# Transcriptional Dysfunction in Dentate Gyrus Cell Types: Roles of Retinoic Acid Responsive Genes in Protection Against Alzheimer's Disease Pathogenesis

> **NIH NIH R01** · TEXAS TECH UNIVERSITY HEALTH SCIS CENTER · 2022 · $374,444

## Abstract

PROJECT SUMMARY / ABSTRACT
Hyperexcitability of the hippocampal dentate gyrus (DG) is associated with impaired learning in early stages of
Alzheimer’s disease (AD). Causal upstream signaling mechanisms occurring within DG circuits early in AD
pathogenesis remain poorly understood. The Mitochondrial Free Radical Theory of Aging proposes that
mitochondria, through the production of excess reactive oxygen species (ROS), cause oxidative damage to
proteins, lipids, and DNA ¾ a process termed oxidative stress (OS). Antioxidants (AOs) normally counteract
this process by scavenging excess ROS, thereby preventing OS. The antioxidant all-trans retinoic acid
(ATRA), the active form of retinol, has a dual role in ROS scavenging and transcriptional control of
synaptic/neuronal proteins via its function as a retinoic acid receptor (RAR) agonist. Recent evidence from
rodents has demonstrated an age-dependent decline in hippocampal ATRA levels due to homeostatic collapse
of the liver-brain axis. We propose that ATRA depletion in the DG is an early event in AD pathogenesis,
leading to excess ROS-induced damage, mitochondrial dysfunction, and reduced occupancy of RARs across
DG cell types, accelerating amyloidosis, network hyperexcitability, and cognitive dysfunction. Bolstering this
scientific premise, secondary analyses of human hippocampal transcriptomic data led us to discover a large
number of OS- and RAR-sensitive genes dysregulated in AD brains. In preliminary studies from the J20 AD
mouse model, chronic treatment with ATRA normalized behavior, prevented the formation of aberrant inhibitory
circuits in the DG, and normalized a number of pathways that included RAR- and OS-sensitive genes in the
DG. Therefore, our central hypothesis is that ATRA depletion induces oxidative stress and loss of
transcriptional control of RAR-sensitive genes in DG cell types, which can be accelerated or delayed
by bidirectionally manipulating DG ATRA levels. Using an innovative multidisciplinary approach that
uniquely combines DG-dependent learning paradigms, single cell transcriptomics, and cellular/synaptic
analysis in two AD mouse models, we will determine how bidirectional manipulation of ATRA levels alters
transcriptional control of RAR-sensitive genes across DG cell types and impacts DG-dependent learning and
cellular/synaptic function. SA1 tests the hypothesis that impaired DG-specific reversal learning is accompanied
by impaired transcription of RAR-sensitive genes in DG cell types, increased OS, and mitochondrial
dysfunction in two AD mouse models. SA2 tests the hypothesis that reversal learning performance, OS levels,
and RAR-sensitive gene expression in DG cell types depend on dietary retinol intake in two AD mouse models.
Finally, SA3 tests the hypothesis that DG circuit function depends on dietary retinol intake in two AD mouse
models. Successful completion of this project will reveal novel mechanisms of DG-related learning impairments
in AD and discover new AD bioma...

## Key facts

- **NIH application ID:** 10367173
- **Project number:** 1R01AG071859-01A1
- **Recipient organization:** TEXAS TECH UNIVERSITY HEALTH SCIS CENTER
- **Principal Investigator:** John Joshua Lawrence
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $374,444
- **Award type:** 1
- **Project period:** 2022-01-01 → 2026-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10367173

## Citation

> US National Institutes of Health, RePORTER application 10367173, Transcriptional Dysfunction in Dentate Gyrus Cell Types: Roles of Retinoic Acid Responsive Genes in Protection Against Alzheimer's Disease Pathogenesis (1R01AG071859-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10367173. Licensed CC0.

---

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