A Targeted Epigenetic Clock for the Prediction of Biological Age

Abstract

Epigenetic clocks were initially developed to track chronological age, but accumulating evidence indicates that they can also predict biological age. They are usually based on the analysis of DNA methylation by genome-wide methods, but targeted approaches, based on the assessment of a small number of CpG sites, are advisable in several settings. In this study, we developed a targeted epigenetic clock purposely optimized for the measurement of biological age. The clock includes six genomic regions mapping in ELOVL2, NHLRC1, AIM2, EDARADD, SIRT7 and TFAP2E genes, selected from a re-analysis of existing microarray data, whose DNA methylation is measured by EpiTYPER assay. In healthy subjects (n = 278), epigenetic age calculated using the targeted clock was highly correlated with chronological age (Spearman correlation = 0.89). Most importantly, and in agreement with previous results from genome-wide clocks, epigenetic age was significantly higher and lower than expected in models of increased (persons with Down syndrome, n = 62) and decreased (centenarians, n = 106; centenarians’ offspring, n = 143; nutritional intervention in elderly, n = 233) biological age, respectively. These results support the potential of our targeted epigenetic clock as a new marker of biological age and open its evaluation in large cohorts to further promote the assessment of biological age in healthcare practice.

Building Minimized Epigenetic Clock by iPlex MassARRAY Platform

“…For instance, it was shown that Illumina 450K and EPIC BeadChips technologies, in general, have high correlations between results (r > 0.99), but, for many individual CpGs, the values of correlation coefficients were low (r = 0.24), and even negative [51]. Although minimized epigenetic clocks based on MassARRAY (EpiTYPER) technology have been utilized in previous studies [22,23,52], we did not find any information on the development of epigenetic clocks specifically using the iPlex MassARRAY technology. Both technologies are based on mass spectrometry and share similarities in sample preparation processes; however, EpiTYPER technology does not enable the simultaneous assessment of methylation in multiple CpGs across different genes.…”

“…Firstly, the sample size was relatively small, and it did not include individuals from extreme age ranges. To further validate our minimized clocks, it would be beneficial to test them on accelerated and delayed aging models, such as individuals with Down syndrome, centenarians, and their descendants [22]. Secondly, for some CpGs, we obtained significantly different methylation values for the same subjects using iPlex MassARRAY and EPIC BeadChips.…”

“…The biological age estimation model based on the methylation patterns of seven groups of adjacent CpGs using the EpiTYPER method has been proposed [22]. This model showed a high correlation with chronological age (r = 0.89), as well as the rate of aging (accelerated/decelerated).…”

An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review

“…They include pyrosequencing [15,25,[31][32][33], massive parallel sequencing (MPS) [34][35][36][37], SNaPshot assays [38,39], and EpiTYPER [13,28,40,41]. It is important to point out that methylation profiles obtained with these different sequencing/typing methods provide largely comparable results [42].…”

Discovering Biological Mechanisms of Exceptional Human Health Span and Life Span

“…Methylation patterns have been noted to change with aging and may affect the transcribed DNA. Initial studies have shown significant differences in methylation patterns between centenarians and younger controls, with several groups currently pursuing this line of research (Gutman et al 2020b;Daunay et al 2022;Gensous et al 2022). Finally, longevity-associated microRNAs have been identified (Gombar et al 2012), with a number of microRNAs linked to frailty resilience (Inglés et al 2022).…”