# Multiomic methods for the characterization of cellular aging

> **NIH NIH R56** · UNIVERSITY OF PENNSYLVANIA · 2024 · $400,000

## Abstract

PROJECT SUMMARY
Age-related diseases are together the leading causes of death in the United States, and drugs targeting basic
mechanisms of aging have recently entered clinical trials. Single cell sequencing has enabled unprecedented
resolution in the study of cell types implicated during aging, contributing to our study of age-related
diseases. Yet, critical deficiencies remain in our experimental and computational toolbox, limiting our ability to
study cellular aging in two fundamental ways: (1) A hallmark of cellular aging is stochastic epigenetic drift,
where cells gradually accumulate errors in their cytosine methylation and histone modification profiles, leading
to cell-type specific aging phenotypes, such as loss of plasticity in stem cell populations. It is unclear how
errors accumulated at the chromatin level propagate to RNA transcription and splicing and how these errors
impact observed aging-related phenomenon, such as cellular senescence. This gap in knowledge is due, in
part, to the lack of formal definitions and actionable models for measuring epigenetic and transcriptomic
dysregulation. (2) The accumulation of senescent cells, i.e. cells that have entered irreversible cell cycle
arrest, in our tissues as we age has been widely appreciated as a driver of aging. Yet, there are few studies of
the relationship between epigenetic and transcriptomic noise and cellular senescence, partly because of the
aforementioned lack of analysis tools, and partly because senescent cells, which are usually present at small
proportions even in aging tissue, are difficult to isolate and characterize. In this project, we will develop
methods to estimate intrinsic noise, as it was classically defined by Elowitz, Levine, Siggia, and Swain (2022),
from single cell sequencing data. Across tissues and cell types, our preliminary studies show that intrinsic
noise measures the accumulation of error at the per-cell and per-gene level. We will develop computational
methods for the measurement of intrinsic biological noise at the levels of chromatin accessibility, gene
expression, and transcript splicing. Synergistically, we will perform experiments on which the new methods will
be applied to investigate the relationship between intrinsic cellular noise and cellular senescence, and address
essential questions in cellular aging, senescence, and anti-aging drug therapy. Our central hypothesis is that
epigenetic, transcriptional, and splicing noise provides both a quantitative profile of cellular aging and a critical
new perspective for understanding gene (dys)regulation, senescence, and tissue aging in a cell type specific
manner. Preliminary results support this hypothesis and suggest that our methods will be of interest to the
broader research community with the potential for wide adoption.

## Key facts

- **NIH application ID:** 11170824
- **Project number:** 1R56AG081351-01A1
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** F. Brad Johnson
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $400,000
- **Award type:** 1
- **Project period:** 2024-09-15 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11170824

## Citation

> US National Institutes of Health, RePORTER application 11170824, Multiomic methods for the characterization of cellular aging (1R56AG081351-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11170824. Licensed CC0.

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