# Profiling epigenetic age in single cells and in a high-throughput manner

> **NIH NIH R56** · BRIGHAM AND WOMEN'S HOSPITAL · 2022 · $310,454

## Abstract

Abstract
DNA methylation of a defined set of CpG dinucleotides emerged as a critical and precise biomarker of
the aging process. Multivariate machine learning models, known as epigenetic clocks, can exploit
quantitative changes in the methylome to predict the age of biological samples with high accuracy.
However, existing clocks have only been built on and applied to bulk samples, obscuring the inherent
heterogeneity that exists at the level of single cells. We have recently developed a novel, robust, and
flexible epigenetic clock framework capable of imputation-free profiling of biological age in single cells,
enabling for the first time the investigation of the individual aging trajectories of cells. We validated our
method on some tissues and cell types in mice and observed strong correlations and low error rates. We
seek to further improve and refine our method, as well as to apply it to additional tissues in mice,
specifically in the context of lifespan-extending interventions. We will also extend our single-cell clock
method to human samples, enabling the novel assessment of epigenetic aging of individual human cells.
In addition, we propose to develop epigenetic age profiling via low-cost and high-throughput
methodologies for assessing biological age in standard conditions and in response to certain longevity
treatments. These studies will make critical advances in the aging field, enabling both low-cost and
scalable epigenetic age profiling of samples as well as dissection of the single-cell epigenomic aging
landscape in both mice and humans.

## Key facts

- **NIH application ID:** 10688326
- **Project number:** 1R56AG076607-01
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Vadim N. Gladyshev
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $310,454
- **Award type:** 1
- **Project period:** 2022-09-30 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10688326

## Citation

> US National Institutes of Health, RePORTER application 10688326, Profiling epigenetic age in single cells and in a high-throughput manner (1R56AG076607-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10688326. Licensed CC0.

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