Réka Faludi1, Gabriella Nagy2, Margit Tőkés-Füzesi3, Krisztina Kovács4, László Czirják2, András Komócsi5. 1. Heart Institute, Faculty of Medicine, University of Pécs, Pécs, Hungary. Electronic address: faludi.reka@pte.hu. 2. Department of Rheumatology and Immunology, Faculty of Medicine, University of Pécs, Pécs, Hungary. 3. Department of Laboratory Medicine, Faculty of Medicine, University of Pécs, Pécs, Hungary. 4. Department of Biochemistry and Medical Chemistry, Faculty of Medicine, University of Pécs, Pécs, Hungary. 5. Heart Institute, Faculty of Medicine, University of Pécs, Pécs, Hungary.
Abstract
BACKGROUND: Galectin-3 is a beta-galactoside-binding lectin that may be related to tissue sclerosis or aberrant activation of angiogenesis in systemic sclerosis (SSc). The aim of our study was to determine the associations between galectin-3 levels and patient characteristics, as well as to investigate the long term prognostic value of galectin-3 in a large cohort of SSc patients. METHODS: 152 patients with SSc (55±11years, 138 female) were included in our follow-up study. Blood samples and clinical data were collected at baseline. Primary and secondary outcomes were all-cause and cardiovascular mortality, respectively. RESULTSS: Galectin-3 levels showed positive correlation with the grade of left ventricular diastolic function (r=0.193; p=0.026), erythrocyte sedimentation rate (r=0.172; p=0.036) and serum level of C-reactive protein (r=0.200; p=0.015) while negative correlation with diffusing capacity for carbon monoxide (r=-0.228; p=0.006), in age, gender and BSA adjusted analyses. During the follow-up of 7.2±2.3years, 35 SSc patients (23%) died. In multivariate Cox regression analyses adjusted for age, gender, BSA, creatinine and NT-proBNP levels, galectin-3 was an independent predictor both of the all-cause mortality (HR: 2.780, 95% CI: 1.320-5.858, p=0.007) and cardiovascular mortality (HR: 3.346, 95% CI: 1.118-10.012, p=0.031). Using receiver-operating characteristic analysis, galectin-3>10.25ng/ml was found to be the best predictor of the all-cause mortality. CONCLUSIONS: Our results suggest that galectin-3 is an independent predictor of all-cause and cardiovascular mortality in SSc. Validation studies are required to establish whether galectin-3 may be proposed as simple biomarker for identifying patients with high mortality risk in SSc.
BACKGROUND: Galectin-3 is a beta-galactoside-binding lectin that may be related to tissue sclerosis or aberrant activation of angiogenesis in systemic sclerosis (SSc). The aim of our study was to determine the associations between galectin-3 levels and patient characteristics, as well as to investigate the long term prognostic value of galectin-3 in a large cohort of SSc patients. METHODS: 152 patients with SSc (55±11years, 138 female) were included in our follow-up study. Blood samples and clinical data were collected at baseline. Primary and secondary outcomes were all-cause and cardiovascular mortality, respectively. RESULTSS: Galectin-3 levels showed positive correlation with the grade of left ventricular diastolic function (r=0.193; p=0.026), erythrocyte sedimentation rate (r=0.172; p=0.036) and serum level of C-reactive protein (r=0.200; p=0.015) while negative correlation with diffusing capacity for carbon monoxide (r=-0.228; p=0.006), in age, gender and BSA adjusted analyses. During the follow-up of 7.2±2.3years, 35 SSc patients (23%) died. In multivariate Cox regression analyses adjusted for age, gender, BSA, creatinine and NT-proBNP levels, galectin-3 was an independent predictor both of the all-cause mortality (HR: 2.780, 95% CI: 1.320-5.858, p=0.007) and cardiovascular mortality (HR: 3.346, 95% CI: 1.118-10.012, p=0.031). Using receiver-operating characteristic analysis, galectin-3>10.25ng/ml was found to be the best predictor of the all-cause mortality. CONCLUSIONS: Our results suggest that galectin-3 is an independent predictor of all-cause and cardiovascular mortality in SSc. Validation studies are required to establish whether galectin-3 may be proposed as simple biomarker for identifying patients with high mortality risk in SSc.
Authors: Cory A Perugino; Sultan B AlSalem; Hamid Mattoo; Emanuel Della-Torre; Vinay Mahajan; Gayathri Ganesh; Hugues Allard-Chamard; Zachary Wallace; Sydney B Montesi; Johannes Kreuzer; Wilhelm Haas; John H Stone; Shiv Pillai Journal: J Allergy Clin Immunol Date: 2018-05-29 Impact factor: 10.793
Authors: Catherine E Simpson; Rachel L Damico; Paul M Hassoun; Lisa J Martin; Jun Yang; Melanie K Nies; R Dhananjay Vaidya; Stephanie Brandal; Michael W Pauciulo; Eric D Austin; D Dunbar Ivy; William C Nichols; Allen D Everett Journal: Chest Date: 2020-01-25 Impact factor: 9.410
Authors: Efstathia Pasmatzi; Christina Papadionysiou; Alexandra Monastirli; George Badavanis; Dionysios Tsambaos Journal: An Bras Dermatol Date: 2019-07-29 Impact factor: 1.896
Authors: Salvatore Sciacchitano; Luca Lavra; Alessandra Morgante; Alessandra Ulivieri; Fiorenza Magi; Gian Paolo De Francesco; Carlo Bellotti; Leila B Salehi; Alberto Ricci Journal: Int J Mol Sci Date: 2018-01-26 Impact factor: 5.923