International Journal of Molecular Sciences (Nov 2019)

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

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

DOI
https://doi.org/10.3390/ijms20215508
Journal volume & issue
Vol. 20, no. 21
p. 5508

Abstract

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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 (mtDNA4977), 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 ± 8.3 years) with known or suspected stable CAD. LTL and mtDNA4977 deletion were assessed in peripheral blood using qRT-PCR. During a median follow-up of 5.4 ± 1.2 years, MACEs were 140 while 86 deaths were recorded. After adjustments for confounding risk factors, short LTLs and high mtDNA4977 deletion levels acted independently as predictors of MACEs (HR: 2.2, 95% CI: 1.2−3.9, p = 0.01 and HR: 1.7, 95% CI: 1.1−2.9, p = 0.04; respectively) and all-cause mortality events (HR: 2.1, 95% CI: 1.1−4.6, p = 0.04 and HR: 2.3, 95% CI: 1.1−4.9, p = 0.02; respectively). Patients with both short LTLs and high mtDNA4977 deletion levels had an increased risk for MACEs (HR: 4.3; 95% CI: 1.9−9.6; p = 0.0006) and all-cause mortality (HR: 6.0; 95% CI: 2.0−18.4; p = 0.001). The addition of mtDNA4977 deletion to a clinical reference model was associated with a significant net reclassification improvement (NRI = 0.18, p = 0.01). Short LTL and high mtDNA4977 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.

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