# Profiling Epigenetic Aging at Cell‐Type Resolution Through Long‐Read Sequencing

## TL;DR

This paper introduces a new method called LongReadAge to study how different cell types age by analyzing DNA methylation patterns using long-read sequencing, without the need to separate cells.

## Contribution

The novel contribution is a probabilistic aging model, LongReadAge, that enables cell-type-specific epigenetic aging profiling from bulk samples using long-read sequencing.

## Key findings

- LongReadAge successfully tracks aging in myeloid cells and lymphocytes from bulk leukocyte data.
- The method performs robustly even with limited shared features across samples.
- Cell-type-specific methylation profiles are generated without the need for cell sorting.

## Abstract

DNA methylation can give rise to robust biomarkers of aging, yet most studies profile it at the bulk tissue level, which masks cell type‐specific alterations that may follow distinct aging trajectories. Long‐read sequencing technology enables methylation profiling of extended DNA fragments, enabling mapping to their cell type of origin. In this study, we introduce a framework for evaluating cell type‐specific aging using long‐read sequencing data, without the need for cell sorting. Leveraging cell type‐specific methylation patterns, we map long‐read fragments to individual cell types and generate cell type‐specific methylation profiles, which are used as input to a newly developed probabilistic aging model, LongReadAge, capable of predicting epigenetic age at the cell type level. We use LongReadAge to track aging of myeloid cells and lymphocytes from bulk leukocyte data as well as circulating cell‐free DNA, demonstrating robust performance in predicting age despite limited shared features across samples. This approach provides a novel method for profiling the dynamics of epigenetic aging at cell type resolution.

Here we introduce LongReadAge, a probabilistic method leveraging long‐read sequencing to profile epigenetic aging at cell‐type resolution from a bulk sample, without cell sorting. Applied to bulk white blood cell data, our method robustly tracks aging trajectories of both myeloid cells and lymphocytes.