Functional genetic analysis of epigenetic age acceleration and the regulatory landscape of the methylome

DNA甲基化（DNAm）在个体之间表现出显著的差异，并随着年龄的增长而改变。DNAm -

DNA methylation (DNAm) shows significant variation between individuals and is altered by aging. The DNAm- based estimate of biological age (DNAmAge; aka, “epigenetic clock”) is a robust and widely used biomarker of aging, but its underlying mechanisms remain mostly unknown. The rate at which the epigenetic clock ticks, commonly referred to as epigenetic age acceleration (EAA or DNAmAge-acc), is a measure of the rate of biological aging and is predictive of health and life expectancy, and modifiable by diet. We have found that EAA varies significantly between mouse strains belonging to the BXD family, and is a highly heritable trait that is linked to strong QTLs. Strikingly, the QTLs we have uncovered for EAA in the BXDs, overlap loci and candidate genes that are also associated with EAA in humans. These include genes such as Stxbp4, Nkx2–3, and Cutc. In Aim 1a, we will perform CRISPR/Cas9 based gene deletion of few of these candidate genes in mouse fibroblast cells. We will use cells derived from the two parent strains of the BXDs (C57BL/6J, and DBA/2J). If gene deletion or knockdown is found to have an impact on the epigenetic clock, we will follow-up with deep sequencing of the transcriptome (Aim 1b) to gain deeper insights into the associated gene expression changes and potential mechanisms. In Aim 2, we will apply integrative systems genetics to define the genetic variants that contribute to variability in the larger methylome by performing methylation QTL (meQTL) analyses. This will be carried out in a larger panel of the BXD recombinant inbred and advanced intercross strains that will give us sufficient power for QTL detection. Aim 2 will leverage an existing resource of biobanked liver specimens. From preliminary work, we have found that some of the highly variable CpG regions in the liver are significantly correlated with body weight, and with strain differences in life expectancy. We will chart the networks of cis- and trans-acting genetic variants that configure the methylome in a highly metabolic tissue (i.e., liver), and examine whether these cis and trans-meQTLs also relate to complex traits such as body weight, and natural variation in lifespan. Furthermore, these liver samples already have multi- omics datasets (transcriptomics, proteomics, and metabolomics), and this will add an epigenomic layer that will facilitate multi-scalar integrative analyses. Together, the two aims will shed light on the genes that regulate the epigenetic clock, and the genetic variants that contribute to shaping the larger methylome. Additionally, we will be able to study how these epigenetic traits associate with, and possibly mediate, downstream molecular traits such as gene expression, and higher order traits such as body weight, metabolism, and longevity.