Abstract

Population aging is a looming global health challenge. New biological aging metrics based on DNA methylation levels have been developed in addition to traditional aging biomarkers. The prospective relationships of aging biomarkers with mitochondrial changes are still not well understood. Here, we examined the prospective associations of mitochondrial copy number (mtDNAcn) with several aging biomarkers – DNAm-Age, DNAm-PhenoAge, DNAm-GrimAge, and leukocyte telomere length. We analyzed 812 individuals from Veteran Affairs Normative Aging Study (NAS) with available blood samples from 1999-2013. Whole blood mtDNAcn and relative leukocyte telomere length were measured via qPCR. DNA methylation was assessed and used to calculate DNAm-Age, DNAm-GrimAge, and DNAm-PhenoAge. Linear mixed models were used to quantify the associations of mtDNAcn with DNAm-Age, DNAm-GrimAge, DNAm-PhenoAge, and leukocyte telomere length. In multivariable cross-sectional analyses, mtDNAcn is negatively associated with DNAm-Age PhenoAge and DNAm-PhenoAge. In contrast, mtDNAcn is associated with prospective measures of higher DNAm-PhenoAge and shorter leukocyte telomere length. Our study shows that higher mtDNAcn is associated with prospective measures of greater DNAm-PhenoAge and shorter leukocyte telomere length independent of chronological age. This indicates a role for mitochondrial in aging-related disease and mortality, but not the departure of biological age from chronological age.

Highlights

  • In 2015, 8.3% of the global population was older than 65 years of age, but as the world population ages, this number is estimated to grow to 15.8% by 2050 [1]

  • To investigate possible presence of reversal causality, we examined whether baseline DNA methylation (DNAm)-Age and baseline DNAm-PhenoAge were associated with prospective measures of Mitochondrial DNA copy number (mtDNAcn)

  • Our results suggest the mitochondria plays an active role in biological aging, with higher mtDNAcn leading to higher DNAmPhenoAge and shorter telomere length independent of any underlying process that may cause both

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Summary

Introduction

In 2015, 8.3% of the global population was older than 65 years of age, but as the world population ages, this number is estimated to grow to 15.8% by 2050 [1]. A metaanalysis of 13 population-based cohorts including a total 13,089 individuals found that blood DNAm-Age was predictive of mortality, even when accounting for chronological age, concurrent diseases, and lifestyle risk factors [12], suggesting that DNAm-Age captures at least in part some additional aspect of biological aging. Another DNAm based marker, DNAm-PhenoAge, was developed to be an improved predictor of mortality and health span [13] using phenotypic age estimated from a range of aging-related clinical measures. Another metric, DNAm-GrimAge [14], has been developed to predict all cause mortality and health span

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