title: Phenomapping for the Identification of Hypertensive Patients with the Myocardial Substrate for Heart Failure with Preserved Ejection Fraction.
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.
authors.affiliation: Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Daniel H
authors.initials: DH
authors.lastname: Katz
authors.affiliation: 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.
authors.forename: Rahul C
authors.initials: RC
authors.lastname: Deo
authors.affiliation: Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St., Suite 600, Chicago, IL, 60611, USA.
authors.forename: Frank G
authors.initials: FG
authors.lastname: Aguilar
authors.affiliation: Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St., Suite 600, Chicago, IL, 60611, USA.
authors.forename: Senthil
authors.initials: S
authors.lastname: Selvaraj
authors.affiliation: Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St., Suite 600, Chicago, IL, 60611, USA.
authors.forename: Eva E
authors.initials: EE
authors.lastname: Martinez
authors.affiliation: Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St., Suite 600, Chicago, IL, 60611, USA.
authors.forename: Lauren
authors.initials: L
authors.lastname: Beussink-Nelson
authors.affiliation: Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
authors.forename: Kwang-Youn A
authors.initials: KA
authors.lastname: Kim
authors.affiliation: Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
authors.forename: Jie
authors.initials: J
authors.lastname: Peng
authors.affiliation: Departments of Epidemiology and Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: Marguerite R
authors.initials: MR
authors.lastname: Irvin
authors.affiliation: Departments of Epidemiology and Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: Hemant
authors.initials: H
authors.lastname: Tiwari
authors.affiliation: Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.
authors.forename: D C
authors.initials: DC
authors.lastname: Rao
authors.affiliation: School of Public Health, University of Kentucky, Lexington, KY, USA.
authors.forename: Donna K
authors.initials: DK
authors.lastname: Arnett
authors.affiliation: Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St., Suite 600, Chicago, IL, 60611, USA. sanjiv.shah@northwestern.edu.
authors.forename: Sanjiv J
authors.initials: SJ
authors.lastname: Shah
mesh_terms: D000328:Adult; D000368:Aged; D001696:Biomechanical Phenomena; D001794:Blood Pressure; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D015150:Echocardiography, Doppler; D005260:Female; D006333:Heart Failure / Q000000981:diagnostic imaging / Q000209:etiology* / Q000503:physiopathology; D006801:Humans; D006973:Hypertension / Q000145:classification / Q000150:complications* / Q000000981:diagnostic imaging / Q000503:physiopathology; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated; D010641:Phenotype; D011237:Predictive Value of Tests; D011379:Prognosis; D018570:Risk Assessment; D012307:Risk Factors; D013314:Stress, Mechanical; D013318:Stroke Volume; D014481:United States
keywords: Cardiac mechanics; Heart failure with preserved ejection fraction; Hypertension; Machine learning; Speckle-tracking echocardiography