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Reporter: Aviva Lev-Ari, PhD, RN

Systems Pharmacology – Pathways to Patient Response @ BioIT World, April 9-11, 2013, World Trade Center, Boston, MA

Jake Y. Chen’s presentation at the conference is to be viewed at the link, below

http://www.chiresource.com/BIT-05-23/Presentations/NPC/Chen_Jake.pdf

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Reporter: Aviva Lev-Ari, PhD, RN

Systems Pharmacology – Pathways to Patient Response @ BioIT World, April 9-11, 2013, World Trade Center, Boston, MA

Eric Sobie’s presentation at the conference is to be viewed at the link, below

http://www.chiresource.com/BIT-05-23/Presentations/NPC/Sobie_Eric.pdf

http://www.mountsinai.org/profiles/eric-a-sobie

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We celebrate 1,544 articles, 5,683 tags, 303,847 views, first article 4/30/2012 – Open Access Online Scientific Journal

Reporter: Aviva Lev-Ari, PhD, RN

Updated on 11/13/2023

2023 Update from LPBI Group

https://pharmaceuticalintelligence.com/2022/02/21/update-from-lpbi-group/

Update on 1/1/2023 by Srinivas Sriram and Abhisar Anand

1/1/2023- 2,205,188 views

Content

1/1/2023- 6,162 Posts

754 Categories

10,688 Tags

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WordPress.com Annual Report for 2013

The Louvre Museum has 8.5 million visitors per year. This blog was viewed about 220,000 times in 2013. If it were an exhibit at the Louvre Museum, it would take about 9 days for that many people to see it.

In 2013, there were 958 new posts, growing the total archive of this blog to 1,505 posts. There were 982 pictures uploaded, taking up a total of 253 MB. That’s about 3 pictures per day.

The busiest day of the year was September 19th with 2,501 views. The most popular post that day was Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?.

SOURCE

http://pharmaceuticalintelligence.com/2013/annual-report/

UPDATES on 1/4/2014

On 1/4/2014

We celebrate 1,544 articles, 5,683 tags, 303,847 views, first article 4/30/2012 – Open Access Online Scientific Journal  

UPDATED on 11/10/2013

On April 15, 2013

We celebrate 800 articles, 4040 tags, 158,147 views, first article 4/30/2012 – Open Access Online Scientific Journal

On November 10, 2013

We celebrate 1,338 articles, 5,316 tags, 275,104 views, first article 4/30/2012 – Open Access Online Scientific Journal

Encouragement by the Founder: Aviva Lev-Ari, PhD, RN

Updated CURRENT NEEDS on 1/1/2014:

We are SEEKING resources to satisfy our needs at present time:

1. Efforts to find a buyer for our Scientific Journal for 12/2014

http://pharmaceuticalintelligence.com

2. Efforts to find a Publisher for a hardcopy version of a Three Volume Series  onCardiovascular Diseases

3. Find few additional Authors for the Journal

4. Find Editors for Cardiovascular Diseases e-Books

5. Find one Editor for Infectious Diseases

6. Find one Editor for immunology

7. Find few Patent Holders in BioMed, for our Business Partner in Shanghai to be connected to Private Equity investors

8. Find Angel Investors for Venture #5

Business Portfolios

VENTURE #1:

e-Publishing: Medicine, HealthCare, Life Sciences, BioMed, Pharmaceutical

  • Open Access Online Scientific Journal

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Site statistics http://pharmaceuticalintelligence.com/wp-admin/index.php?page=stats

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VENTURE #2:

1. BioMedical e-Books Series:

http://pharmaceuticalintelligence.com/biomed-e-books/

2. on Amazon’s Kindle e-Books List since 6/2013

3. Plans for Volume 1,2,3 – Hardcover

 

VENTURE #3:

International Scientific Delegations

http://pharmaceuticalintelligence.com/scientific-delegation/

  • Shanghai, May 2014 
  • Barcelona, Spain, November 2014
  • Amsterdam, May 2015
  • Geneva, November 2015

VENTURE #4:

Joint Ventures

http://pharmaceuticalintelligence.com/joint-ventures/

  • Leaders in Pharmaceutical Business Intelligence AND NEW MEDICINE, INC. [ongoing]
  • Leaders in Pharmaceutical Business Intelligence AND Bio-Tree Systems [pending Bio-Tree finding funding]
  • Leaders in Pharmaceutical Business Intelligence AND Lou Pharma [pending finding Licensees for drugs manufactured in Spain]
  • Leaders in Pharmaceutical Business Intelligence AND AlphaSzenszor Inc.
  • Leaders in Pharmaceutical Business Intelligence AND ValveCure, LLC

VENTURE #5:

Invented HERE!

1.  Development of a NEW Nitric Oxide monitor to Alpha Szenszor Inc. sensor portfolio. A concept for a low cost POC e-nose, capable of real time ppb detection of Cancer
The Cancer Team at Leaders in Pharmaceutical Business Intelligence under the leadership of Dr. Williams

2.  Development of a NEW Nitric Oxide monitor to Alpha Szenszor Inc. sensor portfolio. A concept for Inhaled Nitric Oxide for the Adult HomeCare Market –

IP by Dr. Pearlman and Dr. A. Lev-Ari

a.  iknow iNO is i-kNOw – Inhaled Nitric Oxide for the HomeCare Market

http://pharmaceuticalintelligence.com/2013/10/16/iknow-ino-is-i-know-inhaled-nitric-oxide-for-the-homecare-market/

b. electronic Book on Nitric Oxide by Nitric Oxide Team @ Leaders in Pharmaceutical Business Intelligence (LPBI)

Perspectives on Nitric Oxide in Disease Mechanisms

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

c. The rationale and use of inhaled NO in Pulmonary Artery Hypertension and Right Sided Heart Failure

Larry H. Bernstein 8/20/2012

d. Inhaled Nitric Oxide in Adults: Clinical Trials and Meta Analysis Studies – Recent Findings

3.  Cancer Genomics for NEW product development in diagnosis and treatment of Cancer Patients using sensory technology with applications for Radiation Therapy – The Cancer Team at Leaders in Pharmaceutical Business Intelligence under leadership of Dr. Sidney Kadish.

4.  Developing Mitral Valve Disease: MRI Methods and Devices for Percutaneous Mitral Valve Replacement and Mitral Valve Repair
Augmentation of Patented Technology using RF – Dr. Pearlman’s IP Non-Hardware Mitral Annuloplasty – Dr. Justin D. Pearlman

http://pharmaceuticalintelligence.com/joint-ventures/valvecure-llc/non-hardware-mitral-annuloplasty-dr-justin-d-pearlman/

5.  Novel Technology using MRI for Vascular Lesions, Tumors, Hyperactive Glands and non-Surgical Cosmetic Reconstruction – Dr. Pearlman’s IP

http://pharmaceuticalintelligence.com/biomed-e-books/series-a-e-books-on-cardiovascular-diseases/httppharmaceuticalintelligence-combiomed-e-bookscardiovascular-diseases-causes-risks-and-management/cvd-business-affairs/mitral-valve-disease-mri-methods-and-devices/

VENTURE # 6:

PRESS Coverage of Conferences

http://pharmaceuticalintelligence.com/press-coverage/

Top Authors for all days ending 2014-01-05 (Summarized)

 

Author Views
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Curator: Aviva Lev-Ari, PhD, RN

 

UPDATED on 7/29/2018

 

HDL-C: Is It Time to Stop Calling It the ‘Good’ Cholesterol? – Medscape – Jul 27, 2018.

 

In Eli Lilly’s Pipeline: DISCONTINUING Evacetrapib, a CETP inhibitor that’s meant to boost HDL

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/10/12/in-eli-lillys-pipeline-discontinuing-evacetrapib-a-cetp-inhibitor-thats-meant-to-boost-hdl/

 

On April 3, 2012 we published

Fight against Atherosclerotic Cardiovascular Disease: A Biologics not a Small Molecule – Recombinant Human lecithin-cholesterol acyltransferase (rhLCAT) attracted AstraZeneca to acquire AlphaCore

ACP-501, a recombinant human lecithin-cholesterol acyltransferase (LCAT) enzyme.

LCAT, an enzyme in the bloodstream, is a key component in the reverse cholesterol transport (RCT) system, which is thought to play a major role in driving the removal of cholesterol from the body and may be critical in the management of high-density lipoprotein (HDL) cholesterol levels.  The LCAT enzyme could also play a role in a rare, hereditary disorder called familial LCAT deficiency (FLD) in which the LCAT enzyme is absent.

http://pharmaceuticalintelligence.com/2013/04/03/fight-against-atherosclerotic-cardiovascular-disease-a-biologics-not-a-small-molecule-recombinant-human-lecithin-cholesterol-acyltransferase-rhlcat-attracted-astrazeneca-to-acquire-alphacore/

On April 4, 2013, the next day, a new study was published on a novel class of compounds, cholesteryl ester transfer protein (CETP) inhibitors, has demonstrated many potentially beneficial lipid-modifying effects was published on Anacetrapib, a compound that causes near-complete CETP inhibition, has among its effects, robust reductions in LDL-C and lipoprotein(a) as well as dramatic increases in HDL-C. The ability of anacetrapib to reduce coronary disease events is being tested in the Randomized EValuation of the Effects of Anacetrapib Through Lipid-modification (REVEAL) trial (NCT01252953).

Writer’s VIEWS:

    • AstraZeneca acquisition of AlphaCore represents its market entry into the CETP inhibitor segment via an acquisition where the company did not have presence or inhouse research. The results of the second study will position Merck at a superior position upon completion of Phase III Clinical Trials for Anacetrapib
    • If Biologics will help increase HDL in wide market penetration, the market share of Statins will be negatively impacted. Patent expiration and generic market availability of Statin erode future profits
    • Anacetrapib in in Phase III clinical Trial, if successfully completed — will be the FIRST biologics to use CETP inhibition biology of lipid metabolism in the quest to fight atherosclerosis by improving CVD outcomes
    • A connection between this two events and cites in Disclosure, AstraZeneca, Merck, supporting the research of Christopher P Cannon on the study on Anacetrapib.
    • Full Article PDF file was published in Research Reports in Clinical Cardiology, one of the Journals on Beall’s list publisher, where scientists pay to have the article been published, Dove Press, on its Web site says, “There are no limits on the number or size of the papers we can publish.” See reference for Beall’s list publishers http://www.nytimes.com/2013/04/08/health/for-scientists-an-exploding-world-of-pseudo-academia.html?pagewanted=1&_r=0&emc=eta1

Study Goals:

  • testing the hypothesis that CETP inhibition may reduce atherosclerotic outcomes. 
  • answer important questions regarding the role of CETP in the biology of lipid metabolism and atherosclerosis.

Research Reports in Clinical Cardiology, 4 April 2013 Volume 2013:4 Pages 39 – 53

Dylan L Steen,1 Amit V Khera,2 Christopher P Cannon1

1TIMI Study Group, Cardiovascular Division, 2Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA

Disclosure

Dr Cannon is a member of the advisory boards of and has received grant support from Alnylam, Bristol-Myers Squibb, Pfizer, and CSL Behring; has received grant support from Accumetrics, AstraZeneca, Essentialis, GlaxoSmithKline, Merck, Regeneron, Sanofi, and Takeda; and is a clinical advisor to Automated Medical Systems. All other authors have reported that they have no relationships relevant to the contents of this paper.

Abstract: Despite major advances in cardiovascular care in recent decades, atherosclerotic cardiovascular disease remains the leading cause of morbidity and mortality worldwide. Statins have been shown to reduce cardiovascular events by 25%–40% in a dose-dependent fashion; yet additional therapies are needed to reduce vascular disease progression and acute thrombotic events. In addition to low-density lipoprotein cholesterol (LDL-C) reduction, other lipid risk factors, such as low high-density lipoprotein cholesterol (HDL-C), have created interest as therapeutic targets to lower cardiovascular risk. However, the absence of compelling data for incremental benefit of non-LDL-centric therapies in the statin era has limited their clinical use. A novel class of compounds, cholesteryl ester transfer protein (CETP) inhibitors, has demonstrated many potentially beneficial lipid-modifying effects. While in vitro and animal data for CETP inhibition have been encouraging, the initial enthusiasm for the class has been tempered by the failure of two CETP inhibitors (torcetrapib and dalcetrapib) in Phase III trials to reduce cardiovascular outcomes. Anacetrapib, a compound that causes near-complete CETP inhibition, has among its effects, robust reductions in LDL-C and lipoprotein(a) as well as dramatic increases in HDL-C. The ability of anacetrapib to reduce coronary disease events is being tested in the Randomized EValuation of the Effects of Anacetrapib Through Lipid-modification (REVEAL) trial (NCT01252953).

Keywords: anacetrapib, cholesteryl ester transfer protein, cholesteryl ester transfer protein inhibitor, atherosclerosis

  • Niacin, which augments HDL-C by 20%–25%, recently failed to lower atherosclerotic events in both the Atherothrombosis Intervention in Metabolic Syndrome with Low HDL/High Triglycerides and Impact on Global Health Outcomes (AIM-HIGH)6 and Treatment of HDL to Reduce the Incidence of Vascular Events (HPS2-THRIVE) trials.7,8
  • Lp(a) lowering has not yet been evaluated in randomized controlled trials, but observational and genetic (including Mendelian randomization) analyses have demonstrated an independent association of increased Lp(a) levels with increased CV events, suggesting Lp(a) lowering may confer benefit.9
  • surprising failure of the first two CETP inhibitors (torcetrapib and dalcetrapib) in Phase III outcomes trials has somewhat tempered this initial excitement and forced a re-evaluation of the complex effects of CETP inhibition on lipid metabolism and vascular biology.
  • Anacetrapib results in near-complete CETP inhibition with more pronounced lipid effects than its predecessors and is currently in a Phase III study for secondary prevention of coronary events. If successful it is likely that anacetrapib will also be considered for statin-intolerant patients and for primary prevention in patients who require LDL-C lowering beyond statin monotherapy
  • Human CETP is a 476-residue, 74 kDa, hydrophobic glycoprotein primarily secreted by the liver and adipose tissue.13 CETP was first cloned in 1987.14 The structure of CETP allows formation of a tunnel with the opening on one end interacting with HDL and the other with a very low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), or LDL particle. The hydrophobic central cavity of this tunnel is large enough to allow transfer of neutral lipids (eg, cholesteryl esters [CEs], triglycerides [TGs]) from donor to acceptor particles, but conformational changes may occur to accommodate larger lipoprotein particles. The concave surface of CETP matches the curvature of the HDL particles to which it is primarily bound in the bloodstream.15,16
  • The overall effect of CETP is a net transfer of CE from HDL to these apolipoprotein B (apoB)-containing particles and TG to HDL and LDL
  • An important driver of the transfer of CE from HDL to apoB-containing particles is the production of CE from free cholesterol within HDL by lecithin acetyltransferase (LCAT).17

    The role of CETP in reverse cholesterol transport.

    Beginning in the peripheral tissues, free cholesterol is predominantly taken up by small “immature” HDL particles (eg, pre-β-HDL) via the ABCA1 transporter. Alternatively, it can be taken up by larger “mature” HDL particles (eg, HDL2) via the ABCG1 transporter. LCAT converts free cholesterol into cholesteryl ester, which is then shuttled to apoB-lipoproteins (eg, LDL, VLDL) in exchange for triglycerides. Only a minority of cholesteryl ester is delivered directly to the liver by HDL via the SR-BI; the majority is delivered indirectly to the liver by apoB-lipoproteins via the LDL recepter.

    Abbreviations: CETP, cholesteryl ester transfer protein; HDL, high-density lipoprotein; ABCA1, ATP-binding cassette transporter A1; ABCG1, ATP-binding cassette transporter G1; LCAT, lecithin acetyltransferase; apoB, apolipoprotein B; LDL, low-density lipoprotein; VLDL, very low density lipoprotein; SR-BI, scavenger receptor-BI; FC, free cholesterol; CE, cholesteryl ester.

  • One of the interesting questions in CETP deficiency is whether the HDL particles produced by potent CETP inhibition are functional. Regardless of whether reverse cholesterol transport is increased, the initial steps of cholesterol efflux from foam cells may be one of the key anti-atherogenic functions of HDL.5
  • This increased efflux is related to the very high content of LCAT and apoE in these large HDL particles, presumably driving net cholesterol efflux by promoting cholesterol esterification.36
  • effect of CETP deficiency on liver uptake of cholesteryl ester, an important downstream step in a reverse cholesterol transport. These studies suggest that there may be increased CE uptake via SR-BI as well as through a high affinity of large apoE-rich HDL for LDL receptors.20
  • meta-analysis established that three CETP genotypes were not only associated with decreased CETP activity and increased HDL but also with a lower risk of myocardial infarction (MI). For example, for each allele inherited, individuals with the TaqIB polymorphism had lower mean CETP activity (−8.6%), higher mean HDL-C (4.5%), higher mean apoA-I (2.4%), and an odds ratio for coronary disease of 0.95 (95% confidence intervals [CI], 0.92, 0.99). Similar associations were found for the other two CETP genotypes.40
  • Subsequent studies have confirmed that genetic variants leading to reduced CETP activity and its corresponding anti-atherogenic lipid profile are associated with reduced atherosclerotic outcomes.41–43
  • In ILLUSTRATE, an inverse association between HDL-C achieved and the primary endpoint of atheroma volume (r = −0.17, P , 0.001) was found. In addition, the highest quartile of HDL-C achieved (.86 mg/dL) demonstrated atheroma regression, suggesting that there may be a “threshold effect” to HDL-C elevation.68
  • Other CETP inhibitors:

Dalcetrapib
was developed by Hoffmann–La Roche until May 2012. It did not raise blood pressure and did raise HDL, but it showed no clinically meaningful efficacy.

Evacetrapib 

is under development by Eli Lilly & Company.
Torcetrapib
was developed by Pfizer until December 2006 but caused unacceptable increases in blood pressure and had net cardiovascular detriment.
Anacetrapib At the 16th International Symposium on Drugs Affecting Lipid Metabolism (New York, Oct 4-7, 2007), Merck reported on a Phase IIb study. The eight week study reported dosage correlated reduction in LDL-C and increases in HDL-C levels with no corresponding increases in blood pressure in any cohort. The increase in HDL was particularly significant, averaging 44 percent, 86 percent, 139 percent and 133 percent at doses of 10 mg, 40 mg, 150 mg and 300 mg. Merck performed a dose-ranging study of anacetrapib, with the results presented in 2009.

Anacetrapib 

Anacetrapib is a 3,5-bis-trifluoromethyl-benzene derivative with similar binding properties to CETP as torcetrapib. The compound was developed when it was found that a substitution modification of the oxazolidinone ring increased its potency for CETP inhibition in a transgenic mouse model.85 In terms of its pharmacokinetics and pharmacodynamics, anacetrapib is rapidly absorbed with a time-to-peak plasma concentration of about 4 hours. The oral bioavailability of anacetrapib is poor, with only about 20% being absorbed; however at this exposure, LDL-C is reduced up to 40% and HDL-C increased up to 140%. It is recommended that anacetrapib be taken with food (ie, low-fat diet) to increase drug exposure (and efficacy) as well as compliance.86

Anacetrapib is highly protein bound (eg, CETP) in the plasma (.99.5%). It is cleared by oxidative metabolism via Cytochrome P450 3A4 (CYP3A4) with excretion of the metabolites via the biliary/fecal route. Only a trace amount is eliminated by urinary excretion.87 Importantly, while anacetrapib is a sensitive CYP3A4 substrate, anacetrapib neither inhibits nor induces CYP3A4 activity. No meaningful interactions have been found between anacetrapib and simvastatin, digoxin, or warfarin.86 Anacetrapib in part to its redistribution to adipose tissue has a long terminal half-life.88

In terms of safety endpoints, anacetrapib demonstrated no increase in side effects (including myalgia), drug-related adverse effects, adverse events leading to drug discontinuation, or other important safety endpoints, such as BP, electrolyte, aldosterone, creatinine kinase, or transaminase levels. A very small increase in C-reactive protein of undetermined significance was seen with anacetrapib, which notably was also reported with torcetrapib and dalcetrapib in their Phase III studies. It is unknown whether this is a class effect as the small sample size in the evacetrapib Phase II study limits evaluation of small C-reactive protein changes.

It is expected that the REVEAL (the Phase III) population will also have lower starting LDL-C levels, both because statin-intolerant subjects will not be enrolled and because of more stringent lipid entry criteria. The final major difference is that the primary endpoint in REVEAL is focused on coronary events, while ACCELERATE has a broader primary endpoint. A broader primary endpoint along with a slightly higher risk population will allow for a shorter follow-up duration and much smaller sample size in ACCELERATE.

Conclusion

  • CETP remains a valid target and that the lipid changes resulting from its inhibition may be protective. The biology of CETP inhibition is complex, and questions remain regarding which lipid changes (eg, reductions in LDL and Lp(a), increases in HDL) are most likely to be important and whether there are still unknown effects that may negate any overall clinical benefit.
  • if potent CETP inhibition is found to be beneficial, it is still unclear whether this effect will be homogeneous or vary based on individual metabolism.
  • anacetrapib-induced HDL (especially the apoE-rich HDL2 particles) may have an enhanced ability for reverse cholesterol transport without any known adverse effects. Importantly, if a threshold effect for HDL-C augmentation exists, the vast majority of patients taking anacetrapib would be expected to cross it.
  • Despite a difficult beginning for the class of CETP inhibitors, anacetrapib and evacetrapib hold promise as future therapies for patients with atherosclerosis
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28. Plump AS, Masucci–Magoulas L, Bruce C, Bisgaier CL, Breslow JL, Tall AR. Increased atherosclerosis in ApoE and LDL receptor gene knock-out mice as a result of human cholesteryl ester transfer protein transgene expression. Arterioscler Thromb Vasc Biol. 1999;19(4):1105–1110.

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31. Schwartz CC, VandenBroek JM, Cooper PS. Lipoprotein cholesteryl ester production, transfer, and output in vivo in humans. J Lipid Res. 2004;45(9):1594–1607.

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70. Barter PJ, Rye KA, Tardif JC, et al. Effect of torcetrapib on glucose, insulin, and hemoglobin A1c in subjects in the investigation of lipid level management to understand its impact in atherosclerotic events (ILLUMINATE) trial. Circulation. 2011;124(5):555–562.

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75. Niesor EJ, Magg C, Ogawa N, et al. Modulating cholesteryl ester transfer protein activity maintains efficient pre-beta-HDL formation and increases reverse cholesterol transport. J Lipid Res. 2010;51(12): 3443–3454.

76. Derks M, Anzures–Cabrera J, Turnbull L, Phelan M. Safety, tolerability and pharmacokinetics of dalcetrapib following single and multiple ascending doses in healthy subjects: A randomized, double-blind, placebo-controlled, phase I study. Clin Drug Investig. 2011;31(5):325–335.

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83. Nicholls SJ, Brewer HB, Kastelein JJ et al. Effects of the CETP Inhibitor evacetrapib administered as monotherpay or in combination with statins on HDL and LDL cholesterol: a randomized controlled trial. JAMA. 2011;306(19):2099-2109.

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86. Gutstein DE, Krishna R, Johns D, et al. Anacetrapib, a novel CETP inhibitor: Pursuing a new approach to cardiovascular risk reduction. Clin Pharmacol Ther. 2012;91(1):109–122.

87. Kumar S, Tan EY, Hartmann G, et al. Metabolism and excretion of anacetrapib, a novel inhibitor of the cholesteryl ester transfer protein, in humans. Drug Metab Dispos. 2010;38(3):474–483.

88. Dansky HM, Bloomfield D, Gibbons P, et al. Efficacy and safety after cessation of treatment with the cholesteryl ester transfer protein inhibitor anacetrapib (MK-0859) in patients with primary hypercholesterolemia or mixed hyperlipidemia. Am Heart J. 2011;162(4): 708–716.

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90. Krishna R, Anderson MS, Bergman AJ, et al. Effect of the cholesteryl ester transfer protein inhibitor, anacetrapib, on lipoproteins in patients with dyslipidaemia and on 24-h ambulatory blood pressure in healthy individuals: Two double-blind, randomised placebo-controlled phase I studies. Lancet. 2007;370(9603):1907–1914.

91. Krauss RM, Wojnooski K, Orr J, et al. Changes in lipoprotein subfrac­tion concentration and composition in healthy individuals treated with the CETP inhibitor anacetrapib. J Lipid Res. 2012;53(3): 540–547.

92. Krishna R, Bergman AJ, Green M, Dockendorf MF, Wagner JA, Dykstra K. Model-based development of anacetrapib, a novel cholesteryl ester transfer protein inhibitor. AAPS J. 2011;13(2): 179–190.

93. Yvan–Charvet L, Kling J, Pagler T, et al. Cholesterol efflux potential and antiinflammatory properties of high-density lipoprotein after treatment with niacin or anacetrapib. Arterioscler Thromb Vasc Biol. 2010;30(7):1430–1438.

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98. Brinton E, Liu S, Stepanavage M, et al. Lipid-modifying effects of anacetrapib in patients with lower versus higher baseline levels of HDL-C, LDL-C, and TG: Pre-specified subgroup analyses of the DEFINE (determining the efficacy and tolerability of CETP INhibition with AnacEtrapib) trial. Circulation. 2011;124:A9649.

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Treatment for Infective Endocarditis

Curator: Larry H Bernstein, MD, FACP

UPDATED on 3/4/2019

WATCH VIDEO

https://consultqd.clevelandclinic.org/tricuspid-valve-reconstruction-for-infective-endocarditis-operative-highlights-video/amp/?__twitter_impression=true

Tricuspid Valve Reconstruction for Infective Endocarditis: Operative Highlights (Video)

There are no easy solutions for acute infective tricuspid valve endocarditis in IV drug users, as the risk of prosthetic endocarditis in this population is high. Complete valve resection without replacement is feasible but leads to progressive right-sided heart failure. Reconstruction of the tricuspid valve with autologous pericardium is an alternative option, as demonstrated in the video case study below.

A 29-year-old female drug abuser with fever, hemoptysis and MRSA bacteremia was started on IV antibiotics. She looked frail and had prominent jugular venous pressure as well as 95 percent saturation on 2 liters of nasal cannula oxygen. She was not on inotropes and had a pulmonary artery pressure of 40/20 mmHg with a good cardiac index. Chest CT showed a large left pleural effusion with associated atelectasis of the left lung. The right lung had manifestations of septic emboli and a smaller pleural effusion.

A Cleveland Clinic surgical team led by cardiothoracic surgeon Faisal Bakaeen, MD, proceeded to excise the patient’s extensive infected and devitalized tissue around the tricuspid valve, leaving only a portion of the anterior leaflet to serve as a reference for reconstruction using autologous pericardium. Dr. Bakaeen walks us through the essential surgical steps — and their underlying rationale — in the narrated operative video below.

SOURCE

https://consultqd.clevelandclinic.org/tricuspid-valve-reconstruction-for-infective-endocarditis-operative-highlights-video/amp/?__twitter_impression=true

 

An article that appeared in NEJM compares early surgery versus conventional treatment for infective endocarditis.
Early Surgery versus Conventional Treatment for Infective Endocarditis
Duk-Hyun Kang, Yong-Jin Kim, Sung-Han Kim, Byung Joo Sun, et al.

N Engl J Med June 28, 2012; 366:2466-2473. http://doi.org/10.1056/NEJMoa1112843

Background and Purpose: While current guidelines advocate surgical management for complicated left-sided infective endocarditis and early surgery for patients with infective endocarditis and congestive heart failure, the indications for surgical intervention to prevent systemic embolism remain unclear. Surgery is favored by experience with complete excision of infected tissue and valve repair, and low operative mortality, but it does not remove concerns about residual active infection, which results in two sets of guidelines, the 2006 ACC-AHA for class IIa indication only for recurrent emboli and persistent vegetation, and the 2009 ESC guidelines for class IIb indication for very large, isolated vegetations. The Early Surgery versus Conventional Treatment in Infective Endocarditis (EASE) trial was conducted to determine whether early surgical intervention woulddecrease rate of death or embolic events.

Patient Enrollment: The study enrolled 76 consecutive patients, 18 years of age or older, with left-sided, native-valve infective endocarditis and a high risk of embolism. For all patients with suspected infective endocarditis, blood cultures were obtained and transthoracic echocardiography was performed within 24 hours after hospitalization. Patients were only eligible for enrollment if they had received a diagnosis of definite infective endocarditis and had severe mitral valve or aortic valve disease and vegetation with a diameter greater than 10 mm. Patients were excluded if they had moderate-to-severe congestive heart failure, infective endocarditis complicated by heart block, annular or aortic abscess, destructive penetrating lesions requiring urgent surgery, or fungal endocarditis, or were over 80 years age, or coexisting major embolic stroke with a risk of hemorrhagic transformation at the time of diagnosis, and a serious coexisting condition. Patients were also excluded if they had infective endocarditis involving a prosthetic valve, right-sided vegetations, or small vegetations (diameter, ≤10 mm) or had been referred from another hospital more than 7 days after the diagnosis of infective endocarditis.
The protocol specified that patients who were assigned to the early-surgery group should undergo surgery within 48 hours after randomization. Patients assigned to the conventional-treatment group were treated according to the AHA guidelines, and surgery was performed only if complications requiring urgent surgery developed during medical treatment or if symptoms persisted after the completion of antibiotic therapy. Details of the study procedures are provided in the Supplementary Appendix, available at NEJM.org.

Study End Points: The primary end point was a composite of in-hospital death or clinical embolic events that occurred within 6 weeks after randomization. An embolic event was defined as a systemic embolism fulfilling both prespecified criteria: the acute onset of clinical symptoms or signs of embolism and the occurrence of new lesions, as confirmed by follow-up imaging studies. Prespecified secondary end points, at 6 months of follow-up, included death from any cause, embolic events, recurrence of infective endocarditis, and repeat hospitalization due to the development of congestive heart failure.

Clinical and Echocardiographic Characteristics of the Patients at Baseline, According to Treatment Group:

The mean age of the patients was 47 years, and 67% were men. The mitral valve was involved in 45 patients, the aortic valve in 22, and both valves in 9. Severe mitral regurgitation was observed in 45 patients, severe aortic regurgitation in 23, severe aortic stenosis in 3, severe mitral regurgitation and stenosis in 1, and both severe mitral regurgitation and aortic regurgitation in 4. The median diameter of vegetation was 12 mm (interquartile range, 11 to 17). All patients met the Duke criteria for definite endocarditis; the most common pathogens in both groups were viridans streptococci (in 30% of all patients), other streptococci (in 30%), and Staphylococcus aureus (in 11%). Characteristics of Antibiotic Therapy, According to Treatment Group: There were no significant between-group differences in terms of control of the underlying infection, the antibiotic regimen used, or the duration of antibiotic therapy.

Surgical Procedures: All patients in the early-surgery group underwent valve surgery within 48 hours after randomization; the median time between randomization and surgery was 24 hours (interquartile range, 7 to 45). Of the 22 patients with involvement of the mitral valve, 8 patients underwent mitral-valve repair and 14 underwent mitral-valve replacement with a mechanical valve. Of the 15 patients with involvement of the aortic valve or both the mitral and aortic valves, 14 underwent mechanical-valve replacement and 1 underwent valve replacement with a biologic prosthesis. Concomitant coronary-artery bypass grafting at the time of valve surgery was performed in 2 patients (5%).

Conventional Therapy: Of the 39 patients assigned to the conventional-treatment group, 30 (77%) underwent surgery during the initial hospitalization (27 patients) or during follow-up (3). The surgical procedures included 11 mitral-valve repairs, 6 mitral-valve replacements (with 5 patients receiving a mechanical valve and 1 a biologic prosthesis), 11 aortic-valve replacements (with 9 patients receiving a mechanical valve and 2 a biologic prosthesis), and 2 combined aortic-valve replacements (with 1 patient receiving a mechanical valve and 1 a biologic prosthesis) and mitral-valve repairs. In 8 patients (21%), indications for urgent surgery developed during hospitalization (median time to surgery after randomization, 6.5 days [interquartile range, 6 to 10]). Elective surgery was performed in an additional 22 patients owing to symptoms or left ventricular dysfunction more than 2 weeks after randomization. Surgical results are shown in the Supplementary Appendix.

Primary End Point: The primary end point of in-hospital death or embolic events within the first 6 weeks after randomization occurred in one patient (3%) in the early-surgery group, as compared with nine (23%) in the conventional-treatment group (hazard ratio, 0.10; 95% confidence interval [CI], 0.01 to 0.82; P=0.03). In the early-surgery group, one patient died in the hospital and no patients had embolic events; in the conventional-treatment group, one patient died in the hospital and eight patients had embolic events (Table 3TABLE 3).
http://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/2012/nejm_2012.366.issue-26/nejmoa1112843/production/images/small/nejmoa1112843_t3.gif

At 6 weeks after randomization, the rate of embolism was 0% in the early-surgery group, as compared with 21% in the conventional-treatment group (P=0.005). No patient in either group had an embolic event or was hospitalized for congestive heart failure during follow-up. Recurrence of infective endocarditis within 6 months after discharge was not observed in any patient in the early-surgery group but was reported in 1 patient in the conventional-treatment group. Among the 11 patients (28%) in the conventional-treatment group who were treated medically and discharged without undergoing surgery, 1 (3%) died suddenly, 7 (18%) had symptoms related to severe valve disease or recurrence of infective endocarditis (3 of whom underwent surgery during follow-up), and 3 (8%) had no symptoms or embolic events (Table S3 in the Supplementary Appendix).
There was no significant difference between the early-surgery and conventional-treatment groups in all-cause mortality at 6 months (3% and 5%, respectively; hazard ratio, 0.51; 95% CI, 0.05 to 5.66; P=0.59) (Figure 2AFIGURE 2).
http://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/2012/nejm_2012.366.issue-26/nejmoa1112843/production/images/small/nejmoa1112843_f2.gif
Kaplan–Meier Curves for the Cumulative Probabilities of Death and of the Composite End Point at 6 Months, According to Treatment Group.

At 6 months, the rate of the composite of death from any cause, embolic events, recurrence of infective endocarditis, or repeat hospitalization due to the development of congestive heart failure was 3% in the early-surgery group, as compared with 28% in the conventional-treatment group (hazard ratio, 0.08; 95% CI, 0.01 to 0.65; P=0.02). The estimated actuarial rate of end points was significantly lower in the early-surgery group than in the conventional-treatment group (P=0.009 by the log-rank test) (Figure 2B).

Conclusion: Early surgery performed within 48 hours after diagnosis reduced the composite primary end point of death from any cause or embolic events by effectively reducing the risk of systemic embolism. Moreover, these improvements in clinical outcomes were achieved without an increase in operative mortality or recurrence of infective endocarditis.

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

The essence of the message is summarized by Larry Bernstein, MD, FACP, as follows:

[1] we employ a massively parallel reporter assay (MPRA) to measure the transcriptional levels induced by 145bp DNA segments centered on evolutionarily-conserved regulatory motif instances and found in enhancer chromatin states
[2] We find statistically robust evidence that (1) scrambling, removing, or disrupting the predicted activator motifs abolishes enhancer function, while silent or motif-improving changes maintain enhancer activity; (2) evolutionary conservation, nucleosome exclusion, binding of other factors, and strength of the motif match are all associated with wild-type enhancer activity; (3) scrambling repressor motifs leads to aberrant reporter expression in cell lines where the enhancers are usually not active.
[3] Our results suggest a general strategy for deciphering cis-regulatory elements by systematic large-scale experimental manipulation, and provide quantitative enhancer activity measurements across thousands of constructs that can be mined to generate and test predictive models of gene expression.

Manolis Kellis and co-authors from the Massachusetts Institute of Technology and the Broad Institute describe a massively parallel reporter assay that they used to systematically study regulatory motifs falling within thousands of predicted enhancer sequences in the human genome. Using this assay, they examined 2,104 potential enhancers in two human cell lines, along with another 3,314 engineered enhancer variants. “Our results suggest a general strategy for deciphering cis-regulatory elements by systematic large-scale experimental manipulation,” they write, “and provide quantitative enhancer activity measurements across thousands of constructs that can be mined to generate and test predictive models of gene expression.”

SOURCE:

http://www.genomeweb.com//node/1206571?hq_e=el&hq_m=1536519&hq_l=4&hq_v=e1df6f3681

Systematic dissection of regulatory motifs in 2,000 predicted human enhancers using a massively parallel reporter assay

  1. Pouya Kheradpour1,
  2. Jason Ernst1,
  3. Alexandre Melnikov2,
  4. Peter Rogov2,
  5. Li Wang2,
  6. Xiaolan Zhang2,
  7. Jessica Alston2,
  8. Tarjei S Mikkelsen2 and
  9. Manolis Kellis1,3

+Author Affiliations


  1. 1 MIT;

  2. 2 Broad Institute
  1. * Corresponding author; email: manoli@mit.edu

Abstract

Genome-wide chromatin maps have permitted the systematic mapping of putative regulatory elements across multiple human cell types, revealing tens of thousands of candidate distal enhancer regions. However, until recently, their experimental dissection by directed regulatory motif disruption has remained unfeasible at the genome scale, due to the technological lag in large-scale DNA synthesis. Here, we employ a massively parallel reporter assay (MPRA) to measure the transcriptional levels induced by 145bp DNA segments centered on evolutionarily-conserved regulatory motif instances and found in enhancer chromatin states. We select five predicted activators (HNF1, HNF4, FOXA, GATA, NFE2L2) and two predicted repressors (GFI1, ZFP161) and measure reporter expression in erythroleukemia (K562) and liver carcinoma (HepG2) cell lines. We test 2,104 wild-type sequences and an additional 3,314 engineered enhancer variants containing targeted motif disruptions, each using 10 barcode tags in two cell lines and 2 replicates. The resulting data strongly confirm the enhancer activity and cell type specificity of enhancer chromatin states, the ability of 145bp segments to recapitulate both, the necessary role of regulatory motifs in enhancer function, and the complementary roles of activator and repressor motifs. We find statistically robust evidence that (1) scrambling, removing, or disrupting the predicted activator motifs abolishes enhancer function, while silent or motif-improving changes maintain enhancer activity; (2) evolutionary conservation, nucleosome exclusion, binding of other factors, and strength of the motif match are all associated with wild-type enhancer activity; (3) scrambling repressor motifs leads to aberrant reporter expression in cell lines where the enhancers are usually not active. Our results suggest a general strategy for deciphering cis-regulatory elements by systematic large-scale experimental manipulation, and provide quantitative enhancer activity measurements across thousands of constructs that can be mined to generate and test predictive models of gene expression.

  • Received June 26, 2012.
  • Accepted March 14, 2013.

This manuscript is Open Access.

This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), as described at http://creativecommons.org/licenses/by-nc/3.0/.

SOURCE:

http://genome.cshlp.org/content/early/2013/03/19/gr.144899.112.abstract

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Protein-folding Simulation: Stanford’s Framework for Testing and Predicting Evolutionary Outcomes in Living Organisms – Work by Marcus Feldman

Reporter: Aviva Lev-Ari, PhD, RN

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UPDATED 9/16/2013

VIDEO CLIPS
Enzymes That Are Not Proteins: The Discovery of Ribozymes
Listen to past HHMI President Dr. Thomas Cech discussing his Nobel Prize-winning discovery of RNA’s catalytic properties.

http://www.hhmi.org/biointeractive/enzymes-are-not-proteins-discovery-ribozymes

Stanford Report, March 15, 2013

Long-term evolution is ‘surprisingly predictable,’ Stanford experiment shows

A protein-folding simulation shows that the debated theory of long-term evolution is not only possible, but that the outcomes are predictable. The Stanford experiment provides a framework for testing evolutionary outcomes in living organisms.

BY BJORN CAREY

L.A. CiceroVisiting scholar Mike Palmer left, and Professor Marcus FeldmanDr. Michael Palmer, left, and Professor Marcus Feldman, with co-author Arnav Moudgil (not pictured), found that the long-term evolutionary dynamics were surprisingly predictable in a model of protein folding and binding.

Two birds are vying for food. One bird’s beak is shaped, by virtue of a random mutation, such that it’s slightly more adept at cracking seeds. This sets the bird on the road toward acquiring more food, a better chance of scoring a mate and, most important, passing on its genetic endowment.

This individual’s success is an example of short-term evolution, the widely accepted Darwinian process of natural selection by which individual organisms that have better adapted to their surroundings prevail.

In recent years, however, some scientists have argued that natural selection occurs not just at the individual organism level, but also between lineages over the course of many generations. In a new study, Stanford biologists have demonstrated that not only is this long-term evolution possible, but that long-term evolutionary outcomes can be surprisingly predictable.

The group set up a computer simulation in which 128 lineages of proteins continuously folded into new shapes, competing to bind with other molecules, called ligands, in each new configuration. The better each protein could attach itself to the ligands, the more ligands it would scoop up, and the higher its fitness – that is, its average number of “offspring” – would be. The simulation was run for 10,000 generations.

Although the chaos of 128 lineages – a total of more than 16,000 individual proteins – mutating over thousands of generations might seem unpredictable, and that it would be nearly impossible for the same thing to happen twice, it’s actually the opposite.

“Even though things look complicated, the possible evolutionary trajectories are quite constrained,” said lead author Michael Palmer, a computational biologist at Stanford. “There are only a few viable mutations at any point, which makes the dynamics predictable and repeatable, even over the long term.”

The study, co-authored by Marcus Feldman, a biology professor at Stanford, and Stanford research biologist Arnav Moudgil, was recently published in the Journal of the Royal Society Interface.

In some experiments, the lineages that consistently came out on top in the long term were not initially the best adapted at binding to ligands. “The immediate fitness is not the only important thing,” Palmer said. “Yes, a lineage does have to survive in the short term. But just as important is how it is able to adapt to new and potentially variable environments over the longer term.”

A good example of this scenario is Darwin’s famous finches. It’s thought that individuals – perhaps just a single pair of birds – from a South American species ended up on the Galápagos Islands about 1 million years ago. Today their descendants have diversified into about 15 modern species. Some eat seeds, some eat insects, or flowers. Some eat ticks, or even drink the blood of other birds.

“If there was some catastrophe that removed one of those food sources, it might wipe out one or more of the 15 species, but the rest of the lineage – the descendants of that initial pair of birds – would persist,” Palmer said. “Now say there was a competing lineage that was great at cracking seeds, but unable to evolve to other diets due to some prior genetic constraint. The same catastrophe could wipe it out.”

The finding, and others like it, could represent a significant shift in viewpoint for biologists. For one thing, it means that in certain situations, scientists should look beyond the details at the level of the individual organism, as the evolutionary dynamics can be accurately understood as lineage selection.

It also has implications on a species’ genomic architecture, or how a genome is organized on the lineage level. While a lineage’s genome might primarily select for a particular set of traits in order for individuals to survive in the short term, in order to out-compete other lineages, it must also be able to adapt to new conditions over the long term.

“An individual can have a lucky mutation that produces an immediate adaptation,” said Palmer. “Or a lineage can have a lucky mutation that happens to position it to adapt to the range of environments it will experience over the next thousand generations. A single mutation can have a distinct short-term and long-term fitness.”

The authors believe that the work can be replicated in microorganisms, and are now hoping that microbiologists will apply the new metrics of selection in vitro.

“There is already some evidence in vitro that there is a lot of constraint on evolutionary trajectories,” Palmer said, “and we think we’ve come up with a good framework to quantify evolutionary predictability and long-term fitness.”

Media Contact

Michael Palmer, Biology: (415) 867-3653, mepalmer@charles.stanford.edu

Bjorn Carey, Stanford News Service: (650) 725-1944, bccarey@stanford.edu

SOURCE:

http://news.stanford.edu/news/2013/march/long-term-evolution-031513.html

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Predicting Drug Toxicity for Acute Cardiac Events

Reporter: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/?p=10679/Predicting Drug Toxicity for Acute Cardiac Events

Pharmaceuticals Dilemma

The pharmaceutical industry has, as the clinical diagnostics industry, consolidated, and seen new entries that are at some time merged into an established giant, needing resources to grow.  In the past, it was considered essential for a scientific commercial entity to invest at least 8 percent of budget to R&D.   However, the cost of manufacturing has gone down, but a large part of the budget outside of manufacture has to be taken up with, maybe a few exceptions, development, validation in clinical trials, and marketing.  This leaves the situation precarious without a basic research base, and has lead to consortia between academic centers, the federal governmant, and the industries.  I can’t venture into the role of Wall Street Investment and Venture Capital in the process of innovation, proprietary rights to discoveries, and viability.  A large problem they encounter really comes down to complexity of the biomedical reality, that keeps peeling off layers like an onion, exposing new problems to deal with.  As a result, we have seen repeated recalls of drugs that were blockbusters, over the last 2 decades.  To date, every “miracle” drug to manage sepsis and the several cardiac related drugs have  resulted in unexpected toxicities.
One of the leading causes of drug attrition during development is cardiac toxicity, which has a serious impact on cost and can impact getting new drugs to patients. Detecting cardiovascular safety issues earlier in the drug development program

  • would produce significant benefits for pharmaceutical companies and, ultimately, public health, but
    • the reduction of therapeutic toxicities will not be easy and depends on the
    • emergence of genomic-based personalized medicine.

Comprehensive cardiovascular and electrophysiology assessments are routinely conducted in vivo and in vitro early in the preclinical or lead optimization phases of drug development. For example,

  • the isolated perfused guinea pig heart preparation (classically called the Langendorff preparation)
  • can be used to screen a series of related new chemical entities (NCE)

in the lead optimization phase for preliminary information on the relative effects on contractility and rhythm.
Additionally, intact animal non-GLP studies—generally conducted in anesthetized, non-recovery models—are designed to assess

  • effects of NCEs on a range of acute hemodynamic and cardiac parameters such as
    • heart rate,
    • blood pressure,
    • electrocardiogram (ECG),
    • ventricular contractility,
    • vascular resistance,
    • cardiac output, etc.

These studies employ small numbers of animals, but may allow termination of research into NCEs with obvious cardiovascular side effects. These preparations also provide information on the involvement of the

  • autonomic nervous system in the cardiovascular responses of the NCE.

Such effects can be important determinants in the total cardiovascular response to an NCE, and this information cannot be obtained with any known in vitro method.
But what if there are dangers that are not predictable in the short term because of the time span under which the effects can be viewed? The effects themselves are a result of interactions between

  • the drug,
  • endothelial cell receptors,
  • and/or imbalance in oxidative stress promoters and suppressors,
  • and involve signaling pathways.

That is a difficult challenge that may only be realized

  • by rapidly advancing knowledge at the molecular cell level.

The ICH S7A and ICH S7B guidelines provide

  • guidance on important physiological systems and
  • assessment of pharmaceuticals on
    • ventricular repolarization and
    • proarrhythmic risk.

The guidelines were designed to protect patients from potential adverse effects of pharmaceuticals. Since these guidelines were issued in 2000 and 2005, respectively,

  • cardiac safety study designs have been realigned
  • to identify potential concerns prior to administering the first dose to humans.

It is now routine for all NCEs to be evaluated using an

  • in vitro Ikr assay such as the hERG voltage patch clamp assay to assess for
    • the potential for QT interval prolongation.

Systems have evolved to screen large numbers of compounds

  • using automated high-throughput patch clamp systems early in the lead
  • optimization/drug discovery phase.

This is a cost effective method for determining an initial go/no-go gate. Once a compound has progressed to

  • the development phase, it can once again be assessed with the hERG assay
  • utilizing the gold standard manual patch clamp assay.

If the NCE under investigation is a cardiovascular therapy, then

  • pharmacological characterization should occur
  • early in the lead development process.

In addition to the techniques just discussed,

  • a variety of “disease models” are available to help determine
    • whether the NCE will be efficacious in a clinical setting.

However sound the in vitro data used in screening and selection process (e.g., receptor-binding studies),

  • NCEs that have been shown to be active in at least one in vivo model (e.g,. salt-sensitive Dahl rat model)
  • have a higher likelihood of clinical success.

Once a lead is identified, it should still go through the generalized safety characterization discussed earlier.
The in vivo study designs for NCEs reaching the development phase to support the Investigational New Drug (IND) application (just prior to the first human dose) require acquisition of

  1. heart rate,
  2. blood pressure, and
  3. ECG data
    • using an appropriate species
    • at and above clinically relevant doses.

The trend in the industry for these regulatory-driven studies has been to

  • utilize animals surgically instrumented with telemetry devices that
  • can acquire the required parameters.

The advantage of using instrumented animals over anesthetized animals is that

  • data can be acquired from freely moving animals over greater periods of time
  • without anesthetic in the test system,
    • which has the potential to confound and perturb results interpretation.

Appropriate dose selection relative to those used in the clinic provides valuable information about

  • potential acute cardiac events and
  • how they may impact trial participants.

The obvious limitation here is that the method of observation is essentially

  • the same or less than that which is used in clinical practice,
  • relying mainly on classical physiology to detect
    • inherently deep seated processes.

But it is not the same scale of issue as for the patient emergently presenting to the ED. Despite enormous efforts to reduce the development of and the complications of acute ischemia related cardiac events,

the accurate diagnosis of the patient presenting to the emergency room is still, as always, reliant on

  • clinical history,
  • physical examination,
  • effective use of the laboratory, and
  • increasingly helpful imaging technology.

and age, sex, diet, and ability to carry out the activities of daily living before treatment and 6 months to a year after discharge are relevant.

The main issue that we have a consensus agreement that PLAQUE RUPTURE is not the only basis for a cardiac ischemic event. There will be more to say about this.
Animal studies
Telemetry-instrumented animals can be used as screening tools earlier in the drug selection phase. Colonies of animals that can be reused, following a suitable wash-out period,
provide an excellent resource for screening compounds to detect unwanted side effects. The use of these animals

  • coupled with
  • recent advances in software-analysis systems allow for rapid data turnaround,
    • enables scientists to quickly determine if there are any potentially unwanted signals.

If any effects are detected on, for example, blood pressure or QT interval, then the decision to

  • either shelve the drug or
  • conduct additional studies

can be made before advancing any further in the developmental phase.   While this is very good for observing large effects, is it really sufficient for avoidance of late phase failure?

Interestingly, the experience that has been acquired since the approval of the ICH guidelines

  • has allowed pharmaceutical companies to temper their response to finding a potentially unwanted signal.
  • Rather than permanently shelve libraries of compounds that, for example, were
  • found to be positive in the hERG assay—common practice when the 2005 guidelines came into being—
    • companies can now determine a risk potential based on knowledge gained with the intact animal studies.

Similarly, if changes in hemodynamic parameters are detected, there are follow-up experiments employing anesthetized or telemetry models that include additional measurements like

left ventricular pressure.
These experiments can be utilized to further assess their potential clinical impact
by examining effects on
myocardial contractility,
relaxation, and
conduction velocity.
These techniques primarily address acute effects: those following a single exposure.
Chronic effects—those seen with long-term administration of the NCE to an intact organism—are difficult to obtain in early development, but are routinely monitored during safety studies,
are conducted non-clinically during Phase 1 and 2 of the development process.

  • ECGs typically are collected to evaluate the chronic cardiac effects in non-rodent species during these studies. It is recommended that
    • JET (jacketed external telemetry) techniques, which permit the recording of ECG’s—
    • but not blood pressure—

be applied in freely moving animals. If chronic effects are discovered,

  • follow-up experiments can be conducted with any of the techniques mentioned in this article.

As the focus on cardiac safety has matured over the last 10 years, the Safety Pharmacology Society has led efforts to establish an approach

  • to determine best practices for conducting key preclinical cardiovascular assessments in drug development.
  •  to provide sensitive preclinical assays that can detect high-probability safety concerns.

Parallel efforts have been made to more accurately assess the translation of preclinical cardiovascular data into

  • clinical outcomes and
  • to encourage collaborations
    • between preclinical and clinical scientists involved in cardiac safety assessment.

This has been conducted under the umbrella of the International Life Science Institute–Health and Environmental Services Institute (ILSI-HESI) consortium, which has bought together

  • industrial,
  • academic, and
  • government scientists
    • to discuss and determine what steps are necessary
    • to establish an integrated cardiovascular safety assessment program.

The goal is to provide better ways of predicting potential adverse events, allowing for earlier detection of cardiovascular safety issues and reducing the number of clinical trial failures.
http://www.dddmag.com/articles/2012/08/predicting-potential-cardiac-events?et_cid=2816494&et_rid=45527476&linkid=http%3a%2f%2fwww.dddmag.com%2farticles%2f2012%2f08%2fpredicting-potential-cardiac-events.

A recent poster presentation I think makes a good statement of advances that should move us forward:

http://www.biotechniques.com/multimedia/archive/00178/BTN_0311-March_Post_178205a.pdf

Another possibility is genetic testing to determine the likelihood of stroke, for example Corus CAD is

  • a shoebox-size kit that uses a simple blood draw to measure the RNA levels of 23 genes.
  •  it creates an algorrhytm-based score that determines the likelihood that a patient has obstructive coronary artery disease.

http://pharmaceuticalintelligence.com/2012/08/14/obstructive-coronary-artery-disease-diagnosed-by-rna-levels-of-23-genes-cardiodx-heart-disease-test-wins-medicare-coverage/
“By providing Medicare beneficiaries access to Corus CAD, this coverage decision enables patients to avoid unnecessary procedures and risks associated with cardiac imaging and elective invasive angiography, while helping payers address an area of significant healthcare spending,” CardioDx President and CEO David Levison said in a press release.
This discussion will be followed with a discussion of the evaluation of the patient acutely presenting with symptoms and signs that are suggestive of either acute pulmonary or cardiac disease, or both, that may be suggestive of a non ST elevation AMI. It becomes more difficult if ST depression or T-wave inversion is not detected.
Related articles
Obstructive Coronary Artery Disease diagnosed by RNA levels of 23 genes – CardioDx, a Pioneer in the Field of Cardiovascular Genomic Diagnostics
http://pharmaceuticalintelligence.com/2012/08/14/obstructive-coronary-artery-disease-diagnosed-by-rna-levels-of-23-genes-cardiodx-heart-disease-test-wins-medicare-coverage/

English: QT interval corrected by heart rate.

English: QT interval corrected by heart rate. (Photo credit: Wikipedia)

Schematic diagram of normal sinus rhythm for a...

Schematic diagram of normal sinus rhythm for a human heart as seen on ECG (with English labels). (Photo credit: Wikipedia)

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Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013

 

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

 

348 articles that appeared in AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013 were classified by the curators of this article into the following TEN categories. The first 9, represent DIAGNOSES of cardiovascular diseases, the last, deals with Pharmacogenomics.

The Cardiovascular Diagnoses that were covered in the period of 3/2010 – 3/2013, include the following:

  • Preventative Cardiology
  • MicroRNA in Serum as Bimarker for Cardiovascular Pathologies: acute myocardial infarction, viral myocarditis, diastolic dysfunction, and acute heart failure
  • Genetic Determinants of Potassium Sensitivity and Hypertension
  • Heart and Aging Research in Genomic Epidemiology: 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients
  • Genetics of CVD and Hyperlipidemia, Hyper Cholesterolemia, Metabolic Syndrome
  • Genomics and Valvular Disease
  • Pharmacogenomics

Introductions

Larry H. Bernstein, MD, FCAP

 

The curation of this large amount of material in 10 categories begins with a first chapter on preventative cardiology, which has had much public attention for the last decade.  Much of the concern with preventive cardiology has emphasized diet and exercise.  There is much to be said about this in articles not yet written.  However, there are several decades of research on the amino acid composition of foods, and the essential fatty acids, that indicates an essential balance between proinflammatory and antiinflammatory fatty acids in polyunsaturated fatty acids, and of the harmful effects of saturated fats.  There is also much to be said of essential amino acids, and in particular, those essential for methylation processes, and sulfur metabolism.

The next eight chapters are all concerned with genomics in cardiovascular disease.  This is in no small part a follow up on the completion of the genetic code in 2003, a seminal event.  Let us look at these in clusters.

[1]   microRNA in serum is now considered for a biomarker for cardiovascular disease.  It can be measured at very low levels, but we don’t yet know where it fits.   It might be more revealing once we understand the adaptive mechanism in development of congestive heart failure, renal hypertension, and post-genomic events.

[2]  It appears to me that potassium sensitivity and hypertension approached from the genomic side is more complicate.  Why is that?   The kidney excretes a sodium load and in metabolic acidosis, the serum potassium rises with a metabolic acidemia that can’t be compensated by the respiratory loss of CO2 through the carbonic anhydrase mechanism.

[3]  Heart and aging research is a rich area for work on the long term post-genomic changes, and it involves a large population base.

[4][5]  The genomics of cardiac dysrrhytmias and cardiomyopathies will open new doors into our understanding of the mechanisms of these diseases, and perhaps find therapeutic targets.  There has been a large volume of work on lipid synthesis, the role of the liver in generating apolipoproteins, and this has new answers on the way.  The most important feature, not readily accepted is the measurement of particles, which has now been done by a monoclonal antibody.  Metabolic syndrome brings together adipose tissue metabolism, endocrine and changes in CRP and IL-1.

[6]   Vascular pathologies and coagulation, hyperviscosity has had an enormous increase in intensity of research.  The concept of plaque rupture to account for all AMIs is being modified, and the high sensitivity cardio-specific troponins have become the most widely use test.

[7]  The genomics of valvular disease fits with the increased surgical procedures for valvular disease related to atheroschlerosis and advent of minimally invasive surgical procedures for the reapir and replacement of valves, procedure called TAVR vs. Openhealrt surgery for valve replacement.

[8]  Inherited cardiovascular disease is an older family of disorders, going back to Victor McKusik, and also the “Blue Baby” operation, both at Johns Hopkins.

[9] Pharmacogenomics is a vary active field of investigation and has uncovered inter-individual differences in handling Warfarin as a starter.

 

 

Preventative Cardiology

 

Methods in Genetics and Clinical Interpretation Randomized Trial of Personal Genomics for Preventive Cardiology Design and Challenges

Joshua W. Knowles, MD, PhD, Themistocles L. Assimes, MD, PhD, Michaela Kiernan, PhD, Aleksandra Pavlovic, BS, Benjamin A. Goldstein, PhD, Veronica Yank, MD, Michael V. McConnell, MD, Devin Absher, PhD, Carlos Bustamante, PhD, Euan A. Ashley, MD, DPhil and John P.A. Ioannidis, MD, DSc

Author Affiliations

From the Division of Cardiovascular Medicine (J.W.K., T.L.A., A.P., M.V.M., E.A.A.), Stanford Prevention Research Center (M.K., V.Y., J.P.A.I.), Division of General Medical Disciplines (V.Y.), Department of Genetics (C.B.), Department of Health Research and Policy (J.P.A.I.), Stanford University School of Medicine, Stanford, CA; Quantitative Sciences Unit, Stanford University School of Medicine, Palo Alto, CA (B.A.G.); HudsonAlpha Institute for Biotechnology, Huntsville, AL (D.A.); Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, CA (J.P.A.I.).

Correspondence to Joshua W. Knowles, MD, PhD, Stanford University School of Medicine, Division of Cardiovascular Medicine, Falk CVRC, 300 Pasteur Dr, Stanford, CA 94305. E-mail knowlej@stanford.edu

Background

Genome-wide association studies (GWAS) have identified more than 1500 disease-associated single nucleotide polymorphisms (SNPs), including many related to atherosclerotic cardiovascular disease (CVD). Associations have been found for most traditional risk factors (TRFs), including lipids,1,2 blood pressure/hypertension,3,4 weight/body mass index,5,6 smoking behavior,7 and diabetes.8–13 GWAS have also identified susceptibility variants for coronary heart disease (CHD). The first and, so far, strongest of these signals was found in the 9p21.3 locus, where common variants in this region increase the relative risk of CVD by 15% to 30% per risk allele in most race/ethnic groups.13–20 Subsequent large-scale GWAS meta-analyses and replication studies in largely white/European populations have led to the reliable identification of an additional 26 loci conferring susceptibility to CHD,2,20–23 all with substantially lower effects sizes compared with the 9p21 locus. Many of these CVD susceptibility loci appear to be conferring risk independent of TRFs and thus cannot currently be assessed by surrogate clinical measures (Table 1). Among the 27 independent loci identified in the most recent large meta-analyses of CVD, 21 were reported not to be associated with any of the TRFs.20,21

 SOURCE

Circulation: Cardiovascular Genetics 2012; 5: 368-376

doi: 10.1161/ CIRCGENETICS.112.962746

 

 

MicroRNA in Serum as Bimarker for Cardiovascular Pathologies: acute myocardial infarction, viral myocarditis,  diastolic dysfunction, and acute heart failure

Increased MicroRNA-1 and MicroRNA-133a Levels in Serum of Patients With Cardiovascular Disease Indicate Myocardial Damage

 

Yasuhide Kuwabara, MD, Koh Ono, MD, PhD, Takahiro Horie, MD, PhD, Hitoo Nishi, MD, PhD, Kazuya Nagao, MD, PhD, Minako Kinoshita, MD, PhD, Shin Watanabe, MD, PhD, Osamu Baba, MD, Yoji Kojima, MD, PhD, Satoshi Shizuta, MD, Masao Imai, MD, Toshihiro Tamura, MD, Toru Kita, MD, PhD and Takeshi Kimura, MD, PhD

Author Affiliations

From the Department of Cardiovascular Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan (Y. Kuwabara, K.O., T.H., H.N., K.N., M.K., S.W., O.B., Y. Kojima, S.S., M.I., T.T., T. Kimura); and Kobe City Medical Center General Hospital, Kobe, Japan (T. Kita).

Correspondence to Koh Ono, MD, PhD, Department of Cardiovascular Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-kawahara-cho, Sakyo-ku, Kyoto, Japan 606-8507. E-mail kohono@kuhp.kyoto-u.ac.jp

 

Abstract

Background—Recently, elevation of circulating muscle-specific microRNA (miRNA) levels has been reported in patients with acute myocardial infarction. However, it is still unclear from which part of the myocardium or under what conditions miRNAs are released into circulating blood. The purpose of this study was to identify the source of elevated levels of circulating miRNAs and their function in cardiovascular diseases.

Conclusions—These results suggest that elevated levels of circulating miR-133a in patients with cardiovascular diseases originate mainly from the injured myocardium. Circulating miR-133a can be used as a marker for cardiomyocyte death, and it may have functions in cardiovascular diseases.

SOURCE:

Circulation: Cardiovascular Genetics. 2011; 4: 446-454

Published online before print June 2, 2011,

doi: 10.1161/ CIRCGENETICS.110.958975

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Circulating MicroRNA-208b and MicroRNA-499 Reflect Myocardial Damage in Cardiovascular Disease

Maarten F. Corsten, MD, Robert Dennert, MD, Sylvia Jochems, BSc, Tatiana Kuznetsova, MD, PhD, Yvan Devaux, PhD, Leon Hofstra, MD, PhD, Daniel R. Wagner, MD, PhD, Jan A. Staessen, MD, PhD, Stephane Heymans, MD, PhD and Blanche Schroen, PhD

Author Affiliations

From the Center for Heart Failure Research (M.F.C., R.D., S.J., S.H., B.S.), Cardiovascular Research Institute, Maastricht, The Netherlands; the Division of Hypertension and Cardiovascular Rehabilitation (T.K., J.A.S.), Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium and Department of Epidemiology, Maastricht University Medical Center, Maastricht, The Netherlands; Centre de Recherche Public–Santé, Luxembourg (Y.D., D.R.W.), Luxembourg; Maastricht University Medical Center (L.H.), Maastricht, The Netherlands; and Centre Hospitalier Luxembourg (D.R.W.), Luxembourg.

Correspondence to Blanche Schroen, PhD, Center for Heart Failure Research, Cardiovascular Research Institute Maastricht, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands. E-mail b.schroen@cardio.unimaas.nl

Drs Heymans and Schroen contributed equally to this work.

Abstract

Background— Small RNA molecules, called microRNAs, freely circulate in human plasma and correlate with varying pathologies. In this study, we explored their diagnostic potential in a selection of prevalent cardiovascular disorders.

Methods and Results— MicroRNAs were isolated from plasmas from well-characterized patients with varying degrees of cardiac damage:

(1) acute myocardial infarction,

(2) viral myocarditis,

(3) diastolic dysfunction, and

(4) acute heart failure.

Plasma levels of selected microRNAs, including heart-associated (miR-1, -133a, -208b, and -499), fibrosis-associated (miR-21 and miR-29b), and leukocyte-associated (miR-146, -155, and -223) candidates, were subsequently assessed using real-time polymerase chain reaction. Strikingly, in plasma from acute myocardial infarction patients, cardiac myocyte–associated miR-208b and -499 were highly elevated, 1600-fold (P<0.005) and 100-fold (P<0.0005), respectively, as compared with control subjects. Receiver operating characteristic curve analysis revealed an area under the curve of 0.94 (P<1010) for miR-208b and 0.92 (P<109) for miR-499. Both microRNAs correlated with plasma troponin T, indicating release of microRNAs from injured cardiomyocytes. In viral myocarditis, we observed a milder but significant elevation of these microRNAs, 30-fold and 6-fold, respectively. Plasma levels of leukocyte-expressed microRNAs were not significantly increased in acute myocardial infarction or viral myocarditis patients, despite elevated white blood cell counts. In patients with acute heart failure, only miR-499 was significantly elevated (2-fold), whereas no significant changes in microRNAs studied could be observed in diastolic dysfunction. Remarkably, plasma microRNA levels were not affected by a wide range of clinical confounders, including age, sex, body mass index, kidney function, systolic blood pressure, and white blood cell count.

Conclusions— Cardiac damage initiates the detectable release of cardiomyocyte-specific microRNAs-208b and -499 into the circulation.

SOURCE:

Circulation: Cardiovascular Genetics. 2010; 3: 499-506

Published online before print October 4, 2010,

doi: 10.1161/ CIRCGENETICS.110.957415

 

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Genetic Determinants of Potassium Sensitivity and Hypertension

 

Integrated Computational and Experimental Analysis of the Neuroendocrine Transcriptome in Genetic Hypertension Identifies Novel Control Points for the Cardiometabolic Syndrome

Ryan S. Friese, PhD, Chun Ye, PhD, Caroline M. Nievergelt, PhD, Andrew J. Schork, BS, Nitish R. Mahapatra, PhD, Fangwen Rao, MD, Philip S. Napolitan, BS, Jill Waalen, MD, MPH, Georg B. Ehret, MD, Patricia B. Munroe, PhD, Geert W. Schmid-Schönbein, PhD, Eleazar Eskin, PhD and Daniel T. O’Connor, MD

Author Affiliations

From the Departments of Bioengineering (R.S.F., G.W.S.-S.), Medicine (R.S.F., A.J.S., F.R., P.S.N., D.T.O.), Pharmacology (D.T.O.), and Psychiatry (C.M.N.), the Bioinformatics Program (C.Y.), and the Institute for Genomic Medicine (D.T.O.), University of California at San Diego; the VA San Diego Healthcare System, San Diego, CA (D.T.O.); the Departments of Computer Science & Human Genetics, University of California at Los Angeles (E.E.); the Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India (N.R.M.); Clinical Pharmacology and The Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (P.B.M.); Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (G.B.E.); and Scripps Research Institute, La Jolla, CA (J.W.).

Correspondence to Daniel T. O’Connor, MD, Department of Medicine, University of California at San Diego School of Medicine, VASDHS (0838), Skaggs (SSPPS) Room 4256, 9500 Gilman Drive, La Jolla, CA 92093-0838. E-mail doconnor@ucsd.edu

Abstract

Background—Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability.

Methods and Results—We developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes) to identify candidate genes for essential hypertension and the metabolic syndrome. We first undertook transcriptome profiling on adrenal glands from blood pressure extreme mouse strains: the hypertensive BPH (blood pressure high) and hypotensive BPL (blood pressure low). Microarray data clustering revealed a striking pattern of global underexpression of intermediary metabolism transcripts in BPH. The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes, and we then hypothesized that regulation through this motif contributed to the global underexpression. Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors HOXA3, SRY, and YY1. We finally hypothesized that genetic variation at HOXA3, SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with blood pressure in a human population blood pressure extreme sample with the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on systolic blood pressure, diastolic blood pressure, body mass index, and fasting glucose. Meta-analysis extended the YY1 results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose.

Conclusions—The results outline an innovative, systematic approach to the genetic pathogenesis of complex cardiovascular disease traits and point to transcription factor YY1 as a potential candidate gene involved in essential hypertension and the cardiometabolic syndrome.

 SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 430-440

Published online before print June 5, 2012,

doi: 10.1161/ CIRCGENETICS.111.962415

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

 

Genome-Wide Association Study of Cardiac Structure and Systolic Function in African Americans

The Candidate Gene Association Resource (CARe) Study

Ervin R. Fox, MD*, Solomon K. Musani, PhD*, Maja Barbalic, PhD*, Honghuang Lin, PhD, Bing Yu, MS, Kofo O. Ogunyankin, MD, Nicholas L. Smith, PhD, Abdullah Kutlar, MD, Nicole L. Glazer, MD, Wendy S. Post, MD, MS, Dina N. Paltoo, PhD, MPH, Daniel L. Dries, MD, MPH, Deborah N. Farlow, PhD, Christine W. Duarte, PhD, Sharon L. Kardia, PhD, Kristin J. Meyers, PhD, Yan V. Sun, PhD, Donna K. Arnett, PhD, Amit A. Patki, MS, Jin Sha, MS, Xiangqui Cui, PhD, Tandaw E. Samdarshi, MD, MPH, Alan D. Penman, PhD, Kirsten Bibbins-Domingo, MD, PhD, Petra Bůžková, PhD, Emelia J. Benjamin, MD, David A. Bluemke, MD, PhD, Alanna C. Morrison, PhD, Gerardo Heiss, MD, J. Jeffrey Carr, MD, MSc, Russell P. Tracy, PhD, Thomas H. Mosley, PhD, Herman A. Taylor, MD, Bruce M. Psaty, MD, PhD, Susan R. Heckbert, MD, PhD, Thomas P. Cappola, MD, ScM and Ramachandran S. Vasan, MD

Author Affiliations

Guest Editor for this article was Barry London, MD, PhD.

Correspondence to Ervin Fox, MD MPH, FAHA, FACC, Professor of Medicine, Department of Medicine, University of Mississippi Medical Center, 2500 North State St, Jackson, MS 39216. E-mail efox@medicine.umsmed.edu

* These authors contributed equally as joint first authors.

Abstract

Background—Using data from 4 community-based cohorts of African Americans, we tested the association between genome-wide markers (single-nucleotide polymorphisms) and cardiac phenotypes in the Candidate-gene Association Resource study.

Methods and Results—Among 6765 African Americans, we related age, sex, height, and weight-adjusted residuals for 9 cardiac phenotypes (assessed by echocardiogram or magnetic resonance imaging) to 2.5 million single-nucleotide polymorphisms genotyped using Genome-wide Affymetrix Human SNP Array 6.0 (Affy6.0) and the remainder imputed. Within the cohort, genome-wide association analysis was conducted, followed by meta-analysis across cohorts using inverse variance weights (genome-wide significance threshold=4.0 ×107). Supplementary pathway analysis was performed. We attempted replication in 3 smaller cohorts of African ancestry and tested lookups in 1 consortium of European ancestry (EchoGEN). Across the 9 phenotypes, variants in 4 genetic loci reached genome-wide significance: rs4552931 in UBE2V2 (P=1.43×107) for left ventricular mass, rs7213314 in WIPI1 (P=1.68×107) for left ventricular internal diastolic diameter, rs1571099 in PPAPDC1A (P=2.57×108) for interventricular septal wall thickness, and rs9530176 in KLF5 (P=4.02×107) for ejection fraction. Associated variants were enriched in 3 signaling pathways involved in cardiac remodeling. None of the 4 loci replicated in cohorts of African ancestry was confirmed in lookups in EchoGEN.

Conclusions—In the largest genome-wide association study of cardiac structure and function to date in African Americans, we identified 4 genetic loci related to left ventricular mass, interventricular septal wall thickness, left ventricular internal diastolic diameter, and ejection fraction, which reached genome-wide significance. Replication results suggest that these loci may be unique to individuals of African ancestry. Additional large-scale studies are warranted for these complex phenotypes.

SOURCE:

Circulation: Cardiovascular Genetics. 2013; 6: 37-46

Published online before print December 28, 2012,

doi: 10.1161/ CIRCGENETICS.111.962365

 

Heart and Aging Research in Genomic Epidemiology: 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients

 

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

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 5×108 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

 

 

Genomics of Ventricular arrhythmias, A-Fib, Right Ventricular Dysplasia, Cardiomyopathy

 

Comprehensive Desmosome Mutation Analysis in North Americans With Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy

A. Dénise den Haan, MD, Boon Yew Tan, MBChB, Michelle N. Zikusoka, MD, Laura Ibañez Lladó, MS, Rahul Jain, MD, Amy Daly, MS, Crystal Tichnell, MGC, Cynthia James, PhD, Nuria Amat-Alarcon, MS, Theodore Abraham, MD, Stuart D. Russell, MD, David A. Bluemke, MD, PhD, Hugh Calkins, MD, Darshan Dalal, MD, PhD and Daniel P. Judge, MD

Author Affiliations

From the Department of Medicine/Cardiology (A.D.d.H., B.Y.T., M.N.Z., L.I.L., R.J., A.D., C.T., C.J., N.A.-A., T.A., S.D.R., H.C., D.D., D.P.J.), Johns Hopkins University School of Medicine, Baltimore, Md; Department of Cardiology, Division of Heart and Lungs (A.D.d.H.), University Medical Center Utrecht, Utrecht, The Netherlands; and National Institutes of Health, Radiology and Imaging Sciences (D.A.B.), Bethesda, Md.

Correspondence to Daniel P. Judge, MD, Johns Hopkins University, Division of Cardiology, Ross 1049; 720 Rutland Avenue, Baltimore, MD 21205. E-mail djudge@jhmi.edu

Abstract

Background— Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is an inherited disorder typically caused by mutations in components of the cardiac desmosome. The prevalence and significance of desmosome mutations among patients with ARVD/C in North America have not been described previously. We report comprehensive desmosome genetic analysis for 100 North Americans with clinically confirmed or suspected ARVD/C.

Methods and Results— In 82 individuals with ARVD/C and 18 people with suspected ARVD/C, DNA sequence analysis was performed on PKP2, DSG2, DSP, DSC2, and JUP. In those with ARVD/C, 52% harbored a desmosome mutation. A majority of these mutations occurred in PKP2. Notably, 3 of the individuals studied have a mutation in more than 1 gene. Patients with a desmosome mutation were more likely to have experienced ventricular tachycardia (73% versus 44%), and they presented at a younger age (33 versus 41 years) compared with those without a desmosome mutation. Men with ARVD/C were more likely than women to carry a desmosome mutation (63% versus 38%). A mutation was identified in 5 of 18 patients (28%) with suspected ARVD. In this smaller subgroup, there were no significant phenotypic differences identified between individuals with a desmosome mutation compared with those without a mutation.

Conclusions— Our study shows that in 52% of North Americans with ARVD/C a mutation in one of the cardiac desmosome genes can be identified. Compared with those without a desmosome gene mutation, individuals with a desmosome gene mutation had earlier-onset ARVD/C and were more likely to have ventricular tachycardia.

SOURCE:

Circulation: Cardiovascular Genetics.2009; 2: 428-435

Published online before print June 3, 2009,

doi: 10.1161/ CIRCGENETICS.109.858217

 

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Heart. 2010;96:1268-1274, AbstractFull TextPDF

Desmosomal gene analysis in arrhythmogenic right ventricular dysplasia/cardiomyopathy: spectrum of mutations and clinical impact in practice 
Europace. 2010;12:861-868,

 AbstractFull TextPDF

 

Large-Scale Candidate Gene Analysis in Whites and African Americans Identifies IL6R Polymorphism in Relation to Atrial Fibrillation

The National Heart, Lung, and Blood Institute’s Candidate Gene Association Resource (CARe) Project

Renate B. Schnabel, MD, MSc*, Kathleen F. Kerr, PhD*, Steven A. Lubitz, MD*, Ermeg L. Alkylbekova, MD*, Gregory M. Marcus, MD, MAS, Moritz F. Sinner, MD, Jared W. Magnani, MD, Philip A. Wolf, MD, Rajat Deo, MD, Donald M. Lloyd-Jones, MD, ScM, Kathryn L. Lunetta, PhD, Reena Mehra, MD, MS, Daniel Levy, MD, Ervin R. Fox, MD, MPH, Dan E. Arking, PhD, Thomas H. Mosley, PhD, Martina Müller-Nurasyid, MSc, PhD, Taylor R. Young, MA, H.-Erich Wichmann, MD, PhD, Sudha Seshadri, MD, Deborah N. Farlow, PhD, Jerome I. Rotter, MD, Elsayed Z. Soliman, MD, MSc, MS, Nicole L. Glazer, PhD, James G. Wilson, MD, Monique M.B. Breteler, MD, Nona Sotoodehnia, MD, MPH, Christopher Newton-Cheh, MD, MPH, Stefan Kääb, MD, PhD, Patrick T. Ellinor, MD, PhD*, Alvaro Alonso, MD*, Emelia J. Benjamin, MD, ScM*, Susan R. Heckbert, MD, PhD* and for the Candidate Gene Association Resource (CARe) Atrial Fibrillation/Electrocardiography Working Group

Correspondence to Susan R. Heckbert, MD, PhD, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA 98101. E-mail heckbert@u.washington.edu; Emelia J. Benjamin, MD, ScM, Medicine and Epidemiology, Boston University Schools of Medicine and Public Health, The Framingham Heart Study, 73 Mount Wayte Ave, Framingham, MA 01702–5827. E-mail emelia@bu.edu; Renate B. Schnabel, MD, MSc, Department of Medicine 2, Cardiology, Johannes Gutenberg University, Langenbeckstr 1, 55131 Mainz, Germany. E-mail schnabelr@gmx.de

* These authors contributed equally to the manuscript.

Abstract

Background—The genetic background of atrial fibrillation (AF) in whites and African Americans is largely unknown. Genes in cardiovascular pathways have not been systematically investigated.

Methods and Results—We examined a panel of approximately 50 000 common single-nucleotide polymorphisms (SNPs) in 2095 cardiovascular candidate genes and AF in 3 cohorts with participants of European (n=18 524; 2260 cases) or African American descent (n=3662; 263 cases) in the National Heart, Lung, and Blood Institute’s Candidate Gene Association Resource. Results in whites were followed up in the German Competence Network for AF (n=906, 468 cases). The top result was assessed in relation to incident ischemic stroke in the Cohorts for Heart and Aging Research in Genomic Epidemiology Stroke Consortium (n=19 602 whites, 1544 incident strokes). SNP rs4845625 in the IL6R gene was associated with AF (relative risk [RR] C allele, 0.90; 95% confidence interval [CI], 0.85–0.95; P=0.0005) in whites but did not reach statistical significance in African Americans (RR, 0.86; 95% CI, 0.72–1.03; P=0.09). The results were comparable in the German AF Network replication, (RR, 0.71; 95% CI, 0.57–0.89; P=0.003). No association between rs4845625 and stroke was observed in whites. The known chromosome 4 locus near PITX2 in whites also was associated with AF in African Americans (rs4611994; hazard ratio, 1.40; 95% CI, 1.16–1.69; P=0.0005).

Conclusions—In a community-based cohort meta-analysis, we identified genetic association in IL6R with AF in whites. Additionally, we demonstrated that the chromosome 4 locus known from recent genome-wide association studies in whites is associated with AF in African Americans.

 SOURCE:

Circulation: Cardiovascular Genetics.2011; 4: 557-564

Published online before print August 16, 2011,

doi: 10.1161/ CIRCGENETICS.110.959197

PITX2c Is Expressed in the Adult Left Atrium, and Reducing Pitx2c Expression Promotes Atrial Fibrillation Inducibility and Complex Changes in Gene Expression

Paulus Kirchhof, MD*, Peter C. Kahr*, Sven Kaese, Ilaria Piccini, PhD, Ismail Vokshi, BSc, Hans-Heinrich Scheld, MD, Heinrich Rotering, MD, Lisa Fortmueller, MD (vet), Sandra Laakmann, MD (vet), Sander Verheule, PhD, Ulrich Schotten, MD, PhD, Larissa Fabritz, MD and Nigel A. Brown, PhD

Author Affiliations

From the Department of Cardiology and Angiology (P.K., P.C.K., S.K., I.P., L.F., S.L., L.F.) and the Department of Thoracic and Cardiovascular Surgery (H.-H.S., H.R.), University Hospital Muenster, Germany; Division of Biomedical Sciences (P.C.K., I.V., N.A.B.), St. George’s, University of London, United Kingdom; and the Department of Physiology (S.V., U.S.), Maastricht University, The Netherlands.

Correspondence to Nigel A. Brown, PhD, Division of Biomedical Sciences, St George’s, University of London, Cranmer Terrace, London, SW17 0RE, UK. E-mail nbrown@sgul.ac.uk

* Drs Kirchhof and Kahr contributed equally to this work.

Abstract

Background— Intergenic variations on chromosome 4q25, close to the PITX2 transcription factor gene, are associated with atrial fibrillation (AF). We therefore tested whether adult hearts express PITX2 and whether variation in expression affects cardiac function.

Methods and Results— mRNA for PITX2 isoform c was expressed in left atria of human and mouse, with levels in right atrium and left and right ventricles being 100-fold lower. In mice heterozygous for Pitx2c (Pitx2c+/), left atrial Pitx2c expression was 60% of wild-type and cardiac morphology and function were not altered, except for slightly elevated pulmonary flow velocity. Isolated Pitx2c+/ hearts were susceptible to AF during programmed stimulation. At short paced cycle lengths, atrial action potential durations were shorter in Pitx2c+/ than in wild-type. Perfusion with the β-receptor agonist orciprenaline abolished inducibility of AF and reduced the effect on action potential duration. Spontaneous heart rates, atrial conduction velocities, and activation patterns were not affected in Pitx2c+/ hearts, suggesting that action potential duration shortening caused wave length reduction and inducibility of AF. Expression array analyses comparing Pitx2c+/ with wild-type, for left atrial and right atrial tissue separately, identified genes related to calcium ion binding, gap and tight junctions, ion channels, and melanogenesis as being affected by the reduced expression of Pitx2c.

Conclusions— These findings demonstrate a physiological role for PITX2 in the adult heart and support the hypothesis that dysregulation of PITX2 expression can be responsible for susceptibility to AF.

 SOURCE:

Circulation: Cardiovascular Genetics.2011; 4: 123-133

Published online before print January 31, 2011,

doi: 10.1161/ CIRCGENETICS.110.958058

 

Genetics of CVD and Hyperlipidemia, Hyper Cholesterolemia, Metabolic Syndrome

 

Genetic Loci Associated With Plasma Concentration of Low-Density Lipoprotein Cholesterol, High-Density Lipoprotein Cholesterol, Triglycerides, Apolipoprotein A1, and Apolipoprotein B Among 6382 White Women in Genome-Wide Analysis With Replication

Daniel I. Chasman, PhD*, Guillaume Paré, MD, MS*, Robert Y.L. Zee, PhD, MPH, Alex N. Parker, PhD, Nancy R. Cook, ScD, Julie E. Buring, ScD, David J. Kwiatkowski, MD, PhD, Lynda M. Rose, MS, Joshua D. Smith, BS, Paul T. Williams, PhD, Mark J. Rieder, PhD, Jerome I. Rotter, MD, Deborah A. Nickerson, PhD, Ronald M. Krauss, MD, Joseph P. Miletich, MD and Paul M Ridker, MD, MPH

Author Affiliations

From the Center for Cardiovascular Disease Prevention (D.I.C., G.P., R.Y.L.Z., N.R.C., J.E.B., L.M.R., P.M.R.) and Donald W. Reynolds Center for Cardiovascular Research (D.I.C., G.P., R.Y.L.Z., N.R.C., D.J.K., P.M.R.), Brigham and Women’s Hospital, Harvard Medical School, Boston, Mass; Amgen, Inc, Cambridge, Mass (A.N.P., J.M.P.); Department of Genome Sciences, University of Washington, Seattle, Wash (J.D.S., M.J.R., D.A.N.); Life Science Division, Lawrence Berkeley National Laboratory, Berkeley, Calif (P.T.W., R.M.K.); Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, Calif (J.I.R.); and Children’s Hospital Oakland Research Institute, Oakland, Calif (R.M.K.).

Correspondence to Daniel I. Chasman, Center for Cardiovascular Disease Prevention, Brigham and Women’s Hospital, 900 Commonwealth Ave E, Boston, MA 02215. E-mail dchasman@rics.bwh.harvard.edu

Abstract

Background— Genome-wide genetic association analysis represents an opportunity for a comprehensive survey of the genes governing lipid metabolism, potentially revealing new insights or even therapeutic strategies for cardiovascular disease and related metabolic disorders.

Methods and Results— We have performed large-scale, genome-wide genetic analysis among 6382 white women with replication in 2 cohorts of 970 additional white men and women for associations between common single-nucleotide polymorphisms and low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, apolipoprotein (Apo) A1, and ApoB. Genome-wide associations (P<5×108) were found at the PCSK9 gene, the APOB gene, the LPL gene, the APOA1-APOA5 locus, the LIPC gene, the CETP gene, the LDLR gene, and the APOE locus. In addition, genome-wide associations with triglycerides at the GCKR gene confirm and extend emerging links between glucose and lipid metabolism. Still other genome-wide associations at the 1p13.3 locus are consistent with emerging biological properties for a region of the genome, possibly related to the SORT1 gene. Below genome-wide significance, our study provides confirmatory evidence for associations at 5 novel loci with low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglycerides reported recently in separate genome-wide association studies. The total proportion of variance explained by common variation at the genome-wide candidate loci ranges from 4.3% for triglycerides to 12.6% for ApoB.

Conclusion— Genome-wide associations at the GCKR gene and near the SORT1 gene, as well as confirmatory associations at 5 additional novel loci, suggest emerging biological pathways for lipid metabolism among white women.

 SOURCE:

Circulation: Cardiovascular Genetics.2008; 1: 21-30

doi: 10.1161/ CIRCGENETICS.108.773168

 

 

Integrated Computational and Experimental Analysis of the Neuroendocrine Transcriptome in Genetic Hypertension Identifies Novel Control Points for the Cardiometabolic Syndrome

Ryan S. Friese, PhD, Chun Ye, PhD, Caroline M. Nievergelt, PhD, Andrew J. Schork, BS, Nitish R. Mahapatra, PhD, Fangwen Rao, MD, Philip S. Napolitan, BS, Jill Waalen, MD, MPH, Georg B. Ehret, MD, Patricia B. Munroe, PhD, Geert W. Schmid-Schönbein, PhD, Eleazar Eskin, PhD and Daniel T. O’Connor, MD

Author Affiliations

From the Departments of Bioengineering (R.S.F., G.W.S.-S.), Medicine (R.S.F., A.J.S., F.R., P.S.N., D.T.O.), Pharmacology (D.T.O.), and Psychiatry (C.M.N.), the Bioinformatics Program (C.Y.), and the Institute for Genomic Medicine (D.T.O.), University of California at San Diego; the VA San Diego Healthcare System, San Diego, CA (D.T.O.); the Departments of Computer Science & Human Genetics, University of California at Los Angeles (E.E.); the Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India (N.R.M.); Clinical Pharmacology and The Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (P.B.M.); Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (G.B.E.); and Scripps Research Institute, La Jolla, CA (J.W.).

Correspondence to Daniel T. O’Connor, MD, Department of Medicine, University of California at San Diego School of Medicine, VASDHS (0838), Skaggs (SSPPS) Room 4256, 9500 Gilman Drive, La Jolla, CA 92093-0838. E-mail doconnor@ucsd.edu

Abstract

Background—Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability.

Methods and Results—We developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes) to identify candidate genes for essential hypertension and the metabolic syndrome. We first undertook transcriptome profiling on adrenal glands from blood pressure extreme mouse strains: the hypertensive BPH (blood pressure high) and hypotensive BPL (blood pressure low). Microarray data clustering revealed a striking pattern of global underexpression of intermediary metabolism transcripts in BPH. The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes, and we then hypothesized that regulation through this motif contributed to the global underexpression. Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors HOXA3, SRY, and YY1. We finally hypothesized that genetic variation at HOXA3, SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with blood pressure in a human population blood pressure extreme sample with the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on systolic blood pressure, diastolic blood pressure, body mass index, and fasting glucose. Meta-analysis extended the YY1 results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose.

Conclusions—The results outline an innovative, systematic approach to the genetic pathogenesis of complex cardiovascular disease traits and point to transcription factor YY1 as a potential candidate gene involved in essential hypertension and the cardiometabolic syndrome.

 SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 430-440

Published online before print June 5, 2012,

doi: 10.1161/ CIRCGENETICS.111.962415

 

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

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

Author Affiliations

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

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

Abstract

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

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

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

SOURCE:

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

Published online before print March 8, 2012,

doi: 10.1161/ CIRCGENETICS.111.962191

 

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

 

Genome-Wide Association Study Pinpoints a New Functional Apolipoprotein B Variant Influencing Oxidized Low-Density Lipoprotein Levels But Not Cardiovascular Events

AtheroRemo Consortium

Kari-Matti Mäkelä, BM, BSc, Ilkka Seppälä, MSc, Jussi A. Hernesniemi, MD, PhD, Leo-Pekka Lyytikäinen, MD, Niku Oksala, MD, PhD, DSc, Marcus E. Kleber, PhD, Hubert Scharnagl, PhD, Tanja B. Grammer, MD, Jens Baumert, PhD, Barbara Thorand, PhD, Antti Jula, MD, PhD, Nina Hutri-Kähönen, MD, PhD, Markus Juonala, MD, PhD, Tomi Laitinen, MD, PhD, Reijo Laaksonen, MD, PhD, Pekka J. Karhunen, MD, PhD, Kjell C. Nikus, MD, PhD, Tuomo Nieminen, MD, PhD, MSc, Jari Laurikka, MD, PhD, Pekka Kuukasjärvi, MD, PhD, Matti Tarkka, MD, PhD, Jari Viik, PhD, Norman Klopp, PhD, Thomas Illig, PhD, Johannes Kettunen, PhD, Markku Ahotupa, PhD, Jorma S.A. Viikari, MD, PhD, Mika Kähönen, MD, PhD, Olli T. Raitakari, MD, PhD, Mahir Karakas, MD, Wolfgang Koenig, MD, PhD, Bernhard O. Boehm, MD, Bernhard R. Winkelmann, MD, Winfried März, MD and Terho Lehtimäki, MD, PhD

Correspondence to Kari-Matti Mäkelä, Department of Clinical Chemistry, Finn-Medi 2, PO Box 2000, FI-33521 Tampere, Finland. E-mail kari-matti.makela@uta.fi

Abstract

Background—Oxidized low-density lipoprotein may be a key factor in the development of atherosclerosis. We performed a genome-wide association study on oxidized low-density lipoprotein and tested the impact of associated single-nucleotide polymorphisms (SNPs) on the risk factors of atherosclerosis and cardiovascular events.

Methods and Results—A discovery genome-wide association study was performed on a population of young healthy white individuals (N=2080), and the SNPs associated with a P<5×10–8 were replicated in 2 independent samples (A: N=2912; B: N=1326). Associations with cardiovascular endpoints were also assessed with 2 additional clinical cohorts (C: N=1118; and D: N=808). We found 328 SNPs associated with oxidized low-density lipoprotein. The genetic variant rs676210 (Pro2739Leu) in apolipoprotein B was the proxy SNP behind all associations (P=4.3×10–136, effect size=13.2 U/L per allele). This association was replicated in the 2 independent samples (A and B, P=2.5×10–47 and 1.1×10–11, effect sizes=10.3 U/L and 7.8 U/L, respectively). In the meta-analyses of cohorts A, C, and D (excluding cohort B without angiographic data), the top SNP did not associate significantly with the age of onset of angiographically verified coronary artery disease (hazard ratio=1.00 [0.94–1.06] per allele), 3-vessel coronary artery disease (hazard ratio=1.03 [0.94–1.13]), or myocardial infarction (hazard ratio=1.04 [0.96–1.12]).

Conclusions—This novel genetic marker is an important factor regulating oxidized low-density lipoprotein levels but not a major genetic factor for the studied cardiovascular endpoints.

 SOURCE:

Circulation: Cardiovascular Genetics.2013; 6: 73-81

Published online before print December 17, 2012,

doi: 10.1161/ CIRCGENETICS.112.964965

Genome-Wide Screen for Metabolic Syndrome Susceptibility Loci Reveals Strong Lipid Gene Contribution But No Evidence for Common Genetic Basis for Clustering of Metabolic Syndrome Traits

Kati Kristiansson, PhD, Markus Perola, MD, PhD, Emmi Tikkanen, MSc, Johannes Kettunen, PhD, Ida Surakka, MSc, Aki S. Havulinna, DSc (Tech.), Alena Stančáková, MD, PhD, Chris Barnes, PhD, Elisabeth Widen, MD, PhD, Eero Kajantie, MD, PhD, Johan G. Eriksson, MD, DMSc, Jorma Viikari, MD, PhD, Mika Kähönen, MD, PhD, Terho Lehtimäki, MD, PhD, Olli T. Raitakari, MD, PhD, Anna-Liisa Hartikainen, MD, PhD, Aimo Ruokonen, MD, PhD, Anneli Pouta, MD, PhD, Antti Jula, MD, PhD, Antti J. Kangas, MSc, Pasi Soininen, PhD, Mika Ala-Korpela, PhD, Satu Männistö, PhD, Pekka Jousilahti, MD, PhD, Lori L. Bonnycastle, PhD, Marjo-Riitta Järvelin, MD, PhD, Johanna Kuusisto, MD, PhD, Francis S. Collins, MD, PhD, Markku Laakso, MD, PhD, Matthew E. Hurles, PhD, Aarno Palotie, MD, PhD, Leena Peltonen, MD, PhD*, Samuli Ripatti, PhD and Veikko Salomaa, MD, PhD

Correspondence to Dr Kati Kristiansson, National Institute for Health and Welfare, University of Helsinki, Biomedicum, PL 104, FI-00251 Helsinki, Finland. E-mail kati.kristiansson@thl.fi

Abstract

Background—Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibility loci to the syndrome as an entity. We conducted a GWA study on MetS and its component traits in 4 Finnish cohorts consisting of 2637 MetS cases and 7927 controls, both free of diabetes, and followed the top loci in an independent sample with transcriptome and nuclear magnetic resonance-based metabonomics data. Furthermore, we tested for loci associated with multiple MetS component traits using factor analysis, and built a genetic risk score for MetS.

Methods and Results—A previously known lipid locus, APOA1/C3/A4/A5 gene cluster region (SNP rs964184), was associated with MetS in all 4 study samples (P=7.23×109 in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 was associated with various very low density lipoprotein, triglyceride, and high-density lipoprotein metabolites (P=0.024–1.88×105). Twenty-two previously identified susceptibility loci for individual MetS component traits were replicated in our GWA and factor analysis. Most of these were associated with lipid phenotypes, and none with 2 or more uncorrelated MetS components. A genetic risk score, calculated as the number of risk alleles in loci associated with individual MetS traits, was strongly associated with MetS status.

Conclusions—Our findings suggest that genes from lipid metabolism pathways have the key role in the genetic background of MetS. We found little evidence for pleiotropy linking dyslipidemia and obesity to the other MetS component traits, such as hypertension and glucose intolerance.

 SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 242-249

Published online before print March 7, 2012,

doi: 10.1161/ CIRCGENETICS.111.961482

 

Genetics and Vascular Pathologies and Platelet Aggregation, Cardiac Troponin T in Serum

 

 

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

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

Author Affiliations

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

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

Abstract

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

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

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

SOURCE: 

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

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

Matrix Metalloproteinase-9 Genotype as a Potential Genetic Marker for Abdominal Aortic Aneurysm

Tyler Duellman, BS, Christopher L. Warren, PhD, Peggy Peissig, PhD, Martha Wynn, MD and Jay Yang, MD, PhD

Author Affiliations

From the Molecular and Cellular Pharmacology Graduate Program (T.D., J.Y.) and Department of Anesthesiology (M.W., J.Y.), University of Wisconsin School of Medicine and Public Health, Madison; Illumavista Biosciences LLC, Madison, WI (C.L.W.); and Biomedical Informatics Research Center, Marshfield Clinics Research Foundation, Marshfield, WI (P.P.).

Correspondence to Jay Yang, MD, PhD, Department of Anesthesiology, University of Wisconsin SMPH, SMI 301, 1300 University Ave, Madison, WI 53706. E-mail Jyang75@wisc.edu

Abstract

Background—Degradation of extracellular matrix support in the large abdominal arteries contribute to abnormal dilation of aorta, leading to abdominal aortic aneurysms, and matrix metalloproteinase-9 (MMP-9) is the predominant enzyme targeting elastin and collagen present in the walls of the abdominal aorta. Previous studies have suggested a potential association between MMP-9 genotype and abdominal aortic aneurysm, but these studies have been limited only to the p-1562 and (CA) dinucleotide repeat microsatellite polymorphisms in the promoter region of the MMP-9 gene. We determined the functional alterations caused by 15 MMP-9 single-nucleotide polymorphisms (SNPs) reported to be relatively abundant in the human genome through Western blots, gelatinase, and promoter–reporter assays and incorporated this information to perform a logistic-regression analysis of MMP-9 SNPs in 336 human abdominal aortic aneurysm cases and controls.

Methods and Results—Significant functional alterations were observed for 6 exon SNPs and 4 promoter SNPs. Genotype analysis of frequency-matched (age, sex, history of hypertension, hypercholesterolemia, and smoking) cases and controls revealed significant genetic heterogeneity exceeding 20% observed for 6 SNPs in our population of mostly white subjects from Northern Wisconsin. A step-wise logistic-regression analysis with 6 functional SNPs, where weakly contributing confounds were eliminated using Akaike information criteria, gave a final 2 SNP (D165N and p-2502) model with an overall odds ratio of 2.45 (95% confidence interval, 1.06–5.70).

Conclusions—The combined approach of direct experimental confirmation of the functional alterations of MMP-9 SNPs and logistic-regression analysis revealed significant association between MMP-9 genotype and abdominal aortic aneurysm.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 529-537

Published online before print August 31, 2012,

doi: 10.1161/ CIRCGENETICS.112.963082

Common Genetic Variation in the 3BCL11B Gene Desert Is Associated With Carotid-Femoral Pulse Wave Velocity and Excess Cardiovascular Disease Risk

The AortaGen Consortium

Gary F. Mitchell, MD*, Germaine C. Verwoert, MSc*, Kirill V. Tarasov, MD, PhD*, Aaron Isaacs, PhD, Albert V. Smith, PhD, Yasmin, BSc, MA, PhD, Ernst R. Rietzschel, MD, PhD, Toshiko Tanaka, PhD, Yongmei Liu, MD, PhD, Afshin Parsa, MD, MPH, Samer S. Najjar, MD, Kevin M. O’Shaughnessy, MA, BM, DPhil, FRCP, Sigurdur Sigurdsson, MSc, Marc L. De Buyzere, MSc, Martin G. Larson, ScD, Mark P.S. Sie, MD, PhD, Jeanette S. Andrews, MS, Wendy S. Post, MD, MS, Francesco U.S. Mattace-Raso, MD, PhD, Carmel M. McEniery, BSc, PhD, Gudny Eiriksdottir, MSc, Patrick Segers, PhD, Ramachandran S. Vasan, MD, Marie Josee E. van Rijn, MD, PhD, Timothy D. Howard, PhD, Patrick F. McArdle, PhD, Abbas Dehghan, MD, PhD, Elizabeth S. Jewell, MS, Stephen J. Newhouse, MSc, PhD, Sofie Bekaert, PhD, Naomi M. Hamburg, MD, Anne B. Newman, MD, MPH, Albert Hofman, MD, PhD, Angelo Scuteri, MD, PhD, Dirk De Bacquer, PhD, Mohammad Arfan Ikram, MD, PhD†, Bruce M. Psaty, MD, PhD†, Christian Fuchsberger, PhD‡, Matthias Olden, PhD‡, Louise V. Wain, PhD§, Paul Elliott, MB, PhD§, Nicholas L. Smith, PhD‖, Janine F. Felix, MD, PhD‖, Jeanette Erdmann, PhD¶, Joseph A. Vita, MD, Kim Sutton-Tyrrell, PhD, Eric J.G. Sijbrands, MD, PhD, Serena Sanna, PhD, Lenore J. Launer, MS, PhD, Tim De Meyer, PhD, Andrew D. Johnson, MD, Anna F.C. Schut, MD, PhD, David M. Herrington, MD, MHS, Fernando Rivadeneira, MD, PhD, Manuela Uda, PhD, Ian B. Wilkinson, MA, BM, FRCP, Thor Aspelund, PhD, Thierry C. Gillebert, MD, PhD, Luc Van Bortel, MD, PhD, Emelia J. Benjamin, MD, MSc, Ben A. Oostra, PhD, Jingzhong Ding, MD, PhD, Quince Gibson, MBA, André G. Uitterlinden, PhD, Gonçalo R. Abecasis, PhD, John R. Cockcroft, BSc, MB, ChB, FRCP, Vilmundur Gudnason, MD, PhD, Guy G. De Backer, MD, PhD, Luigi Ferrucci, MD, Tamara B. Harris, MD, MS, Alan R. Shuldiner, MD, Cornelia M. van Duijn, PhD, Daniel Levy, MD*, Edward G. Lakatta, MD* and Jacqueline C.M. Witteman, PhD*

Correspondence to Gary F. Mitchell, MD, Cardiovascular Engineering, Inc, 1 Edgewater Dr, Suite 201A, Norwood, MA 02062. E-mail GaryFMitchell@mindspring.com

* These authors contributed equally.

Abstract

Background—Carotid-femoral pulse wave velocity (CFPWV) is a heritable measure of aortic stiffness that is strongly associated with increased risk for major cardiovascular disease events.

Methods and Results—We conducted a meta-analysis of genome-wide association data in 9 community-based European ancestry cohorts consisting of 20 634 participants. Results were replicated in 2 additional European ancestry cohorts involving 5306 participants. Based on a preliminary analysis of 6 cohorts, we identified a locus on chromosome 14 in the 3′-BCL11B gene desert that is associated with CFPWV (rs7152623, minor allele frequency=0.42, β=−0.075±0.012 SD/allele, P=2.8×1010; replication β=−0.086±0.020 SD/allele, P=1.4×106). Combined results for rs7152623 from 11 cohorts gave β=−0.076±0.010 SD/allele, P=3.1×1015. The association persisted when adjusted for mean arterial pressure (β=−0.060±0.009 SD/allele, P=1.0×1011). Results were consistent in younger (<55 years, 6 cohorts, n=13 914, β=−0.081±0.014 SD/allele, P=2.3×109) and older (9 cohorts, n=12 026, β=−0.061±0.014 SD/allele, P=9.4×106) participants. In separate meta-analyses, the locus was associated with increased risk for coronary artery disease (hazard ratio=1.05; confidence interval=1.02–1.08; P=0.0013) and heart failure (hazard ratio=1.10, CI=1.03–1.16, P=0.004).

Conclusions—Common genetic variation in a locus in the BCL11B gene desert that is thought to harbor 1 or more gene enhancers is associated with higher CFPWV and increased risk for cardiovascular disease. Elucidation of the role this novel locus plays in aortic stiffness may facilitate development of therapeutic interventions that limit aortic stiffening and related cardiovascular disease events.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 81-90

Published online before print November 8, 2011,

doi: 10.1161/ CIRCGENETICS.111.959817

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:

CIRCGENETICS.112.964627

Published online before print February 7, 2013,

doi: 10.1161/ CIRCGENETICS.111.964627

Association of Genome-Wide Variation With Highly Sensitive Cardiac Troponin-T Levels in European Americans and Blacks

A Meta-Analysis From Atherosclerosis Risk in Communities and Cardiovascular Health Studies

Bing Yu, MD, MSc, Maja Barbalic, PhD, Ariel Brautbar, MD, Vijay Nambi, MD, Ron C. Hoogeveen, PhD, Weihong Tang, PhD, Thomas H. Mosley, PhD, Jerome I. Rotter, MD, Christopher R. deFilippi, MD, Christopher J. O’Donnell, MD, Sekar Kathiresan, MD, Ken Rice, PhD, Susan R. Heckbert, MD, PhD, Christie M. Ballantyne, MD, Bruce M. Psaty, MD, PhD and Eric Boerwinkle, PhD on behalf of the CARDIoGRAM Consortium

Author Affiliations

From the Human Genetic Center, University of Texas Health Science Center at Houston, Houston, TX (B.Y., M.B., E.B.); Deptartment of Medicine (A.B., V.N., R.C.H., C.M.B.), and Human Genome Sequencing Center (E.B.), Baylor College of Medicine, Houston, TX; Department of Epidemiology, University of Minnesota, Minneapolis, MN (W.T.); Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS (T.H.M.); Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA (J.I.R.); School of Medicine, University of Maryland, Baltimore, MD (C.R.D.); National Heart, Lung, and Blood Institute and Framingham Heart Study, National Institutes of Health, Bethesda, MD (C.J.O.D.); Center for Human Genetic Research & Cardiovascular Research Center, Massachusetts General Hospital and Department of Medicine, Harvard Medical School, Boston, MA (S.K.); Department of Biostatistics (K.R.), and Cardiovascular Health Research Unit & Department of Epidemiology (S.R.H.), University of Washington, Seattle, WA; and Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington & Group Health Research Institute, Group Health Cooperative, Seattle, WA (B.M.P.).

Correspondence to Eric Boerwinkle, PhD, Human Genetic Center, University of Texas School of Public Health, 1200 Herman Pressler E-447, Houston, TX 77030. E-mail Eric.Boerwinkle@uth.tmc.edu

Abstract

Background—High levels of cardiac troponin T, measured by a highly sensitive assay (hs-cTnT), are strongly associated with incident coronary heart disease and heart failure. To date, no large-scale genome-wide association study of hs-cTnT has been reported. We sought to identify novel genetic variants that are associated with hs-cTnT levels.

Methods and Results—We performed a genome-wide association in 9491 European Americans and 2053 blacks free of coronary heart disease and heart failure from 2 prospective cohorts: the Atherosclerosis Risk in Communities Study and the Cardiovascular Health Study. Genome-wide association studies were conducted in each study and race stratum. Fixed-effect meta-analyses combined the results of linear regression from 2 cohorts within each race stratum and then across race strata to produce overall estimates and probability values. The meta-analysis identified a significant association at chromosome 8q13 (rs10091374; P=9.06×109) near the nuclear receptor coactivator 2 (NCOA2) gene. Overexpression of NCOA2 can be detected in myoblasts. An additional analysis using logistic regression and the clinically motivated 99th percentile cut point detected a significant association at 1q32 (rs12564445; P=4.73×108) in the gene TNNT2, which encodes the cardiac troponin T protein itself. The hs-cTnT-associated single-nucleotide polymorphisms were not associated with coronary heart disease in a large case-control study, but rs12564445 was significantly associated with incident heart failure in Atherosclerosis Risk in Communities Study European Americans (hazard ratio=1.16; P=0.004).

Conclusions—We identified 2 loci, near NCOA2 and in the TNNT2 gene, at which variation was significantly associated with hs-cTnT levels. Further use of the new assay should enable replication of these results.

 SOURCE:

Circulation: Cardiovascular Genetics.2013; 6: 82-88

Published online before print December 16, 2012,

doi: 10.1161/ CIRCGENETICS.112.963058

 

Genomics and Valvular Disease

 

Supravalvular Aortic Stenosis Elastin Arteriopathy

 

Giuseppe Merla, PhD, Nicola Brunetti-Pierri, MD, Pasquale Piccolo, PhD, Lucia Micale, PhD and Maria Nicla Loviglio, PhD, MSc

Author Affiliations

From the Medical Genetics Unit, IRCCS Casa Sollievo Della Sofferenza Hospital, San Giovanni Rotondo, Italy (G.M., L.M., M.N.L.); Telethon Institute of Genetics and Medicine, Napoli, Italy (N.B-P., P.P.); Department of Pediatrics, Federico II University of Naples, Naples, Italy (N.B-P.); and CIG Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland (M.N.L.).

Correspondence to Giuseppe Merla, PhD, Medical Genetics Unit, IRCCS Casa Sollievo della Sofferenza, viale Cappuccini, 71013 San Giovanni Rotondo, Italy. E-mail g.merla@operapadrepio.it

Abstract

Supravalvular aortic stenosis is a systemic elastin (ELN) arteriopathy that disproportionately affects the supravalvular aorta. ELN arteriopathy may be present in a nonsyndromic condition or in syndromic conditions such as Williams–Beuren syndrome. The anatomic findings include congenital narrowing of the lumen of the aorta and other arteries, such as branches of pulmonary or coronary arteries. Given the systemic nature of the disease, accurate evaluation is recommended to establish the degree and extent of vascular involvement and to plan appropriate interventions, which are indicated whenever hemodynamically significant stenoses occur. ELN arteriopathy is genetically heterogeneous and occurs as a consequence of haploinsufficiency of the ELN gene on chromosome 7q11.23, owing to either microdeletion of the entire chromosomal region or ELN point mutations. Interestingly, there is a prevalence of premature termination mutations resulting in null alleles among ELN point mutations. The identification of the genetic defect in patients with supravalvular aortic stenosis is essential for a definitive diagnosis, prognosis, and genetic counseling.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 692-696

doi: 10.1161/ CIRCGENETICS.112.962860

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-mail m.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

 

Joint Associations of 61 Genetic Variants in the Nicotinic Acetylcholine Receptor Genes with Subclinical Atherosclerosis in American Indians

A Gene-Family Analysis

Jingyun Yang, PhD*, Yun Zhu, MS*, Elisa T. Lee, PhD, Ying Zhang, PhD, Shelley A. Cole, PhD, Karin Haack, PhD, Lyle G. Best, BS MD, Richard B. Devereux, MD, Mary J. Roman, MD, Barbara V. Howard, PhD and Jinying Zhao, MD, PhD

Author Affiliations

From the Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (J.Y., Y. Zhu, J.Z.); Center for American Indian Health Research, University of Oklahoma Health Sciences Center, Oklahoma City, OK (E.T.L., Y. Zhang); Texas Biomedical Research Institute, San Antonio, TX (S.A.C., K.H.); Missouri Breaks Industries Research Inc, Timber Lake, SD (L.G.B.); The New York Hospital-Cornell Medical Center, New York, NY (R.B.D., M.J.R.); MedStar Health Research Institute, Hyattsville, MD (B.V.H.); and Georgetown and Howard Universities Centers for Translational Sciences, Washington, DC (B.V.H.).

Correspondence to Jinying Zhao, MD, PhD, Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal St, SL18, New Orleans, LA 70112. E-mail jzhao5@tulane.edu

* These authors contributed equally to this work.

Abstract

Background—Atherosclerosis is the underlying cause of cardiovascular disease, the leading cause of morbidity and mortality in all American populations, including American Indians. Genetic factors play an important role in the pathogenesis of atherosclerosis. Although a single-nucleotide polymorphism (SNP) may explain only a small portion of variability in disease, the joint effect of multiple variants in a pathway on disease susceptibility could be large.

Methods and Results—Using a gene-family analysis, we investigated the joint associations of 61 tag SNPs in 7 nicotinic acetylcholine receptor genes with subclinical atherosclerosis, as measured by carotid intima-media thickness and plaque score, in 3665 American Indians from 94 families recruited by the Strong Heart Family Study (SHFS). Although multiple SNPs showed marginal association with intima-media thickness and plaque score individually, only a few survived adjustments for multiple testing. However, simultaneously modeling of the joint effect of all 61 SNPs in 7 nicotinic acetylcholine receptor genes revealed significant association of the nicotinic acetylcholine receptor gene family with both intima-media thickness and plaque score independent of known coronary risk factors.

Conclusions—Genetic variants in the nicotinic acetylcholine receptor gene family jointly contribute to subclinical atherosclerosis in American Indians who participated in the SHFS. These variants may influence the susceptibility of atherosclerosis through pathways other than cigarette smoking per se.

SOURCE:

Circulation: Cardiovascular Genetics.2013; 6: 89-96

Published online before print December 22, 2012,

doi: 10.1161/ CIRCGENETICS.112.963967

 

 

Heredity of Cardiovascular Disorders Inheritance

 

A Clinical Approach to Common Cardiovascular Disorders When There Is a Family History

The Implications of Inheritance for Clinical Management

Srijita Sen-Chowdhry, MBBS, MD, FESC, Daniel Jacoby, MD and William J. McKenna, MD, DSc, FESC

Author Affiliations

From the Institute of Cardiovascular Science, University College London, London, United Kingdom (S.S-C., W.J.M.); Department of Epidemiology, Imperial College, London, London, United Kingdom (S.S-C.); Division of Cardiology, Yale School of Medicine, New Haven, CT (D.J., W.J.M.).

Correspondence to Professor William J. McKenna, MD, DSc, FESC, Institute of Cardiovascular Science, University College London, The Heart Hospital, 16-18 Westmoreland Street, London, E-mail william.mckenna@uclh.nhs.uk

Introduction

Since the advent of genotyping, recognition of heritable disease has been perceived as an opportunity for genetic diagnosis or new gene identification studies to advance understanding of pathogenesis. Until recently, however, clinical application of DNA-based testing was confined largely to Mendelian disorders. Even within this remit, predictive testing of relatives is cost-effective only in diseases in which the majority of families harbor mutations in known causal genes, such as adult polycystic kidney disease and hypertrophic cardiomyopathy, but not dilated cardiomyopathy. Confirmatory genetic testing of index cases with borderline clinical features may be economic in the still smaller subset of diseases with limited locus heterogeneity, such as Marfan syndrome. Furthermore, Mendelian diseases account for ≈5% of total disease burden.1 Genome-wide association studies have made headway in elucidating the genetic contribution to the more common, complex diseases, and high throughput techniques promise to facilitate integration of genetic analysis into clinical practice. Nevertheless, many genes remain to be identified and implementation of genomic profiling as a population screening tool would not be cost-effective at present. The implications of heredity, however, extend beyond serving as a platform for genetic analysis, influencing diagnosis, prognostication, and treatment of both index cases and relatives, and enabling rational targeting of genotyping resources. This review covers acquisition of a family history, evaluation of heritability and inheritance patterns, and the impact of inheritance on subsequent components of the clinical pathway.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 467-476

doi: 10.1161/ CIRCGENETICS.110.959361

Clinical Considerations of Heritable Factors in Common Heart Failure

Thomas P. Cappola, MD, ScM and Gerald W. Dorn II, MD

Author Affiliations

From the Department of Medicine, University of Pennsylvania, Philadelphia, PA (T.P.C.), and Center for Pharmacogenomics, Washington University School of Medicine, St Louis, MO (G.W.D.II.).

Correspondence to Gerald W. Dorn II, MD, Center for Pharmacogenomics, Washington University, 660 S Euclid Ave, Campus Box 8220, St Louis, MO 63110. E-mail gdorn@dom.wustl.edu

 

Introduction

Heart failure is a common condition responsible for at least 290 000 deaths each year in the United States alone.1 A small minority of heart failure cases are attributed to Mendelian or familial cardiomyopathies. The majority of systolic heart failure cases are not familial but represent the end result of 1 or many conditions that primarily injure the myocardium sufficiently to diminish cardiac output in the absence of compensatory mechanisms. Paradoxically, because they also injure the myocardium, it is the chronic actions of the compensatory mechanisms that in many instances contribute to the progression from simple cardiac injury to dilated cardiomyopathy and overt heart failure. Thus, the epidemiology of common heart failure appears to be just as sporadic as its major antecedent conditions (atherosclerosis, diabetes, hypertension, and viral myocarditis).

Familial trends in preclinical cardiac remodeling2 and risk of developing heart failure3 reveal an important role for genetic modifiers in addition to clinical and environmental factors. Candidate gene studies performed over the past 10 years have identified a few polymorphic gene variants that modify risk or progression of common heart failure.4 Whole-genome sequencing will lead to the discovery of other genetic modifiers that were not candidates.5 The imminent availability of individual whole-genome sequences at a cost competitive with available genetic tests for familial cardiomyopathy will no doubt further expand the list of putative genetic heart failure modifiers. Heart failure risk alleles along with traditional clinical factors will need to be considered by clinical cardiologists in their design of optimal disease surveillance and prevention programs and in individually tailoring heart failure management.

The use of individual genetic make-up is likely to have the earliest and greatest impact on managing patients with heart failure by tailoring available pharmacotherapeutics to optimize patient response and minimize adverse effects (ie, the area of pharmacogenetics). Modern heart failure management has been derived and directed by the results of large, randomized, multicenter clinical trials. When standard therapies are applied according to the selection criteria used in these trials, they prolong average survival across affected populations or decrease the incidence of heart failure in populations at risk.6 For this reason, standardized treatment guidelines prescribe heart failure therapies according to trial designs, aiming for the same target doses and general treatment approaches,7 and largely ignore individual characteristics. In this article, we review established and emerging knowledge of genetic influence on common heart failure and try to anticipate how these genetic factors may be best used to eschew the cookie-cutter approach to heart failure management and move toward implementing a personalized medicine approach for the treatment and prevention of this important and prevalent disease.

The Concept of Genotype-Directed Personal Medical Management in Heart Failure

Variation in clinical heart failure progression and therapeutic response (either benefits or side effects) supports the need for a more individualized approach to disease management. On the basis of clinical stratification (eg, by etiology of heart failure as ischemic versus nonischemic, functional status, comorbid disease), physicians try to match each patient’s specific heart failure syndrome with a therapeutic regime devised to provide the most benefit. Standard heart failure pharmacotherapy currently comprises a minimum of 3 medications (angiotensin-converting enzyme [ACE] inhibitors, β-blockers, and aldosterone antagonists), with consideration of additional medications (hydralazine/isosorbide, angiotensin receptor blockers) and diuretics. The recommended target dosages for these agents, derived from their respective clinical trials, is rarely achieved,8 partly because of untoward clinical side effects such as low blood pressure or renal dysfunction. Accordingly, the published guidelines most often are applied in each individual patient using ad hoc approaches derived from personal experience and the “art of medicine.”

Technological advances in human genomics promise a different approach and are bringing cardiology into an era of clinically applied pharmacogenetics9 (whether we want to or not). As sequencing costs decline, it is not hard to envision that patients will present having had their entire genome already sequenced. The imperative to apply genome information in clinical settings will increase, as demonstrated by recent proof-of-concept studies.10 Our field seems poorly prepared for this type of evolution in care; Roden et al9 identified 3 major barriers: First is the absence of rapidly available genotype information in the clinical workflow. This barrier is being overcome with whole-genome sequencing, which (with proper analysis) promises a permanent and largely immutable genetic roadmap for individual disease risk and drug response at a cost comparable to many other clinical tests.11 Second, we must have the knowledge to properly apply information on genetic variants for the diseases we are managing and the drugs we are using. As we describe, this knowledge is accumulating for heart failure and for other cardiac conditions, and the rate at which we are gaining additional information and developing further expertise appears to be accelerating.

The third and perhaps most formidable barrier is the lack of clinical evidence showing how real-time application of genetic information can best benefit patients. As has been broadly communicated to the medical community and lay public, common functional gene variants in CYP2C19 can impair the transformation of clopidogrel into its active metabolite, leading to increased risk of stent thrombosis after percutaneous coronary intervention.12 The relevant question thus becomes the following: If physicians have this information at the time of clinical care and reacted by adjusting clopidogrel dose or substituting prasugrel, which is unaffected by CYP2C19 genotype,13 would there be any improvement in clinical outcome? It is also important to consider whether any observed benefits justify the additional costs of genetic testing and for the alternate drug. Studies are currently examining these questions, and similar clinical trials will prospectively examine whether a genotype-guided strategy of warfarin dosing will be superior to the standard genotype-blinded approach in reaching target anticoagulation goals. At this time, there are no similar prospective, randomized, blinded trials of genotype-guided care for common heart failure.

Emerging Variants

The variants described here are established, but new ones are emerging. Although findings in heart failure genome-wide association studies have been limited, we can expect additional common heart failure variants to emerge as sample sizes increase.65 The CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium published a genome-wide association study of incident heart failure that tested for associations between >2.4 million HapMap-imputed polymorphisms in >20 000 subjects.7 They identified 2 loci associated with heart failure, rs10519210 (15q22, containing USP3 encoding a ubiquitin-specific protease) in subjects of European ancestry and rs11172782 (12q14, containing LRIG3 encoding a leucine-rich, immunoglobulin-like domain-containing protein of uncertain function) in subjects of African ancestry.66 In a companion study using the same population and genotyping results, mortality analysis of the subgroup of individuals who developed heart failure implicated an intronic SNP in CMTM7 (CKLF-like MARVEL transmembrane domain-containing 7).67 These genetic associations require independent replication and further study to identify the underlying biological mechanisms.

A recently published genome-wide association study by a European consortium on dilated cardiomyopathy identified common variants in BAG3 (BCL2-associated athanogene 3) associated with heart failure57 and identified rare BAG3 missense and truncation mutations that segregate with familial cardiomyopathy. These findings were consistent with an earlier exome-sequencing study that identified BAG3 as a familial dilated cardiomyopathy gene and showed recapitulation of cardiomyopathy with BAG3 morpholino knockdown in zebra fish.68 Together, these studies convincingly support variation in BAG3 as a genetic risk factor of cardiomyopathy and heart failure. It is noteworthy that both common and rare functional variations were identified at this locus. A unifying hypothesis for these findings, which needs to be formally tested, is that common variants in BAG3 serve as proxies for rare functional BAG3 mutations with large effects. In this situation, the underlying genetic lesion is a rare variant with a large functional effect. This has recently been described for common variants in MYH6 that correlated with rare functional MYH6 variants to cause sick sinus syndrome.69 It is premature to speculate on the clinical applications of these newer findings.

Moving Knowledge to Practice

A small number of genomic variants have been identified that modify heart failure by affecting well-understood physiological systems. The principal barrier preventing their adoption in practice may be lack of evidence showing how application of this information can best be used for clinical benefit. Trials testing genotype targeting of antiplatelet therapy and anticoagulation will be completed in the coming years. The findings from these studies will likely determine the level of enthusiasm for conducting genotype-guided trials of β-blockers and RAAS antagonists in heart failure. Given that the lifetime risk of heart failure in the United States is estimated at 1 in 5, even a small favorable effect on heart failure prevention or outcome through use of genome-guided therapy has the potential for a large public health impact. We therefore believe that a near-term goal should be to conduct pharmacogenomic trials in heart failure based on our current understanding of heart failure variants.

Looking ahead, unbiased approaches will continue to reveal a large number heart failure-modifying variants (both common and rare). Based on experience in other complex phenotypes, such has height70 and plasma lipid levels,71 the underlying genetic mechanisms for many new heart failure variants will be completely unknown, and their sheer number will preclude detailed experimentation using murine models to figure them out. Leveraging these variants for clinical application is a challenge that we will be forced to confront.

As our ability to identify rare, disease-causing variants improves through personal genome sequencing, we will be faced with the additional problem of how best to estimate the disease risk conferred by a sequence variant for which there has been no biological validation. In probabilistic terms, because there are 3 billion nucleotides in the human genome and over twice that many humans on the planet, it is likely that a nucleotide substitution for every position is represented in someone. Obviously, it will be impossible to recombinantly express and functionally characterize every DNA variant that is going to be implicated in heart failure. Bioinformatics filters have been used to try and separate functionally significant from insignificant variants based on the likelihood of changing transcript expression or protein function. These tools are limited but will improve if we tailor their results to the known characteristics of each gene product. For example, current approaches to categorize amino acid substitutions as conservative or nonconservative based only on charge or side chains can be improved by molecular modeling that incorporates protein-specific structure-function information. This approach has been used to estimate the pathogenicity of myosin heavy chain (MHC) mutations in an effort to determine which mutations are likely to cause familial cardiomyopathy when linkage analysis is not feasible.72 In concept, this approach can be applied to any protein for which structure-function activities have been finely mapped to distinct domains.

A promising extension of this approach may be to use evolutionary genetics to infer disease causality. Again, using the MHC genes as examples, human genome data show a greater prevalence of nonsynonymous gene variants in MYH6, which encodes the minor cardiac α-MHC isoform, compared with the adjacent MYH7, which encodes the major β-MHC isoform. This disparity suggests a greater tolerance for protein changes in the α-MHC isoform and negative selection against these in β-MHC. We can infer, therefore, that amino acid changes are more likely to have adverse impacts in MYH7-encoded β-MHC. If this paradigm survives prospective testing, then the forthcoming explosion of individual genetic data not only will present a massive problem in interpretation, but also will provide the genetic information by which analyses of rare sequence variants across large unaffected populations can help to differentiate the tolerable variants from those that are more likely to alter disease risk.

Each Reference above is found in:

http://circgenetics.ahajournals.org/content/4/6/701.full

SOURCE: 

Circulation: Cardiovascular Genetics.2011; 4: 701-709

doi: 10.1161/ CIRCGENETICS.110.959379

 

Pharmacogenomics

 

Hypertension Susceptibility Loci and Blood Pressure Response to Antihypertensives

Results From the Pharmacogenomic Evaluation of Antihypertensive Responses Study

Yan Gong, PhD, Caitrin W. McDonough, PhD, Zhiying Wang, MS, Wei Hou, PhD, Rhonda M. Cooper-DeHoff, PharmD, MS, Taimour Y. Langaee, PhD, Amber L. Beitelshees, PharmD, MPH, Arlene B. Chapman, MD, John G. Gums, PharmD, Kent R. Bailey, PhD, Eric Boerwinkle, PhD, Stephen T. Turner, MD and Julie A. Johnson, PharmD

Author Affiliations

From the Department of Pharmacotherapy and Translational Research (Y.G., C.W.M., R.M.C.-D., T.Y.L., J.G.G., J.A.J.), Department of Biostatistics, College of Medicine (W.H.), Division of Cardiovascular Medicine, College of Medicine (R.M.C.-D., J.A.J.), and Department of Community Health and Family Medicine (J.G.G.), University of Florida, Gainesville, FL; Division of Epidemiology, University of Texas at Houston, Houston, TX (Z.W., E.B.); Division of Endocrinology, Diabetes and Nutrition, University of Maryland, Baltimore, MD (A.L.B.); Renal Division, Emory University, Atlanta, GA (A.B.C.); and Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN (S.T.T.).

Correspondence to Yan Gong, PhD, Department of Pharmacotherapy and Translational Research, University of Florida, PO Box 100486, 1600 SW Archer Rd, Gainesville, FL 32610. E-mail gong@cop.ufl.edu.

Abstract

Background—To date, 39 single nucleotide polymorphisms (SNPs) have been associated with blood pressure (BP) or hypertension in genome-wide association studies in whites. Our hypothesis is that the loci/SNPs associated with BP/hypertension are also associated with BP response to antihypertensive drugs.

Methods and Results—We assessed the association of these loci with BP response to atenolol or hydrochlorothiazide monotherapy in 768 hypertensive participants in the Pharmacogenomics Responses of Antihypertensive Responses study. Linear regression analysis was performed on whites for each SNP in an additive model adjusting for baseline BP, age, sex, and principal components for ancestry. Genetic scores were constructed to include SNPs with nominal associations, and empirical P values were determined by permutation test. Genotypes of 37 loci were obtained from Illumina 50K cardiovascular or Omni1M genome-wide association study chips. In whites, no SNPs reached Bonferroni-corrected α of 0.0014, 6 reached nominal significance (P<0.05), and 3 were associated with atenolol BP response at P<0.01. The genetic score of the atenolol BP-lowering alleles was associated with response to atenolol (P=3.3×10–6 for systolic BP; P=1.6×10–6 for diastolic BP). The genetic score of the hydrochlorothiazide BP-lowering alleles was associated with response to hydrochlorothiazide (P=0.0006 for systolic BP; P=0.0003 for diastolic BP). Both risk score P values were <0.01 based on the empirical distribution from the permutation test.

Conclusions—These findings suggest that selected signals from hypertension genome-wide association studies may predict BP response to atenolol and hydrochlorothiazide when assessed through risk scoring.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 686-691

Published online before print October 19, 2012,

doi: 10.1161/ CIRCGENETICS.112.964080

 

Genetic Determinants of Statin-Induced Low-Density Lipoprotein Cholesterol Reduction

The Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) Trial

Daniel I. Chasman, PhD, Franco Giulianini, PhD, Jean MacFadyen, BA, Bryan J. Barratt, PhD, Fredrik Nyberg, MD, PhD, MPH and Paul M Ridker, MD, MPH

Author Affiliations

From the Center for Cardiovascular Disease Prevention (D.I.C., F.G., J.M., P.M.R.), JUPITER Trial Coordinating Center (D.I.C., F.G., J.M., P.M.R.), Brigham and Women’s Hospital and Harvard Medical School (D.I.C., P.M.R.), Boston, MA; Personalised Healthcare and Biomarkers, AstraZeneca Research and Development, Alderley Park, United Kingdom (B.J.B.); AstraZeneca Research and Development, Mölndal, Sweden (F.N.); and Unit of Occupational and Environmental Medicine, Department of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden (F.N.).

Correspondence to Daniel I. Chasman, PhD, Center for Cardiovascular Disease Prevention, Brigham and Women’s Hospital, 900 Commonwealth Ave E, Boston, MA 02215. E-mail dchasman@rics.bwh.harvard.edu

Abstract

Background—In statin trials, each 20 mg/dL reduction in cholesterol results in a 10–15% reduction of annual incidence rates for vascular events. However, interindividual variation in low-density lipoprotein cholesterol (LDL-C) response to statins is wide and may partially be determined on a genetic basis.

Methods and Results—A genome-wide association study of LDL-C response was performed among a total of 6989 men and women of European ancestry who were randomly allocated to either rosuvastatin 20 mg daily or placebo. Single nucleotide polymorphisms (SNPs) for genome-wide association (P<5×108) with LDL-C reduction on rosuvastatin were identified at ABCG2, LPA, and APOE, and a further association at PCSK9 was genome-wide significant for baseline LDL-C and locus-wide significant for LDL-C reduction. Median LDL-C reductions on rosuvastatin were 40, 48, 51, 55, 60, and 64 mg/dL, respectively, among those inheriting increasing numbers of LDL-lowering alleles for SNPs at these 4 loci (P trend=6.2×1020), such that each allele approximately doubled the odds of percent LDL-C reduction greater than the trial median (odds ratio, 1.9; 95% confidence interval, 1.8–2.1; P=5.0×1041). An intriguing additional association with sub–genome-wide significance (P<1×10-6) was identified for statin related LDL-C reduction at IDOL, which mediates posttranscriptional regulation of the LDL receptor in response to intracellular cholesterol levels. In candidate analysis, SNPs in SLCO1B1 and LDLR were confirmed as associated with LDL-C lowering, and a significant interaction was observed between SNPs in PCSK9 and LDLR.

Conclusions—Inherited polymorphisms that predominantly relate to statin pharmacokinetics and endocytosis of LDL particles by the LDL receptor are common in the general population and influence individual patient response to statin therapy.

SOURCE:

Circulation: Cardiovascular Genetics.2012; 5: 257-264

Published online before print February 13, 2012,

doi: 10.1161/ CIRCGENETICS.111.961144

Genetic Variation in the β2 Subunit of the Voltage-Gated Calcium Channel and Pharmacogenetic Association With Adverse Cardiovascular Outcomes in the INternational VErapamil SR-Trandolapril STudy GENEtic Substudy (INVEST-GENES)

Yuxin Niu, PhD*, Yan Gong, PhD*, Taimour Y. Langaee, PhD, Heather M. Davis, PharmD, Hazem Elewa, PhD, Amber L. Beitelshees, PharmD, MPH, James I. Moss, PhD, Rhonda M. Cooper-DeHoff, PharmD, Carl J. Pepine, MD and Julie A. Johnson, PharmD

Author Affiliations

From the Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics (Y.N., Y.G., T.Y.L., H.M.D., H.E., J.I.M., R.M.C.-D., J.A.J.), College of Pharmacy, University of Florida, Gainesville, Fla; Division of Endocrinology, Diabetes and Nutrition (A.L.B.), University of Maryland School of Medicine, Baltimore, Md; and Division of Cardiovascular Medicine (R.M.C.-D., C.J.P., J.A.J.), University of Florida College of Medicine, Gainesville, Fla.

Correspondence to Julie A. Johnson, PharmD, Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, PO Box 100486, Gainesville, FL 32610. E-mail Johnson@cop.ufl.edu

* Drs Niu and Gong contributed equally to this work.

Abstract

Background— Single-nucleotide polymorphisms (SNPs) within the regulatory β2 subunit of the voltage-gated calcium channel (CACNB2) may contribute to variable treatment response to antihypertensive drugs and adverse cardiovascular outcomes.

Methods and Results— SNPs in CACNB2 from 60 ethnically diverse individuals were identified and characterized. Three common SNPs (rs2357928, rs7069292, and rs61839258) and a genome-wide association study-identified intronic SNP (rs11014166) were genotyped for a clinical association study in 5598 hypertensive patients with coronary artery disease randomized to a β-blocker (BB) or a calcium channel blocker (CCB) treatment strategy in the INternational VErapamil SR-Trandolapril STudy GENEtic Substudy (INVEST-GENES). Reporter gene assays were conducted on the promoter SNP, showing association with clinical outcomes. Twenty-one novel SNPs were identified. A promoter A>G SNP (rs2357928) was found to have significant interaction with treatment strategy for adverse cardiovascular outcomes (P for interaction, 0.002). In whites, rs2357928 GG patients randomized to CCB were more likely to experience an adverse outcome than those randomized to BB treatment strategy, with adjusted hazard ratio (HR) (CCB versus BB) of 2.35 (95% CI, 1.19 to 4.66; P=0.014). There was no evidence for such treatment difference in AG (HR, 1.16; 95% CI, 0.75 to 1.79; P=0.69) and AA (HR, 0.63; 95% CI, 0.36 to 1.11; P=0.11) patients. This finding was consistent in Hispanics and blacks. CACNB2 rs11014166 showed similar pharmacogenetic effect in Hispanics, but not in whites or blacks. Reporter assay analysis of rs2357928 showed a significant increase in promoter activity for the G allele compared to the A allele.

Conclusions— These data suggest that genetic variation within CACNB2 may influence treatment-related outcomes in high-risk patients with hypertension.

Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT00133692.

SOURCE:

Circulation: Cardiovascular Genetics.2010; 3: 548-555

doi: 10.1161/ CIRCGENETICS.110.957654

 

Hepatic Metabolism and Transporter Gene Variants Enhance Response to Rosuvastatin in Patients With Acute Myocardial Infarction

The GEOSTAT-1 Study

Kristian M. Bailey, MBChB, Simon P.R. Romaine, BSc, Beryl M. Jackson, RGN, Amanda J. Farrin, MSc, Maria Efthymiou, MSc, Julian H. Barth, MD, Joanne Copeland, BSc, Terry McCormack, MBBS, Andrew Whitehead, MSc, Marcus D. Flather, MBBS, Nilesh J. Samani, MD, FMedSci, Jane Nixon, PhD, Alistair S. Hall, MD, PhD, Anthony J. Balmforth, PhD and on behalf of the SPACE ROCKET Trial Group

Author Affiliations

From the Division of Cardiovascular and Diabetes Research (K.M.B., S.P.R.R., B.M.J., A.J.B.), and Division of Cardiovascular and Neuronal Remodelling (A.S.H.), Multidisciplinary Cardiovascular Research Centre, Leeds Institute of Genetics, Health and Therapeutics, University of Leeds, Leeds, United Kingdom; Clinical Trials Research Unit (A.J.F., M.E., J.C., J.N.), University of Leeds, Leeds, United Kingdom; Clinical Biochemistry (J.H.B.), Leeds General Infirmary, Leeds, United Kingdom; Whitby Group Practice (T.M.), Spring Vale Medical Centre, Whitby, North Yorkshire, United Kingdom; Pharmacy Department (A.W.), Leeds General Infirmary, Leeds, United Kingdom; Clinical Trials and Evaluation Unit (M.D.F.), Royal Brompton and Harefield NHS Trust and Imperial College, London, United Kingdom; and Department of Cardiovascular Sciences (N.J.S.), University of Leicester, Leicester, United Kingdom.

Correspondence to Alistair S. Hall, Clinical Cardiology, Multidisciplinary Cardiovascular Research Centre (MCRC), G Floor, Jubilee Building, Leeds General Infirmary, Leeds, LS1 3EX, United Kingdom. E-mail A.S.Hall@leeds.ac.uk

* Dr Bailey, Mr Romaine, Dr Hall, and Dr Balmforth contributed equally to this study.

Abstract

Background— Pharmacogenetics aims to maximize benefits and minimize risks of drug treatment. Our objectives were to examine the influence of common variants of hepatic metabolism and transporter genes on the lipid-lowering response to statin therapy.

Methods and Results— The Genetic Effects On STATins (GEOSTAT-1) Study was a genetic substudy of Secondary Prevention of Acute Coronary Events—Reduction of Cholesterol to Key European Targets (SPACE ROCKET) (a randomized, controlled trial comparing 40 mg of simvastatin and 10 mg of rosuvastatin) that recruited 601 patients after myocardial infarction. We genotyped the following functional single nucleotide polymorphisms in the genes coding for the cytochrome P450 (CYP) metabolic enzymes, CYP2C9*2 (430C>T), CYP2C9*3 (1075A>C), CYP2C19*2 (681G>A), CYP3A5*1 (6986A>G), and hepatic influx and efflux transporters SLCO1B1 (521T>C) and breast cancer resistance protein (BCRP; 421C>A). We assessed 3-month LDL cholesterol levels and the proportion of patients reaching the current LDL cholesterol target of <70 mg/dL (<1.81 mmol/L). An enhanced response to rosuvastatin was seen for patients with variant genotypes of either CYP3A5 (P=0.006) or BCRP (P=0.010). Furthermore, multivariate logistic-regression analysis revealed that patients with at least 1 variant CYP3A5 and/or BCRP allele (n=186) were more likely to achieve the LDL cholesterol target (odds ratio: 2.289; 95% CI: 1.157, 4.527; P=0.017; rosuvastatin 54.0% to target vs simvastatin 33.7%). There were no differences for patients with variants of CYP2C9, CYP2C19, or SLCO1B1 in comparison with their respective wild types, nor were differential effects on statin response seen for patients with the most common genotypes for CYP3A5 and BCRP (n=415; odds ratio: 1.207; 95% CI: 0.768, 1.899; P=0.415).

Conclusion— The LDL cholesterol target was achieved more frequently for the 1 in 3 patients with CYP3A5 and/or BCRP variant genotypes when prescribed rosuvastatin 10 mg, compared with simvastatin 40 mg.

Clinical Trial Registration— URL: http://isrctn.org. Unique identifier: ISRCTN 89508434.

SOURCE:

Circulation: Cardiovascular Genetics.2010; 3: 276-285

Published online before print March 5, 2010,

doi: 10.1161/ CIRCGENETICS.109.898502

 

Comprehensive Whole-Genome and Candidate Gene Analysis for Response to Statin Therapy in the Treating to New Targets (TNT) Cohort

John F. Thompson, PhD, Craig L. Hyde, PhD, Linda S. Wood, MS, Sara A. Paciga, MA, David A. Hinds, PhD, David R. Cox, MD, PhD, G. Kees Hovingh, MD, PhD and John J.P. Kastelein, MD, PhD

Author Affiliations

From the Helicos BioSciences (J.F.T.), Cambridge, Mass; Molecular Medicine (J.F.T., L.S.W., S.A.P.) and Statistical Applications (C.L.H.), Pfizer Global Research and Development, Groton, Conn; Perlegen Sciences (D.A.H., D.R.C.), Mountain View, Calif; and Department of Vascular Medicine (G.K.H., J.J.P.K.), Academic Medical Center, Amsterdam, The Netherlands.

Correspondence to John J.P. Kastelein, MD, PhD, Department of Vascular Medicine, Academic Medical Center, Meibergdreef 9, Room F4-159.2, 1105 AZ Amsterdam, The Netherlands. E-mail j.j.kastelein@amc.uva.nl or j.s.jansen@amc.uva.nl

Abstract

Background— Statins are effective at lowering low-density lipoprotein cholesterol and reducing risk of cardiovascular disease, but variability in response is not well understood. To address this, 5745 individuals from the Treating to New Targets (TNT) trial were genotyped in a combination of a whole-genome and candidate gene approach to identify associations with response to atorvastatin treatment.

Methods and Results— A total of 291 988 single-nucleotide polymorphisms (SNPs) from 1984 individuals were analyzed for association with statin response, followed by genotyping top hits in 3761 additional individuals. None was significant at the whole-genome level in either the initial or follow-up test sets for association with low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglyceride response. In addition to the whole-genome platform, 23 candidate genes previously associated with statin response were analyzed in these 5745 individuals. Three SNPs in apoE were most highly associated with low-density lipoprotein cholesterol response, followed by 1 in PCSK9 with a similar effect size. At the candidate gene level, SNPs in HMGCR were also significant though the effect was less than with those in apoE and PCSK9. rs7412/apoE had the most significant association (P=6×1030), and its high significance in the whole-genome study (P=4×109) confirmed the suitability of this population for detecting effects. Age and gender were found to influence low-density lipoprotein cholesterol response to a similar extent as the most pronounced genetic effects.

Conclusions— Among SNPs tested with an allele frequency of at least 5%, only SNPs in apoE are found to influence statin response significantly. Less frequent variants in PCSK9 and smaller effect sizes in SNPs in HMGCR were also revealed.

SOURCE:

Circulation: Cardiovascular Genetics.2009; 2: 173-181

Published online before print February 12, 2009,

doi: 10.1161/ CIRCGENETICS.108.818062

Summary

Larry H. Bernstein, MD, FCAP

This review has examined a compendium of well regarded documents drawn from 248 articles in Circulation Cardiovascular Genetics from March 2010 to March 2013. The large amount of evidence obtained from large population studies identifying Genome Wide Analysis Studies (GWAS) examines a host of cardiac and vascular diseases in which there is association between specific single nucleotide peptides (SNPs), and gene loci, that may play or have no significant role in developing heart disease. It certainly is evidence of the role that the American Heart Association has is in supporting the leading research today for tomorrow’s patients.   It is too early to sort them out, but it speaks to a large volume of discovery in this area.

It raises another issue that we have been confronted with mostly since the second half of the 20th century.  What is that issue?  The issue, it appears to me, is the vast improvements in analytical technology so that “imprecision” is far less likely to be a confounder in biological measurements and this lends access to far better accuracy?  But from that question arises another! Accuracy only refers to what is measured, but does it give us better ability to explain a complex and dynamic process?  In other words, what is what we are looking at representative of in manageable events?   I think that this is the most important idea that should come out of the recent criticism of the trajectory that molecular genetics been on in the last 5 years.

It was still in an era that “BIG’ science was not the normal.  One could spend an enormous effort at stepwise purification of a protein or enzyme, or other biomolecule starting with a slurry made from 100 lbs of “chicken heart”, for example.  These separations were based on negative charges on the molecules and positive charges on the column, and the molecules of no interest were eluted by gradient elution.  Much was learned about large scale preparation from small scale trials.  But this work was not undertaken without the intent to carry out a number of investigations to understand the “functionality” of a link in a metabolic pathway.  The studies that followed the purification required kinetic investigation with a coenzyme, or with a synthetically modified coenzyme, amino acid sequencing, NMR studies, etc.  You could not put together a “mechanism” without having the minimum amount of necessary information for a reliable account.  It is probably this requirement that led to today’s “BIG” science, that is founded upon multiple methods, now large data bases, and teams of investigators across institutions and continents.  The acquisition of knowledge has been astounding, but the integration of knowledge has not caught up.

However, let’s see if we can sort out the most meaningful signals from what I too am beginning to call the “noisy channel”.  As often happens, important areas of research are opened up that are followed by significant discovery and, in the long run, many other dead end publications that have no lasting significance.  In order to do justice to the work, I’ll pick through documents I find interesting, keeping in mind there is a hidden layer of complexity of which only sufficient information leads to a better understanding.  As much literature calls attention to, much of what ails us has nothing to do with classical Mendelian genetics, and has a postgenomic component.

The most fascinating aspect of this is the withering “dark matter” of the genome. While that component may be silent or expressed, the understanding comes at a higher observed order.  The dark became light! The expression became subtle, like weak bond interactions. The underlying organization is a component of the adaptive ability of an organism or individual in an environment with plants and animals in a changing climate, at particular altitudes, with given water supplies, with disease vectors, and with endogenous sources of essential nutrients.  This brings into focus the regulatory role of the genome as just as important a factor as transmission of the genetic code, especially in somatic cell populations.

The remainder of this discussion deals specifically with my observations on cardiovascular genomics. The following conclusion is appropriate, if incomplete, at this time on circulating miRNAs, particularly miR-133a:

  • elevated levels of circulating miR-133a in patients with cardiovascular diseases originate mainly from the injured myocardium.
  • Circulating miR-133a can be used as a marker for cardiomyocyte death, and

A number of articles that cite this article suggest that it may be useful for following disease progression:
Plasma microRNAs serve as biomarkers of therapeutic efficacy and disease progression in hypertension-induced heart failure  Eur J Heart Fail  2013

MicroRNAs Within the Continuum of Postgenomics Biomarker Discovery Arterio. Thromb. Vasc. Bio. 2013;33:206-214

“Need for Rigor in Design, Reporting, and Interpretation of Transcriptomic Biomarker Studies”  J. Clin. Microbiol.. 2012;50:4192-4193

Circulating microRNAs as diagnostic biomarkers for cardiovascular diseases. Am. J. Physiol. Heart Circ. Physiol.. 2012;303:H1085-H1095,

Circulating MicroRNAs: Novel Biomarkers and Extracellular Communicators in Cardiovascular Disease? Circ. Res.. 2012;110:483-495

Circulating MicroRNAs: Biomarkers or Mediators of Cardiovascular Diseases?  Arterioscler. Thromb. Vasc. Bio. 2011;31:2383-2390,

Circulating MicroRNA-208b and MicroRNA-499 Reflect Myocardial Damage in Cardiovascular Disease MF Corsten, R Dennert, S Jochem, T Kuznetsova,  et al.

The finding refers to an association that is related to the appearance of a miRNA in the circulation of patients with acute cardiac ischemia, and particular released into the circulation of patients from injured myocardium.  This finding has to be distinguished from a finding of another miRNA released with acute injury.  In the case of miR499 (and miR208b), there is a comparison with plasma cTnT, and an ROC curve is produced.

The List of this follows:

Circulation: Cardiovascular Genetics 2010; 3: 499-506

Strikingly, in plasma from

  • acute myocardial infarction patients, cardiac myocyte–associated miR-208b and -499 were highly elevated, 1600-fold (P<0.005) and 100-fold (P<0.0005), respectively, as compared with control subjects. Receiver operating characteristic curve analysis revealed an area under the curve of 0.94 (P<10−10) for miR-208b and 0.92 (P<10−9) for miR-499. Both microRNAs correlated with plasma troponin T, indicating release of microRNAs from injured cardiomyocytes.
  • In patients with acute heart failure, only miR-499 was significantly elevated (2-fold), whereas
  • no significant changes in microRNAs studied could be observed in diastolic dysfunction.

Remarkably, plasma microRNA levels were not affected by a wide range of clinical confounders, including

  • age,
  • sex,
  • body mass index,
  • kidney function,
  • systolic blood pressure, and
  • white blood cell count.

This is miRNA with a different twist.  It appears that there are 3 types found in AMI (133a, 208b, 409).  But type 499 alone is increased with acute heart failure (no mention of chronic cardiomyopathy and no effect of estimated GFR, or of age).

If the problem was just of AMI, then we have to know what this brings to the table.  As it is the hs-troponins have yet to be shown to effectively not only increase the high sensitivity of the tests, but to decrease the confusion generated by the elevation.  The enormous improvement of a test that may be superior to the hs-ctn’s is for the patient with very indeterminiate shortness of breath, a nondefinitive ECG, and in a prodromal phase of AMI.  This happened in the past, and it may happen now, and it may account for many cases of silent MI that were found at autopsy.

Cited by
Plasma microRNAs serve as biomarkers of therapeutic efficacy and disease progression in hypertension-induced heart failure Eur J Heart Fail. 2013;0:hft018v1-hft018,
Circulating microRNAs as diagnostic biomarkers for cardiovascular diseases Am. J. Physiol. Heart Circ. Physiol.. 2012;303:H1085-H1095,

Circulation Editors’ Picks: Most Read Articles in Cardiovascular Genetics Circulation. 2012;126:e163-e169,
MicroRNAs in Patients on Chronic Hemodialysis (MINOS Study) CJASN. 2012;7:619-623,

Novel techniques and targets in cardiovascular microRNA research Cardiovasc Res. 2012;93:545-554,

Microparticles: major transport vehicles for distinct microRNAs in circulation Cardiovasc Res. 2012;93:633-644,

Profiling of circulating microRNAs: from single biomarkers to re-wired networks Cardiovasc Res. 2012;93:555-562,

Small but smart–microRNAs in the centre of inflammatory processes during cardiovascular diseases, the metabolic syndrome, and ageing   Cardiovasc Res. 2012;93:605-613,

Circulation: Heart Failure Editors’ Picks: Most Important Papers in Pathophysiology and Genetics Circ Heart Fail. 2012;5:e32-e49

Use of Circulating MicroRNAs to Diagnose Acute Myocardial Infarction   Clin. Chem. 2012;58:559-567,

Circulating microRNAs to identify human heart failure   Eur J Heart Fail. 2012;14:118-119,

Next Steps in Cardiovascular Disease Genomic Research–Sequencing, Epigenetics, and Transcriptomics  Clin. Chem. 2012;58:113-126,

Most Read in Cardiovascular Genetics on Biomarkers, Inherited Cardiomyopathies and Arrhythmias, Metabolomics, and Genomics Circ Cardiovasc Genet. 2011;4:e24-e30,

MicroRNA-126 modulates endothelial SDF-1 expression and mobilization of Sca-1+/Lin- progenitor cells in ischaemia  Cardiovasc Res. 2011;92:449-455,

The use of genomics for treatment is another matter, and has several factors, e.g., age, residual function after AMI, comorbidities

This is a lot of interesting work that opens as many questions as it answers. The observations are real, and they lead to questions relating to the heart and the circulation.  Maybe it will generate answers to very tough issues concerning hypertension, renal disease and the heart.  It is far too early to tell.  It appears that we are about to hear a cacophony of miR’s in a symphony on cardiac and circulatory diseases not be be pieced together soon. But we have many more tools at our disposal than we did when Karmen discovered and made a distinction between

  • Aspartate and Alanine aminotransferases in the late 1950s, followed in the 1960s by
  • Creatine phosphokinase, the
  • MB-isoenzyme of CK by Sobel, Shell and Kjeckshus,
  • isoenzyme-1 of lactate dehydrogenase, and later the
  • Troponins,

leading to the programs to “reduce the extent of infarct damage”.  Then came the

  • a- and b-type natriuretic peptides,

which are still not fully understood in their role in congestive heart failure and in renal disease.

One item strikes the imagination as a fruitful area of further study.   Genetic Determinants of Potassium Sensitivity and Hypertension.    Integrated Computational and Experimental Analysis of the Neuroendocrine Transcriptome in Genetic Hypertension Identifies Novel Control Points for the Cardiometabolic Syndrome

Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability.

The researchers

  • developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes)
  • to identify candidate genes for essential hypertension and the metabolic syndrome.

Method  …  transcriptome profiling on adrenal glands from blood pressure extreme mouse strains:

  1. the hypertensive BPH (blood pressure high) and
  2. hypotensive BPL (blood pressure low).

Results….   Microarray data clustering revealed

  • underexpression of intermediary metabolism transcripts in HIGH BLOOD PRESSURE.
  • The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes,
  • They decide that regulation through this motif contributed to the global underexpression.
  • Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors
    • HOXA3,
    • SRY, and
    •  YY1.

They finally hypothesized that genetic variation at HOXA3, SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with

  • blood pressure in a human population blood pressure extreme sample with
  • the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on
  1. systolic blood pressure,
  2. diastolic blood pressure,
  3. body mass index, and
  4. fasting glucose.

Meta-analysis extended the YY1 results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose.

It will take much more of this beautiful integrative work to open up our imagination as to what physiological processes are occurring.

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Ca2+ Signaling: Transcriptional Control

Reporter: Larry H. Bernstein, MD, FCAP

Cardiac Physiology (excitation-transcription coupling)(transient receptor potential channels canonical; TRPCs)
The other side of cardiac Ca2+ signaling: transcriptional control
Domínguez-Rodríguez A, Ruiz-Hurtado G, Benitah J-P and Gómez AM
Front. Physio.2012; 3:452.    http://dx.doi.org/10.3389/fphys.2012.00452
 http://www.FrontPhysiol.com/The_other_side_of_cardiac_Ca2+_signaling:_transcriptional_control
http://www.frontiersin.org/Computational_Physiology_and_Medicine/10.3389/fphys.2012.00299/full

Integration of expression data in genome-scale metabolic network reconstructions
Anna S. Blazier and Jason A. Papin*
Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
Front. Physiol., 06 August 2012 |          http://dx.doi.org/10.3389/fphys.2012.00299
http://

The other side of cardiac Ca2+ signaling: transcriptional control
Alejandro Domínguez-Rodríguez1, Gema Ruiz-Hurtado2, Jean-Pierre Benitah1 and Ana M. Gómez1*
Ca2+ is probably the most versatile signal transduction element used by all cell types. In the heart, it is essential to activate cellular contraction in each heartbeat. Nevertheless Ca2+ is not only a key element in excitation-contraction coupling (EC coupling), but it is also

  • a pivotal second messenger in cardiac signal transduction, being able to control processes such as
    • excitability, metabolism, and transcriptional regulation.

Regarding the latter, Ca2+ activates Ca2+-dependent transcription factors by a process called excitation-transcription coupling (ET coupling). ET coupling is an integrated process by which

  • the common signaling pathways that regulate EC coupling
    • activate transcription factors.

In studies on the development of cardiac hypertrophy, two Ca2+-dependent enzymes are key actors:

  1. Ca2+/Calmodulin kinase II (CaMKII) and
  2. phosphatase calcineurin,
    • both of which are activated by the complex Ca2+/Calmodulin.

The question now is how ET coupling occurs in cardiomyocytes, where intracellular Ca2+ is continuously oscillating. We draw attention to location of Ca2+ signaling:

  1. intranuclear ([Ca2+]n) or cytoplasmic ([Ca2+]c), and
  2. the specific ionic channels involved in the activation of cardiac ET coupling.

We highlight the role of the 1,4,5 inositol triphosphate receptors (IP3Rs) in the elevation of [Ca2+]n levels, which are important to

  • locally activate CaMKII, and
  • the role of transient receptor potential channels canonical (TRPCs) in [Ca2+]c,
    • needed to activate calcineurin (Cn).

Keywords: heart, calcium, excitation-transcription coupling, TRPC, nuclear calcium
Citation: Domínguez-Rodríguez A, Ruiz-Hurtado G, Benitah J-P and Gómez AM (2012) The other side of cardiac Ca2+ signaling: transcriptional control.
Front. Physio. 3:452.   http://dx.doi.org/10.3389/fphys.2012.00452       Published online: 28 November 2012.
Edited by:Eric A. Sobie, Mount Sinai School of Medicine, USA; Reviewed by: Jeffrey Varner, Cornell University, USA; Ravi Radhakrishnan, University of Pennsylvania, USA

Integration of expression data in genome-scale metabolic network reconstructions
Anna S. Blazier and Jason A. Papin*
Front. Physiol., 06 August 2012 | doi: 10.3389/fphys.2012.00299

With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of “omics” data,

  • quantifying thousands of cellular components across a variety of scales,
    • ranging from mRNA transcript levels to metabolite quantities.

Methods are needed to not only

  • integrate this omics data but to also
  • use this data to heighten the predictive capabilities of computational models.

Several recent studies have successfully demonstrated how flux balance analysis (FBA), a constraint-based modeling approach, can be used

  • to integrate transcriptomic data into genome-scale metabolic network reconstructions
    • to generate predictive computational models.

We summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

Introduction
  1. Genomics provides data on a cell’s DNA sequence,
  2. transcriptomics on the mRNA expression of cells,
  3. proteomics on a cell’s protein composition, and
  4. metabolomics on a cell’s metabolite abundance.

Computational methods are needed to reduce this dimensionality across the wide spectrum of omics data to improve understanding of the underlying biological processes (Cakir et al., 2006Pfau et al., 2011).

Metabolic network reconstructions are an advantageous platform for the integration of omics data (Palsson, 2002). Assembled in part from

  • annotated genomes as well as
    • biochemical, genetic, and cell phenotype data,
  • a metabolic network reconstruction is a manually-curated, computational framework that

Numerous studies have demonstrated how such reconstructions of metabolism can guide the development of biological hypotheses and discoveries (Oberhardt et al., 2010Sigurdsson et al., 2010Chang et al., 2011).

Flux balance analysis (FBA), a constraint-based modeling approach, can be used to probe these network reconstructions by

  • predicting physiologically relevant growth rates as a function of the underlying biochemical networks (Gianchandani et al., 2009).

To do so, FBA involves delineating constraints on the network according to

After applying constraints, the solution space of possible phenotypes narrows, allowing for more accurate characterization of the reconstructed metabolic network,

  • Omics data can be used to further constrain the possible solution space and
  • enhance the model’s predictive powers

Given the wealth of transcriptomic data, efforts to integrate mRNA expression data with metabolic network reconstructions, have, in particular, made significant progress when using FBA as an analytical platform (Covert and Palsson, 2002Akesson et al., 2004Covert et al., 2004). However, despite this abundance of data, the integration of expression data faces unique challenges such as

  • experimental and inherent biological noise,
  • variation among experimental platforms,
  • detection bias, and the
  • unclear relationship between gene expression and reaction flux

The past few years have witnessed several advances in the integration of transcriptomic data with genome-scale metabolic network reconstructions. Specifically, numerous FBA-driven algorithms have been introduced that use experimentally derived mRNA transcript levels to modify the network’s reactions either by

  • inactivating them entirely or
  • by constraining their activity levels.

Such algorithms have demonstrated their applicability by, for example,

  1. We give an overview of the formulation of FBA.
  2. We summarize various FBA-driven methods for integrating expression data into genome-scale metabolic network reconstructions.
  3. We survey the limitations of these algorithms as well as look to the future of
    • multi-omics data integration using genome-scale metabolic network reconstructions as the scaffold.

Flux balance analysis

FBA is a constraint-based modeling approach that characterizes and predicts aspects of an organism’s metabolism (Gianchandani et al., 2009) To use FBA, the user supplies a metabolic network reconstruction in the form of a stoichiometric matrix, S, where

  1. the rows in S correspond to the metabolites of the reconstruction and
  2. the columns in S represent reactions in the reconstruction.
  3.  a stoichiometric coefficient sij conveys the molecularity of a certain metabolite in a particular reaction, with
    • sij ≥ 1 indicating that the metabolite is a product of the reaction,
    • sij ≤ −1 a reactant, and
    • sij = 0 signifies that the metabolite is not involved.

A system of linear equations is established by multiplying the matrix by a column vector, v, which contains the unknown fluxes through each of the reactions of the S matrix. Under the assumption that the system operates at steady-state, that is to say there is no net production or consumption of mass within the system, the product of this matrix multiplication must equal zero, S · v = 0 (Gianchandani et al., 2009). Because the resulting system is underdetermined (i.e., too few equations, too many unknowns), linear programming (LP) is used to optimize for a particular flux,Z, the objective function, subject to underlying constraints. The objective function typically takes on the form of:    Z = c ⋅ v
where c is a row vector of weights for each of the fluxes in column vector v, indicating how much each reaction in v contributes to the objective function,Z (Lee et al., 2006; Orth et al., 2010). Examples of objective functions include maximizing biomass, ATP production, and the production of a metabolite of interest (Lewis et al., 2012).

equation M2     (1)

subject to

S ⋅ v = 0
(2)
lb ≤ v ≤ ub                     
(3)

(1) outlines the objective function to be optimized,

(2) the steady state assumption, and

(3) describes the upper and lower bounds, ub and lb, of each of the fluxes in v according to such constraints as

  • enzyme capacities,
  • maximum uptake and secretion rates, and
  • thermodynamic constraints
    • (Price et al., 2003; Jensen and Papin, 2011).

Through this application of constraints, the solution space of physiologically feasible flux distributions for v shrinks. Thus, the task of FBA is to find a solution to v that lies within the bounded solution space and that optimizes the objective function at the same time.

Several recently developed algorithms have demonstrated how expression data can be incorporated into FBA models to further constrain the flux distribution solution space in genome-scale metabolic network reconstructions .
Summary of the algorithms for the integration of expression data.     Table 1 image URL  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3429070/table/T1/?report=thumb

List of Methods:

GIMME guarantees to both produce a functioning metabolic model based on gene expression levels and quantify the agreement between the model and the data is called the Gene Inactivity Moderated by Metabolism and Expression (GIMME) algorithm (Becker and Palsson, 2008).

iMAT Similar to GIMME, the Integrative Metabolic Analysis Tool (iMAT) results in a functioning model in which the fluxes of reactions correlated with high mRNA levels are maximized and the fluxes of reactions associated with low mRNA levels are minimized (Shlomi et al., 2008; Zur et al., 2010). A key difference is that iMAT does not require a priori knowledge of a defined metabolic functionality. Briefly, this method establishes a tri-valued gene-to-reaction mapping for each reaction in the model according to the level of gene expression in the data. iMAT requires that reactions catalyzed by the products of highly expressed genes are able to carry a minimum flux. By removing this need for user-specified objective functions, iMAT bypasses assumptions about metabolic functionalities of a particular network, which proves advantageous for models where there is no clear objective function, as in models of mammalian cells.

MADE While both GIMME and iMAT rely on user-specified threshold values to determine which reactions are highly expressed and which reactions are lowly expressed, Metabolic Adjustment by Differential Expression (MADE) uses statistically significant changes in gene expression measurements to determine sequences of highly and lowly expressed reactions (Jensen and Papin, 2011). The lack of correlation between mRNA levels and protein levels makes it difficult to accurately determine when genes are “turned on,” and when they are “turned off.” Therefore, in eliminating this need for thresholding, MADE removes significant user-bias from the system.

E-Flux Whereas GIMME, iMAT, and MADE incorporate gene expression data into their models by reducing gene expression levels to binary states, the method E-Flux attempts to more directly incorporate gene expression data into FBA optimization problems by constraining the maximum possible flux through the reactions (Colijn et al., 2009). Rather than setting the upper bounds of a reaction to some large constant or 0, mirroring the implementation of binary-based algorithms, E-Flux constrains the upper bound of a reaction according to its respective gene expression level relative to a particular threshold. In cases where the gene expression data is below a certain threshold, tight constraints are placed on the flux through the corresponding reactions in the reconstruction; conversely, in cases where the gene expression is above a certain threshold, loose constraints are placed on the flux through the corresponding reactions.

PROM In contrast to the other methods discussed, which focused solely on integrating gene expression data into genome-scale metabolic network reconstructions, Probabilistic Regulation of Metabolism (PROM) aims to fuse together metabolic networks and transcription regulatory networks with expression data (Chandrasekaran and Price, 2010). To run PROM, the user supplies a genome-scale metabolic network reconstruction, a regulatory network structure describing transcription factors and their targets, and a range of expression data from various environmental and genetic perturbations. Given this expression data, PROM binarizes the genes with respect to a user-supplied threshold to evaluate the likelihood of the expression of a target gene given the expression of that gene’s transcription factor.

 Challenges facing the integration of expression data

Each of the methods discussed hinges on the assumption that mRNA transcript levels are a strong indicator for the level of protein activity. For instance, GIMME and iMAT assume that mRNA levels below a certain threshold suggest that the corresponding reactions are inactive. MADE follows a similar logic, turning reactions on and off depending on the changes in mRNA transcript levels. E-Flux and PROM assume that transcript levels indicate the degree to which reactions are active, evident in the constraining of the upper bounds in the FBA optimization problems associated with these methods.

Rather than requiring that the reconstruction mirror the expression data exactly, the methods allow for deviations in the FBA flux solution space in order to generate a functioning model that adheres to the specified constraints. In the case of GIMME, highly expressed reactions are prioritized relative to lowly expressed reactions; however, in the event that an optimal, functioning solution cannot be found, the assumption can be violated and lowly expressed reactions can be added back into the reconstruction. Thus, this assumption that mRNA transcript levels correlate to protein levels serves as a cue rather than a mandate.

Conclusion

The above methods have been used to not only integrate expression data from a variety of sources but to also make progress toward overcoming key challenges in the field of systems biology. For instance, iMAT, highlighting its applicability in multi-cellular organisms, was used to curate the human metabolic network reconstruction and predict tissue-specific gene activity levels in ten human tissues (Duarte et al., 2007; Shlomi et al., 2008). Additionally, both E-Flux and PROM have been used to discover novel drug targets in Mycobacterium tuberculosis (Colijn et al., 2009; Chandrasekaran and Price, 2010).

Given the recent success with using genome-scale metabolic network reconstructions as a platform for integrating expression data, efforts should focus on multi-omics data integration. A handful of methods have already been introduced that integrate two or more types of omics data into genome-scale metabolic network reconstructions. For example, despite the current dearth of quantitative metabolomics data, a method has been developed that demonstrates how semi-quantitative metabolomics data can be used with transcriptomic data to curate genome-scale metabolic network reconstructions and identify key reactions involved in the production of certain metabolites (Cakir et al., 2006). Another algorithm, called Integrative Omics-Metabolic Analysis (IOMA), integrates metabolomics data and proteomics data into a genome-scale metabolic network reconstruction by evaluating kinetic rate equations subject to quantitative omics measurements (Yizhak et al., 2010). Furthermore, Mass Action Stoichiometric Simulation (MASS) uses metabolomic, fluxomic, and proteomic data to transform a static stoichiometric reconstruction of an organism into a large-scale dynamic network model (Jamshidi and Palsson, 2010). And finally, building off of iMAT, the Model-Building Algorithm (MBA) utilizes literature-based knowledge, transcriptomic, proteomic, metabolomic, and phenotypic data to curate the human metabolic network reconstruction to derive a more complete picture of tissue-specific metabolism (Jerby et al., 2010). Such algorithms show promise in their ability to easily integrate high-throughput data into genome-scale metabolic network reconstructions to generate phenotypically accurate and predictive computational models.

calcium release calmodulin

calcium release calmodulin

Ca(2+) and contraction

Ca(2+) and contraction

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