Applying blood-derived epigenetic algorithms to saliva: cross-tissue similarity of DNA-methylation indices of aging, physiology, and cognition.

Abstract

Epigenetic algorithms of aging, health, and cognition, based on DNA-methylation (DNAm) patterns, are prominent tools for measuring biological age and have been linked to age-related diseases, cognitive decline, and mortality. While most of these methylation profile scores (MPSs) are developed in blood tissue, there is growing interest in using less invasive tissues like saliva. The aim of the current study is to probe the cross-tissue intraclass correlation coefficients (ICCs) of MPSs developed in blood applied to saliva DNAm from the same people. While our primary focus is on MPSs that were previously found to be robustly correlated with social determinants of health, including second- and third-generation clocks and MPSs of physiology and cognition, we also report ICC values for first-generation clocks to enable comparison across metrics. We pooled three publicly available datasets that had both saliva and blood DNAm from the same individuals (total n = 107, aged 5-74 years), corrected MPSs for cell composition within each tissue, and computed the cross-tissue ICCs.