Abstract. de Boer RA, van Veldhuisen DJ, Gansevoort RT, Muller Kobold AC, van Gilst WH, Hillege HL, Bakker SJL, van der Harst P (University of Groningen). The fibrosis marker galectin-3 and outcome in the general population. J Intern Med 2012; 272: 55-64.Objective. Galectin-3 is involved in fibrosis and inflammation and plays a role in heart failure, renal disease, obesity and cancer. We aimed to establish the relationship between galectin-3 and cardiovascular (CV) risk factors and mortality in the general population.Design and subjects. This study included 7968 subjects from the Prevention of REnal and Vascular ENd-stage Disease (PREVEND) cohort, with a median follow-up of approximately 10 years. Plasma galectin-3 was measured in baseline samples.Main outcome measures. We investigated the relationships between galectin-3 levels, demographic characteristics and risk factors of CV disease. We determined the prognostic value for all-cause, CV and cancer mortality.Results. The mean age of the population was 50 ± 13 years. Mean blood pressure was 129 ⁄ 74 mmHg, mean cholesterol was 5.7 ± 1.1 mmol L )1 and median galectin-3 was 10.9 ng mL )1 [interquartile range (IQR) 9.0-13.1]. Galectin-3 levels correlated with a wide range of risk factors of CV disease, including blood pressure, serum lipids, body mass index, renal function and N-terminal pro-B-type natriuretic peptide (P < 0.0001). We observed a strong association between galectin-3 and age. Furthermore, we found a gender interaction, with female subjects (n = 4001) having higher median galectin-3 levels (11.0 ng mL )1 , IQR 9.1-13.4 vs. men (n = 3967) 10.7 ng mL )1 , IQR 8.9-12.8; P < 0.0001), and galectin-3 levels in women more strongly correlated with risk factors of CV disease. After correction for the classical CV risk factors (smoking, blood pressure, cholesterol and diabetes), galectin-3 levels independently predicted all-cause mortality (hazard ratio per SD galectin-3 1.09, 95% CI 1.01-1.19; P = 0.036), but not CV and cancer mortality separately.Conclusions. Galectin-3 is associated with age and risk factors of CV disease, with a strong gender interaction for these correlations. Galectin-3 predicts all-cause mortality in the general population.
BackgroundThe clustering of metabolic and cardiovascular risk factors is known as metabolic syndrome (MetS). The risk of having MetS is strongly associated with increased adiposity and can be further modified by smoking behavior. Apolipoproteins (apo) associated with low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C) may be altered in MetS. This study aimed to examine the association between smoking and the following parameters: MetS and its components, levels of apolipoproteins and estimated lipoprotein particle size, separately for men and women, and in different body mass index (BMI) classes.MethodsWe included 24,389 men and 35,078 women aged between 18 and 80 years who participated in the LifeLines Cohort Study between December 2006 and January 2012; 5,685 men and 6,989 women were current smokers. Participants were categorized into three different body mass index (BMI) classes (BMI <25; BMI 25 to 30; BMI ≥30 kg/m2). MetS was defined according to the National Cholesterol Education Program’s Adult Treatment Panel III (NCEP:ATPIII) criteria. Blood pressure, anthropometric and lipid measurements were rigorously standardized, and the large sample size enabled a powerful estimate of quantitative changes. The association between smoking and the individual MetS components, and apoA1 and apoB, was tested with linear regression. Logistic regression was used to examine the effect of smoking and daily tobacco smoked on risk of having MetS. All models were age adjusted and stratified by sex and BMI class.ResultsPrevalence of MetS increased with higher BMI levels. A total of 64% of obese men and 42% of obese women had MetS. Current smoking was associated with a higher risk of MetS in both sexes and all BMI classes (odds ratio 1.7 to 2.4 for men, 1.8 to 2.3 for women, all P values <0.001). Current smokers had lower levels of HDL cholesterol and apoA1, higher levels of triglycerides and apoB, and higher waist circumference than non-smokers (all P <0.001). Smoking had no consistent association with blood pressure or fasting blood glucose. In all BMI classes, we found a dose-dependent association of daily tobacco consumption with MetS prevalence as well as with lower levels of HDL cholesterol, higher triglyceride levels and lower ratios of HDL cholesterol/apoA1 and, only in those with BMI <30, LDL cholesterol/apoB (all P <0.001).ConclusionsSmoking is associated with an increased prevalence of MetS, independent of sex and BMI class. This increased risk is mainly related to lower HDL cholesterol, and higher triglycerides and waist circumference. In addition, smoking was associated with unfavorable changes in apoA1 and apoB, and in lipoprotein particle size.Please see related commentary: http://www.biomedcentral.com/1741-7015/11/196.
AimsBiomarkers can be used for diagnosis, risk stratification, or management of patients with heart failure (HF). Knowledge about the biological variation is needed for proper interpretation of serial measurements. Therefore, we aimed to determine and compare the biological variation of a large panel of biomarkers in healthy subjects and in patients with chronic HF.Methods and resultsThe biological variability of established biomarkers [NT‐proBNP and high‐sensitivity troponin T (hsTnT)], novel biomarkers [galectin‐3, suppression of tumorigenicity 2 (ST2), and growth differentiation factor 15 (GDF‐15)], and renal/neurohormonal biomarkers (aldosterone, phosphate, parathyroid hormone, plasma renin concentration, and creatinine) was determined in 28 healthy subjects and 83 HF patients, over a period of 4 months and 6 weeks, respectively. The analytical (CVa), intraindividual (CVi), and interindividual (CVg) variations were calculated, as well as the reference change value (RCV), which reflects the percentage of change that may indicate a ‘relevant’ change. All crude biomarker levels were significantly increased or decreased in HF patients compared with controls (all P < 0.01). Variation indices were comparable in healthy individuals and HF patients. CVi was not influenced by the individual levels of the biomarker itself. NT‐proBNP and GDF‐15 had relatively high CVi (21.8% and 16.6%) and RCV (61.7% and 64.3%), whereas ST2 (CVi, 15.0; RCV, 42.9%), hsTnT (CVi, 11.1; RCV, 31.4%), and galectin‐3 (CVi, 8.1; RCV, 25.0%) had lower indices of variation.ConclusionBiological variation indices are comparable between healthy subjects and HF patients for a broad spectrum of biomarkers. NT‐proBNP and GDF‐15 have substantial variation, with lower variation for ST2, hsTnT, and galectin‐3. These data are instrumental in proper interpretation of biomarker levels in HF patients.
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