly, the most significant SNP for fPS plasma levels (rs1413885) also showed suggestive association with funcPS, underpinning the involvement of DNAJC6 in different PS traits. The exact function of DNAJC6 is still unknown; according to the UniProt database (http://www.uniprot.org) the protein coded by DNAJC6 resembles a tyrosine-protein phosphatase auxilin, an enzyme promoting the uncoating of clathrin-coated vesicles, thus playing a possible role in endocytosis. Endocytosis itself, followed by partial proteolysis, is involved in coagulation, through the molecular modification of FV and FVIII: partially proteolyzed FV exhibits significant procoagulant activity and resistance to activated PC . Thus, a similar mechanism involving DNAJC6 and fPS is possible, although the validation of this hypothesis would require further investigation.
Even though we were successful in discovering a novel locus for fPS plasma levels (DNAJC6) and replicating previous data on PC plasma levels, we did not find any significant associations for funcPS and total PS plasma levels. An ad hoc query of the STRING database (http://string.embl.de) for pathways of possible biological relevance involving the top hits from each PS phenotype (as listed in Table 1) gave no evidence of protein–protein interactions.
In a previous linkage study based on the GAIT sample, we reported NQO1 as a candidate gene affecting variation in PC plasma levels . Further analysis showed that one intronic SNP (rs1437135) from NQO1 was significantly associated with PC plasma levels . Unfortunately, this SNP was not present in the Illumina chip that we used for our genome-wide association analysis, so no direct comparisons could be made. Nevertheless, another SNP from the NQO1 genomic region (rs1800566) was included in the Illumina chip. Although this SNP is in full LD with rs1437135, it did not show significant association with PC plasma levels on a genome-wide level (p = 0.061). Moreover, we have reported strong evidence of linkage between chromosomal region 1q32 and fPS plasma levels; interestingly, this region contains two genes of high biological relevance, C4BPA and C4BPB, coding for the principal binding protein of PS . However, our genome-wide association study found no association between these two genes and any of the PS phenotypes on a genome-wide level.
This is the first time we have evidence that the PROCR gene is associated with PC plasma levels in the GAIT sample, as the linkage study performed previously  did not identify any linkage between the PROCR genomic region and this phenotype [logarithm of the odds (LOD) score = 0.670]. In a similar manner, no linkage was previously found between the DNAJC6 genomic region and fPS plasma levels (LOD score = 0.089) . Several issues arise from this apparent lack of concordance between genome-wide association and genome-wide linkage studies from the GAIT Project. It is important to note that GAIT is one of the few projects that allow us to perform this comparison.
From the methodological point of view, linkage differs from association in that it is based on the joint transmission of a marker and a functional site from parent to offspring (i.e. co-segregation), rather than on correlation due to LD. In this context, the association approach has difficulty in detecting rare variants through LD with common SNP markers, but such variants can be found by linkage. Thus, an explanation for the failure to detect the same loci in our analysis might be that linkage signals in GAIT might be due to rare variants at those loci, whereas association might be due to more common variants. This observation does not rule out the presence of other variants at those loci with small effect on PC or PS levels and our study does not have enough power to detect such small effects. It is important to note that if we cannot detect the effect of the other QTLs because it is small, this emphasizes our results that PROCR and DNAJC6 are major determinants of PC and PS levels in the Spanish population.
Taken together, the linkage and association analyses we carried out in the context of the GAIT Project are a good example of how rare and common variants underlying the genetic architecture of complex traits, such as PC and PS plasma levels. In addition, it is important to emphasize that no single method or model for studying genetic architecture can be adopted universally. No single method can answer all or even some of the questions without being used in concert with additional approaches.
In summary, our work provides evidence that the PROCR and DNAJC6 loci are involved in the genetic determination of the PC and fPS plasma levels respectively. However, these observations should be further validated by means of functional experiments, especially for the fPS plasma levels, as the function of the DNAJC6 gene is still unknown.
The authors would like to thank Professor William H. Stone for his helpful advice and constructive discussion, as well as all the families who participated in the GAIT Project. Without them, this work would never have been accomplished.
Conceived and designed the experiments: JCS MB JF. Performed the experiments: MB ML. Analyzed the data: AB LA GA JMS SL AMP. Contributed reagents/materials/analysis tools: JCS JMS JF ML SL LA. Wrote the paper: GA JMS.
- 1. Walker FJ (1981) Regulation of activated protein C by protein S: the role of phospholipid in factor V inactivation. J Biol Chem 256: 11128–11131.FJ Walker1981Regulation of activated protein C by protein S: the role of phospholipid in factor V inactivation.J Biol Chem2561112811131
- 2. Walker FJ, Chavin SI, Fay PJ (1987) Inactivation of factor VIII by activated protein C and protein S. Arch Biochem Biophys 252: 322–328.FJ WalkerSI ChavinPJ Fay1987Inactivation of factor VIII by activated protein C and protein S.Arch Biochem Biophys252322328
- 3. Van de Wouwer M, Collen D, Conway EM (2004) Thrombomodulin-protein C-EPCR system: integrated to regulate coagulation and inflammation. Arterioscler Thromb Vasc Biol 24: 1374–1383.M. Van de WouwerD. CollenEM Conway2004Thrombomodulin-protein C-EPCR system: integrated to regulate coagulation and inflammation.Arterioscler Thromb Vasc Biol2413741383
- 4. Hackeng TM, Sere KM, Tans G, Rosing J (2006) Protein S stimulates inhibition of the tissue factor pathway by tissue factor pathway inhibitor. Proc Natl Acad Sci USA 103: 3106–3111.TM HackengKM SereG. TansJ. Rosing2006Protein S stimulates inhibition of the tissue factor pathway by tissue factor pathway inhibitor.Proc Natl Acad Sci USA10331063111
- 5. Dahlback B (2007) The tale of protein S and C4b–binding protein, a story of affection. Thromb Haemost 98: 90–96.B. Dahlback2007The tale of protein S and C4b–binding protein, a story of affection.Thromb Haemost989096
- 6. Maurissen LF, Thomassen MC, Nicolaes GA, Dahlbäck B, Tans G, et al. (2008) Re–evaluation of the role of the protein S–C4b binding protein complex in activated protein C–catalyzed factor Va–inactivation. Blood 111: 3034–3041.LF MaurissenMC ThomassenGA NicolaesB. DahlbäckG. Tans2008Re–evaluation of the role of the protein S–C4b binding protein complex in activated protein C–catalyzed factor Va–inactivation.Blood11130343041
- 7. Lane DA, Mannucci PM, Bauer KA, Bertina RM, Bochkov NP, et al. (1996) Inherited Thrombophilia: Part 1. Thromb Haemost 76: 651–662.DA LanePM MannucciKA BauerRM BertinaNP Bochkov1996Inherited Thrombophilia: Part 1.Thromb Haemost76651662
- 8. Gandrille S, Borgel D, Eschwege-Gufflet V, Aillaud M, Dreyfus M, et al. (1995) Identification of 15 different candidate casual point mutations and three polymorphisms in 19 patients with protein S deficiency using a scanning method for analysis of the protein S active gene. Blood 85: 130–138.S. GandrilleD. BorgelV. Eschwege-GuffletM. AillaudM. Dreyfus1995Identification of 15 different candidate casual point mutations and three polymorphisms in 19 patients with protein S deficiency using a scanning method for analysis of the protein S active gene.Blood85130138
- 9. Reitsma PH, Bernardi F, Doig RG, Gandrille S, Greengard JS, et al. (1995) Protein C deficiency: a database of mutations, 1995 update. On behalf of the Subcommittee on Plasma Coagulation Inhibitors of the Scientific and Standardization Committee of the ISTH. Thromb Haemost 73: 876–889.PH ReitsmaF. BernardiRG DoigS. GandrilleJS Greengard1995Protein C deficiency: a database of mutations, 1995 update. On behalf of the Subcommittee on Plasma Coagulation Inhibitors of the Scientific and Standardization Committee of the ISTH.Thromb Haemost73876889
- 10. Franco RF, Reitsma PH (2001) Genetic risk factors of venous thrombosis. Hum Genet 109: 369–384.RF FrancoPH Reitsma2001Genetic risk factors of venous thrombosis.Hum Genet109369384
- 11. Koeleman BP, Reitsma PH, Bertina RM (1997) Familial thrombophilia: a complex genetic disorder. Semin Hematol 34: 256–264.BP KoelemanPH ReitsmaRM Bertina1997Familial thrombophilia: a complex genetic disorder.Semin Hematol34256264
- 12. Spek CA, Koster T, Rosendaal FR, Bertina RM, Reitsma PH (1995) Genotypic variation in the promoter region of the protein C gene is associated with plasma protein C levels and thrombotic risk. Arterioscler Thromb Vasc Biol 15: 214–218.CA SpekT. KosterFR RosendaalRM BertinaPH Reitsma1995Genotypic variation in the promoter region of the protein C gene is associated with plasma protein C levels and thrombotic risk.Arterioscler Thromb Vasc Biol15214218
- 13. Buil A, Soria JM, Souto JC, Almasy L, Lathrop M, et al. (2004) Protein C levels are regulated by a quantitative trait locus on chromosome 16: results from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) Project. Arterioscler Thromb Vasc Biol 24: 1321–1325.A. BuilJM SoriaJC SoutoL. AlmasyM. Lathrop2004Protein C levels are regulated by a quantitative trait locus on chromosome 16: results from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) Project.Arterioscler Thromb Vasc Biol2413211325
- 14. Almasy L, Soria JM, Souto JC, Coll I, Bacq D, et al. (2003) A quantitative trait locus influencing free plasma protein S levels on human chromosome 1q: results from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) project. Arterioscler Thromb Vasc Biol 23: 508–511.L. AlmasyJM SoriaJC SoutoI. CollD. Bacq2003A quantitative trait locus influencing free plasma protein S levels on human chromosome 1q: results from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) project.Arterioscler Thromb Vasc Biol23508511
- 15. Reiner AP, Carty CL, Jenny NS, Nievergelt C, Cushman M, et al. (2008) PROC, PROCR and PROS1 polymorphisms, plasma anticoagulant phenotypes, and risk of cardiovascular disease and mortality in older adults: the Cardiovascular Health Study. J Thromb Haemost 6: 1625–1632.AP ReinerCL CartyNS JennyC. NievergeltM. Cushman2008PROC, PROCR and PROS1 polymorphisms, plasma anticoagulant phenotypes, and risk of cardiovascular disease and mortality in older adults: the Cardiovascular Health Study.J Thromb Haemost616251632
- 16. Tang W, Basu S, Kong X, Pankow JS, Aleksic N, et al. (2010) Genome–wide association study identifies novel loci for plasma levels of protein C: the ARIC study. Blood 116: 5032–5036.W. TangS. BasuX. KongJS PankowN. Aleksic2010Genome–wide association study identifies novel loci for plasma levels of protein C: the ARIC study.Blood11650325036
- 17. Wichers IM, Tanck MW, Meijers JC, Lisman T, Reitsma PH, et al. (2009) Assessment of coagulation and fibrinolysis in families with unexplained thrombophilia. Thromb Haemost 101: 465–470.IM WichersMW TanckJC MeijersT. LismanPH Reitsma2009Assessment of coagulation and fibrinolysis in families with unexplained thrombophilia.Thromb Haemost101465470
- 18. Tanck MW, Wichers IM, Meijers JC, Büller HR, Reitsma PH, et al. (2011) Quantitative trait locus for protein C in a family with thrombophilia. Thromb Haemost 105: 199–201.MW TanckIM WichersJC MeijersHR BüllerPH Reitsma2011Quantitative trait locus for protein C in a family with thrombophilia.Thromb Haemost105199201
- 19. Pintao MC, Roshani S, de Visser MC, Tieken C, Tanck MW, et al. (2011) High levels of protein C are determined by PROCR haplotype 3. J Thromb Haemost 9: 969–976.MC PintaoS. RoshaniMC de VisserC. TiekenMW Tanck2011High levels of protein C are determined by PROCR haplotype 3.J Thromb Haemost9969976
- 20. Souto JC, Almasy L, Borrell M, Garí M, Martínez E, et al. (2000) Genetic determinants of hemostasis phenotypes in Spanish families. Circulation 101: 1546–1551.JC SoutoL. AlmasyM. BorrellM. GaríE. Martínez2000Genetic determinants of hemostasis phenotypes in Spanish families.Circulation10115461551
- 21. Souto JC, Almasy L, Borrell M, Blanco-Vaca F, Mateo J, et al. (2000) Genetic susceptibility to thrombosis and its relationship to physiological risk factors: the GAIT study Genetic Analysis of Idiopathic Thrombophilia. Am J Hum Genet 67: 1452–1459.JC SoutoL. AlmasyM. BorrellF. Blanco-VacaJ. Mateo2000Genetic susceptibility to thrombosis and its relationship to physiological risk factors: the GAIT study Genetic Analysis of Idiopathic Thrombophilia.Am J Hum Genet6714521459
- 22. Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2002) Merlin-rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 30: 97–101.GR AbecasisSS ChernyWO CooksonLR Cardon2002Merlin-rapid analysis of dense genetic maps using sparse gene flow trees.Nat Genet3097101
- 23. Almasy L, Blangero J (1998) Multipoint quantitative–trait linkage analysis in general pedigrees. Am J Hum Genet 62: 1198–1211.L. AlmasyJ. Blangero1998Multipoint quantitative–trait linkage analysis in general pedigrees.Am J Hum Genet6211981211
- 24. Blangero J, Williams JT, Almasy L (2000) Quantitative trait locus mapping using human pedigrees. Hum Biol 72: 35–62.J. BlangeroJT WilliamsL. Almasy2000Quantitative trait locus mapping using human pedigrees.Hum Biol723562
- 25. Blangero J, Williams JT, Almasy L (2001) Variance component methods for detecting complex trait loci. Adv Genet 42: 151–181.J. BlangeroJT WilliamsL. Almasy2001Variance component methods for detecting complex trait loci.Adv Genet42151181
- 26. Blangero J, Williams JT, Almasy L (2003) Novel family-based approaches to genetic risk in thrombosis. J Thromb Haemost 1: 1391–1397.J. BlangeroJT WilliamsL. Almasy2003Novel family-based approaches to genetic risk in thrombosis.J Thromb Haemost113911397
- 27. Boerwinkle E, Chakraborty R, Sing CF (1986) The use of measured genotype information in the analysis of quantitative phenotypes in man. I. Models and analytical methods. Ann Hum Genet 50: 181–194.E. BoerwinkleR. ChakrabortyCF Sing1986The use of measured genotype information in the analysis of quantitative phenotypes in man. I. Models and analytical methods.Ann Hum Genet50181194
- 28. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Statist Soc B 57: 289–300.Y. BenjaminiY. Hochberg1995Controlling the false discovery rate: a practical and powerful approach to multiple testing.J Roy Statist Soc B57289300
- 29. Laszik Z, Mitro A, Taylor FB Jr, Ferrell G, Esmon CT (1997) Human protein C receptor is present primarily on endothelium of large blood vessels: implications for the control of the protein C pathway. Circulation 96: 3633–3640.Z. LaszikA. MitroFB Taylor JrG. FerrellCT Esmon1997Human protein C receptor is present primarily on endothelium of large blood vessels: implications for the control of the protein C pathway.Circulation9636333640
- 30. Stearns-Kurosawa DJ, Kurosawa S, Mollica JS, Ferrell GL, Esmon CT (1996) The endothelial cell protein C receptor augments protein C activation by the thrombin-thrombomodulin complex. Proc Natl Acad Sci U S A 93: 10212–10216.DJ Stearns-KurosawaS. KurosawaJS MollicaGL FerrellCT Esmon1996The endothelial cell protein C receptor augments protein C activation by the thrombin-thrombomodulin complex.Proc Natl Acad Sci U S A931021210216
- 31. Uitte de Willige S, Van Marion V, Rosendaal FR, Vos HL, de Visser MC, et al. (2004) Haplotypes of the EPCR gene, plasma sEPCR levels and the risk of deep venous thrombosis. J Thromb Haemost 2: 1305–1310.S. Uitte de WilligeV. Van MarionFR RosendaalHL VosMC de Visser2004Haplotypes of the EPCR gene, plasma sEPCR levels and the risk of deep venous thrombosis.J Thromb Haemost213051310
- 32. Simioni P, Morboeuf O, Tognin G, Gavasso S, Tormene D, et al. (2006) Soluble endothelial PC receptor (sEPCR) levels and venous thromboembolism in carriers of two dysfunctional protein C variants. Thromb Res 117: 523–528.P. SimioniO. MorboeufG. TogninS. GavassoD. Tormene2006Soluble endothelial PC receptor (sEPCR) levels and venous thromboembolism in carriers of two dysfunctional protein C variants.Thromb Res117523528
- 33. Trégouët DA, Heath S, Saut N, Biron-Andreani C, Schved JF, et al. (2009) Common susceptibility alleles are unlikely to contribute as strongly as the FV and ABO loci to VTE risk: results from a GWAS approach. Blood 113: 5298–5303.DA TrégouëtS. HeathN. SautC. Biron-AndreaniJF Schved2009Common susceptibility alleles are unlikely to contribute as strongly as the FV and ABO loci to VTE risk: results from a GWAS approach.Blood11352985303
- 34. Galanaud JP, Cochery-Nouvellon E, Alonso S, Chauleur C, Mercier E, et al. (2010) Paternal endothelial PC receptor 219Gly variant as a mild and limited risk factor for deep vein thrombosis during pregnancy. J Thromb Haemost 8: 707–713.JP GalanaudE. Cochery-NouvellonS. AlonsoC. ChauleurE. Mercier2010Paternal endothelial PC receptor 219Gly variant as a mild and limited risk factor for deep vein thrombosis during pregnancy.J Thromb Haemost8707713
- 35. Medina P, Navarro S, Estellés A, Vayá A, Bertina RM, et al. (2005) Influence of the 4600A/G and 4678G/C polymorphisms in the endothelial PC receptor (EPCR) gene on the risk of venous thromboembolism in carriers of factor V Leiden. Thromb Haemost 94: 389–394.P. MedinaS. NavarroA. EstellésA. VayáRM Bertina2005Influence of the 4600A/G and 4678G/C polymorphisms in the endothelial PC receptor (EPCR) gene on the risk of venous thromboembolism in carriers of factor V Leiden.Thromb Haemost94389394
- 36. Navarro S, Medina P, Mira Y, Estellés A, Villa P, et al. (2008) Haplotypes of the EPCR gene, prothrombin levels, and the risk of venous thrombosis in carriers of the prothrombin G20210A mutation. Haematologica 93: 885–891.S. NavarroP. MedinaY. MiraA. EstellésP. Villa2008Haplotypes of the EPCR gene, prothrombin levels, and the risk of venous thrombosis in carriers of the prothrombin G20210A mutation.Haematologica93885891
- 37. Camire RM, Bos MH (2009) The molecular basis of factor V and VIII procofactor activation. J Thromb Haemost 7: 1951–1961.RM CamireMH Bos2009The molecular basis of factor V and VIII procofactor activation.J Thromb Haemost719511961