Open Access

Genetic association of PROC variants with pulmonary embolism in Northern Chinese Han population

  • Zengliang Wang1,
  • Tianhe Wang2,
  • Jianyong Chang3,
  • Hua Li4,
  • Chengdong Wang5,
  • Yongyong Li6,
  • Xuhe Lang7,
  • Shimei Jing3,
  • Guoqing Zhang8 and
  • Yuting Wang3Email author
SpringerPlus20165:147

https://doi.org/10.1186/s40064-016-1801-9

Received: 13 August 2015

Accepted: 12 February 2016

Published: 24 February 2016

Abstract

To evaluate SNPs (single nucleotide polymorphism) in PROC (protein C gene) associated with pulmonary embolism (PE) susceptibility in North Chinese Han population. A case-control study design was used, and patients with PE and healthy participants were enrolled from the Emerging Department of the several hospitals in Weifang, Shandong, China. SNPs in PROC were genotyped using Mass ARRAY system. The allele frequency of rs199469469 was significantly different between PE patients and the control [OR (95 % CI) = 5.00 (1.66–15.12), P = 0.004], and the difference remained significantly after controlling for age and gender [OR (95 % CI) = 5.34 (1.47–19.39), P = 0.011). The G(del)G in the haplotype includes rs1799809|rs199469469|rs2069928 was of a significantly difference (P = 0.016) among PE patients and the controls, and remained significant (P = 0.015) after adjustment for age and sex. Our study reports that PROC SNPs (rs199469469) might be associated with PE susceptibility, with the G allele of rs199469469 serving as the protective factors for incidence of PE. These findings may contribute to the understanding and primary prevention of PE.

Keywords

Pulmonary embolism PROC (protein C gene) Single nucleotide polymorphism

Background

The major thrombotic medical disorders include venous thromboembolism (VTE), a multifactorial disorder consisting of deep venous thrombosis (DVT) and pulmonary embolism (PE). PE is one manifestation of venous thromboembolism (VTE) and is a frequent, recurrent and potentially fatal disease (Goldhaber and Bounameaux 2012; Goldhaber 2012). PE contributes to 5–10 % of deaths in hospitalized patients and VTE is a leading preventable cause of in-hospitalized death (Alikhan et al. 2004; Cohen et al. 2008). In USA, the incidence of all DVT/PE events is 300,000–600,000 cases per year (approximately 1–2 per 1000 persons per year) and the mortality rates of all DVT/PE events is 60,000–100,000 cases per year (Beckman et al. 2010). However, it is difficult to estimate accurate mortality rates of the PE, because of the presence of related diseases and the large proportion of undiagnosed PE (Laack and Goyal 2004).With the improvement of its diagnosis and the development of access to healthcare, VT in Asian populations is now thought to be rising (Roberts et al. 2009; Zakai and McClure 2011).

PE is caused by both genetic and environmental factors, among which genetic factors account for up to 60 % of risk (Souto et al. 2000). Studies have shown that single nucleotide polymorphisms (SNPs) in genes (protein C gene, protein S gene and antithrombin gene) may contribute to the susceptibility to PE (Roberts et al. 2009; Suehisa et al. 2001). Protein C (PROC, or PC) is a vitamin K-dependent serine protease zymogen, which is an inactive zymogen and can be stimulated by the thrombin–thrombomodulin (TM)—endothelial protein C receptor complex on endothelial cell surfaces. TM-bound thrombin cleaves the 158–169 activation peptide of PC and generates activated PC (APC) (Wildhagen et al 2011). APC is a key component of the anticoagulation system. APC inhibits the coagulation pathway by proteolysis of coagulation factor Va (the activated form of coagulation factor V) and coagulation factor VIIIa (Cramer and Gale 2011). The decreasing of APC level is an independent risk factor for both venous and arterial thrombosis (Soare and Popa 2010).

The human PROC is located on 2q13–q14 and comprises 9 exons. Up to date more than 200 mutations were identified in the PROC gene (D’Ursi et al 2007). Most studies were conducted in Western populations, and few in the Asian population (Gandrille et al. 1995; Miyata et al. 1998; Reitsma et al. 1991; Shen et al. 1997). These studies show that the mutation pattern of PROC is of significant ethnic differences, thus, some mutations (Arg230Cys, Arg178Trp, Gln132X, Val297Met and Pro168Leu) are common in the Caucasian population, while the others (Phe139Val/ rs199469470, Arg169Trp/ rs759316085, Val297Met, Met364Ile, and G8857del) are observed in the Japanese population. So far, few studies have been published to investigate the association between PROC variants with incidence of PE in mainland China.

In this study, we investigated the association between PROC variants and incidence of PE in a case-control study of North China Han population.

Results

In total, 101 cases of PE (61 males and 40 females; with median age 63 year-old, ranged 24–85), and 279 healthy controls (187 males and 92 females; with median age 65 year-old, ranged 48–87 year-old) were finally included in the study. Six polymorphisms in the PROC gene were genotyped through Mass ARRAY system, with success rate of 99.7, 96.8, 96.6, 92.1, 97.6 and 97.6% for rs1799809, rs199469469, rs2069928, rs7580688, rs2240817 and rs3771293, respectively (Fig. 1).
Fig. 1

Genotyping of six SNPs in PROC gene

All the six polymorphisms in cases and controls were both confirmed to Hardy–Weinberg equilibrium (Table 1). Table 1 showed that the “del” allele of rs199469469 (AAG/del) was of allele difference between the case and the control (OR = 5.00, 95 % CI 1.66–15.12, P = 0.004), and the association remained significant after adjustment for age and sex (OR = 5.34, 95 % CI 1.47–19.39, P = 0.011). For the other 5 SNPs, no statistical significances were observed (Table 1). rs199469469 was associated with PE in genotype and dominant model, but not in recessive model (Table 2).
Table 1

The allele frequency of SNPs in PROC in patients with PE and the controls

SNPs

Allele

Hardy–Weinberg equilibrium

Minor allele frequency (%)

Univariate analysis

Multivariate analysisa

The cases

The controls

Case

Control

OR (95% CI)

P

OR (95% CI)

P

GENO

P

GENO

P

rs1799809

A>G

5/25/71

0.170

9/61/198

0.140

0.173

0.147

1.212 (0.784–1.874)

0.424

1.131 (0.714–1.791)

0.599

rs199469469

AAG>del

0/9/91

1.000

0/5/263

1.000

0.045

0.009

5.004 (1.656–15.120)

0.004

5.339 (1.470–19.390)

0.011

rs2069928

G>T

11/45/45

1.000

28/117/121

1.000

0.332

0.325

1.030 (0.730–1.453)

0.861

1.102 (0.759–1.601)

0.609

rs7580688

A>G

16/54/29

0.310

38/119/94

1.000

0.434

0.388

1.209 (0.866–1.687)

0.267

1.270 (0.867–1.859)

0.219

rs2240817

A>G

4/28/69

0.510

6/83/171

0.400

0.178

0.183

0.970 (0.635–1.482)

0.915

1.187 (0.742–1.899)

0.476

rs3771293

A>G

4/37/60

0.770

10/79/171

0.840

0.223

0.190

1.219 (0.819–1.813)

0.351

1.155 (0.739–1.805)

0.528

SNPs single nucleotide polymorphisms, CI confidence interval, OR odds ratio

aAdjusted for sex and age

Table 2

the association between SNP rs199469469 with PE in three genetic models

Model

Case

Control

P

GENO

0/9/91

0/5/263

0.003

DOM

9/91

5/263

0.003

REC

0/100

0/268

1.000

The frequencies of Haplotype were evaluated using the Chi-square test, and Logistic regression analysis was performed to adjust for age and gender. The results showed that Haplotype G(del)G frequency (rs1799809|rs199469469|rs2069928) between the case and the control (P = 0.016) was of significant difference, and remained significant (P = 0.015) after adjustment for age and sex (Table 3).
Table 3

The haplotype distribution of PROC (rs1799809|rs199469469|rs2069928) in the cases and the controls

Haplotype

F-Affected

F-Control

Chi-square

P

P adj

G(AAG)T

0.027

0.030

0.049

0.824

0.922

A(AAG)T

0.310

0.296

0.130

0.718

0.630

G(Del)G

0.030

0.007

5.790

0.016

0.015

G(AAG)G

0.119

0.111

0.107

0.743

0.958

A(AAG)G

0.514

0.556

1.037

0.309

0.209

P adj adjust for age and gender

We also described the allele frequency data in the present study as well as 1000 genome project. Except for rs199469469, the allele frequency of other 5 SNPs are comparable among the present study and these in 1000 Genome of different ethnic groups (Table 4). This paper confirms data reported by Tang et al. (2012b) who identified that the rs199469469 in PROC was associated with both decreased protein C anticoagulation activity and an increased risk of thrombosis in Chinese subjects of South China, whereas no allele frequency of rs199469469 were reported in 1000 Genome or other populations. Therefore, the “del” allele of rs199469469 could be considered typical of Chinese people, and should be validated in large cohort of different ethnic groups.
Table 4

The minor allele frequency of selected SNPs in the present study and 1000 genome

SNPs

Minor allele

The present study

1000 genome

Case

Control

CHB

CHS

JPT

CEU

YRI

rs1799809

G

0.173

0.147

0.175

0.152

0.139

0.409

0.806

rs199469469

del

0.045

0.009

rs2069928

T

0.332

0.325

0.374

0.295

0.255

0.248

0.088

rs7580688

G

0.434

0.388

0.369

0.371

0.260

0.313

0.588

rs2240817

G

0.178

0.183

0.151

0.133

0.130

0.152

0.120

rs3771293

G

0.223

0.190

0.199

0.219

0.130

0.152

0.278

CHB Han Chinese Beijing; CHS Southern Han Chinese; JPT Japanese in Tokyo; YRI Yoruba in Ibadan, Nigeria; CEU Utah residences with Northern and Western Ancestry

Discussion

In this study, we investigated the association between PROC variants and the development of PE, and revealed that the rs199469469 (also designated as c.574_576del or p.Lys150del, located in exon 7 of the PROC gene) predispose people to PE. The case-control study showed that variant confers an approximately 5.00-fold increased risk of PE in the north Chinese population, and the results persist after adjustment for age and sex (OR = 5.34, P = 0.011).

PROC, with a single chain and synthesized by hepatocytes, is composed of a short activation peptide, a serine protease domain, carboxy-glutamic acid residue (Gla) domain, two epidermal growth factor (EGF)-like domains (Fisher et al. 1994; Perera et al. 2000). The deletion of lysine in PROC (rs19469469) can caused conformational changes in the protease domain (Chen et al. 2008), resulting in the elimination of a positive charge (Wildhagen et al. 2011). The most important is that the deletion is located at the ‘linking peptide (residues 137–157)’, which precedes the activation peptide and excised upon protein C activation. Residues Gly142–Leu155 are well conserved among species, and previously researches showed the region is important for anticoagulant activity (Mesters et al. 1993; Lu et al. 2013). Factor-V-Leiden mutation in the coding sequence of F5 (Dahlbäck et al. 1993; Koster et al. 1993; Bertina et al. 1994), prothrombin-G20210A mutation in the 3′ UTR of F2 and antithrombin-Cambridge-II mutation in SERPINC1 are common genetic risk factors for VT in whites (Poort et al. 1996; Corral et al. 2007). However, these polymorphisms are rare in Asians, including Chinese populations. Little is known about the genetic background of VT, and no common genetic risk factors have been identified in the Chinese population until recently. Tang et al (2012a) carried out the first study on the genetic background of PC deficiency in the Chinese population, and identified a common mutation in PROC (rs146922325, c.565C>T) in a family study (first-degree relatives bearing this variant had an 8.8-fold increased risk of venous thrombosis), which has been further verified by our case-control study (the mutant allele conferred a high predisposition to venous thrombosis (adjusted OR = 7.34, 95 % CI 3.61–14.94). Tang et al (2012b, 2013) further identified that rs199469469 in PROC was associated with both decreased protein C anticoagulant activity and an increased risk of VTE in Chinese (Hubei Province), with an odds ratio of 2.93, and 2.84 (Tang et al. 2012b, 2013). The studies by Tang et al (2012a, b, 2013) were performed in Southern China, and our study performed in Northern China confirmed that rs199469469 in PROC was associated with an increased risk of VTE in Chinese.

Conclusion

We firstly showed that the “del” allele of rs199469469 in PROC is associated with the increased risk of PE in a Northern Chinese Han population and the finding was consistent with that in Southern Chinese. Further epidemiologic studies are required to determine this association in larger populations, and functional studies are needed to determine the effect of this mutation contributing to susceptibility to PE. These studies will be a benefit to early predication or primary prevention of PE.

Methods

Participants

This study was approved by the ethics committee of Weifang People’s Hospital. A total of 101 unrelated patients diagnosed with PE in 2011 and 2012 were recruited from the Emerging Department of the hospitals in North China. The diagnosis of PE met the criteria recommended by the European Society of Cardiology (ESC) published in 2008 (Torbicki et al. 2008), and the patients with PE for patent foramen ovale were not screened. The inclusion criteria were: (1) Chinese Han population; (2) > or = 18 year-old. While the exclusion criteria were: (1) patients with acute liver disease or nephrotic syndrome; (2) recurrent venous thrombosis or pulmonary embolism; (3) patients with personal or family history of venous thromboembolism or other blood disease; (4) patients with the special history of drug use; (5) patients with chronic diseases such as hypertension; (6) patients with insertion of pacemaker.

The controls were 279 ethnic matched healthy individuals recruited in physical examination. All the patients and the control have given their written consents to participate in the study.

Selection of SNPs and genotyping

For the selection of candidate SNPs, we firstly downloaded all SNPs information in PROC region (including 5000 bp in the upstream and 5000 bp in the downstream) from Hapmap (Version 3, Release 2, Analysis Panel CHB), then we screened the SNPs with Minor Allele Frequency ≥0.10, and P ≥ 0.10 in Hardy–Weinberg Equilibrium test, finally we selected the tag SNPs (r2 ≥ 0.80) using Tagger function of Haploview (Barrett et al. 2005). Five SNPs near PROC (rs1799809, rs199469469, rs2069928, rs7580688, rs2240817) meet the criteria. rs199469469 was also added because it was associated with both decreased protein C anticoagulation activity and an increased risk of thrombosis in Chinese subjects of South China (Tang et al. 2012b).

Genomic DNA was extracted from whole-blood samples using QIAamp DNA Blood Mini Kit (Qiagen, German) according to the manual instructions. Genomic DNA samples were subsequently diluted to 25 ng/μl. SNPs were genotyped using Mass ARRAY system (Sequenom, Inc., SanDiego, CA). Sequenom Mass-ARRAY® Assay Design 3.0 software (Sequenom, Inc., San Diego, CA, USA) was used to design Multiplexed SNP Mass-EXTEND assays (Gabriel et al. 2009). SNP genotyping was performed using the standard protocol recommended by the manufacturer with a Sequenom Mass-ARRAY® RS1000 (Sequenom, Inc.). Sequenom Typer 4.0 software was used for data management and analyses (Thomas et al. 2007).

Statistical analysis

The Hardy–Weinberg equilibrium (HWE) of each SNP was evaluated using the Chi-square test. Differences between groups were analyzed by a Student’s t test or Mann–Whitney U test depending on the distribution of the laboratory data for continuous variables. The associations between PE and specific PROC genotypes were estimated by computing the odds ratios (OR) and 95 % confidence intervals (95 % CI) from the Chi-square test or Fisher’s exact test. Logistic regression analysis was performed to adjust for conventional risk factors including age and gender. Two-sided significance level was 0.05. The statistical analyses were performed by SPSS 13.0 (SPSS Inc., Chicago, IL, USA).

Abbreviations

SNP: 

single nucleotide polymorphism

PROC

protein C

PE: 

pulmonary embolism

VTE: 

venous thromboembolism

DVT: 

deep venous thrombosis

VTE: 

venous thromboembolism

TM: 

thrombin–thrombomodulin

APC: 

activated PC

Gla: 

glutamic acid residue

EGF: 

epidermal growth factor

ESC: 

European Society of Cardiology

HWE: 

the Hardy–Weinberg equilibrium

Declarations

Authors’ contributions

YW, GZ, ZW conceived the study and wrote the manuscript. ZW, TW, JC, HL, CW, YL, XL carried out the sample collection and the genotyping, ZW, SJ performed the statistical analysis. All authors read and approved the final manuscript.

Acknowledgements

We thank all the participants in the study. The study was supported by the Laboratory Project of Beijing Municipal Key Laboratory of Clinical Epidemiology (2014LCLB04).

Competing interests

The authors declare that they have no competing interests.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Department of Thorax, Anqiu People’s Hospital
(2)
Department of Brain EMG, Anqiu People’s Hospital
(3)
Department of Neurosurgery, Weifang People’s Hospital
(4)
Department of Neurology, Anqiu People’s Hospital
(5)
Key Laboratory of Weifang Brain Hospital, Weifang People’s Hospital
(6)
Department of Surgery, Anqiu Municipal Hospital
(7)
Department of Nephrology, Anqiu People’s Hospital
(8)
Department of Neurosurgery, People’s Hospital of Weifang High Tech Industry Development Zone

References

  1. Alikhan R, Peters F, Wilmott R, Cohen AT (2004) Fatal pulmonary embolism in hospitalised patients: a necropsy review. J Clin Pathol 57:1254–1257View ArticleGoogle Scholar
  2. Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21(2):263–265View ArticleGoogle Scholar
  3. Beckman MG, Hooper WC, Critchley SE, Ortel TL (2010) Venous thromboembolism: a public health concern. Am J Prev Med 38(Suppl):S495–S501View ArticleGoogle Scholar
  4. Bertina RM, Koeleman BP, Koster T, Rosendaal FR, Dirven RJ, de Ronde H, van der Velden PA, Reitsma PH (1994) Mutation in blood coagulation factor V associated with resistance to activated protein C. Nature 369:64–67View ArticleGoogle Scholar
  5. Chen QX, Wu SJ, Wang HH, Lv C, Cheng BL, Xie GH, Fang XM (2008) Protein C -1641A/-1654C haplotype is associated with organ dysfunction and the fatal outcome of severe sepsis in Chinese Han population. Hum Genet 123:281–287View ArticleGoogle Scholar
  6. Cohen AT, Tapson VF, Bergmann JF, Goldhaber SZ, Kakkar AK, Deslandes B, Huang W, Zayaruzny M, Emery L Jr, Anderson FA, ENDORSE Investigators (2008) Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): a multinational cross-sectional study. Lancet 371:387–394View ArticleGoogle Scholar
  7. Corral J, Hernandez-Espinosa D, Soria JM, Gonzalez-Conejero R, Ordonez A, Gonzalez-Porras JR, Perez-Ceballos E, Lecumberri R, Sanchez I, Roldan V, Mateo J, Minano A, Gonzalez M, Alberca I, Fontcuberta J, Vicente V (2007) Antithrombin Cambridge II (A384S): an underestimated genetic risk factor for venous thrombosis. Blood 109:4258–4263View ArticleGoogle Scholar
  8. Cramer TJ, Gale AJ (2011) Function of the activated protein C (APC) autolysis loop in activated FVIII inactivation. Br J Haematol 153:644–654View ArticleGoogle Scholar
  9. D’Ursi P, Marino F, Caprera A, Milanesi L, Faioni EM, Rovida E (2007) ProCMD: a database and 3D web resource for protein C mutants. BMC Bioinform 8(Suppl 1):S11View ArticleGoogle Scholar
  10. Dahlbäck B, Carlsson M, Svensson PJ (1993) Familial thrombophilia due to a previously unrecognized mechanism characterized by poor anticoagulant response to activated protein C: prediction of a cofactor to activated protein C. Proc Natl Acad Sci USA 90:1004–1008View ArticleGoogle Scholar
  11. Fisher CL, Greengard JS, Griffin JH (1994) Models of the serine protease domain of the human antithrombotic plasma factor activated protein C and its zymogen. Protein Sci 3:588–599View ArticleGoogle Scholar
  12. Gabriel S, Ziaugra L, Tabbaa D (2009) SNP genotyping using the Sequenom MassARRAY iPLEX platform. Curr Protoc Hum Genet Chapter 2: Unit 2.12. doi:https://doi.org/10.1002/0471142905.hg0212s60
  13. Gandrille S, Greengard JS, Alhenc-Gelas M, Juhan-Vague I, Abgrall JF, Jude B, Griffin JH, Aiach M (1995) Incidence of activated protein C resistance caused by the ARG 506 GLN mutation in factor V in 113 unrelated symptomatic protein C-deficient patients, The French Network on the behalf of INSERM. Blood 86:219–224Google Scholar
  14. Goldhaber SZ (2012) Venous thromboembolism: epidemiology and magnitude of the problem. Best Pract Res Clin Haematol 25:235–242View ArticleGoogle Scholar
  15. Goldhaber SZ, Bounameaux H (2012) Pulmonary embolism and deep vein thrombosis. Lancet 379:1835–1846View ArticleGoogle Scholar
  16. Koster T, Rosendaal FR, de Ronde H, Briët E, Vandenbroucke JP, Bertina RM (1993) Venous thrombosis due to poor anticoagulant response to activated protein C: leiden Thrombophilia Study. Lancet 342:1503–1506View ArticleGoogle Scholar
  17. Laack TA, Goyal DG (2004) Pulmonary embolism: an unsuspected killer. Emerg Med Clin North Am 22:961–983View ArticleGoogle Scholar
  18. Lu X, Tang L, Xu K, Ma J, Guo T, Mei H, Yang R, Yu J, Wang Q, Yang Y, Jian X, Hu Y (2013) Novel association of a PROC variant with ischemic stroke in a Chinese Han population. Hum Genet 132:69–77View ArticleGoogle Scholar
  19. Mesters RM, Heeb MJ, Griffin JH (1993) A novel exosite in the light chain of human activated protein C essential for interaction with blood coagulation factor Va. Biochemistry 32:12656–12663View ArticleGoogle Scholar
  20. Miyata T, Sakata T, Yasumuro Y, Okamura T, Katsumi A, Saito H, Abe T, Shirahata A, Sakai M, Kato H (1998) Genetic analysis of protein C deficiency in nineteen Japanese families: five recurrent defects can explain half of the deficiencies. Thromb Res 92:181–187View ArticleGoogle Scholar
  21. Perera L, Foley C, Darden TA, Stafford D, Mather T, Esmon CT, Pedersen LG (2000) Modeling zymogen protein C. Biophys J 279:2925–2943View ArticleGoogle Scholar
  22. Poort SR, Rosendaal FR, Reitsma PH, Bertina RM (1996) A common genetic variation in the 30-untranslated region of the prothrombin gene is associated with elevated plasma prothrombin levels and an increase in venous thrombosis. Blood 88:3698–3703Google Scholar
  23. Reitsma PH, Poort SR, Allaart CF, Briët E, Bertina RM (1991) The spectrum of genetic defects in a panel of 40 Dutch families with symptomatic protein C deficiency type I: heterogeneity and founder effects. Blood 78:890–894Google Scholar
  24. Roberts LN, Patel RK, Arya R (2009) Venous thromboembolism and ethnicity. Br J Haematol 146:369–383View ArticleGoogle Scholar
  25. Shen MC, Lin JS, Tsay W (1997) High prevalence of antithrombin III, protein C and protein S deficiency, but no factor V Leiden mutation in venous thrombophilic Chinese patients in Taiwan. Thromb Res 87:377–385View ArticleGoogle Scholar
  26. Soare AM, Popa C (2010) Deficiencies of proteins C, S and antithrombin and factor V Leiden and the risk of ischemic strokes. J Med Life 3:235–238Google Scholar
  27. Souto JC, Almasy L, Borrell M, Blanco-Vaca F, Mateo J, Soria JM, Coll I, Felices R, Stone W, Fontcuberta J, Blangero J (2000) Genetic susceptibility to thrombosis and its relationship to physiological risk factors: the GAIT study. Genetic analysis of idiopathic thrombophilia. Am J Hum Genet 67:1452–1459View ArticleGoogle Scholar
  28. Suehisa E, Nomura T, Kawasaki T, Kanakura Y (2001) Frequency of natural coagulation inhibitor (antithrombin III, protein C and protein S) deficiencies in Japanese patients with spontaneous deep vein thrombosis. Blood Coagul Fibrinolysis 12:95–99View ArticleGoogle Scholar
  29. Tang L, Guo T, Yang R, Mei H, Wang H, Lu X, Yu J, Wang Q, Hu Y (2012a) Genetic background analysis of protein C deficiency demonstrates a recurrent mutation associated with venous thrombosis in Chinese population. PLoS One 7:e35773View ArticleGoogle Scholar
  30. Tang L, Lu X, Yu JM, Wang QY, Yang R, Guo T, Mei H, Hu Y (2012b) PROC c.574_576del polymorphism: a common genetic risk factor for venous thrombosis in the Chinese population. J Thromb Haemost 10:2019–2026View ArticleGoogle Scholar
  31. Tang L, Wang HF, Lu X, Jian XR, Jin B, Zheng H, Li YQ, Wang QY, Wu TC, Guo H, Liu H, Guo T, Yu JM, Yang R, Yang Y, Hu Y (2013) Common genetic risk factors for venous thrombosis in the Chinese population. Am J Hum Genet 92:177–187View ArticleGoogle Scholar
  32. Thomas RK, Baker AC, Debiasi RM et al (2007) High-throughput oncogene mutation profiling in human cancer. Nat Genet 39(3):347–351View ArticleGoogle Scholar
  33. Torbicki A, Perrier A, Konstantinides S, Agnelli G, Galiè N, Pruszczyk P, Bengel F, Brady AJ, Ferreira D, Janssens U, Klepetko W, Mayer E, Remy-Jardin M, Bassand JP, ESC Committee for Practice Guidelines (CPG) (2008) Guidelines on the diagnosis and management of acute pulmonary embolism: the Task Force for the Diagnosis and Management of Acute Pulmonary Embolism of the European Society of Cardiology (ESC). Eur Heart J 29:2276–2315View ArticleGoogle Scholar
  34. Wildhagen K, Lutgens E, Loubele S, ten Cate H, Nicolaes GAF (2011) The structure-function relationship of activated protein C: lessons from natural and engineered mutations. Thromb Haemost 106:1034–1045View ArticleGoogle Scholar
  35. Zakai NA, McClure LA (2011) Racial differences in venous thromboembolism. J Thromb Haemost 9:1877–1882View ArticleGoogle Scholar

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© Wang et al. 2016