M R Bristow

University of Colorado, Denver, Colorado, United States

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Publications (464)3554.49 Total impact

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    ABSTRACT: Background The interpretation of the results from genome-scale experiments is a challenging and important problem in contemporary biomedical research. Biological networks that integrate experimental results with existing knowledge from biomedical databases and published literature can provide a rich resource and powerful basis for hypothesizing about mechanistic explanations for observed gene-phenotype relationships. However, the size and density of such networks often impede their efficient exploration and understanding. Results We introduce a visual analytics approach that integrates interactive filtering of dense networks based on degree-of-interest functions with attribute-based layouts of the resulting subnetworks. The comparison of multiple subnetworks representing different analysis facets is facilitated through an interactive super-network that integrates brushing-and-linking techniques for highlighting components across networks. An implementation is freely available as a Cytoscape app. Conclusions We demonstrate the utility of our approach through two case studies using a dataset that combines clinical data with high-throughput data for studying the effect of β-blocker treatment on heart failure patients. Furthermore, we discuss our team-based iterative design and development process as well as the limitations and generalizability of our approach. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0550-z) contains supplementary material, which is available to authorized users.
    BMC Bioinformatics 12/2015; 16(1). DOI:10.1186/s12859-015-0550-z · 2.67 Impact Factor
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    ABSTRACT: Despite the global burden of cardiovascular disease, investment in cardiovascular drug development has stagnated over the past 2 decades, with relative underinvestment compared with other therapeutic areas. The reasons for this trend are multifactorial, but of primary concern is the high cost of conducting cardiovascular outcome trials in the current regulatory environment that demands a direct assessment of risks and benefits, using clinically-evident cardiovascular endpoints. To work toward consensus on improving the environment for cardiovascular drug development, stakeholders from academia, industry, regulatory bodies, and government agencies convened for a think tank meeting in July 2014 in Washington, DC. This paper summarizes the proceedings of the meeting and aims to delineate the current adverse trends in cardiovascular drug development, understand the key issues that underlie these trends within the context of a recognized need for a rigorous regulatory review process, and provide potential solutions to the problems identified. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
    Journal of the American College of Cardiology 04/2015; 65(15):1567-1582. DOI:10.1016/j.jacc.2015.03.016 · 15.34 Impact Factor
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    ABSTRACT: -When β-blockers produce reverse-remodeling in idiopathic dilated cardiomyopathy (IDC) they partially reverse changes in fetal-adult/contractile protein, natriuretic peptide, SR-Ca2+-ATPase gene "program" constituents. The objective of the current study was to further test the hypothesis that reverse-remodeling is associated with favorable changes in myocardial gene expression by measuring additional contractile, signaling and metabolic genes that exhibit a fetal/adult expression predominance, are thyroid hormone-responsive, and/or are regulated by β1-adrenergic receptor signaling. A secondary objective was to identify which of these putative regulatory networks is most closely associated with observed changes. -Forty-seven IDC patients (LVEF 0.24±0.09) were randomized to the adrenergic-receptor blockers metoprolol (β1-selective), metoprolol+doxazosin (β1/α1), or carvedilol (β1/β2/α1). Serial radionuclide ventriculography and endomyocardial biopsies were performed at baseline, 3, and 12 months. Expression of 50 mRNA gene products was measured by quantitative PCR. Thirty-one patients achieved LVEF reverse-remodeling response defined as improvement by ≥0.08 at 12 months or by ≥0.05 at 3 months (ΔLVEF=0.21±0.10). Changes in gene expression in Responders vs. Nonresponders were decreases in NPPA and NPPB and increases in MYH6, ATP2A2, PLN, RYR2, ADRA1A, ADRB1, MYL3, PDFKM, PDHX, and CPT1B. All except PDHX involved increase in adult or decrease in fetal cardiac genes, but 100% were concordant with changes predicted by inhibition of β1-adrenergic signaling. -In addition to known gene expression changes, additional calcium-handling, sarcomeric, adrenergic signaling, and metabolic genes were associated with reverse-remodeling. The pattern suggests a fetal-adult paradigm but may be due to reversal of gene expression controlled by a 'β1-adrenergic receptor gene network.' Clinical Trial Registration-www.clinicaltrials.gov; Unique Identifier: NCT01798992.
    Circulation Cardiovascular Genetics 01/2015; 8(2). DOI:10.1161/CIRCGENETICS.114.000767 · 5.34 Impact Factor
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    ABSTRACT: Objectives and Background: We evaluated the ability of 23 genetic variants to provide prognostic information in patients enrolled in the Genetic Substudy of the Surgical Treatment for Ischemic Heart Failure (STICH) trials. Methods: Patients assigned to STICH Hypothesis 1 were randomized to medical therapy with or without coronary artery bypass grafting (CABG). Those assigned to STICH Hypothesis 2 were randomized to CABG or CABG with left ventricular reconstruction. Results: In patients assigned to STICH Hypothesis 2 (n = 714), no genetic variant met the prespecified Bonferroni-adjusted threshold for statistical significance (p < 0.002); however, several variants met nominal prognostic significance: variants in the β2-adrenergic receptor gene (β2-AR Gln27Glu) and in the A1-adenosine receptor gene (A1-717 T/G) were associated with an increased risk of a subject dying or being hospitalized for a cardiac problem (p = 0.027 and 0.031, respectively). These relationships remained nominally significant even after multivariable adjustment for prognostic clinical variables. However, none of the 23 genetic variants influenced all-cause mortality or the combination of death or cardiovascular hospitalization in the STICH Hypothesis 1 population (n = 532) by either univariate or multivariable analysis. Conclusion: We were unable to identify the predictive genotypes in optimally treated patients in these two ischemic heart failure populations. © 2015 S. Karger AG, Basel.
    Cardiology 01/2015; 130(2):69-81. DOI:10.1159/000368221 · 2.04 Impact Factor
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    ABSTRACT: Increasing availability of high-dimensional clinical data, which improves the ability to define more specific phenotypes, as well as molecular data, which can elucidate disease mechanisms, is a driving force and at the same time a major challenge for translational and personalized medicine. Successful research in this field requires an approach that ties together specific disease and health expertise with understanding of molecular data through statistical methods. We present PEAX (Phenotype-Expression Association eXplorer), built upon open-source software, which integrates visual phenotype model definition with statistical testing of expression data presented concurrently in a web-browser. The integration of data and analysis tasks in a single tool allows clinical domain experts to obtain new insights directly through exploration of relationships between multivariate phenotype models and gene expression data, showing the effects of model definition and modification while also exploiting potential meaningful associations between phenotype and miRNA-mRNA regulatory relationships. We combine the web visualization capabilities of Shiny and D3 with the power and speed of R for backend statistical analysis, in order to abstract the scripting required for repetitive analysis of sub-phenotype association. We describe the motivation for PEAX, demonstrate its utility through a use case involving heart failure research, and discuss computational challenges and observations. We show that our visual web-based representations are well-suited for rapid exploration of phenotype and gene expression association, facilitating insight and discovery by domain experts.
    Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 01/2015; 20:419-30.
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    ABSTRACT: Because of its comparatively recent evolution, Homo sapiens exhibit relatively little within-species genomic diversity. However, because of genome size, a proportionately small amount of variation creates ample opportunities for both rare mutations that may cause disease as well as more common genetic variations that may be important in disease modification or pharmacogenetics. Primarily because of the East African origin of modern humans, individuals of African ancestry (AA) exhibit greater degrees of genetic diversity than more recently established populations, such as those of European ancestry (EA) or Asian ancestry. Those population effects extend to differences in frequency of common gene variants that may be important in heart failure natural history or therapy. For cell-signaling mechanisms important in heart failure, we review and present new data for genetic variation between AA and EA populations. Data indicate that: 1) neurohormonal signaling mechanisms frequently (16 of the 19 investigated polymorphisms) exhibit racial differences in the allele frequencies of variants comprising key constituents; 2) some of these differences in allele frequency may differentially affect the natural history of heart failure in AA compared with EA individuals; and 3) in many cases, these differences likely play a role in observed racial differences in drug or device response.
    12/2014; DOI:10.1016/j.jchf.2014.06.010
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    ABSTRACT: Rationale: H2RA use is common and may act directly on the heart through myocardial H2 receptors or indirectly through changes in pulmonary vascular resistance. Objective: To determine the relationship between histamine H2 receptor antagonist (H2RA) use and right ventricular (RV) morphology. Methods: We studied 4,124 participants in the Multi-Ethnic Study of Atherosclerosis without overt cardiovascular disease who had magnetic resonance imaging (MRI) assessment of RV morphology and ascertainment of medication use. Multivariable linear regression estimated cross-sectional associations between H2RA use and RV morphology after adjusting for demographics, anthropometrics, smoking status, diabetes mellitus and hypertension. Further adjustment for co-medication use, left ventricular (LV) parameters, lung structure and function, renal function, or inflammatory markers were considered in separate models. Analyses in a sub-cohort restricted to H2RA or proton pump inhibitor (PPI) users accounted for confounding by the indication of gastroesophageal reflux disease. Measurements and Main Results: H2RA use was associated with lower RV mass (-0.7 g, 95% confidence interval (CI): -1.2 to -0.2 g, p=0.004) and smaller RV end-diastolic volume (EDV) (-4.2 mL, 95% CI: -7.2 to -1.2 mL, p=0.006). This relationship was unchanged with adjustment for co-medication use, lung structure and function, renal function, and inflammation. The relationship with RV mass was independent of LV mass. Results were similar in a smaller sub-cohort restricted to PPI and H2RA users. Conclusion: H2RA use was associated with lower RV mass and smaller RVEDV. This finding is novel. Additional study of histamine and H2 receptors in cardiopulmonary diseases affecting the RV may have direct clinical relevance.
    10/2014; DOI:10.1513/AnnalsATS.201407-344OC
  • Michael R Bristow
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    Journal of Cardiac Failure 08/2014; 20(8S):S82. DOI:10.1016/j.cardfail.2014.06.233 · 3.07 Impact Factor
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    ABSTRACT: Atrial Fibrillation and heart failure with reduced left ventricular ejection fraction have interrelated pathophysiologies. New onset atrial fibrillation in heart failure patients has been associated with increased mortality, but has not been definitively related to clinical heart failure progression.
    The American Journal of Medicine 06/2014; 127(10). DOI:10.1016/j.amjmed.2014.06.006 · 5.30 Impact Factor
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    ABSTRACT: -Remodeling of myocardial phospholipids has been reported in various forms of heart failure for decades, but the mechanism and pathophysiological relevance of this phenomenon have remained unclear. We examined the hypothesis that delta-6 desaturase (D6D), the rate limiting enzyme in long-chain polyunsaturated fatty acid (PUFA) biosynthesis, mediates the signature pattern of fatty acid redistribution observed in myocardial phospholipids following chronic pressure overload, and explored plausible links between this process and disease pathogenesis. -Compositional analysis of phospholipids from hearts explanted from patients with dilated cardiomyopathy revealed elevated PUFA product/precursor ratios reflective of D6D hyperactivity, manifesting primarily as lower levels of linoleic acid with reciprocally higher levels of arachidonic and docosahexaenoic acids. This pattern of remodeling was attenuated in failing hearts chronically unloaded with a left ventricular assist device. Chronic inhibition of D6D in vivo reversed similar patterns of myocardial PUFA redistribution in rat models of pressure overload and hypertensive heart disease, and significantly attenuated cardiac hypertrophy, fibrosis and contractile dysfunction in both models. D6D inhibition also attenuated myocardial elevations in pathogenic eicosanoid species, lipid peroxidation, and ERK1/2 activation; normalized cardiolipin composition in mitochondria; reduced circulating levels of inflammatory cytokines; and elicited model-specific effects on cardiac mitochondrial respiratory efficiency, NFκB activation and caspase activities. -These studies demonstrate a pivotal role of essential fatty acid metabolism though D6D in myocardial phospholipid remodeling induced by hemodynamic stress, and reveal novel links between this phenomenon and the propagation of multiple pathogenic systems involved in maladaptive cardiac remodeling and contractile dysfunction.
    Circulation Heart Failure 11/2013; 7(1). DOI:10.1161/CIRCHEARTFAILURE.113.000744 · 5.95 Impact Factor
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    ABSTRACT: The complexity of standard medical treatment for heart failure is growing, and such therapy typically involves 5 or more different medications. Given these pressures, there is increasing interest in harnessing cardiovascular biomarkers for clinical application to more effectively guide diagnosis, risk stratification, and therapy. It may be possible to realize an era of personalized medicine for heart failure treatment in which therapy is optimized and costs are controlled. The direct mechanistic coupling of biologic processes and therapies achieved in cancer treatment remains elusive in heart failure. Recent clinical trials and meta-analyses of biomarkers in heart failure have produced conflicting evidence. In this article, which comprises a summary of discussions from the Global Cardiovascular Clinical Trialists Forum held in Paris, France, we offer a brief overview of the background and rationale for biomarker testing in heart failure, describe opportunities and challenges from a regulatory perspective, and summarize current positions from government agencies in the United States and European Union.
    Journal of cardiac failure 08/2013; 19(8):592-9. DOI:10.1016/j.cardfail.2013.05.012 · 3.07 Impact Factor
  • Ryan Aleong, William H. Sauer, Gordon Davis, Michael R. Bristow
    Journal of Cardiac Failure 08/2013; 19(8):S24. DOI:10.1016/j.cardfail.2013.06.082 · 3.07 Impact Factor
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    ABSTRACT: This study assessed the impact of bucindolol, a beta-blocker/sympatholytic agent, on the development of atrial fibrillation (AF) in advanced chronic heart failure with reduced left ventricular ejection fraction (HFREF) patients enrolled in the BEST (Beta-Blocker Evaluation of Survival Trial). β-Blockers have modest efficacy for AF prevention in HFREF patients. Bucindolol's effects on HF and ventricular arrhythmic endpoints are genetically modulated by β1- and α2c-adrenergic receptor (AR) polymorphisms that can be used to subdivide HFREF populations into those with bucindolol effectiveness levels that are enhanced, unchanged, or lost. BEST enrolled 2,708 New York Heart Association (NYHA) class III to IV HFREF patients. A substudy in which 1,040 patients' DNA was genotyped for the β1-AR position 389 Arg/Gly and the α2c322-325 wild type (Wt)/deletion (Del) polymorphisms, and new-onset AF was assessed from adverse event case report forms or electrocardiograms at baseline and at 3 and 12 months. In the entire cohort, bucindolol reduced the rate of new-onset AF compared to placebo by 41% (hazard ratio [HR]: 0.59 [95% confidence interval (CI): 0.44 to 0.79], p = 0.0004). In the 493 β1389 arginine homozygotes (Arg/Arg) in the DNA substudy, bucindolol reduced new-onset AF by 74% (HR: 0.26 [95% CI: 0.12 to 0.57]), with no effect in β1389 Gly carriers (HR: 1.01 [95% CI: 0.56 to 1.84], interaction test = 0.008). When β1389 Gly carriers were subdivided by α2c Wt homozygotes (n = 413, HR: 0.94 [95% CI: 0.48 to 1.82], p = 0.84) or Del variant carriers (n = 134, HR: 1.33 [95% CI: 0.32 to 5.64], p = 0.70), there was a positive interaction test (p = 0.016) when analyzed with β1389 Arg homozygotes. Bucindolol prevented new-onset AF; β1 and α2c polymorphisms predicted therapeutic response; and the 47% of patients who were β1389 Arg homozygotes had an enhanced effect size of 74%. (Beta-Blocker Evaluation in Survival Trial [BEST]; NCT00000560).
    08/2013; 1(4):338-344. DOI:10.1016/j.jchf.2013.04.002
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    ABSTRACT: BACKGROUND: -Patients with heart failure and coronary artery disease often undergo coronary artery bypass grafting (CABG) but assessment of the risk of an adverse outcome in these patients is difficult. To evaluate the ability of biomarkers to contribute independent prognostic information in these patients, we measured levels in patients enrolled in the Biomarker Sub-studies of the Surgical Treatment for Ischemic Heart Failure (STICH) trials. Patients in STICH Hypothesis 1 were randomized to medical therapy or CABG whereas those in STICH Hypothesis 2 were randomized to CABG or CABG with left ventricular reconstruction. METHODS AND RESULTS: -In sub-study patients assigned to STICH Hypothesis 1 (n=606), plasma levels of sTNFR-1 and BNP were highly predictive of the primary outcome variable of mortality by univariate analysis (BNP χ(2)=40.6; p<0.0001: sTNFR-1 χ(2)=38,9; p<0.0001). When considered in the context of multivariable analysis, both BNP and sTNFR-1 contributed independent prognostic information beyond the information provided by a large array of clinical factors independent of treatment assignment. Consistent results were seen when assessing the predictive value of BNP and sTNFR-1 in patients assigned to STICH Hypothesis 2 (n=626). Both plasma levels of BNP (χ(2)=30.3) and sTNFR-1 (χ(2)=45.5) were highly predictive in univariate analysis (p<0.0001) as well as in multivariable analysis for the primary endpoint of death or cardiac hospitalization. In multivariable analysis, the prognostic information contributed by BNP (χ(2)=6.0; p=0.049) and sTNFR-1 (χ(2)=8.8; p=0.003) remained statistically significant even after accounting for other clinical information. Although the biomarkers added little discriminatory improvement to the clinical factors (increase in c-index ≤ 0.1), Net Reclassification Improvement (NRI) for the primary endpoints was 0.29 for BNP and 0.21 for sTNFR-1in the Hypothesis 1 cohort, and 0.15 for BNP and 0.30 for sTNFR-1 in the Hypothesis 2 cohort, reflecting important predictive improvement. CONCLUSIONS: -Elevated levels of sTNFR-1 and BNP are strongly associated with outcomes, independent of therapy, in two large and independent studies, thus providing important cross-validation for the prognostic importance of these two biomarkers.
    Circulation Heart Failure 04/2013; 6(3). DOI:10.1161/CIRCHEARTFAILURE.112.000185 · 5.95 Impact Factor
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    Journal of the American College of Cardiology 03/2013; 61(10). DOI:10.1016/S0735-1097(13)60714-7 · 15.34 Impact Factor
  • Michael R. Bristow, Ryan G. Aleong
    02/2013; 1(1):29–30. DOI:10.1016/j.jchf.2012.10.001
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    ABSTRACT: BACKGROUND: -In patients with chronic heart failure and reduced left ventricular ejection fraction (HFREF) β-blockers prevent cardiac arrhythmias, including ventricular tachycardia/fibrillation (VT/VF). We hypothesized that prevention of ventricular arrhythmias by the β-blocker/sympatholytic agent bucindolol is influenced by genetic variation in adrenergic receptors (ARs). METHODS AND RESULTS: -From a substudy of the β-Blocker Evaluation of Survival Trial (BEST, n = 1040), we identified those with the high functioning 389Arg vs. the lower function 389Gly β(1) adrenergic receptor (AR) variant, and the loss of function (α2C)322-325 AR deletion vs. the 322-325 wild type (Wt)/deletion (Del) variant. VT/VF was recorded on case report forms as an adverse event. There were 493 Arg 389 β(1) receptor homozygotes (β(1)389 Arg/Arg) vs. 547 Gly389 carriers and 207 (α2C)322-325 Del carriers vs. 833 homozygous Wts ((α2C)322-325 Wt/Wt). In all genotypes bucindolol was associated with a lower incidence of VT/VF (subhazard ratio (SHR) 0.42 (0.27, 0.64), P=0.00006). Bucindolol reduced VT/VF in β(1)389 Arg homozygotes (SHR 0.26 (0.14, 0.50), P=0.00005) but not in β(1)389 Gly carriers (SHR 0.60 (0.34, 1.07), P=0.09). For genotype combinations, the (α2C)322-325 polymorphism altered the VT/VF bucindolol response in β(1)389 Gly carriers, with (α2C) Del genotypes associated with complete efficacy loss. A test of interaction was statistically significant (P=0.028) for treatment group and a β(1)389/(α2C)322-325 three genotype construct, effectively identifying patients who exhibited enhanced response, no substantial response modification and loss of response. CONCLUSIONS: -Bucindolol prevents VT/VF in HFREF subjects, and this effect is modulated by β(1)389 Arg/Gly and (α2C)322-325 Wt/Del AR polymorphisms.
    Circulation Arrhythmia and Electrophysiology 12/2012; 6(1). DOI:10.1161/CIRCEP.111.969618 · 5.42 Impact Factor
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    ABSTRACT: AIMS: There is little evidence of beta-blocker treatment benefit in patients with heart failure and reduced left ventricular ejection fraction (HFREF) and atrial fibrillation (AF). We investigated the effects of bucindolol in HFREF patients with AF enrolled in the Beta-blocker Evaluation of Survival Trial (BEST). METHODS AND RESULTS: A post-hoc analysis of patients in BEST with and without AF was performed to estimate the effect of bucindolol on mortality and hospitalization. Patients were also evaluated for treatment effects on heart rate and the influence of beta(1)-adrenergic receptor position 389 (β(1)389) arginine (Arg) vs. glycine (Gly) genotypes. In the 303/2708 patients in AF, patients receiving bucindolol were more likely to achieve a resting heart rate ≤80 b.p.m. at 3 months (P < 0.005) in the absence of treatment-limiting bradycardia. In AF patients and sinus rhythm (SR) patients who achieved a resting heart rate ≤80 b.p.m., there were beneficial treatment effects on cardiovascular mortality/cardiovascular hospitalization [hazard ratio (HR) 0.61, P = 0.025, and 0.79, P = 0.002]. Without achieving a resting heart rate ≤80 b.p.m., there were no treatment effects on events in either group. β(1)389-Arg/Arg AF patients had nominally significant reductions in all-cause mortality/HF hospitalization and cardiovascular mortality/hospitalization with bucindolol (HR 0.23, P = 0.037 and 0.28, P = 0.039), whereas Gly carriers did not. There was no evidence of diminished heart rate response in β(1)389-Arg homozygotes. CONCLUSION: In HFREF patients with AF, bucindolol was associated with reductions in composite HF endpoints in those who achieved a resting heart rate ≤80 b.p.m. and nominally in those with the β(1)389-Arg homozygous genotype.
    European Journal of Heart Failure 12/2012; 15(3). DOI:10.1093/eurjhf/hfs181 · 6.58 Impact Factor
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    ABSTRACT: BACKGROUND: Heart failure patients with reduced ejection fraction (HFREF) are heterogenous, and our ability to identify patients likely to respond to therapy is limited. We present a method of identifying disease subtypes using high-dimensional clinical phenotyping and latent class analysis that may be useful in personalizing prognosis and treatment in HFREF. METHODS: A total of 1121 patients with nonischemic HFREF from the β-blocker Evaluation of Survival Trial were categorized according to 27 clinical features. Latent class analysis was used to generate two latent class models, LCM A and B, to identify HFREF subtypes. LCM A consisted of features associated with HF pathogenesis, whereas LCM B consisted of markers of HF progression and severity. The Seattle Heart Failure Model (SHFM) Score was also calculated for all patients. Mortality, improvement in left ventricular ejection fraction (LVEF) defined as an increase in LVEF ≥5% and a final LVEF of 35% after 12 months, and effect of bucindolol on both outcomes were compared across HFREF subtypes. Performance of models that included a combination of LCM subtypes and SHFM scores towards predicting mortality and LVEF response was estimated and subsequently validated using leave-one-out cross-validation and data from the Multicenter Oral Carvedilol Heart Failure Assessment Trial. RESULTS: A total of 6 subtypes were identified using LCM A and 5 subtypes using LCM B. Several subtypes resembled familiar clinical phenotypes. Prognosis, improvement in LVEF, and the effect of bucindolol treatment differed significantly between subtypes. Prediction improved with addition of both latent class models to SHFM for both 1-year mortality and LVEF response outcomes. CONCLUSIONS: The combination of high-dimensional phenotyping and latent class analysis identifies subtypes of HFREF with implications for prognosis and response to specific therapies that may provide insight into mechanisms of disease. These subtypes may facilitate development of personalized treatment plans.
    PLoS ONE 11/2012; 7(11):e48184. DOI:10.1371/journal.pone.0048184 · 3.53 Impact Factor

Publication Stats

30k Citations
3,554.49 Total Impact Points

Institutions

  • 1992–2015
    • University of Colorado
      • Division of Cardiology
      Denver, Colorado, United States
  • 2014
    • University of South Florida
      Tampa, Florida, United States
  • 2013
    • University of North Carolina at Chapel Hill
      North Carolina, United States
  • 2012
    • Duke University
      Durham, North Carolina, United States
    • Duke University Medical Center
      Durham, North Carolina, United States
  • 2010
    • Case Western Reserve University School of Medicine
      Cleveland, Ohio, United States
  • 2008–2010
    • University of Denver
      Denver, Colorado, United States
  • 1997–2010
    • Columbia University
      • • Department of Medicine
      • • College of Physicians and Surgeons
      New York City, NY, United States
  • 1987–2010
    • University of Utah
      • • Division of Cardiology
      • • Department of Internal Medicine
      • • Division of Cardiothoracic Surgery
      Salt Lake City, Utah, United States
  • 1991–2008
    • University of California, Los Angeles
      • Department of Pediatrics
      Los Ángeles, California, United States
  • 2007
    • University of California, San Francisco
      San Francisco, California, United States
  • 1982–2007
    • Stanford University
      • Department of Medicine
      Palo Alto, California, United States
  • 2005
    • Baylor College of Medicine
      • Winters Center for Heart Failure Research
      Houston, TX, United States
    • University of Washington Seattle
      • Division of Cardiology
      Seattle, WA, United States
    • The Ohio State University
      • Division of Medical Oncology
      Columbus, OH, United States
  • 1992–2005
    • University of Colorado Hospital
      • • Division of Cardiology
      • • Department of Medicine
      Denver, Colorado, United States
  • 2004
    • Colorado College
      Colorado Springs, Colorado, United States
  • 1999–2004
    • University of Sioux Falls
      Sioux Falls, South Dakota, United States
  • 1988–2004
    • Johns Hopkins University
      • • Division of Cardiology
      • • Department of Medicine
      Baltimore, Maryland, United States
  • 2003
    • University of Colorado at Boulder
      • Department of Molecular, Cellular, and Developmental Biology (MCDB)
      Boulder, CO, United States
  • 1998
    • Rush University Medical Center
      • Section of Cardiology
      United States
  • 1996
    • University of Texas Southwestern Medical Center
      • Department of Internal Medicine
      Dallas, TX, United States
  • 1995
    • Montreal Heart Institute
      Montréal, Quebec, Canada
  • 1989–1991
    • Salt Lake City Community College
      Salt Lake City, Utah, United States
    • University of Duisburg-Essen
      Essen, North Rhine-Westphalia, Germany
  • 1986
    • Dallas Zoo
      Dallas, Texas, United States
  • 1981–1985
    • Stanford Medicine
      • Department of Medicine
      Stanford, California, United States