Venous thrombosis: a multicausal disease

doi:10.1016/S0140-6736(98)10266-0

The Lancet

Volume 353, Issue 9159, 3 April 1999, Pages 1167-1173

https://doi.org/10.1016/S0140-6736(98)10266-0 Get rights and content

Summary

The risk factors for venous thrombosis differ from those for arterial vascular disease. During the past 5 years, knowledge about the aetiology of venous thrombosis has advanced with the discovery of several factors that contribute to the incidence of thrombosis, particularly the role of coagulation abnormalities. These abnormalities are common in the general population and therefore will be present simultaneously in some individuals. The resultant genegene and gene-environment interactions between risk factors are the key to the understanding of why a certain person develops thrombosis at a specific point in time.

Section snippets

Risk factors

The risk factors for venous thrombosis differ from those for arterial disease—myocardial infarction, stroke, and atherogenic factors such as smoking, hypertension, or hyperlipidaemia do not increase the risk of venous thrombosis. Virchow⁷ famously postulated three main causes of thrombosis: stasis of the blood, changes in the vessel wall, and changes in the composition of the blood. The known risk factors for venous thrombosis fall in the first group (stasis) and third group (composition

Prevalence and risk estimates

The impact of a risk factor is a function of its prevalence and relative risk. Table 1 shows the prevalence of various risk factors among white people in the general population of developed countries and among patients with venous thrombosis.14, 30, 31, 32, 33, 34, 35 Deficiencies of protein C, protein S, and antithrombin are rare, even among patients with thrombosis. Since these deficiencies are rare, the risk is not easy to assess and the risk estimates vary. A fair estimate seems to be that

Thrombosis as a multicausal disease

Thrombosis manifests itself as a multicausal disease most clearly in children. In the rare event of thrombosis in children, several acquired and genetic risk factors are usually present simultaneously. Not only is it rare to find children with thrombosis without any risk factor, but many have three or four risk factors. In 25–30% of children with thrombosis, deficiencies of protein C, protein S, or antithrombin have been reported, but thrombosis did not develop until other risk factors were

Selection and interaction

Among families with a tendency to thrombosis, the prevalence of thrombogenic abnormalities is much higher than among the unselected “average” patient with thrombosis who is described in table 1. In thrombophilic families, deficiencies of the main coagulation inhibitors occur in 15%, prothrombin 20210A in nearly 20%, and factor V Leiden in 40–60%. The risk of thrombosis is also higher in members of these families than among other individuals with similar defects.12, 33, 42, 43, 44, 45, 46, 47

Gene-gene interaction

The high risk of thrombosis associated with the combination of protein C deficiency and factor V Leiden is an example of gene-gene interaction. Similar findings have been documented for families with protein S deficiency,⁵⁰ antithrombin deficiency,⁵¹ and prothrombin 20210A;⁵² factor V Leiden is common in these families, and those with a combined defect have a high risk of thrombosis. These findings all suggest that the risk of abnormalities will be an overestimate if it is derived from family

Gene-environment interaction

Since some of the recently discovered genetic abnormalities are common, as are several acquired risk factors, the joint effects of such factors on risk of thrombosis warrants investigation. Clear indications of synergistic effects come from studies in thrombophilic families, where high risks were found in pregnancy and the puerperium, and during use of oral contraceptives, for women with deficiencies of protein C, protein S, or antithrombin.56, 58, 59, 60, 61, 62 In several series of unselected

Models of thrombosis risk

When the first coagulation defects that underlie thrombophilia were discovered, such as, deficiencies of antithrombin, protein C, and protein S, thrombosis was considered a single-gene defect.70, 71 Since the first families studied were those with the most pronounced thrombophilia, for reasons explained above, it is understandable that for some time one defect was thought sufficient for thrombosis. Of course, the risk in these families was so high because they harboured several defects. Since

Interaction

Interaction occurs when two risk factors in combination produce an effect that exceeds the sum of their separate effects. It has been shown that different hypothetical biological mechanisms may lead to diverse risk profiles.⁷⁵ Interaction is, therefore, defined in numerical terms, and not in terms of biological mechanism, and the presence or absence of interaction does not allow conclusions about biological mechanisms, even though the finding of interaction may prompt research into mechanisms.⁷⁶

Conclusion

Thrombosis is a disease in which genetic and acquired risk factors interact dynamically. A time-dependent model that incorporates interaction of risk factors is valuable to explain why thrombosis occurs in one person at a specific time. Such a model will primarily be useful to shape thinking about the aetiology of thrombosis. Theoretically, this model will guide us to be able to provide individual risk estimates and set guidelines for prevention and prophylaxis. This process will require much

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VTE was unevenly distributed in the population; the Gini coefficient was 0.59. Higher VTE density in pedigrees was associated in the offspring with a higher risk of different VTE manifestations (deep venous thrombosis, pulmonary embolism, pregnancy-related VTE, unusual thrombosis, and superficial thrombophlebitis), thrombophilia, and lower age of first VTE event. Moreover, VTE density in pedigrees was significantly associated in the offspring with obesity, diabetes, gout, varicose veins, and arterial embolism and thrombosis (excluding brain and heart). No significant associations were observed for retinal vein occlusion, hypercholesterolemia, hypertension, coronary heart disease, myocardial infarction, ischemic stroke, atrial fibrillation, heart failure, primary pulmonary hypertension, cerebral hemorrhage, aortic aneurysm, peripheral artery disease, and overall mortality.
Offspring of pedigrees with a high density of VTE are disadvantaged regarding VTE manifestations and certain cardiometabolic disorders.
Proportion of venous thromboembolism attributed to recognized prothrombotic genotypes in men and women
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Data on the proportion of venous thromboembolism (VTE) risk attributed to prothrombotic genotypes in men and women are limited.
We aimed to estimate the population attributable fraction (PAF) of VTE for recognized, common prothrombotic genotypes in men and women using a population-based case cohort.
Cases with incident VTE (n = 1493) and a randomly sampled subcohort (n = 13,069) were derived from the Tromsø study (1994-2012) and the Trøndelag Health Study (1995-2008) cohorts. DNA samples were genotyped for 17 single-nucleotide polymorphisms (SNPs) previously associated with VTE. PAFs with 95% bias-corrected CIs (based on 10,000 bootstrap samples) were estimated for SNPs significantly associated with VTE, and a 6-SNP cumulative model was constructed for both sexes.
In women, the individual PAFs for SNPs included in the cumulative model were 16.9% for ABO (rs8176719), 17.6% for F11 (rs2036914), 15.1% for F11 (rs2289252), 8.7% for FVL (rs6025), 6.0% for FGG (rs2066865), and 0.2% for F2 (rs1799963). The cumulative PAF for this 6-SNP model was 37.8%. In men, the individual PAFs for SNPs included in the cumulative model were 21.3% for ABO, 12.2% for F11 (rs2036914), 10.4% for F11 (rs2289252), 7.5% for FVL, 7.8% for FGG, and 1.1% for F2. This resulted in a cumulative PAF in men of 51.9%.
Our findings in a Norwegian population suggest that 52% and 38% of the VTEs can be attributed to known prothrombotic genotypes in men and women, respectively.
Serial values of hematologic variables and deep venous thrombosis: Red cell distribution width is associated with deep venous thrombosis
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As 30 to 50% of deep venous thrombosis (DVT) cases remain idiopathic, an increased focus on hematologic variables may therefore reveal novel correlates of DVT. Very few studies have investigated the association of hematological parameters with DVT and the causal relationship between them is still to be elucidated. Therefore, we aimed to investigate the association between serial values of hematologic variables and DVT.
Complete blood count parameters were serially measured at baseline and then at approximately 3-month intervals for 12 months in 152 adults with the first episode of DVT and 152 age- and sex-matched controls. The odds ratio (OR) with the 95% confidence interval (95%CI) was calculated as a measure of association between hematological parameters and DVT.
The red cell distribution width (RDW) was the only hematologic variable which showed an independent and consistent association with DVT at all time points (multivariable-adjusted OR [95%CI] 3.38 [1.28 – 8.91] at baseline, 2.24 [0.85 – 5.92] at 3 months and 2.12 [0.81 – 5.55] at 12 months for RDW > 14.0%). This association was higher for provoked DVT than unprovoked DVT and for DVT plus pulmonary embolism than DVT alone. No significant correlation was found between the high RDW and classical thrombotic risk factors, except malignancy.
We demonstrated an independent and consistent association of the high RDW with the first episode of DVT in adult patients. The study was probably underpowered to evaluate the association between the high RDW and recurrent DVT. Further large studies with long follow-up are needed to confirm this association.
Genomic science of risk prediction for venous thromboembolic disease: convenient clarification or compounding complexity
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Venous thromboembolism (VTE) refers to abnormal blood clots in veins occurring in 1 to 2 per 1000 individuals every year. While anticoagulant treatment can prevent VTE, it increases the risk of bleeding. This emphasizes the importance of identifying individuals with a high risk of VTE and providing prophylactic interventions to these individuals to reduce both VTE and bleeding risks. Current risk assessment of VTE is based on the combination of mainly clinical risk factors. With the identification of an increasing number of genetic variants associated with the risk of VTE, the addition of genetic findings to clinical prediction models can improve risk prediction for VTE. Especially for individuals in high-risk situations, the added value of genetic findings to clinical prediction models may have benefits such as better prophylaxis of VTE and the reduced side effects of bleeding from unnecessary treatment. Nevertheless, the question of whether these models will eventually have clinical utility remains to be proven. Here, we review the current state of knowledge on genetic risk factors for VTE, explore genetic prediction models for VTE, and discuss their clinical implications and challenges.
An ultrasound imaging and computational fluid dynamics protocol to assess hemodynamics in iliac vein compression syndrome
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Elevated shear rates are known to play a role in arterial thrombosis; however, shear rates have not been thoroughly investigated in patients with iliac vein compression syndrome (IVCS) owing to imaging limitations and assumptions on the low shear nature of venous flows. This study was undertaken to develop a standardized protocol that quantifies IVCS shear rates and can aid in the diagnosis and treatment of patients with moderate yet symptomatic compression.
Study patients with and without IVCS had their iliac vein hemodynamics measured via duplex ultrasound (US) at two of the following three vessel locations: infrarenal inferior vena cava (IVC), right common iliac vein, and left common iliac vein, in addition to acquiring data at the right and left external iliac veins. US velocity spectra were multiplied by a weighted cross-sectional area calculated from US and computed tomography (CT) data to create flow waveforms. Flow waveforms were then scaled to enforce conservation of flow across the IVC and common iliac veins. A three-dimensional (3D), patient-specific model of the iliac vein anatomy was constructed from CT and US examination. Flow waveforms and the 3D model were used as a basis to run a computational fluid dynamics (CFD) simulation. Owing to collateral vessel flow and discrepancies between CT and US area measurements, flows in internal iliac veins and cross-sectional areas of the common iliac veins were calibrated iteratively against target common iliac flow. Simulation results on mean velocity were validated against US data at measurement locations. Simulation results were postprocessed to derive spatial and temporal values of quantities such as velocity and shear rate.
Using our modeling protocol, we were able to build CFD models of the iliac veins that matched common iliac flow splits within 2% and measured US velocities within 10%. Proof-of-concept analyses (1 subject, 1 control) have revealed that patients with IVCS may experience elevated shear rates in the compressed left common iliac vein, more typical of the arterial rather than the venous circulation. These results encourage us to extend this protocol to a larger group of patients with IVCS and controls.
We developed a protocol that obtains hemodynamic measurements of the IVC and iliac veins from US, creates patient-specific 3D reconstructions of the venous anatomy using CT and US examinations, and computes shear rates using calibrated CFD methods. Proof-of-concept results have indicated that patients with IVCS may experience elevated shear rates in the compressed left common iliac vein. Larger cohorts are needed to assess the relationship between venous compression and shear rates in patients with IVCS as compared with controls with noncompressed iliac veins. Further studies using this protocol may also give promising insights into whether or not to treat patients with moderate, yet symptomatic compression.
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SeriesVenous thrombosis: a multicausal disease

Summary

Section snippets

Risk factors

Prevalence and risk estimates

Thrombosis as a multicausal disease

Selection and interaction

Gene-gene interaction

Gene-environment interaction

Models of thrombosis risk

Interaction

Conclusion

Prog Cardiovasc Dis

Lancet

Blood

Lancet

Lancet

Am J Clin Nutr

Blood

Blood

Lancet

Lancet

Blood

Blood

Lancet

Blood

Blood

Blood

Lancet

J Pediatr

Lancet

Cell

Blood

A prospective study of the incidence of deep-vein thrombosis with a defined urban population

J Intern Med

A population based perspective of the hospital incidence and case-fatality rates of deep vein thrombosis and pulmonary embolism. The Worcester DVT study

Arch Intern Med

Thrombosis in the young: epidemiology and risk factors, a focus on venous thrombosis

Thromb Haemost

Pathogenesis of venous thombosis

Phlogose und Thrombose im Gefässystem. In: Gesammelte Abhandlungen zur Wissenschaftlichen Medizin

Inherited antithrombin deficiency causing thrombophilia

Thromb Diath Haemorrh

Deficiency of protein C in congenital thrombotic disease

J Clin Invest

Plasma protein S deficiency in familial thrombotic disease

Blood

Familial thrombophilia due to a previously unrecognised mechanism characterized by poor anticoagulant response to activated protein C: prediction of a cofactor to activated protein C

Proc Natl Acad Sci USA

Mutation in blood coagulation factor V associated with resistance to activated protein C

Nature

Markers of procoagulant imbalance in patients with inherited thrombophilic syndromes

Thromb Haemost

Familial clustering of factor VIII and von Willebrand factor levels

Thromb Haemost

Analysis of the F8 gene in individuals with high plasma factor VIII:C levels and associated venous thrombosis

Thromb Haemost

Epidemiological study on factor VII, factor VIII and fibrinogen in an industrial population. I. Baseline data on the relation to age, gender, body-weight, smoking, alcohol, pill-using, and menopause

Thromb Haemost

Epidemiological study on factor VII, factor VIII and fibrinogen in an industrial population. II. Baseline data on the relation of blood pressure, blood glucose, uric acid, and lipid fractions

Thromb Haemost

Epidemiology of coagulation factors, inhibitors and activation markers: the Third Glasgow MONICA Survey. I. Illustrative reference ranges by age, sex, and hormone use

Br J Haematol

Hemostatic effects of oral contraceptives in women who developed deep-vein thrombosis while using oral contraceptives

Thromb Haemost

Series
Venous thrombosis: a multicausal disease