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Archive for the ‘Cardiovascular Pharmacogenomics’ Category

The Cost to Value Conundrum in Cardiovascular Healthcare Provision

The Cost to Value Conundrum in Cardiovascular Healthcare Provision

Author: Larry H. Bernstein, MD, FCAP

Article ID #98: The Cost to Value Conundrum in Cardiovascular Healthcare Provision. Published on 1/1/2014

WordCloud Image Produced by Adam Tubman

I write this introduction to Volume 2 of the e-series on Cardiovascular Diseases, which curates the basic structure and physiology of the heart, the vasculature, and related structures, e.g., the kidney, with respect to:

1. Pathogenesis
2. Diagnosis
3. Treatment

Curation is an introductory portion to Volume Two, which is necessary to introduce the methodological design used to create the following articles. More needs not to be discussed about the methodology, which will become clear, if only that the content curated is changing based on success or failure of both diagnostic and treatment technology availability, as well as the systems needed to support the ongoing advances.  Curation requires:

  • meaningful selection,
  • enrichment, and
  • sharing combining sources and
  • creation of new synnthesis

Curators have to create a new perspective or idea on top of the existing media which supports the content in the original. The curator has to select from the myriad upon myriad options available, to re-share and critically view the work. A search can be overwhelming in size of the output, but the curator has to successfully pluck the best material straight out of that noise.

Part 1 is a highly important treatment that is not technological, but about the system now outdated to support our healthcare system, the most technolog-ically advanced in the world, with major problems in the availability of care related to economic disparities.  It is not about technology, per se, but about how we allocate healthcare resources, about individuals’ roles in a not full list of lifestyle maintenance options for self-care, and about the important advances emerging out of the Affordable Care Act (ACA), impacting enormously on Medicaid, which depends on state-level acceptance, on community hospital, ambulatory, and home-care or hospice restructuring, which includes the reduction of management overhead by the formation of regional healthcare alliances, the incorporation of physicians into hospital-based practices (with the hospital collecting and distributing the Part B reimbursement to the physician, with “performance-based” targets for privileges and payment – essential to the success of an Accountable Care Organization (AC)).  One problem that ACA has definitively address is the elimination of the exclusion of patients based on preconditions.  One problem that has been left unresolved is the continuing existence of private policies that meet financial capabilities of the contract to provide, but which provide little value to the “purchaser” of care.  This is a holdout that persists in for-profit managed care as an option.  A physician response to the new system of care, largely fostered by a refusal to accept Medicaid, is the formation of direct physician-patient contracted care without an intermediary.

In this respect, the problem is not simple, but is resolvable.  A proposal for improved economic stability has been prepared by Edward Ingram. A concern for American families and businesses is substantially addressed in a macroeconomic design concept, so that financial services like housing, government, and business finance, savings and pensions, boosting confidence at every level giving everyone a better chance of success in planning their personal savings and lifetime and business finances.

http://macro-economic-design.blogspot.com/p/book.html

Part 2 is a collection of scientific articles on the current advances in cardiac care by the best trained physicians the world has known, with mastery of the most advanced vascular instrumentation for medical or surgical interventions, the latest diagnostic ultrasound and imaging tools that are becoming outdated before the useful lifetime of the capital investment has been completed.  If we tie together Part 1 and Part 2, there is ample room for considering  clinical outcomes based on individual and organizational factors for best performance. This can really only be realized with considerable improvement in information infrastructure, which has miles to go.  Why should this be?  Because for generations of IT support systems, they are historically focused on billing and have made insignificant inroads into the front-end needs of the clinical staff.

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Platelet Endothelial Aggregation Receptor-1 (PEAR1) Gene to be most strongly associated with Dual Antiplatelet Therapy Response: Genetic Determinants of Variable Response to Aspirin (alone and in combination with Clopidogrel)

Reporter: Aviva Lev-Ari, PhD, RN

4 Genetic Variation in PEAR1 is Associated with Platelet Aggregation and Cardiovascular Outcomes

Joshua P. Lewis1, Kathleen Ryan1, Jeffrey R. O’Connell1, Richard B. Horenstein1,Coleen M. Damcott1, Quince Gibson1, Toni I. Pollin1, Braxton D. Mitchell1, Amber L. Beitelshees1, Ruth Pakzy1, Keith Tanner1, Afshin Parsa1, Udaya S. Tantry2, Kevin P. Bliden2, Wendy S. Post3, Nauder Faraday3, William Herzog4, Yan Gong5, Carl J. Pepine6, Julie A. Johnson5, Paul A. Gurbel2 and Alan R. Shuldiner7*

Author Affiliations

1University of Maryland School of Medicine, Baltimore, MD

2Sinai Hospital of Baltimore, Baltimore, MD

3Johns Hopkins University School of Medicine, Baltimore, MD

4Sinai Hospital of Baltimore & Johns Hopkins University School of Medicine, Baltimore, MD

5University of Florida College of Pharmacy, Gainesville, FL

6University of Florida College of Medicine, Gainesville, FL

7University of Maryland School of Medicine & Veterans Administration Medical Center, Baltimore, MD

↵* University of Maryland School of Medicine & Veterans Administration Medical Center, Baltimore, MD ashuldin@medicine.umaryland.edu

Abstract

Background-Aspirin or dual antiplatelet therapy (DAPT) with aspirin and clopidogrel is standard therapy for patients at increased risk for cardiovascular events. However, the genetic determinants of variable response to aspirin (alone and in combination with clopidogrel) are not known.

Methods and Results-We measured ex-vivo platelet aggregation before and after DAPT in individuals (n=565) from the Pharmacogenomics of Antiplatelet Intervention (PAPI) Study and conducted a genome-wide association study (GWAS) of drug response. Significant findings were extended by examining genotype and cardiovascular outcomes in two independent aspirin-treated cohorts: 227 percutaneous coronary intervention (PCI) patients, and 1,000 patients of the International VErapamil SR/trandolapril Study (INVEST) GENEtic Substudy (INVEST-GENES). GWAS revealed a strong association between single nucleotide polymorphisms on chromosome 1q23 and post-DAPT platelet aggregation. Further genotyping revealed rs12041331 in the platelet endothelial aggregation receptor-1 (PEAR1) gene to be most strongly associated with DAPT response (P=7.66×10-9). In Caucasian and African American patients undergoing PCI, A-allele carriers of rs12041331 were more likely to experience a cardiovascular event or death compared to GG homozygotes (hazard ratio = 2.62, 95%CI 0.96-7.10, P=0.059 and hazard ratio = 3.97, 95%CI 1.10-14.31, P=0.035 respectively). In aspirin-treated INVEST-GENES patients, rs12041331 A-allele carriers had significantly increased risk of myocardial infarction compared to GG homozygotes (OR=2.03, 95%CI 1.01-4.09, P=0.048).

Conclusions – Common genetic variation in PEAR1 may be a determinant of platelet response and cardiovascular events in patients on aspirin, alone and in combination with clopidogrel.

Clinical Trial Registration Information-clinicaltrials.gov; Identifiers:NCT00799396 and NCT00370045

SOURCE:

http://www.ncbi.nlm.nih.gov/pubmed/23392654

http://circgenetics.ahajournals.org/content/6/2/184.short?rss=1

Circulation: Cardiovascular Genetics.2013; 6: 184-192 Published online before print February 7, 2013,doi: 10.1161/​CIRCGENETICS.111.964627

 

 

 

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Atherosclerosis Independence: Genetic Polymorphisms of Ion Channels Role in the Pathogenesis of Coronary Microvascular Dysfunction and Myocardial Ischemia (Coronary Artery Disease (CAD))

Reviewer and Co-Curator: Larry H Bernstein, MD, FCAP

and

Curator: Aviva Lev-Ari, PhD, RN

Article XII Atherosclerosis Independence Genetic Polymorphisms of Ion Channels Role in the Pathogenesis of Coronary Microvascular Dysfunction and Myocardial Ischemia (Coronary Artery

Image created by Adina Hazan 06/30/2021

The role of ion channels in Na(+)-K(+)-ATPase: regulation of ion
transport across the plasma membrane has been studied by our Team in 2012 and 2013. This is article TWELVE in a 13 article series listed at the end of this article.

Chiefly, our sources of inspiration were the following:

1.            2013 Nobel work on vesicles and calcium flux at the neuromuscular junction

Machinery Regulating Vesicle Traffic, A Major Transport System in our Cells 

The 2013 Nobel Prize in Physiology or Medicine is awarded to Dr. James E. Rothman, Dr. Randy W. Schekman and Dr. Thomas C. Südhof for their discoveries of machinery regulating vesicle traffic, a major transport system in our cells. This represents a paradigm shift in our understanding of how the eukaryotic cell, with its complex internal compartmentalization, organizes the routing of molecules packaged in vesicles to various intracellular destinations, as well as to the outside of the cell. Specificity in the delivery of molecular cargo is essential for cell function and survival. 

http://www.nobelprize.org/nobel_prizes/medicine/laureates/2013/advanced-medicineprize2013.pdf

Synaptotagmin functions as a Calcium Sensor: How Calcium Ions Regulate the fusion of vesicles with cell membranes during Neurotransmission

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

http://pharmaceuticalintelligence.com/2013/09/10/synaptotagmin-functions-as-a-calcium-sensor-how-calcium-ions-regulate-the-fusion-of-vesicles-with-cell-membranes-during-neurotransmission/

2. Perspectives on Nitric Oxide in Disease Mechanisms

available on Kindle Store @ Amazon.com

http://www.amazon.com/dp/B00DINFFYC

http://pharmaceuticalintelligence.com/biomed-e-books/series-a-e-books-on-cardiovascular-diseases/perspectives-on-nitric-oxide-in-disease-mechanisms-v2/

3.            Professor David Lichtstein, Hebrew University of Jerusalem, Dean, School of Medicine

Lichtstein’s main research focus is the regulation of ion transport across the plasma membrane of eukaryotic cells. His work led to the discovery that specific steroids that have crucial roles, as the regulation of cell viability, heart contractility, blood pressure and brain function. His research has implications for the fundamental understanding of body functions, as well as for several pathological states such as heart failure, hypertension and neurological and psychiatric diseases.

Physiologist, Professor Lichtstein, Chair in Heart Studies at The Hebrew University elected Dean of the Faculty of Medicine at The Hebrew University of Jerusalem

Reporter: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/12/18/physiologist-professor-lichtstein-chair-in-heart-studies-at-the-hebrew-university-elected-dean-of-the-faculty-of-medicine-at-the-hebrew-university-of-jerusalem/

4.            Professor Roger J. Hajjar, MD at Mount Sinai School of Medicine

Calcium Cycling (ATPase Pump) in Cardiac Gene Therapy: Inhalable Gene Therapy for Pulmonary Arterial Hypertension and Percutaneous Intra-coronary Artery Infusion for Heart Failure: Contributions by Roger J. Hajjar, MD

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/08/01/calcium-molecule-in-cardiac-gene-therapy-inhalable-gene-therapy-for-pulmonary-arterial-hypertension-and-percutaneous-intra-coronary-artery-infusion-for-heart-failure-contributions-by-roger-j-hajjar/

5.            Seminal Curations by Dr. Aviva Lev-Ari on Genetics and Genomics of Cardiovascular Diseases with a focus on Conduction and Cardiac Contractility

Aviva Lev-Ari, PhD, RN

Aviva Lev-Ari, PhD, RN

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

Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

Other related research by the Team of Leaders in Pharmaceutical Business Intelligence published on the Open Access Online Scientific Journal

http://pharmaceuticalintelligence.com

See References to articles at the end of this article on

  • ION CHANNEL and Cardiovascular Diseases

http://pharmaceuticalintelligence.com/?s=Ion+Channel

  • Calcium Role in Cardiovascular Diseases – The Role of Calcium Calmodulin Kinase  (CKCaII) and Ca(2) flux
  • Mitochondria and Oxidative Stress Role in Cardiovascular Diseases

Thus, the following article follows a series of articles on ion-channels and cardiac contractility mentioned, above. The following article is closely related to the work of Prof. Lichtstein.

These investigators studied the possible correlation between

  • Myocardial Ischemia (Coronary Artery Disease (CAD)) aka Ischemic Heart Disease (IHD) and
  • single-nucleotide polymorphisms  (SNPs) genes encoding several regulators involved in Coronary Blood Flow Regulation (CBFR), including
  • ion channels acting in vascular smooth muscle and/or
  • endothelial cells of coronary arteries.

They completely analyzed exon 3 of both KCNJ8 and KCNJ11 genes (Kir6.1 and Kir6.2 subunit, respectively) as well as

  • the whole coding region of KCN5A gene (Kv1.5 channel).
The work suggests certain genetic polymorphisms may represent a non-modifiable protective factor that could be used
  • to identify individuals at relatively low-risk for cardiovascular disease
  • an independent protective role of the
    • rs5215_GG against developing CAD and
    • a trend for rs5219_AA to be associated with protection against coronary microvascular dysfunction

Their findings are a lead into further investigations on ion channels and IHD affecting the microvasculature.

Role of genetic polymorphisms of ion channels in the pathophysiology of coronary microvascular dysfunction and ischemic heart disease

BasicResCardiol(2013)108:387   http//dx.dio.org/10.1007/s00395-013-0387-4

F Fedele1•M Mancone1•WM Chilian2•P Severino2•E Canali•S Logan•ML DeMarchis3•M Volterrani4•R Palmirotta3•F Guadagni3

1Department of Cardiovascular, Respiratory, Nephrology, Anesthesiology and Geriatric Sciences,Sapienza University of Rome, UmbertoI Policlinic, Rome, Italy  e-mail:francesco.fedele@uniroma1.it
2Department of Integrative Medical Sciences, Northeastern Ohio Universities College of Medicine, Rootstown,OH
3Department of Advanced Biotechnologies and Bioimaging, IRCCS San Raffaele Pisana,Rome,It
4Cardiovascular Research Unit, Department of Medical Sciences, Centre for Clinical and Basic Research, Raffaele Pisana, Rome, Italy (CBFR)

BasicResCardiol(2013)108:387   http//dx.dio.org/10.1007/s00395-013-0387-4
This article is published with open access at Springerlink.com

Abstract

Conventionally,ischemic heart disease (IHD) study is equated with large vessel coronary disease (CAD). However, recent evidence has suggested

  • a role of compromised microvascular regulation in the etiology of IHD.

Because regulation of coronary blood flow likely involves

  • activity of specific ion-channels, and
  • key factors involved in endothelium-dependent dilation,

genetic anomalies of ion-channels or specific endothelial-regulators may underlie coronary microvascular disease.

We aimed to evaluate the clinical impact of single-nucleotide polymorphisms in genes encoding for

  • ion-channels expressed in the coronary vasculature and the possible
  • correlation with IHD resulting from microvascular dysfunction.

242 consecutive patients who were candidates for coronary angiography were enrolled. A prospective, observational, single-center study was conducted, 

  • analyzing genetic polymorphisms relative to

(1) NOS3 encoding for endothelial nitric oxide synthase (eNOS);
(2) ATP2A2 encoding for the Ca/H-ATP-ase pump (SERCA);
(3) SCN5A encoding for the voltage-dependent Na channel (Nav1.5);
(4) KCNJ8 and in KCNJ11 encoding for the Kir6.1and Kir6.2 subunits
of genetic K-ATP channels, respectively;and
(5) KCN5A encoding for the voltage-gated K channel (Kv1.5).

No significant associations between clinical IHD manifestations and

  • polymorphisms for SERCA, Kir6.1, and Kv1.5. were observed (p[0.05),

whereas specific polymorphisms detected in eNOS, as well as in Kir6.2 and Nav1.5 were found to be correlated with

  • IHD and microvascular dysfunction.

 Interestingly, genetic polymorphisms of ion-channels  seem to have an important clinical impact

  • influencing the susceptibility for microvascular dysfunction and (IHD,
  • independent of the presence of classic cardiovascular risk factors: atherosclerosis   

http//dx.dio.org/10.1007/s00395-013-0387-4

Keywords: Ion-channels, Genetic polymorphisms, Coronary microcirculation, Endothelium, Atherosclerosis Ischemic heart disease

 Introduction

Historically, in the interrogation of altered vascular function in patientswith ischemic heart disease (IHD), scientists have focused their attention on the correlation between

  • endothelial dysfunction and
  • atherosclerosis [11, 53, 65, 67].

The endothelium-independent dysfunction in coronary microcirculation and its possible correlations with  

  • atherosclerotic disease and
  • myocardial ischemia has not been extensively investigated.

In normal conditions, coronary blood flow regulation (CBFR) is mediated by several different systems, including

  • endothelial,
  • nervous,
  • neurohumoral,
  • myogenic, and
  • metabolic mechanisms [2, 10, 14, 15, 63, 64, 69].

Physiologic CBFR depends also on several ion channels, such as

  • ATP-sensitive potassium (KATP) channels,
  • voltage-gated potassium (Kv) channels,
  • voltage-gated sodium (Nav) channels, and others.

Ion channels regulate the concentration of calcium in both

  • coronary smooth muscle and endothelial cells, which
  • modulates the degree of contractile tone in vascular muscle and
  • the amount of nitric oxide that is produced by the endothelium

Ion channels play a primary role in the rapid response of both

  • the endothelium and vascular smooth muscle cells of coronary arterioles
  • to the perpetually fluctuating demands of the myocardium for blood flow
    [5, 6, 13, 18, 33, 45, 46, 51, 52, 61, 73, 75].

Despite this knowledge, there still exists an important gap about 

  • the clinical relevance and 
  • causes of microvascular dysfunction in IHD. 

By altering the overall

  • regulation of blood flow in the coronary system,
  • microvascular dysfunction could alter the normal distribution of shear forces in large coronary arteries

Proximal coronary artery stenosis could

  • contribute to microvascular dysfunction [29, 60]. But
  • ion channels play a critical role in microvascular endothelial
  • and smooth muscle function.

Therefore, we hypothesized  that alterations of coronary ion  channels could be the primary cause in a chain of events leading to

  • microvascular dysfunction and 
  • myocardial ischemia, 

independent of the presence of atherosclerosis.

Therefore, the objective of our study was to evaluate the possible correlation between

  • IHD and single-nucleotide polymorphisms  (SNPs) for genes encoding several regulators involved in CBFR, including
  • ion channels acting in vascular smooth muscle and/or
  • endothelial cells of coronary arteries.

Discussion

Implications of the present work. This study describes the possible correlation of polymorphisms in genes encoding for CBFR effectors (i.e., ion channels, nitric oxide synthase, and SERCA) with the susceptibility for microcirculation dysfunction and IHD.

Our main findings are as follows: (Group 3 – Normal Patients – anatomically and functionally normal coronary arteries).

  • In Group 3, the genotype distribution of SNP rs5215 (Kir6.2/KCNJ11) moderately deviates from the HW equilibrium (p = 0.05).
  • In Group 1 (CAD), the polymorphism rs6599230 of Nav1.5/SCN5A showed deviation from HW equilibrium (p = 0.017).
  • The genotypic distribution of rs1799983 polymorphism for eNOS/NOS3 is inconsistent with the HW equilibrium in groups 1, 2, and 3 (p = 0.0001, p = 0.0012 and p = 0.0001, respectively).

Haplotype analyses revealed that there is no linkage disequilibrium between polymorphisms of the analyzed genes. There was no significant difference in the prevalence of T2DM (p = 0.185) or dyslipidemia (p = 0.271) between groups, as shown in Table2. In regards to genetic characteristics, no significant differences between the three.

1. A marked HW disequilibrium in the genotypic distribution of rs1799983 polymorphism for eNOS/NOS3 was observed in all three populations. Moreover, this SNP seems to be an independent risk factor for microvascular dysfunction, as evidenced by multivariate analysis;
2. The SNPs rs5215_GG, rs5218_CT, and rs5219_AA for Kir6.2/KCJ11 could reduce susceptibility to IHD, since they were present more frequently in patients with anatomically and functionally normal coronary arteries;
3. In particular, with regard to rs5215 for Kir6.2/KCJ11, we observed a moderate deviation from the HW equilibrium in the genotypic
distribution in the control group. In addition, this genotype appears to be an independent protective factor in the development of IHD, as evidenced by multivariate analysis;
4. Furthermore, the trend observed for the SNP  rs5219_AA of Kir6.2/KCNJ11 may suggest an independent protective factor  in the development of coronary microvascular dysfunction
5. The rs1805124_GG genotype of Nav1.5/SCN5A seems to play a role against CAD;
6. No association seems to exist between the polymorphisms of SERCA/ATP2A2, Kir6.1/KCNJ8, and Kv1.5/KCNA5 and the presence of IHD;
7. All groups are comparable regarding the cardiovascular risk factors of T2DM and dyslipidemia, illustrating a potentially important implication of genetic polymorphisms in the susceptibility to IHD.

It is important to underline that the control group (Group 3) is a high-risk population, because of their cardiovascular risk factors

  • hypertension = 17 %,
  • T2DM = 34.1 %,
  • dyslipidemia = 41.4 %,

with an appropriate indication for coronary angiography, in accordance with current guidelines. Nevertheless, these patients were demonstrated to have both anatomically and functionally normal coronary arteries. Moreover, as shown in Tables 2 and 3, we observed that

  • rs5215_GG, rs5218_CT and rs5219_AA for Kir6.2/KCNJ11 had a higher prevalence in this group,compared to patients with CAD
  • and patients with microvascular dysfunction.

Moreover, as shown in Table 4, the presence of the rs5215_GG polymorphism for the Kir6.2 subunit was

  • inversely correlated with the prevalence of cardiovascular risk factors and CAD,whereas
  • rs5219_AA of the Kir6.2 subunit trended towards an inverse correlation with coronary microvascular dysfunction.

On the other hand, the SNP rs1799983_GT of eNOS was

  • confirmed to be an independent risk factor for microvascular dysfunction.

Our data suggest that the presence of certain genetic polymorphisms may represent a non-modifiable protective factor that could be used

  • to identify individuals at relatively low-risk for cardiovascular disease,
  • regardless of the presence of T2DM and dyslipidemia.

Current Clinical and Research Context

In normal coronary arteries, particularly the coronary microcirculation, there are several different mechanisms of CBFR, including

  • endothelial, neural, myogenic, and metabolic mediators [2, 8, 10, 12, 14, 15, 37, 55, 63, 64, 69].

In particular, endothelium-dependent vasodilation acts mainly via eNOS-derived nitric oxide (NO) in response to acetylcholine and shear stress.

  • NO increases intracellular cyclic guanosine monophosphate. It also causes vasodilation via
  • activation of both K-Ca channels and K-ATP channels.

Recent data suggested a pathophysiologically relevant role for the polymorphisms of eNOS/NOS3 in human coronary vasomotion [40–43]. Our data suggest that rs1799983_GT at exon 7 (Glu298Asp, GAG-GAT) of eNOS/NOS3 represents

  • an independent risk factor for coronary micro-vascular dysfunction, which agrees with a recent meta-analysis reporting an
  • association of this SNP with CAD in Asian populations [74]. In addition,
  • this SNP has been associated with endothelial dysfunction, although the mechanisms are not well defined [30].

Consistently, a recent study performed on 60 Indian patients with documented history of CAD reported a significantly higher frequency of rs1799983 (p.05) compared to control subjects, indicating that

  • variations in NOS3 gene may be useful clinical markers of endothelial dysfunction in CAD [54].
Interestingly, another association between rs1799983_GT and impaired collateral development has been observed in patientswith a

  • high-grade coronary stenosis or occlusion [19].
As is well known, the significance of the mechanisms of CBFR is partly determined by the location within the coronary vasculature. For instance, for vessels with a diameter of < 200 µm—which comprise the coronary microcirculation—metabolic regulation of coronary blood flow is considered the most important mechanism [24, 63]. Importantly, many of these mediators of metabolic regulation act through specific ion channels. In particular, in both coronary artery smooth muscle cells and endothelial cells
  • potassium channels determine the resting membrane potential (Em) and serve as targets of endogenous and therapeutic vasodilators [9, 27].
Several types of K+ channels are expressed in the coronary tree.
  • The K-ATP channels couple cell metabolic demand to conductance, via pore-forming (Kir6.1 and/or Kir6.2) subunits and regulatory
    [sulphonylurea-binding (SUR 1, 2A, or 2B)] subunits.
  • Kir6.x allows for channel inhibition by ATP, while SURx is responsible for channel activation by ADP and Mg2+.
K-ATP channel activation results in an outward flux of potassium and

  • consequent hyperpolarization, resulting in
  • voltage-gated calcium channel closure,
  • decreased Ca2+ influx, and ultimately
  • vasodilation [1, 5, 18, 20, 21, 33, 61, 62, 73, 75].

Our data do not support any significant difference regarding the Kir6.1 subunit of the K-ATP channel. On the other hand, this study suggests

  • an important role of specific SNPs for the Kir6.2 subunit (Tables 2, 3)—i.e., rs5215, rs5219, and rs5218—

in the susceptibility to IHD and microvascular dysfunction. These SNPs are among the most studied K-ATP channel polymorphisms, especially in the context of diabetes mellitus. In fact, in both Caucasian and Asian populations, these three SNPs as well as other genetic polymorphisms for the KCNJ11 gene have been associated with diabetes mellitus [34, 35, 44, 50, 57, 58, 70].

Nevertheless, the precise

  • structure–function impacts of the various amino acid substitutions remain unclear.

The rs5215 and rs5219 polymorphisms, also known as I337V and E23K, respectively, are highly linked with reported

  • concordance rates between 72 and 100 % [22, 23, 56].

The high concordance between rs5219 and rs5215 suggests that these polymorphisms

  • may have originated in a common ancestor, further indicating a
  • possible evolutionary advantage to their maintenance in the general population [49].

In our study, multivariate analysis suggests both an independent protective role of the

  • rs5215_GG against developing CAD and
  • a trend for rs5219_AA to be associated with protection against coronary microvascular dysfunction (Table 4a, b).
  • The variant rs5215_GG is a missense SNP located in the gene KCNJ11 at exon 1009 (ATC-GTC) and results in
    the substitution of isoleucine (I) residue with valine (V) [23].

Future studies are necessary to better understand the influence of this single amino acid variant on the function of the channel.

In humans, vasodilation of the coronary microvasculature in response to hypoxia and K-ATP channel opening
  • are both impaired in diabetes mellitus [39].
It is also described that gain-of-function mutations of the KCNJ11 gene cause neonatal diabetes mellitus, and loss-of-function mutations lead to congenital hyperinsulinism [43]. Our study is not discordant with previous studies about the correlation of SNPs of the Kir6.2 subunit and diabetes mellitus. Rather, our findings show that these SNPs are correlated with anatomically and functionally normal coronary arteries,
  • independent of the presence of either diabetes mellitus or dyslipidemia.
These data suggest the possibility that these particular SNPs may identify individuals with decreased risk for coronary microcirculatory dysfunction and IHD,
  • regardless of the presence of T2DM and/or dyslipidemia.

However, further studies are necessary to confirm these findings. In this context, to better investigate the implications of genetic variation in the K-ATP channel,

  • future studies should include ion channel’s functional modification due to the SNPs and analysis of SUR subunits.

More than 40-kV channel subunits have been identified in the heart, and sections of human coronary smooth muscle cells demonstrate Kv1.5 immunoreactivity [16, 17, 27, 38]. Through constant regulation of smooth muscle tone, Kv channels contribute to the control of coronary microvascular resistance [4, 7]. Pharmacologic molecules that inhibit Kv1.5 channels such as

  • pergolide [25],
  • 4-amino-pyridine [32], and
  • correolide [17]

lead to coronary smooth muscle cell contraction and block the coupling between

  • cardiac metabolic demand and
  • coronary blood flow.

However, no significant differences were identified between the study groups in terms of the particular polymorphisms for Kv1.5 that were analyzed in this study. Expression of

  • the voltage-dependent Na+ channel (Nav) has been demonstrated in coronary microvascular endothelia cells [3, 66].

Our analysis reveals a possible implication of the polymorphism rs1805124_GG for Nav1.5 channel with the presence of anatomically and functionally normal coronary arteries. This SNP leads to a homozygous 1673A-G transition, resulting in a His558-to-Arg (H558R) substitution. It is important to underline that

  • our data are the first to correlate the polymorphism rs1805124_GG with IHD.

Further research is necessary to confirm the observed implication.

Finally, we have analyzed the sarco/endoplasmic reticulum calcium transporting Ca2+-ATPase (SERCA), which is fundamental in the regulation of intracellular Ca2+ concentration [6].

SERCA is an intracellular pump that

  • catalyzes the hydrolysis of ATP coupled with the
  • translocation of calcium from the cytosol into the lumen of the sarcoplasmic reticulum.

Although this pump plays a critical role in regulation of the contraction/relaxation cycle, our analysis did not reveal any apparent association between

  • genetic variants of SERCA and the
  • prevalence of microvascular dysfunction or IHD.

Conclusions

This pilot study is the first to compare the prevalence of SNPs in genes encoding coronary ion channels between patients
  • with CAD or microvascular dysfunction and those with both anatomically and functionally normal coronary arteries.
Taken together, these results suggest the possibility of associations between SNPs and IHD and microvascular dysfunction, although

  • the precise manners by which specific genetic polymorphisms affect ion channel function and expression
have to be clarified by further research involving larger cohorts.

Limitations and future perspectives

Notable limitations of this pilot study are as follows:

1. Due to the lack of pre-existing data, the power calculation was performed in advance on the basis of assumptions of allele frequencies and the population at risk.
2. The sample size for each group is small, mainly due to both the difficulty in enrolling patients with normal coronary arteries and normal microvascular function (group 3) and the elevated costs of the supplies such as Doppler flow wires.
3. There is a lack of ethnic diversity of our cohort.
4. Currently, there is an absence of supportive findings in another independent cohort or population. However, our pilot study included patients within a well-defined, specific population and was aimed to identify the presence of statistical associations between selected genetic polymorphisms and the prevalence of a specific disease.
5. There is a lack of functional characterization of the described genetic polymorphisms.
6. We have not identified any correlation between novel SNPs and IHD. Nevertheless, we completely analyzed exon 3 of both KCNJ8 and KCNJ11 genes (Kir6.1 and Kir6.2 subunit, respectively) as well as the whole coding region of KCN5A gene (Kv1.5 channel).  Moreover, we examined previously described SNPs since there are no data in the literature regarding the possible association of the prevalences of those polymorphisms in the examined population.More extensive studies are necessary to confirm our  findings, possibly with a larger number of patients. Future investigations are also required to confirm the roles of ion  channels in the pathogenesis of coronary microvascular dysfunction and IHD. These studies should involve analysis of both other subunits of the K-ATP channels

  • sulfonylurea receptor, SURx and further coronary ion channels (e.g., calcium-dependent K channels), as well as
  • in vitro evaluation of ion channel activity by patch clamp and analysis of channel expression in the human cardiac tissue.

Moreover, to better address the significance of microvascular dysfunction in IHD, it could be interesting to analyze

  • typical atherosclerosis susceptibility genes (e.g., PPAP2B, ICAM1, et al.).

Methods

In this prospective, observational, single-center study – 242 consecutive patients admitted to our department were enrolled with

  • the indication to undergo coronary angiography .

All patients matched inclusion criteria

  1. age [18];
  2. suspected or documented diagnosis of acute coronary syndrome or stable angina
  3. with indication(s) for coronary angiography, in accordance with current guidelines [36, 68], and
  4. the same ethno-geographic Caucasian origin) and

Exclusion Criteria

  1. previous allergic reaction to iodine contrast,
  2. renal failure,
  3. simultaneous genetic disease,
  4. cardiogenic shock,
  5. non- ischemic cardiomyopathy

All patients signed an informed consent document  –

prior to participation in the study, which included

  • acknowledgement of the testing procedures to be performed
    (i.e., coronary angiography; intracoronary tests; genetic analysis, and processing of personal data).

The study was approved by the Institution’s Ethics Committee.
All clinical and instrumental characteristics were collected in a dedicated  database.

 Study Design

(a)  Standard therapies were administered, according to current guidelines [36, 68].
(b) An echocardiography was performed before and after coronary angiography
(c)  Coronary angiography was performed using radial artery or femoral artery
Judkins approach via sheath insertion.
(d) In patients showing normal epicardial arteries, intracoronary functional tests
were performed through Doppler flow wire to evaluate

  1. both endothelium-dependent microvascular function
    [via intracoronary (IC) infusion of acetylcholine (2.5–10 lg)] and
  2. nonendothelium-dependent microvascular function
    [via IC infusion of adenosine (5 lg)] [31]. 

(e) In all enrolled patients, a peripheral blood sample for genetic analysis was taken. 

On the basis  of the  coronary angiography and the intracoronary functional tests, 

  • the 242 patients were divided into three groups (see also Fig. 1).
  1. Group 1: 155 patients with anatomic coronary alteration
    (comprising patients with acute coronary syndrome and chronic stable angina).

    • microvascular dysfunction defined as coronary flow reserve (CFR) \ 2.5
    • after IC infusion of acetylcholine and adenosine].
  2. Group 2: 46 patients with functional coronary alteration
    [normal coronary arteries as assessed by angiography, and

    • as assessed by angiography and with normal functional tests
      (CFR C 2.5 after intracoronary infusion of acetylcholine and adenosine) (Fig. 1).
  3. Group 3: 41 patients with anatomically and functionally normal coronary arteries

 

BRC 2013 fedele genetic polymorphisms of ion channels.pdf_page_2

Fig. 1 Study design: 242 consecutive not randomized patients matching inclusion and exclusion criteria were enrolled.
In all patients, coronary angiography was performed, according to current ESC/ACC/AHA guidelines. In patients with
angiographically normal coronary artery, intracoronary functional tests were performed. In 242 patients
(155 with coronary artery disease, 46 patients with micro-vascular dysfunction, endothelium and/or non-endothelium
dependent, and 41 patients with anatomically and functionally normal coronary arteries) genetic analysis was performed.

Genetic Analysis

In conformity with the study protocol, ethylenediaminetetraacetic acid (EDTA) whole blood samples were collected according
to the international guidelines reported in the literature [48]. Samples were transferred to the Interinstitutional Multidisciplinary
BioBank (BioBIM) of IRCCS San Raffaele Pisana (Rome) and stored at -80 C until DNA extraction. Bibliographic research by
PubMed and web tools OMIM (http://www.ncbi.nlm.nih.gov/omim), Entrez SNP (http://www.ncbi.nlm.nih.gov/snp), and
Ensembl (http://www.ensembl.org/index.html) were used to select variants of genes involved in signaling pathways

  • related to ion channels and/or reported to be associated with
  • microvascular dysfunction and/or myocardial ischemia and/or
  • diseases correlated to IHD, such as diabetes mellitus.
Polymorphisms for the following genes were analyzed:
  1. NOS3 (endothelial nitric oxide synthase, eNOS),
  2. ATP2A2 (Ca2+/H+-ATPase pump, SERCA2),
  3. SCN5A (voltage-dependent Na+ channel,
  4. Nav1.5),
  5. KCNJ11 (ATP-sensitive K+ channel, Kir6.2 subunit),
  6. KCNJ8 (ATP-sensitive K+ channel, Kir6.1 subunit) and
  7. KCNA5 (voltage-gated K+ channel, Kv1.5).

In particular, we completely analyzed by direct sequencing

  • exon 3 of KCNJ8 (Kir6.1 subunit), which includes eight SNPs, as well as
  • the whole coding region of KCNA5 (Kv1.5 channel), which includes 32 SNPs and
  • four previously described variants [26, 47, 71, 72].
We also examined
  • the whole coding region of KCNJ11 (Kir6.2 subunit), for which sequence variants are described [26, 28].

All SNPs and sequence variants analyzed—a total of 62 variants of 6 genes—are listed in Table 1.

BRC 2013 fedele genetic polymorphisms of ion channels_page_004
BRC 2013 fedele genetic polymorphisms of ion channels_page_005

DNA was isolated from EDTA anticoagulated whole blood using the MagNA Pure LC instrument and theMagNA Pure LC
total DNA isolation kit I (Roche Diagnostics, Mannheim, Germany) according to the manufacturer’s instructions. Standard
PCR was performed in a GeneAmp PCR System 9700 (Applied Biosystems, CA) using HotStarTaq Master Mix
(HotStarTaq Master Mix Kit, QIAGEN Inc, CA). PCR conditions and primer sequences are listed in Table 1.

In order to exclude preanalytical and analytical errors, all direct sequencing analyses were carried out on both
strands using Big Dye Terminator v3.1 Cycle Sequencing kit
(Applied Biosystems), run on an ABI 3130
Genetic Analyzer (Applied Biosystems), and repeated on PCR products obtained from new nucleic acid extractions.
All data analyses were performed in a blind fashion.

Statistical Analysis

This report, intended as pilot study, is the first to compare

  • the prevalence of SNPs in genes encoding  several effectors (including ion channels)
  • involved in CBFR between these groups of patients.

No definite sample size could be calculated to establish a power analysis. groups of patients. However, assuming

  • a 15 % prevalence of normal  macrovascular and microvascular coronary findings in unselected patients
    undergoing coronary angiography,

we estimated that

  • a sample size of at least 150 patients could enable the computation of two-sided 95 % confidence intervals for
    • such prevalence estimates ranging between -5.0 and + 5.0 %.

The significance of the differences of observed alleles and genotypes between groups, as well as

  • analysis of multiple inheritance models for SNPs were also tested
    (co-dominant, dominant, recessive, over-dominant and log-additive)
  • using a free web-based application (http://213. 151.99.166/index.php?module=Snpstats)
  • designed from a genetic epidemiology  point of view to analyze association studies.

Akaike Information Criterion (AIC) was used to determine the best-fitting inheritance model for analyzed SNPs,

  • with the model with the lowest AIC reflecting the best balance of  goodness-of-fit and parsimony.

Moreover,  the allelic frequencies were estimated by gene counting, and the genotypes were scored. For each gene,

  • the observed numbers of each genotype were compared with those expected for a population in Hardy–Weinberg (HW) equilibrium
  • using a free web-based application  (http://213.151.99.166/index.php?module=Snpstats) [59].

Linkage disequilibrium coefficient (D0) and  haplotype analyses were assessed using  the  Haploview 4.1 program.
Statistical analysis was performed using SPSS software package for Windows v.16.0 (SPSS Inc., Chicago, IL).

All categorical variables are expressed as percentages, and all continuous variables as mean ± standard deviation.
Differences between categorical variables

  • were analyzed by Pearson’s Chi-SQ test.

Given the presence of three groups, differences  between continuous variables, were calculated using
(including the number of SNPs tested),

  • one-way ANOVA; a post-hoc analysis with Bonferroni correction was made for multiple comparisons.

Univariate and multivariate logistic regression analyses

  • the independent impact of genetic polymorphisms on
    • coronary artery disease and microvascular dysfunction,

were performed to assess the independent impact of

  • genetic polymorphisms on coronary artery disease
    and microvascular dysfunction
    ,

while adjusting for other confounding variables.  The following parameters were entered into the model:

  • age,
  • male gender,
  • type 2 diabetes mellitus (T2DM),
  • systemic arterial hypertension,
  • dyslipidemia,
  • smoking status, and
  • family history of myocardial infarction (MI).

Only variables with a p value < 0.10 after univariate analysis were entered

  • into the multivariable model as covariates.

A two-tailed p < 0.05 was considered statistically significant.

Definition of Cardiovascular Risk Factors

Patients were classified as having T2DM if they had

  • fasting levels of glucose of >126 mg/dL in two separate measurements or
  • if they were taking hypoglycemic drugs.

Systemic arterial hypertension was defined as

  • systolic blood pressure  > 140 mmHg / diastolic blood pressure > 90 mmHg
  • in two separate measurements or
  • if the patient was currently taking antihypertensive drugs.

Dyslipidemia was considered to be present if

  • serum cholesterol levels were>220 mg/dL or
  • if the patient was being treated with cholesterol-lowering drugs.

Family history of MI was defined as a first-degree relative with MI before the age of 60 years.

Results

Sixty-two polymorphisms distributed among six genes coding for
  • nitric oxide synthase,
  • the SERCA pump, and
  • ion channels
    • were screened for sequence variations using PCR amplification and
    • direct DNA sequencing analysis

in the population of

  • 155 patients with CAD (group 1),
  • 46 patients with microvascular dysfunction (group 2), and
  • 41 patients with normal coronary arteries and
    • normal endothelium dependent and endothelium-independent vasodilation (group 3).
In Group 3, the genotype distribution of

  • SNP rs5215 (Kir6.2/KCNJ11) moderately deviates from the HW equilibrium (p = 0.05).
In Group 1 (CAD), the polymorphism

  • rs6599230 of Nav1.5/SCN5A showed deviation from HW equilibrium (p = 0.017).
The genotypic distribution of groups in terms of polymorphisms for
  • eNOS/NOS3, SERCA/ATP2A2, Nav1.5/SCN5A, Kir6.1/KCNJ8, or Kv1.5/KCNA5
were noticed. However, significant differences (p.05) for the SNPs
  • rs5215_GG, and
  • rs5219_AA of Kir6.2/KCNJ11 were observed,
as shown in Table 2. 

Table 3 displays 
significant differences between normal subjects (group 3) and
  • patients with either CAD (group 1) or microvascular dysfunction (group 2).

BRC 2013 fedele genetic polymorphisms of ion channels_page_006

When correcting for other covariates as risk factors, the rs5215_GG genotype of Kir6.2/KCNJ11 was found to be 

  • significantly associated with CAD after multivariate analysis (OR = 0.319, p = 0.047, 95 % CI = 0.100–0.991), evidencing
  • a ‘‘protective’’ role of this genotype, as shown in Table 4a.

Similarly, a trend that supports this role of Kir6.2/KCNJ11 was also observed

  • in microvascular dysfunction for rs5219 AA. In contrast,
  • rs1799983_GT for eNOS/NOS3 was identified as an independent risk factor

following multivariate analysis (Table 4b), which agrees with literature findings as described below. 

BRC 2013 fedele genetic polymorphisms of ion channels_page_007

SOURCE for TABLES

BasicResCardiol(2013)108:387   http//dx.dio.org/10.1007/s00395-013-0387-4

Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

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Reporter: Aviva Lev-Ari, PhD, RN

Common Variation in Fatty Acid Genes and Resuscitation From Sudden Cardiac Arrest

Catherine O. Johnson, PhD, MPH, Rozenn N. Lemaitre, PhD, MPH, Carol E. Fahrenbruch, MSPH, Stephanie Hesselson, PhD, Nona Sotoodehnia, MD, MPH,Barbara McKnight, PhD, Kenneth M. Rice, PhD, Pui-Yan Kwok, MD, PhD, David S. Siscovick, MD, MPH and Thomas D. Rea, MD, MPH

Author Affiliations

From the Departments of Medicine (C.O.J., R.N.L., N.S., D.S.S., T.D.R.), Biostatistics (B.M., K.M.R.), and Epidemiology (D.S.S), University of Washington, Seattle; King County Emergency Medical Services, Seattle, WA (C.E.F.); and Institute of Human Genetics, University of California San Francisco (S.H., P.-Y.K.).

Correspondence to Catherine O. Johnson, PhD, MPH, Department of Medicine, University of Washington, CHRU 1730 Minor Ave, Suite 1360, Seattle, WA 98101. E-mail johnsoco@uw.edu

Abstract

Background—Fatty acids provide energy and structural substrates for the heart and brain and may influence resuscitation from sudden cardiac arrest (SCA). We investigated whether genetic variation in fatty acid metabolism pathways was associated with SCA survival.

Methods and Results—Subjects (mean age, 67 years; 80% male, white) were out-of-hospital SCA patients found in ventricular fibrillation in King County, WA. We compared subjects who survived to hospital admission (n=664) with those who did not (n=689), and subjects who survived to hospital discharge (n=334) with those who did not (n=1019). Associations between survival and genetic variants were assessed using logistic regression adjusting for age, sex, location, time to arrival of paramedics, whether the event was witnessed, and receipt of bystander cardiopulmonary resuscitation. Within-gene permutation tests were used to correct for multiple comparisons. Variants in 5 genes were significantly associated with SCA survival. After correction for multiple comparisons, single-nucleotide polymorphisms in ACSL1 and ACSL3 were significantly associated with survival to hospital admission. Single-nucleotide polymorphisms in ACSL3, AGPAT3, MLYCD, and SLC27A6 were significantly associated with survival to hospital discharge.

Conclusions—Our findings indicate that variants in genes important in fatty acid metabolism are associated with SCA survival in this population.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 422-429

Published online before print June 1, 2012

doi: 10.1161/ CIRCGENETICS.111.961912

 

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Heart and Aging Research in Genomic Epidemiology: 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients: Design of Prospective Meta-Analyses of Genome-Wide Association Studies From 5 Cohorts

Reporter: Aviva Lev-Ari, PhD, RN

 

Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

Heart and Aging Research in Genomic Epidemiology: 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients: Design of Prospective Meta-Analyses of Genome-Wide Association Studies From 5 Cohorts

Bruce M. Psaty, MD, PhD, Christopher J. O’Donnell, MD, MPH, Vilmundur Gudnason, MD, PhD, Kathryn L. Lunetta, PhD, Aaron R. Folsom, MD, Jerome I. Rotter, MD,André G. Uitterlinden, PhD, Tamara B. Harris, MD, Jacqueline C.M. Witteman, PhD,Eric Boerwinkle, PhD and on Behalf of the CHARGE Consortium

Author Affiliations

From the Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Wash; Center for Health Studies, Group Health (B.M.P.), Seattle, Wash; the National Heart, Lung and Blood Institute and the Framingham Heart Study (C.J.O.D.), Framingham, Mass; Icelandic Heart Association and the Department of Cardiovascular Genetics (Y.G.), University of Iceland, Reykjavik, Iceland; Department of Biostatistics (K.L.), Boston University School of Public Health, Mass; Division of Epidemiology and Community Health (A.R.F.), University of Minnesota, Minneapolis; Medical Genetics Institute (J.I.R.), Cedars-Sinai Medical Center, Los Angeles, Calif; Departments of Internal Medicine (A.G.U.) and Epidemiology (A.G.U., J.C.M.W.), Erasmus Medical Center, Rotterdam, The Netherlands; Laboratory of Epidemiology, Demography, and Biometry (T.B.H.), Intramural Research Program, National Institute on Aging, Bethesda, Md; and Human Genetics Center and Division of Epidemiology (E.B.), University of Texas, Houston.

Guest editor for this article was Elizabeth R. Hauser, PhD.

Abstract

Background— The primary aim of genome-wide association studies is to identify novel genetic loci associated with interindividual variation in the levels of risk factors, the degree of subclinical disease, or the risk of clinical disease. The requirement for large sample sizes and the importance of replication have served as powerful incentives for scientific collaboration.

Methods— The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium was formed to facilitate genome-wide association studies meta-analyses and replication opportunities among multiple large population-based cohort studies, which collect data in a standardized fashion and represent the preferred method for estimating disease incidence. The design of the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium includes 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility—Reykjavik Study, the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study. With genome-wide data on a total of about 38 000 individuals, these cohort studies have a large number of health-related phenotypes measured in similar ways. For each harmonized trait, within-cohort genome-wide association study analyses are combined by meta-analysis. A prospective meta-analysis of data from all 5 cohorts, with a properly selected level of genome-wide statistical significance, is a powerful approach to finding genuine phenotypic associations with novel genetic loci.

Conclusions— The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and collaborating non-member studies or consortia provide an excellent framework for the identification of the genetic determinants of risk factors, subclinical-disease measures, and clinical events.

Example of Coronary Heart Disease

The cohort-study methods papers provide detail about many of the phenotypes listed in Table 2. For coronary heart disease, investigators knowledgeable about the phenotype in each study decided to focus on fatal and nonfatal myocardial infarction (MI) as the primary outcome because the MI criteria differed in only trivial ways among the studies. There were some minor differences in the definition of the composite outcome of MI, fatal coronary heart disease, and sudden death, which became the secondary outcome. Only subjects at risk for an incident event were included in the analysis. MI survivors whose DNA was drawn after the event were not eligible. The primary analysis was restricted to Europeans or European Americans. Patients entered the analysis at the time of the DNA blood draw, and were followed until an event, death, loss to follow up, or the last visit. The main recommendations of the Analysis Committee were adopted, and a threshold of 5×10−8 was selected for genome-wide statistical significance. Analyses in progress include about 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients. Each cohort conducted its own analysis, and results were uploaded to a secure share site for the fixed-effects meta-analysis. Even with this number of events (Supplemental Figure 2), power is good for only for relatively high minor allele frequencies (>0.25) and large relative risks (>1.3).

The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.

Discussion

In thousands of published papers, the 5 CHARGE cohort studies and many of the collaborating studies have already characterized the risk factors for and the incidence and prognosis of a variety of aging-related and cardiovascular conditions. The analysis of the incident MI, for instance, is free from the survival bias typically associated with cross-sectional or case-control studies. The methodologic advantages of the prospective population-based cohort design, the similarity of phenotypes across 5 studies, the availability of genome-wide genotyping data in each cohort, and the need for large sample sizes to provide reliable estimates of genotype-phenotype associations have served as the primary incentives for the formation of the CHARGE consortium, which includes GWAS data on about 38 000 individuals. The consortium effort relies on collaborative methods that are similar to those used by the individual contributing cohorts.

Phenotype experts who know the studies and the data well are responsible for phenotype-standardization across cohorts. The coordinated prospectively planned meta-analyses of CHARGE provide results that are virtually identical to a cohort-adjusted pooled analysis of individual level data. This approach–the within-study analysis followed by a between-study meta-analysis–avoids the human subjects issues associated with individual-level data sharing.

Editors, reviewers, and readers expect replication as the standard in science.6 The finding of a genetic association in one population with evidence for replication in multiple independent populations provides moderate assurance against false-positive reports and helps to establish the validity of the original finding. In a single experiment, the discovery-replication structure is traditionally embodied in a 2-stage design. The CHARGE consortium includes up to 5 independent replicate samples as well as additional collaborating studies for some phenotype working groups, so that it would have been possible to set up analysis plans within CHARGE to mimic the traditional 2-stage design for replication. For instance, the 2 largest cohorts could have served as the discovery set and the others as the replication set. However, attaining the extremely small probability values expected in GWAS requires large sample sizes. For any phenotype, a prospective meta-analysis of all participating cohorts, with a properly selected level of genome-wide statistical significance to minimize the chance of false-positives, is the most powerful approach to finding new genuine associations for genetic loci.25 When findings narrowly miss the prespecified significance threshold, genotyping individuals in other independent populations provides additional evidence about the association. For findings that substantially exceed pre-established significance thresholds, the results of a CHARGE meta-analysis effectively provide evidence of a multistudy replication.

The effort to assemble and manage the CHARGE consortium has provided some interesting and unanticipated challenges. Participating cohorts often had relationships with outside study groups that predated the formation of CHARGE. Timelines for genotyping and imputation have shifted. Purchases of new computer systems for the volume of work were sometimes necessary. Each cohort came to the consortium with their own traditions for methods of analysis, organization, and authorship policies that, while appropriate for their own work, were not always optimal for collaboration with multiple external groups. Within each cohort, the investigators had often formed working groups that divided up the large number of available phenotypes in ways that made sense locally but did not necessarily match the configuration that had been adopted by other cohorts. The Research Steering Committee has attempted to create a set of CHARGE working groups that accommodate the needs and the conventions of the various cohorts. Transparency, disclosure, and professional collaborative behavior by all participating investigators have been essential to the process.

Resource limitations are another challenge. Grant applications that funded the original single-study genome-wide genotyping effort typically imagined a much simpler design. The CHS whole-genome study had as its primary aim, for instance, the analysis of data on 3 endpoints, coronary disease, stroke and heart failure. With a score of active phenotype working groups, the CHARGE collaboration broadened the scope of the short-term work well beyond initial expectations for all the participating cohorts.

One of the premier challenges has been communications among scores of investigators at a dozen sites. CHS and ARIC are themselves multi-site studies. To be successful, the CHARGE collaboration has required effective communications: (1) within each cohort; (2) between cohorts; (3) within the CHARGE working groups; and (4) among the major CHARGE committees. In addition to the traditional methods of conference calls and email, the CHARGE “wiki,” set up by Dr J. Bis (Seattle, Wash), has provided a crucial and highly functional user-driven website for calendars, minutes, guidelines, working group analysis plans, manuscript proposals, and other documents. In the end, there is no substitute for face-to-face meetings, especially at the beginning of the collaboration, and this complex meta-organization has benefited from several CHARGE-wide meetings.

The major emerging opportunity is the collaboration with other studies and consortia. Many working groups have already incorporated nonmember studies into their efforts. Several working groups have coordinated submissions of initial manuscripts with the parallel submission of manuscripts from other studies or consortia. Several working groups have embarked on plans for joint meta-analyses between CHARGE and other consortia. CHARGE has tried to acknowledge and reward the efforts of champions, who assume leadership responsibility for moving these large complex projects forward and who are often hard-working young investigators, the key to the future success of population science.

The CHARGE Consortium represents an innovative model of collaborative research conducted by research teams that know well the strengths, the limitations, and the data from 5 prospective population-based cohort studies. By leveraging the dense genotyping, deep phenotyping and the diverse expertise, prospective meta-analyses are underway to identify and replicate the major common genetic determinants of risk factors, measures of subclinical disease, and clinical events for cardiovascular disease and aging.

SOURCE:

Circulation: Cardiovascular Genetics.2009; 2: 73-80

doi: 10.1161/ CIRCGENETICS.108.829747

 

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Physiologist, Professor Lichtstein, Chair in Heart Studies at The Hebrew University elected Dean of the Faculty of Medicine at The Hebrew University of Jerusalem

Reporter: Aviva Lev-Ari, PhD, RN

Professor David Lichtstein Elected Dean of Hebrew University’s Faculty of Medicine

December 2, 2013

Jerusalem — Professor David Lichtstein has been elected dean of the Faculty of Medicine at The Hebrew University of Jerusalem. Professor Lichtstein is the Walter & Greta Stiel Chair in Heart Studies at The Hebrew University. He replaces Professor Eran Leitersdorf, who recently completed his four-year term as dean.

According to Professor Lichtstein, “The Hebrew University’s Faculty of Medicine is devoted to creating innovative teaching, research and patient care programs that will meet the demands of 21st century health care. As global health care moves towaProfessor David Lichtsteinrd prevention, wellness and cost effectiveness, we are adapting how we train the next generation of physicians, nurses, pharmacists and biomedical researchers. Through fruitful collaborations between preclinical and clinical faculty, we are also translating basic biomedical insights into clinical treatments. Thus, the Faculty of Medicine is well-positioned to maintain its leading role in the scientific community of Israel and the world.”

Professor Lichtstein was born in Lodz, Poland, and immigrated to Israel with his family in 1957. As a student at The Hebrew University, he completed a Bachelor’s degree in Physiology and Zoology in 1970, followed by a Master’s degree in Physiology in 1972 and a Ph.D. in Physiology in 1977. He joined the Department of Physiology of The Hebrew University-Hadassah Medical School in 1980 as a lecturer, and received full professorship in 1994. Prof. Lichtstein has held many roles at The Hebrew University and its Faculty of Medicine, including Chairman of the Neurobiology Teaching Division, Chairman of the Department of Physiology, Chairman of the Institute for Medical Sciences and, until recently, Chairman of the Faculty of Medicine. From 2007 to 2011, Professor Lichtstein was the Jacob Gitlin Chair in Physiology at The Hebrew University. In 2011 he was named the Walter & Greta Stiel Chair in Heart Studies at The Hebrew University. He also served as the President of the Israel Society for Physiology and Pharmacology from 1996 to 1999.

From 1977-1979 Professor Lichtstein was a Postdoctoral Fellow at the Roche Institute of Molecular Biology in New Jersey. He was a visiting scientist at the National Institute of Child Health and Human Development (1985-1986) and the Eye Institute (1997-1998) at the National Institutes of Health in Maryland, and a visiting professor at the Toledo School of Medicine in Ohio (2007).

Professor. Lichtstein’s main research focus is the regulation of ion transport across the plasma membrane of eukaryotic cells. His work led to the discovery that specific steroids that were known to be present in plants and amphibians are actually normal constituents of the human body and have crucial roles, such as the regulation of cell viability, heart contractility, blood pressure and brain function. His research has implications for the fundamental understanding of body functions, as well as for several pathological states such as heart failure, hypertension and neurological and psychiatric diseases.

SOURCE

http://www.afhu.org/professor-david-lichtstein-elected-dean-hebrew-universitys-faculty-medicine

Field of Study

Regulation of ion transport across the plasma membrane:
The primary focus of the research in my laboratory is the regulation of ion transport across the plasma membrane of eukaryotic cells. In particular, we study the main transport system for sodium and potassium, the sodium-potassium-ATPase, and its regulation by cardiac steroids.
Specific areas of interest:
Identification of endogenous cardiac steroids in mammalian tissue; The biological consequences of the interaction of cardiac steroids with the sodium-potassium-ATPase; Biosynthesis of the cardiac steroids in the adrenal gland; Effects of endogenous sodium-potassium-ATPase inhibitors on cell differentiation; Determination of the levels of endogenous sodium-potassium-ATPase inhibitors in pathological states, including hypertension, preeclampsia; malignancies (cancer) and manic depressive illnesses; Involvement of the sodium-potassium–ATPase/cardiac steroids system in depressive disorders; Involvement of the sodium-potassium-ATPase/cardiac steroids system in cardiac function; Involvement of intestinal signals in the regulation of phosphate homeostasis; Volume regulation and its involvement in the mitogenic response.
Cardiac Steroids and the Na+, K+-ATPase and Cardiac Steroids
Cardiac steroids, such as ouabain, digoxin and bufalin are hormones synthesized by and released from the adrenal gland and the hypothalamus. These compounds, the structure of which resembles that of plant and amphibian and butterfly steroids, interact only with the plasma membrane Na+, K+-ATPase (Figure 1). This interaction elicits numerous specific biological responses affecting the function of cells and organs.
Topics Currently under investigation include
Cardiac Steroids
  • Ouabain
  • Bufalin
  • Dogoxin
Involvement of the sodium-potassium–ATPase/cardiac steroids system in depressive disorders
Depressive disorders, including major depression, dysthymia and bipolar disorder, are a serious and devastating group of diseases that have a major impact on the patients’ quality of life, and pose a significant concern for public health. The etiology of depressive disorders remains unclear. The Monoaminergic Hypothesis, suggesting that alterations in monoamine metabolism in the brain are responsible for the etiology of depressive disorders, is now recognized as insufficient to explain by itself the complex etiology of these diseases. Data from our and other laboratories has provided initial evidence that endogenous cardiac steroids and their only established receptor, the Na+, K+-ATPase, are involved in the mechanism underlining depressive disorders, and BD in particular. Our study (Biol. Psychiatry. 60:491-499, 2006) has proven that Na+, K+-ATPase and DLC are involved in depressive disorders particularly in manic-depression. We have also shown that specific genetic alterations in the Na+, K+-ATPase α isoforms are associated with bipolar disorders (Biol. Psychiatry, 65:985-991, 2009). Our recent study in this project (Eur. Neuropsychopharmacol. 22:72-729, 2012) showed that drugs affecting the Na+, K+-ATPase/cardiac steroids system are beneficial for the treatment of depression. Hence our work is in accordance to the proposition that mal functioning of the Na+, K+-ATPase/cardiac steroids system may be involved in manifestation of depressive disorders and identify new compounds as potential drug for the treatment of these maladies.
Involvement of the sodium-potassium-ATPase/cardiac steroids system in cardiac function
The classical and best documented effect of cardiac steroids, as their name implies, is to increase the force of contraction of heart muscle. Indeed, cardiac steroids were widely used in Western and Eastern clinical practices for the treatment of heart failure and atrial fibrillation. Despite extensive research, the mechanism underlying cardiac steroids actions have not been fully elucidated. The dogmatic explanation for cardiac steroids-induced increase in heart contractility is that the inhibition of Na+, K+-ATPase by the steroids causes an increase in intracellular Na+ which, in turn, attenuates the Na+/Ca++ exchange, resulting in an increased intracellular Ca++ concentration, and hence greater contractility. However, recent observations led to the hypothesis that the ability of cardiac steroids to modulate a number of intracellular signaling processes may be responsible for both short- and long-term changes in CS action on cardiac function. We are addressing this hypothesis using the zebrafish model and our ability to quantify heart function in-vivo. Heart contractility measurements were performed using a series of software tools for the analysis of high-speed video microscopic images, allowing the determination of ventricular heart diameter and perimeter during both diastole and systole. The ejection fraction (EF) and fractional area changes (FAC) were calculated from these measurements, providing two independent parameters of heart contractility (see attached movie bellow). We are currently testing the effect of cardiac steroids in the presence and absence of intracellular signaling pathways (MAP, AKT, IP3R) inhibitors. Reduction in the steroids ability to increase the force of contraction will serve as the first evidence, in-vivo, for the participation of the signaling processes in the molecular mechanisms responsible for the action of cardiac steroids on heart muscle.
Laboratory Techniques
We employ a broad range of preparations and techniques. These include isolated organs (arterial rings, smooth and cardiac muscle strips) and isolated nerve endings, as well as primary and established tissue-cultured cells. Our studies involve the application of biochemical and immunological techniques (transport and enzymatic activity measurements, RIA, ELISA), molecular biological techniques (e.g., Western and Northern blotting, and PCR), protein purification (HPLC), cellular techniques muscle contractility, cell proliferation and differentiation’ in-vivo measurements of heart contractility and blood flow in Zebrafish and behavior measurements in rodents.

Biography

Education
1970
B.Sc. in Physiology and Zoology, The Hebrew University, Jerusalem, Israel
1970-1972 M.Sc. in Physiology, Department of Physiology, The Hebrew University, Hadassah Medical School, Jerusalem, Israel.
1973-1977
Ph.D., Department of Physiology, Hebrew University Hadassah Medical School, Jerusalem, Israel. (Thesis: “Increased Production of Gamma Aminobutyryl choline in Cerebral Cortex Caused by Afferent Electrical Stimulation” (Thesis Advisors: Prof. J. Dobkin and Prof. J. Magnes).
1977-1979
Postdoctoral Fellow, Department of Physiological Chemistry and Pharmacology, Roche Institute of Molecular Biology, Nutley, New Jersey, U.S.A.
Positions held

1970-1972
Teaching and Research Assistant, Department of Physiology, The Hebrew University, Hadassah Medical School, Jerusalem, Israel
1972-1974 Assistant Instructor, Department of Physiology, The Hebrew University, Hadassah Medical School, Jerusalem, Israel
1975-1977 Instructor, Department of Physiology, The Hebrew University, Hadassah Medical School, Jerusalem, Israel
1977-1979
Postdoctoral Fellow, Department of Physiological Chemistry and Pharmacology, Roche Institute of Molecular Biology, Nutley, New Jersey, U.S.A.
1979-1983
Lecturer, (REVSON fellowship) Department of Physiology, The Hebrew University, Hadassah Medical School, Jerusalem, Israel
1981 (summer)
Visiting Scientist, Department of Physiological Chemistry and Pharmacology, Roche Institute of Molecular Biology, Nutley, New Jersey, USA
1983-1987 Senior Lecturer, Department of Physiology, The Hebrew University Hadassah Medical School, Jerusalem, Israel.
1985-1986
Visiting Scientist, Laboratory of Theoretical and Physical Biology, NICHD, National Institutes of Health, Bethesda, Maryland, USA
1988-1994 Associate Professor, Department of Physiology, The Hebrew University Hadassah Medical School, Jerusalem, Israel
1994-present Professor of Physiology, Department of Physiology, The Hebrew University Hadassah Medical School, Jerusalem, Israel
1997-1998 Visiting Scientist, Laboratory of Mechanisms of Ocular Diseases, NEI, National Institutes of Health, Bethesda, Maryland, USA
2007 (summer)
Visiting Professor, Department of Physiology, Pharmacology, Metabolism and cardiovascular Sciences, Medical Center University of Toledo, Toledo, Ohio, USA
2007-2011 Jacob Gitlin Chair in Physiology, The Hebrew University, Jerusalem, Israel
​2011-present ​Walter & Greta Stiel Chair in Heart Studies, The Hebrew University, Jerusalem
Professional Membership
1979-present International Society of Neurochemistry
1979-present Israel Society for Physiological and Pharmacological
1980-present Society of Neurosciences (Europe)
1986-present The American Society of Hypertension
1992-present Israeli Society for Neurosciences
1999-present The American Physiological Society
Editorial Tasks
Serving as a Reviewer for the scientific journals:
• American Journal of Hypertension • Journal of Neural Transmission
• American Journal of Physiology • Journal of Neurochemistry
• Apoptosis • Journal of Pharmacology and Experimental Therapeutics
• Biochemical and Biophysical Research Communications • Life Sciences
• Basic Journal of Physiology and Pharmacology • NANO
• Brain Research • Neurochemistry International
• Bioconjugate Chemistry • Neuroscience
• Cell Calcium • Neurotoxicity Research
• Clinical Science • Pathophysiology
• Endocrinology • Physiology and Behavior
• European Neuropsychopharmacology • PNAS
• General and Comparative Endocrinology • Psychiatry Research
• Hypertension • Translational Research
• Journal of Cell Sciences
University and Other Activities
1982-1985 Chairman of the Neurobiology Teaching Division, The Hebrew University, Jerusalem
1988-1994 Elected representative of the Senior Lecturers and Associate Professors for the University Senate
1989-1997 Member of the admission committee of the Medical School, The Hebrew University, Jerusalem
1990-1996 Member of the Committee for cellular biology of the graduate studies, The Hebrew University, Jerusalem
1992-1996 Member of the Teaching Committee, Faculty of Medicine, The Hebrew University, Jerusalem
1992-1996
Chairman, Department of Physiology, The Hebrew University, Hadassah Medical School, Jerusalem
1994-1997 Member of the Committee for graduate studies, The Hebrew University, Jerusalem
1992-2002
Member of the Management Committee of The Institute for Medical Sciences, Faculty of Medicine, The Hebrew University, Jerusalem
1996-1999
President of the Israel Society for Physiology and Pharmacology
1998- 2002 Chairman, Institute of Medical Sciences, The Hebrew University, Hadassah Medical School, Jerusalem
1999-2002 Member of the Planning and Development Committee of the Faculty of Medicine, The Hebrew University, Jerusalem
2007–Present Elected representative of the Professors for the executive University Senate
2008-2012 Member of the Planning and Development Committee of the Faculty of Medicine, The Hebrew University, Jerusalem
2008-2012 Chairman, Institute for Medical Research Israel-Canada, The Hebrew University, Hadassah Medical School, Jerusalem
2009 – Present Elected member of the Senate to the Executive Committee of the Hebrew University

PUBLICATIONS 2006 – 2012

Search By:  Author Abeles, M Abramovitch, R Allweis, C Altuvia, S Amedi, A Amster-Choder, O Anglister, L Aqeilan, RI Aronovitch, Y Bachrach, U Baniyash, M Barak, V Barenholz, Y Bar-Shalita, T Bar-Shavit, R Bar-Shavit, Z Bar-Tana, J Becker, Y Behar, O Ben-Ishay, Z Benita, S Ben-Neriah, Y Benny, O Ben-Or, S Ben-porath, I Ben-Sasson, S Ben-Sasson, SZ Ben-Shaul, Y Ben-Yehuda, S Bercovier, H Berger, M Bergman, H Bergman, Y Berry, E Bialer, M Binshtok, AM Blum, G Brandes, R Brautbar, C Breuer, E Cedar, H Chevion, M Chinitz, D Citri, N Cohen, A Cohen, E Deutsch, J Dikstein, S Domb, A Dor, Y Dror, OE Dzikowski, R Elkin, M Engelberg-Kulka, H Even-Ram, S Eyal, S Fainsod, A Feintuch, U Friedlander, y Friedman, M Gallily, R Gatt, S Gerlitz, O Gertz, SD Gibson, D Glaser, G Goelman, G Goldberg, I Goldberg, JA Goldblum, A Golenser, J Golomb, G Golos, A Gordon, A Gorinstein, S Gorodetsky, R Granot, Z Greenblatt, CL Greenwald, T Gross, E Grover, N Gutman, Y Hahn-Markowitz, J Hamburger, J Hanani, M Hanski, E Hartman-Maeir, A Hellman, A Hochner, H Hoffman, A Honigman, A Horowitz, M Ilani, A Inbal, A Jaffe, CL Jarrous, N Kaempfer, R Kalcheim, C Kanner, BI Kapitulnik, J Karni, R Katz, E Katzav, S Katz-Brull, R Katzhendler, J Kedar, E Keren, N Keshet, E Klar, A Kohen, R Konijn, A Kotler, M Langer, D Laskov, R Lazarovici, P Levi-Schaffer, F Lev-Tov, A Lichtstein, D Liebergall, M Lorberboum-Galski, H Magen, H Mandelboim, O Manor, O Margalit, H Matok, I Mechoulam, R Meiri, H Melloul, D Meyuhas, O Minke, B Mishani, E Mitrani-Rosenbaum, S Mumcuoglu, K Naor, D Naveh-Many, T Neumark, Y Nussinovitch, I Oppenheim, A Ornoy, A Panet, A Paroush, Z Parush, S Peled, A Pikarsky, E Pines, O Priel, A Prut, Y Rachmilewitz, J Rahamimoff, H Ravid, S Razin, A Razin, E Razin, S Reich, R Reshef, L Richter, E Ringel, I Rokem, JS Rom, M Ron, A Rosen, H Rosenshine, I Rotenberg-Shpigelman, S Rotshenker, S Rottem, S Rubinstein, A Samueloff, S Samuni, A Sasson, S Schlein, Y Schlesinger, M Schueler-Furman, O Sharon, D Sharon, R Shaulian, E Shlomai, J Shmueli, A Shohami, E Shtarkshall, R Shurki, A Simon, I Smith, P Sohmer, H Sperling, D Steinitz, M Stern-Bach, Y Tal, M Taraboulos, A Ta-Shma, R Tirosh, B Touitou, E Trachtenberg, S Traub, R Treinin, M Tsvelikhovsky, D Vaadia, E Warburg, A Weinstock, M  Weintraub, N Weiss, D Weiss, R Wiener, R Wormser, U Yaari, Y Yagen, B Yaka, R yanai, J Yavin, E Yedgar, S Yefenof, E Yisraeli, JK Yochman, A Yogev, D Yosselson-Superstine, S Zajicek, G Zakay-Rones, Z  Sort By:  Year Descending Year Ascending  Text:
Dvela, M., Rosen, H., Ben-Ami, H. C., Lichtstein, D.
American journal of physiology. Cell physiology, 302(2), C442-52, 2012
Goldstein, I., Lax, E., Gispan-Herman, I., Ovadia, H., Rosen, H., Yadid, G., Lichtstein, D.
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology, 22(1), 72-9, 2012
Nesher, M., Shpolansky, U., Viola, N., Dvela, M., Buzaglo, N., Cohen Ben-Ami, H., Rosen, H., Lichtstein, D.
British journal of pharmacology, 160(2), 346-54, 2010
Guttmann-Rubinstein, L., Lichtstein, D., Ilani, A., Gal-Moscovici, A., Scherzer, P., Rubinger, D.
Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme, 42(4), 230-6, 2010
Jaiswal, M. K., Dvela, M., Lichtstein, D., Mallick, B. N.
Journal of sleep research, 19(1 Pt 2), 183-91, 2010
Nesher, M., Dvela, M., Igbokwe, V. U., Rosen, H., Lichtstein, D.
American journal of physiology. Heart and circulatory physiology, 297(6), H2026-34, 2009
Goldstein, I., Lerer, E., Laiba, E., Mallet, J., Mujaheed, M., Laurent, C., Rosen, H., Ebstein, R. P., Lichtstein, D.
Biological psychiatry, 65(11), 985-91, 2009
Nesher, M., Vachutinsky, Y., Fridkin, G., Schwarz, Y., Sasson, K., Fridkin, M., Shechter, Y., Lichtstein, D.
Bioconjugate chemistry, 19(1), 342-8, 2008
Dvela, M., Rosen, H., Feldmann, T., Nesher, M., Lichtstein, D.
Pathophysiology : the official journal of the International Society for Pathophysiology / ISP, 14(3-4), 159-66, 2007
Feldmann, T., Glukmann, V., Medvenev, E., Shpolansky, U., Galili, D., Lichtstein, D., Rosen, H.
American journal of physiology. Cell physiology, 293(3), C885-96, 2007
Chirinos, J. A., Corrales-Medina, V. F., Garcia, S., Lichtstein, D. M., Bisno, A. L., Chakko, S.
Clinical rheumatology, 26(4), 590-5, 2007
Lichtstein, D. M., Arteaga, R. B.
The American journal of the medical sciences, 332(2), 103-5, 2006
Morla, D., Alazemi, S., Lichtstein, D.
Journal of general internal medicine, 21(7), C11-3, 2006
Chirinos, J. A., Corrales, V. F., Lichtstein, D. M.
Clinical rheumatology, 25(1), 111-2, 2006
Deutsch, J., Jang, H. G., Mansur, N., Ilovich, O., Shpolansky, U., Galili, D., Feldman, T., Rosen, H., Lichtstein, D.
Journal of medicinal chemistry, 49(2), 600-6, 2006
Goldstein, I., Levy, T., Galili, D., Ovadia, H., Yirmiya, R., Rosen, H., Lichtstein, D.
Biological psychiatry, 60(5), 491-9, 2006
Chirinos, J. A., Garcia, J., Alcaide, M. L., Toledo, G., Baracco, G. J., Lichtstein, D. M.
American journal of cardiovascular drugs : drugs, devices, and other interventions, 6(1), 9-14, 2006
Rosen, H., Glukmann, V., Feldmann, T., Fridman, E., Lichtstein, D.
Cellular and molecular biology (Noisy-le-Grand, France), 52(8), 78-86, 2006

SOURCE

https://medicine.ekmd.huji.ac.il/En/Publications/publications/Pages/default.aspx?aut=Lichtstein,%20D

 

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Genetics of Aortic and Carotid Calcification: The Role of Serum Lipids

Reporter: Aviva Lev-Ari, PhD, RN

Genetic Loci for Coronary Calcification and Serum Lipids Relate to Aortic and Carotid Calcification

Daniel Bos, MD, M. Arfan Ikram, MD, PhD, Aaron Isaacs, PhD, Benjamin F.J. Verhaaren, MD, Albert Hofman, MD, PhD, Cornelia M. van Duijn, PhD, Jacqueline C.M. Witteman, PhD, Aad van der Lugt, MD, PhD and Meike W. Vernooij, MD, PhD

Author Affiliations

From the Departments of Radiology (D.B., M.A.I., B.F.J.V., A.v.d.L., M.W.V), Epidemiology (D.B., M.A.I., A.I., B.F.J.V., A.H., C.M.v.D., J.C.M.W., M.W.V.), and Genetic Epidemiology Unit (A.I., C.M.v.D.), Erasmus MC, Rotterdam, the Netherlands.

Correspondence to Meike W. Vernooij, MD, PhD, Department of Radiology, Erasmus MC, Gravendijkwal 230, PO Box 2040, 3000CA Rotterdam, the Netherlands. E-mailm.vernooij@erasmusmc.nl

Abstract

Background—Atherosclerosis in different vessel beds shares lifestyle and environmental risk factors. It is unclear whether this holds for genetic risk factors. Hence, for the current study genetic loci for coronary artery calcification and serum lipid levels, one of the strongest risk factors for atherosclerosis, were used to assess their relation with atherosclerosis in different vessel beds.

Methods and Results—From 1987 persons of the population-based Rotterdam Study, 3 single-nucleotide polymorphisms (SNPs) for coronary artery calcification and 132 SNPs for total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides were used. To quantify atherosclerotic calcification as a marker of atherosclerosis, all participants underwent nonenhanced computed tomography of the aortic arch and carotid arteries. Associations between genetic risk scores of the joint effect of the SNPs and of all calcification were investigated. The joint effect of coronary artery calcification–SNPs was associated with larger calcification volumes in all vessel beds (difference in calcification volume per SD increase in genetic risk score: 0.15 [95% confidence interval, 0.11–0.20] in aorta, 0.14 [95% confidence interval, 0.10–0.18] in extracranial carotids, and 0.11 [95% confidence interval, 0.07–0.16] in intracranial carotids). The joint effect of total cholesterol SNPs, low-density lipoprotein SNPs, and of all lipid SNPs together was associated with larger calcification volumes in both the aortic arch and the carotid arteries but attenuated after adjusting for the lipid fraction and lipid-lowering medication.

Conclusions—The genetic basis for aortic arch and carotid artery calcification overlaps with the most important loci of coronary artery calcification. Furthermore, serum lipids share a genetic predisposition with both calcification in the aortic arch and the carotid arteries, providing novel insights into the cause of atherosclerosis.

 SOURCE:

Circulation: Cardiovascular Genetics.2013; 6: 47-53

Published online before print December 16, 2012,

doi: 10.1161/ CIRCGENETICS.112.963934

 

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Gene Study of Blood Pressure Response to Dietary Potassium Intervention: Genetic Epidemiology of Salt Sensitivity

Reporter: Aviva Lev-Ari, PhD, RN

Genome-Wide Linkage and Positional Candidate Gene Study of Blood Pressure Response to Dietary Potassium Intervention

The Genetic Epidemiology Network of Salt Sensitivity Study

Tanika N. Kelly, PhD, James E. Hixson, PhD, Dabeeru C. Rao, PhD, Hao Mei, MD, PhD,Treva K. Rice, PhD, Cashell E. Jaquish, PhD, Lawrence C. Shimmin, PhD, Karen Schwander, MS, Chung-Shuian Chen, MS, Depei Liu, PhD, Jichun Chen, MD,Concetta Bormans, PhD, Pramila Shukla, MS, Naveed Farhana, MS, Colin Stuart, BS,Paul K. Whelton, MD, MSc, Jiang He, MD, PhD and Dongfeng Gu, MD, PhD

Author Affiliations

From the Department of Epidemiology (T.N.K., H.M., C.-S.C., J.H.), Tulane University School of Public Health and Tropical Medicine, and Department of Medicine (J.H.), Tulane University School of Medicine, New Orleans, La; Department of Epidemiology (J.E.H., L.C.S., C.B., P.S., N.F., C.S.), University of Texas School of Public Health, Houston, Tex; Division of Biostatistics (D.C.R., T.K.R., K.S.), Washington University School of Medicine, St Louis, Mo; Division of Prevention and Population Sciences (C.E.J.), National Heart, Lung, Blood Institute, Bethesda, Md; National Laboratory of Medical Molecular Biology (D.L.), Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Cardiovascular Institute and Fuwai Hospital (J.C., D.G.), Chinese Academy of Medical Sciences and Peking Union Medical College and Chinese National Center for Cardiovascular Disease Control and Research, Beijing, China; and Office of the President (P.K.W.), Loyola University Health System and Medical Center, Maywood, Ill.

Correspondence to Dongfeng Gu, MD, PhD, Division of Population Genetics and Prevention, Cardiovascular Institute and Fuwai Hospital, 167 Beilishi Rd, Beijing 100037, China. E-mail gudongfeng@vip.sina.com

Abstract

Background— Genetic determinants of blood pressure (BP) response to potassium, or potassium sensitivity, are largely unknown. We conducted a genome-wide linkage scan and positional candidate gene analysis to identify genetic determinants of potassium sensitivity.

Conclusions— Genetic regions on chromosomes 3 and 11 may harbor important susceptibility loci for potassium sensitivity. Furthermore, the AGTR1 gene was a significant predictor of BP responses to potassium intake.

SOURCE:

Circulation: Cardiovascular Genetics. 2010; 3: 539-547

Published online before print September 22, 2010,

doi: 10.1161/ CIRCGENETICS.110.940635

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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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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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