# QUANTITATIVE ASSESSMENT OF BIOLOGICAL AGE AND ITS APPLICATIONS

> **NIH NIH R01** · YALE UNIVERSITY · 2023 · $224,999

## Abstract

ABSTRACT
Quantifying aging is a major goal in Geroscience research as the availability of a reliable marker of aging can
facilitate understanding of the fundamental biology of aging, enable tracking of the aging process in different
tissues and cell systems, and support identification and validation of interventions that extend lifespan and
healthspan. Traditionally, aging has been monitored by following chronological age, mortality, age-related
changes in gene expression, and/or other molecular features, however, there is currently no consensus on the
best practices for quantitatively tracking progression through aging. The recent advent of biomarkers based on
advanced omics approaches, such as DNA methylation, have provided some hope to support development of
precise estimates of age, both in humans and mice. Nevertheless, the majority of such measures are trained as
chronological age predictors, with little to no integration of biological, functional, or phenotypic data. Further, the
modifiability of aging measures based on DNA methylation in response to lifespan and healthspan extending
interventions is almost entirely unknown. We propose to address these challenges by developing a series of
novel DNA methylation clocks by integrating information on phenotypic and functional aging, investigating links
between DNA methylation and aging hallmarks, and evaluating DNA methylation responses to longevity
interventions. We suggest that these clocks will offer a much-needed resource for the Geroscience community.
We will develop these clocks using three general approaches. First, we will use cultured cells (MEFs) to induce
or establish models of three well-known hallmarks of aging—cellular senescence, DNA damage, and
mitochondrial dysregulation. We will then train epigenetic predictors of these hallmarks and validate them in vivo.
We will also establish epigenetic alterations in response to novel and established longevity interventions. In doing
so, we will develop biomarkers of intervention response that can be used to test mimetics, and/or optimize aging
biomarkers. Finally, building on the highly characterized SLAM colony of C57Bl/6 and UM-HET3 animals, we will
produce longitudinal methylation data across the lifespan that can be used to develop an epigenetic clock that
can serve as a robust predictor of healthspan. We hypothesize that these new clocks will better capture biological
age than chronological age trained clocks. Given that they were developed to capture different facets associated
with the aging process, they can be combined to create a single aging measure that is more biologically informed
and characterized compared to existing epigenetic clocks.

## Key facts

- **NIH application ID:** 10833859
- **Project number:** 3R01AG065403-04S1
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Vadim N. Gladyshev
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $224,999
- **Award type:** 3
- **Project period:** 2020-08-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10833859

## Citation

> US National Institutes of Health, RePORTER application 10833859, QUANTITATIVE ASSESSMENT OF BIOLOGICAL AGE AND ITS APPLICATIONS (3R01AG065403-04S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10833859. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*