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Phenomapping for the Identification of Hypertensive Patients with the Myocardial Substrate for Heart Failure with Preserved Ejection Fraction

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Abstract

We sought to evaluate whether unbiased machine learning of dense phenotypic data (“phenomapping”) could identify distinct hypertension subgroups that are associated with the myocardial substrate (i.e., abnormal cardiac mechanics) for heart failure with preserved ejection fraction (HFpEF). In the HyperGEN study, a population- and family-based study of hypertension, we studied 1273 hypertensive patients utilizing clinical, laboratory, and conventional echocardiographic phenotyping of the study participants. We used machine learning analysis of 47 continuous phenotypic variables to identify mutually exclusive groups constituting a novel classification of hypertension. The phenomapping analysis classified study participants into 2 distinct groups that differed markedly in clinical characteristics, cardiac structure/function, and indices of cardiac mechanics (e.g., phenogroup #2 had a decreased absolute longitudinal strain [12.8 ± 4.1 vs. 14.6 ± 3.5%] even after adjustment for traditional comorbidities [p < 0.001]). The 2 hypertension phenogroups may represent distinct subtypes that may benefit from targeted therapies for the prevention of HFpEF.

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Abbreviations

BIC:

Bayesian information criterion

BMI:

Body mass index

CAD:

Coronary artery disease

CV:

Cardiovascular

DBP:

Diastolic blood pressure

CS:

Circumferential strain

LS:

Longitudinal strain

RS:

Radial strain

HyperGEN:

Hypertension Genetic Epidemiology Network

LV:

Left ventricular

SBP:

Systolic blood pressure

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Authors and Affiliations

  1. Department of Medicine, Massachusetts General Hospital, Boston, MA, USA

    Daniel H. Katz

  2. Division of Cardiology, Department of Medicine, Institute for Human Genetics, California Institute for Quantitative Biosciences, and Cardiovascular Research Institute, University of California, San Francisco, CA, USA

    Rahul C. Deo

  3. Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St., Suite 600, Chicago, IL, 60611, USA

    Frank G. Aguilar, Senthil Selvaraj, Eva E. Martinez, Lauren Beussink-Nelson & Sanjiv J. Shah

  4. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Kwang-Youn A. Kim & Jie Peng

  5. Departments of Epidemiology and Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

    Marguerite R. Irvin & Hemant Tiwari

  6. Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO, USA

    D. C. Rao

  7. School of Public Health, University of Kentucky, Lexington, KY, USA

    Donna K. Arnett

Authors
  1. Daniel H. Katz
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  2. Rahul C. Deo
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  4. Senthil Selvaraj
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  7. Kwang-Youn A. Kim
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  11. D. C. Rao
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  13. Sanjiv J. Shah
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Corresponding author

Correspondence to Sanjiv J. Shah.

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Conflicts of Interest

The authors declare that they have no conflict of interest.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Funding Sources

The HyperGEN cardiac mechanics ancillary study was funded by the National Institutes of Health (NIH; R01 HL107577 to S.J.S.). The HyperGEN echocardiography ancillary study was funded by the National Institutes of Health (R01 HL55673 to D.K.A.). The HyperGEN parent study was funded by cooperative agreements (U10) with the National Heart, Lung, and Blood Institute: HL54471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515. Dr. Shah was also supported by NIH HL127028 and American Heart Association grants #16SFRN28780016 and 15CVGPSD27260148). Dr. Katz was supported by an Alpha Omega Alpha Carolyn L. Kuckein Research Fellowship.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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None.

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Associate Editor Paul J. R. Barton oversaw the review of this article

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Katz, D.H., Deo, R.C., Aguilar, F.G. et al. Phenomapping for the Identification of Hypertensive Patients with the Myocardial Substrate for Heart Failure with Preserved Ejection Fraction. J. of Cardiovasc. Trans. Res. 10, 275–284 (2017). https://doi.org/10.1007/s12265-017-9739-z

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