Abstract
Background:
Obesity and insulin resistance are prevalent in heart failure with preserved ejection fraction (HFpEF) and are associated with adverse cardiovascular outcomes. Measuring insulin resistance is difficult outside of research settings, and its correlation to parameters of myocardial dysfunction and functional status is unknown.
Methods:
A total of 92 HFpEF patients with New York Heart Association class II to IV symptoms underwent clinical assessment, 2D echocardiography, and 6-min walk (6 MW) test. Insulin resistance was defined by estimated glucose disposal rate (eGDR) using the formula: eGDR = 19.02 – [0.22 × body mass index (BMI), kg/m2] – (3.26 × hypertension, presence) – (0.61 × glycated hemoglobin, %). Lower eGDR indicates increased insulin resistance (unfavorable). Myocardial structure and function were assessed by left ventricular (LV) mass, average E/e’ ratio, right ventricular systolic pressure, left atrial volume, LV ejection fraction, LV longitudinal strain (LVLS), and tricuspid annular plane systolic excursion. Associations between eGDR and adverse myocardial function were evaluated in unadjusted and multivariable-adjusted analyses using analysis of variance testing and multivariable linear regression.
Results:
Mean age (SD) was 65 (11) years, 64 % were women, and 95 % had hypertension. Mean (SD) BMI was 39 (9.6) kg/m2, glycated hemoglobin 6.7 (1.6) %, and eGDR 3.3 (2.6) mg × kg−1 min−1. Increased insulin resistance was associated with worse LVLS in a graded fashion [mean (SD) – 13.8 % (4.9 %), – 14.4 % (5.8 %), – 17.5 % (4.4 %) for first, second, and third eGDR tertiles, respectively, p = 0.047]. This association persisted after multivariable adjustment, p = 0.040. There was also a significant association between worse insulin resistance and decreased 6 MW distance on univariate analysis, but not on multivariable adjusted analysis.
Conclusion:
Our findings may inform treatment strategies focused on the use of tools to estimate insulin resistance and selection of insulin sensitizing drugs which may improve cardiac function and exercise capacity.
Keywords: Heart failure, Heart failure with preserved ejection fraction, Insulin resistance, Echocardiography
Introduction
Heart failure with preserved ejection fraction (HFpEF) accounts for half of all hospitalizations for heart failure and is associated with high morbidity and mortality [1]. The prevalence of HFpEF has increased in the past decade [2], likely due to an aging population and an increasing burden of cardiovascular comorbidities, particularly obesity and insulin resistance, both common in HFpEF [3]. A popular paradigm in the understanding of HFpEF is that the condition likely represents a heterogenous group of separate phenotypes, with an increasingly prevalent phenotype related to insulin resistance [4]. However, although insulin resistance is a key feature of diabetes mellitus (DM) and is linked to the development of HFpEF in overweight individuals, it is often present before the development of DM, and is difficult to measure in clinical practice. Furthermore, it is unknown if measures of insulin resistance in patients with HFpEF are associated with subclinical and clinical cardiovascular abnormalities.
Insulin resistance may be quantified by calculating the estimated glucose disposal rate (eGDR) which incorporates glycated hemoglobin (HbA1c), presence or absence of hypertension, and body mass index (BMI), and is a validated clinical tool that correlates well with the gold standard measurement of insulin sensitivity, the euglycemic-hyperinsulinemic clamp, where hyperinsulinemia is achieved via constant insulin infusion and euglycemia is maintained by a variable infusion rate of glucose [5]. To our knowledge, however, no studies have evaluated the contribution of insulin resistance to cardiac pathology in HFpEF, reflected by cardiac structural and functional abnormalities detected non-invasively. Furthermore, it is unknown whether the negative impact of insulin resistance on cardiovascular pathology relates to important functional metrics in HFpEF patients such as six-minute walk test. We therefore aimed to assess the role of eGDR, an easily calculated metric using commonly available clinical variables that reflects insulin resistance, in a well characterized cohort of HFpEF patients. We tested the hypothesis that increased insulin resistance, as measured by reduced eGDR, is associated with abnormalities in cardiac structure and function among individuals with HFpEF.
Methods
In this observational cohort study, 92 HFpEF patients were prospectively enrolled between September 2016 and November 2019 from the HFpEF clinics at Johns Hopkins University (JHU) and Northwestern University (NU) as part of the American Heart Association GoRed for Women Strategic Focused Research Network study [6]. Participants with HFpEF were included if they met the criteria: age > 21 years, left ventricular (LV) ejection fraction ≥ 50 % within the preceding 6 months, presence of HF as defined by the Framingham criteria for HF, including N-terminal pro-brain natriuretic peptide ≥ 100 pg/mL [7], and symptoms of HF (New York Heart Association class II-IV) at the time of enrollment. The Framingham criteria for HF are similar to the recently proposed universal definition of HF, although they may be less sensitive [8]. Exclusion criteria were previously published [9]. The study was approved by the institutional review boards of both JHU and NU. All participants provided written informed consent and all study visits were part of the research protocol.
The research study visit included detailed demographic and medical history collected using a standardized questionnaire, as well as phlebotomy, review of medical records, six-minute walk test, and a two-dimensional (2D) transthoracic echocardiogram (TTE). BMI was calculated at this visit as weight (kg)/height (m)2; obesity was defined as BMI ≥ 30 kg/m2. Presence of hypertension was determined by review of the pre-existing medical record, use of antihypertensive agents, or blood pressure ≥ 130/90 mmHg at the visit [10]. Presence of DM was determined by review of the pre-existing medical record, use of antihyperglycemic agents, or a HbA1c ≥ 6.5 %. Other clinical variables were assessed from medical record documentation at a previous clinical evaluation and verified with the patient at the initial study visit. All laboratory data were obtained at the visit, or within 3 months. Estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [11], and chronic kidney disease was defined as eGFR < 60 mL/min/1.73 m2.
The eGDR was calculated using the formula: eGDR = 19:02–(0:22 × BMI; in kg/m2)–(3:26×hypertension; presence)–(0:61×HbA1c; percentile), with a normal eGDR being between 8 and 11 mg kg−1 min−1 and low eGDR below 4–7 mg kg−1 min−1 [12,13].
TTE with speckle tracking echocardiography was performed per American Society of Echocardiography guidelines and measurements were performed blinded and standardized at the NU echocardiography core laboratory. Standard echocardiographic parameters were collected including LV mass, average E/e’ ratio, a 2D echocardiography-derived marker of LV end-diastolic filling pressures, right ventricular systolic pressure (RVSP), left atrial (LA) volume, LV longitudinal strain (LVLS), LV ejection fraction, and tricuspid annular plane systolic excursion (TAPSE) [14]. Strain analysis was conducted with TomTec 2D Cardiac Performance Analysis software (TomTec Corporation, Chicago, IL, USA). Additionally, subjects were asked to walk as far as possible for 6 min, and the distance was measured (6 MW distance). This test was done according to guidelines by trained staff [15].
Associations between eGDR and TTE parameters of myocardial function as well as between eGDR and 6 MW distance were evaluated using analysis of variance testing and multivariate linear regression, adjusting for age, sex, BMI, the presence of DM, the presence of hypertension, and creatinine. Statistical analyses were performed using Stata 17 statistical software (StataCorp, College Station, TX, USA). All authors had full access to the data in the study and take responsibility for its integrity and the data analyses.
Results
A total of 92 HFpEF patients were studied with mean age 65 ± 11 years, with 64 % women, and 49 % black individuals, Table 1. The average BMI was 39.0 ± 9.6 kg/m2, 95 % had hypertension, 20 % had coronary artery disease, and mean biplane ejection fraction was 61 ± 0.8 %. The mean HbA1c was 6.7 ± 1.6 % and the mean creatinine was 1.3 ± 0.89 mg/dL. Background medical therapy and baseline characteristics of the study population stratified by eGDR tertile are displayed in Table 1. Representative violin plots of the eGDR stratified by tertile of the study cohort are shown in Fig. 1.
Table 1.
Baseline characteristics, n = 92, stratified by eGDR tertile.
| eGDR 1 (n = 30) in mean (SD), no (%) | eGDR 2 (n = 31) in mean (SD), no (%) | eGDR 3 (n = 31) in mean (SD), no (%) | p-Value | |
|---|---|---|---|---|
| eGDR, mg kg−1 min−1 | 0.42 (1.08) | 3.21 (0.72) | 6.04 (1.96) | <0.001 |
| Age, years | 57 (12) | 66 (9) | 71 (9) | <0.001 |
| Sex, women | 20 (67 %) | 19 (61 %) | 20 (65 %) | 0.999 |
| Race, Black or African-American | 19 (63 %) | 19 (61 %) | 7 (23 %) | 0.052 |
| BMI, kg m−2 | 48.3 (7.4) | 39.4 (4.0) | 29.6 (5.4) | <0.001 |
| Hypertension | 14 (47 %) | 14 (45 %) | 9 (29 %) | 0.074 |
| Coronary artery disease | 3 (10 %) | 7 (23 %) | 8 (26 %) | 0.784 |
| Atrial fibrillation or flutter | 2 (7 %) | 10 (32 %) | 13 (42 %) | 0.748 |
| NT-proBNP, pg/mL | 178 (240) | 714 (1123) | 594 (937) | 0.069 |
| Hb A1c, % | 7.88 (2.03) | 6.35 (1.01) | 5.95 (0.94) | <0.001 |
| Creatinine, mg/dL | 1.41 (1.36) | 1.42 (0.67) | 1.18 (0.38) | 0.495 |
| eGFR, ml min−11.73 m2 | 67.6 (26.7) | 57.1 (23.5) | 58.5 (16.4) | 0.155 |
| Total cholesterol, mg/dL | 169 (38.2) | 158 (38.5) | 155 (48.9) | 0.462 |
| Triglycerides, mg/dL | 131 (60.1) | 114 (60.1) | 101 (42.7) | 0.111 |
| HDL-C, mg/dL | 58.9 (43.2) | 51.6 (14.3) | 55.7 (18.7) | 0.608 |
| LDL-C, mg/dL | 91.4 (35.9) | 84.3 (33.8) | 79.0 (45.5) | 0.476 |
| Loop diuretic | 29 (97 %) | 29 (94 %) | 25 (81 %) | 0.413 |
| Thiazide diuretic | 1 (1 %) | 1 (1 %) | 3 (3 %) | 0.897 |
| Mineralocorticoid receptor antagonist | 20 (22 %) | 20 (22 %) | 18 (20 %) | 0.991 |
| Aspirin | 24 (80 %) | 20 (65 %) | 18 (58 %) | 0.621 |
| Statin | 25 (83 %) | 20 (65 %) | 25 (81 %) | 0.623 |
| ACE inhibitor | 15 (50 %) | 6 (19 %) | 4 (13 %) | 0.034 |
| Angiotensin receptor blocker | 6 (20 %) | 9 (29 %) | 8 (26 %) | 0.984 |
| Beta blocker | 17 (57 %) | 18 (58 %) | 19 (61 %) | 0.999 |
| SGLT2 inhibitor | 2 (7 %) | 3 (10 %) | 1 (3 %) | 0.958 |
| Metformin | 16 (53 %) | 5 (16 %) | 4 (13 %) | 0.009 |
| Other oral hypoglycemic | 7 (23 %) | 6 (19 %) | 3 (10 %) | 0.835 |
| Insulin | 12 (40 %) | 10 (32 %) | 1 (3 %) | 0.031 |
ACE, angiotensin converting enzyme; BMI, body mass index; eGDR, estimated glucose disposal rate; eGFR, estimated glomerular filtration rate; Hb A1c, hemoglobin A1c, HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; NT-proBNP, N-terminal prohormone of brain natriuretic peptide; SGLT2, sodium glucose cotransporter 2. P-values were determined by ANOVA or χ2 statistical testing. Bold indicates statistically significant values, with p-value of less than 0.05.
Fig. 1.
Estimated glucose disposal rate (eGDR) by tertile. The violin plots illustrate kernel probability density, with the width of the shaded area representing the proportion of the data located therein. The inner horizontal dashed lines represent the median, and the upper and lower dotted lines represent the third and first quartiles, respectively.
The mean calculated eGDR for the cohort was 3.3 ± 2.6 mg × kg−1 min−1. Based on tertiles of eGDR, worse insulin resistance (lower eGDR) was associated with worse LVLS, Table 2. In the first tertile, with the highest insulin resistance, the mean LVLS was −13.8 ± 4.9 %. In the third tertile, with the lowest degree of insulin resistance and the highest eGDR, the mean LVLS was −17.5 ± 4.4 %, p-value = 0.047. Other structural and functional echocardiographic parameters were not significantly associated with insulin resistance, including LV ejection fraction, although an association between increased LV mass and higher insulin resistance approached significance (p-value = 0.06).
Table 2.
Echocardiographic features of adverse myocardial function by tertiles of insulin resistance.
| eGDR 1 (n = 30) | eGDR 2 (n = 31) | eGDR 3 (n = 31) | p-Value | |
|---|---|---|---|---|
| LV mass, g | 203.2 (48.1) | 202.1 (54.5) | 174.6 (48.6) | 0.06 |
| LVLS, % | −13.8 (4.9) | −14.4 (5.8) | −17.5 (4.4) | 0.047 |
| Average E/e’ | 11.0 (3.2) | 12.8 (4.0) | 11.4 (4.4) | 0.16 |
| LA volume, mL | 67.9 (19) | 74.7 (24.3) | 79.2 (29.0) | 0.23 |
| TAPSE, cm | 2.1 (0.33) | 2.1 (0.39) | 1.9 (0.40) | 0.19 |
| RVSP, mmHg | 26.0 (8.6) | 29.4 (10.4) | 28.5 (11.0) | 0.54 |
LA, left atrial; LV, left ventricular; LVLS, left ventricular longitudinal strain; RVSP, right ventricular systolic pressure; TAPSE, tricuspid annular plane systolic excursion.
eGDR, estimated glucose disposal rate, with eGDR 1 indicating the lowest values meaning the highest insulin resistance, ranging from nearly zero to 1.91. eGDR2 indicates the second tertile, ranging from 2.0 to 4.2. eGDR 3 indicates the highest tertile values indicative of the lowest levels of insulin resistance, and ranges from 4.29 to 11.3. Bold indicates statistically significant values, with p-value of less than 0.05.
In multivariable analysis of the continuous eGDR variable, a significant relationship persisted between better (more negative) LVLS values and lower insulin resistance by eGDR (β = 1.5, 95 % CI 0.071–2.9, p-value = 0.040) as shown in Table 3. Of note, LVLS was adjusted for LV mass. Other echocardiographic structural and functional parameters, including LA reservoir strain and RV free wall strain were not significantly associated with degree of insulin resistance after adjustment.
Table 3.
Associations between eGDR and echocardiographic features of adverse myocardial function by linear regression.
| Univariate |
Multivariatea |
|||
|---|---|---|---|---|
| eGDR β (95 %CI) | p-Value | eGDR β (95 % CI) | p-Value | |
| LV Mass, g | −5.3 (−9.5 to −1.2) | 0.013 | 2.2 (−10.0–14.0) | 0.718 |
| LVLS, % | 0.60 (0.14–1.1) | 0.012 | 1.5 (0.071–2.9) | 0.040 |
| Average E/e’ | 0.030 (−0.30–0.36) | 0.853 | −0.203 (−1.2–0.78) | 0.681 |
| LA Volume, mL | 2.15 (0.11–4.20) | 0.039 | 7.0 (0.79–13.0) | 0.280 |
| TAPSE, cm | −0.30 (−0.07–0.002) | 0.062 | 0.01 (−0.096–0.11) | 0.897 |
| RVSP, mmHg | 0.19 (−0.78–1.16) | 0.697 | 2.2 (−1.3–5.8) | 0.211 |
eGDR, estimated glucose disposal rate; LA, left atrial; LV, left ventricular; RVSP right ventricular systolic pressure; LVEF, left ventricular systolic function; LVLS, left ventricular longitudinal strain; TAPSE, tricuspid annular plane systolic excursion.
Multivariate adjusted for age, sex, body mass index, diabetes, hypertension, and creatinine. LVLS is also adjusted for LV mass. Bold indicates statistically significant values, with p-value of less than 0.05.
Additionally, we observed that lower insulin resistance was associated with greater six-minute walk distance in a graded fashion, Table 4. However, after multivariable adjustment for age, sex, BMI, the presence of DM, the presence of hypertension, and creatinine, this association was no longer statistically significant, p-value = 0.068.
Table 4.
Functional capacity as measured by 6MWD by tertiles of insulin resistance.
| eGDR 1 (n = 31) | eGDR 2 (n = 31) | eGDR 3 (n = 30) | p-Value | |
|---|---|---|---|---|
| 6-min walk distance (m) | 263.0 (102.1) | 277.7 (114.6) | 370.1 (122.8) | <0.001 |
6MWD, distance walked in 6 min. eGDR, estimated glucose disposal rate, with eGDR 1 indicating the lowest values meaning the highest insulin resistance. eGDR 3 indicates the highest tertile values indicative of the lowest levels of insulin resistance. Bold indicates statistically significant values, with p-value of less than 0.05.
Discussion
In a well characterized cohort of patients with HFpEF, our study demonstrated a significant relationship between eGDR, a clinical tool for measuring degree of insulin resistance, and LVLS, a sensitive measure of myocardial function on 2D echocardiography, suggesting that insulin resistance is associated with cardiovascular pathology that contributes to HFpEF pathophysiology, independent of common covariates implicated in HFpEF. Furthermore, we observed a significant, stepwise reduction in six-minute walk distance with worsening insulin resistance. Although impaired health status has been linked to cardiometabolic abnormalities in HFpEF [9], to our knowledge this is the first study to examine the role of insulin resistance as measured using eGDR in cardiovascular pathology in this population. Increasing insulin resistance may be an early harbinger of subclinical LV dysfunction and exercise limitation and may necessitate early intervention targeted towards improving insulin resistance and health outcomes in patients with HFpEF.
Our diverse cohort resembles the general HFpEF population well, and our findings have implications that may inform management strategies for individuals with HFpEF. Patients with HFpEF have a high prevalence of obesity (84 %) [16] and type 2 DM (20–56 %) [17,18] lending support to the notion that there is likely a cardiometabolic phenotype of HFpEF. Previously collected evidence has linked impaired cardiac insulin metabolic signaling in rodents to HFpEF [19]. Further, normalization of glycemia reduces diastolic dysfunction in rodent models of type 1 diabetes mellitus [20]. On a cellular level, insulin resistance has been shown to decrease glucose transporter type 4 recruitment to the cardiomyocyte plasma membrane and subsequent glucose uptake, causing decreased sarcoplasmic reticulum calcium pump activity, increased intracellular calcium, and increased cardiac stiffness [21]. High insulin levels themselves decrease coronary endothelial nitric oxide synthase activity, induce expression of genes responsible for hypertrophy, and increase cardiac fibrosis [21–23]. In human subjects, insulin resistance may be quantified by the eGDR which has been validated in multiple clinical studies, and correlates well with the gold standard of insulin sensitivity, the euglycemic-hyperinsulinemic clamp [5,12,13]. Insulin resistance measured with eGDR is associated with the development of clinical HF in overweight individuals [24,25], obese individuals [26–28], and patients with diastolic dysfunction [29]. Given the obesity epidemic and high prevalence of cardiometabolic abnormalities in HFpEF, our study suggests a potential role of measuring eGDR, a simple, calculated metric of insulin resistance that may be easily incorporated in the outpatient setting.
Although prior studies have primarily studied the role of the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) in cardiovascular disease in obese individuals, none has evaluated the effect of insulin resistance on cardiac dysfunction and morbidity in HFpEF, and eGDR has not been studied in this population. Prior studies showed that HOMA-IR was related to worse LV global circumferential peak strain, peak diastolic strain rates, and LV global longitudinal strain in obese and overweight individuals, and these findings may herald worsening functional and disease clinical status as well as worsened prognosis [24,25,30]. However, to our knowledge, no studies have evaluated the relationship between insulin resistance measured by eGDR and cardiac structure and functional status in patients with HFpEF. An advantage of eGDR is that it represents a validated clinical tool using simple, widely available metrics (HbA1c, presence of hypertension, BMI) to measure insulin resistance that correlates well with gold standard measurements of insulin sensitivity [5]. Importantly, the eGDR is more adaptable to clinical practice than is HOMA-IR, which requires quantification of fasting serum insulin and glucose, which are not often available outside of research settings. Therefore, HOMA-IR has limited clinical utility at the current time, whereas eGDR may be incorporated into routine clinical practice right now.
Our study findings have important therapeutic implications. The identification of insulin resistance may allow for earlier therapeutic intervention that may target the related deranged metabolic pathways, and in so doing, may slow the progression of or prevent the development of HFpEF altogether. Recently, several clinical trials showed that sodium-glucose cotransporter 2 (SGLT2) inhibitors reduced the risk of cardiovascular death and HF hospitalization in HFpEF patients, and improved quality of life [31,32]. The PRESERVED-HF trial showed that treatment with the SGLT2 inhibitor dapagliflozin improved both symptoms and exercise function in patients with HFpEF with and without diabetes [33]. It is therefore possible that eGDR measures not only may help identify patients with subclinical LV function, but also may identify patients with HFpEF who may benefit from treatment with insulin sensitizers, such as SGLT2 inhibitors or metformin. However, prospective studies are needed to test this hypothesis.
This study has several important limitations. First, this was a cross-sectional analysis with a modest sample size, and thus temporal relationships between global longitudinal strain, LV remodeling, and insulin resistance cannot be determined. Additionally, the sample size inherently increases the likelihood of type II statistical error. It is possible that if more patients were studied, significant differences in other echocardiographic parameters would become apparent, such as in LV mass, which approached but did not reach significance. In addition, this was a dual center study from academic tertiary referral centers and thus has inherent flaws related to selection and referral bias.
In conclusion, insulin resistance measured by eGDR is significantly associated with subclinical myocardial dysfunction measured by LVLS and reduced functional capacity in patients with HFpEF. Characterizing the degree of insulin resistance in HFpEF patients may help identify individuals at risk of worsening HF and who may warrant earlier preventive medical therapy. Further studies are needed to study the utility of eGDR in identifying individuals who may benefit from the early use of agents that improve insulin sensitivity and the role of measuring eGDR over time in patients with HFpEF.
Funding
This study was funded by an American Heart Association Go Red for Women Strategically Focused Research Network grant (#16SFRN28780016). SJS is also funded by grants from the National Institutes of Health (U54 HL160273, R01 HL107577, R01 HL127028, R01 HL140731, and R01 HL149423). KS is also funded by the American Heart Association and AGH is also funded by R01HL159715 and 1R01HL147660.
Disclosures
SJS has received research grants from Actelion, AstraZeneca, Corvia, Novartis, and Pfizer; and has received consulting fees from Abbott, Actelion, AstraZeneca, Amgen, Aria CV, Axon Therapies, Bayer, Boehringer-Ingelheim, Boston Scientific, Bristol-Myers Squibb, Cardiora, Coridea, CVRx, Cyclerion, Cytokinetics, Edwards Lifesciences, Eidos, Eisai, Imara, Impulse Dynamics, Intellia, Ionis, Ironwood, Lilly, Merck, MyoKardia, Novartis, Novo Nordisk, Pfizer, Prothena, Regeneron, Rivus, Sanofi, Shifamed, Tenax, Tenaya, and United Therapeutics. KS is a consultant and advisory board member of AstraZeneca, Bayer, Boehringer-Ingelheim, Imbria, Janssen, Novartis, Novo Nordisk, and Rivus and receives honoraria. The other authors have no relevant disclosures.
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