Increasing adiposity increases the risk for left ventricular (LV) hypertrophy. Adipokines are hormone-like substances from adipose tissue that influence several metabolic pathways relevant to LV hypertrophy. Data were obtained from participants enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) who underwent magnetic resonance imaging of the heart and who also had fasting venous blood assayed for 4 distinct adipokines (adiponectin, leptin, tumor necrosis factor-α, and resistin). One-thousand four hundred sixty four MESA participants had complete data. The mean age was 61.5 years, the mean body mass index was 27.6 kg/m 2 , and 49% were women. With adjustment for age, gender, race, height, and weight, multivariate linear regression modeling revealed that a 1-SD increment in leptin was significantly associated with smaller LV mass (ß: −4.66% predicted, p <0.01), LV volume (−5.87% predicted, p <0.01), stroke volume (−3.23 ml, p <0.01), and cardiac output (−120 ml/min, p = 0.01) as well as a lower odds ratio for the presence of LV hypertrophy (odds ratio 0.65, p <0.01), but a higher ejection fraction (0.44%, p = 0.05). Additional adjustment for the traditional cardiovascular disease risk factors, insulin resistance, physical activity, education, income, inflammatory biomarkers, other selected adipokines, and pericardial fat did not materially change the magnitude or significance of the associations. The associations between the other adipokines and LV structure and function were inconsistent and largely nonsignificant. In conclusion, the results indicate that higher levels of leptin are associated with more favorable values of several measures of LV structure and function.
Increasing adiposity confers an increased risk for left ventricular (LV) hypertrophy. In those who are of normal weight or overweight, this association appears to be independent of the contribution of arterial blood pressure suggesting a nonhemodynamic mechanism of hypertrophy. In this regard, if the normal regulation of triglycerides is disrupted, they can be deposited in other locations to include the cardiac myocyte and, if excessive, may lead to dilated cardiomyopathy. The metabolism of triglycerides is, at least partially, regulated by cytokines that are secreted from a variety of tissues. Those that are secreted by adipose tissue are called adipokines and include adiponectin, leptin, tumor necrosis factor-α, and resistin. Adiponectin and leptin regulate insulin action and energy metabolism in both adipose and muscle tissues. As such, these adipokines may influence the accumulation of triglycerides in nonadipose tissue compartments, such as the LV. Given this, we aimed to determine the magnitude and significance of the associations between selected adipokines and different measures of LV structure and function.
Methods
The Multi-Ethnic Study of Atherosclerosis (MESA) is a longitudinal cohort study of multiethnic groups. In brief, from July 2000 to August 2002, 6,814 men and women who were 45 to 84 years old and were free of clinically apparent cardiovascular disease were recruited from 6 United States communities. Enrolled participants returned for follow-up clinic visits 2, 4, and 6 years after the baseline clinic visit that were labeled as clinic visits 2, 3, and 4. Written informed consent was obtained on Institutional Review Board–approved forms from all participants.
At clinic visits 2 and 3, a random subsample of 1,970 participants enrolled in an ancillary study on body composition and adiposity-associated inflammation. Fasting venous blood was collected from these participants and used for measuring different adipokines (discussed later). These participants are the focus of the present study.
At all clinic visits, standardized questionnaires obtained sociodemographic, ethnicity, and health history information. Cigarette smoking was defined as current, former, or never. Height, weight, waist, and hip circumferences were measured with participants wearing light clothing and no shoes. Blood pressure at rest was measured 3 times in seated participants with a Dinamap model Pro 100 automated oscillometric sphygmomanometer (Critikon, Tampa, Florida). Hypertension was defined as systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg (measured at the clinic visit) or current use of an antihypertensive medication.
At the baseline clinic visit, magnetic resonance imaging (MRI) examinations of the heart were performed using scanners with 1.5-T magnets to determine specific measures of cardiac structure and function. Imaging consisted of fast gradient echo cine LV images using a phased-array surface coil with time resolution of <50 ms and the following scan protocol: 6 mm slice thickness, 400 mm field of view, 256 × 128 matrix, 20° flip angle, echo time = 3 to 5 ms, and repetition time = 8 to 10 ms. Imaging data were read using the MASS software (MEDIS, The Netherlands) at a single reading center by readers trained in the MESA protocol and without knowledge of risk factor information. Reliability (by intraclass correlations) was 0.97 for LV mass, 0.98 for end-diastolic volume, and 0.95 for end-systolic volume.
At the baseline clinic visit, all subjects underwent ultrafast computed tomography of the thorax to ascertain the presence and extent of coronary artery calcium. The images from these scans were analyzed for the extent of adipose tissue in the pericardium (pericardial fat). The method for this procedure has already been described.
At all clinic visits, fasting morning blood samples were collected, centrifuged, and shipped overnight to the MESA central laboratory, stored at −80°C and subsequently assayed for total and high-density lipoprotein cholesterol, triglycerides, and glucose levels, as well as markers C-reactive protein, fibrinogen, interleukin-6, and insulin concentration. Dyslipidemia was defined as a total cholesterol/HDL cholesterol ratio of >5.0 or if the participant used medication to reduce cholesterol. Diabetes was defined as fasting glucose ≥126 mg/dl or use of hypoglycemic medication.
Stored fasting blood samples from visits 2 and 3 were analyzed to provide levels of adiponectin, leptin, tumor necrosis factor-α, and resistin. These adipokines were measured using Bio-Rad Luminex flow cytometry (Millepore, Billerica, Maryland) at the MESA central laboratory. Average analytical coefficients of variation across control samples for these analytes ranged from 6.0% to 13.0%.
LV hypertrophy was defined as having an indexed LV mass more than the ninety-fifth percentile, relative to body size and gender. Because body size is strongly related to leptin and both LV mass and volume, and to account for the potential confounding by body size, we constructed outcome variables for LV mass and volume that were indexed and resulted in the predicted percentage of LV mass and volume based on height, weight and gender. The results using these indices were similar to analyses using unindexed variables and that were adjusted for height and weight. Therefore, we used nonindexed values for LV mass and volume and adjusted for height and weight in the models.
The adipokines were skewed and therefore log transformed. To provide comparability across the different adipokines, we used 1-SD increments in these variables. Potential confounding was assessed by sequential linear regression modeling: model 1 adjusted for the adipokine, age, gender, race or ethnicity, height, weight, and the waist-to-hip ratio; model 2 additionally controlled for hypertension, dyslipidemia, smoking, diabetes mellitus, family history of coronary heart disease, education, income, physical activity, and insulin resistance (by homeostatic model assessment); model 3 added C-reactive protein, interleukin-6, fibrinogen, and the other adipokines; and model 4 further added pericardial fat. When height and weight were replaced with body mass index, the results were not different. Therefore, and because height and weight explained a higher proportion of the variance than body mass index (R 2 : 0.54 vs 049, respectively), we elected to use height and weight in the multivariate models.
Generalized additive models were then used to test for nonlinearity in the relations between each adipokine and each end point. Significant nonlinearity was detected in the models for leptin and both LV mass and volume and further quantified using quartiles of leptin.
Results
Of the 1,970 participants who were included in the ancillary study on abdominal body composition, 1,464 had baseline MRI scans of the heart and complete biomarker data for the adipokines. The characteristics of this study cohort are listed in Table 1 .
| Characteristic | Value |
|---|---|
| Age (yrs) ∗ | 61.5 (9.6)/61.0 |
| Women † | 720 (49) |
| Caucasian † | 590 (40) |
| Chinese American † | 214 (15) |
| African-American † | 278 (19) |
| Hispanic American † | 382 (26) |
| High school graduate or higher † | 1,207 (82) |
| Income >$49,000 † | 578 (39) |
| Body mass index (kg/m 2 ) ∗ | 27.6 (4.7)/27.0 |
| Fasting glucose (mg/dl) | 97.8 (27.3)/91.0 |
| Urine creatinine (mg/dl) | 118.9 (67.7)/111.9 |
| Systolic blood pressure (mm Hg) | 123 (20.5)/120 |
| Diastolic blood pressure (mm Hg) | 70 (10.0)/70 |
| Current smoker † | 184 (13) |
| Former smoker † | 519 (35) |
| Impaired fasting glucose † | 175 (12) |
| Untreated diabetes † | 42 (3) |
| Treated diabetes † | 116 (8) |
| Hypertension medication use † | 500 (34) |
| Total cholesterol (mg/dl) | 189 (35) |
| LDL cholesterol (mg/dl) | 112 (31) |
| Triglycerides (mg/dl) | 134 (95) |
| Lipid lowering medication use † | 235 (16) |
| Family history of cardiovascular disease † | 191 (13) |
| C-reactive protein (mg/L) ∗ | 3.3 (4.8)/1.7 |
| Interleukin-6 (pg/ml) ∗ | 2.3 (1.7)/1.8 |
| Fibrinogen (mg/dl) ∗ | 431 (84.0)/424 |
| Adiponectin (ng/ml) ∗ | 20.9 (13.3)/17.6 |
| Leptin (pg/ml) ∗ | 19.4 (21.6)/12.1 |
| TNF-α (pg/ml) ∗ | 5.8 (10.7)/4.6 |
| Resistin (pg/ml) ∗ | 16.0 (6.7)/14.8 |
| LV mass (grams) | 146.8 (38.6)/141.0 |
| LV volume (ml) | 127.9 (30.5)/124.1 |
| LV ejection fraction (%) | 69.2 (7.3)/69.8 |
| Cardiac output (L/min) | 5.8 (1.4)/5.6 |
| LV mass/volume ratio (g/ml) | 1.2 (0.2)/1.1 |
With adjustment for age, gender, race, height, and weight, multivariate linear regression modeling revealed that a 1-SD increment in leptin was significantly associated with smaller LV mass, volume, and stroke volume, as well as cardiac output and a lower odds ratio for the presence of LV hypertrophy, but a higher ejection fraction ( Table 2 ). After the same adjustment, higher adiponectin was associated with larger LV volume, LV stroke volume, and cardiac output, but a lower LV ejection fraction. Adiponectin was not significantly associated with LV mass or the odds for LV hypertrophy. When the other adipokines were assessed, the only significant associations were between resistin and both LV ejection fraction and LV hypertrophy.
| Adipokine | Mass | Volume | Ejection Fraction | Stroke Volume | Cardiac Output | Hypertrophy |
|---|---|---|---|---|---|---|
| β (95% CI) | β (95% CI) | β (95% CI) | β (95% CI) | β (95% CI) | OR (95% CI) | |
| Panel 1—adipokines modeled separately | ||||||
| Leptin | −4.66 (−6.3 to −3.0) † | −5.87 (−7.4 to −4.4) † | 0.44 (0.0 to 0.9) † | −3.23 (−4.3 to −2.2) † | −0.12 (−0.2 to 0.0) † | 0.65 (0.5 to 0.9) † |
| Adiponectin | 0.83 (−1.8 to 3.4) | 4.07 (1.7 to 6.4) † | −0.68 (−1.4 to 0.0) † | 1.77 (0.1 to 3.4) † | 0.16 (0.0 to 0.3) † | 0.82 (−0.5 to 1.3) |
| Resistin | 1.63 (−1.8 to 5.0) | −0.01 (−3.1 to 3.1) | −0.95 (−1.8 to −0.1) † | −1.33 (−3.5 to 0.8) | −0.05 (−0.2 to 0.1) | 2.24 (1.2 to 4.1) † |
| TNF-α | 1.65 (−0.8 to 4.1) | −0.80 (−3.0 to 1.4) | −0.54 (−1.2 to 0.1) | −1.24 (−2.8 to 0.3) | −0.03 (−0.2 to 0.1) | 1.06 (−0.7 to 1.6) |
| Panel 2—adipokines modeled together | ||||||
| Leptin | −4.86 (−6.6 to −3.1) † | −5.38 (−6.8 to −3.8) † | 0.41 (−0.1 to 0.9) | −2.92 (−4.0 to −1.8) † | −0.10 (−0.2 to 0.0) † | 0.60 (0.5 to 0.8) † |
| Adiponectin | −0.18 (−2.8 to 2.5) | 2.76 (0.4 to 5.1) † | −0.47 (−1.2 to 0.2) | 1.25 (−0.4 to 2.9) | 0.15 (0.0 to 0.3) † | 0.69 (−0.4 to 1.1) |
| Resistin | 1.77 (−1.7 to 5.2) | −0.10 (−3.2 to 3.0) | −0.63 (−1.5 to 0.3) | −0.87 (−3.1 to 1.3) | −0.04 (−0.2 to 0.1) | 2.64 (1.4 to 2.5) † |
| TNF-α | 2.23 (−0.3 to 4.8) | 0.14 (−2.1 to 2.4) | −0.50 (−1.2 to 0.2) | −0.55 (2.2 to 1.1) | −0.00 (−0.1 to 0.1) | 1.06 (−0.7 to 1.7) |
∗ Adipokine adjusted for age, gender, ethnicity, height, and weight.
Because the associations appeared to be the most robust and consistent for leptin, we constructed general additive model plots to determine if these associations were nonlinear ( Figure 1 ). After adjustment, there were significant nonlinear associations with LV mass and LV volume (p <0.01 for both), but not for ejection fraction, stroke volume, or cardiac output (p = 0.25, 0.37, and 0.23, respectively). For both LV mass and volume, the inflection points were between leptin values of 20 and 40 pg/ml.
On the basis of these findings, we categorized leptin into quartiles and conducted multivariate linear regression analyses ( Table 3 ). With adjustment for age, gender, ethnicity, height, and weight, and compared with quartile 1, quartiles 2 to 4 were significantly associated with progressively smaller LV mass, LV volume, and LV stroke volume, as well as significantly less odds for the presence of LV hypertrophy. Additional adjustments for the traditional cardiovascular disease risk factors, education, income, physical activity, and insulin resistance (model 2); inflammatory biomarkers including the other adipokines (model 3); and the extent of pericardial fat (model 4), did not materially change the magnitude or significance of the associations. Higher levels of leptin were not significantly associated with LV ejection fraction or cardiac output.
| Leptin Quartile | Mass | Volume | Ejection Fraction | Stroke Volume | Cardiac Output | Hypertrophy |
|---|---|---|---|---|---|---|
| ß (95% CI) | ß (95% CI) | ß (95% CI) | ß (95% CI) | ß (95% CI) | OR (95% CI) | |
| Model 1 | ||||||
| Q2 | −6.5 (–10.3 to −2.7) ∗ | −9.4 (−12.8 to −6.1) ∗ | 0.50 (−0.5 to 1.5) | −5.9 (−8.3 to −3.6) ∗ | −0.25 (−0.4 to −0.1) ∗ | 0.45 (0.2 to 0.9) ∗ |
| Q3 | −10.2 (–14.5 to −5.9) ∗ | −11.0 (−14.8 to −7.1) ∗ | 0.83 (−0.3 to 2.0) | −6.3 (−9.0 to −3.6) ∗ | −0.12 (−0.3 to 0.1) | 0.40 (0.2 to 0.9) ∗ |
| Q4 | −13.9 (−19.3 to −8.6) ∗ | −12.9 (−17.6 to −8.2) ∗ | 0.62 (−0.8 to 2.00) | −7.7 (−11.1 to −4.4) ∗ | −0.23 (−0.5 to 0.1) | 0.31 (0.1 to 0.8) ∗ |
| Model 2 | ||||||
| Q2 | −6.5 (−10.2 to −2.9) ∗ | −8.9 (−12.3 to −5.5) ∗ | 0.23 (−0.8 to 1.2) | −6.0 (−8.4 to −3.7) ∗ | −0.23 (−0.4 to 0.0) ∗ | 0.35 (0.2 to 0.8) ∗ |
| Q3 | −10.1 (−14.4 to −5.9) ∗ | −10.2 (−14.1 to −6.2) ∗ | 0.69 (−0.5 to 1.9) | −6.0 (−8.8 to −3.3) ∗ | −0.11 (−0.3 to 0.1) | 0.31 (0.1 to 0.7) ∗ |
| Q4 | −15.5 (−20.7 to −10.2) ∗ | −12.1 (−16.9 to −7.2) ∗ | 0.50 (−0.9 to 1.9) | −7.5 (−10.9 to −4.0) ∗ | −0.22 (−0.5 to 0.1) | 0.17 (0.1 to 0.5) ∗ |
| Model 3 | ||||||
| Q2 | −6.5 (−10.3 to −2.8) ∗ | −8.9 (−12.3 to −5.5) ∗ | 0.17 (−0.8 to 1.2) | −6.1 (−8.6 to −3.7) ∗ | −0.24 (−0.4 to 0.0) ∗ | 0.37 (0.2 to 0.8) ∗ |
| Q3 | −10.8 (−15.1 to −6.4) ∗ | −10.4 (−14.4 to −6.4) ∗ | 0.81 (−0.4 to 2.0) | −6.0 (−8.8 to −3.2) ∗ | −0.12 (−0.4 to 0.1) | 0.28 (0.1 to 0.7) ∗ |
| Q4 | −16.0 (−21.5 to −10.6) ∗ | −12.1 (−17.1 to −7.0) ∗ | 0.63 (−0.8 to 2.1) | −7.3 (−10.8 to −3.7) ∗ | −0.21 (−0.5 to 0.1) | 0.14 (0.1 to 0.4) ∗ |
| Model 4 | ||||||
| Q2 | −6.1 (−9.8 to −2.4) ∗ | −8.4 (−11.9 to −5.0) ∗ | 0.24 (−0.8 to 1.3) | −5.8 (−8.2 to −3.3) ∗ | −0.25 (−0.5 to −0.1) | 0.39 (0.2 to 0.9) ∗ |
| Q3 | −10.3 (−14.7 to −6.0) ∗ | −9.9 (−13.9 to −5.9) ∗ | 0.89 (−0.3 to 2.1) | −5.6 (−8.4 to −2.8) ∗ | −0.13 (−0.4 to 0.1) | 0.29 (0.1 to 0.7) ∗ |
| Q4 | −15.5 (−21.3 to −10.4) ∗ | −11.8 (−16.9 to −6.8) ∗ | 0.66 (−0.8 to 2.1) | −7.10 (−10.6 to −3.6) ∗ | −0.22 (−0.5 to 0.1) | 0.13 (0.1 to 0.4) ∗ |
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