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Archive for the ‘Coagulation Therapy and Internal Bleeding’ Category

Aortic Aneurysm Pathogenesis: The Role of TGFβRIIb Mutations in  Altering Transforming Growth Factor β2 Signal Transduction

Reporter: Aviva Lev-Ari, PhD, RN

TGFβRIIb Mutations Trigger Aortic Aneurysm Pathogenesis by Altering Transforming Growth Factor β2 Signal Transduction

Katharine J. Bee, PhD, David C. Wilkes, PhD, Richard B. Devereux, MD, Craig T. Basson, MD, PhD and Cathy J. Hatcher, PhD

Author Affiliations

From the Center for Molecular Cardiology, Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY.

Correspondence to Cathy J. Hatcher, PhD, Greenberg Division of Cardiology, Weill Cornell Medical College, 525 E. 68th St, New York, NY 10065. E-mailcjhatche@med.cornell.edu

Abstract

Background—Thoracic aortic aneurysm (TAA) is a common progressive disorder involving gradual dilation of the ascending and/or descending thoracic aorta that eventually leads to dissection or rupture. Nonsydromic TAA can occur as a genetically triggered, familial disorder that is usually transmitted in a monogenic autosomal dominant fashion and is known as familial TAA. Genetic analyses of families affected with TAA have identified several chromosomal loci, and further mapping of familial TAA genes has highlighted disease-causing mutations in at least 4 genes: myosin heavy chain 11 (MYH11), α-smooth muscle actin (ACTA2), and transforming growth factor β receptors I and II (TGFβRI and TGFβRII).

Methods and Results—We evaluated 100 probands to determine the mutation frequency in MYH11ACTA2TGFβRI, and TGFβRII in an unbiased population of individuals with genetically mediated TAA. In this study, 9% of patients had a mutation in one of the genes analyzed, 3% of patients had mutations in ACTA2, 3% in MYH11, 1% in TGFβRII, and no mutations were found in TGFβRI. Additionally, we identified mutations in a 75 base pair alternatively spliced TGFβRII exon, exon 1a that produces the TGFβRIIb isoform and accounted for 2% of patients with mutations. Our in vitro analyses indicate that the TGFβRIIb activating mutations alter receptor function on TGFβ2 signaling.

Conclusions—We propose that TGFβRIIb expression is a regulatory mechanism for TGFβ2 signal transduction. Dysregulation of the TGFβ2 signaling pathway, as a consequence of TGFβRIIb mutations, results in aortic aneurysm pathogenesis.

SOURCE: 

Circulation: Cardiovascular Genetics.2012; 5: 621-629

Published online before print October 24, 2012,doi: 10.1161/ CIRCGENETICS.112.964064

 

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The Role of Sibling Kinship, Sex, and Age of Ischemic Stroke Onset: The Familial Component

Reporter: Aviva Lev-Ari, PhD, RN

 

Familial Effects on Ischemic Stroke – The Role of Sibling Kinship, Sex, and Age of Onset

Katherine Kasiman, MSc, Cecilia Lundholm, MSc, Sven Sandin, MSc, Ninoa Malki, MSc, Pär Sparén, PhD and Erik Ingelsson, MD, PhD

Author Affiliations

From the Department of Medical Epidemiology and Biostatistics (K.K., C.L., S.S., N.M., P.S., E.I.), Karolinska Institutet, Stockholm, Sweden; Centre for Molecular Epidemiology (K.K.), Saw Swee Hock School of Public Health, National University of Singapore, Singapore.

Correspondence to Prof Erik Ingelsson, MD, PhD, FAHA, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Box 281, Nobels väg 12A, SE-171 77 Stockholm, Sweden. E-mail erik.ingelsson@ki.se

Abstract

Background—Previous studies on familial risk of ischemic stroke have supported genetic influence on the disease incidence. This study aimed to characterize these familial effects in a nationwide population-based study by taking into account sibling relations, sex of siblings, and age of onset, with respect to ischemic stroke incidence.

Methods and Results—Incident ischemic stroke cases identified from the Swedish Hospital Discharge and Cause of Death Registers between 1987 and 2007 were linked to their stroke-free siblings (study participants), forming an exposed sib-pair. Each exposed sib-pair was matched up to 5 unexposed sib-pairs from the Multi-Generation Registry by birth and calendar years. Incident ischemic stroke risk was assessed using hazard estimates obtained from stratified Cox regression analyses. A total of 30 735 exposed and 152 391 unexposed study participants were included in the analyses. The overall risk of incident ischemic stroke when exposed was significantly increased (relative risk, 1.61; 95% confidence interval, 1.48–1.75;P<0.001). Familial risk was higher in full (relative risk, 1.64; 95% confidence interval, 1.50–1.81; P<0.001) than in half (relative risk, 1.41; 95% confidence interval, 1.10–1.82; P=0.007) siblings. Familial risk of early ischemic stroke almost doubled when exposed to early ischemic stroke (relative risk, 1.94; 95% confidence interval, 1.41–2.67; P<0.001).

Conclusions—There was a 60% increased risk for ischemic stroke in individuals having a sibling with prior stroke. The familial effect was even higher for full-sibling relations. Familial effects were observed in both male and female individuals, and no differential effects depending on the sex of either of the siblings were found.

Published online before print March 8, 2012,

doi: 10.1161/ CIRCGENETICS.111.962191

http://circgenetics.ahajournals.org/content/5/2/226.abstract?sid=5201ab39-7f11-4007-b159-2d1e15663cd5

 

 

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Genomics of Incident Ischemic Stroke Events, Stroke and Cardiovascular Disease

Reporter: Aviva Lev-Ari, PhD, RN

 

Associations Between Incident Ischemic Stroke Events and Stroke and Cardiovascular Disease-Related Genome-Wide Association Studies Single Nucleotide Polymorphisms in the Population Architecture Using Genomics and Epidemiology Study

Cara L. Carty, PhD, Petra Bůžková, PhD, Myriam Fornage, PhD, Nora Franceschini, MD, Shelley Cole, PhD, Gerardo Heiss, MD, PhD, Lucia A. Hindorff, PhD, MPH, Barbara V. Howard, PhD, Sue Mann, MPH, Lisa W. Martin, MD, Ying Zhang, PhD, Tara C. Matise, PhD, Ross Prentice, PhD, Alexander P. Reiner, MD, MS and Charles Kooperberg, PhD

Author Affiliations

From the Public Health Sciences, Fred Hutchinson Cancer Research Center (C.L.C., S.M., R.P., C.K.); Department of Biostatistics, University of Washington, Seattle, WA (P.B.); Institute of Molecular Medicine, University of Texas Health Sciences Center at Houston, Houston, TX (M.F.); Division of Epidemiology, School of Public Health, University of Texas Health Sciences Center, Houston, TX (M.F.); Department of Epidemiology, University of North Carolina, Chapel Hill, NC (N.F., G.H.); Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX (S.C.); Office of Population Genomics, National Human Genome Research Institute, Bethesda, MD (L.A.H.); Medstar Health Research Institute, Washington, DC (B.V.H.); George Washington University School of Medicine, Washington, DC (B.V.H., L.W.M.); University of Oklahoma Health Sciences Center, Oklahoma City, OK (Y.Z.); Department of Genetics, Rutgers University, Piscataway, NJ (T.C.M.); Department of Epidemiology, University of Washington, Seattle, WA (A.P.R.).

Correspondence to Dr Cara L. Carty, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N./M3-A410, Seattle, WA 98109. E-mail ccarty@fhcrc.org

Abstract

Background—Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different populations has been largely unexplored.

Methods and Results—Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein [HDL], low density lipoprotein [LDL], and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomicsand Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were associated with increased IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS.

Conclusions—Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 210-216

 

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Novel Macromolecular IV to Oral Delivery Conversion Pathway: Anti-thrombolytic post-surgical – Catalent OptiGel Bio™ Technology

Reporter: Aviva Lev-Ari, PhD, RN

Case Study

OptiGel BioTechnology Enables IV to Oral Therapy Conversion

Executive Summary

An early-stage biotechnology company had developed a novel macromolecular intravenous (IV) therapy for an anti-thrombolytic post-surgical indication. While the therapy had shown complete absorption via IV, the dose form was not ideal due to a number of factors including manufacturing costs, compliance, and ease of use, as well as as well as the long term treatment requirements. This case study demonstrates how Catalent OptiGel Bio™ technology can provide a pathway for an IV to oral delivery conversion, resulting in enhanced therapies for patients.

The Challenges

Though soluble, the macromolecule presented a number of permeability challenges, which hindered delivery of an active therapeutic dose across the lumen of the small intestine to achieve the desired therapeutic effect.

*Salamat-Miller N et al. , Pharmaceutical Research, 2005, 22(2):245-254

By incorporating OptiGel Bio™ technology and our formulation expertise, an optimized oral therapy was developed combining permeation enhancement and targeted delivery.

physiochemical properties High molecular weight (>2500 Da)Strong negative charge*

Rigid, inflexible geometry*

targeted delivery Functional API must be delivered to the small intestine in order to achieve bioavailability
permeability Mucus layer physical barrierRandom and limited transcellular pathways

“Fence and gate” function of tight junctions

pharmacokinetic profile Oral delivery must reach exposure within therapeutic range

The Catalent Solution

enhanced permeability The first challenge to overcome in development was enhancing the permeability of the macromolecule. A stepwise screening approach utilizing both in vitro and in vivo models yielded lead formulation candidates for further evaluation.

The Catalent Solution

https://kapost-files-prod.s3.amazonaws.com/uploads/direct/1382388405-22-3748/274-01_CaseStudy_OptiGelBio.pdf

enhanced permeability The first challenge to overcome in development was enhancing the permeability of the macromolecule. A stepwise screening approach utilizing both in vitro and in vivo models yielded lead formulation candidates for further evaluation.

Conclusion

Using OptiGel Bio™ technology, we overcame the challenges traditionally associated with the oral delivery of macromolecules and enabled conversion from an IV to a more efficient, more convenient and less invasive oral dose form while maintaining an effective pK profile. Through a multi-step drug delivery screening process and our OptiGel Bio™ technology, we can enable enhanced therapies—resulting in better treatments and more value for innovators, healthcare professionals and patients.

SOURCE

https://kapost-files-prod.s3.amazonaws.com/uploads/direct/1382388405-22-3748/274-01_CaseStudy_OptiGelBio.pdf

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Anticoagulation Genotype guided Dosing

Author and Curator: Larry H. Bernstein, MD, FCAP 

 

A common complication of patients on Warfarin (coumadin) is massive hematoma associated with a fall.  Warfarin is an inhibitor of the liver production of prothrombin.  Inadequate Warfarin dosing results in a risk of thromboembolism to the lungs or the brain, depending on where the clot is initiated.  However, there is a pharmacogenomic problem in that there are individuals who have a genetic polymorphism (CYP2C9 and VKORC1) that affects the coagulation effect of the coumadin.  This introduces the question of whether such individuals should be identified and dosed according to pharmacogenomic testing.  The usual measurement of the effect of the drug is the International Normalized Ratio (INR) from the Prothrombin Time (PT).  The existence of chronic liver disease and the use of coumadin are perhaps almost the exclusive value for the PT.
A similar question arises for the genotyping of clopidogrel for antiplatelet guidance. Does it reduce risk in stenting?

A Pharmacogenetic versus a Clinical Algorithm for Warfarin Dosing

Stephen E. Kimmel, M.D., Benjamin French, Ph.D., Scott E. Kasner, M.D., Julie A. Johnson, Pharm.D., and others

Center for Therapeutic Effectiveness Research,  Philadelphia, PA 19104-6021, or at stevek@mail.med.upenn.edu.

A complete list of investigators and committees in the Clarification of Optimal Anticoagulation through Genetics (COAG) trial is provided in the Supplementary Appendix, available at NEJM.org.

November 19, 2013 | NEJM
http://dx.doi.org/10.1056/NEJMoa1310669

Comparison of  genotype-guided dosing algorithm with the clinically guided dosing algorithm for Warfarin dosing

Abstract

nejmoa1310669.pdf  

Background

The clinical utility of genotype-guided (pharmacogenetically based) dosing of warfarin has been tested only in small clinical trials or observational studies, with equivocal results.
Methods
We randomly assigned 1015 patients to receive doses of warfarin during the first 5 days of therapy that were determined according to a dosing algorithm that included both clinical variables and genotype data or to one that included clinical variables only. All patients and clinicians were unaware of the dose of warfarin during the first 4 weeks of therapy. The primary outcome was the percentage of time that the international normalized ratio (INR) was in the therapeutic range from day 4 or 5 through day 28 of therapy.

Results

At 4 weeks, the mean percentage of time in the therapeutic range was 45.2% in the genotype-guided group and 45.4% in the clinically guided group (adjusted mean difference, [genotype-guided group minus clinically guided group], −0.2; 95% confidence interval, −3.4 to 3.1; P=0.91). There also was no significant between-group difference among patients with a predicted dose difference between the two algorithms of 1 mg per day or more. There was, however, a significant interaction between dosing strategy and race (P=0.003). Among black patients, the mean percentage of time in the therapeutic range was less in the genotype-guided group than in the clinically guided group. The rates of the combined outcome of any INR of 4 or more, major bleeding, or thromboembolism did not differ significantly according to dosing strategy.

Conclusions

Genotype-guided dosing of warfarin did not improve anticoagulation control during the first 4 weeks of therapy. (Funded by the National Heart, Lung, and Blood Institute and others; COAG ClinicalTrials.gov number, NCT00839657.)
Figure 1 Distribution of Time in the Therapeutic Range.
nejmoa1310669_f1 Distribution of Time in the Therapeutic Range.
Figure 2 Range of INRs during the 4-Week Study.
nejmoa1310669_f2 Range of INRs during the 4-Week Study.

Introduction

The need for clinical trials before widespread adoption of genotype-guided drug dosing and selection remains widely debated.1-4 Warfarin therapy has served as a model for the potential for pharmacogenetics to improve patient care.1 Observational studies have identified two genes, CYP2C9 and VKORC1, that are associated with variation in warfarin maintenance doses. However, the clinical utility of starting warfarin at the maintenance dose predicted by genotype-guided algorithms has been tested only in small trials, none of which were definitive.5-8 In contrast, observational studies have suggested potential benefits from genotype-guided dosing.9,10 In addition, previous clinical trials could not determine the usefulness of current dosing algorithms among black patients, for whom genotype-guided algorithms perform less well than for other populations.11-13
On the basis of available data, the Food and Drug Administration (FDA) has updated the label for warfarin twice, suggesting that variants in CYP2C9 and VKORC1 may be taken into consideration when choosing the initial warfarin dose. However, the Centers for Medicare and Medicaid Services did not find sufficient evidence to cover the cost of genotyping for warfarin dosing.14 Our study, called the Clarification of Optimal Anticoagulation through Genetics (COAG) trial, was designed to test the effect of genotype-guided dosing on anticoagulation control.

Methods

Study Design and Oversight

The COAG trial was a multicenter, double-blind, randomized, controlled trial that compared a genotype-guided warfarin-dosing strategy with a clinically based dosing strategy during the first 5 days of therapy among patients initiating warfarin treatment.15-17 The study was designed by the authors and approved by the institutional review board at the University of Pennsylvania and at each participating clinical center. The data were collected, analyzed, and interpreted by the authors. A steering committee provided oversight of the trial (for details, see the Supplementary Appendix, available with the full text of this article at NEJM.org). An independent data and safety monitoring board monitored the trial and made recommendations to the National Heart, Lung, and Blood Institute. The first two authors wrote the first draft of the manuscript, which was edited and approved by all the authors. The National Heart, Lung, and Blood Institute supported this study. Bristol-Myers Squibb donated Coumadin (warfarin). GenMark Diagnostics and AutoGenomics loaned genotyping platforms to the clinical centers. None of the companies supporting the trial had any role in the design of the protocol or in the collection, analysis, or interpretation of the data. The authors vouch for the data and the analyses, and for the fidelity of this report to the trial protocol, which is available at NEJM.org.

Study Patients and Randomization

From September 2009 through April 2013, we enrolled both inpatients and outpatients at 18 clinical centers in the United States. All the patients were adults initiating warfarin therapy with a target international normalized ratio (INR) of 2 to 3. Detailed inclusion and exclusion criteria are provided in the Supplementary Appendix. All patients provided written informed consent.
Patients were randomly assigned, in a 1:1 ratio, to the use of a dosing algorithm that included both clinical variables and genotype data or to a clinically guided dosing strategy. Randomization was stratified according to clinical center and self-reported race (black vs. nonblack).
Genotyping for CYP2C9 and VKORC1 at each clinical center was performed with the use of one of two FDA-approved platforms, the GenMark Dx eSensor XT-8 or the AutoGenomics INFINITI Analyzer. Per protocol, genotyping was performed in all patients immediately after blood-sample collection to maintain blinding to the treatment assignment. Genotyping was repeated at the central laboratory with the use of either pyrosequencing or real-time polymerase-chain-reaction assay to measure the accuracy at clinical centers.

Study Intervention and Follow-up

The study intervention period was the first 5 days of warfarin therapy. During this period, the prespecified algorithms were used to determine the warfarin dose. For each dosing strategy, a dose-initiation algorithm was used during the first 3 days of therapy, and a dose-revision algorithm was used on day 4, 5, or both. The algorithms for the genotype-guided dosing strategy12,18 included clinical variables and genotype data for CYP2C9*2, CYP2C9*3, and VKORC1. The algorithms for the clinically based dosing strategy included clinical variables only. The dosing algorithms are provided in the Supplementary Appendix. If genotype information was not available for a patient in the genotype-guided dosing group before the administration of warfarin on any given day in the first 5 days, the clinical algorithm was used on that day.
During the first 4 weeks of therapy, patients and clinicians were unaware of the actual dose of warfarin that was administered, because the pills were encapsulated to prevent identification of the dose (see the Supplementary Appendix). After the 5-day initiation period, we adjusted the dose during the first 4 weeks using standardized dose-adjustment techniques,5,10 starting with the doses predicted by the algorithms and making the same relative adjustments on the basis of the INR in the two study groups. Clinicians were informed of the relative dose change (e.g., a 10% dose increase) at each INR measurement but not the actual dose of warfarin. Clinicians could contact the medical monitor (who was aware of the study-group assignments) to request an override of these relative dose changes without being informed of the actual dose. All patients were to be followed for a total of 6 months.

Study Outcomes

The primary outcome was the percentage of time in the therapeutic range (INR, 2 to 3) from the completion of the intervention period (day 4 or 5) through day 28 of therapy. We calculated the percentage of time in the therapeutic range using a standard linear interpolation method between successive INR values,19 as detailed in the Supplementary Appendix. Each clinical center measured INRs with the use of instruments certified by the Clinical Laboratory Improvement Amendments and following strict quality assurance.
Secondary outcomes included a composite outcome of any INR of 4 or more, major bleeding, or thromboembolism in the first 4 weeks (principal secondary outcome); the time to the first therapeutic INR; the time to the determination of a maintenance dose (which was defined as the time to the first of two consecutive INR measurements, measured at least 1 week apart, that were in the therapeutic range without a dose change); and the time to an adverse event (death from any cause, major bleeding, thromboembolism, or any clinically relevant nonmajor bleeding event20,21) in the first 4 weeks. Two physicians who were unaware of the study-group assignments adjudicated major bleeding and thromboembolic serious adverse events. The definitions of major bleeding,22 clinically relevant nonmajor bleeding, and thromboembolism are provided in the Supplementary Appendix.

Statistical Analysis

We analyzed the primary outcome in the modified intention-to-treat population, which included all patients who underwent randomization with the exception of patients for whom INR data were not available (Fig. S1 in the Supplementary Appendix). Safety outcomes were analyzed in the entire cohort, regardless of whether patients received the study drug. We used regression models to analyze the primary and secondary outcomes, using linear regression for the percentage of time in the therapeutic range and Cox regression for time-to-event outcomes. The protocol specified that we conduct coprimary analyses in which we evaluated the primary outcome in all patients and in a primary subgroup, which comprised patients who had an absolute difference of 1.0 mg or more in the predicted initial daily dose between the genotype-guided dosing algorithm and the clinical dosing algorithm. We used an alpha allocation approach, which formally allows for the evaluation of the treatment benefit in an enriched subgroup as a coprimary end point. In this approach, the overall type I error rate of 0.05 for the primary outcome was split between the analyses performed among all patients and among those in the primary subgroup.17 All models were adjusted for the stratification variables (center and race). Additional subgroups, which were prespecified, were race (black vs. nonblack), sex, and the total number of allelic variants (1 variant vs. 0 or >1 variant in either CYP2C9 or VKORC1 5). All statistical tests were two-sided. All analyses were performed with the use of the R statistical package, version 3.0.1 (R Development Core Team).
We specified a minimum detectable difference of 5.5% in the mean percentage of time in the therapeutic range between the genotype-guided group and the clinically guided group in the entire study population.16 We assumed a standard deviation for the percentage of time in therapeutic range of 25% and a potential dropout rate of 10%. On the basis of recruitment rates,15 the initial sample size of 1238 patients was revised to 1022 patients on September 16, 2012 (with the approval of the data and safety monitoring board). The revised sample size provided a power of at least 80% to detect a between-group difference of 5.5% at a type I error rate of 0.04 among all patients and a 9.0% difference at a type I error rate of 0.01 among patients in the coprimary analysis.

Results

Patients, Genotyping, and Follow-up

A total of 1015 patients were enrolled and randomly assigned to either the genotype-guided dosing algorithm or the clinically guided dosing algorithm (Fig.S1 in the Supplementary Appendix). There were no significant between-group differences at baseline (Table 1Table 1Characteristics of the Patients at Baseline.). The characteristics of the patients according to self-reported race are provided in Table S1 in the Supplementary Appendix. A total of 60 participants (30 in each group) withdrew before completing the intervention period and did not have an available percentage of time in the therapeutic range, resulting in an analytic sample size of 955. A median of six INRs were measured during the first 4 weeks in each of the two study groups. Dispensed doses during the intervention period are summarized in Table S2 in the Supplementary Appendix.
Genotype data were available in the genotype-guided group for 45% of the patients before the first warfarin dose, for 94% before the second warfarin dose, and for 99% before the application of the dose-revision algorithm on day 4 or 5. The mean (±SD) difference between the dose calculated for patients without genotype data on day 1, as compared with the dose they would have received if genotype data had been available, was −0.1±0.4 mg per day during the first 3 days. The central laboratory confirmed 99.8% of all genotyping results from the clinical centers. All genotype distributions were in Hardy–Weinberg equilibrium (P>0.20 for all comparisons).

Primary Outcome

At 4 weeks, there was no significant between-group difference in the mean percentage of time in the therapeutic range: 45.2% in the genotype-guided group and 45.4% in the clinically guided group (adjusted mean difference [genotype-guided group minus clinically guided group], −0.2%; 95% confidence interval, −3.4 to 3.1; P=0.91) (Table 2Table 2Percentage of Time in the Therapeutic INR Range through Week 4 of Therapy, According to Subgroup. and Figure 1Figure 1Distribution of Time in the Therapeutic Range.). There was also no significant between-group difference in the percentage of time in the therapeutic range among patients in the coprimary analysis (Table 2). When the 4-week trial was divided into two 2-week intervals, there was also no significant difference between the groups in either interval (Table 2).
However, there was a significant interaction between race and dosing strategy (P=0.003) (Table 2). Among black patients, the mean percentage of time in the therapeutic range was less in the genotype-guided group than in the clinically guided group (35.2% vs. 43.5%; adjusted mean difference, −8.3%; P=0.01). Among nonblack patients, the mean percentage of time in the therapeutic range was slightly higher in the genotype-guided group than in the clinically guided group (48.8% vs. 46.1%; adjusted mean difference, 2.8%; P=0.15). There were no significant differences in the percentage of time in the therapeutic range according to sex or the total number of genetic variants (Table 2).

Anticoagulation Control and Dose Prediction

There were no significant between-group differences in the mean percentage of time above the therapeutic range (INR, >3) or below the therapeutic range (INR, <2) (Figure 2Figure 2Range of INRs during the 4-Week Study., and Table S3 in the Supplementary Appendix). However, black patients in the genotype-guided group were more likely to have INRs above the therapeutic range than were those in the clinically guided group (Fig. S2 and Table S3 in the Supplementary Appendix).
There was no overall between-group difference in the time to the first INR in the therapeutic range (Table S4 in the Supplementary Appendix). However, black patients in the genotype-guided group took longer on average to reach the first therapeutic INR than did those in the clinically guided group (Table S4 and Fig. S3 in the Supplementary Appendix). The time to the determination of the maintenance dose did not differ significantly between the two groups overall or according to the primary subgroup, race, or total number of genetic variants (Table S5 in the Supplementary Appendix).
The performance characteristics of the dosing algorithms with respect to the maintenance dose that was determined are shown in Table S6 (which includes the accuracy of a hypothetical, empirical dosing strategy of 5 mg per day) and in Fig. S4, both in the Supplementary Appendix. The genotype-guided algorithms performed better at predicting the maintenance dose among nonblack patients than among black patients. Dose overrides during the first 4 weeks were rare, occurring in only 3.9% of doses in the genotype-guided group and 3.6% of those in the clinically guided group; rates of overrides did not differ according to race.

Adverse Events

At 4 weeks, there were no significant between-group differences in the principal secondary outcome (the time to any INR of ≥4, major bleeding, or thromboembolism) or any other adverse events (Table 3Table 3Adverse Events through Day 28 of Warfarin Therapy., and Table S7 in the Supplementary Appendix). Safety data for the entire duration of follow-up (i.e., past the primary outcome duration) are provided in Table S8 in the Supplementary Appendix.

Discussion

In our study, we found no benefit of genotype-guided dosing of warfarin with respect to the primary outcome of the percentage of time in the therapeutic INR range, either overall or among patients with a predicted dose difference between the genotype-guided algorithm and the clinically guided algorithm of at least 1 mg per day. Our findings exclude a meaningful effect of genotype-guided dosing on the percentage of time in the therapeutic range during the first month of warfarin treatment. However, there was a significant difference in the effects of the algorithms in the prespecified subgroup of black patients, as compared with nonblack patients. Although the interaction between race and dosing strategy with respect to the primary outcome could be due to chance, the analysis was prespecified and was consistent with our a priori hypothesis that there would be race-based differences.
The dosing algorithms that we used in the trial have been validated and account for race (specifically black vs. nonblack).11-13,18 The genotype-guided algorithm performed as well as anticipated on the basis of previous studies,5,8,10-12,18,23 with an R2 of 0.48 and a mean absolute error of 1.3 mg per day for the dose-initiation algorithm and an R2 of 0.69 and a mean absolute error of 1.0 mg per day for the dose-revision algorithm. Despite this accuracy in predicting maintenance doses, there was no benefit of genotype-guided dosing with respect to anticoagulation control.
Observational studies have shown an association between the use of genetic algorithms and improved outcomes, but because of limitations in the study design, they were unable to assess whether the observed associations were causal.1,9,10 Previous clinical trials have produced equivocal results,5-8 but these trials were limited by a small size and lack of blinding to the warfarin dose. The two trials that suggested possible benefit also were limited by large numbers of dropouts6 and a comparison with nonalgorithm-based dosing.8 Previous studies also enrolled either no black patients6-8 or a minimal number of black patients5 (a total of 3) (Anderson J: personal communication).
The average percentage of time in the therapeutic range of 45% in our study is similar to that in other trials, taking into account the range of INRs used for the calculation and the timing and duration of therapy (Tables S9A and S9B in the Supplementary Appendix).5,10,24,25 Unlike previous trials that used only a baseline genotype-guided algorithm, our study used both a dose-initiation and a dose-revision algorithm. A recent study comparing a similar initiation algorithm with a combined initiation and revision algorithm showed no effect on the percentage of time in the therapeutic range with the addition of the revision algorithm.10
There are several questions that our study was not designed to answer. First, the trial did not compare genotype-based dosing with usual care or a fixed initial dose (e.g., 5 mg per day). However, such a comparison could not have discerned whether differences in outcomes were due to the marginal benefit of genetic information or to the use of the clinical information that is included in all genotype-guided dosing algorithms. Second, our study does not address the question of whether a longer duration of genotype-guided dosing would have improved INR control,26 an issue that is being addressed in another trial.27 Third, the dosing algorithms that we used included the three single-nucleotide polymorphisms among the two genes that are most likely to influence warfarin dosing. Although other genes may contribute to warfarin dosing, it is unlikely that they have a substantial effect, particularly in white populations.28 Fourth, although there were no significant between-group differences in the rates of bleeding or thromboembolic events during the primary follow-up period of 4 weeks, the trial was not powered for these outcomes. Fifth, the first dose of warfarin was not informed by genotyping in 55% of the patients; whether this influenced the results is unknown. However, the effect of missing genetics data on day 1 on the dose administered during the first 3 days of therapy was trivial.
In conclusion, our findings do not support the hypothesis that initiating warfarin therapy at a genotype-guided maintenance dose for the first 5 days, as compared with initiating warfarin at a clinically predicted maintenance dose, improves anticoagulation control during the first 4 weeks of therapy. Our results emphasize the importance of performing randomized trials for pharmacogenetics, particularly for complex regimens such as warfarin.

References

1 Ginsburg GS, Voora D. The long and winding road to warfarin pharmacogenetic testing. J Am Coll Cardiol 2010;55:2813-2815
2 Burke W, Laberge AM, Press N. Debating clinical utility. Public Health Genomics 2010;13:215-223
3 Ashley EA, Hershberger RE, Caleshu C, et al. Genetics and cardiovascular disease: a policy statement from the American Heart Association. Circulation 2012;126:142-157
4 Woodcock J, Lesko LJ. Pharmacogenetics — tailoring treatment for the outliers. N Engl J Med 2009;360:811-813
5 Anderson JL, Horne BD, Stevens SM, et al. Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation 2007;116:2563-2570
6 Caraco Y, Blotnick S, Muszkat M. CYP2C9 genotype-guided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomized controlled study. Clin Pharmacol Ther 2008;83:460-470
A complete list of investigators and committees in the Clarification of Optimal Anticoagulation through Genetics (COAG) trial is provided in the Supplementary Appendix, available at NEJM.org.

Editorial

Do Pharmacogenetics Have a Role in the Dosing of Vitamin K Antagonists?

Bruce Furie, M.D.
Nov 19, 2013    http://dx.doi.org/10.1056/NEJMe1313682

 

Article

Vitamin K plays a single role in human biology — as a cofactor for the synthesis of γ-carboxyglutamic acid. This amino acid is a component of at least 14 proteins, including 4 blood-coagulation proteins (factor IX, factor VII, factor X, and prothrombin) and 2 regulatory proteins (protein C and protein S), and it is critical for the physiologic function of these proteins. Humans do not synthesize vitamin K. Rather, we ingest it in our diet. The vitamin K quinone is reduced to the semiquinone, and this reduced vitamin K is a cofactor that is required for the conversion of specific glutamic-acid residues on the vitamin K–dependent proteins to γ-carboxyglutamic acid by the vitamin K–dependent carboxylase. Vitamin K epoxide, a product of this reaction, is converted back to the vitamin K quinone by the vitamin K epoxide reductase, otherwise known as VKOR. This vitamin K cycle can be broken, and a state of vitamin K deficiency at the carboxylase level effected, by the inhibition of VKOR by vitamin K antagonists, including warfarin.
Warfarin and its analogues have been used as oral anticoagulant agents for more than 50 years. By targeting VKOR, the post-translational modification of the vitamin K–dependent blood-coagulation proteins is impaired. A reduced functional level of factor IX, factor VII, factor X, and prothrombin leads to delayed blood coagulation. This inhibition is monitored in the clinical laboratory with the use of the prothrombin time and is corrected for the varied potencies of tissue factor used in the assay by means of a calibration factor, yielding the international normalized ratio (INR). The intensity of therapy with vitamin K antagonists varies according to the indication for anticoagulation, and the INR is adjusted by varying the dose of the vitamin K antagonist.
The goal of therapy is to keep the INR in the therapeutic range, since patients with an INR that is subtherapeutic are at increased risk for thrombosis and patients with an INR that is supratherapeutic are at increased risk for bleeding. Keeping the INR within the therapeutic range can be challenging. Warfarin binds to albumin, and only about 3% is free and pharmacologically active. A number of medications can displace warfarin, leading to its increased activity and subsequent increased rate of degradation. Diet, specifically the intake of foods containing vitamin K, can offset the effect of the daily dose of the vitamin K antagonist. Age, weight, and sex are other factors that influence the dose.
In addition, the catabolic rate of the vitamin K antagonists appears to have a genetic basis. Genetic polymorphisms in the cytochrome P-450 enzyme CYP2C9 include two variants, C144R in CYP2C9*2 and I359L in CYP2C9*3. These variants have substantially reduced activity, as compared with CYP2C9*1, and are associated with reduced clearance and thus a decrease in the warfarin-dose requirement.1 Similarly, mutations in VKOR, the target of the vitamin K antagonists, lead to various degrees of warfarin resistance. Polymorphisms in VKORC1, the gene encoding this protein, lead to variability in the sensitivity to vitamin K antagonists.2
Might genotyping of CYP2C9 and VKORC1 in patients initiating anticoagulant therapy with vitamin K antagonists lead to more precise dosing and, by extrapolation, reduce the risk of thrombotic and bleeding complications? Numerous anecdotal, observational, and small clinical trials have been published on the use of this information, with many authorities promoting this approach.
The results of three large, randomized clinical trials that test this hypothesis have now been published in the Journal.3-5 Although they vary in organization and structure (duration of study, vitamin K antagonist used, double-blind vs. single-blind design, racial characteristics of the study group, and method for dosing in the control group), they are also similar (large, multicenter, randomized studies; primary end point of the time in the therapeutic range; genotyping of CYP2C9 and VKORC1; and the use of the INR target as a biomarker for the risk of bleeding and thrombosis). Importantly, these trials all examine the initiation of therapy with vitamin K antagonists and use as a primary end point the percentage of time that a patient is within the therapeutic range during the initial phase of treatment. The more important end point, the rate of bleeding and thrombotic complications, was beyond the power design of these trials.
Despite design differences, the conclusions of the three studies are similar. In an initial period of 4 weeks of anticoagulation with warfarin, the randomized, double-blind study by Kimmel et al.3 showed results in the study group that included pharmacogenetic information to supplement clinically guided dosing that were nearly identical to the results in the group that used clinically guided dosing alone (percentage of time in the therapeutic INR range, 45.2% vs. 45.4%). In the 12 weeks after the initiation of anticoagulation with acenocoumarol and phenprocoumon, Verhoef et al.4 used a new point-of-care device and found that a genotype-guided algorithm that included clinical variables yielded results that were similar to those achieved with an algorithm based on clinical variables (61.6% vs. 60.2% at 12 weeks). Pirmohamed et al.5 compared genotype-guided dosing of warfarin, also using a point-of-care device, with standard dosing methods used in clinical practice. The results at 12 weeks were 67.4% and 60.3%, which are significantly different albeit similar, indicating a modest improvement.
What can we conclude from these trials? First, we must recall that these trials address the process of the initiation of anticoagulant therapy — during the very first week — and not an approach to intermediate or long-term anticoagulation. Second, it would appear that, despite the variation in trial design, these trials indicate that this pharmacogenetic testing has either no usefulness in the initial dosing of vitamin K antagonists or, at best, marginal usefulness, given the cost and effort required to perform this testing.
Improved safety with the use of vitamin K antagonists is nonetheless an important goal, and it remains so, despite the introduction of new oral anticoagulants. Perhaps we should concentrate on improvements in the infrastructure for INR testing, including better communication among the laboratory, the physician, and the patient (e.g., through social media); in the use of formal algorithms for dosing, without concern for genotype; in patient adherence to therapy and possibly more responsibility for dosing being assumed by the patient; and in increased diligence by medical and paramedical personnel in testing, monitoring, and dosing on the basis of the INR, given the high percentage of medical mismanagement associated with these anticoagulant agents.  http://dx.doi.org/nejm1313682.pdf

References

1 Aithal GP, Day CP, Kesteven PJ, Daly AK. Association of polymorphisms in the cytochrome P450 CYP2C9 with warfarin dose requirement and risk of bleeding complications. Lancet 1999;353:717-719
2 D’Andrea G, D’Ambrosio RL, Di Perna P, et al. A polymorphism in the VKORC1 gene is associated with an interindividual variability in the dose-anticoagulant effect of warfarin. Blood 2005;105:645-649
3 Kimmel SE, French B, Kasner SE, et al. A pharmacogenetic versus a clinical algorithm for warfarin dosing. N Engl J Med 2013. DOI: 10.1056/NEJMoa1310669.
4 Verhoef TI, Ragia G, de Boer A, et al. A randomized trial of genotype-guided dosing of acenocoumarol and phenprocoumon. N Engl J Med 2013. DOI: 10.1056/NEJMoa1311388.
5 Pirmohamed M, Burnside G, Eriksson N, et al. A randomized trial of genotype-guided dosing of warfarin. N Engl J Med 2013. DOI: 10.1056/NEJMoa1311386.

Rapid Warfarin Reversal With 4-Factor Prothrombin Complex Concentrate

Samuel Z. Goldhaber, MD    Nov 07, 2013     Clotblog at theheart.org

Hello. This is Dr. Sam Goldhaber from the Clotblog at theheart.org, speaking to you from Brigham and Women’s Hospital and Harvard Medical School on the important topic of 4-factor prothrombin complex concentrate (4F-PCC), which is the optimal approach to urgent warfarin reversal.
The US Food and Drug Administration only recently approved 4F-PCC to reverse excessive bleeding from warfarin. We have had 3-factor PCC around for a long time but it doesn’t have much factor XII in it. Our European colleagues have had 4F-PCC for the past few years.
I was very pleased recently to have had the opportunity to use 4F-PCC to reverse an intracranial hemorrhage in a patient who had an international normalized ratio (INR) of 2.8 and a spontaneous head bleed. She was receiving warfarin for anticoagulation, and within about 15 minutes the 4F-PCC, along with 10 mg of intravenous vitamin K, returned her INR to normal. Of greater importance, the head bleeding stopped and she regained virtually all of her neurologic function. It seemed miraculous to me and it happened so quickly that it was very gratifying.
Almost simultaneously with my clinical experience, we published an observational study in Circulation [1] with about 300 patients who bled on warfarin. Approximately 80% of these patients were on warfarin because of permanent atrial fibrillation, and they had an average age in the 70s. Initially patients received fresh frozen plasma (before 4F-PCC became available in Canada) and their outcomes with fresh frozen plasma were tracked very carefully. When 4F-PCC came along and practice switched to that therapy, those outcomes were tracked as well.

Clopidogrel Genotyping for Antiplatelet Guidance in MI Stenting: Maybe Reduced Ischemic Risk

Steve Stiles    Nov 06, 2013

SAN FRANCISCO, CA — A novel study of genotype-guided antiplatelet therapy in patients who received a stent for acute MI saw a sharp drop in ischemic events over one year among those who tested positive for a clopidogrel loss-of-function (LOF) gene pattern and had their originally prescribed antiplatelet therapy altered based on the assay results.
In the prospective GIANT trial with 1445 patients, reported here at TCT 2013 , it was discretionary whether clinicians raised the clopidogrel dosage or switched thienopyridine agents based on the assay results, which they had in hand within 48 hours after stenting. Such changes were made in 86% of the 316 who tested positive for the LOF genotype, a group known to be at increased ischemic risk on standard clopidogrel-containing antiplatelet therapy after stenting.
Among those 272 patients with assay-guided antiplatelet changes, the one-year composite risk of death, MI, or stent thrombosis closely matched that of patients lacking the high-risk genotype, according to co–principal investigator Dr Bernard R Chevalier (L’Institut CardioVasculaire Paris-Sud, Massy, France), who presented the study.
Dr Bernard R Chevalier
Of note, the composite end point was about five times higher for the remaining 14% of LOF-genotype patients whose antiplatelet therapy wasn’t changed based the assay.
“These are really the first clinical-trial data in the genotype space compared with the phenotype space, and I think it’s long overdue,” according to Dr Daniel I Simon (University Hospitals Case Medical Center, Cleveland, OH), speaking from the panel charged with critiquing GIANT after its formal presentation. As did many throughout TCT 2013, Simon was weighing two different approaches to sharpening thienopyridine selection for dual-agent antiplatelet therapy after coronary interventions, specifically those focusing on genotyping for the CYP2C19 clopidogrel loss-of-function variant vs platelet-function assays like VerifyNow (Accumetrics).
Such platelet-function testing with coronary stenting has its supporters and detractors but hasn’t found a consistent role in managing patients undergoing PCI, even for acute coronary syndromes, as heartwire has long reported.
One-Year Rates (%) of Primary End Point (Death, MI, or Stent Thrombosis) by Clopidogrel LOF Genotype Status
End point Normal
LOF, treatment is adjusted LOF, treatment is not adjusted
                              n=1118           n=272                     n=55
Primary              3.04                 3.3*                        15.6
 *p=0.83 vs normal; p<0.0001 for noninferiority; p=0.04 vs LOF-treatment-is-not-adjusted
“I think these are amazing results,” Dr Cindy L Grines (Detroit Medical Center Cardiovascular Institute, MI) said at a press briefing on GIANT, referring to both the high event rate in LOF-genotype patients whose treatment wasn’t changed and similarly lower event rates in the other two groups. “Both of those [findings] are a little bit unexpected, I’d guess?” She asked Chevalier why clinicians did not modify antiplatelet therapy in 14% of patients positive for the LOF genotype.
In GIANT, said Chevalier in his presentation, investigators were “strongly recommended” to give such patients prasugrel (Effient, Lilly/Daiichi-Sanyo) or, if they had contraindications to prasugrel, to double their clopidogrel dosage.
But prasugrel, a more potent antiplatelet than clopidogrel, had already been chosen for initial antiplatelet therapy in more than half of patients in the study. Perhaps clinicians believed such patients would benefit from it regardless of their ultimate genotype status. Indeed, some patients later found not to have the clopidogrel LOF genotype were switched from prasugrel to clopidogrel, perhaps satisfied by the assay that the latter drug would be adequate after all.
Chevalier speculated that clinicians also may not have boosted antiplatelet therapy in some LOF-genotype patients if it was considered too risky, such as for those with bleeding risk factors. The high event rate in patients with the LOF genotype whose antiplatelet therapy wasn’t adjusted, therefore, may be more related to how sick the patient was, rather than any cues from genotyping. He said his group is currently looking for the answer in further analyses.
Prevalence of Thienopyridine Use and Dosages, Before and After Genotyping, by Assay Outcome
Thienopyridine and dosage by timing
n=1118                                     treatment is  adjusted,   (%)                 n=272 (%)
                                                                           Normal,     LOF          p
Clopidogrel 75 mg/d (preassay)           35.6           34.7      NS
Clopidogrel 75 mg/d (postassay)        44.5             0       <0.001
Clopidogrel 150 mg/d (preassay)        10               9.1         NS
Clopidogrel 150 mg/d (postassay)    8.9             16.8   <0.05
Prasugrel 10 mg/d (preassay)            53.3           55.5       NS
Prasugrel 10 mg/d (postassay)         46.1            83.1    <0.001
NS=nonsignificant
GIANT was funded by Biotronik. Chevalier discloses consulting for or receiving research grants or speaker fees from Abbott Vascular, Asahi, Astra Zeneca, AVI, Boston Scientific, Biotronik, Colibri, Cook, Cordis, Daiichi Sankyo, Eli-Lilly, Iroko, Medtronic, and Terumo and being general director of and owning equity interest in the European Cardiovascular Research Center.

 Bivalirudin Started during Emergency Transport for Primary PCI

Philippe Gabriel Steg, M.D., Arnoud van ‘t Hof, M.D., Ph.D., Christian W. Hamm, M.D., Peter Clemmensen, M.D., Ph.D., Frédéric Lapostolle, M.D., Ph.D., Pierre Coste, M.D., Jurrien Ten Berg, M.D., Ph.D., Pierre Van Grunsven, M.D., Gerrit Jan Eggink, M.D., Lutz Nibbe, M.D., Uwe Zeymer, M.D., Marco Campo dell’ Orto, M.D., Holger Nef, M.D., Jacob Steinmetz, M.D., Ph.D., Louis Soulat, M.D., Kurt Huber, M.D., Efthymios N. Deliargyris, M.D., Debra Bernstein, Ph.D., Diana Schuette, Ph.D., Jayne Prats, Ph.D., Tim Clayton, M.Sc., Stuart Pocock, Ph.D., Martial Hamon, M.D., and Patrick Goldstein, M.D. for the EUROMAX Investigators

N Engl J Med 2013; 369:2207-2217December 5, 2013DOI: 10.1056/NEJMoa1311096

 

 Background

Bivalirudin, as compared with heparin and glycoprotein IIb/IIIa inhibitors, has been shown to reduce rates of bleeding and death in patients undergoing primary percutaneous coronary intervention (PCI). Whether these benefits persist in contemporary practice characterized by prehospital initiation of treatment, optional use of glycoprotein IIb/IIIa inhibitors and novel P2Y12 inhibitors, and radial-artery PCI access use is unknown.

 

 Methods

We randomly assigned 2218 patients with ST-segment elevation myocardial infarction (STEMI) who were being transported for primary PCI to receive either bivalirudin or unfractionated or low-molecular-weight heparin with optional glycoprotein IIb/IIIa inhibitors (control group). The primary outcome at 30 days was a composite of death or major bleeding not associated with coronary-artery bypass grafting (CABG), and the principal secondary outcome was a composite of death, reinfarction, or non-CABG major bleeding.

 Results

Bivalirudin, as compared with the control intervention, reduced the risk of the primary outcome (5.1% vs. 8.5%; relative risk, 0.60; 95% confidence interval [CI], 0.43 to 0.82; P=0.001) and the principal secondary outcome (6.6% vs. 9.2%; relative risk, 0.72; 95% CI, 0.54 to 0.96; P=0.02). Bivalirudin also reduced the risk of major bleeding (2.6% vs. 6.0%; relative risk, 0.43; 95% CI, 0.28 to 0.66; P<0.001). The risk of acute stent thrombosis was higher with bivalirudin (1.1% vs. 0.2%; relative risk, 6.11; 95% CI, 1.37 to 27.24; P=0.007). There was no significant difference in rates of death (2.9% vs. 3.1%) or reinfarction (1.7% vs. 0.9%). Results were consistent across subgroups of patients.

 Conclusions

Bivalirudin, started during transport for primary PCI, improved 30-day clinical outcomes with a reduction in major bleeding but with an increase in acute stent thrombosis. (Funded by the Medicines Company; EUROMAX ClinicalTrials.gov number, NCT01087723.)

  Source Information

The authors’ affiliations are listed in the Appendix.
Dr. Steg at Cardiologie, Département Hospitalo-Universitaire FIRE, Hôpital Bichat, Assistance Publique–Hôpitaux de Paris,  Paris, France, or at gabriel.steg@bch.aphp.fr.
A complete list of the European Ambulance Acute Coronary Syndrome Angiography (EUROMAX) investigators is provided in the Supplementary Appendix, available at NEJM.org.

 

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Hyperhomocysteinemia interaction with Protein C and Increased Thrombotic Risk

Reporter and Curator: Larry H Bernstein, MD, FCAP

 

This document explores the relationship between thromboembolic risk related to hyperhomocysteinemia related to the HHcy interaction with and blocking the protective effect of APC.

Previous Venous Thromboembolism Relationships With Plasma Homocysteine Levels

Marco Cattaneo, Franca Franchi, Maddalena L. Zighetti, Ida Martinelli, Daniela Asti, P. Mannuccio Mannucci
Arterioscler Thromb Vasc Biol. 1998;18:1371-1375.
Received January 28, 1998; revision accepted March 16, 1998. From the Angelo Bianchi Bonomi Hemophilia and Thrombosis Center, Institute of Internal Medicine, IRCCS Ospedale Maggiore, University of Milano, Italy.
Correspondence to Marco Cattaneo, MD, Hemophilia and Thrombosis Center, Via Pace 9, 20122 Milano, Italy. E-mail marco.cattaneo@unimi.it © 1998 American Heart Association, Inc. 1371 Original Contributions

Abstract—

The proteolytic enzyme activated protein C (APC) is a normal plasma component, indicating that protein C (PC) is continuously activated in vivo. High concentrations of homocysteine (Hcy) inhibit the activation of PC in vitro;

  • this effect may account for the high risk for thrombosis in patients with hyperhomocysteinemia (HyperHcy).

We measured the plasma levels of APC in 128 patients with previous venous thromboembolism (VTE) and in 98 age- and sex-matched healthy controls and

  • correlated them with the plasma levels of total Hcy (tHcy) measured before and after an oral methionine loading (PML).

Forty- eight patients had HyperHcy and 80 had normal levels of tHcy. No subject was known to have any of the congenital or acquired thrombophilic states at the time of the study.  Because the plasma levels of APC and PC were correlated in healthy controls,  the APC/PC ratios were also analyzed.

Plasma APC levels and APC/PC ratios were significantly higher in VTE patients than in controls (P < 0.03 and 0.0004, respectively).

  • Most of the increase in APC levels and APC/PC ratios were attributable to patients with HyperHcy.

Patients with normal tHcy had intermediate values, which did not differ significantly from those of healthy controls.

  • There was no correlation between the plasma levels of tHcy or its PML increments and APC or APC/PC ratios in controls.
  • The fasting plasma levels of APC and APC/PC ratios of 10 controls did not increase 4 hours PML, despite a 2-fold increase in tHcy.

This study indicates that

  • APC plasma levels are sensitive markers of activation of the hemostatic system in vivo and
  • that Hcy does not interfere with the activation of PC in vivo.

Key Words: homocysteine, protein C, thromboembolism, activated protein C, hypercoagulability,  T mechanism.

The zymogen protein C is converted to the active protease, activated protein C (APC),

  • through proteolytic cleavage by thrombin bound to its endothelial membrane receptor thrombomodulin.1

The demonstration that APC is a normal plasma component,2,3whose enzymatic activity can be detected with specific and sensitive methods,4,5indicates that

  • the protein C anticoagulant pathway is continuously activated in vivo.

Measurement of APC plasma levels might therefore be helpful in determining the in vivo integrity of the protein C anticoagulant pathway. More generally,

  • APC levels might mirror the in vivo activation of the coagulation system and
  • serve as a marker of thrombin activity in the circulation.4

The mechanism(s) by which a moderate elevation of plasma levels of homocysteine (Hcy) increases the risk for arterial and venous thrombotic disease is still unclear.6,7 In vitro studies showed that

  • Hcy inhibits the thrombomodulin- dependent protein C activation to APC and
  • interferes with the expression of thrombomodulin on human umbilical vein endothelial cells.8–10

These findings may be relevant to unravel the thrombogenic mechanism of Hcy, because

the protein C anticoagulant system is of major physiological importance in the regulation of the hemostatic  congenital or acquired disorders

  • characterized by impaired production or function of APC are associated with a high risk for venous thromboembolism (VTE).11

It must be noted, how ever, that these in vitro findings have been obtained by using very high concentrations of Hcy,

  • at least 1 order of magnitude higher than the plasma concentrations found in patients with homozygous homocystinuria.12,13

Their clinical relevance is therefore uncertain and awaits confirmation from ex vivo and/or in vivo studies in humans. In this study, we compared the plasma levels of APC with those of the prothrombin fragment F1,2, a marker of thrombin generation,14in healthy subjects and patients with previous episodes of VTE and

  • tested whether the levels are affected by plasma Hcy concentrations.

Methods

Materials

L-Methionine, tri-n-butylphosphine, 7-fluoro-2,1,3-benzoxadiazole- 4-sulfonamide (ABDF), L-cystine, Tween 20, Tween 80, benzamidine, and HEPES were from Sigma. (4-Amidinophenyl)-methanesulfonylfluoride (APMSF) was from Boehringer, BSA from Calbiochem, and the chromogenic substrate L-homocystine, ovalbumin, S-2366 from Chromogenics. The monoclonal antibody directed against the light chain of protein C (C3-Mab) was a kind gift of Dr H.P. Schwarz (Immuno, Vienna, Austria). All other chemicals were of reagent grade. Subjects We studied 128 patients with previous VTE and 98 healthy controls. All diagnoses of thrombotic episodes, excluding those of superficial veins, had been confirmed by objective methods: compression ultrasonography or venography for deep vein thrombosis; and ventilation/perfusion scintigraphy for pulmonary embolism. The contemporary presence of deep vein thrombosis in patients with superficial vein thrombosis had not been excluded by objective methods. Table 1 shows the characteristics of the patients studied.

They belonged to a cohort of 315 patients who had been screened for thrombophilic states at our Center between December 1993 and July 1995 and were selected on the basis of the following characteristics:
(1) absence of congenital or acquired thrombophilic states except hyperhomocysteinemia (HyperHcy) (see below);
(2) oral anticoagu- lant therapy discontinued at least 1 month before screening;
(3) at least 4 months elapsed since the last thrombotic episode; and
(4) willingness to participate in the study.

The screening for thrombophilia included the following tests:

  • prothrombin time;
  • activated partial thromboplastin time;
  • thrombin time;
  • plasma levels of fibrinogen,
  • protein C,
  • protein S, and
  • antithrombin;
  • APC resistance; and
  • screening for antiphospholipid syndrome15 and
  • plasma levels of total homocysteine (tHcy)

before and 4 hours after an oral methionine load. Patients with abnormal APC resistance were also screened for factor V Leiden.16

The study was designed and completed before the demonstration that the mutation G20210A of the prothrombin gene is a risk factor for deep vein thrombosis.17 This mutation therefore was looked for retrospectively only in those subjects whose DNA was still available for analysis (all controls and 50 patients): 5 patients (10%) and 2 controls (2.1%) were heterozygous for the mutation. Of the 128 patients enrolled in the study,

  • 48 had hyperhomocysteinemia (VTE-HyperHcy) according to the diagnostic criteria outlined below, and
  • 80 had normal Hcy levels (VTE-NormoHcy).
    • The healthy controls, who were age and sex matched with the patients (male/female, 50/45; median age, 40 years [range, 20 to 73 years]), had been chosen from the same geographical area and with the same socioeconomic background as the patients.
  1. Previous episodes of thrombosis had been ruled out by a validated structured questionnaire.18
  2. No subject had abnormal liver or renal function, or overt autoimmune or neoplastic disease.
  3. Informed consent to participate in the study was obtained from all subjects.
  4. The study was approved by the ethics committee of the University of Milano.

Study Protocol

After an overnight fast, blood samples were drawn between 8:30 and 9:30 AM in K3-EDTA for measurement of total Hcy (tHcy), in 0.013 mol/L trisodium citrate for measurement of F1?2 and protein C, and in citrate plus 0.03 mol/L benzamidine (a reversible inhibitor of APC) for measurement of APC. L-Methionine (3.8 g/m2body surface area) was then administered orally in approximately 200 mL of orange juice. Four hours later, a second blood sample was collected in EDTA for tHcy measurement from all subjects and in citrate plus benzamidine for measurement of APC plasma levels from 10 controls. All subjects remained in the fasting state until the second blood sample had been taken. Plasma Hcy Assay Blood samples in K3-EDTA were immediately placed on ice and centrifuged at 2000xG, 4°C, for 15 minutes. The supernatant was stored in aliquots at < 70°C until assay.
The plasma levels of tHcy (free and protein bound) were determined by high-performance liquid chromatography (Waters Millipore 6000A pump, Millipore) and fluorescence detection (Waters 474) by the method of Ubbink et al,19with slight modifications.20 Briefly, 100 uL of plasma was incubated with 10 uL of 10% tri-n-butylphosphine in dimethylfor- mamide at 4°C for 30 minutes to reduce homocystine and mixed disulfide and deconjugate Hcy from plasma proteins. Then, 100 uL of 10% trichloroacetic acid was added, and the mixture was centrifuged in an Eppendorf microcentrifuge at 13 000 rpm for 10 minutes.
After centrifugation, the mixture was incubated with 1 mg/mL ABDF in borate buffer to derivatize the thiols. The mobile phase, pumped at 1 mL/min, consisted of 0.1 mol/L potassium dihydrogenophosphate, 0.06 mmol/L EDTA, and 12% acetonitrile (pH = 2.1).

Criteria for Diagnosis of HyperHcy  HyperHcy was diagnosed when
  1. fasting plasma levels of tHcy or its postmethionine load absolute increments above fasting levels exceeded the 95th percentiles of distribution of values obtained in 388 healthy controls.
Measurement of Plasma APC  Plasma APC levels were measured with < enzyme capture assay, essentially as described by Gruber and Griffin.4 Blood samples were

TABLE 1.
Patients With Previous VTE-NormoHcy

Demographic Characteristics of Patients With Previous VTE-HyperHcy
VTE-HyperHcyVTE-NormoHcy                                                                                                        4880
No. Males/females                                                                                                                                                23/25
Median age, y (range)                                                                                                                                     36 (19–69)
Median age at the first thrombotic episode, y (range)                                                                     32 (17–62)
Time elapsed since last episode, mo (range)                                                                                        14 (4–70)
Time elapsed since discontinuation of oral anticoagulant therapy, mo (range)                   11 (1–64)Type of first thrombotic episode
Deep vein thrombosis                                                                                                                                       31/49
Pulmonary embolism                                                                                                                                    36 (14–62)
Superficial vein thrombosis                                                                                                                       31 (13–60)
Venous thrombosis of other sites                                                                                                           14 (4–90)                                                                                                                                                                          
With 1 or more episodes                                                                                                                              11 (1–70)
2233                                                                                                                                                                    26 (54.2%)
With circumstantial risk factors* at first episode                                                                             44 (55%)
*The following circumstantial risk factors were considered: surgery (26), trauma (50), immobilization (47), pregnancy/puerperium (16,21), and oral contraceptives (22).

1372

Activated Protein C, Thrombosis, and Homocysteine

centrifuged within 60 minutes from collection at 1200xG, 4°C, for 30 minutes to obtain platelet-poor plasma, which was frozen in aliquots at < 70°C. A plasma pool from 30 healthy individuals (15 men, 15 women) was obtained in the same way and used to prepare the standards.
(removed)…  The chromogenic substrate for APC S-2366 (0.46 mmol/L in Tris-buffered saline, pH 7.4) was then added to the wells. After incubation of the sealed plates at 4°C in wet chambers for 3 weeks, hydrolysis of the substrate was monitored at a dual wavelength setting of 405/655 nm.
The concentration of APC in the unknown samples was calculated from the absorbance of each sample with the standard curve as a reference. Results were expressed as percentage of pooled normal plasma. Measurement of Plasma F1?2 F1?2 was assayed by a commercial ELISA (Behringwerke), as previously described.21

Statistical Analysis

The two-tailed t test was used to compare VTE patients and healthy controls. ANOVA was used to compare VTE-HyperHcy, VTE controls, and healthy controls, followed by the Dunnett’s test for internal contrasts. The Pearson r value was calculated for correla- tions between the variables studied.

Results

The results obtained in all VTE patients and controls are presented, including those with the heterozygous G20210A mutation of the prothrombin gene. A subanalysis of the results obtained in the 40 patients and 98 controls, in whom the mutation was looked for, revealed that

  • exclusion of the subjects heterozygous for the mutation did not significantly affect the results.

Plasma tHcy Levels

The mean (SD) fasting levels of plasma tHcy were significantly higher in VTE-HyperHcy (28.8?19.5 ?mol/L) than in VTE-NormoHcy (12.0+5.2, P<0.001) and healthy con- trols (11.0+5.3, P<0.001). The mean postmethionine load increments of tHcy above fasting levels were also higher in VTE-HyperHcy (32.9+13.5 umol/L) than in VTE- NormoHcy (19.8+7.5, P<0.001) and healthy controls (16.1+7.6, P<0.001). Differences between VTE-NormoHcy and healthy controls were not statistically significant. Six healthy controls (6.3%) had HyperHcy, according to the diagnostic criteria previously outlined. Plasma Levels of APC Healthy Controls The mean plasma level of APC in healthy controls was 116(20%). There was a statistically significant correlation between the plasma levels of APC and those of protein C (r?0.48, P?0.001) (Figure 1). Therefore, because APC levels are influenced by the concentration of their zymogen, both the absolute APC levels and the activated protein C/protein C (APC/PC) ratios were used for subsequent analysis. The mean value of the APC/PC ratio in healthy controls was 1.01?0.2.

There was no correlation between the plasma levels of APC (not shown) or the APC/PC ratios and the fasting plasma levels of tHcy (Figure 2) or its postmethionine load increments above fasting levels (not shown). The mean APC plasma levels and APC/PC ratios were similar in healthy controls whose tHcy plasma levels fell within the first (115 and 1.0), second (118 and 0.96), or third (115 and 1.01) tertiles of distribution. The mean fasting plasma levels of APC and the APC/PC ratios of 10 healthy controls

– did not significantly differ from those measured in the same subjects 4 hours after an oral methionine load,
– which increased the concentration of tHcy by more than 2-fold (Table 2).

VTE Patients

The mean plasma levels of APC and APC/PC ratios were higher in VTE patients than in healthy controls (124?32 versus 116?20, P?0.03 and 1.12?0.32 versus 0.99?0.19, P?0.0004). This difference was mostly due to VTE- HyperHcy patients whose plasma APC levels and APC/PC ratios were significantly higher than those of healthy controls (Table 3). In contrast, differences between VTE-NormoHcy and healthy controls and between VTE-HyperHcy and VTE- NormoHcy did not reach statistical significance (Table 3). Results did not change substantially when we excluded patients with thrombosis of the superficial veins (APC levels, 124+26 in VTE-HyperHcy and 121?31 in VTE-NormoHcy; APC/PC ratio, 1.17?0.25 in VTE-HyperHcy and 1.09?0.3 Figure 1. Correlation between the plasma levels of protein C and APC in 98 healthy volunteers. Values are expressed as per- centage of the concentrations measured in pooled normal plasma from 30 healthy blood donors. Figure 2. Correlation between the fasting plasma levels of tHcy and APC/PC ratios of 98 healthy volunteers. Cattaneo et al September 1998 1373 in VTE-NormoHcy) or women taking oral contraceptives (APC levels, 115?19 in controls, 130?29 in VTE- HyperHcy, and 121+33 in VTE-NormoHcy; APC/PC ratio, 0.98?0.23 in controls, 1.13?0.4 in VTE-HyperHcy, and 1.08?0.3 in VTE-NormoHcy). The prevalence of high APC/PC ratios was significantly higher in VTE patients than in controls, independent of the tHcy levels in their plasma (Table 4),

-whereas that of high plasma APC levels was significantly increased in VTE- HyperHcy patients only (Table 4).

Plasma Levels of F1?2

The mean plasma level of F1?2 in VTE patients (1.6?0.5 nmol/L) did not significantly differ from that measured in healthy controls (1.5?0.6 nmol/L). There was no statistically significant difference between plasma levels of F1?2 in VTE-HyperHcy (1.6?0.6 nmol/L), VTE-NormoHcy (1.6?0.6 nmol/L), and healthy controls. The mean F1?2 plasma levels were similar in healthy controls whose plasma levels of tHcy fell within the first, second, or third tertiles of distribution (not shown). F1?2 levels and APC/PC ratios were significantly correlated in controls (r?0.28, P?0.005) but not in VTE-HyperHcy (r? ?0.03, P?0.05) or VTE- NormoHcy (r?0.08, P?0.05).

Discussion

This study shows that

–  patients with previous episodes of VTE have higher circulating plasma levels of APC than healthy controls, particularly if they have HyperHcy.

The patients studied had none of the known congenital or acquired thrombophilic states, in which

–  the circulating levels of markers of activation of the coagulation system may be increased.21–24Even
– though the recently described G20210A mutation of the prothrombin gene17could be looked for retrospectively in only approximately one third of the pa- tients, also those patients in whom the prothrombin mutation was ruled out had high APC levels,
– excluding that they were mainly due to the presence of the mutation.

APC is generated from its plasma precursor, protein C, on activation by thrombin-thrombomodulin complex on the endothelial cell surface, probably acting in concert with the endothelial cell protein C receptor.1Subcoagulant amounts of thrombin in the circulation may increase the plasma levels of endogenous APC, which can therefore be considered markers of a hypercoagulable state.4Accordingly, the high APC plasma levels that we measured in patients with previous episodes of VTE may be interpreted as an index of ongoing thrombin formation,
despite the fact that at least 4 months (and a median of 14 months) elapsed since their last thrombotic episode. However,

–  the plasma concentrations of F1?2, a marker of thrombin generation, were not increased signifi cantly in the same VTE patients and were not correlated with APC levels or APC/PC ratios.

In contrast to VTE patients, a statistically significant correlation between APC and F1?2 plasma levels was found in healthy controls. On the basis of these data, we hypothesize that

–  the increased plasma levels of APC found in patients with previous episodes of VTE are not caused by heightened thrombin generation but by alternative mechanisms. Although we did not measure markers of activation of the fibrinolytic system,

– the possibility that high plasma levels of plasmin could be responsible for protein C activation25in these patients should be considered.

The greatest increase of APC plasma levels in VTE patients was observed in subjects with fasting and/or postmethionine-loading HyperHcy. VTE patients with nor mal plasma levels of tHcy had lower concentrations of APC than patients with HyperHcy, but this

–  difference could be due to chance alone, because it was not statistically significant. These results contrast with the alleged inhibitory effect of Hcy on protein C activation that was shown in in vitro studies.8–10

Our data obtained in healthy individuals

– support the view that Hcy does not affect protein C activation in vivo, because the
– mean plasma levels of APC of subjects in the highest tertile of distribution of tHcy levels were not different from those of subjects in the lowest tertile. Moreover,
– the rapid increase in plasma tHcy brought about by an oral methionine load did not affect the concentration of circulating APC

TABLE 2. Healthy Controls Before and 4 Hours After Methionine Loading (PML) Plasma Levels tHcy, APC, and APC/PC Ratios in 10 tHcy, ?mol/LAPC, %APC/PC Ratio Baseline 4 h PML* P† 10.5?3.8 29.5?7.6 0.0001 118?43 113?32 0.57 0.98?0.2 0.95?0.1 0.7 Data are mean?SD. *Methionine was given orally at a dose of 3.8 g/m2body surface area. †t test for paired samples. TABLE 4. APC/PC Ratios in Healthy Controls, Patients With Previous VTE-HyperHcy, and Patients With Previous VTE-NormoHcy Prevalences of High Plasma Levels of APC and Subjectsn With High APC LevelsWith High APC/PC Ratio n (%)OR (95% CI) n (%)OR (95% CI) Healthy controls 98 10 (10.2) 1.0 (reference) 10 (10.2) 1.0 (reference) VTE-HyperHcy48 12 (25.0) 2.9 (1.1–8.3) VTE-NormoHcy80 16 (20.0) 2.2 (0.9–5.7) 16 (33.3) 4.4 (1.7–11.4) 22 (27.5) 3.3 (1.4–8.1) CI indicates confidence interval. The cutoff points, which corresponded to the 90th percentiles of distribution among healthy controls, were 143.1% for APC levels and 1.22 for APC/PC ratios.

TABLE 3. Controls, Patients With Previous VTE-HyperHcy, and Patients With Previous VTE-NormoHcy

Plasma Levels of APC and APC/PC Ratios in Healthy Subjects nAPC,* %APC/PC Ratio† Healthy controls VTE-HyperHcy VTE-NormoHcy P (ANOVA) 98 48 80 116?20 128?29 121?33 0.03 0.99?0.19 1.15?0.33 1.10?0.31 0.002 Data are mean?SD. *VTE-HyperHcy versus VTE-NormoHcy (Dunnett’s test), P?NS; VTE- HyperHcy versus healthy controls, P?0.01; VTE-NormoHcy versus healthy controls, P?NS. †VTE-HyperHcy versus VTE-NormoHcy (Dunnett’s test), P?NS; VTE- yperHcy versus healthy controls, P?0.001; VTE-NormoHcy versus healthy controls, P?0.01. 1374

Activated Protein C, Thrombosis, and Homocysteine

Therefore, the results of our study suggest that Hcy does not negatively influence the plasma APC levels and argue against the hypothesis that

– it inhibits the activation of protein C in vivo by interfering with the activity of thrombomodulin.

Recently, Lentz et al,26in an experimental study of mon- keys with diet-induced moderate HyperHcy, showed that

– the thrombin-stimulated endothelium of aortas from hyperhomocysteinemic animals activated protein C in vitro less effectively than that of control animals.

This study, which supports the hypothesis that Hcy interferes with protein C activation, is in apparent contradiction with our results. At least two possible explanations for their different results can be proposed.

First, Hcy would not affect protein C activation that is ongoing in vivo under physiological conditions, whereas it would interfere with its activation at sites at which athero- genic or thrombogenic stimuli injured the endothelium and increased the local concentration of thrombin.
Second, due to the different relative densities of endothelial cell protein C receptor and thrombomodulin on the endothelium of large vessels and capillaries,1the regulation of protein C activation may differ in the two vascular districts. Although Lentz et al26 measured protein C activation by the endothelium of the aorta, we measured circulating APC, which mostly reflects protein C activation occurring in the microcirculation.

On the basis of the considerations above, we speculate that
– Hcy does not interfere with protein C activation ongoing in the micro- circulation under physiological conditions, whereas
– it could inhibit protein C activation on large, injured vessels.

In conclusion, our study shows that APC plasma levels are high in patients with previous episodes of VTE in whom the plasma levels of F1?2 are normal. Therefore, APC plasma levels represent a sensitive marker of activation of the hemostatic system. In addition, the study showed that high Hcy levels are not associated with heightened thrombin generation and do not interfere with the activation of protein C under physiological conditions in vivo. Further studies are needed to unravel the mechanism(s) by which HyperHcy increases the risks for atherosclerosis and thrombosis.

References

1. Esmon CT, Ding W, Yasuhiro K, Gu J-M, Ferrel G, Regan LM, Stearns- Kurosawa DJ, Kurosawa S, Mather T, Laszik Z, Esmon NL. The protein C pathway: new insights. Thromb Haemost. 1997;78:70–74.
2. Bauer KA, Kass BL, Beeler DL, Rosenberg RD. Detection of protein C activation in humans. J Clin Invest. 1984;74:2033–2041.
3. Heeb MJ, Mosher D, Griffin JH. Inhibition and complexation of activated protein C by two major inhibitors in plasma. Blood. 1989;73:446–454.
4. Gruber A, Griffin JH. Direct detection of activated protein C in blood from human subjects. Blood. 1992;79:2340–2348.
5. Espan ˜a F, Zuazu I, Vicente V, Estelle ´s A, Marco P, Aznar J. Quantifi- cation of circulating activated protein C in human plasma by immuno- assays: enzyme levels are proportional to total protein C levels. Thromb Haemost. 1996;75:56–61.
6. Cattaneo M. Hyperhomocysteinemia: a risk factor for arterial and venous thrombotic disease. Int J Clin Lab Res. 1997;27:139–144.
7. Harpel PC, Zhang X, Borth W. Homocysteine and hemostasis: patho- genetic mechanisms predisposing to thrombosis. J Nutr. 1996;126: 1285S–1289S.
8. Rodgers GM, Conn MT. Homocysteine, an atherogenic stimulus, reduces protein C activation by arterial and venous endothelial cells. Blood. 1990;75:895–901.
9. Lentz SR, Sadler JE. Inhibition of thrombomodulin surface expression and protein C activation by the thrombogenic agent homocysteine. J Clin Invest. 1991;88:1906–1914.
10. Hayashi T, Honda G, Suzuki K. An atherogenic stimulus homocysteine inhibits cofactor activity of thrombomodulin and enhances thrombo- modulin expression in human umbilical vein endothelial cells. Blood. 1992;79:2930–2936.
saee original manuscript for further referencesz  and for figures (not shown)

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Cardiology, Genomics and Individualized Heart Care: Framingham Heart Study (65 y-o study) & Jackson Heart Study (15 y-o study)

Cardiology, Genomics and Individualized Heart Care

Curator: Aviva Lev-Ari, PhD, RN

Article ID #90: Cardiology, Genomics and Individualized Heart Care: Framingham Heart Study (65 y-o study) & Jackson Heart Study (15 y-o study). Published on 12/1/2014

WordCloud Image Produced by Adam Tubman

 

The topic of Cardiology, Genomics and Individualized Heart Care is been developed in the following forthcoming e-Book on a related subject matter:

Curators: Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

This e-Book has the following Parts:

PART 1
Genomics and Medicine

Introduction to Volume Three
1.1: Genomics and Medicine: The Physician’s View
1.2: Ribozymes and RNA Machines – Work of Jennifer A. Doudn
1.3: Genomics and Medicine: The Geneticist’s View
1.4: Genomics in Medicine – Establishing a Patient-Centric View of Genomic Data

PART 2
Epigenetics- Modifiable Factors Causing Cardiovascular Diseases

2.1 Diseases Etiology

2.1.1 Environmental Contributors Implicated as Causing Cardiovascular Diseases
2.1.2 Diet: Solids and Fluid Intake
2.1.3 Physical Activity and Prevention of Cardiovascular Diseases
2.1.4 Psychological Stress and Mental Health: Risk for Cardiovascular Diseases
2.1.5 Correlation between Cancer and Cardiovascular Diseases
2.1.6 Medical Etiologies for Cardiovascular Diseases: Evidence-based Medicine – Leading DIAGNOSES of Cardiovascular Diseases, Risk Biomarkers and Therapies
2.1.7 Signaling Pathways
2.1.8 Proteomics and Metabolomics

2.2 Assessing Cardiovascular Disease with Biomarkers

2.2.1 Issues in Genomics of Cardiovascular Diseases
2.2.2 Endothelium, Angiogenesis, and Disordered Coagulation
2.2.3 Hypertension BioMarkers
2.2.4 Inflammatory, Atherosclerotic and Heart Failure Markers
2.2.5 Myocardial Markers

2.3  Therapeutic Implications: Focus on Ca(2+) signaling, platelets, endothelium

2.3.1 The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and Ryanodine Receptors

2.3.2 Platelets in Translational Research ­ 2

2.3.3 The Final Considerations of the Role of Platelets and Platelet Endothelial Reactions in Atherosclerosis

2.3.4 Nitric Oxide Synthase Inhibitors (NOS-I)

2.3.5 Resistance to Receptor of Tyrosine Kinase

2.3.6 Oxidized Calcium Calmodulin Kinase and Atrial Fibrillation

2.3.7 Advanced Topics in Sepsis and the Cardiovascular System at its End Stage

2.4 Comorbidity of Diabetes and Aging

PART 3
Determinants of Cardiovascular Diseases
Genetics, Heredity and Genomics Discoveries

Introduction
3.1 Why cancer cells contain abnormal numbers of chromosomes (Aneuploidy)
3.2 Functional Characterization of Cardiovascular Genomics: Disease Case Studies @ 2013 ASHG
3.3 Leading DIAGNOSES of Cardiovascular Diseases covered in Circulation: Cardiovascular Genetics, 3/2010 – 3/2013
3.4  Commentary on Biomarkers for Genetics and Genomics of Cardiovascular Disease

PART 4
Individualized Medicine Guided by Genetics and Genomics Discoveries

4.1 Preventive Medicine: Cardiovascular Diseases
4.2 Gene-Therapy for Cardiovascular Diseases
4.3 Congenital Heart Disease/Defects
4.4 Pharmacogenomics for Cardiovascular Diseases

SOURCE

http://pharmaceuticalintelligence.com/biomed-e-books/series-a-e-books-on-cardiovascular-diseases/volume-three-etiologies-of-cardiovascular-diseases-epigenetics-genetics-genomics/

The Next Frontier in Heart Care

Research Aims to Personalize Treatment With Genetics

Nov. 25, 2013 7:18 p.m. ET

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http://online.wsj.com/news/articles/SB10001424052702304281004579220373600912930#!

Two influential heart studies are joining forces to bring the power of genetics and other 21st century tools to battle against heart disease and stroke. Ron Winslow and study co-director Dr. Vasan Ramachandran explain. Photo: Shubhangi Ganeshrao Kene/Corbis.

Scientists from two landmark heart-disease studies are joining forces to wield the power of genetics in battling the leading cause of death in the U.S.

Cardiologists have struggled in recent years to score major advances against heart disease and stroke. Although death rates have been dropping steadily since the 1960s, progress combating the twin diseases has plateaued by other measures.

Genetics has had a profound impact on cancer treatment in recent years. Now, heart-disease specialists hope genetics will reveal fresh insight into the interaction between a

  • person’s biology,
  • living habits and
  • medications

that can better predict who is at risk of a heart attack or stroke.

“There’s a promise of new treatments with this research,” said Daniel Jones, chancellor of the University of Mississippi and former principal investigator of the 15-year-old Jackson Heart Study, a co-collaborator in the new genetics initiative.

Scienc e Source /Photo Researchers Inc. (hearts); below, l-r: Boston University; Robert Jordan/Univ. of Miss.; Jay Ferchaud/Univ. of Miss Medical Center

Prevention efforts also could improve with the help of genetics research, Dr. Jones said. For example, an estimated 75 million Americans currently have high blood pressure, or hypertension, but only about half of those are able to control it with medication. It can take months of trial-and-error for a doctor to get the right dose or combination of pills for a patient. Researchers hope genetic and other information might enable doctors to identify subgroups of hypertension that respond to specific treatments and target patients with an appropriate therapy.

Also collaborating on the genetics project is the 65-year-old Framingham Heart Study. Its breakthrough findings decades ago linked heart disease to such factors as smoking, high blood pressure and high cholesterol. Framingham findings have been a foundation of cardiovascular disease prevention policy for a half-century.

More than 15,000 people have participated in the Framingham study. The Jackson study, with more than 5,000 participants, was launched in 1998 to better understand risk factors in African-Americans, who were underrepresented in Framingham and who bear a higher burden of cardiovascular disease than the rest of the population. Both studies are funded by the National Heart, Lung, and Blood Institute, part of the National Institutes of Health.

Exactly how the collaboration, announced last week, will proceed hasn’t been determined. One promising area is the “biobank,” the collection of more than one million blood and other biological samples gathered during biennial checkups of Framingham study participants going back more than a half century.

The samples are stored in freezers in an underground earthquake-proof facility in Massachusetts, said Vasan Ramachandran, a Boston University scientist who takes over at the beginning of next year as principal investigator of the Framingham Heart Study. Another 40,000 samples from the Jackson study are kept in freezers in Vermont. By subjecting samples to DNA sequencing and other tests, researchers say they may be able to identify variations linked to progression of cardiovascular disease—or protection from it.

Each study is likely to enroll new participants as part of the collaboration to allow tracking of risk factors and diet and exercise habits, for instance, in real time instead of only during infrequent checkups.

Heart disease is linked to about 800,000 deaths a year in the U.S. In 2010, some 200,000 of those deaths could have been avoided, including more than 112,300 deaths among people younger than 65, according to a recent analysis by the Centers for Disease Control and Prevention. But those avoidable deaths reflected a 3.8% per year decline in mortality rates during the previous 10 years.

Now, widespread prevalence of obesity and diabetes threatens to undermine such gains. And a large gap remains between how white patients and minorities—especially African-Americans—benefit from effective strategies.

There have been few new transformative cardiovascular treatments since the mid-1980s to early 1990s, when a stream of large-scale trials of new agents ranging from clot-busters to treat heart attacks to the mega class of statins electrified the cardiology field with evidence of significant improvements in survival from the disease. One reason: Some of those remedies have proven tough to beat with new treatments.

What’s more, use of the current menu of medicines for reducing heart risk remains an imprecise art. Besides

  • blood pressure drugs,
  • cholesterol-lowering statins

also are widely prescribed. Drug-trial statistics show that to prevent a single first heart attack in otherwise healthy patients can require prescribing a statin to scores of patients, but no one knows for sure who actually benefits and who doesn’t.

“It would be great if we could make some more paradigm-shifting discoveries,” said Michael Lauer, director of cardiovascular sciences at the NHLBI, which is a part of the National Institutes of Health.

Finding new treatments isn’t the only aim of the new project. “You could use existing therapies smarter,” said Joseph Loscalzo, chairman of medicine at Brigham and Women’s Hospital in Boston.

The American Heart Association launched the initiative and has committed $30 million to it over the next five years. The AHA sees the project as critical to its goal to achieve a 20% improvement in cardiovascular health in the U.S. while also reducing deaths from heart disease and stroke by 20% for the decade ending in 2020, said Nancy Brown, the nonprofit organization’s chief executive.

The Jackson study has already identified characteristics of cardiovascular risk among African-American patients “that may have promise for new insights” in a collaborative effort, said Adolfo Correa, professor of medicine and pediatrics at University of Mississippi Medical Center and interim director of the Jackson study.

For instance, there is a higher prevalence of obesity among Jackson participants than seen in the Framingham cohorts. Obesity is associated with high blood pressure, diabetes and cardiovascular risk. Diabetes is also more prevalent among blacks than whites.

But African-Americans of normal weight appear to have higher rates of hypertension and diabetes than whites of normal weight. “The question is, should [measures] for defining diabetes be different or the same for the [different] populations and are they associated with the same risk of cardiovascular disease?” said Dr. Correa. The collaboration, he said, may provide better comparisons.

Researchers, who plan to use tools other than genetics, think more might be learned about blood pressure and heart and stroke risk by monitoring patients in real time using mobile devices rather than taking readings only in periodic office visits. For example, high blood pressure during sleep or spikes during exercise could indicate risks that don’t show up in a routine measurement in the doctors’ office.

A big challenge is making sense of the huge amounts of data involved in sequencing DNA and linking it to

  • medical records,
  • diet and
  • exercise habits and other variables that influence risk.

“The analytical methods for sorting out these complex relationships are still in evolution,” said Dr. Loscalzo, of Brigham and Women’s Hospital. “The cost of sequencing is getting cheaper and cheaper. The hard part is analyzing the data.”

Write to Ron Winslow at ron.winslow@wsj.com

SOURCE

http://online.wsj.com/news/articles/SB10001424052702304281004579220373600912930#!

The e-Reader is advised to to review tightly related articles in

http://pharmaceuticalintelligence.com/biomed-e-books/series-a-e-books-on-cardiovascular-diseases/volume-three-etiologies-of-cardiovascular-diseases-epigenetics-genetics-genomics/

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Larry H Bernstein, MD, FCAP, Reporter and curator

αllbβ3 Antagonists As An Example of Translational Medicine Therapeutics

http://phrmaceuticalintelligence.com/2013-10-12/larryhbern_BS-Coller/αllbβ3 Antagonists As An Example of Translational Medicine Therapeutics

by Barry S. Coller, MD
Rockefeller University

Introduction

This article is a segment in several articles about platelets, platelet function, and advances in applying the surge of knowledge to therapy.  In acute coronary syndromes, plaque rupture leads to thrombotic occlusion.  We have also seen that the development of a plaque occurs in 3 stages, only the last of which involves plaque rupture.  Platelets interact with the vascular endothelium, and platelet-endothelial as well as platelet-platelet interactions are known to be important in atherogenesis.  We learned that platelets are derived from megakaryocytes that break up and these elements are released into the blood stream.  It has recently been discovered that platelets can replicate in the circulation.  The turnover of platelets is rapid, and platelets sre stored at room temperature with shaking, and are viable for perhaps only 3-4 days once they are received in the blood bank for use.  In cardiology, the identification, isolation, and characterization of GPIIb/IIIa from the platelet was a huge advance in the potential for coronary intervention, and that potential became of paramount importance with the introduction of GPIIb/IIIa inhibitors as a standard in coronary vascular therapeutic procedures.   The following manuscript by Barry Coller, at Rockefeller University,  is a presentation of the GPIIb/IIIa story as an excellent example of Translational Medicine.

Search for GPIIb/IIIa inhibitor of the (anti-αIIb133 (GPIIb/IIIa) receptor)

The deliberate search for drugs to inhibit the αIIb133 (GPIIb/IIIa) receptor ushered in the era of rationally designed antiplatelet therapy and thus represents an important milestone in the evolution of antiplatelet drug development. The selection of the αIIb133 receptor as a therapeutic target rested on a broad base of basic and clinical research conducted by many investigators in the 1960s and 1970s working in the fields of platelet physiology, the rare bleeding disorder Glanzmann thrombasthenia, platelet membrane glycoproteins, integrin receptors, coronary artery pathology, and experimental thrombosis. Thus, αIIb133 was found to mediate platelet aggregation by virtually all of the physiology agonists (e.g., ADP, epinephrine, and thrombin) through a mechanism in which platelet activation by these agents results in a change in the conformation of the receptor. This is followed by increased affinity of the receptor for the multivalent ligands fibrinogen and von Willebrand factor, both of which are capable of binding to receptors on two platelets simultaneously, producing platelet crosslinking and aggregation. At about the same time, experimental studies demonstrated platelet thrombus formation at sites of vascular injury, and biochemical studies in humans demonstrated evidence of platelet activation during acute ischemic cardiovascular events.

Our own studies initially focused on platelet-fibrinogen interactions using an assay in which normal platelets agglutinated fibrinogen-coated beads. The agglutination was enhanced with platelet activators. Platelets from patients with Glanzmann thrombasthenia, who lack the αIIb133 receptor, did not agglutinate the beads. We adapted this assay to a microtiter plate system to identify monoclonal antibodies that inhibited platelet-fibrinogen interactions and then demonstrated that these antibodies bound to αIIb133. They were also more potent inhibitors of platelet aggregation than any known antiplatelet agent and produced a pattern of aggregation that was virtually identical to that found using platelets from patients with Glanzmann thrombasthenia.

I recognized the theoretical potential of using an antibody to inhibit platelets in vivo but also recognized the challenges and limitations. Since experimental models of thrombosis had been developed in the dog, and since the antibody we initially worked with did not react with dog platelets, we had to go back to our original samples to identify an antibody (7E3) that reacted with dog platelets in addition to human platelets. Since coating platelets with immunoglobulins results in their rapid elimination of the platelets from the circulation, and since the clearance is mediated by the immunoglobulin Fc region, we prepared F(ab’)2 fragments of 7E3 for our in vivo studies. Additional challenges included preparing large quantities of antibody on a very limited budget and purifying the antibodies so they contained only minimal amounts of endotoxin. With the small amount of 7E3-F(ab’)2 we initially prepared, we were able to show dose response inhibition of platelet aggregation in three dogs, achieving greater inhibition than with aspirin or ticlopidine, the only antiplatelet agents approved for human use at that time. We also devised an assay using radiolabeled 7E3 to quantify the percentage of platelet αIIbβ3 receptors that were blocked when a specific dose of 7E3-F(ab’)2 was administered in vivo. This allowed us to directly measure the effect of the agent on its target receptor on its target cell.

I considered two criteria most important in selecting the initial animal models in which to test the efficacy and safety of administering 7E3-F(ab’)2:

  • 1) the model had to convincingly simulate a human vascular disease, and
  • 2) aspirin had to have failed to produce complete protection from thrombosis.

The latter criterion was particularly important because I planned to stop this line of research if the 7E3-F(ab’)2 was not more efficacious than aspirin.

Ultimately, we collaborated with Dr. John Folts of the University of Wisconsin, who had developed a dog model of unstable angina by attaching a short cylindrical ring to partially occlude a coronary artery and using a hemostat to induce vascular injury. Pretreatment of the animal with 7E3-F(ab’)2 was more effective than aspirin or any other compound Dr. Folts had previously tested in preventing platelet thrombus formation, as judged by its effects on the characteristic repetitive cycles of platelet deposition and embolization. Electron microscopy of the vessels confirmed the reduction in platelet thrombi by 7E3-F(ab’)2, with only a monolayer of platelets typically deposited.

Dr. Chip Gold and his colleagues at Massachusetts General Hospital had developed a dog model to assess the effects of tissue plasminogen activator (t-PA) on experimental thrombi induced in the dog coronary artery. Although t-PA was effective in lysing the thrombi, the blood vessels rapidly reoccluded with new thrombi that were rich in platelets. Aspirin could not prevent reocclusion, whereas 7E3-F(ab’)2 not only prevented reocclusion, but also increased the speed of reperfusion by t-PA.

The next steps in drug development could not be performed in my laboratory because they required resources far in excess of those in my grant from the National Heart, Lung, and Blood Institute to study basic platelet physiology. As a result, in 1986 the Research Foundation of the State University of New York licensed the 7E3 antibody to Centocor, Inc., a new biotechnology company specializing in the diagnostic and therapeutic application of monoclonal antibodies.

Subsequent Development of 7E3

The subsequent development of 7E3 as a therapeutic agent required extensive collaboration among myself, a large number of outstanding scientists at Centocor, and many leading academic cardiologists. Many decisions and hurdles remained for us, including the decision to develop a mouse/human chimeric 7E3 Fab (c7E3 Fab); the design and execution of the toxicology studies; the assessment of the potential toxicity of 7E3 crossreactivity with αVβ3; the development of sensitive and specific assays to assess immune responses to c7E3 Fab; the design, execution, and analysis of the Phase I, II, and III studies; and the preparation, submission, and presentation of the Product Licensing  Application to the Food and Drug Administration, and comparable documents to European and Scandinavian agencies.

Based on the results of the 2,099 patient EPIC trial, in which conjunctive treatment with a bolus plus infusion of c7E3 Fab significantly reduced the risk of developing an ischemic complication (death, myocardial infarction, or need for urgent intervention) after coronary artery angioplasty or atherectomy in patients at high risk of such complications, the Food and Drug Administration approved the conjunctive use of c7E3 Fab (generic name, abciximab) in high-risk angioplasty and atherectomy on December 22, 1994. Since then it has been administered to more than 2.5 million patients in the U.S., Europe, Scandinavia, and Asia. Its optimal role in treating cardiovascular disease continues to evolve in response to the introduction of new anticoagulants, antiplatelet agents, stents, and procedures.

Extended Investigations

We have also been able to apply the monoclonal antibodies we prepared to αIIb33 to the prenatal detection of Glanzmann thrombasthenia, and have used the antibodies as probes for characterizing both the biogenesis of the receptor and the conformational changes that the receptor undergoes with activation. We have been able to precisely map the 7E3 epitope on 33, providing additional insights into the mechanism by which it prevents ligand binding. We have also exploited the ability of another antibody to αIIb33 to stabilize the receptor complex in order to facilitate production of crystals of the αIIb33 headpiece; the x-ray diffraction properties of these crystals were studied in collaboration with Dr. Timothy Springer’s group at Harvard and provide the first structural information on the receptor.

In landmark studies in the 1980s, Pierschbacher and Ruoslahti demonstrated the importance of the arginine-aspartic acid (RGD) sequence in the interaction of the integrin α531 with fibronectin, and they went on to show that peptides with the RGD sequence could inhibit this interaction. Subsequent studies by many groups demonstrated that these peptides could also inhibit the interaction of platelet αIIb33 with fibrinogen and von Willebrand factor. Dr. David Phillip and Dr. Robert Scarbrough led the team at Cor Therapeutics that made a cyclic pentapeptide with high selectivity for αIIb33 over αV33 by patterning their compound on the KGD sequence in the snake venom barbourin. The resulting antiplatelet agent, eptifibatide, received FDA approval in May 1998. At Merck, Dr. Robert Gould led the team that developed the nonpeptide RGD-mimetic tirofiban, which also is selective for αIIb33 compared to αV33. It also received FDA approval in May 1998. Our recent x-ray crystallographic studies in collaboration with Dr. Springer’s group provided structural information on the mechanisms and sites of binding of these drugs with αIIb33.

Translation of Basic Science into Therapy

Many important elements and an enormous amount of good fortune were needed for the translation of the basic science information about platelet aggregation into the drug abciximab, including, but not limited to:

  • 1) the support of basic studies of platelet physiology by the National Institutes of Health in my laboratory and many other laboratories,
  • 2) the creation and ongoing funding of a core facility available to all faculty members to prepare monoclonal antibodies at the State University of New York at Stony Brook under the direction of Dr. Arnold Levine,
  • 3) the 1988 Bayh-Dole Act and its subsequent amendments, and the expertise of the Technology Transfer Office at Stony Brook in licensing 7E3 to Centocor, which then provided the capital and additional expertise required for its development, and
  • 4) the expert and enthusiastic collaboration by two large and disciplined cooperative groups of interventional cardiologists (TAMI, EPIC) under the dynamic leadership of Drs. Eric Topol and Rob Califf,

tirofiban, that were eager to test the safety and efficacy of the 7E3 derivatives. Although the translation of each new scientific discovery into improved health via novel preventive, diagnostic, or therapeutic strategies requires the blazing of a unique path, optimizing these elements and similar ones may allow the path to be shorter and/or to be traversed more easily, at a lower cost, or in a shorter period of time.

 

Related articles in Pharmaceutical Intelligence:

Platelets in Translational Research – 1   Larry H. Bernstein, MD, FCAP
http://pharmaceuticalintelligence.com/10-6-2013/larryhbern/Platelets_in_Translational_Research-1
Platelets in Translational Research – 2  Larry H. Bernstein, MD, FCAP
http://phramaceuticalintelligence.com/2013-10-7/larryhbern/Platelets-in-Translational-Research-2/

Do Novel Anticoagulants Affect the PT/INR? The Cases of XARELTO (rivaroxaban) and PRADAXA (dabigatran)
Vivek Lal, MBBS, MD, FCIR, Justin D Pearlman, MD, PhD, FACC and Aviva Lev-Ari, PhD, RN
http://pharmaceuticalintelligence.com/2013/09/23/do-novel-anticoagulants-affect-the-ptinr-the-cases-of-xarelto-rivaroxaban-and-pradaxa-dabigatran/

 

Read Full Post »

Platelets in Translational Research – Part 1

 

Reviewer and Curator: Larry H Bernstein, MD, FCAP 

 

Introduction

This article is one of a 2 part presentation posted as an example of a central role of platelet biology in translational medicine investigations leading to the prevention and control of hemolytic and coagulopathic conditions, and to an understanding of atherosclerotic cardiovascular disease. The study of coagulation traces back to the early work on Warfarin in bleeding, and even earlier than that to the geneological evidence of inherited hemophilia in the Royal family of 18th Century Victoria.  The amount of work has been voluminous, and the conceptual framework has been difficult to put into practice over generations of postgraduate physicians.  No wonder, considering the clotting proteins and the amazing platelet.

Part I of Platelets in Translaional Research is a comprehensive coberage of the signaling and control involved in platelet-endothelial reactions, platelet-platelet reactions, and platelet transciptomics, all of which have a significant bearing on atherosclerotic plaque buildup, plaque rupture, and acute coronary syndrome as well as chronic ischemic heart disease.

Part II will cover a range of studies pointing to anti-platelet therapeutic targets.

Related work in Pharmaceutical Intelligence

Advanced Topics in Sepsis and the Cardiovascular System at its End Stage

Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/08/18/advanced-topics-in-sepsis-and-the-cardiovascular-system-at-its-end-stage/

‎ Special Considerations in Blood Lipoproteins, Viscosity, Assessment and Treatment

Larry H. Bernstein, MD, FCAP and Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/11/28/special-considerations-in-blood-lipoproteins_ viscosity_assessment-and-treatment/

What is the role of plasma viscosity in hemostasis and vascular disease risk?

Larry H Bernstein, MD  and Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/11/28/What-is-the-role-of-plasma-viscosity-in-hemostasis-and-vascular-disease-risk?

Biochemistry of the Coagulation Cascade and Platelet Aggregation – Part I

Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/11/26/Biochemistry-of-the-Coagulation-Cascade-and-Platelet-Aggregation-Part_I

Nitric Oxide Function in Coagulation

Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/11/26/nitric-oxide-function-in-coagulation/

Coagulation: Transition from a familiar model tied to laboratory testing, and the new cellular-driven model

Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/11/10/coagulation-transition-from-a familiar-model-tied-to-laboratory-testing-and-the-new-cellular-driven-model/

Nitric Oxide, Platelets, Endothelium and Hemostasis

Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/11/08/nitric-oxide-platelets-endothelium-and-hemostasis/

Interaction of Nitric Oxide and Prostacyclin in Vascular Endothelium

Larry H. Bernstein, MD

http://pharmaceuticalintelligence.com/2012/09/14/interaction-of-nitric-oxide-and-prostacyclin-in-vascular-endothelium

The Effects of Aprotinin on Endothelial Cell Coagulant Biology

Demet Sag, PhD*†, Kamran Baig, MBBS, MRCS; James Jaggers, MD, Jeffrey H. Lawson, MD, PhD

http://pharmaceuticalintelligence.com/2013/07/20/the-effects-of-aprotinin-on-endothelial-cell-coagulant-biology/

Platelet Role in Atheroscleosis

Platelets and Cardiovascular Disease

David Gregg, MD; Pascal J. Goldschmidt-Clermont, MD
Duke University Medical Center, Durham, NC.

Platelets are specialized disk-shaped cells in the blood stream that are involved in the formation of blood clots that play an important role in heart attacks, strokes, and peripheral vascular disease. In most people, the more than 200 million platelets in a milliliter of blood act as tiny building blocks to form the basis of a clot to stop bleeding from cuts or injuries. Platelets can detect a disruption in the lining of a blood vessel and react to build a wall to stop bleeding.

F1.large  platelr forms plug

Figure 1. Platelets form a platelet plug to stop bleeding from an injured blood vessel.

In cardiovascular disease, abnormal clotting occurs that can result in heart attacks or stroke. Blood vessels injured by smoking, cholesterol, or high blood pressure develop cholesterol-rich build-ups (plaques) that line the blood vessel; these plaques can rupture and cause the platelets to form a clot. Even though no bleeding is occurring, platelets sense the plaque rupture and are confused, thinking that an injury has taken place that will cause bleeding. Instead of sealing the vessel to prevent bleeding as would occur with a cut, a clot forms in an intact blood vessel, causing a blockage of blood flow (Figure 2). Without blood, a portion of the heart muscle can die, leading to a heart attack.

F2.large   clot formation blocks flow

Figure 2. Plaque rupture results in clot formation to block blood flow, which may result in a heart attack or stroke

Platelet Disorders

Platelets may be abnormal either quantitatively (too many or too few) or qualitatively (the right number but they do not work correctly). The number of platelets is routinely tested as part of the complete blood count (CBC). Normal counts range from 150 000 to 450 000. A decrease in the number of platelets indicates a condition known as thrombocytopenia and may result in increased bleeding, the first signs of which may include gum bleeding, nose bleeds, and increased bruising. In cardiology, the most frequent cause of a low platelet count is an abnormal immune response caused by drug therapy, particularly with the intravenous blood thinner heparin (heparin-induced thrombocytopenia), and rarely with other drugs to control high blood pressure or symptoms of congestive heart failure (diuretics), to control diabetes (antidiabetic medications), or to regulate your blood clotting (antiplatelet drugs). Elevated platelet counts can also occur, usually in association with diseases in the elderly, and can result in either excess clotting or even abnormal bleeding.

Because platelets are so important in stopping bleeding from everyday injuries such as cuts or bruises, severe inherited disorders of platelets are quite rare. Researchers, however, have discovered more subtle genetic variations in platelets called polymorphisms that may alter platelets in subtle ways to raise the risk of cardiovascular disease when combined with other risk factors, but which on their own do not result in overt disease. These polymorphisms may also be important in understanding who may gain the greatest benefit from anti-platelet drugs.

The most commonly used antiplatelet agent is aspirin, although you may also be prescribed other oral agents, such as ticlopidine, clopidogrel, or dipyridamole, or intravenous antiplatelet drugs such as abciximab or eptifibatide while you are in the hospital or undergoing angioplasty procedures. Each agent affects platelets in slightly different ways and may have unique side effects, but all either cause the platelets to stick together or induce them to clot less well. Your doctor will choose the drug that best suits your situation. Table 1 shows some of the unique features of commonly used oral antiplatelet drugs

TABLE 1. Commonly Used Oral Antiplatelet Drugs: Uses and Side Effects

Aspirin Clopidogrel Ticlopidine Dipyridamole + Aspirin
Uses Heart disease and stroke; inexpensive Heart disease and stroke, particularly after stenting Mostly in stroke; requires blood count monitoring Stroke; may not be suitable for patients with heart disease
Side effects Gastrointestinal (GI) intolerance; GI bleeding Diarrhea (much less common than with ticlopidine); rash and itching Diarrhea and GI upset (usually resolves in 2 weeks); may decrease blood counts, particularly white blood cells Headache; GI bleeding; GI intolerance

Antiplatelet drugs are different than blood thinners or anticoagulants such as warfarin (Coumadin, Bristol-Myers Squibb) or heparin. Anticoagulants block a second step in clotting known as coagulation but do not directly affect the platelets.

Eur J Cardiovasc Nurs. 2002 Dec;1(4):273-88.

Platelets and cardiovascular disease

Willoughby S, Holmes A, Loscalzo J.
Queen Elizabeth Hospital, Adelaide University, South Australia, Adelaide, Au

Platelets play an important, but often under-recognized role in cardiovascular disease. For example, the normal response of the platelet can be altered, either by increased pro-aggregatory stimuli or by diminished anti-aggregatory substances to produce conditions of increased platelet activation/aggregation and occur in active cardiovascular disease states both on a chronic (e.g. stable angina pectoris) and acute basis (e.g. acute myocardial infarction). In addition, platelet hyperaggregability is also associated with the risk factors for coronary artery disease (e.g. smoking, hypertension, and hypercholesterolaemia). Finally, the utility of an increasing range of anti-platelet therapies in the management of the above disease states further emphasizes the pivotal role platelets play in the pathogenesis of cardiovascular disease. This paper provides a comprehensive overview of the normal physiologic role of platelets in maintain homeostasis, the pathophysiologic processes that contribute to platelet dysfunction in cardiovascular disease and the associated role and benefits of anti-platelet therapies.   PMID: 14622657

Triggering of Plaque Disruption and Arterial Thrombosis in an Atherosclerotic Rabbit Model

GS Abela, PD Picon, SE Friedl, OC Gebara, A Miyamoto, et al.
Deaconess Hospital, Harvard Medical School, Boston, Mass; Federal Univ and Univ Passo Fundo (P.D.P.), Rio Grande de Sul, Brazil;  Heart Institute, Univ São Paulo (O.C.G.), São Paulo, Brazil; National Defense Medical College (A.K.), Saitama, Jp.

It is now recognized that plaque disruption and thrombosis, a process often triggered by activities of the patient, is generally the cause of the onset of acute coronary syndromes. Plaque disruption and subsequent arterial thrombosis are now recognized as critical to the onset of acute coronary ischemic syndromes. It is hypothesized that occurrence of thrombotic coronary occlusion has three components. First, a plaque that is vulnerable to disruption must be present. Second, acute physiological events are required to induce plaque disruption and thrombosis. Third, a relatively hypercoagulable state and heightened vasomotor tone increase the likelihood that arterial thrombosis will produce complete lumen occlusion.

In human patients, the opportunity to study factors responsible for acute onset of myocardial infarction is limited because coronary angiography performed before the event cannot prospectively identify plaques vulnerable to disruption. After the event, angiography cannot distinguish the features of the plaque responsible for the disruption from those resulting from the disruption. Moreover, plaque disruptions producing total vascular occlusion and death may be more severe than those occurring in asymptomatic individuals or in patients with unstable angina or nonfatal myocardial infarction. These difficulties, inherent in the study of plaque disruption and thrombosis in human patients, create a great need for an animal model of the process.  An atherosclerotic rabbit model of triggering of arterial thrombosis that was introduced by Constantinides and Chakravarti more than 30 years ago but not subsequently used. Aortic plaques were induced by a high-cholesterol diet, by mechanical balloon injury of the artery, or by a combination of the two. Triggering was attempted by injection of Russell’s viper venom (RVV), which is a proteolytic procoagulant, and histamine. A recent review of the animal models of thrombosis currently in use noted that “thus far, it has not been possible to duplicate in a model the most common clinical cause of thrombosis—an ulcerated atherosclerotic plaque.” The advantage of the Constantinides model over other animal models used to study thrombosis is that it uses a biological intervention to trigger localized atherosclerotic plaque disruption and formation of platelet-rich arterial thrombi.  Disadvantages of the Constantinides model are (1) the low yield of triggering (only about one third of the rabbits developed thrombosis) and (2) the long (8-month) preparatory period. In addition, there is a need to replicate the findings of Constantinides and Chakravarti13 from 30 years ago because of the biological variability of rabbit strains and RVV. It cannot be assumed that the rabbits and RVV currently available will produce the results obtained in the 1960s.

A total of 53 New Zealand White rabbits were exposed to one of four preparatory regimens: rabbits in group I (n=9) were fed a regular diet for 8 months; rabbits in group II (n=13) were fed a diet of 1% cholesterol for 2 months alternated with 2 months of a regular diet for a total of 8 months; rabbits in group III (n=5) underwent balloon-induced arterial wall injury, then were given a regular diet for 8 months; and rabbits in group IV (n=14) underwent balloon-induced arterial wall injury, then were given a diet of 1% cholesterol for 2 months followed by a regular diet for 2 months for a total of 4 months. After completion of the preparatory regimen, triggering of plaque disruption and thrombosis was attempted by injection of RVV (0.15 mg/kg IP) and histamine (0.02 mg/kg IV). In group I, normal control rabbits without atherosclerosis, only one small thrombus was noted in 1 of 9 rabbits. In group II, cholesterol-fed rabbits, thrombosis occurred in 3 of 13 rabbits. Thrombus occurred in all rabbits in group III (5 of 5) and in 10 of 14 rabbits in group IV. Although the frequency of thrombosis was not significantly different between groups I and II, possibly due to a small sample size, it was significantly different among all four groups (P<.001). Also, the frequency and amount of thrombus formation were significantly different among all four groups (P<.001; P<.0001) but not between groups I and II. Rabbits with atherosclerosis (those in groups II and IV) demonstrated plaque disruption and overlying platelet-rich thrombus formation similar to that observed in patients with acute coronary syndromes. The surface area covered by thrombus was 2 mm2 in group I, 15.3±19.2 mm2 in group II, 223±119 mm2 in group III, and 263±222 mm2 in group IV. Rabbits in groups III and IV had the greatest amount of thrombus, and this amount was significantly greater than in rabbits in groups I and II (P<.001 and P<.03, respectively).

The intima in group I rabbits appeared normal by gross inspection. In group II rabbits, white-yellow plaque was widely distributed over the arterial surface, with focal punctate ulceration occasionally noted under a dissecting microscope. In group III rabbits, the intima was smooth and widely covered with white plaque. Group IV rabbits had extensive sheets of elevated white-yellow plaque. By gross visualization, ulceration of the surface was present without superimposed thrombus in two rabbits in group IV.  In sections from groups II and IV, some areas of plaque directly adjacent to the thrombi had marked thinning of the connective tissue cap and areas of dehiscent foam cells. These observations were rare and were noted in <0.5% of the examined lesions. In most cases, the arterial thrombus was not located at a site of obvious plaque rupture. Foam cell infiltration was also noted adjacent to sites of thrombosis. Scanning electron microscopy demonstrated fissures of various lengths below areas from which overlying thrombi were removed. Endothelial cells could be seen lining the intimal surface of the aorta in the rabbits that had undergone balloon-induced arterial wall injury 8 months earlier. Surface blebs and focal endothelial breakdown with ulcer formation, without grossly visible thrombosis, were occasionally seen in samples from groups II and IV. The base of these ulcers was layered with platelets, fibrin, and red blood cells. Transmission electron microscopy of areas with thrombosis confirms that the thrombi were platelet rich.

In the two groups that received cholesterol feeding, the total cholesterol content in tissue samples pooled from the thoracic and abdominal aorta was significantly higher in group IV (16±7.2 mg/g) than in group II (2.8±1.6 mg/g) (P<.0001). Rabbits that were maintained on a regular diet (groups I and III) had equally low levels of tissue cholesterol (0.05±0.04 versus 0.06±0.02 mg/g, P=NS). The average fibrinogen level before triggering in the 27 rabbits in which fibrinogen was measured was 210±119 mg/dL; it rose to 403±168 mg/dL 48 hours after triggering (P<.001). Plasma fibrinolytic activity did not change after triggering (85.5±37.8 versus 94.8±33.5 arbitrary units). Platelet counts (measured in only 19 rabbits in groups II and IV) decreased from 350±84×103 to 215±116×103 per cubic millimeter after triggering (P<.001).

Conclusions

The results demonstrate that vulnerable plaques can be produced and that plaque disruption and platelet-rich arterial thrombus formation may be triggered pharmacologically in an animal model of arterial plaque. This finding documents that the New Zealand White rabbit strains and the RVV currently available can be used to obtain the same results observed by Constantinides and Chakravarti13 more than 30 years ago. This animal model is suitable for the study of plaque disruption and arterial thrombosis. Hypercholesterolemia and mechanical arterial wall injury seemed to produce plaques vulnerable to triggering of disruption and thrombosis, whereas normal arteries were relatively resistant to triggering. The model provides a method to evaluate agents that might decrease the occurrence of vulnerable plaques or the amount of thrombus formed after triggering. Most important, the model can be used to identify the features of vulnerable plaques and the pharmacological stressors that trigger plaque disruption and thrombus formation.

Certain features of the lesions seen in this model are similar to those of human lesions seen at autopsy of patients with fatal myocardial infarction, ie, a lesion with a fissured collagen cap overlying a lipid mass of amorphous and crystalline lipid. However, most of the lesions in the model did not have these features and were more consistent with a recent pathological study of fatal coronary thrombosis, which revealed that in approximately half the cases, the plaque was relatively intact but an inflammatory infiltrate was present. Perhaps the incidence of plaque rupture causing thrombus may be even lower in patients with nonfatal coronary thrombosis, as suggested from angioscopic studies of coronary arteries that have shown plaque ulceration of various severities.  Analyses of human plaques have demonstrated that disrupted plaques have significantly less collagen, glycosaminoglycans, and smooth muscle cells and more extracellular lipid and macrophages  than do nondisrupted plaques. This is consistent with findings in our study that rabbits in group II had more connective tissue and a lower rate of disruption and thrombosis than those in groups III and IV.

references

Herrick JB. Clinical features of sudden obstruction of the coronary arteries. JAMA. 1912;59:2015-2020.
Chapman I. Morphogenesis of occluding coronary artery thrombosis. Arch Pathol. 1965;80:256-261.
Friedman M, van den Bovenkamp GJ. The pathogenesis of a coronary thrombus. Am J Pathol. 1966;80:19-44.

This reader sees a validation in this study of the noted cardiologist, Alan Jaffe, at Mayo Clinic, in referring to Type I and Type II myocardial infarcts, which accounts for differences in troponin elevations in patients.

The Platelet in Cardiovascular Disease

1. microthrombi adhering to foam cells
2. Platelets secrete

–  Platelet-derived growth factor (PDGF) that promotes smooth muscle cell migration and collagen production

– Plasminogen activator inhibitor-1 (PAI-1) that suppresses fibrinolysis

Davies MJ, Woolf N, Rowles PM, et al. Morphology of the endothelium over atherosclerotic plaques in human coronary arteries. Br Heart J 1988;60:459-64.

– Microhemorrhages attract and activate neighboring platelets, support fibrin generation

Inoue M, Itoh H, Ueda M, et al. Vascular endothelial growth factor (VEGF) expression in human coronary atherosclerotic lesions: Possible pathophysiological significance in progression of atherosclerosis. Circulation 1998;98:2108-16.

Systems biology of platelet-vessel wall interactions

Scott L. Diamond*, Jeremy Purvis, Manash Chatterjee and Matthew H. Flamm
Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, PA
Front Phys 26 August 2013    http://dx.doi.org/10.3389/fphys.2013.00229

Blood systems biology seeks to quantify outside-in signaling as platelets respond to numerous external stimuli, typically under flow conditions. Platelets can activate via GPVI collagen receptor and numerous G-protein coupled receptors (GPCRs) responsive to ADP, thromboxane, thrombin, and prostacyclin. A bottom-up ODE approach allowed prediction of platelet calcium and phosphoinositides following P2Y1 activation with ADP, either for a population average or single cell stochastic behavior. The homeostasis assumption (i.e., a resting platelet stays resting until activated) was particularly useful in finding global steady states for these large metabolic networks. Alternatively, a top-down approach involving Pairwise Agonist Scanning (PAS) allowed large data sets of measured calcium mobilization to predict an individual’s platelet responses. The data was used to train neural network (NN) models of signaling to predict patient-specific responses to combinatorial stimulation. A kinetic description of platelet signaling then allows prediction of inside-out activation of platelets as they experience the complex biochemical milieu at the site of thrombosis. Multiscale lattice kinetic Monte Carlo (LKMC) utilizes these detailed descriptions of platelet signaling under flow conditions where released soluble species are solved by finite element method and the flow field around the growing thrombus is updated using computational fluid dynamics or lattice Boltzmann method. Since hemodynamic effects are included in a multiscale approach, thrombosis can then be predicted under arterial and venous thrombotic conditions for various anatomical geometries. Such systems biology approaches accommodate the effect of anti-platelet pharmacological intervention where COX1 pathways or ADP signaling are modulated in a patient-specific manner.

CLOTTING UNDER FLOW CONDITIONS

Collagen is sufficient to capture and activate platelets under venous wall shear rates (ãw  100–200s_1). In the arterial circulation (ãw 1000–2000 s_1), collagen adsorbed von Willebrand factor (vWF) facilitates platelet capture, allowing col­lagen induced GPVI signaling and subsequent á2â1 and á2bâ3 activation. Under flow conditions, red blood cells help enrich the platelet concentration by 3–8x in the plasma layer near the wall. At pathological high shear exposures (>5000 s_1) encountered in severe stenosis, mechanical heart valves, and continuous LVAD pumps, the plasma vWF may undergo structural changes, such as a transition from a globular to an extended state (Schneider et al., 2007), likely increasing the availability of A1 domains in the vWF polymer for multivalent contacting with platelet GPIb receptors.

GROWTH OF THE PLATELET AGGREGATE VIA AUTOCATALYTIC SIGNALING

Collagen triggers GPVI clustering, leading to rapid phosphorylation of the GPVI-associated Fc receptor by Src family tyrosine kinases. Such phosphotyrosine residues are recognized by Syk, and the binding and activation of Syk activates PLCã2. PLCã2 converts phosphatidylinositol (PI)-4,5-P2 (PIP2) to inositol 1,4,5-trisphosphate (1,4,5-IP3 or IP3) and diacyclglycerol (DAG). IP3 opens Ca2+ channels in the platelet dense tubular system (DTS). Depletion of DTS Ca2+ results in STIM1 activation and bind­ing to Orai1, leading to store operated calcium entry (SOCE). DAG/Ca2+ activates protein kinase C (PKC) in platelets, which in turn governs several serine/threonine phosphorylation events.

Beyond the first monolayer of platelets adherent to colla-gen/VWF, the addition of subsequent layers of platelets to the growing thrombus is strongly potentiated by locally released ADP and thromboxane (TXA2) as well as locally generated thrombin. ADP activates P2Y1 and P2Y12 while TXA2 activates the TP receptor and thrombin cleaves PAR1 and PAR4. Activation of a GPCR causes an exchange of GTP for GDP on the α subunit of the G protein and dissociation of the α and γ subunits. Both these units in turn interact with secondary effectors such as PLC and adenylate cyclase. Human platelets express at least 10 forms of Gα (including members of the Gq, Gi, G12, and Gs fami­lies) (Brass et al., 2006; Offermanns, 2006). Thrombin, ADP, and TXA2 activate PLC via Gq. PLC generates IP3 from membrane PIP2. Rising Ca2+ levels activate the Ras family member, Rap1B via Cal-DAG GEF. Rap1B activation is a precursor to αIIb 3 acti­vation and allows the platelets to form aggregates with other platelets through fibrinogen cross-bridging. Ca2+-dependent signaling drives myosin light chain kinase and activation of GTP binding proteins of the Rho family. Rho acti­vation in turn activates kinases like p160ROCK and 5 LIM-kinase that can phosphorylate myosin light chain kinase and cofilin to regulate actin-dependent cytoskeletal shape changes. Endothelial derived prostacyclin (PGI2) binds the IP recep­tor and causes Gs mediated increase in adenyl cyclase activity. Also, NO from the endothelium and platelets can activate guany-late cyclase resulting in elevated cGMP levels that subsequently inhibit the hydrolysis of cAMP by intracellular phosphodi-esterases. Taken together these mechanisms elevate intracellular cAMP levels, which strongly downregulate platelet signaling. Agonists coupled to Gi family members inhibit cAMP production in platelets, thus allowing activation to proceed unhindered. Additionally the âã subunits of these receptors can activate PLCâ and the ã isoform of PI3K. The effectors for PI3K include Rap1b and Akt.

Fig 1 reaction schemes for platelet signaling

FIGURE 1 | Detailed reaction schemes for platelet signaling modules. Four interconnected models were defined: (A) Ca2+ module: cytosolic and DTS compartments are separated by the DTS membrane, which contains the IP3R and SERCA. (B) Phosphoinositide (PI) module: Membrane-bound PIs are cleaved by PLC-â to form diffusible inositol phosphates and DAG, which are substrates for resynthesis of PIs. (C) PKC module: Ca2+i and DAG activate PKC, which migrates to the plasmamembrane where it phosphorylates PLC-â. (D) P2Y1 module: extracellular ADP binds to and activates P2Y1. Active P2Y1 accelerates guanine nucleotide exchange on bound Gq. The Gq·GTP binds and activates PLC-â, which increases the GTPase activity of Gq·GTP.

ADP is stored in platelet dense granules and is released upon activation. P2Y1 and P2Y12 are the primary receptors for this agonist. P2Y1 is Gq coupled and signaling through this receptor causes Ca2+ mobilization, shape change, and thromboxane generation. P2Y12 is the target of the commonly used anti-platelet drug Plavix, and is a Gi2 coupled receptor that inhibits cAMP production in platelets. Thrombin is a potent platelet agonist that causes fast mobi­lization of intracellular Ca2+, and activation of phospholipase A2 and subsequent thromboxane generation (Offermanns et al., 1997). Also, thrombin can trigger Rho dependent signaling pathways in platelets (Moers et al., 2003), that contribute to actin modeling and shape change. Thrombin signals through the protease-activated receptor (PAR) family of GPCRs. PAR1 and PAR4 are expressed on human platelets, while PAR3 and PAR4 are expressed on mouse platelets. Thrombin cleaves the N-terminus of these receptors, exposing a new N-terminus that serves as a tethered ligand for these receptors. Synthetic pep­tides are able to selectively activate these receptors and mimic the actions of thrombin (for example, SFLLRN for PAR1, and AYPGKF for PAR4). Kinetic studies have shown that the human platelet response to thrombin is biphasic and involves first signal­ing through PAR1 and subsequent signaling through PAR4 (Covic et al., 2000). In mouse platelets signaling occurs primarily via PAR4, and is facilitated by PAR3. In addition to the PAR recep­tors, GP1bá has high affinity for thrombin. Absence of GP1bá reduces responses to low doses of thrombin and diminishes PAR1 signaling, suggesting that this receptor facilitates signaling through the PARs (Dormann et al., 2000). Ca2+ mobilization also activates phospholipase A2 (PLA2), which in turn converts mem­brane phospholipids to arachidonic Acid. TXA2 is produced from membrane arachidonate by the aspirin sensitive cyclooxygenase (COX-1) enzyme. TXA2 causes Ca2+ mobilization, aggregation, secretion, phosphoinositide hydrolysis, and protein phosphoryla-tion. TXA2 can diffuse across the membrane and activate nearby platelets, but its activity is limited by the molecule’s short half life (∼30 s).

These modules use previously validated or data-consistent kinetic networks for SERCA, IP3-Receptor, PKC translocation, and GPCR signaling (Figures 1E–H). Assembling the four modules together results in a global ODE model that has 77 reactions, 132 fixed kinetic rate constants, and 70 species. Since the reaction network (Figure 1) and the kinetic parameters are fixed, the reaction topology of the model is also fixed. Such a model takes the general form: dc/dt = F(c) and c(t = 0) = co where c is a vector of all species concentrations and co is a specified initial condition vector at t = 0. To determine appropriate sets of co that are suitable for use in modeling platelets, a challenge exists that the copy number of each species in a resting platelet is not known. Imposing a homeostasis assumption results in powerful tool to define a set of acceptable co vectors. The homeostasis assumption states that a resting platelet remains resting until activated. This means that an acceptable ini­tial condition co also represents a steady state for the system and will satisfy the equation dc/dt = 0. Finding a global co involves assembling the steady state solutions of each module (Figure 2).

Fig 2 Assembly of full model from steady-state modules

FIGURE 2 | Homeostasis requirement: Assembly of full model from steady-state modules using principle component analysis (PCA). The full model is assembled by combining PCA-reduced, steady-state solution spaces from each module into a combined steady state solution space. This global space is searched for full-length, steady-state solution vectors that satisfy both the steady state requirements of each module and the desired time-dependent properties when the steady-state is perturbed. A simple linear constraint is imposed for every pair of modules that share a common molecule ci to ensure that steady state solutions are Keywords: platelet, thrombosis, hemodynamic, ADP, thromboxane consistent. To assemble the platelet signaling model, a set of 16 PC vectors representing all 72 unknown variables in the model were used as search directions in a global optimization routine. The global solution space was searched for models with accurate dynamic behavior using experimental time-series data for ADP-stimulated Ca2+ release. Species are grouped according to compartment. Color values correspond to molar concentrations (mol/L or mol/m2) or as indicated: DTS species (mol L1). †Extracellular species (mol L1). DTS volume (L). §PM leak conductance/area (S m−2).

The first phase of the method involves generating a com­pact representation of the steady-state solutions for each module. First, conservative bounds are chosen for c based on physiological and practical considerations. Also, because molecular concentra­tions can span several orders of magnitude, it is most efficient to delineate this range of values on a logarithmic scale rather than a linear scale. Once the sampling distribution for c has been defined, steady-state solutions (co = c55) for each module are cal­culated using fixed kinetic parameters for each reaction in the module. For non-oscillating systems, steady-state solutions may be obtained by simulating the system until equilibrium is reached (i.e., until dc/dt = 0). In the third step, a large collection of steady-state solutions for each module is subjected to principal component analysis (PCA) (Purvis et al., 2009). PCA is then used to transform these points to a new coordinate set that optimally covers the space of steady-state solutions using the fewest num­ber of dimensions. For example, if two molecule concentrations in the steady-state space are highly correlated due to participation in the same reaction, PCA will locate a single dimension to rep­resent each pair of points in the transformed space. Ultimately, these new dimensions will be combined across all modules to search for global solutions that lie in the steady-state space for the fully combined network. Since PCA is a linear method, a steady-state solution space that is highly nonlinear may require more principal component vectors to accurately estimate the solutions. The reduction procedure is shown for the human platelet model comprising 4 interlinked signaling modules (Figure 2). For this step, we generated more than 109 sets of initial guesses (co) for each module, computed the initial value problem for each co until a steady state was reached (dc/dt ≈ 0), and selected only those steady states (c55) that were consistent with known con­centrations (i.e., [Ca2+]o ∼100 nM).  Interestingly, only a small fraction of initial guesses produce steady-state solutions that are also consistent with known concentration values. For example, it was shown that only 50,000 of 109 initial guesses (0.005%) in the Ca2+ balance module (Figure 1A) met both requirements and were suitable for further analysis. This observation shows that the kinetic topology of these molecular networks places very strong constraints on the range of concentrations that can exist at steady state. In biological terms, this suggests that fixed kinetic proper­ties at the molecular level (e.g., IP3R and SERCA kinetics) can affect not only the dynamical features of a biochemical system but can also determine the abundance of chemical species and the compartmental structures that contain them. A fully assem­bled initial condition vector results (bottom, Figure 2) results in new hypotheses about allowable concentrations and ratios of con­centrations (i.e., IP3/SERCA ratio is very small). The allowed co = css is consistent with the known resting levels of Ca2+, IP3, P2Y1, DAG, PA, PI, PIP2, and PIP (bottom, Figure 2) as well as the stimulated response of platelets to increasing amounts of ADP (right, Figure 2). With a global simulation of P2Y1 signaling, it is possible to simulate the ADP dose-response of calcium mobiliza­tion and IP3 generation in platelets as well as the mobilization of intracellular calcium in a single platelet due to stochastic fluctuations (Figure 3).

Fig 3. P2Y1 signalink model

FIGURE 3 | Tests of P2Y1 signaling model. ADP dose response for the full platelet model from 100 nM to 10 ìM ADP for calcium mobilization (A) or IP3 generation (B). Stochastic simulation of a single platelet (C). A single, fura-2-loaded platelet was immobilized on a fibrinogen-coated coverslip and activated with 40 ìM ADP at t = 90 [Ca2+ trace from Heemskerk et al. (2001)]. After 90 s of simulated rest, the platelet model was activated by setting extracellular [ADP] to 40ìM. Simulated interval times were binned in 2s increments for direct comparison with experiment (inset).

Since many initial condition vectors can be found to allow a resting platelet to remain resting and then respond appropriately to stimulation, investigation of these multiple steady states and associated cell responses can allow an ad-hoc sensitivity analysis. Some species (flexible nodes) may vary widely in the allowed ini­tial condition vectors but have little effect on system response. In contrast, other species (rigid nodes) may be forced to take on val­ues in a very narrow range due to the kinetic constraints of the problem.

To examine the changes in steady-state properties caused by kinetic perturbations in the P2Y1 model, we altered the rates of important regulatory reactions and observed the system response to each perturbation. Each perturbation cause a brief adjustment phase lasting ∼200 s followed by a more gradual phase char­acterized by a new steady-state profile. After 1 h of simulated time, steady-state concentrations and reaction fluxes were quan­tified relative to their original steady-state levels (Figure 4). In a computational perturbation, the inhibition of phospholipase C-β (PLC-β) activity by PKC was reduced 10-fold. Since PKC has a negative-feedback role in suppressing the platelet-stimulating activity of PLC-β, this perturbation caused a 2-fold increase

in steady-state PIP2 hydrolysis, elevated IP3 concentration, and accelerated Ca2+ release. This was a compensatory effect caused by the negative feedback loop involving Ca2+-regulated activity of PKC, a resulting new hypothesis that can be probed experi­mentally. In another example, increasing the hydrolytic activity of PLC-â for the substrate PIP2 by 10-fold caused an expected stimulatory effect, raising intracellular calcium and steady-state levels of cytosolic inositol phosphates (IP3, IP2, and IP) between 2- and 3-fold. Interestingly, reaction fluxes for phosphoinositide hydrolysis were diminished, possibly due to substrate depletion. Taken together, these examples illustrate the system-wide effects of perturbations in the kinetic rate processes. The procedure could easily be extended to examine multiple simultaneous per­turbations in both reaction rates and steady-state concentrations. In future applications of this approach, genomic or proteomic information of multiple perturbations could be used to help predict platelet signaling phenotypes.

Fig 4 Shifts in steady-state profiles caused by kinetic perturbations

FIGURE 4 | Shifts in steady-state profiles caused by kinetic perturbations. The steady-state platelet model was perturbed by changing selected kinetic parameters (±10-fold) and simulating for 1 h. After approaching a new steady state, the model concentrations and fluxes were determined relative to their original steady-state values and colored according to fold-change. Green indicates no change (NC) relative to initial flux/concentration. Red indicates a relative increase and blue indicates a relative decrease. Note that the color scale in each panel is normalized separately to maximize distinctions in fold change. New steady states were achieved after (top) 10-fold decrease in PKC-mediated inhibition of PLC-β, and (bottom) 10-fold increase in PIP2 hydrolysis (10-fold increase in kcat of hydrolysis). ∗, active state.

Fig 5. predicting global calcium response

FIGURE 5 | Pairwise agonist scanning to predict global calcium response in human platelets. (A) Simplified schematic of signaling pathways examined in this study that converge on intracellular calcium release in human platelets. (B) Dynamic NN model used to train platelet response to combinatorial agonist activation. A sequence of input signals representing agonist concentrations is introduced to the network at each time point. Processing layers integrate input values with feedback signals to predict the next time point. (C) A total of 154 calcium traces were measured for single and pairwise activation using 6 different agonists (“Experiment”) and used for neural network training. The NN training accurately predicted (“NN Prediction”) the training data.

Fig 6. Multiscale modeling with 4 components

FIGURE 6 | Multiscale modeling. The multiscale model has four main components (A) fluid flow, transport of soluble species, motion and binding of platelets, and the activation state of each platelet. The fluid flow is perturbed by the growing clot and is determined using the lattice Boltzmann method. The released soluble agonists form a boundary layer in the flow, and this process is determined using the finite element method. Platelet motion and bonding are simulated with lattice kinetic Monte Carlo. Platelet activation state is estimated from the history of intracellular calcium concentration, which is determined by a neural network model. (B) Multiscale simulation of patient-specific platelet deposition under flow for a specific donor and PAS-trained neural network of calcium signaling. Platelet activation (black, unactivated; white, activated) and deposition at 500 s (inlet wall shear rate, 200 s−1) showing released ADP (top) and TXA2 (middle) and perturbation of the flow field (bottom). Flow: left to right (streamlines, black lines); surface collagen (250 ìm long): red bar.  

PLATELET INTERACTIONS WITH THE VESSEL WALL

The multiscale systems biology model accommodates platelet sig­naling, platelet adhesion to collagen and other activated platelets, release of soluble agonists, thrombus growth, and distortion of the prevailing flow field (Figure 6A). The lattice Boltzmann (LB) method is used to solve for the velocity field of the fluid. Platelets in the growing aggregate release ADP and TXA2 into the fluid, and a boundary layer is formed with the flow. The dynamics of this process are determined with a finite element method solution of the convection-diffusion-reaction equation for each of the soluble species, ADP and TXA2. Platelets move in the fluid by convection and RBC-augmented dispersion. They also bind to the collagen surface as well as previously bound platelets. The motion and binding of platelets is simulated using the convective lattice kinetic Monte Carlo (LKMC) algorithm validated for stochastic convective-diffusive particle transport (Flamm et al., 2009, 2011, 2012). The level of integrin activation and associated adhesiveness for each platelet is related to the cumulative intracellular calcium concentration. The intracellu­lar calcium concentration is determined using a NN trained on a specifc patient’s platelet PAS phenotyping experiment. Using this multiscale approach, Multiscale simulations predicted the density of platelets adherent to the surface, platelet activation states, as well as the spatiotemporal dynamics of ADP and TXA2 release, morphology of the growing aggregate, and the distribu­tion of shear along the solid-fluid boundary (Figure 6B). Platelets stick to the collagen surface and release ADP and TXA2 which forms a boundary layer extending up to 10 pm from the throm­bus. Boundary layer concentrations of up to 10 pM ADP and 0.1 pM TXA2 were found by simulation. TXA2 concentrations were found to be sub-physiological (<0.0067 pM or <0.1 xEC50) until a sufficient platelet mass accumulated at the surface after ∼250 s. Boundary layer ADP concentrations were within the effective dynamic range (0.1–10 pM) throughout the simulation. The strong temporal and spatial fluctuations in the concentration of ADP were predominately driven by the short release time (5 s), whereas the longer release time of TXA2 (100 s) smoothed fluc­tuations. The shear rate along the solid-fluid boundary became nonuniform during the simulation (5–10-fold increase above 200 s−1) due to surface roughness. At 500 s, the platelet deposit was characterized by platelet clusters 20–30 pm in length, fully consistent with microfluidic measurements of platelet cluster size on collagen at this shear rate.

Developing tools to define platelet variations between patients and the relationship of platelet phenotype to prothrombotic or bleeding traits will have significant impact in stratifying patients according to risk. This multiscale approach also makes feasible patient-specific prediction of platelet deposi­tion and drug response in more complex in vivo geometries such as stenosis, aneurysms, stented vessels, valves, bifurcations, or ves­sel rupture (for prediction of bleeding risks) or in geometries encountered in mechanical biomedical devices.

 Platelet–Leukocyte–Endothelial Cell Interactions After Middle Cerebral Artery Occlusion

Mami Ishikawa, *Dianne Cooper, *Thiruma V. Arumugam, †John H. Zhang, †Anil Nanda, and *D. Neil Granger
Departments of *Molecular and Cellular Physiology, and †Neurosurgery, Louisiana State University Health Sciences Center, Shreveport, LA
Journal of Cerebral Blood Flow & Metabolism 24:907–915 © 2004 

Summary: The adhesion of both leukocytes and platelets to microvascular endothelial cells has been implicated in the pathogenesis of ischemia/reperfusion (I/R) injury in several vascular beds. The objectives of this study were to (1) assess the platelet–leukocyte–endothelial cell interactions induced in the cerebral microvasculature by middle cerebral artery occlu­sion (MCAO)/reperfusion, and (2) define the molecular deter­minants of the prothrombogenic and inflammatory responses in this model of focal I/R. MCAO was induced for 1 hour in wild-type (WT) mice, WT mice treated with a monoclonal antibody (mAb) to either P-selectin or GPIIb/IIIa, and in P-selectin−/−(P-sel−/−) chimeras. Isolated platelets labeled with carboxyfluorescein diacetate succinimidyl ester (CFDASE) were administered intravenously and observed with intravital fluorescence microscopy. Leukocytes were observed after in­travenous injection of rhodamine 6G. One hour of MCAO fol­lowed by 1 hour of reperfusion resulted in the rolling and adhesion of leukocytes in venules, and after 4 hours of reperfusion, the adhesion of both leukocytes and platelets was de­tected. Although both the P-selectin and GPIIb/IIIa mAbs sig­nificantly reduced the adhesion of leukocytes and platelets at 4 hours of reperfusion, the antiadhesive effects of the P-selectin mAb were much greater. The leukocyte and platelet adhesion responses were significantly attenuated in both P-sel−/−-WT and WT-P-sel−/− bone marrow chimeras, compared with WT-WT chimeras. Neutropenia, induced by antineutrophil serum treatment, also reduced the recruitment of leukocytes and platelets after cerebral I/R. These findings implicate a ma­jor role for both platelet-associated and endothelial cell– associated P-selectin, as well as neutrophils in the inflamma­tory and prothrombogenic responses in the microcirculation after focal cerebral I/R.
Key Words: Platelet—Leukocyte—P-selectin—GPIIb/IIIa—Cerebral ischemia—Reperfusion.

Adhesion of leukocytes and platelets after treatment with mAb against P-selectin or GPIIIb/IIIa

The I/R-induced recruitment of rolling and adherent leuko­cytes was significantly attenuated in P-selectin mAb-treated mice, compared with the responses noted in untreated mice exposed to 1-hour MCAO and 4-hour reperfusion (Figs. 3A and 3B). However, the number of adherent leukocytes after P-selectin mAb treatment remained elevated above the level de­tected in sham experiments. Both the rolling and firm adhesion of platelets was reduced to sham levels in the P-selectin mAb-treated mice. Although treatment with a GPIIb/IIIa mAb sig­nificantly reduced the adhesion of both platelets and leukocytes after I/R, the reductions noted were relatively small compared with the responses seen with the P-selectin mAb.

Leukocyte and platelet adhesion in P-selectin–deficient bone marrow chimeras

Our findings related to the role of platelet-associated and endothelial cell–associated P-selectin in mediating the I/R-induced rolling and adhesion of leukocytes and platelets are summarized in Fig. 4.  In P-sel / -WT chimeras, the number of rolling and adherent leukocytes were significantly but not completely reduced compared with WT—WT chimeras. However, compared with WT—WT chimeras, the rolling and firm adhesion of platelets was virtually abolished after I/R. In WT—P-sel−/− chimeras, the number of rolling and adherent leu­kocytes and platelets also decreased significantly com­pare with WT—WT chimeras; however, some adhesion of leukocytes and platelets was still detected after I/R, similar to the responses noted in the group treated with the P-selectin blocking mAb.

Plateletleukocyte interaction

Platelets were noted to adhere directly onto adherent leukocytes and platelet-bearing leukocytes were occa­sionally observed rolling in postischemic venules. Some free-flowing platelets were seen to suddenly bind (with-out rolling) on adherent leukocytes. Some of these plate­lets detached from the adherent leukocyte whereas others adhered firmly on the leukocyte. Other platelets were seen to roll and adhere directly on venular endothelium. To quantify the contribution of leukocytes to I/R-induced platelet recruitment, some mice were rendered neutropenic with antineutrophil serum. Although leuko­cyte rolling and adherence were still observed in cerebral venules of serum-treated mice after I/R, the responses were dramatically reduced. The cerebral venules of neutropenic mice also exhibited large and significant reduc­tions in rolling and adherent platelets after I/R (Fig. 5).

Fig  platelet and endothelial cell–associated P-selectin in mediating rolling and adhesion of leukocytes

FIG. 4. Role of platelet-associated and endothelial cell–associated P-selectin in mediating I/R-induced rolling and adhesion of leuko­cytes (A) and platelets (B). Four or five animals were studied in each group. Mice in all groups were exposed to 1 hour of MCAO followed by 4 hours of reperfusion. WT—*WT and WT—*P-sel−/− chi­meras received CFDASE-labeled platelets from WT mice. P-sel−/−—*WT chimeras received CFDASE-labeled platelets from P-sel−/− mice. *P < 0.05 relative to the WT*WT (control) chimeras.

Signal-Dependent Protein Synthesis by Activated Platelets: New Pathways to Altered Phenotype and Function

Guy A. Zimmerman and Andrew S. Weyrich
Arterioscler Thromb Vasc Biol. 2008;28:s17-s24       http://dx.do.org/10.1161/ATVBAHA.107.160218      http://atvb.ahajournals.org/content/28/3/s17         Online ISSN: 1524-4636

New biologic activities of platelets continue to be discovered, indicating that concepts of platelet function in hemostasis, thrombosis, and inflammation require reconsideration as new paradigms evolve. Studies done over 3 decades ago demonstrated that mature circulating platelets have protein synthetic capacity, but it was thought to be low level and inconsequential. In contrast, recent discoveries demonstrate that platelets synthesize protein products with important biologic activities in a rapid and sustained fashion in response to cellular activation. This process, termed signal-dependent translation, uses a constitutive transcriptome and specialized pathways, and can alter platelet phenotype and functions in a fashion that can have clinical relevance. Signal-dependent translation and consequent protein synthesis are examples of a diverse group of posttranscriptural mechanisms in activated platelets that are now being revealed. (Arterioscler Thromb Vasc Biol. 2008;28:s17-s24)
Key Words: platelets . translation . protein synthesis . transcriptome . proteome . thrombosis

This article is part of a multi-part CME-certified activity titled Translational Therapeutics at the Platelet Vascular Interface. 

New Paradigms at the Vascular Interface

The acute hemostatic functions of platelets are well known, have dominated the attention of the field for decades, and have been the founda­tion for discoveries that generated new molecular therapies. Rapid, immediate activation responses mediate platelet-dependent thrombosis in a variety of pathologic conditions, and pharmacological antiplatelet strategies are largely aimed at these events. Nevertheless, the focus on adhesion, aggre­gation, and secretion, and the view that platelets have a repertoire of activities primarily restricted to these acute processes, have also generated a central dogma that may inappropriately limit our view of their actions at the vascular interface and in other settings in health and disease. Clearly, our understanding of the molecular mechanisms by which platelets influence hemostasis, thrombosis, regulated and dysregulated inflammation, and neoplasia remains incom­plete and continues to evolve. New paradigms are emerging as previously unrecognized pathways in platelets are identi­fied, and unanticipated activities are characterized. In this regard, the current state of the field of platelet biology may be akin to that of endothelial cells several decades ago, when endothelium was thought by most investigators and physi­cians to have a limited range of responses; on the contrary, however, when this dogma was reexamined using new approaches that included primary culture of human endothe-lium, active participation of these cells in interactions with leukocytes and a variety of other previously unrecognized functions were discovered. If the comparison is accurate, new paradigms relevant to activities of platelets at the vascular interface are likely to be reported with some frequency.

Alternative and traditional views of selected features of platelet biology are listed in the Table. There is already considerable evidence for some of the alternative themes, such as inflammatory and immune activities of platelets,10–16 whereas others are less well explored and more speculative. The remainder of this review summarizes evidence for one such functional capability not generally recognized in plate­lets until recent discoveries revealed it: synthesis of new protein products in response to cellular activation (reviewed in references5,17).

Table. New Biology of Platelets: Traditional Paradigms May Be Insufficient to Understand Platelet Activities at the Vascular Interface

Traditional View                                                                                                                                              Alternate View

Platelets are biologically simple because they are anucleate                   Platelets have specializations and biologic activities that are novel and complex. Some

and have a limited repertoire of responses.                                                                                     activities are yet to be discovered.

Platelets do not express new gene products.                                             Platelets have diverse posttranscriptional mechanisms and use a transcriptome and

specialized pathways to modify their proteome, phenotype, and functions.

Platelets are short-acting cells in clots and damaged tissue.                      Platelets can be relatively long-lived and can mediate cell-cell interactions for many

hours after initial adhesion, aggregation, and secretion.

Platelets operate exclusively in the intravascular                                               Platelets can influence critical events in the extravascular milieu in direct

compartment.                                                                                                                                            and indirect fashions.

Observations from a number of laboratories now demonstrate that physiologically relevant activation signals induce translation of proteins with impor­tant functions from constitutive or posttranscriptionally pro­cessed messenger RNAs (mRNAs) in human and murine platelets, a process that we have termed signal-dependent translation. These and other studies indicate that the platelet has intricate posttranscriptional mechanisms that allow it to alter its proteome, phenotype, and functions by accomplish­ing new protein synthesis in response to cellular activation. This capacity may allow platelets to modify the complex milieu of the vascular interface in ways that were previously unrecognized.

Essentially, all of the platelets isolated from normal subjects incorporated radiolabeled amino acids into new protein, demonstrating that this function is not a property of a subset of immature cells. Platelets from splenectomized subjects with idiopathic throm-bocytopenic purpura had increased levels of amino acid incorporation into protein, indicating that the physiological state of the subject or the age and maturity of the platelets influence protein synthesis. Extracellular factors were re­ported to alter protein synthesis by human platelets under some conditions. This provided evidence suggesting that the synthetic mechanisms involved are regulated.

The Platelet Transcriptome

Circulating human platelets have a substantial and diverse transcriptome, in addition to protein synthetic machinery. RNA-selective fluorescent dyes stain the entire population of platelets isolated from normal subjects, indicating the presence of RNA species transcribed by parent megakaryocytes. Messenger RNAs with 5′-methylguanosyl (m7G) caps and 3′ untranslated region polyadenylated tails are present, as are 18S and 28S ribosomal proteins, which are integral to the structure of ribo-somes. Early experiments with intact platelets from nor­mal subjects indicated that some of the mRNA transcripts are competent to serve as templates for proteins and have relatively long functional half lives that correlate with the lifespan of platelets in the circulation. This observation then lay fallow, for the most part, until the advent of reverse transcriptase polymer-ase chain reaction (RT-PCR) analysis and cDNA cloning meth-odologies. This infusion of new technology resulted in construction of cDNA libraries from platelet transcripts. Most recently, transcript profiling by microarray analysis and serial analysis of gene expression (SAGE) have been applied to platelets, identifying 1500 to 3000 unique transcripts in platelets from normal subjects, depending on the approach. Both cytoplasmic and mitochondrial transcripts are represented.35 There is substantial consistency between data generated by microarray analysis and SAGE, and in platelets isolated from different normal donors.

Multiple Proteins Are Synthesized by Activated Human Platelets

Although early studies indicated that platelets have protein synthetic capacity, the general concept in the field has been that it is low level, vestigial, and likely inconsequential. Several texts of hemostasis and platelet biology do not mention this function, and some commentaries conclude that platelets are simply incapable of any new protein synthesis. Consistent with the notion that platelets have low basal protein synthesis, little incorporation of the radiolabeled amino acid is detectable when freshly isolated human plate­lets are incubated with [35S] methionine under resting condi­tions in the absence of activation. However, when an activat­ing signal is delivered to platelets incubated in parallel, multiple labeled proteins are synthesized when lysates and soluble fractions are analyzed by 1-dimensional or 2-dimensional gel electrophoresis (Lindemann S, Weyrich AS, Zimmerman GA, 2001). Some of these newly synthe­sized proteins have been identified and mechanisms of their signal-dependent translation determined.

Recent findings provided clear evidence for signal-dependent (that is, induced by activating signals) translation of Bcl-3 from mRNA that is transcribed in parent megakaryocytes but is repressed, or “silenced,” in circulating platelets under resting, basal conditions. Immunocytochemical de­tection of Bcl-3 in platelets in inflamed and thrombosed human vessels in surgical specimens (Figure 1D) provided in situ evidence that the experimental observations have physi­ological and clinical relevance. We subsequently found that collagen, platelet-activating factor, ADP, and epinephrine are also agonists for signal-dependent translation in plate-lets. Collagen was recently reported to induce Bcl-3 synthesis by platelets in experiments by other investigators. The time course of Bcl-3 synthesis in response to thrombin yielded additional important insights: newly synthesized Bcl-3 could be detected in activated platelets within 15 to 30 minutes in some experiments, consistent with translation of constitutively present mRNA without a requirement for new transcription. This feature is also consistent with the biology of platelets as rapid response cells. Nevertheless, synthesis of Bcl-3 is also prolonged over many hours, indicating that platelets may have important functions in thrombi and injured vessels well beyond the first few minutes of acute activation.

We examined the effect of rapamycin and found that it completely and selectively inhibited Bcl-3 synthesis in thrombin-stimulated platelets, and also inhibited phosphorylation of 4E-BP1 assayed as a marker of mTOR activation in parallel. Pharmacological inhibition of phosphatidylinositol-3-kinase, which lies upstream from

mTOR in signaling cascades linking surface receptors to mTOR activation,49 also blocked both 4E-BP1 phosphoryla-tion and Bcl-3 synthesis.52 Together, these studies demon­strated that synthesis of Bcl-3 is controlled by mTOR and provided evidence for a new and previously unrecognized activity of mTOR as a regulator of expression of specific protein products and phenotypic changes in terminally differ­entiated cells in response to signals delivered via G protein– coupled receptors and integrins.52 This observation in platelets contributed to a parallel set of discoveries demonstrating that mTOR has similar roles in myeloid leukocytes.69–71 The find­ings also suggest that inhibition of mTOR by rapamycin may have novel therapeutic effects on gene expression by platelets and leukocytes independent of inhibition of proliferation of other cell types when this agent is applied in antiangiogenic strategies and in “drug-eluting” vascular stents in the clinic.72

Although Bcl-3 provided an index example of specialized, signal-dependent translation of a protein product in activated platelets the functional relevance of this event was not immediately obvious and was initially perplexing because the activity assigned to Bcl-3 at that time was as a transcriptional regulator. A clue lay in the domain structure of Bcl-3, which includes ankyrin repeats and proline-rich N and C termini, suggesting the possibility of multiple protein-protein interactions. Based on this information, we designed experi­ments to determine whether newly synthesized Bcl-3 interacts with other intracellular proteins. We found that Bcl-3 specifi­cally binds to the tyrosine kinase Fyn via the Fyn SH2 domain in activated platelets and transfected COS cells. Bcl-3 also associates with the actin cytoskeleton in platelets.53

Because Fyn and related intracellular tyrosine kinases influence contractile responses of activated platelets, we examined the contributions of Bcl-3 and mTOR to fibrin clot retraction. Clot retraction is proposed to stabilize thrombi and to modify thrombus remodeling and resolution. It can be modeled in vitro, where activated platelets retract and condense fibrin strands in a fashion that can be examined macroscopically and microscopically (Figure 1E). In paral­lel loss-of-function and gain-of-function strategies, inhibition of mTOR activity in human platelets using rapamycin under conditions that block Bcl-3 synthesis inhibited clot retraction,

Common and Specialized Elements in Platelet Translational Pathways and Transcripts

Biologic Advantages of Signal-Dependent Translation, and Potential Roles in Disease

Novel Pathways to Signal-Dependent Translation in Activated Human Platelets

Activated Platelets Synthesize Additional Proteins Under Signal-Dependent Control

Translation in Activated Human Platelets

Discovery of synthesis of Bcl-3 by activated platelets sparked a search for the identities of other protein products, yielding IL-1J3 and TF. It also led to the unexpected discovery that their synthesis is preceded by signal-dependent cytoplasmic splicing of IL-1J3 and TF pre-mRNAs, yielding mature transcripts that are translated into precursor (IL-1J3) and active (TF) proteins.24,43,44 This identified a novel mechanism not previously recognized in activated mammalian cells. The splicing capacities of activated platelets are intricate and will be reviewed separately. Signal-dependent splicing, to­gether with the mTOR-dependent translational control mech­anism and other regulatory pathways discussed here, indicate that platelets have unexpected diversity in posttranscriptional control. Previous and ongoing studies add to this conclusion and suggest that platelets may also use ribosomal “stalling” or polypeptide termination, participation of micro RNAs (Denis MM, Trask B, Schwertz H, Weyrich AS, Zimmerman GA, 2004) and, potentially, other modes of control.

References

  1. Lindemann S, McIntyre TM, Prescott SM, Zimmerman GA, Weyrich AS. Platelet signal-dependent protein synthesis. In: Quinn M, Fitzgerald D, eds. Platelet Function: Assessment, Diagnosis, and Treatment. Totowa, NJ: Humana Press Inc.;2005:149-74.
  2. Weyrich AS, Lindemann S, Tolley ND, Kraiss LW, Dixon DA, Mahoney TM, Prescott SP, McIntyre TM, Zimmerman GA. Change in protein phenotype without a nucleus: translational control in platelets. Semin Thromb Hemost. 2004;30:491–498.

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nihms-292073-f0002  platelet and vessel

Protein_Slide_2  proteome

nihms-292073-f0001  platelets support integrity and barrier function

Read Full Post »

Do Novel Anticoagulants Affect the PT/INR? The Cases of  XARELTO (rivaroxaban) or PRADAXA (dabigatran)

Curators: Vivek Lal, MBBS, MD, FCIR, Justin D Pearlman, MD, PhD, FACC

and

Article Curator: Aviva Lev-Ari, PhD, RN

WC 3

WordCloud by Zach Day; Article Title: Do Novel Anticoagulants Affect the PT/INR? The Cases of XARELTO (rivaroxaban) and PRADAXA (dabigatran)

UPDATED on 7/16/2019

More of Xarelto’s scripts came from Medicare Part D patients in Q2 of this year compared with last, according to J&J’s earnings presentation. And J&J was on the hook for a bigger share of patient costs in Medicare Part D’s donut hole. Congress implemented the donut hole change last year, forcing drugmakers to pay more to move patients out of the coverage gap.

Once J&J gets a few quarters ahead of those changes, Xarelto should start turning in more impressive growth percentages, Duato said. How? J&J plans to grow Xarelto’s market share and volume in existing uses, plus focus on launches in new indications, Duato said, though he didn’t specify exactly how it’ll pump up that volume.

Bristol-Myers Squibb and Pfizer’s rival drug Eliquis is surely facing some of the same issues—the donut hole provision, for instance—but its sales look much healthier. While BMS hasn’t yet released second-quarter results, it did report a 36% boost to U.S. Eliquis sales in the first quarter, to $1.2 billion. For comparison, J&J’s Xarelto posted a 6.3% decrease to $542 million for the same period in the U.S.

SOURCE

J&J execs have plenty to brag about in pharma. Why downplay Xarelto, Zytiga woes?

https://www.fiercepharma.com/pharma/j-j-strives-for-above-market-growth-despite-challenges-for-zytiga-xarelto?mkt_tok=eyJpIjoiWldFNE1EY3dNemhoWWpOaiIsInQiOiJcL1BuSDVXcWZmMDd6NE9YQjV0S2ZRSTVKMnpWb3dZXC9NS3Q3NWlyb3BWUlBpZEF3SjZpUWdtTWRvemhIQ0hBa0lxa0h4WEdSc1p4XC9oTTQ2cmVpSG10dGJSTmp3cmJOMWNlb2xPNXVFeExVZ3d6cHJFdkFDc052NkUxMWozWitEaiJ9&mrkid=993697

UPDATED ON 7/21/2016

Xarelto Lawsuits

The blood-thinner Xarelto can cause uncontrolled bleeding — a dangerous and possibly fatal side effect for which there is no antidote. Plaintiffs who say they were harmed by the drug and family members who lost loved ones to severe bleeding filed lawsuits against Bayer, the drug’s maker. They claim Bayer failed to warn them and manufactured a faulty drug.

SOURCE

https://www.drugwatch.com/xarelto/lawsuit/

UPDATED on 8/4/2014

A cost-analysis model for anticoagulant treatment in the hospital setting

Journal of Medical Economics

July 2014, Vol. 17, No. 7 , Pages 492-498 (doi:10.3111/13696998.2014.914032)

aJanssen Scientific Affairs, LLC,

Raritan, NJ

USA

bAnalysis Group, Inc.,

Boston, MA

USA

cGroupe d’analyse, Ltée,

Montréal, Québec

Canada

dJanssen Scientific Affairs, LLC,

Raritan, NJ

USA

Address for correspondence: 

Lynn Huynh, Associate

Analysis Group, Inc.,

111 Huntington Ave. Tenth Floor, Boston, MA 02199

USA. Tel.: 617-425-8189; Fax: 617-425-8001

 

Abstract

Background:

Rivaroxaban is the first oral factor Xa inhibitor approved in the US to reduce the risk of stroke and blood clots among people with non-valvular atrial fibrillation, treat deep vein thrombosis (DVT), treat pulmonary embolism (PE), reduce the risk of recurrence of DVT and PE, and prevent DVT and PE after knee or hip replacement surgery. The objective of this study was to evaluate the costs from a hospital perspective of treating patients with rivaroxaban vs other anticoagulant agents across these five populations.

Methods:

An economic model was developed using treatment regimens from the ROCKET-AF, EINSTEIN-DVT and PE, and RECORD1-3 randomized clinical trials. The distribution of hospital admissions used in the model across the different populations was derived from the 2010 Healthcare Cost and Utilization Project database. The model compared total costs of anticoagulant treatment, monitoring, inpatient stay, and administration for patients receiving rivaroxaban vs other anticoagulant agents. The length of inpatient stay (LOS) was determined from the literature.

Results:

Across all populations, rivaroxaban was associated with an overall mean cost savings of $1520 per patient. The largest cost savings associated with rivaroxaban was observed in patients with DVT or PE ($6205 and $2742 per patient, respectively). The main driver of the cost savings resulted from the reduction in LOS associated with rivaroxaban, contributing to ∼90% of the total savings. Furthermore, the overall mean anticoagulant treatment cost was lower for rivaroxaban vs the reference groups.

Limitations:

The distribution of patients across indications used in the model may not be generalizable to all hospitals, where practice patterns may vary, and average LOS cost may not reflect the actual reimbursements that hospitals received.

Conclusion:

From a hospital perspective, the use of rivaroxaban may be associated with cost savings when compared to other anticoagulant treatments due to lower drug cost and shorter LOS associated with rivaroxaban.

SOURCE

http://informahealthcare.com/doi/abs/10.3111/13696998.2014.914032

Introduction

Justin D Pearlman, MD, PhD, FACC

The classic medication for chronic anti-coagulation is coumadin, but it is problematic. Coumadin impedes the production of coagulation proteins that depend on vitamin K (factors 7, 9, 10, and 2, in order of half-lifes, which range 2-72 hours). Consequently, a change in dose today does not have full impact for 2-3 days. Physicians and pharmacists have difficulties adjusting the dose to its target effect on the biomarker test International Normalized Ratio (INR). The therapeutic range is very narrow. A change in intake of leafy green vegetables can have profound impact (by changing intake of vitamin K). A change in virtually any medication or vitamin that can bind to albumin can also profoundly change the INR to a life-threatening level, because 80% of coumadin is inactivated by binding to albumin, and displacement of coumadin by other agents can boost the effective circulating amount. Those limitations, and the need for testing each month and each medication change have stimulated the development of alternatives. For example, rivaroxaban is a new anticogulant that focuses on factor 10 (factor X), deemed as good as coumadin without the need for the blood tests. In fact, INR test for rivaroxaban is misleading, as values may range as high at 7 (“DANGER”) at normal therapeutic dosing. The following reviews some of the data on that unexpected issue. Physicians not aware of this “false positive” have demanded stoppage of therapy due to the inapplicable spuriously high INR values.

UPDATED on 9/25

Dabigatran versus Warfarin in Patients with Mechanical Heart Valves

Dabigatran is an oral direct thrombin inhibitor that has been shown to be an effective alternative to warfarin in patients with atrial fibrillation. We evaluated the use of dabigatran in patients with mechanical heart valves.

RESULTS

The trial was terminated prematurely after the enrollment of 252 patients because of an excess of thromboembolic and bleeding events among patients in the dabigatran group. In the as-treated analysis, dose adjustment or discontinuation of dabigatran was required in 52 of 162 patients (32%). Ischemic or unspecified stroke occurred in 9 patients (5%) in the dabigatran group and in no patients in the warfarin group; major bleeding occurred in 7 patients (4%) and 2 patients (2%), respectively. All patients with major bleeding had pericardial bleeding.

CONCLUSIONS

The use of dabigatran in patients with mechanical heart valves was associated with increased rates of thromboembolic and bleeding complications, as compared with warfarin, thus showing no benefit and an excess risk. (Funded by Boehringer Ingelheim; ClinicalTrials.gov numbers, NCT01452347 and NCT01505881.)

SOURCE

N Engl J Med 2013; 369:1206-1214 September 26, 2013 DOI: 10.1056/NEJMoa1300615

UPDATED on 9/23

ESC: Edoxaban Bests Warfarin on Safety in VTE

By Peggy Peck, Editor-in-Chief, MedPage Today
Reviewed by Robert Jasmer, MD; Associate Clinical Professor of Medicine, University of California, San Francisco and Dorothy Caputo, MA, BSN, RN, Nurse Planner
Action Points

AMSTERDAM — Edoxaban, a novel factor Xa inhibitor, met its primary endpoints in a trial that pitted it against warfarin for treatment of symptomatic venous thromboembolism (VTE).

Among more than 8,000 patients with deep-vein thrombosis (DVT) or pulmonary embolism (PE), 130 (3.2%) of the patients treated with edoxaban had a recurrent, symptomatic VTE versus 146 (3.5%) warfarin-treated patients, a hazard ratio of 0.89 (95% CI 0.70-1.13, P<0.004 for non-inferiority), Harry R. Büller, MD, of the Academic Medical Center, Amsterdam, reported in a Hot Line session at theEuropean Society of Cardiology meeting here.

The safety endpoint was bleeding (major or clinically relevant non-major bleeding), and in that analysis edoxaban was superior to warfarin, as 8.5% of the edoxaban patients had bleeding events versus 10.3% of the patients in the warfarin group (P=0.004 for superiority).

Moreover, edoxaban appeared to work best in the highest-risk patients — 938 patients with pulmonary embolism and right ventricular dysfunction assessed by N-terminal pro-brain natriuretic peptide levels. In those patients, the recurrent VTE rate was 3.3% in the edoxaban group versus 6.2% in the warfarin group, Büller said.

Based on the results in that very high risk population, Büller predicted that clinicians treating those patients will consider that efficacy profile when selecting an oral Factor Xa inhibitor.

The study, from the Hokusai VTE Investigators, was simultaneously published online by the New England Journal of Medicine.

In the highly competitive oral anticoagulant group, those numbers look good, but at first blush the two already approved Factor Xa inhibitors, rivaroxaban (Xarelto) and apixaban (Eliquis) looked better when they were studied in VTE.

In EINSTEIN-VTE, rivaroxaban had a recurrent symptomatic VTE rate of 2.1%, and 8.1% of patients met the safety endpoint.

Likewise, in another VTE trial — AMPLIFY-EXT — apixaban (2.5 mg or 5 mg twice a day) had a recurrent or VTE-related death rate of 1.7%, and 3.2% of the patients who received low-dose apixaban reached the safety endpoint, as did 4.3% of patients treated with 5 mg of apixaban.

Patrick T. O’Gara, MD, American College of Cardiology president-elect, praised the design of the trial, but he agreed that “for mortality benefit, apixaban does appear to have the edge.”

That apixaban benefit, O’Gara said, is militated by the fact that patients need to take the drug twice daily, while “edoxaban is once a day, as is rivaroxaban.”

Asked if there was a specific population that might benefit from edoxaban versus rivaroxaban or apixaban, O’Gara, who is director of clinical cardiology at Brigham and Women’s Hospital and a professor at Harvard Medical School, said the findings from the Hokusai researchers did not provide that answer.

The attempt at a cross-trial comparison drew harsh criticism from Elliott Antman, MD, principal investigator in a trial of edoxaban for prevention of stroke in patients with atrial fibrillation (ENGAGE-AF).

Antman, who like O’Gara is a Harvard professor, said that comparing the edoxaban VTE results to EINSTEIN-VTE or AMPLIFY-EXT would only lead to false conclusions. “You could repeat the rivaroxaban trial 100 times and still not achieve data that can be compared.”

Stavros V. Konstantinides MD, PhD, of the Medical University in Mainz, Germany, who was the ESC discussant for the paper, said that, despite the advantage of once-daily dosing of edoxaban, “apixaban has the best safety profile so far.”

Moreover, unlike the VTE studies of apixaban and rivaroxaban, all patients in the Hokusai trial received heparin for 5 days. After that heparin run-in, patients were randomized to edoxaban or to warfarin. The median duration of heparin after randomization was 7 days.

Antman said that design best replicated real-world clinical practice, in which heparin is usually started before warfarin.

Buller noted that he was an investigator for the EINSTEIN-VTE study, “and after that the thinking was maybe we don’t need low molecular weight heparin, but now I think we need to reconsider that assumption.”

The Hokusai-VTE trial recruited 4,921 patients with DVT and 3,319 patients with PE. Patients initially were treated with heparin, and then were randomized to edoxaban (60 mg or 30 mg) or warfarin. There was an overlap of the heparin therapy when warfarin was started.

During a press conference, Keith Fox, MBChB, chair of the ESC scientific program, asked Buller if that overlap could have increased bleeding risk in the warfarin arm, thus introducing bias, but Buller said the overlap merely allowed warfarin to reach therapeutic range.

The edoxaban regimen “may be less handy, especially for early-discharge patients… [though] some doctors may feel more comfortable starting with low molecular weight heparin and then switching to edoxaban for the one-third of patients with severe PE,” Konstantinides said.

He added, “The NOACs [new oral anticoagulants] have shown efficacy and safety. Now, the test under real life conditions begins. They have to prove efficacy and safety there. I expect that. And they now must justify the high cost by showing … an improvement in patient treatment satisfaction and quality of life and, hopefully, a reduction in healthcare costs … with lower hospitalizations.”

The average age of patients in the Hokusai study was 56-57, and just over half were men.

Patients were enrolled from January 2011 through October 2012 at 439 centers in 37 countries.

About 40% of patients were treated for a year, and 80% of the edoxaban group was adherent to study treatment. Among the warfarin patients, average time in therapeutic range was 63.5%.

The study was supported by Daiichi-Sankyo, which is developing edoxaban.

Buller reported personal fees from Daichi Sankyo during the study, as well as grant support and personal fees from Bayer Health Care and Pfizer. He also received personnal fees from Boehringer Ingelheim, Bristol-Myers Squibb, Isis Pharmaceuticals, and ThromboGenics outside the submitted work.

Antman has a research grant from Daiichi-Sankyo through Brigham and Women’s Hospital. O’Gara said he had no financial disclosures.

SOURCE

http://www.medpagetoday.com/MeetingCoverage/ESC/41301?isalert=1#!

END of UPDATE

Introduction

Author: Vivek Lal, MBBS, MD, FCIR

Pathological thromboembolism, as seen in Myocardial Infarction or stroke, led to the use of low dose aspirin as an-antiplatelet drug, as a prophylaxis for subsequent intravascular thrombotic episodes.  Aspirin, an irreversible Cyclo-oxygenase inhibitor, resulted in a reduction of the production of Thromboxane A2, which in itself is a powerful vaso-constrictor and a platelet aggregator.   Certain limitation with the use of aspirin necessitated the search for newer anti-platelet drugs, with a quicker onset of action, quick termination of action on cessation of treatment, and minimal side effects like bleeding.  ADP inhibitors like Clopidogrel, which inhibits the ADP dependent activation of Glycoprotein IIb/IIIa receptors, was the next in the armamentarium of these drugs.  Later, oral anti-coagulants like coumadin (warfarin sodium) were added to anti-platelet approach, to tackle the overactive coagulation cascade in pathological intravascular thrombosis.  Warfarin is a drug which counters the effects of Vit-K on the synthesis of coagulation factors in the liver.  Thus, all green leafy vegetables, which contain high amounts of Vit-K, will interfere with the action of Warfarin.   Moreover, warfarin is extremely prone to drug interations, owing to its biotransformation by hepatic microsomal enzymes, which are also metabolizing many other drugs.  Thus, a therapeutic drug monitoring of warfarin action is mandatory, which, is a big limitation to its use.  The quest for pharmacologically superior oral anticoagulants, as compared to Warfarin, reached an important milestone with the discovery of two major drugs, Dabigatran and Rivaroxaban.  Both these drugs are Direct Thrombin Inhibitors, though the indications and adverse events are somewhat different.  This post will discuss Rivaroxaban pharmacology in brief, and address certain clinical issues.

Question: Does rivaroxaban or dabigatran affect the PT or INR? Can either be monitored using the PT or INR?

Response from Jenny A. Van Amburgh, PharmD, CDE

Assistant Dean of Academic Affairs and Associate Clinical Professor, School of Pharmacy, Northeastern University; Director of the Clinical Pharmacy Team and Residency Program Director, Harbor Health Services, Inc., Boston, Massachusetts

Warfarin is the most commonly used anticoagulant for the prevention of thrombosis or stroke. Because of a narrow therapeutic window, it requires regular coagulation monitoring of the prothrombin time (PT)/international normalized ratio (INR).[1] As such, the inconvenience of frequent blood draws remains a major burden. For the first time in over 50 years, 2 new oral anticoagulants, dabigatran, a direct thrombin inhibitor, and rivaroxaban, a factor Xa inhibitor, were approved by the US Food and Drug Administration. While these anticoagulants carry similar side effects to warfarin, such as risk for gastrointestinal bleeding and intracranial hemorrhage, INR and PT monitoring are not required. How then are providers to gauge the safety and efficacy of the medication in a patient? Can clinicians monitor these medications with the conventional coagulation assays, or are they rendered useless?[1]

The effect of both dabigatran and rivaroxaban on commonly used coagulation assays has been evaluated in the literature, both in vitro and in vivo. The usefulness of these tests relates directly to the medications’ mechanisms of action. For both agents, the use of an INR to determine the effectiveness and safety is meaningless because INR is calibrated for use with vitamin K antagonists (such as warfarin) only.[1] Although use may be associated with an increase in INR, this increase does not relate to the effectiveness of therapy or provide a linear correlation of concentration and effect that is seen when measuring warfarin levels.[2,3] In some instances, point-of-care INR measurements have been drawn on patients using dabigatran; however, the results have failed to correlate to appropriateness in therapy and have varied greatly case by case.[4]

As dabigatran directly inhibits thrombin, PT measures lack the sensitivity to detect therapeutic levels.[1,5] Often, if this assay is measured in patients taking dabigatran, a subtherapeutic level is noted, regardless of concentration of dabigatran.[6] More appropriate assays for dabigatran may be activated partial thromboplastin time (aPTT), diluted thrombin time (TT), or ecarin clotting time (ECT). These tests are better able to capture changes throughout the clotting cascade. Using aPTT may underestimate high levels and could be used more as a qualitative assessment of activity instead of a quantitative assessment.[7] Where available and if desired, monitoring via the diluted TT or ECT has proved a more useful measure for dabigatran.[1]

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Information from Industry

Unlike dabigatran, studies have demonstrated a correlation between the levels of rivaroxaban and PT through inhibition of factor Xa, but not to the same extent as warfarin.[8] In some instances, the use of PT monitoring for this medication may be useful. A linear response between PT and rivaroxaban can be seen; however, the accuracy of the test improves when concentrations of rivaroxaban are higher. Additionally, the use of PT for monitoring rivaroxaban can be difficult because the measurement differs greatly depending on the reagent used to determine PT. Calibrating PT assays to assess rivaroxaban appropriately is an option currently being evaluated.[8]

In conclusion, the INR is not a viable option when assessing the use of dabigatran or rivaroxaban. Additionally, PT is not a viable option when monitoring a patient on dabigatran. However, PT may be an option for monitoring select patients on rivaroxaban until more reliable standardized tests are developed. Methods of measuring the effectiveness of these agents are currently being developed and tested; however, until they are made available, the existing tests may be adapted to be used in a more effective manner.

The author wishes to acknowledge the assistance of Jacqueline M. Kraft, PharmD, Ngoc Diem Nguyen, PharmD, and Phillipa Scheele, PharmD, PGY1 Residents, and Michael P. Conley, PharmD, and Nga T. Pham, PharmD, CDE, AE-C, Assistant Clinical Professors at Northeastern University — School of Pharmacy and Harbor Health Services, Inc., Boston, Massachusetts.

References

  1. Favaloro EJ, Lippi G. The new oral anticoagulants and the future of haemostasis laboratory testing. Biochem Med (Zagreb). 2012;22:329-341.
  2. Dager WE, Gosselin RC, Kitchen S, Dwyre D. Dabigatran effects on the international normalized ratio, activated partial thromboplastin time, thrombin time, and fibrinogen: a multicenter, in vitro study. Ann Pharmacother. 2012;46:1627-1636. Abstract
  3. Samama MM, Martinoli JL, LeFlem L, et al. Assessment of laboratory assays to measure rivaroxaban — an oral, direct factor Xa inhibitor. Thromb Haemost. 2010;103:815-825. Abstract
  4. O’Riordan M. Falsely elevated point-of-care INR values in dabigatran-treated patients. Heartwire. July 7, 2011.http://www.theheart.org/article/1251461.do. Accessed January 11, 2013.
  5. Halbmayer WM, Weigel G, Quehenberger P, et al. Interference of the new oral anticoagulant dabigatran with frequently used coagulation tests. Clin Chem Lab Med. 2012;50:1601-1605. Abstract
  6. Lindahl TL, Baghaei F, Blixter IF, et al. Effects of the oral, direct thrombin inhibitor dabigatran on five common coagulation assays. Thromb Haemost. 2011;105:371-378. Abstract
  7. Freyburger G, Macouillard G, Labrouche S, Sztark F. Coagulation parameters in patients receiving dabigatran etexilate or rivaroxaban: two observational studies in patients undergoing total hip or total knee replacement. Thromb Res. 2011;127:457-465. Abstract
  8. Hillarp A, Baghaei F, Fagerberg Blixter I, et al. Effects of the oral, direct factor Xa inhibitor rivaroxaban on commonly used coagulation assays. J Thromb Haemost. 2011;9:133-139. Abstract

SOURCE

http://www.medscape.com/viewarticle/778063

PRADAXA (dabigatran)

COMPARE TO WARFARIN FOR AFIB NOT CAUSED BY A HEART VALVE PROBLEM

PRADAXA represents progress in helping to reduce the risk of stroke due to atrial fibrillation (AFib) not caused by a heart valve problem.

Review the chart below to compare PRADAXA and warfarin (also known as Coumadin® or Jantoven®). And find out why your doctor may choose PRADAXA. Remember, only your doctor can decide which treatment may be right for you.

Medication type:
Both PRADAXA and warfarin are anticoagulants. These blood-thinning medicines help to stop clots by targeting factors your blood needs to form clots.PRADAXA and warfarin work differently to help reduce the risk of stroke due to AFib not caused by a heart valve problem.
PRADAXA is a direct thrombin inhibitor that helps to stop clots from forming by working directly on thrombin.PRADAXA is not for use in people with artificial (prosthetic) heart valves Warfarin is a vitamin K antagonist that helps to stop clots from forming by interfering with vitamin K—a vitamin your body needs to form clots.
Stroke risk reduction:
PRADAXA and warfarin help to stop clots by targeting factors your blood needs to form clots.
In a clinical trial of more than 18,000 people, PRADAXA 150 mg capsules was proven superior to warfarin at reducing the risk of stroke. Warfarin has been extensively studied and prescribed by doctors to help reduce the risk of stroke in people with AFib since 1954.
How you take the medication: PRADAXA is taken by mouth 2 times each day. Warfarin is taken by mouth once every day.
Dosing options: PRADAXA comes in 75 mg and 150 mg strengths.Your doctor will decide which dose is right for you based on a simple kidney function test. Warfarin comes in 1 mg, 2 mg, 2-1/2 mg, 3 mg, 4 mg, 5 mg, 6 mg, 7-1/2 mg, and 10 mg strengths.Your doctor will decide which dose is right for you. He or she will adjust your dose based on the results ofregular blood tests.Based on these tests, your doctor will determine your dose and adjust it, if necessary.
Monitoring: No need for regular blood tests.PRADAXA has been clinically proven to help reduce the risk of stroke in people with AFib not caused by a heart valve problem. And, unlike warfarin, there is no need for regular blood tests to see if your blood-thinning level is in the right range.
Learn more 
Requires regular blood test.Warfarin has also been proven to be an effective blood thinner. When you take warfarin, you need to have a regular blood test to measure International Normalized Ratio (INR) to determine the time it takes for your blood to clot.
Dietary restrictions: No dietary restrictionsPRADAXA requires no changes to your diet. Dietary restrictions requiredWhen you take warfarin, you need to limit foods high in vitamin K, such as large amounts of leafy green vegetables and some vegetable oils. This is because Vitamin K can affect the way warfarin works in your body.You may also need to limit alcohol, cranberry juice, and products containing cranberries.

SOURCE

https://www.pradaxa.com/compare-warfarin.jsp

 XARELTO (rivaroxaban)

WHAT IS XARELTO®?

XARELTO® is a prescription medicine used to reduce the risk of stroke and blood clots in people with atrial fibrillation, not caused by a heart valve problem. For patients currently well managed on warfarin, there is limited information on how XARELTO® and warfarin compare in reducing the risk of stroke.

XARELTO® is also a prescription medicine used to treat deep vein thrombosis and pulmonary embolism, and to help reduce the risk of these conditions occurring again.

XARELTO® is also a prescription medicine used to reduce the risk of forming a blood clot in the legs and lungs of people who have just had knee or hip replacement surgery.

IMPORTANT SAFETY INFORMATION

WHAT IS THE MOST IMPORTANT INFORMATION I SHOULD KNOW ABOUT XARELTO®?

  • For people taking XARELTO® for atrial fibrillation:
  • People with atrial fibrillation (an irregular heart beat) are at an increased risk of forming a blood clot in the heart, which can travel to the brain, causing a stroke, or to other parts of the body. XARELTO® lowers your chance of having a stroke by helping to prevent clots from forming. If you stop taking XARELTO®, you may have increased risk of forming a clot in your blood.
  • Do not stop taking XARELTO® without talking to the doctor who prescribes it for you. Stopping XARELTO® increases your risk of having a stroke.
  • If you have to stop taking XARELTO®, your doctor may prescribe another blood thinner medicine to prevent a blood clot from forming.
  • XARELTO® can cause bleeding, which can be serious, and rarely may lead to death. This is because XARELTO® is a blood thinner medicine that reduces blood clotting. While you take XARELTO® you are likely to bruise more easily and it may take longer for bleeding to stop.

You may have a higher risk of bleeding if you take XARELTO® and take other medicines that increase your risk of bleeding, including:

  • Aspirin or aspirin-containing products
  • Non-steroidal anti-inflammatory drugs (NSAIDs)
  • Warfarin sodium (Coumadin®, Jantoven®)
  • Any medicine that contains heparin
  • Clopidogrel (Plavix®)
  • Other medicines to prevent or treat blood clots

Tell your doctor if you take any of these medicines. Ask your doctor or pharmacist if you are not sure if your medicine is one listed above.

Call your doctor or get medical help right away if you develop any of these signs or symptoms of bleeding:

  • Unexpected bleeding or bleeding that lasts a long time, such as:
    • Nosebleeds that happen often
    • Unusual bleeding from gums
    • Menstrual bleeding that is heavier than normal, or vaginal bleeding
  • Bleeding that is severe or that you cannot control
  • Red, pink, or brown urine
  • Bright red or black stools (looks like tar)
  • Cough up blood or blood clots
  • Vomit blood or your vomit looks like “coffee grounds”
  • Headaches, feeling dizzy or weak
  • Pain, swelling, or new drainage at wound sites

Spinal or epidural blood clots (hematoma): People who take a blood thinner medicine (anticoagulant) like XARELTO®, and have medicine injected into their spinal and epidural area, or have a spinal puncture, have a risk of forming a blood clot that can cause long-term or permanent loss of the ability to move (paralysis). Your risk of developing a spinal or epidural blood clot is higher if:

  • A thin tube called an epidural catheter is placed in your back to give you certain medicine
  • You take NSAIDs or a medicine to prevent blood from clotting
  • You have a history of difficult or repeated epidural or spinal punctures
  • You have a history of problems with your spine or have had surgery on your spine

If you take XARELTO® and receive spinal anesthesia or have a spinal puncture, your doctor should watch you closely for symptoms of spinal or epidural blood clots. Tell your doctor right away if you have tingling, numbness, or muscle weakness, especially in your legs and feet.

XARELTO® is not for patients with artificial heart valves.

WHO SHOULD NOT TAKE XARELTO®?

Do not take XARELTO® if you:

  • Currently have certain types of abnormal bleeding. Talk to your doctor before taking XARELTO® if you currently have unusual bleeding.
  • Are allergic to rivaroxaban or any of the ingredients of XARELTO®.

WHAT SHOULD I TELL MY DOCTOR BEFORE OR WHILE TAKING XARELTO®?

Before taking XARELTO®, tell your doctor if you:

  • Have ever had bleeding problems
  • Have liver or kidney problems
  • Have any other medical condition
  • Are pregnant or plan to become pregnant. It is not known if XARELTO® will harm your unborn baby. Tell your doctor right away if you become pregnant while taking XARELTO®. If you take XARELTO® during pregnancy, tell your doctor right away if you have bleeding or symptoms of blood loss.
  • Are breastfeeding or plan to breastfeed. It is not known if XARELTO® passes into your breast milk. You and your doctor should decide if you will take XARELTO® or breastfeed.

Tell all of your doctors and dentists that you are taking XARELTO®. They should talk to the doctor who prescribed XARELTO® for you before you have any surgery, medical or dental procedure.

Tell your doctor about all the medicines you take, including prescription and nonprescription medicines, vitamins, and herbal supplements. Some of your other medicines may affect the way XARELTO® works. Certain medicines may increase your risk of bleeding. See “What is the most important information I should know about XARELTO®?”

Especially tell your doctor if you take:

  • Ketoconazole (Nizoral®)
  • Itraconazole (Onmel™, Sporanox®)
  • Ritonavir (Norvir®)
  • Lopinavir/ritonavir (Kaletra®)
  • Indinavir (Crixivan®)
  • Carbamazepine (Carbatrol®, Equetro®, Tegretol®, Tegretol®-XR, Teril™, Epitol®)
  • Phenytoin (Dilantin-125®, Dilantin®)
  • Phenobarbital (Solfoton™)
  • Rifampin (Rifater®, Rifamate®, Rimactane®, Rifadin®)
  • St. John’s wort (Hypericum perforatum)

Ask your doctor if you are not sure if your medicine is one listed above. Know the medicines you take. Keep a list of them to show your doctor and pharmacist when you get a new medicine.

HOW SHOULD I TAKE XARELTO®?

Take XARELTO® exactly as prescribed by your doctor.

Do not change your dose or stop taking XARELTO® unless your doctor tells you to.

    • Your doctor will tell you how much XARELTO® to take and when to take it.
    • Your doctor may change your dose if needed.

If you take XARELTO® for:

    • Atrial Fibrillation: Take XARELTO® 1 time a day with your evening meal. If you miss a dose of XARELTO®, take it as soon as you remember on the same day. Take your next dose at your regularly scheduled time.
    • Blood clots in the veins of your legs or lungs:
      • Take XARELTO® once or twice a day as prescribed by your doctor.
      • Take XARELTO® with food at the same time each day.
      • If you miss a dose of XARELTO®:
        • and take XARELTO® 2 times a day: Take XARELTO® as soon as you remember on the same day. You may take 2 doses at the same time to make up for the missed dose. Take your next dose at your regularly scheduled time.
        • and take XARELTO® 1 time a day: Take XARELTO® as soon as you remember on the same day. Take your next dose at your regularly scheduled time.
    • Hip or knee replacement surgery: Take XARELTO® 1 time a day with or without food. If you miss a dose of XARELTO®, take it as soon as you remember on the same day. Take your next dose at your regularly scheduled time.
  • If you have difficulty swallowing the tablet whole, talk to your doctor about other ways to take XARELTO®.
  • Your doctor will decide how long you should take XARELTO®. Do not stop taking XARELTO® without talking to your doctor first.
  • Your doctor may stop XARELTO® for a short time before any surgery, medical or dental procedure. Your doctor will tell you when to start taking XARELTO®again after your surgery or procedure.
  • Do not run out of XARELTO®. Refill your prescription for XARELTO® before you run out. When leaving the hospital following a hip or knee replacement, be sure that you have XARELTO® available to avoid missing any doses.
  • If you take too much XARELTO®, go to the nearest hospital emergency room or call your doctor right away.

WHAT ARE THE POSSIBLE SIDE EFFECTS OF XARELTO®?

Please see “What is the most important information I should know about XARELTO®?”

Tell your doctor if you have any side effect that bothers you or that does not go away.

Call your doctor for medical advice about side effects. You are also encouraged to report side effects to the FDA: visit http://www.fda.gov/medwatch or call 1-800-FDA-1088. You may also report side effects to Janssen Pharmaceuticals, Inc., at 1-800-JANSSEN (1-800-526-7736).

Please see full Prescribing Information, including Boxed Warnings, and Medication Guide.

SOURCE

http://www.xarelto-us.com/?utm_source=google&utm_medium=cpc&utm_campaign=Branded+-+2013&utm_term=rivaroxaban&utm_content=Rivaroxaban|mkwid|soKteU2bx_dc|pcrid|29821628975

Figure-1 : Targets for anti-coagulant drugs in the coagulation cascade

Targets for anticoagulant drugs in the coagulation cascade

Pharmacology of Rivaroxaban 

Rivaroxaban, chemically an oxazolidinone derivative, is a directly acting Coagulation factor Xa inhibitor, acting on both free Factor Xa as well as that bound to the Prothrombinase complex.  It has a good oral bioavailability (~ 80-100%) and a rapid onset of action, with peak plasma concentrations being achieved in about 2-4 hours of oral intake.  It is about 95% plasma protein bound, with an aVd of about 50L.  It is partly metabolized in liver and excreted both unchanged as well as inactive metabolites in the urine, so also in the feces.  Strong CYP3A4 inhibitors like Ketoconazole, Ritonavir, Clarithromycin, Conivaptan etc can increase the pharmacodynamic effects of Rivaroxaban by a gross reduction in its metabolism.   Weaker CYP3A4 inhibitors like Amiodarone, Azithromycin, Diltiazem, Dronaderone, Erythromycin, Felodipine, Quinidine, Ranolazine, Verapamil maybe used with Rivaroxaban except in renal impairment.  Similarly, enzyme inducers like Rifampicin can decrease the plasma concentrations of Rivaroxaban.

Indications : Prophylaxis of stroke and systemic embolism in patients of atrial fibrillation, treatment and prevention of Deep Vein Thrombosis (DVT) and Pulmonary Embolism (PE).

Dosage : 10-20 mg with or without food, depending on the indication.

Adverse Effects : As with any other anticoagulant, an increased risk of bleeding. An increased risk of stroke after discontinuation of the drug in atrial fibrillation, and spinal and epidural hematomas.

Therapeutic monitoring : Both Dabigatran and Rivaroxaban do not mandate a therapeutic monitoring clinically, as in the case of Warfarin.  Moreover, both Prothrombin Time (PT) as well as the International Normalized Ratio (INR) are not suitable to measure the pharmacodynamic profile of Rivaroxaban for various reasons1.  Development of novel methods of assays, for instance Anti Factor Xa assay which utilizes rivaroxaban containing plasma calibrators, may provide optimal therapeutic monitoring modalities for Rivaroxaban in the future.

Figure – 2 : PT and aPTT dependent on plasma concentration of anticoagulant drugs.

(A) rivaroxaban (experimental data from internal studies);

(B) DX-9065a (experimental data from the literature, and

(C) ximelagatran (experimental data for PT and aPTT from the literature. aPTT, activated partial thromboplastin time; INR, international normalized ratio; PT, prothrombin time.

PT

Riva

There is some concern regarding a spurious rise in the INR values if a patient stabilized on warfarin is switched over to Rivaroxaban.  This concern is ill-founded since it is already mentioned above that INR is not a suitable  investigation to give an indication of Rivaroxaban pharmacodynamics.   Moreover, no suitable litrerature is available which can explain the rise in INR values on Rivaroxaban administration.  It may require some additional clinical studies to throw some light on this clinical anomaly.

Figure-3 : Annualized Incidence of Complications of Rivaroxaban

complic

REFERENCE

  1. Lindhoff-Last et al. Assays for measuring Rivaroxaban : Their suitability and Limitations. Ther Drug Monitoring Dec 2010 (32, Issue 6): 673-79.

RESOURCES

Burghaus R, Coboeken K, Gaub T, Kuepfer L, et al. (2011) Evaluation of the Efficacy and Safety of Rivaroxaban Using a Computer Model for Blood Coagulation. PLoS ONE 6(4): e17626. doi:10.1371/journal.pone.0017626

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0017626


Coumadin

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Hurst’s The Heart
 > Part 6. Rhythm and Conduction Disorders > Chapter 40. Atrial Fibrillation, Atrial Flutter, and Atrial Tachycardia > Atrial Fibrillation > Treatment > Anticoagulation > Antithrombotic Agents >

Rivaroxaban

Burghaus R, Coboeken K, Gaub T, Kuepfer L, et al. (2011) Evaluation of the Efficacy and Safety of Rivaroxaban Using a Computer Model for Blood Coagulation. PLoS ONE 6(4): e17626. doi:10.1371/journal.pone.0017626

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0017626

Other articles published on this Open Access Online Scientific Journal include the following:

Xarelto (Rivaroxaban): Anticoagulant Therapy gains FDA New Indications and Risk Reduction for: (DVT) and (PE), while in use for Atrial fibrillation increase in Gastrointestinal (GI) Bleeding Reported

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