Visceral adiposity, muscle composition, and exercise tolerance in heart failure with preserved ejection fraction

Abstract

Aims Visceral adipose tissue (AT) promotes inflammation and may be associated with disease progression in heart failure with preserved ejection fraction (HFpEF). We characterized regional AT distribution in HFpEF patients and controls and analysed associations with co-morbidities and exercise tolerance. Methods and results Magnetic resonance imaging was performed to quantify epicardial, liver, abdominal, and thigh skeletal muscle AT. We assessed New York Heart Association (NYHA) class, 6 min walk distance, and global well-being score. Multivariable linear regression models adjusting for body surface area were used. We studied 55 HFpEF patients (41 women, mean age 67 ± 11 years) and 33 controls (21 women, mean age 57 ± 10 years). Epicardial AT (median [interquartile range] 4.6 [2.0] vs. 3.2 [1.4] mm, P < 0.001), thigh intermuscular fat (11.0 [11.5] vs. 5.0 [2.7] cm 2 , P < 0.001) and liver fat fraction (6.4% [6.1] vs. 4.1% [5.5], P = 0.001) were higher in HFpEF patients than controls. Women with HFpEF had higher abdominal and thigh subcutaneous AT than men. Greater thigh intermuscular fat was associated with higher blood pressure (β [SE] 0.73 [0.17], P < 0.001) and diabetes (odds ratio [95% confidence interval] 1.2 [1.0-1.5], P = 0.03). Greater thigh intramuscular fat was associated with both worse NYHA class (β [SE] 2.7 [1.0], P = 0.01) and shorter 6 min walk distance (β [SE] À4.1 [1.9], P = 0.03), and greater epicardial AT (β [SE] À0.2 [0.1], P < 0.001) and liver fat fraction (β [SE] À0.4 [0.2], P = 0.04) were associated with lower global well-being score. Conclusions Heart failure with preserved ejection fraction patients have increased epicardial, liver, and skeletal muscle fat compared with controls out of proportion to their increased body size, and adiposity was associated with worse NYHA class and exercise tolerance in HFpEF. These results provide the basis for further investigation into the effect of interventions to reduce regional AT distribution in relation to HFpEF symptoms and pathophysiology.

The Role of Systemic Microvascular Dysfunction in Heart Failure with Preserved Ejection Fraction

“…Excess epicardial adipose tissue (EAT) was found in HFpEF patients compared to HFrEF and healthy controls [ 135 , 136 ], which was associated with worse exercise capacity and worse survival [ 135 ]. Higher cardiac filling pressures were also found in obese HFpEF patients with excess EAT compared to those without excess EAT [ 125 ].…”

“…The strong influence of EAT on local cardiac structure and function is further supported by a recent cardiac MRI study in a mixed HFpEF/HF cohort with mildly reduced ejection fraction (HFmrEF) [ 137 ]. In addition to excess EAT, HFpEF patients showed several enlarged adipose tissue depots (visceral and intramuscular) compared to controls, and these enlarged depots were associated with impaired exercise tolerance [ 74 , 136 ] and higher filling pressures [ 138 ]. The latter finding was, however, only present in female HFpEF patients [ 138 ], supporting the concept that sex differences in fat tissue properties play a role in HFpEF [ 4 ], which is reviewed in detail elsewhere [ 139 , 140 ].…”

Epicardial Fat Expansion in Diabetic and Obese Patients With Heart Failure and Preserved Ejection Fraction—A Specific HFpEF Phenotype

“…Recently, a growing number of publications also demonstrate the easiness of epicardial fat quantification using artificial intelligence (AI) algorithms (69). Beside the heart, the same approach can also be applied to other organ regions in patients with HFpEF like the abdomen (70). Since CMR allows imaging also in severely obese patients, functional evaluation of the systolic and diastolic function including myocardial work is feasible (71).…”

Coronary Endothelial Dysfunction in People Living With HIV Is Related to Body Fat Distribution

“…29 A custom-made MATLAB (MathWorks, Natick, MA) tool was used to segment and separate abdominal fat into SAT and VAT compartments using a semiautomated algorithm for quantification of each compartment. 30…”