Obese-Inflammatory Phenotypes in Heart Failure With Preserved Ejection Fraction.

CIRCULATION-HEART FAILURE(2020)

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摘要
BACKGROUND:Comorbidity-driven microvascular inflammation is posited as a unifying pathophysiologic mechanism for heart failure with preserved ejection fraction (HFpEF). Obesity is proinflammatory and common in HFpEF. We hypothesized that unique obesity-inflammation HFpEF phenotypes exist and are associated with differences in clinical features, fibrosis biomarkers, and functional performance. METHODS:Patients (n=301) from 3 HFpEF clinical trials were studied. Unsupervised machine learning (hierarchical clustering) with obese status and 13 inflammatory biomarkers as input variables was performed. Associations of clusters with HFpEF severity and fibrosis biomarkers (PIIINP [procollagen III N-terminal peptide], CITP [C-telopeptide for type I collagen], IGFBP7 [insulin-like growth factor-binding protein-7], and GAL-3 [galectin-3]) were assessed. RESULTS:Hierarchical clustering revealed 3 phenotypes: pan-inflammatory (n=129; 64% obese), noninflammatory (n=83; 55% obese), and obese high CRP (C-reactive protein; n=89; 98% obese). The pan-inflammatory phenotype had more comorbidities and heart failure hospitalizations; higher left atrial volume, NT-proBNP (N-terminal pro-B-type natriuretic peptide), and fibrosis biomarkers; and lower glomerular filtration rate, peak oxygen consumption, 6-minute walk distance, and active hours/day (P<0.05 for all). The noninflammatory phenotype had the most favorable values for all measures. The obese high CRP phenotype resembled the noninflammatory phenotype except for isolated elevation of CRP and lower functional performance. Hierarchical cluster assignment was independent of CRP genotype combinations that alter CRP levels and more biologically plausible than other clustering approaches. Multiple traditional analytic techniques confirmed and extended the hierarchical clustering findings. CONCLUSIONS:Unique obesity-inflammation phenotypes exist in HFpEF and are associated with differences in comorbidity burden, HFpEF severity, and fibrosis. These data support comorbidity-driven microvascular inflammation as a pathophysiologic mechanism for many but not all HFpEF patients.
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关键词
cluster analysis,fibrosis,heart failure,inflammation,machine learning,obesity
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