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Posts Tagged ‘Montreal Heart Institute’

Reporter: Aviva Lev-Ari, PhD, RN

Combinatorial Pharmacogenetic Interactions of Bucindolol and β1, α2C Adrenergic Receptor Polymorphisms

 

UPDATED ON 9/4/2019

Beta-Blockers Increase Survival for HF Patients With Renal Impairment

Call for use of the agents in those with heart failure with reduced ejection fraction

 

Christopher M. O’Connor1*, Mona Fiuzat1, Peter E. Carson2, Inder S. Anand3, Jonathan F. Plehn4, Stephen S. Gottlieb5, Marc A. Silver6, JoAnn Lindenfeld7, Alan B. Miller8, Michel White9, Ryan Walsh7, Penny Nelson7, Allen Medway7, Gordon Davis10, Alastair D. Robertson7, J. David Port7,10, James Carr10, Guinevere A. Murphy10,Laura C. Lazzeroni11, William T. Abraham12, Stephen B. Liggett13, Michael R. Bristow7,10

1 Division of Cardiology, Duke University Medical Center/Duke Clinical Research Institute, Durham, North Carolina, United States of America,2 Division of Cardiology, Department of Veterans Affairs, Washington, District of Columbia, United States of America, 3 Division of Cardiology, Department of Veterans Affairs, Minneapolis, Minnesota, United States of America, 4 National Heart, Lung, and Blood Institute, National Institutes of Health, Washington, District of Columbia, United States of America, 5 Department of Medicine, University of Maryland, Baltimore, Maryland, United States of America, 6 Heart and Vascular Institute, Advocate Christ Medical Center, Oak Lawn, Illinois, United States of America, 7 Division of Cardiology/Cardiovascular Institute, University of Colorado School of Medicine, Aurora, Colorado, United States of America, 8 Division of Cardiology, University of Florida Health Sciences Center, Jacksonville, Florida, United States of America, 9 Research Center, Montreal Heart Institute, Montreal, Quebec, Canada, 10 ARCA biopharma, Broomfield, Colorado, United States of America, 11 Department of Psychiatry and Behavioral United States of America, Sciences and of Pediatrics, Stanford University, Stanford, California, United States of America, 12 Ohio State University, Columbus, Ohio, United States of America, 13 Center for Personalized Medicine and Genomics, University of South Florida, Morsani College of Medicine, Tampa, Florida, United States of America

Competing interests: Drs Bristow, Carr, Murphy, and Port and Mr Davis are employees of and own stock or stock options in ARCA biopharma, Inc., which owns the rights to bucindolol. Drs Fiuzat, Liggett, Lindenfeld, and Robertson are consultants of ARCA biopharma. Also, Drs Fiuzat and Liggett own stock or stock options in ARCA biopharma. Drs O’Connor, Carson, Anand, Plehn, Gottlieb, Silver, Miller, White, Lazzeroni, and Abraham and Mr Walsh, Ms Nelson, and Mr Medway have no conflicts to report. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.* E-mail: christophe.oconnor@duke.edu

Background

Pharmacogenetics involves complex interactions of gene products affecting pharmacodynamics and pharmacokinetics, but there is little information on the interaction of multiple genetic modifiers of drug response. Bucindolol is a β-blocker/sympatholytic agent whose efficacy is modulated by polymorphisms in the primary target (β1 adrenergic receptor [AR] Arg389 Gly on cardiac myocytes) and a secondary target modifier (α2C AR Ins [wild-type (Wt)] 322–325 deletion [Del] on cardiac adrenergic neurons). The major allele homozygotes and minor allele carriers of each polymorphism are respectively associated with efficacy enhancement and loss, creating the possibility for genotype combination interactions that can be measured by clinical trial methodology.

Methodology

In a 1,040 patient substudy of a bucindolol vs. placebo heart failure clinical trial, we tested the hypothesis that combinations of β1389 and α2C322–325 polymorphisms are additive for both efficacy enhancement and loss. Additionally, norepinephrine (NE) affinity for β1389 AR variants was measured in human explanted left ventricles.

Principal Findings

The combination of β1389 Arg+α2C322–325 Wt major allele homozygotes (47% of the trial population) was non-additive for efficacy enhancement across six clinical endpoints, with an average efficacy increase of 1.70-fold vs. 2.32-fold in β1389 Arg homozygotes+α2C322–325 Del minor allele carriers. In contrast, the minor allele carrier combination (13% subset) exhibited additive efficacy loss. These disparate effects are likely due to the higher proportion (42% vs. 8.7%, P = 0.009) of high-affinity NE binding sites in β1389 Arg vs. Gly ARs, which converts α2CDel minor allele-associated NE lowering from a therapeutic liability to a benefit.

Conclusions

On combination, the two sets of AR polymorphisms

1) influenced bucindolol efficacy seemingly unpredictably but consistent with their pharmacologic interactions, and

2) identified subpopulations with enhanced (β1389 Arg homozygotes), intermediate (β1389 Gly carriers+α2C322–325 Wt homozygotes), and no (β1389 Gly carriers+α2C322–325 Del carriers) efficacy.

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Figure 1:

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0044324

Limitations

There are some limitations to this study. First, although the substudy was prospectively designed and hypothesis-driven, the pharmacogenetic data were generated and analyzed after the trial’s main results were analyzed and published [5]. However, the investigators generating the pharmacogenetic data remained blinded to the treatment code and to clinical outcomes throughout. Second, approximately two-thirds of the patients were enrolled into the DNA substudy after being randomized into the parent trial. This “late entry” phenomenon has been extensively analyzed, by both L-truncation [12] and, most recently, propensity score statistical methods (unpublished observations). The effect of late entry into the DNA substudy is only to lower event rates for all clinical endpoints, without affecting genotype-specific treatment effects.

Conclusions

The combinatorial interaction of two sets of AR polymorphisms that influence bucindolol’s drug action resulted in unanticipated effects on HF clinical responses, non-additivity in efficacy enhancement for the major allele homozygotes, and additive effects for minor allele carrier-associated efficacy loss. An explanation for these disparate results was provided by the effects of the α2C322–325 minor (Del) allele on facilitating bucindolol’s NE-lowering properties, where excessive NE lowering abolished efficacy when the β1389 Gly minor allele and low NE affinity AR were present but did not alter or even enhance efficacy in the presence of the major allele homozygous β1389 Arg genotype, which encodes ARs with a NE affinity of ~100-fold more than 389 Gly ARs.

Combinatorial genotyping led to improvement in pharmacogenetic differentiation of drug response compared with monotype genotyping. The use of β1389 Arg/Gly and α2C322–325 Wt/Del genotype combinations accomplishes the goal of pharmacogenetics to identify response outliers from both ends of the therapeutic spectrum. Compared with the use of β1389 Arg/Gly or α2C322–325 Wt/Del monotypes, the differential efficacy gained by the use of genotype combinations was increased by respective amounts of 54% and 94%. The new identification of a completely unresponsive genotype, supported by biologic plausibility and bolstered by data consistency across multiple clinical endpoints, is especially important inasmuch as a major goal of pharmacogenetics is to identify patients with no likelihood of benefit who can then be spared drug side effects [21]. Other β-blockers that have been used to treat HF do not have these pharmacogenetic interactions [22][23], but rather exhibit response heterogeneity through other, unknown mechanisms[8]. Thus, the ability to predict drug response through pre-treatment pharmacogenetic testing should improve therapeutic response to this drug class but will need to be confirmed by prospective studies.

Finally, the unexpected results of this study, (i.e., the additive loss of efficacy by minor allele combinations in the absence of additive gain of efficacy by major allele homozygotes) emphasizes that combinations of response-altering polymorphisms may behave in unpredictable ways and in-silico predictions of combinatorial genetic effects will need to be supported by empirical data.

References

  1. [No authors listed] (1999) The Cardiac Insufficiency Bisoprolol Study II (CIBIS-II): a randomised trial. Lancet 353: 9–13. FIND THIS ARTICLE ONLINE
  2. Flather MD, Shibata MC, Coats AJ, Van Veldhuisen DJ, Parkhomenko A, et al. (2005) Randomized trial to determine the effect of nebivolol on mortality and cardiovascular hospital admission in elderly patients with heart failure (SENIORS). Eur Heart J 26: 215–225. FIND THIS ARTICLE ONLINE
  3. [No authors listed] (1999) Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in Congestive Heart Failure (MERIT-HF). Lancet 353: 2001–2007.FIND THIS ARTICLE ONLINE
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  5. The Beta Blocker Evaluation of Survival Trial Investigators (2001) A trial of the beta-blocker bucindolol in patients with advanced chronic heart failure. N Engl J Med 344: 1659–1667. FIND THIS ARTICLE ONLINE
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  7. O’Connor CM, Fiuzat M, Caron MF, Deedwania P, Follmann D, et al. (2011) Influence of global region on outcomes in large heart failure β-blocker trials. J Am Coll Cardiol 58: 915–922. FIND THIS ARTICLE ONLINE
  8. Metra M, Bristow MR (2010) Beta-blocker therapy in chronic heart failure. In: Mann DL, ed. Heart Failure: A companion to Braunwald’s Heart Disease.
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  11. Liggett SB, Mialet-Perez J, Thaneemit-Chen S, Weber SA, Greene SM, et al. (2006) A polymorphism within a conserved beta(1)-adrenergic receptor motif alters cardiac function and beta-blocker response in human heart failure. Proc Natl Acad Sci U S A 103: 11288–11293. FIND THIS ARTICLE ONLINE
  12. Bristow MR, Murphy GA, Krause-Steinrauf H, Anderson JL, Carlquist JF, et al. (2010) An α2C-adrenergic receptor polymorphism alters the norepinephrine lowering effects and therapeutic response of the beta blocker bucindolol in chronic heart failure. Circ Heart Fail 3: 21–28. FIND THIS ARTICLE ONLINE
  13. Mason DA, Moore JD, Green SA, Liggett SB (1999) A gain-of-function polymorphism in a G-protein coupling domain of the human beta1-adrenergic receptor. J Biol Chem 274: 12670–12674. FIND THIS ARTICLE ONLINE
  14. Sandilands AJ, O’Shaughnessy KM, Brown MJ (2003) Greater inotropic and cyclic AMP responses evoked by noradrenaline through Arg389 β1-adrenoceptors versus Gly389 β1-adrenoceptors in isolated human atrial myocardium. Br J Pharmacol 138: 386–392. FIND THIS ARTICLE ONLINE
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  16. Small KM, Forbes SL, Rahman FF, Bridges KM, Liggett SB (2000) A four amino acid deletion polymorphism in the third intracellular loop of the human alpha 2C-adrenergic receptor confers impaired coupling to multiple effectors. J Biol Chem 275: 23059–23064. FIND THIS ARTICLE ONLINE
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  19. Hershberger RE, Wynn JR, Sundberg L, Bristow MR (1990) Mechanism of action of bucindolol in human ventricular myocardium. J Cardiovasc Pharm 15: 959–967. doi: 10.1097/00005344-199006000-00014FIND THIS ARTICLE ONLINE
  20. Bristow MR, Krause-Steinrauf H, Nuzzo R, Liang CS, Lindenfeld J, et al. (2004) Effect of baseline or changes in adrenergic activity on clinical outcomes in the beta-blocker evaluation of survival trial (BEST). Circulation 110: 1437–1442. FIND THIS ARTICLE ONLINE
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  23. Sehnert AJ, Daniels SE, Elashoff M, Wingrove JA, Burrow CR, et al. (2008) Lack of association between beta adrenergic receptor genotype and survival in heart failure patients treated with carvedilol or metoprolol. J Am Coll Cardiol 52: 644–651. FIND THIS ARTICLE ONLINE
Source:

BROOMFIELD, Colo. (TheStreet) — Wacky, inexplicable things sometimes happen to biotech stocks. Like Friday, when ARCA Biopharma (ABIO) shares more than tripled after the small drug company was granted a new U.S. patent for its experimental heart failure drug.

Arca shares rose an astonishing $5.57, or 210%, to close Friday at $8.22. Calculated another way, one U.S. patent for Arca added $40 million in market value.

Not bad, especially considering Friday’s announcement wasn’t particularly new. Arca issued a press release in January announcing the U.S. Patent and Trademark Office had informed the company that the patent was coming. Friday’s press release simply confirmed that the patent had been issued.

In case you’re wondering, Arca shares rose just 17 cents as a result of the January press release.

So, what’s made Arca rocket Friday when it barely budged in January on the same patent news?

Like I said, some things in biotech defy logic. Fundamentals had nothing to do it, clearly. Instead, Friday’s move was more likely a function of momentum traders finding an easy plaything in Arca, which sports a tiny float of just 4.4 million shares.

More than 49 million Arca shares traded hands Friday, or seven times the number of shares outstanding.

It was little noticed Friday, but Arca actually disclosed some bad news regarding the development of its heart failure drug bucindolol. Arca and the U.S. Food and Drug Administration have still not come to agreement on a Special Protocol Assessment for a proposed phase III study of bucindolol. Arca said Friday it had to submit revisions to the design of the study, which will now enroll 3,200 heart failure patients, up from 3,000 patients previously.

Arca needs FDA sign off on the bucindolol trial design, after which the company needs to raise money to conduct the trial. Arca says it can likely start the pivotal bucindolol study one year after both those things happen. The company expects the study to take two years to complete once fully enrolled.

As of December 31, Arca had $7.8 million in its coffers.

http://www.thestreet.com/story/10712682/1/arca-biopharma-patent-deja-vu-biobuzz.html

In a study sponsored by ARCA Biopharma ($ABIO) and carried out by a number of U.S. universities, a pharmacogenetic test predicted which patients would respond to the company’s beta blocker and vasodilator bucindolol (Gencaro), in development for the treatment of chronic heart failure. The level of clinical activity of this oral drug depends on two changes in two genes.

The researchers screened more than a thousand of the patients with congestive heart failure who took part in the Beta-Blocker Evaluation of Survival Trial (BEST) and were given either bucindolol or dummy pills. Based on the patients’ clinical results and genetic profile, the team created a “genetic scorecard.” The results were published in PLoS ONE.

A biomarker for bucindolol will not only speed it through development but could also be used to point out those patients who will (and won’t) respond to which drug, sparing those patients who won’t respond the risk of potential side effects.

According to Stephen B. Liggett of the University of South Florida and founder of ARCA Biopharma, the researchers were able to use the two-gene test to “identify individuals with heart failure who will not respond to bucindolol and those who have an especially favorable treatment response. We also identified those who will have an intermediate level of response. The results showed that the choice of the best drug for a given patient, made the first time without a trial-and-error period, can be accomplished using this two-gene test.”

Bucindolol has been designated as a fast track development program for the reduction of cardiovascular mortality and cardiovascular hospitalizations in a genotype-defined heart failure population.

http://www.fiercebiomarkers.com/press-releases/two-gene-test-predicts-which-patients-heart-failure-respond-best-beta-block?utm_medium=nl&utm_source=internal

October 17, 2012

Two-gene test predicts which patients with heart failure respond best to beta-blocker drug, study finds
Personalized medicine research at University of South Florida strikes early for heart genes

Tampa, FL – A landmark paper identifying genetic signatures that predict which patients will respond to a life-saving drug for treating congestive heart failure has been published by a research team co-led by Stephen B. Liggett, MD, of the University of South Florida.

The study, drawing upon a randomized placebo-controlled trial for the beta blocker bucindolol, appears this month in the  international online journal PLoS ONE.  In addition to Dr. Liggett, whose laboratory discovered and characterized the two genetic variations, Christopher O’Connor, MD, of Duke University Medical Center, and Michael Bristow, MD, PhD, of ARCA biopharma and the University of Colorado Anschutz Medical Campus, were leading members of the research team.
The analysis led to a “genetic scorecard” for patients with congestive heart failure, a serious condition in which the heart can’t pump enough blood to meet the body’s needs, said Dr. Liggett, the study’s co-principal investigator and the new vice dean for research and vice dean for personalized medicine and genomics at the USF Morsani College of Medicine.
“We have been studying the molecular basis of heart failure in the laboratory with a goal of finding genetic variations in a patient’s DNA that alter how drugs work,” Dr. Liggett said.  “We took this knowledge from the lab to patients and found that we can indeed, using a two-gene test, identify individuals with heart failure who will not respond to bucindolol and those who have an especially favorable treatment response. We also identified those who will have an intermediate level of response.” The research has implications for clinical practice, because the genetic test could theoretically be used to target the beta blocker to patients the drug is likely to help. Equally important, its use could be avoided in patients with no likelihood of benefit, who could then be spared potential drug side effects.  Prospective studies are needed to confirm that bucindolol would be a better treatment than other classes of beta blockers for a subset of patients with health failure.

Dr. Liggett collaborated with medical centers across the United States, including the NASDAq-listed biotech company ARCA biopharma, which he co-founded in Denver, CO.   This genetic sub-study involved 1,040 patients who participated in the Beta-Blocker Evaluation of Survival Trial (BEST).  The researchers analyzed mortality, hospital admissions for heart failure exacerbations and other clinical outcome indicators of drug performance.

“The results showed that the choice of the best drug for a given patient, made the first time without a trial-and-error period, can be accomplished using this two-gene test,” Dr. Liggett said.

The genetic test discovered by the Liggett team requires less than 1/100th of a teaspoon of blood drawn from a patient, from which DNA is isolated.  DNA is highly stable when frozen, so a single blood draw will suffice for many decades, Dr. Liggett said. And since a patient’s DNA does not change over their lifetime, as new discoveries are made and other tests need to be run, it would not be necessary to give another blood sample, he added.

This is part of the strategy for the USF Center for Personalized Medicine and Genomics. The discovery of genetic variations in diseases can be targeted to predict three new types of information: who will get a disease, how the disease will progress, and the best drug to use for treatment.

“In the not too distant future, such tests will become routine, and patient outcomes, and the efficiency and cost of medical care will be impacted in positive ways.  We also will move toward an era where we embrace the fact that one drug does not fit all,” Dr. Liggett said.  “If we can identify by straightforward tests which drug is best for which patient, drugs that work with certain smaller populations can be brought to the market, filling a somewhat empty pipeline of new drugs.”

This approach is applicable to most diseases, Dr. Liggett said, but the USF Center has initially concentrated on heart disease, because it is a leading cause of deaths, hospitalizations and lost productivity in the Tampa Bay region and Florida.  Dr. Liggett is a recent recruit to the USF Health Morsani College of Medicine, coming from the University of Maryland School of Medicine.  His work at USF has been supported by several National Institutes of Health grants and $2 million in funding from Hillsborough County.

Heart failure is characterized by an inability of the heart muscle to pump blood, resulting in dysfunction of multiple organs caused by poor blood and oxygen flow throughout the body.  An estimated 6 million Americans are living with heart failure, and more than half a million new cases are diagnosed each year.  About 50 percent of patients diagnosed with heart failure die within five years.  The economic burden of heart failure in the United States is estimated at $40 billion a year.

Article citation:
Christopher M. O’Connor, Mona Fiuzat, Peter E. Carson, Inder S. Anand, Jonathan F. Plehn, Stephen S. Gottlieb, Marc A. Silver, JoAnn Lindenfeld, Alan B. Miller, Michel White, Ryan Walsh, Penny Nelson, Allen Medway, Gordon Davis, Alastair D. Robertson, J. David Port, James Carr, Guinevere A. Murphy, Laura C. Lazzeroni, William T. Abraham, Stephen B. Liggett and Michael Bristow, “Combinatorial Pharmacogenetic Interactions of Bucindolol and β1, α2C Adrenergic Receptor Polymorphisms,” PLoS ONE   7(10): e44324. doi:10.1371/journal.pone.0044324

-USF Health-

USF Health’s mission is to envision and implement the future of health. It is the partnership of the USF Health Morsani College of Medicine, the College of Nursing, the College of Public Health, the College of Pharmacy, the School of Biomedical Sciences and the School of Physical Therapy and Rehabilitation Sciences; and the USF Physician’s Group. The University of South Florida is a global research university ranked 50th in the nation by the National Science Foundation for both federal and total research expenditures among all U.S. universities.

Media contact:
Anne DeLotto Baier, USF Health Communications
(813) 974-3303 or abaier@health.usf.edu

Read more: Two-gene test predicts which patients with heart failure respond best to beta-blocker drug, study finds – FierceBiomarkers http://www.fiercebiomarkers.com/press-releases/two-gene-test-predicts-which-patients-heart-failure-respond-best-beta-block#ixzz29ZLX92k6
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