Plasma levels of free fatty acid differ in patients with left ventricular preserved, mid-range, and reduced ejection fraction

Plasma levels of free fatty acid differ in patients with left ventricular preserved, mid-range,... Background: Free fatty acids (FFAs) predicted the risk of heart failure (HF) and were elevated in HF with very low left ventricular ejection fraction (LVEF) compared to healthy subjects. The aim of this study was to investigate whether total levels of FFA in plasma differed in patients with HF with preserved (HFpEF), mid-range (HFmrEF), and reduced ejection fraction (HFrEF) and the association with the three categories. Methods: One hundred thirty-nine patients with HFpEF, HFmrEF and HFrEF were investigated in this study. Plasma FFA levels were measured using commercially available assay kits, and LVEF was calculated by echocardiography with the Simpson biplane method. Dyspnea ranked by New York Heart Association (NYHA) was also identified. Results: FFA concentrations were higher in HFrEF than in HFmrEF and HFpEF, respectively (689 ± 321.5 μmol/L vs. 537.9 ± 221.6 μmol/L, p = 0.036; 689 ± 321.5 μmol/L vs. 527.5 ± 185.5 μmol/L, p = 0.008). No significant differences in FFA levels were found between HFmrEF and HFpEF (537.9 ± 221.6 μmol/L vs. 527.5 ± 185.5 μmol/L, p = 0.619). In addition, we found a negative correlation between FFA levels and LVEF (regression coefficient: − 0.229, p = 0.004) and a positive correlation between FFAs and NYHA class (regression coefficient: 0.214, p = 0.014) after adjustment for clinical characteristic, medical history and therapies. ROC analysis revealed that FFAs predicted HFrEF across the three categories (AUC: 0.644, p = 0.005) and the optimal cut-off level to predict HFrEF was FFA levels above 575 μmol/L. Conclusions: FFA levels differed across the three categories, which suggests that energy metabolism differs between HFpEF, HFmrEF and HFrEF. Keywords: Heart failure, Preserved ejection fraction, Mid-range ejection fraction, Reduced ejection fraction, Free fatty acid Background < 40% are defined as reduced EF (HFrEF), and therapies During the past 20 years, considerable progress in the have been shown to reduce both morbidity and mortality treatment has improved the survival of patients with [2, 3]. Patients with EF ≥50% are generally considered as heart failure (HF). However HF remains a leading cause preserved EF (HFpEF), and therapies mainly directing at of morbidity and mortality throughout the world [1]. symptoms, comorbidities and risk factors, failed to confer Heart failure is a clinical syndrome characterized by typ- a survival benefit [4, 5]. A ‘grey zone’ of EF 40–49% was ical symptoms and signs resulting from Left ventricular formally termed as heart failure with mid-range ejection ejection fraction (LVEF), which has an essential role in fraction (HFmrEF) in the recent European Society of phenotyping and guiding the therapy [2]. Patients with EF Cardiology (ESC) HF guidelines. However, direct evidence on this group remains lacking and whether HFmrEF pa- tients are characterized by diverse demographic, or clinical features, different co-morbidities and distinct response to * Correspondence: zhuningccc@126.com therapies should be compared to HFpEF or HFrEF [6]. Department of Cardiology, The Third Clinical College of Wenzhou Medical Identifying HFmrEF as a separate group will stimulate University, Wenzhou People’s Hospital, No. 57 Canghou Street, Wenzhou 325000, Zhejiang Province, People’s Republic of China © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 2 of 8 research into the underlying characteristics, pathophysi- Biochemical measurements ology and treatment of this group of patients, and contrib- Following venous blood sample collection, Blood was ute to the better understanding of HF. drawn into chilled glass tubes containing EDTA, placed Under physiological conditions, Free fatty acids (FFAs) on ice and centrifuged at 3000 rpm for 10 min. The releasing from adipose tissue are the major energy separated serum specimens were immediately frozen and sources of the heart, and fatty acids (FAs) are active stored at − 80 °C until the time of the assay. The FFA components of biological membranes [7]. Although serum levels were measured on biochemical instrument FFAs yield the highest ATP, β-oxidation of FFAs uses (Beckman Coulter, USA) by a commercially available FFA more oxygen than glycolysis metabolism. Hence, FFAs kit (Reebio, Ningbo, China). All of assays were conducted are less energy efficient and increase the burden of the according to manufacturer’s guidelines. myocardium in the patients with HF. Furthermore, numerous evidences suggest that blocking fatty acid Ethical considerations oxidation and increasing glucose oxidation can im- The study complied with the Declaration of Helsinki prove cardiac contractile function, leading to improve and was approved by the Wenzhou People’s Hospital prognosis in patients with HF [8, 9]. In general, circu- ethics committee, and all patients gave written informed lating FFAs may be a crucial regulator of myocardial consent. substrate metabolism in HF. The composition of FFAs could also influence myocar- Statistical analysis dial function. It is well known that elevated circulating All the data are presented as mean ± SD. As the data FFA levels could cause chronic inflammation, insulin re- included continuous variables and classification vari- sistance, and cardiovascular disease [10, 11]. These pro- ables, parameter and non-parameter methods were both cesses could occur in many tissues such as the heart, liver, used. Non-parametric tests were also used in case of skeletal muscle and pancreas. Previous studies showed non-normally distributed data. Comparisons were made that patients with HF had higher plasma FFAs than by Pearson chi-square for proportions and Mann– healthy controls [12]. Moreover, FFAs were independently Whitney test and Kruskal–Wallis test for continuous associated with incident HF in older adults [13]. However, variables. The correlation between plasma FFAs and HF FFA levels in patients with HFpEF, HFmrEF and HFrEF risk factors (hypertension, diabetes, weight, BMI, CHD), and the association of FFAs with the three categories re- LVEF and New York Heart Association (NYHA) class was mains unknown. assessed by Spearman rank correlation test. Multiple Thus, the main aim of this observatory study was to regression analysis with input selection method was used investigate whether total levels of FFA in plasma differed to adjust gender, smoking, hypertension, diabetes, coron- across the three categories and the association of FFA ary heart disease, prior revascularization, prior myocardial plasma levels with the extent of heart failure with the infarction, dilated myocardiopathy, atrial fibrillation, di- three categories. uretics, aldosteroneantagonists, beta-blockers, ACEI/ARB, digitoxin, statins and warfarin. The receiver operating Methods characteristic (ROC) curves for associations between Study population FFAs, as well as NT-proBNP and HFpEF, HFmrEF, and A total of 139 men and women were enrolled from HFrEF compared. All P<0.05 were considered significant. Wenzhou People’s Hospital. All these patients were di- agnosed with chronic HF according to contemporary Results guidelines. In addition, all the patients were symptom- A total of 139 patients was classified as HFpEF (n = 51, atic and were treated according to contemporary clin- 36.6%), HFmrEF (n = 39, 28.1%), and HFrEF (n = 49, ical guidelines. Patients were excluded from the study if 35.3%). Table 1 shows the baseline characteristics of the they had any recent acute coronary syndrome, stroke, study population, and most of clinical characteristics dif- immune system disorders, severe valvular disease, or fer across the three categories. HFmrEF was close to any other concomitant terminal disease. Upon entering HFpEF and HFrEF in terms of age, however HFmrEF the study, the set of baseline variables including previ- were more often male than HFpEF and less often male ous clinical history, treatments, the gender, height, and than HFrEF. In addition, the prevalence of hypertension, weight of all the patients were collected. LVEF were diabetes and dilated myocardiopathy were higher in calculated by echocardiography with the Simpson bi- HFmrEF than in HFpEF, but lower than in HFrEF. plane method. Based on the LVEF measured at time of There was more smoking, prior myocardial infarction in inclusion, patients were categorized as HFpEF as LVEF HFmrEF than in HFpEF and HFrEF while there was less ≥50%, HFmrEF as LVEF 40–49%, and HFrEF as LVEF coronary heart disease (CHD) and prior revascularization <40%. in HFmrEF than in HFpEF and HFrEF. There were no Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 3 of 8 Table 1 Characteristics according to categories of left ventricular ejection fraction (LVEF) HFpEF HFmrEF HFrEF Overall HFpEF vs. HFmrEF HFmrEF vs. HFrEF HFpEF vs. HFrEF (n = 51 36.6%) (n = 39 28.1%) (n = 49 35.3%) PP P P Characteristic Age, years 79.3 ± 8.9 77.2 ± 10.2 78.0 ± 11.8 0.553 0.297 0.626 0.501 Male gender 30(58.8%) 26(66.6%) 42(85.7%) <0.001 <0.05 <0.001 <0.001 Current smoking 15(29.4%) 12(30.7%) 15(30.6%) <0.001 <0.001 <0.001 <0.001 Hypertension 33(64.7%) 28(71.7%) 40(81.6%) <0.001 0.001 <0.001 <0.001 Diabetes 12(23.5%) 12(30.7%) 16(32.6%) <0.001 <0.001 0.001 <0.001 NYHA III/IV 37(72.5%) 30(76.9%) 44(89.7%) <0.001 <0.001 <0.001 <0.001 LVEF(%) 60.1 ± 6.6 44.5 ± 2.9 32.6 ± 4.1 <0.001 <0.001 <0.001 <0.001 Weight(kg) 59.4 ± 10.8 60.9 ± 10.2 60.0 ± 10.9 0.735 0.143 0.644 0.799 BMI 22.7 ± 4.0 22.9 ± 3.0 22.0 ± 3.2 0.791 0.654 0.775 0.526 Nt-proBNP 5825.8 ± 6484.2 9664 ± 10,189.1 11,248.1 ± 10,875.1 <0.05 <0.05 0.408 <0.05 Other medical history Coronary heart disease 41((80.3%) 29(74.3%) 39(79.5%) <0.001 <0.001 <0.001 <0.001 Prior revascularization 10(19.6%) 7(17.9%) 17(34.6%) <0.001 <0.001 <0.001 <0.001 Prior myocardial infarction 6(11.7%) 9(23%) 8(16.3) <0.001 <0.001 <0.001 <0.001 Dilated myocardiopathy 0(0%) 5(12.8%) 12(24.4%) <0.001 <0.001 <0.001 <0.001 Atrial fibrillation 29(56.8%) 17(43.5%) 16(32.6%) 0.203 0.833 <0.05 0.317 Therapies Diuretics 39(76.4%) 38(97.4%) 42(85.7%) <0.001 <0.001 <0.001 <0.001 Aldosteroneantagonists 38(77.5%) 26(66.6%) 34(69.3%) <0.001 <0.001 <0.05 <0.001 Beta-blockers 35(68.6%) 21(53.8%) 24(48.9%) 0.075 <0.05 0.831 0.072 ACEI/ARB 32(61.5%) 21(53.8%) 32(65.3%) <0.05 0.092 0.055 <0.05 Digitoxin 8(15.6%) 10(25.6%) 22(44.8%) <0.001 <0.001 <0.05 <0.001 Statins 34(66.6%) 28(71.7%) 33(67.3%) <0.001 <0.001 <0.001 0.001 Warfarin 15(29.4%) 6(15.3%) 6(12.2%) <0.001 <0.001 <0.001 <0.001 Data are presented as mean ± SD, or number or percentage of subjects NYHA New York Heart Association, LVEF left ventricular ejection fraction, BMI body Mass Index, Nt-proBNP N-terminal pro-B-type natriuretic peptide, ACE angiotensin-converting enzyme, ARB angiotensin II receptor blocker, p significance level differences in weight and BMI between HFpEF, HFmrEF, differences in levels of FFA were found between HFmrEF and HFrEF, however HFmrEF had higher weight than and HFpEF (537.9 ± 221.6 μmol/L vs. 527.5 ± 185.5 μmol/ HFpEF. HFmrEF had more atrial fibrillation than HFrEF, L, p = 0.619, Fig. 1). Our data showed FFAs were associ- but similar N-Terminal pro-brain natriuretic peptide ated with hypertension (regression coefficient: 0.156, (NT-proBNP) levels than HFrEF. NYHA III/IV was inter- p =0.033, Table 2), but there was no significant correl- mediate in HFmrEF. ation between plasma FFA levels and diabetes, weight, Regarding therapies, there were highest use of diuretics BMI, CHD (regression coefficient: 0.092, p = 0.28; re- and statins, intermediate use of digitoxin and warfarin, gression coefficient: 0.092, p = 0.28; regression coeffi- and lowest use of aldosteroneantagonist in HFmrEF. cient: 0.151, p = 0.076; regression coefficient: 0.00004, HFmrEF had similar rate of angiotensin-converting en- p =0.713 Table 2). There was still no significant cor- zyme (ACE)-inhibitors and angiotensin receptor blockers relation between plasma FFA levels and weight, BMI (ARBs) and lower rate of Beta-blocker than HFpEF. It was and CHD even after adjusting for gender, smoking, also found that The HFmrEF group had intermediate rate hypertension, diabetes, coronary heart disease, prior of digitoxin. revascularization, prior myocardial infarction, dilated FFA concentrations were higher in HFrEF than in myocardiopathy, atrial fibrillation, diuretics, aldostero- HFmrEF and HFpEF, respectively (689 ± 321.5 μmol/L vs. neantagonists, beta-blockers, ACEI/ARB, digitoxin, statins 537.9 ± 221.6 μmol/L, p = 0.036; 689 ± 321.5 μmol/L vs. and warfarin (regression coefficient: 0.114, p = 0.183; regres- 527.5 ± 185.5 μmol/L, p =0.008, Fig. 1). No significant sion coefficient: 0.214, p = 0.117; regression coefficient: Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 4 of 8 Table 3 Multiple regression analysis Regression coefficient P Weight 0.114 0.183 BMI 0.142 0.117 CHD 0.097 0.459 LVEF −0.229 0.004 NYHA class 0.214 0.014 BMI body Mass Index. CHD coronary heart disease, LVEF Left ventricular ejection fraction, NYHA New York Heart Association, p significance level NT-proBNP and LVEF and NYHA class (regression coeffi- cient: − 0.101, p = 0.025; regression coefficient: 0.234, p = 0.012). ROC analysis revealed FFA predicted HFrEF across the three categories (AUC: 0.644, p = 0.005, Fig. 4a)and the optimal cut-off level to predict HFrEF were FFA levels Fig. 1 Plasma FFA levels in patients with HFpEF, HFmrEF and HFrEF. above 575 μmol/L. ROC analysis showed NT-proBNP also *P<0.05, **P<0.01 predicted HFrEF across the three categories (AUC: 0.619, p = 0.021, Fig. 4b). 0.097, p = 0.459, Table 3). In contrast, we found a nega- tive correlation between FFA levels and LVEF (regres- Discussion sion coefficient: − 0.267, p =0.001, Fig. 2a). A negative This is a pilot study to compare FFAs in HFpEF, correlation was also found between NT-proBNP and HFmrEF, and HFrEF based on the newly defined HF LVEF (regression coefficient: − 0.264, p = 0.002, Fig. 2b). types in the 2016 ESC guideline. Despite a clinical pro- Moreover, there was a positive correlation between file similar to those with HFpEF or HFrEF, patients with FFAs as well as NT-proBNP and NYHA class (regres- HFmrEF have many different characteristics. In line sion coefficient: 0.202, p = 0.017, Fig. 2c; regression co- with previous researches [14–16], our results suggested efficient: 0.302, p < 0.001, Fig. 2d). FFA levels were that patients with HFmrEF constituted a specific HF higher in patients with NYHA class III and IV than in phenotype. In addition, we found that HFrEF had patients with NYHA class I and II (605.3 ± 264 μmol/L higher plasm FFA levels than HFpEF and HFmrEF. vs. 509.2 ± 189 μmol/L, p = 0.034, Fig. 3a). Meanwhile, However, plasma FFA levels in HFmrEF were similar to patients with NYHA class III and IV have also higher that in HFpEF. Plasm FFA levels were negatively associ- NT-proBNP (9933.5 ± 10,156 μmol/L vs. 4171 ± ated with LVEF and positively associated with NYHA 3545 μmol/L, p = 0.0044, Fig. 3b)Multipleregression class, which were similar to NT-proBNP. ROC curve analysis showed FFAs still significantly correlated with showed that FFAs and NT-proBNP predicted HFrEF LVEF and NYHA class after adjustment for gender, across the three categories. smoking, hypertension, diabetes, coronary heart disease, There were limited studies specifically comparing prior revascularization, prior myocardial infarction, HFpEF, HFmrEF and HFrEF, especially in Chinese popula- dilated myocardiopathy, atrial fibrillation, diuretics, tion. Our study showed that many clinical characteristics aldosteroneantagonists, beta-blockers, ACEI/ARB, digi- such as gender, hypertension, dilated myocardiopathy and toxin, statins and warfarin (regression coefficient: − 0.229, atrial fibrillation were on a continuum between HFpEF p = 0.004; regression coefficient: 0.214, p = 0.014, Table 3). and HFrEF but weight and BMI were similar in the three Similar results were found in the correlation between categories. In addition, HFmrEF had higher rates of cor- onary artery disease and revascularization. To the best of our knowledge, this is the first study to Table 2 Association of FFA levels with diabetes, hypertension, examine whether the association of plasma FFA con- weight, BMI and CHD centration with HFpEF, HFmrEF, and HFrEF. The Regression coefficient P associations between FFAs and risk factors including Diabetes 0.092 0.28 hypertension, atrial fibrillation, diabetes mellitus, and Hypertension 0.156 0.033 CHD for HF had rarely been reported. Free fatty acid Weight 0.092 0.28 elevation has been identified as a highly significant risk BMI 0.151 0.076 factor for hypertension [17]. Furthermore, it has been CHD 0.00004 0.713 demonstrated that elevated FFAs are positively associ- BMI body Mass Index, CHD coronary heart disease p significance level ated with systolic blood pressure in men and diastolic Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 5 of 8 Fig. 2 Association of FFA levels and NT-proBNP with left ventricular ejection fraction (a, b) and NYHA class (c, d) Fig. 3 Plasma FFA levels (a) and NT-proBNP levels (b) in patients with NYHA class I/II and NYHA class III/IV. *P<0.05, **P<0.01 Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 6 of 8 Fig. 4 ROC analysis of FFA (a) and NT-proBNP (b) in prediction of HFrEF blood pressure in women [18]. However, the prevalence In accordance with NT-proBNP, our data showed of diabetes in parents was similar in the highest and FFA levels were positively associated with NYHA class lowest quartilesaswell asinboth diabeticand nondia- and negatively associated with LVEF in patients with betic parents. Previous study also showed that FFA HFpEF, HFmrEF, and HFrEF. Moreover, patients with levels modulated microvascular function and subse- NYHA class III and IV had higher FFA levels than in quently resulted in obesity-associated insulin resistance patients with NYHA class I and II, which was also simi- and hypertension [19]. Moreover, a positive association lar to NT-proBNP. These findings suggest FFA levels between plasma FFAs and incident diabetes was ob- are associated with heart function. Although acipimox served during the first 5 years of follow-up [20]. Al- reduced circulating FFAs by − 69% and heart function though several studies reported that plasma FFAs were in Type 2 diabetes (T2DM) patients. [30]. However, 8 associated with CHD [18, 21]. FFA concentrations were T2DM patients had very high LVEF (78 ± 8). And in the not associated with CHD death in the Paris Prospective setting of HF, patients have different internal environ- Study [22]. In this study, we found there was a positive ment, pathophysiological state and impaired LVEF. Fur- association of FFAs and hypertension, but not diabetes thermore, the sample size of this study was very small. and CHD. Therefore, the association of FFAs with Therefore, according to the present study, in the setting diabetes and CHD remains controversial. of HF, high levels of FFA lead to impaired LVEF. Fur- Plasma FFA levels were increased in the obese state ther, trimetazidine improved left ventricular function in and could be normalized by reducing body mass [23, elderly patients with coronary artery disease and low LVEF 24], which was probably due to an increased adipose [31]. As was showed in our study, FFAs were much higher tissue insulin resistance [25]. Our study showed that in HFrEF than in HFpEF and HFmrEF but HFpEF shared FFA levels were not associated with diabetes in HF, similar FFAs with HFmrEF. In addition, ROC analysis which suggests that insulin resistance may not cause showed that high FFA levels predicted HFrEF. Interest- an increase in FFAs. Increased plasma FFAs are also ingly, ROC analysis also showed NT-proBNP predicted associated with an increased cardiac fatty acid uptake. HFrEF across the three categories, which suggest HFrEF is Interestingly, our study also showed that FFAs were great distinct from HFpEF and HFmrEF. Our findings in- not associated with weight and BMI, and BMI showed dicated that FFAs were more likely to affect systolic heart values within the normal range in HFpEF, HFmrEF, function and patients with HFrEF. By contrast, HFmrEF and HFrEF. Therefore, increased FFAs in HF may be may be similar to HFpEF in term of energy metabolism. due to an increase in energy demand and lead to im- Although elevated FFAs could also induce inflammation paired left ventricular function [26]. The structural and oxidative stress and there was an association between and metabolic alterations of myocardial cells conse- FFAs and mortality [12], patients with HF still could gain quent to HF are due to reduction in glucose utilization benefit from inhibition of fatty acid oxidation [32, 33]. and increase in fatty acid utilization. It has been also And our study indicates that patients with HFrEF may demonstrated that Inflammation and oxidative stress gain much more benefit. Directly lowering FFAs could be induced by FFAs are involved in impaired heart func- another effective treatment for HFrEF. Hence, plasma tion [27–29]. FFAs could help identify HFrEF across three categories Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 7 of 8 and the state of energy metabolism, contributing to in- Received: 16 February 2018 Accepted: 25 May 2018 struct drug therapy. Further study should be conducted to identify whether FFA levels have these effects on patients with HFrEF. References 1. Najafi F, Jamrozik K, Dobson AJ. Understanding the ‘epidemic of heart Thepresent studyhas afew limitations.We could failure’: a systematic review of trends in determinants of heart failure. Eur J not exclude an excess intake of FAs could have influ- Heart Fail. 2009;11(5):472–9. enced our data. Nonfasting samples were used in the 2. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, Falk V, study. 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Plasma levels of free fatty acid differ in patients with left ventricular preserved, mid-range, and reduced ejection fraction

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Medicine & Public Health; Cardiology; Cardiac Surgery; Angiology; Blood Transfusion Medicine; Internal Medicine; Medicine/Public Health, general
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Abstract

Background: Free fatty acids (FFAs) predicted the risk of heart failure (HF) and were elevated in HF with very low left ventricular ejection fraction (LVEF) compared to healthy subjects. The aim of this study was to investigate whether total levels of FFA in plasma differed in patients with HF with preserved (HFpEF), mid-range (HFmrEF), and reduced ejection fraction (HFrEF) and the association with the three categories. Methods: One hundred thirty-nine patients with HFpEF, HFmrEF and HFrEF were investigated in this study. Plasma FFA levels were measured using commercially available assay kits, and LVEF was calculated by echocardiography with the Simpson biplane method. Dyspnea ranked by New York Heart Association (NYHA) was also identified. Results: FFA concentrations were higher in HFrEF than in HFmrEF and HFpEF, respectively (689 ± 321.5 μmol/L vs. 537.9 ± 221.6 μmol/L, p = 0.036; 689 ± 321.5 μmol/L vs. 527.5 ± 185.5 μmol/L, p = 0.008). No significant differences in FFA levels were found between HFmrEF and HFpEF (537.9 ± 221.6 μmol/L vs. 527.5 ± 185.5 μmol/L, p = 0.619). In addition, we found a negative correlation between FFA levels and LVEF (regression coefficient: − 0.229, p = 0.004) and a positive correlation between FFAs and NYHA class (regression coefficient: 0.214, p = 0.014) after adjustment for clinical characteristic, medical history and therapies. ROC analysis revealed that FFAs predicted HFrEF across the three categories (AUC: 0.644, p = 0.005) and the optimal cut-off level to predict HFrEF was FFA levels above 575 μmol/L. Conclusions: FFA levels differed across the three categories, which suggests that energy metabolism differs between HFpEF, HFmrEF and HFrEF. Keywords: Heart failure, Preserved ejection fraction, Mid-range ejection fraction, Reduced ejection fraction, Free fatty acid Background < 40% are defined as reduced EF (HFrEF), and therapies During the past 20 years, considerable progress in the have been shown to reduce both morbidity and mortality treatment has improved the survival of patients with [2, 3]. Patients with EF ≥50% are generally considered as heart failure (HF). However HF remains a leading cause preserved EF (HFpEF), and therapies mainly directing at of morbidity and mortality throughout the world [1]. symptoms, comorbidities and risk factors, failed to confer Heart failure is a clinical syndrome characterized by typ- a survival benefit [4, 5]. A ‘grey zone’ of EF 40–49% was ical symptoms and signs resulting from Left ventricular formally termed as heart failure with mid-range ejection ejection fraction (LVEF), which has an essential role in fraction (HFmrEF) in the recent European Society of phenotyping and guiding the therapy [2]. Patients with EF Cardiology (ESC) HF guidelines. However, direct evidence on this group remains lacking and whether HFmrEF pa- tients are characterized by diverse demographic, or clinical features, different co-morbidities and distinct response to * Correspondence: zhuningccc@126.com therapies should be compared to HFpEF or HFrEF [6]. Department of Cardiology, The Third Clinical College of Wenzhou Medical Identifying HFmrEF as a separate group will stimulate University, Wenzhou People’s Hospital, No. 57 Canghou Street, Wenzhou 325000, Zhejiang Province, People’s Republic of China © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 2 of 8 research into the underlying characteristics, pathophysi- Biochemical measurements ology and treatment of this group of patients, and contrib- Following venous blood sample collection, Blood was ute to the better understanding of HF. drawn into chilled glass tubes containing EDTA, placed Under physiological conditions, Free fatty acids (FFAs) on ice and centrifuged at 3000 rpm for 10 min. The releasing from adipose tissue are the major energy separated serum specimens were immediately frozen and sources of the heart, and fatty acids (FAs) are active stored at − 80 °C until the time of the assay. The FFA components of biological membranes [7]. Although serum levels were measured on biochemical instrument FFAs yield the highest ATP, β-oxidation of FFAs uses (Beckman Coulter, USA) by a commercially available FFA more oxygen than glycolysis metabolism. Hence, FFAs kit (Reebio, Ningbo, China). All of assays were conducted are less energy efficient and increase the burden of the according to manufacturer’s guidelines. myocardium in the patients with HF. Furthermore, numerous evidences suggest that blocking fatty acid Ethical considerations oxidation and increasing glucose oxidation can im- The study complied with the Declaration of Helsinki prove cardiac contractile function, leading to improve and was approved by the Wenzhou People’s Hospital prognosis in patients with HF [8, 9]. In general, circu- ethics committee, and all patients gave written informed lating FFAs may be a crucial regulator of myocardial consent. substrate metabolism in HF. The composition of FFAs could also influence myocar- Statistical analysis dial function. It is well known that elevated circulating All the data are presented as mean ± SD. As the data FFA levels could cause chronic inflammation, insulin re- included continuous variables and classification vari- sistance, and cardiovascular disease [10, 11]. These pro- ables, parameter and non-parameter methods were both cesses could occur in many tissues such as the heart, liver, used. Non-parametric tests were also used in case of skeletal muscle and pancreas. Previous studies showed non-normally distributed data. Comparisons were made that patients with HF had higher plasma FFAs than by Pearson chi-square for proportions and Mann– healthy controls [12]. Moreover, FFAs were independently Whitney test and Kruskal–Wallis test for continuous associated with incident HF in older adults [13]. However, variables. The correlation between plasma FFAs and HF FFA levels in patients with HFpEF, HFmrEF and HFrEF risk factors (hypertension, diabetes, weight, BMI, CHD), and the association of FFAs with the three categories re- LVEF and New York Heart Association (NYHA) class was mains unknown. assessed by Spearman rank correlation test. Multiple Thus, the main aim of this observatory study was to regression analysis with input selection method was used investigate whether total levels of FFA in plasma differed to adjust gender, smoking, hypertension, diabetes, coron- across the three categories and the association of FFA ary heart disease, prior revascularization, prior myocardial plasma levels with the extent of heart failure with the infarction, dilated myocardiopathy, atrial fibrillation, di- three categories. uretics, aldosteroneantagonists, beta-blockers, ACEI/ARB, digitoxin, statins and warfarin. The receiver operating Methods characteristic (ROC) curves for associations between Study population FFAs, as well as NT-proBNP and HFpEF, HFmrEF, and A total of 139 men and women were enrolled from HFrEF compared. All P<0.05 were considered significant. Wenzhou People’s Hospital. All these patients were di- agnosed with chronic HF according to contemporary Results guidelines. In addition, all the patients were symptom- A total of 139 patients was classified as HFpEF (n = 51, atic and were treated according to contemporary clin- 36.6%), HFmrEF (n = 39, 28.1%), and HFrEF (n = 49, ical guidelines. Patients were excluded from the study if 35.3%). Table 1 shows the baseline characteristics of the they had any recent acute coronary syndrome, stroke, study population, and most of clinical characteristics dif- immune system disorders, severe valvular disease, or fer across the three categories. HFmrEF was close to any other concomitant terminal disease. Upon entering HFpEF and HFrEF in terms of age, however HFmrEF the study, the set of baseline variables including previ- were more often male than HFpEF and less often male ous clinical history, treatments, the gender, height, and than HFrEF. In addition, the prevalence of hypertension, weight of all the patients were collected. LVEF were diabetes and dilated myocardiopathy were higher in calculated by echocardiography with the Simpson bi- HFmrEF than in HFpEF, but lower than in HFrEF. plane method. Based on the LVEF measured at time of There was more smoking, prior myocardial infarction in inclusion, patients were categorized as HFpEF as LVEF HFmrEF than in HFpEF and HFrEF while there was less ≥50%, HFmrEF as LVEF 40–49%, and HFrEF as LVEF coronary heart disease (CHD) and prior revascularization <40%. in HFmrEF than in HFpEF and HFrEF. There were no Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 3 of 8 Table 1 Characteristics according to categories of left ventricular ejection fraction (LVEF) HFpEF HFmrEF HFrEF Overall HFpEF vs. HFmrEF HFmrEF vs. HFrEF HFpEF vs. HFrEF (n = 51 36.6%) (n = 39 28.1%) (n = 49 35.3%) PP P P Characteristic Age, years 79.3 ± 8.9 77.2 ± 10.2 78.0 ± 11.8 0.553 0.297 0.626 0.501 Male gender 30(58.8%) 26(66.6%) 42(85.7%) <0.001 <0.05 <0.001 <0.001 Current smoking 15(29.4%) 12(30.7%) 15(30.6%) <0.001 <0.001 <0.001 <0.001 Hypertension 33(64.7%) 28(71.7%) 40(81.6%) <0.001 0.001 <0.001 <0.001 Diabetes 12(23.5%) 12(30.7%) 16(32.6%) <0.001 <0.001 0.001 <0.001 NYHA III/IV 37(72.5%) 30(76.9%) 44(89.7%) <0.001 <0.001 <0.001 <0.001 LVEF(%) 60.1 ± 6.6 44.5 ± 2.9 32.6 ± 4.1 <0.001 <0.001 <0.001 <0.001 Weight(kg) 59.4 ± 10.8 60.9 ± 10.2 60.0 ± 10.9 0.735 0.143 0.644 0.799 BMI 22.7 ± 4.0 22.9 ± 3.0 22.0 ± 3.2 0.791 0.654 0.775 0.526 Nt-proBNP 5825.8 ± 6484.2 9664 ± 10,189.1 11,248.1 ± 10,875.1 <0.05 <0.05 0.408 <0.05 Other medical history Coronary heart disease 41((80.3%) 29(74.3%) 39(79.5%) <0.001 <0.001 <0.001 <0.001 Prior revascularization 10(19.6%) 7(17.9%) 17(34.6%) <0.001 <0.001 <0.001 <0.001 Prior myocardial infarction 6(11.7%) 9(23%) 8(16.3) <0.001 <0.001 <0.001 <0.001 Dilated myocardiopathy 0(0%) 5(12.8%) 12(24.4%) <0.001 <0.001 <0.001 <0.001 Atrial fibrillation 29(56.8%) 17(43.5%) 16(32.6%) 0.203 0.833 <0.05 0.317 Therapies Diuretics 39(76.4%) 38(97.4%) 42(85.7%) <0.001 <0.001 <0.001 <0.001 Aldosteroneantagonists 38(77.5%) 26(66.6%) 34(69.3%) <0.001 <0.001 <0.05 <0.001 Beta-blockers 35(68.6%) 21(53.8%) 24(48.9%) 0.075 <0.05 0.831 0.072 ACEI/ARB 32(61.5%) 21(53.8%) 32(65.3%) <0.05 0.092 0.055 <0.05 Digitoxin 8(15.6%) 10(25.6%) 22(44.8%) <0.001 <0.001 <0.05 <0.001 Statins 34(66.6%) 28(71.7%) 33(67.3%) <0.001 <0.001 <0.001 0.001 Warfarin 15(29.4%) 6(15.3%) 6(12.2%) <0.001 <0.001 <0.001 <0.001 Data are presented as mean ± SD, or number or percentage of subjects NYHA New York Heart Association, LVEF left ventricular ejection fraction, BMI body Mass Index, Nt-proBNP N-terminal pro-B-type natriuretic peptide, ACE angiotensin-converting enzyme, ARB angiotensin II receptor blocker, p significance level differences in weight and BMI between HFpEF, HFmrEF, differences in levels of FFA were found between HFmrEF and HFrEF, however HFmrEF had higher weight than and HFpEF (537.9 ± 221.6 μmol/L vs. 527.5 ± 185.5 μmol/ HFpEF. HFmrEF had more atrial fibrillation than HFrEF, L, p = 0.619, Fig. 1). Our data showed FFAs were associ- but similar N-Terminal pro-brain natriuretic peptide ated with hypertension (regression coefficient: 0.156, (NT-proBNP) levels than HFrEF. NYHA III/IV was inter- p =0.033, Table 2), but there was no significant correl- mediate in HFmrEF. ation between plasma FFA levels and diabetes, weight, Regarding therapies, there were highest use of diuretics BMI, CHD (regression coefficient: 0.092, p = 0.28; re- and statins, intermediate use of digitoxin and warfarin, gression coefficient: 0.092, p = 0.28; regression coeffi- and lowest use of aldosteroneantagonist in HFmrEF. cient: 0.151, p = 0.076; regression coefficient: 0.00004, HFmrEF had similar rate of angiotensin-converting en- p =0.713 Table 2). There was still no significant cor- zyme (ACE)-inhibitors and angiotensin receptor blockers relation between plasma FFA levels and weight, BMI (ARBs) and lower rate of Beta-blocker than HFpEF. It was and CHD even after adjusting for gender, smoking, also found that The HFmrEF group had intermediate rate hypertension, diabetes, coronary heart disease, prior of digitoxin. revascularization, prior myocardial infarction, dilated FFA concentrations were higher in HFrEF than in myocardiopathy, atrial fibrillation, diuretics, aldostero- HFmrEF and HFpEF, respectively (689 ± 321.5 μmol/L vs. neantagonists, beta-blockers, ACEI/ARB, digitoxin, statins 537.9 ± 221.6 μmol/L, p = 0.036; 689 ± 321.5 μmol/L vs. and warfarin (regression coefficient: 0.114, p = 0.183; regres- 527.5 ± 185.5 μmol/L, p =0.008, Fig. 1). No significant sion coefficient: 0.214, p = 0.117; regression coefficient: Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 4 of 8 Table 3 Multiple regression analysis Regression coefficient P Weight 0.114 0.183 BMI 0.142 0.117 CHD 0.097 0.459 LVEF −0.229 0.004 NYHA class 0.214 0.014 BMI body Mass Index. CHD coronary heart disease, LVEF Left ventricular ejection fraction, NYHA New York Heart Association, p significance level NT-proBNP and LVEF and NYHA class (regression coeffi- cient: − 0.101, p = 0.025; regression coefficient: 0.234, p = 0.012). ROC analysis revealed FFA predicted HFrEF across the three categories (AUC: 0.644, p = 0.005, Fig. 4a)and the optimal cut-off level to predict HFrEF were FFA levels Fig. 1 Plasma FFA levels in patients with HFpEF, HFmrEF and HFrEF. above 575 μmol/L. ROC analysis showed NT-proBNP also *P<0.05, **P<0.01 predicted HFrEF across the three categories (AUC: 0.619, p = 0.021, Fig. 4b). 0.097, p = 0.459, Table 3). In contrast, we found a nega- tive correlation between FFA levels and LVEF (regres- Discussion sion coefficient: − 0.267, p =0.001, Fig. 2a). A negative This is a pilot study to compare FFAs in HFpEF, correlation was also found between NT-proBNP and HFmrEF, and HFrEF based on the newly defined HF LVEF (regression coefficient: − 0.264, p = 0.002, Fig. 2b). types in the 2016 ESC guideline. Despite a clinical pro- Moreover, there was a positive correlation between file similar to those with HFpEF or HFrEF, patients with FFAs as well as NT-proBNP and NYHA class (regres- HFmrEF have many different characteristics. In line sion coefficient: 0.202, p = 0.017, Fig. 2c; regression co- with previous researches [14–16], our results suggested efficient: 0.302, p < 0.001, Fig. 2d). FFA levels were that patients with HFmrEF constituted a specific HF higher in patients with NYHA class III and IV than in phenotype. In addition, we found that HFrEF had patients with NYHA class I and II (605.3 ± 264 μmol/L higher plasm FFA levels than HFpEF and HFmrEF. vs. 509.2 ± 189 μmol/L, p = 0.034, Fig. 3a). Meanwhile, However, plasma FFA levels in HFmrEF were similar to patients with NYHA class III and IV have also higher that in HFpEF. Plasm FFA levels were negatively associ- NT-proBNP (9933.5 ± 10,156 μmol/L vs. 4171 ± ated with LVEF and positively associated with NYHA 3545 μmol/L, p = 0.0044, Fig. 3b)Multipleregression class, which were similar to NT-proBNP. ROC curve analysis showed FFAs still significantly correlated with showed that FFAs and NT-proBNP predicted HFrEF LVEF and NYHA class after adjustment for gender, across the three categories. smoking, hypertension, diabetes, coronary heart disease, There were limited studies specifically comparing prior revascularization, prior myocardial infarction, HFpEF, HFmrEF and HFrEF, especially in Chinese popula- dilated myocardiopathy, atrial fibrillation, diuretics, tion. Our study showed that many clinical characteristics aldosteroneantagonists, beta-blockers, ACEI/ARB, digi- such as gender, hypertension, dilated myocardiopathy and toxin, statins and warfarin (regression coefficient: − 0.229, atrial fibrillation were on a continuum between HFpEF p = 0.004; regression coefficient: 0.214, p = 0.014, Table 3). and HFrEF but weight and BMI were similar in the three Similar results were found in the correlation between categories. In addition, HFmrEF had higher rates of cor- onary artery disease and revascularization. To the best of our knowledge, this is the first study to Table 2 Association of FFA levels with diabetes, hypertension, examine whether the association of plasma FFA con- weight, BMI and CHD centration with HFpEF, HFmrEF, and HFrEF. The Regression coefficient P associations between FFAs and risk factors including Diabetes 0.092 0.28 hypertension, atrial fibrillation, diabetes mellitus, and Hypertension 0.156 0.033 CHD for HF had rarely been reported. Free fatty acid Weight 0.092 0.28 elevation has been identified as a highly significant risk BMI 0.151 0.076 factor for hypertension [17]. Furthermore, it has been CHD 0.00004 0.713 demonstrated that elevated FFAs are positively associ- BMI body Mass Index, CHD coronary heart disease p significance level ated with systolic blood pressure in men and diastolic Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 5 of 8 Fig. 2 Association of FFA levels and NT-proBNP with left ventricular ejection fraction (a, b) and NYHA class (c, d) Fig. 3 Plasma FFA levels (a) and NT-proBNP levels (b) in patients with NYHA class I/II and NYHA class III/IV. *P<0.05, **P<0.01 Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 6 of 8 Fig. 4 ROC analysis of FFA (a) and NT-proBNP (b) in prediction of HFrEF blood pressure in women [18]. However, the prevalence In accordance with NT-proBNP, our data showed of diabetes in parents was similar in the highest and FFA levels were positively associated with NYHA class lowest quartilesaswell asinboth diabeticand nondia- and negatively associated with LVEF in patients with betic parents. Previous study also showed that FFA HFpEF, HFmrEF, and HFrEF. Moreover, patients with levels modulated microvascular function and subse- NYHA class III and IV had higher FFA levels than in quently resulted in obesity-associated insulin resistance patients with NYHA class I and II, which was also simi- and hypertension [19]. Moreover, a positive association lar to NT-proBNP. These findings suggest FFA levels between plasma FFAs and incident diabetes was ob- are associated with heart function. Although acipimox served during the first 5 years of follow-up [20]. Al- reduced circulating FFAs by − 69% and heart function though several studies reported that plasma FFAs were in Type 2 diabetes (T2DM) patients. [30]. However, 8 associated with CHD [18, 21]. FFA concentrations were T2DM patients had very high LVEF (78 ± 8). And in the not associated with CHD death in the Paris Prospective setting of HF, patients have different internal environ- Study [22]. In this study, we found there was a positive ment, pathophysiological state and impaired LVEF. Fur- association of FFAs and hypertension, but not diabetes thermore, the sample size of this study was very small. and CHD. Therefore, the association of FFAs with Therefore, according to the present study, in the setting diabetes and CHD remains controversial. of HF, high levels of FFA lead to impaired LVEF. Fur- Plasma FFA levels were increased in the obese state ther, trimetazidine improved left ventricular function in and could be normalized by reducing body mass [23, elderly patients with coronary artery disease and low LVEF 24], which was probably due to an increased adipose [31]. As was showed in our study, FFAs were much higher tissue insulin resistance [25]. Our study showed that in HFrEF than in HFpEF and HFmrEF but HFpEF shared FFA levels were not associated with diabetes in HF, similar FFAs with HFmrEF. In addition, ROC analysis which suggests that insulin resistance may not cause showed that high FFA levels predicted HFrEF. Interest- an increase in FFAs. Increased plasma FFAs are also ingly, ROC analysis also showed NT-proBNP predicted associated with an increased cardiac fatty acid uptake. HFrEF across the three categories, which suggest HFrEF is Interestingly, our study also showed that FFAs were great distinct from HFpEF and HFmrEF. Our findings in- not associated with weight and BMI, and BMI showed dicated that FFAs were more likely to affect systolic heart values within the normal range in HFpEF, HFmrEF, function and patients with HFrEF. By contrast, HFmrEF and HFrEF. Therefore, increased FFAs in HF may be may be similar to HFpEF in term of energy metabolism. due to an increase in energy demand and lead to im- Although elevated FFAs could also induce inflammation paired left ventricular function [26]. The structural and oxidative stress and there was an association between and metabolic alterations of myocardial cells conse- FFAs and mortality [12], patients with HF still could gain quent to HF are due to reduction in glucose utilization benefit from inhibition of fatty acid oxidation [32, 33]. and increase in fatty acid utilization. It has been also And our study indicates that patients with HFrEF may demonstrated that Inflammation and oxidative stress gain much more benefit. Directly lowering FFAs could be induced by FFAs are involved in impaired heart func- another effective treatment for HFrEF. Hence, plasma tion [27–29]. FFAs could help identify HFrEF across three categories Zhu et al. BMC Cardiovascular Disorders (2018) 18:104 Page 7 of 8 and the state of energy metabolism, contributing to in- Received: 16 February 2018 Accepted: 25 May 2018 struct drug therapy. Further study should be conducted to identify whether FFA levels have these effects on patients with HFrEF. References 1. Najafi F, Jamrozik K, Dobson AJ. Understanding the ‘epidemic of heart Thepresent studyhas afew limitations.We could failure’: a systematic review of trends in determinants of heart failure. Eur J not exclude an excess intake of FAs could have influ- Heart Fail. 2009;11(5):472–9. enced our data. Nonfasting samples were used in the 2. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, Falk V, study. Our study did not show whether mortality González-Juanatey JR, Harjola VP, Jankowska EA, Jessup M, Linde C, Nihoyannopoulos P, Parissis JT, Pieske B, Riley JP, Rosano GM, Ruilope LM, differed in three categories and was associated with Ruschitzka F, Rutten FH, van der Meer P; Authors/Task Force Members FFA levels by follow-up. Further studies are required to (2016) ESC Guidelines for the diagnosis and treatment of acute and chronic identify whether inhibition of fatty acid oxidation or heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). directly lowering FFAs are efficient treatment for three Developed with the special contribution of the Heart Failure Association categories, especially HFrEF. 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Senni M, Paulus WJ, Gavazzi A, Fraser AG, Díez J, Solomon SD, Smiseth OA, Abbreviations Guazzi M, Lam CS, Maggioni AP, Tschöpe C, Metra M, Hummel SL, FFA: free fatty acid; HFmrEF: Heart failure with mid-range ejection fraction; Edelmann F, Ambrosio G, Stewart Coats AJ, Filippatos GS, Gheorghiade M, HFpEF: Heart failure with preserved ejection fraction; HFrEF: Heart failure with Anker SD, Levy D, Pfeffer MA, Stough WG, Pieske BM. New strategies for reduced ejection fraction; LVEF: left ventricular ejection fraction; NYHA: New heart failure with preserved ejection fraction: the importance of targeted York heart association therapies for heart failure phenotypes. Eur Heart J. 2014;35(40):2797–815. 5. Ohlmeier C, Mikolajczyk R, Frick J, Prütz F, Haverkamp W, Garbe E. Incidence, prevalence and 1-year all-cause mortality of heart failure in Germany: a Acknowledgements study based on electronic healthcare data of more than six million persons. 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BMC Cardiovascular DisordersSpringer Journals

Published: May 29, 2018

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