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.
|Number of pages||10|
|Journal||Journal of Cardiovascular Translational Research|
|State||Published - Jun 1 2017|
Bibliographical noteFunding Information:
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.
© 2017, Springer Science+Business Media New York.
- Cardiac mechanics
- Heart failure with preserved ejection fraction
- Machine learning
- Speckle-tracking echocardiography
ASJC Scopus subject areas
- Molecular Medicine
- Pharmaceutical Science
- Cardiology and Cardiovascular Medicine