Adiponectin exerts anti-inflammatory and antiatherogenic effects and appears to protect against arteriosclerosis. Accordingly, an association between low concentrations of plasma adiponectin and cardiovascular (CV) disease has been demonstrated in several studies. In contrast, elevated plasma adiponectin has been associated with increased mortality and an increasing number of major adverse CV events (MACE). Because of these conflicting results, the true role of adiponectin remains to be elucidated. In the Copenhagen City Heart Study, we prospectively followed up 5,624 randomly selected men and women from the community without CV disease. Plasma adiponectin was measured at the beginning of the study. The median follow-up time was 7.8 years (interquartile range 7.3 to 8.3). The end point was all-cause mortality (n = 801), and the combined end point was MACE, consisting of CV mortality or nonfatal myocardial infarction or ischemic stroke (n = 502). High adiponectin was inversely associated with an increasing number of traditional CV risk factors (p <0.0001). The geometric mean adiponectin concentrations were 10.0 mg/L (95% confidence interval [CI] 9.7 to 10.4) for persons with no CV risk factors present versus 8.1 mg/L (95% CI 7.8 to 8.4) for persons with 4 CV risk factors. After adjustment for confounding risk factors by Cox regression analysis, adiponectin remained an independent predictor of death and MACE. The hazard ratio for each increase in adiponectin of 5 mg/L for death and MACE was 1.20 (95% CI 1.14 to 1.27; p <0.0001) and 1.14 (95% CI 1.05–1.23; p <0.0001), respectively. In conclusion, an increasing number of risk factors for CV disease is associated with decreased plasma adiponectin. High plasma adiponectin independently predicted death and MACE in a large community-based population. These results have confirmed the dual expression indicated by previous studies.
Adiponectin, a protein mainly produced in white adipose tissue, is involved in several antioxidant, anti-inflammatory, and antiarteriosclerotic processes, and hypoadiponectinemia is a risk factor for the development of hypertension and impaired glucose tolerance. In healthy subjects, an elevated plasma adiponectin level has been shown to protect against cardiovascular (CV) disease (CVD). However, in those with CVD or diabetes mellitus (DM), high plasma adiponectin levels have been positively associated with increased mortality and CV events. To explain these conflicting results, it has been proposed that increased adiponectin levels reflect a compensatory and vasculoprotective mechanism; thus, adiponectin can be used as a marker of vascular damage and subclinical arteriosclerosis. This could make adiponectin measurement very useful in the risk prediction of CVD in the general population. To elucidate the prognostic value of plasma adiponectin in the general population, we measured total plasma adiponectin in a large community-based population and performed long-term follow-up.
Methods
The present study included 5,624 men and women (aged 20 to 94 years) without CVD from the Fourth Copenhagen City Heart Study, a longitudinal cohort study of CVD and risk factors that has been previously described. A total of 6,035 subjects were examined; however, we excluded 277 because of prevalent CVD and 134 because of missing data on plasma adiponectin levels. The patients were followed up for 7.8 years (interquartile range 7.3 to 8.3). Follow-up information on death, cause of death, and the occurrence of new myocardial infarction (MI) or ischemic stroke was obtained for all 5,624 subjects (100%) included in the present study from the National Person Identification Registry. The data were collected using hospital source data and data from the highly validated Danish National Board of Health’s National Patient Registry. The end points were all-cause mortality and major CV events (MACE) defined as CV mortality or hospitalization for MI or ischemic stroke. Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or use of antihypertensive medication. DM was defined as a plasma glucose concentration ≥11.1 mmol/L, the use of antidiabetic medicine, self-reported disease, or a hemoglobin A1c level ≥7.0%. Hypercholesterolemia was defined as the use of cholesterol-lowering medicine or a total cholesterol level of ≥7.0 mmol/L. Ischemic heart disease was defined as a history of hospital admission because of acute MI, percutaneous coronary intervention, or coronary artery bypass grafting.
All subjects gave informed consent to participate, and the study was performed in accordance with the second Helsinki Declaration and approved by the regional ethics committee.
Blood samples for measurement of plasma adiponectin were immediately centrifuged at 3,000 rpm for 10 minutes, and the plasma was stored at −80°C until subsequent analysis. Plasma adiponectin was determined by a validated in-house time-resolved immunofluorometric assay, as previously described. All samples were analyzed in duplicate, with a detection limit of 1.5 μg/L and intra- and interassay coefficient of variation of <5% and <7%, respectively. Other blood tests, including high-sensitivity C-reactive protein, blood glucose, lipids, and creatinine were assayed using routine laboratory methods. The estimated glomerular filtration rate was calculated from the serum creatinine, age, and gender using the Cockcroft-Gault formula.
The Framingham risk score was calculated from published equations using age, gender, systolic blood pressure, antihypertensive treatment, smoking, total cholesterol, and high-density lipoprotein cholesterol. The Framingham risk score was used to divide patients into 4 risk groups (low risk, <5%; medium risk, 5% to 10%; high risk, 10% to 20%; and very high risk, ≥20%). Because of missing values and because the Framingham risk score can only be calculated in patients <80 years old, it was only possible to calculate the risk score for 5,023 patients (89%).
Plasma adiponectin concentrations were positively skewed and, therefore, were logarithmically transformed before analysis. Linear trends were tested using linear regression analysis for continuous variables and the Cochran-Armitage test for trend for category variables ( Table 1 ). The Kaplan-Meier curves according to adiponectin quintiles were constructed and compared using the log-rank test. The association of adiponectin with all-cause mortality and MACE were examined using Cox proportional hazards regression analyses, with both follow-up time and age as the underlying time scale. Deviation from linearity was assessed by simultaneous assessment of the linear and quadratic effects. Evaluation of first order interactions was made in the final model, adjusting for multiple testing using the Bonferroni method. Misspecification of the functional form of the covariates and the assumption of proportional hazards were evaluated by plots of the cumulative martingale residuals. Cox proportional hazards regression analyses using nonlogarithmically adiponectin values were used because they complied with the model assumptions. C statistics for survival data were computed, and the differences between models were assessed using bootstrapping. p Values <5% on 2-sided tests were considered significant.
| Variables | Adiponectin Quintile | p Value | ||||
|---|---|---|---|---|---|---|
| 1 (n = 1,102) | 2 (n = 1,111) | 3 (n = 1,138) | 4 (n = 1,139) | 5 (n = 1,134) | ||
| Age (yrs) | 58 ± 17 | 58 ± 17 | 58 ± 17 | 58 ± 17 | 58 ± 17 | — |
| Male gender | 41.5% | 41.4% | 41.4% | 42.1% | 41.7% | — |
| Diabetes mellitus | 15% | 8% | 5% | 4% | 5% | <0.001 |
| Hemoglobin A1c (%) | <0.001 | |||||
| Median | 6.0% | 5.9% | 5.8% | 5.8% | 5.7% | |
| Interquartile range | 5.6–6.4% | 5.5–6.3% | 5.4–6.2% | 5.4–6.1% | 5.4–6.1% | |
| Hypertension ∗ | 51% | 50% | 47% | 48% | 47% | 0.008 |
| Systolic blood pressure (mm Hg) | 138 ± 22 | 138 ± 23 | 137 ± 23 | 137 ± 23 | 137 ± 24 | 0.284 |
| Diastolic blood pressure (mm Hg) | 79 ± 12 | 79 ± 12 | 79 ± 12 | 78 ± 12 | 79 ± 13 | 0.378 |
| Hypercholesterolemia † | 8% | 6% | 6% | 5% | 4% | <0.001 |
| Total cholesterol | 0.988 | |||||
| mmol/L | 5.5 ± 1.2 | 5.4 ± 1.1 | 5.5 ± 1.1 | 5.5 ± 1.1 | 5.5 ± 1.1 | |
| mg/dl | 213 ± 46 | 209 ± 43 | 213 ± 43 | 213 ± 43 | 213 ± 43 | |
| High-density lipoprotein cholesterol | <0.001 | |||||
| mmol/L | ||||||
| Median | 1.2 | 1.3 | 1.4 | 1.5 | 1.7 | |
| Interquartile range | 1.0–1.5 | 1.1–1.6 | 1.2–1.7 | 1.3–1.9 | 1.4–2.1 | |
| mg/dl | ||||||
| Median | 46 | 50 | 54 | 58 | 66 | |
| Interquartile range | 39–58 | 43–62 | 46–66 | 50–73 | 54–81 | |
| Low-density lipoprotein cholesterol | <0.001 | |||||
| mmol/L | ||||||
| Median | 3.5 | 3.5 | 3.5 | 3.4 | 3.3 | |
| Interquartile range | 2.8–4.2 | 2.8–4.2 | 2.8–4.2 | 2.7–4.1 | 2.6–4.0 | |
| mg/dl | ||||||
| Median | 135 | 135 | 135 | 131 | 128 | |
| Interquartile range | 108–162 | 108–162 | 108–162 | 104–159 | 101–155 | |
| Triglycerides | ||||||
| mmol/L | <0.001 | |||||
| Median | 1.7 | 1.5 | 1.3 | 1.2 | 1.0 | |
| Interquartile range | 1.2–2.5 | 1.1–2.1 | 0.9–1.7 | 0.9–1.6 | 0.7–1.4 | |
| mg/dl | ||||||
| Median | 151 | 133 | 115 | 106 | 89 | |
| Interquartile range | 106–221 | 97–186 | 80–151 | 80–142 | 62–124 | |
| Current smoking | 37% | 35% | 33% | 31% | 30% | <0.001 |
| Body mass index (kg/m 2 ) | 27.6 ± 4.6 | 26.5 ± 4.4 | 25.9 ± 4.2 | 25.1 ± 3.9 | 24.2 ± 3.9 | <0.001 |
| High-sensitivity C-reactive protein (mg/L) | <0.001 | |||||
| Median | 2.3 | 1.6 | 1.5 | 1.2 | 1.0 | |
| Interquartile range | 1.0–5.0 | 0.8–3.5 | 0.7–3.5 | 0.6–2.7 | 0.5–2.2 | |
| Creatinine (μmol/L) | 80 ± 14 | 80 ± 15 | 80 ± 15 | 79 ± 14 | 70 ± 15 | 0.357 |
| Estimated glomerular filtration rate (ml/min) | <0.001 | |||||
| Median | 90 | 88 | 85 | 85 | 80 | |
| Interquartile range | 69–112 | 70–107 | 67–104 | 65–104 | 63–100 | |
| Known heart failure | 2.1% | 2.3% | 0.7% | 1.5% | 1.9% | 0.286 |
| Distal blood pressure (mm Hg) | 1.03 ± 0.16 | 1.04 ± 0.15 | 1.04 ± 0.15 | 1.05 ± 0.14 | 1.03 ± 0.15 | 0.844 |
| Distal blood pressure <0.70 mm Hg | 4.5% | 3.0% | 3.6% | 2.3% | 3.4% | 0.106 |
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
