Determinants of temporal changes in galectin-3 level in the general population: Data of PREVEND

• Published in: International journal of cardiology 2016-11, Vol.222, p.385-390
• Main Authors: van der Velde, A. Rogier, Meijers, Wouter C, van den Heuvel, Edwin, Bakker, Stephan J.L, van Gilst, Wiek, van der Harst, Pim, Hillege, Hans, de Boer, Rudolf A
• Format: Article
• Language: English
• Subjects: Adult; Aged; Biomarker; Biomarkers - blood; Blood pressure; Blood Pressure - physiology; Cardiovascular; Cohort Studies; Female; Follow-Up Studies; Galectin 3 - blood; Galectin-3; Humans; Kidney Failure, Chronic - blood; Kidney Failure, Chronic - diagnosis; Kidney Failure, Chronic - prevention & control; Male; Middle Aged; Population Surveillance - methods; Prospective Studies; Serial measurements; Statistics as Topic - trends; Time Factors
• ISSN: 0167-5273; 1874-1754
• DOI: 10.1016/j.ijcard.2016.07.241

Abstract Background High baseline galectin-3 levels are associated with increased risk for adverse cardiovascular outcomes in the general population, but determinants of changes in galectin-3 levels over time have not been established. Therefore, we aimed to identify determinants of (temporal) change in galectin-3 levels. Methods Galectin-3 plasma levels were measured in a large community based cohort (PREVEND study) at 3 different time points: at baseline, after ~ 4 and ~ 9 years. The association of baseline clinical and biochemical factors and (temporal) changes in galectin-3 level was assessed using multivariable mixed-effects regression modeling. Results In 4355 subjects, galectin-3 plasma levels were available at all time points (mean age: 48 ± 12 years; 50% female). Median galectin-3 level at baseline was 10.7 [8.9–12.7] ng/mL which gradually increased to 11.5 [9.4–14.3] ng/mL after ~ 9 years. Using mixed-effects regression modeling, we first validated as independent determinants of baseline circulating galectin-3: eGFR (chi square (χ2 ):210.27, p < 0.0001), gender (χ2 :43.85; p < 0.0001), BMI (χ2 :19.68, p = 0.0001), NT-proBNP (χ2 :18.76, p = 0.0001) and serum (total) cholesterol (χ2 :8.63, p = 0.01). Furthermore, we identified urinary albumin excretion (χ2 :34.03, p-value: < 0.0001) and systolic blood pressure (χ2 :16.81, p = 0.002) as independent determinants of temporal changes of galectin-3. Conclusions In the general population, urinary albumin excretion > 30 mg/ 24 h and systolic blood pressure > 170 mmHg were identified as significant determinants of dynamic increases in galectin-3 levels over time. These results implicate that treatment of high blood pressure might be effective to prevent increasing galectin-3 levels and its associated conditions.