Independent and Combined Effects of Telomere Shortening and mtDNA<sup>4977</sup> Deletion on Long-term Outcomes of Patients with Coronary Artery Disease

oleh: Cecilia Vecoli, Andrea Borghini, Silvia Pulignani, Antonella Mercuri, Stefano Turchi, Eugenio Picano, Maria Grazia Andreassi

Format: Article
Diterbitkan: MDPI AG 2019-11-01

Deskripsi

Aging is one of the main risk factors for cardiovascular disease, resulting in a progressive organ and cell decline. This study evaluated a possible joint impact of two emerging hallmarks of aging, leucocyte telomere length (LTL) and common mitochondrial DNA deletion (mtDNA<sup>4977</sup>), on major adverse cardiovascular events (MACEs) and all-cause mortality in patients with coronary artery disease (CAD). We studied 770 patients (673 males, 64.8 &#177; 8.3 years) with known or suspected stable CAD. LTL and mtDNA<sup>4977</sup> deletion were assessed in peripheral blood using qRT-PCR. During a median follow-up of 5.4 &#177; 1.2 years, MACEs were 140 while 86 deaths were recorded. After adjustments for confounding risk factors, short LTLs and high mtDNA<sup>4977</sup> deletion levels acted independently as predictors of MACEs (HR: 2.2, 95% CI: 1.2&#8722;3.9, <i>p</i> = 0.01 and HR: 1.7, 95% CI: 1.1&#8722;2.9, <i>p</i> = 0.04; respectively) and all-cause mortality events (HR: 2.1, 95% CI: 1.1&#8722;4.6, <i>p</i> = 0.04 and HR: 2.3, 95% CI: 1.1&#8722;4.9, <i>p</i> = 0.02; respectively). Patients with both short LTLs and high mtDNA<sup>4977</sup> deletion levels had an increased risk for MACEs (HR: 4.3; 95% CI: 1.9&#8722;9.6; <i>p</i> = 0.0006) and all-cause mortality (HR: 6.0; 95% CI: 2.0&#8722;18.4; <i>p</i> = 0.001). The addition of mtDNA<sup>4977</sup> deletion to a clinical reference model was associated with a significant net reclassification improvement (NRI = 0.18, <i>p</i> = 0.01). Short LTL and high mtDNA<sup>4977</sup> deletion showed independent and joint predictive value on adverse cardiovascular outcomes and all-cause mortality in patients with CAD. These findings strongly support the importance of evaluating biomarkers of physiological/biological age, which can predict disease risk and mortality more accurately than chronological age.