Sharma et al. [20
] provided the first report in human subjects. They studied ventricular biopsies from patients with aortic stenosis with preserved or depressed ejection fraction and showed that galectin-3 was upregulated in the biopsies from patients with depressed ejection fraction. van Kimmenade et al. [43
] published the first clinical study that evaluated the potential role of galectin-3 as a plasma biomarker in heart failure. In this study, 599 acutely dyspneic subjects were evaluated with the goal to establish the usefulness of N-terminal prohormone brain natriuretic peptide (NT-proBNP), galectin-3, and apelin in diagnosing heart failure and predicting outcome. A blood sample was collected at baseline, and NT-proBNP, galectin-3, and apelin were measured later. A total of 209 patients were diagnosed with heart failure. NT-proBNP was the most powerful predictor for diagnosing heart failure. Receiver operating characteristic analysis examining the value of NT-proBNP for the diagnosis acute heart failure showed an area under the curve (AUC) for NT-proBNP of 0.94 (P
0.0001), whereas the AUC for galectin-3 for the diagnosis acute heart failure was 0.72 (P
< 0.0001). The difference between NT-proBNP and galectin-3 being highly significant (P
< 0.0001). The optimal cut-off of galectin-3 in this study was 6.88 ng/mL, which resulted in a reasonable sensitivity of 80% but a poor specificity of 52% [43
]. For predicting short-term prognosis (60 days, primary end-point rehospitalization caused by heart failure [n
60] or all-cause mortality [n
= 17]), galectin-3 was the most powerful predictor: an AUC for galectin-3 of 0.74 (P
0.0001) and an AUC for NT-proBNP of 0.67 (P
= 0.009), with the difference being borderline significant (P
= 0.05). In multivariate analysis, galectin-3 was the strongest predictor for death and the combination of death and rehospitalizations for heart failure. Remarkably, well-known predictors for outcome, such as NT-proBNP and renal function, were not predictive in this study. Nevertheless, this study provides strong support for the exploration of galectin-3 as a biomarker that may predict prognosis, whereas its usefulness in detecting heart failure or adding incremental value (over currently used clinical correlates and NT-proBNP) in the diagnostic work-up of heart failure remains unclear.
In a larger study in patients with chronic heart failure (n
= 232), showed that galectin-3 predicts long-term outcome (mean follow-up, 3.4 y; HR, 1.95; 95% CI, 1.24–3.09; P
0.004; unpublished data, Lok et al.). Because not many other biomarkers of heart failure were measured, it is impossible to value the precise role of galectin-3 in this cohort from this study.
An interesting mechanistic study by Milting et al. [44
] describes the kinetics of galectin-3 in 55 patients with end-stage heart failure with the need for mechanical circulatory support (MCS). This small study determined several biomarkers especially related to myocardial fibrosis and remodeling. First, the fibrosis-related biomarkers including galectin-3 were increased compared with controls. Second, the authors reported that no fibrosis-related biomarkers, such as tissue inhibitor of metalloproteinases-1 (TIMP-1), tenascin, osteopontin, or galectin-3, were reduced by MCS; only the loading-related biomarker BNP was reduced by MCS. Third, patients who did not survive on MCS, compared with patients who lived until transplantation, had higher baseline galectin-3 levels.
A recent study by Lin et al. [45
] described the relation between serum galectin-3 and markers of extracellular matrix turnover. They studied 106 patients with chronic heart failure (New York Heart Association class II-III; mean LV ejection fraction [LVEF], 35
9%). Serum aminoterminal propeptide of procollagen type I (PINP) and type III (PIIINP), matrix metalloproteinase-2 (MMP-2), and TIMP-1 were analyzed, along with galectin-3. Galectin-3 was correlated with PIIINP, TIMP-1, MMP-2, but not with LVEF, age, and sex. After correction, the correlation between galectin-3 and PIIINP and MMP-2 remained statistically significant. The authors conclude that these findings suggest a relationship between gelactin-3 and extracellular matrix turnover.
Taken together, from available clinical data, plasma and/or serum galectin-3 is increased in acute and chronic heart failure. It seems that galectin-3 may be of particular value to predict prognosis. However, for clinical diagnosing and/or decision making, it seems less powerful, although we do not have sufficient data available.