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Relationship of adiponectin with markers of systemic inflammation, atherogenic dyslipidemia, and heart failure in patients with coronary heart disease.

Adipose tissue is known to secrete adipocytokines that are related to systemic inflammation and glucose and lipid metabolism (1-3). Adiponectin, the most abundant adipocytokine, was found to be decreased in conditions such as obesity, type 2 diabetes, and coronary heart disease (CHD) [3] (4-6). In this context, hypoadiponectinemia was associated with low HDL-cholesterol (HDL-C) concentrations (4), decreased LDL particle size (6), and increased markers of systemic inflammation (7). The authors of a recent study suggested that adiponectin may also exert an independent role in regulating metabolism of triglyceride-rich lipoproteins (8). This notion was supported by 2 recent studies reporting that serum adiponectin was directly associated with enzymes that regulate lipid metabolism (9,10).

Because a well-recognized prospective study previously reported an association between adiponectin and lower cardiovascular risk in men, adiponectin was highlighted as a potential endogenous antiatherogenic factor (11). To further elucidate this hypothesis, correlations between adiponectin and several biomarkers, including B-type natriuretic peptide (BNP) and the N-terminal of the BNP prohormone (NT-proBNP), have been investigated (11-14). However, these associations are less well studied in patients at markedly high risk for future cardiovascular morbidity and mortality.

The aim of the present study was to further explore the clinical importance of serum adiponectin in patients with prevalent CHD. We therefore evaluated the relationship between serum adiponectin concentrations and markers of systemic inflammation, left ventricular function, and lipid metabolism after careful adjustment for established cardiovascular risk factors in a large sample of patients with CHD.

Materials and Methods


All patients with CHD (International Classification of Diseases, 9th Revision, codes 410-414), 30-70 years of age and participating in an in-hospital rehabilitation program between January 1999 and May 2000 in 2 cooperating clinics (Schwabenland-Klinik, Isny, and Klinik im SUdpark, Bad Nauheim, Germany), were enrolled in the study. In Germany, a comprehensive in-hospital rehabilitation program is offered to all acute coronary syndrome and coronary artery revascularization patients after discharge from the acute-care hospital. The International Classification of Diseases diagnosis used in this study was the discharge diagnosis of the acute-care hospital, and this diagnosis was also the decision basis for an in-hospital rehabilitation program in the German rehabilitation system. The design, methods, and laboratory techniques of the KAROLA (Langzeiterfolge der KARdiOLogischen Anschlussheilbehandlung) study have been reported previously (15).

The aims of the 3-week rehabilitation program are to reduce cardiovascular risk factors, to improve health-related quality of life, and to preserve the ability to work if the patient was still at work at the onset of disease, otherwise the aim was to avert the need for nursing care. This in-hospital rehabilitation program usually starts ~3 weeks after the acute event or coronary artery revascularization. In the present study, only patients who were admitted within 3 months after the acute event or coronary artery revascularization were included.

At the beginning of the rehabilitation program, all participants filled out a standardized questionnaire providing information on alcohol intake, smoking status, and medical history (including history of physician-diagnosed diabetes and hypertension). In addition, information was taken from the patients' hospital charts, which included information from the acute-care hospital. The majority of participants were on a calorie-restricted and/or low-cholesterol diet during the rehabilitation program. The study was approved by the Ethics Boards of the Universities of Ulm and Heidelberg and of the Physicians' chamber of the States of Baden-Wuerttemberg and Hessen (Germany). All participants gave written consent.


At the end of the rehabilitation period, we obtained blood samples under standardized conditions from patients in a fasting state and stored the samples at -80[degrees]C until analysis. Serum adiponectin concentrations were measured by ELISA (BioVendor). The intra- and interassay CVs were both <5.0%. A previous study suggested that a single adiponectin measurement is sufficient for risk assessment in epidemiologic studies (16). We measured C-reactive protein with a high-sensitivity assay (hsCRP; N Latex CRP mono), interleukin-6 (IL-6) with a high-sensitivity ELISA (R&D Systems), and NT-proBNP with a 1-step electrochemiluminescence enzyme immunoassay (Roche Diagnostics). Total cholesterol (TC), HDL-C, and LDL-cholesterol (LDL-C) in blood samples from the Isny clinic were quantified on an Olympus AU2700[TM] Chemistry-Immuno Analyzer and an Olympus AU4500 analyzer with cholesterol reagents from Olympus Europe and HDL-C and LDL-C reagents from Wako Chemicals; the same analytes in blood samples from Bad Nauheim were quantified on a Hitachi 704 with cholesterol, HDL-C, and LDL-C reagents from Greiner BioChemika GmbH. We measured fasting plasma glucose (FPG) with a glucose oxidase method. Diagnosis of metabolic syndrome was made according to the criteria of the National Cholesterol Education Program Adult Treatment Panel III (17), with body mass index (BMI) used as a surrogate for waist circumference.


We carried out all statistical procedures with the SAS[R] statistical software package (release 8.2; SAS Institute Inc.). The associations of sociodemographic characteristics and various cardiovascular risk factors with serum adiponectin concentrations (proportions in top quintile vs first, second, third, or fourth quintile) were determined by means of a [chi square] test. Because serum concentrations of adiponectin, IL-6, hsCRP, triglycerides, and NT-proBNP showed a skewed distribution, we used Spearman correlation coefficients to describe the association between adiponectin and the continuous variables of interest. We calculated partial Spearman correlation coefficients for adiponectin, hsCRP, IL-6, leukocyte count, NT-proBNP, blood lipids such as HDL-C, plasma triglycerides, and TC:HDL ratio. The analyses were performed with various levels of adjustment. We adjusted for variables according to 3 models: model 1, which included age and sex; model 2, which included age, sex, alcohol intake, smoking status, history of hypertension and diabetes mellitus, and intake of lipid-lowering drugs; and model 3, which included BMI and FPG in addition to all variables in model 2. Covariables were added to the models because they were identified to be significantly associated with serum adiponectin in this study or were previously described as determinants of serum adiponectin and/or inflammatory markers and lipid values. A two-sided P value <0.05 was considered statistically significant.


The initial management of CHD in 1174 patients in the acute clinic was noninvasive for 222 patients (18.9%), included percutaneous coronary intervention (including stents) for 408 patients (34.8%), and included coronary artery bypass grafting for 544 patients (46.3%).

Additional characteristics of the study population are shown in Table 1. The mean age was 58.6 years, and 84.5% of the patients were male. Overall, 365 patients (31.1%) fulfilled the criteria for the metabolic syndrome, and 204 (17.4%) had a history of diabetes. The majority of the study patients (n = 904; 76.9%) were on lipid-lowering drug therapy, mainly statins (n = 890). Only a very few were treated with fibrates (n = 14). The mean (SD) LDL-C concentration was 2.62 (0.76) mmol/L [101.3 (29.2) mg/ dL].

The bivariate relationships between various sociodemographic and cardiovascular risk factors and a serum adiponectin concentration in the top quintile of the overall distribution are shown in Table 2. We found that the top quintile of the serum adiponectin distribution had a significantly higher proportions of older patients, female patients, and patients with a BMI <25 kg/[m.sup.2] and lower FPG. In addition, the top quintile had a lower proportion of patients with the metabolic syndrome or a history of hypertension. Patients with no reported alcohol intake and never-smokers were also more often represented in the top quintile of the serum adiponectin distribution.

Scatter plots showing the associations between log-transformed adiponectin and indicators of systemic inflammation (hsCRP), lipid metabolism (HDL-C and triglycerides), and NT-proBNP are presented in Fig. 1.

The results of a partial correlation analysis of the association between serum adiponectin and several markers of systemic inflammation and NT-proBNP are presented in Table 3. After adjustment for age and sex, the associations between adiponectin and hsCRP (r = -0.014), IL-6 (r = -0.010), and leukocyte count (r = -0.049) were not statistically significant, whereas adiponectin was significantly associated with serum NT-proBNP concentrations (r = 0.172; P <0.0001). The latter relationship remained statistically significant even after additional adjustment for a history of diabetes or hypertension, smoking status, alcohol consumption, and intake of lipid-lowering drugs (model 2), as well after further adjustment for BMI and FPG (model 3).

The results of a partial correlation analysis of the association between serum adiponectin and several markers of lipid metabolism are presented in Table 4. After adjustment for age and sex, the associations between adiponectin and HDL-C (r = 0.247), triglycerides (r = -0.206), and TC:HDL ratio (r = -0.149) were all statistically significant. These relationships remained significant even after additional adjustment for a history of diabetes or hypertension, smoking status, alcohol consumption, and intake of lipid-lowering drugs (model 2), as well after further adjustment for BMI and FPG (model 3).


This study of 1174 patients 30-70 years of age with prevalent CHD clearly demonstrates a statistically significant association between serum adiponectin and the presence of atherogenic dyslipidemia. The correlation between adiponectin, triglycerides, and HDL-C remained strongly statistically significant even after adjustment for a wide variety of potential influencing factors, such as age, sex, BMI, history of hypertension or diabetes, alcohol intake, smoking status, lipid-lowering drug therapy, and FPG. Furthermore, we found a positive association between serum adiponectin and NT-proBNP concentrations that remained statistically significant even after multivariate adjustment. In contrast, markers of systemic inflammation were not associated with adiponectin concentrations. This observation supports the hypothesis that adiponectin may mediate at least part of its antiatherosclerotic properties by influencing lipid metabolism, possibly primarily through its effect on HDL-C concentrations.

In vitro evidence exists that adiponectin exerts antiatherosclerotic effects in endothelial cells, macrophages, and aortic smooth muscle cells (18-20). Thus, adiponectin seems to play a protective role in experimental models of vascular injury as well as in the early events in the atherosclerotic process. However, the authors of prospective studies investigating the relationship between adiponectin and CHD in humans have reported conflicting results (11-13,21). A recent study also suggested that there may be a true sex difference in the association of adiponectin with CHD (13). Moreover, the causal relationship between adiponectin concentrations and atherosclerosis in humans remains to be elucidated.

In clinical settings, associations between adiponectin and several biomarkers related to cardiovascular disease have been investigated to further explore potential targets of the assumed antiatherosclerotic properties of adiponectin (1, 4, 7,22). Population-based studies of patients without prevalent CHD reported significant associations between the concentrations of inflammatory markers related to increased risk of CHD (23) and serum adiponectin (11-12). Although we did not find a correlation between adiponectin and markers of systemic inflammation in our large study of patients with manifest CHD, our findings do not necessarily contradict those of previous studies. The lack of association in the current study rather suggests the possibility that the role of systemic inflammation as part of the relationship of adiponectin with atherosclerosis may decrease during the course of the disease.

BNP and NT-proBNP are well-established powerful risk markers in chronic heart failure (CHF) (24). The authors of a recent study reported that adiponectin concentrations were associated with NT-proBNP concentrations in patients with CHF (14). We report a positive association between adiponectin and NT-proBNP in patients with prevalent CHD, which was independent of various covariates. In contrast to the work by Kistorp et al. (14), who investigated patients with markedly decreased left ventricular ejection fraction, our study included predominantly patients with no signs of CHF. For 946 (85%) of the 1174 patients in our study, assessment of left ventricular function was available from the discharge report from the acute-care hospital; 84.8% of these patients had no or only very small reductions in left ventricular function. Our data consequently support the notion that adiponectin and BNP are associated.

The authors of a recent intervention trial reported that changes in adiponectin concentrations after weight loss were correlated with improvements in plasma lipid concentrations independent of changes in adiposity and insulin sensitivity (25). We report a statistically strongly significant and multivariable-adjusted association be tween adiponectin, plasma triglycerides, and HDL-C concentrations. We have previously reported a significant association between adiponectin and pivotal enzymes in lipid metabolism (9,10), and these combined findings clearly support the recent hypothesis that adiponectin directly influences the concentrations of circulating lipids, especially plasma HDL-C concentrations (26).


Hypertriglyceridemia and low HDL-C often occur together in a combination that can be described as an abnormality of the triglyceride-HDL axis (27). This lipid abnormality is clearly associated with a high risk for the development of CHD (28) and is therefore also referred to as atherogenic dyslipidemia (29). Atherogenic dyslipidemia is often seen with the metabolic syndrome (30). In our study, however, we found a significant association between adiponectin and atherogenic dyslipidemia regardless of the presence of the main components of the metabolic syndrome. Further studies are needed to investigate direct links between adiponectin and plasma lipids, especially HDL-C concentrations. However, alternative pathways beyond lipid metabolism and systemic inflammation may account for the association between CHD and adiponectin.

Our study has several limitations that should be considered. Because the acute events leading to diagnosis of CHD or myocardial infarction had occurred at least 3 weeks before patients entered the study, selection of patients with a better prognosis than patients within the early phase of newly diagnosed CHD must be assumed because death attributable to myocardial infarction is highest during the prehospital and early in-hospital phases. Hence, severely ill patients may be underrepresented in our study sample. Of 1174 patients, 890 were receiving statin therapy, and statins have been reported to decrease circulating CRP concentrations (31). Although we adjusted for lipid-lowering drugs in the statistical analyses, residual confounding may be one reason that we found no significant association between adiponectin and CRP. Furthermore, results of recent studies have indicated that different adiponectin isoforms may have distinct biological functions (32,33). We were not able to determine specific associations between these adiponectin isoforms and the investigated variables because our ELISA could not distinguish between lower-molecular-mass trimer forms of adiponectin and high-molecular-mass complexes.

In conclusion, in our study population, serum adiponectin was associated with the presence of atherogenic dyslipidemia and with NT-proBNP concentrations but not with markers of systemic inflammation in patients with manifest CHD. Thus, our results are consistent with the hypothesis that adiponectin may mediate part of its proposed antiatherosclerotic properties by influencing HDL-C concentrations. Therefore, the role of adiponectin as a predictor of and potential therapeutic target for atherogenic dyslipidemia and CHD deserves further investigation. Moreover, additional work is required to elucidate the suggested association between adiponectin and BNP in patients with CHD.

This work was supported by the German Federal Ministry of Education and Research (Grant 01GD9820/0) and by the Association of German Pension Fund Agencies (Grant 02708).

Received September 14, 2005; accepted March 3, 2006.

Previously published online at DOI: 10.1373/clinchem.2005.060509


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[1] Department of Medicine I (Endocrinology and Metabolism), Ruprecht-Karls-University of Heidelberg, Heidelberg, Germany.

[2] Department of Epidemiology, German Centre for Research on Ageing, Heidelberg, Germany.

[3] Nonstandard abbreviations: CHD, coronary heart disease; HDL-C and LDL-C, HDL- and LDL-cholesterol, respectively; BNP, B-type natriuretic peptide; NT-proBNP, N-terminal pro-B-type natriuretic peptide; hsCRP, high-sensitivity C-reactive protein; IL-6, interleukin-6; TC, total cholesterol; FPG, fasting plasma glucose; BMI, body mass index; and CHF, chronic heart failure.

* Address correspondence to this author at: Department of Medicine I (Endocrinology and Metabolism), University of Heidelberg, INF 410, D-69120 Heidelberg, Germany. Fax 49-6221-56-4233; e-mail
Table 1. Sociodemographic, clinical, and laboratory characteristics
of the 1174 patients with stable coronary
artery disease.

Characteristics at baseline

Mean (SD) age, years 58.6 (8.12)
Men, n (%) 992 (84.5)
Mean (SD) BMI, kg/[m.sup.2] 26.9 (3.25)
Medications, n (%)
 Lipid-lowering drugs 903 (76.9)
 ACE (a) inhibitor 626 (53.3)
Alcohol intake (g/week), n (%)
 None 305 (26.0)
 <25 134 (11.4)
 25-75 179 (15.2)
 75-125 146 (12.4)
 125-225 191 (16.3)
 >225 211 (18.0)
Smoking status, n (%)
 Never 363 (30.9)
 Former 747 (63.6)
 Current 64 (5.5)
School education at 698 (59.5)
 least 9 years,n (%)
Marital status (married), n (%) 964 (82.1)
Mean (SD) blood pressure, mmHg
 Systolic 119.9 (15.5)
 Diastolic 73.2 (9.0)
Mean (SD) creatinine clearance, 98.3 (29.8)
Mean (SD) FPG, mmol/L [mg/dL] 5.94 (1.81) [107.1 (32.7)]
History of diabetes, n (%) 204 (17.4)
History of hypertension, n (%) 644 (54.9)
Metabolic syndrome, n (%) 365 (31.1)
Mean (SD) cholesterol,
 mmol/L mg/dL
 Total 4.40 (0.83) [169.9 (32.0)]
 LDL-C 2.62 (0.76) [101.3 (29.2)]
 HDL-C 1.03 (0.27) [39.7 (10.5)]
Mean (SD) TC:HDL-C ratio 4.56 (1.54)
Mean (SD) triglycerides, 1.63 (0.78) [144.8 (68.6)]
mmol/L [mg/dL]
 CRP, (b) mg/L 3.45 (1.25-8.47)
 IL-6, (b) nmol/L 3.78 (2.20-7.20)
 NT-proBNP, (b) [micro]g/L 554.0 (277.1-1094.0)
 Adiponectin, (b) mg/L 7.02 (4.70-10.50)

(a) ACE, angiotensin-converting enzyme.

(b) Geometric mean (interquartile range).

Table 2. Variable proportions in top quintile of serum
adiponectin concentration.

 Proportion of patients
 in top quintile of
Variable n distribution, % P (a)

Age, years <0.0001
 30-39 27 7.4
 40-49 156 12.2
 50-59 346 16.2
 60-70 645 24.2

Sex <0.0001
 Female 182 41.2
 Male 992 15.9

BMI, kg/[m.sup.2] <0.0001
 <25 336 31.9
 25-30 628 14.8
 >30 209 15.8

FPG, mmol/L (mg/dL) <0.05
 <5.5 (100) 602 21.6
 5.6-6.9 (100-125) 383 19.3
 >7.0 (126) 189 15.3

Diabetes mellitus NS (b)
 Yes 204 18.1
 No 970 20.2

Metabolic syndrome <0.0001
 Yes 365 14
 No 809 22.5

Hypertension 0.05
 Yes 644 18.6
 No 530 21.3

Alcohol intake 25 <0.0001
 Yes 869 16.8
 No 305 28.9

Smoking status <0.001
 Never 363 26.2
 Former 747 16.6
 Current 64 21.9

(a) P values represent the association of all plasma adiponectin
quintiles with all categories of the other characteristics by
[chi square] test.

(b) NS, not significant.

Table 3. Partial Spearman correlation coefficients for association
between plasma adiponectin and inflammatory markers
and NT-proBNP. (a)

 hsCRP IL-6

 r P r P

Model 1: adjusted for -0.014 0.63 -0.010 0.73
 age and sex
Model 2: adjusted for -0.008 0.79 -0.011 0.72
 multiple covariates (b)
Model 3: adjusted for BMI, 0.006 0.85 -0.008 0.79
 FPG, and same covariates
 as in model 2

 count NT-proBNP

 r P r P

Model 1: adjusted for 0.049 0.09 0.172 <0.0001
 age and sex
Model 2: adjusted for 0.042 0.15 0.177 <0.0001
 multiple covariates (b)
Model 3: adjusted for BMI, 0.035 0.24 0.149 <0.0001
 FPG, and same covariates
 as in model 2

(a) Bold P values indicate statistical significance (P < 0.05).

(b) Adjusted for age, sex, history of diabetes or hypertension,
smoking status, alcohol intake, and lipid-lowering drug therapy.

Table 4. Partial Spearman correlation coefficients for association
between plasma adiponectin and lipid concentrations. (a)

 Triglycerides HDL

 r P r P

Model 1: adjusted for -0.206 <0.0001 0.247 <0.0001
 age and sex
Model 2: adjusted for -0.192 <0.0001 0.234 <0.0001
 multiple covariates (b)
Model 3: adjusted for BMI, -0.162 <0.0001 0.207 <0.0001
 FPG, and same
 covariates as in model 2


 r P

Model 1: adjusted for -0.149 <0.0001
 age and sex
Model 2: adjusted for -0.147 <0.0001
 multiple covariates (b)
Model 3: adjusted for BMI, -0.116 <0.0001
 FPG, and same
 covariates as in model 2

(a) Bold P values indicate statistical significance (P < 0.05).

(b) Adjusted for age, sex, history of diabetes or hypertension,
smoking status, alcohol intake, and lipid-lowering drug therapy.
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Title Annotation:Lipids, Lipoproteins and Cardiovascular Risk Factors
Author:von Eynatten, Maximilian; Hamann, Andreas; Twardella, Dorothee; Nawroth, Peter P.; Brenner, Hermann;
Publication:Clinical Chemistry
Date:May 1, 2006
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