The joint role of collagen turn-over biomarkers and late gadolinium enhancement to predict cardiovascular outcome in nonischemic dilated cardiomyopathy

Abstract

Abstract Background Myocardial scarring is a primary pathogenetic process in nonischemic dilated cardiomyopathy (NIDCM) which is responsible for progressive cardiac remodeling and heart failure, severely impacting the survival of these patients. Although several collagens turn-over biomarkers have been associated with myocardial fibrosis, their clinical utility is still limited. Late gadolinium enhancement (LGE) determined by cardiac magnetic resonance imaging (CMR) has become a feasible method to detect myocardial replacement fibrosis. Purpose We sought to evaluate the association between collagen turn-over biomarkers and replacement myocardial scarring by CMR and, also, to test their ability to predict outcome in conjunction with LGE in patients with NIDCM. Method We conducted a prospective study on 194 patients (48.7±14.3 years of age; 74% male gender) with NIDCM. CMR was used to determine the presence and extent of LGE. Several collagen turn-over biomarkers were determined at the diagnosis, comprising galectin-3 (Gal3), procollagen type I carboxy-terminal pro-peptide (PICP) and N-terminal pro-peptide of procollagen type III (PIIINP). A composite outcome (all-cause mortality, ventricular tachyarrhythmias, heart failure hospitalization) was ascertained over a median of 26 months. Of all, 17% (n=33) of patients reached the outcome: all-cause mortality (n=6), malignant ventricular tachyarrhythmia (n=14) and HF hospitalization (n=13). Results Gal3, PICP and PIIINP were considerably increased in those with LGE+ (p<0.001), being also directly correlated with LGE mass (r2=0.42; r2=0.44; r2=0.31; all p<0.001). Receiver operating characteristic (ROC) analysis revealed significant ability to diagnose LGE, with area under the ROC: 0.816 for Gal3, 0.705 for PICP, and 0.757 for PIIINP (all p<0.0001). Kaplan-Meier analysis showed that at a threshold of >13.8 ng/dL for Gal3 and >97 ng/dL for PICP, they significantly predicted the outcome (HR=2.66, p<0.001; HR=1.93, p<0.002). Moreover, for a combined model of LGE+/Gal3+/PICP+, time-to-event analysis demonstrated the highest ability to predict composite outcome, as compared to any other models (p=0.004). Nevertheless, in multivariate analysis, after adjustment for covariates, only LGE+ and Gal3+ remained independent predictors for outcome (p=0.008; p=0.04). Conclusion In patients with NIDCM, serum collagen turn-over biomarkers such as Gal3, PICP and PIIINP are closely related to the presence and extent of LGE and can significantly predict cardiovascular outcome. The joint use of LGE with Gal3 and PICP significantly improved outcome prediction. Funding Acknowledgement Type of funding sources: None.