# Digital Spatial Profiling of Hippocampal Subregions in Alzheimer’s Disease, Primary Age-Related Tauopathy, and Chronic Traumatic Encephalopathy

> **NIH NIH R21** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2022 · $464,750

## Abstract

Project Summary/Abstract
Alzheimer disease (AD), primary age-related tauopathy (PART), and chronic traumatic encephalopathy (CTE)
all represent tauopathies defined by intra-neuronal neurofibrillary tangle (NFT) formation principally composed
of 3R/4R-positive phosphorylated-tau (p-tau). There are numerous histopathological differences between these
disorders, however. While the neuropathologic diagnosis of AD requires the presence of β-amyloid plaque
deposition in addition to the presence of NFTs, PART and CTE represent β-amyloid-independent tauopathies.
This is a key difference as the presence of β-amyloid plaques is thought to be crucial in the pathogenicity of AD,
and our previous studies have demonstrated that subjects with clinically determined dementia and
neuropathologically-confirmed AD pathology have increased levels of proteins associated with amyloid
processing and inflammation associated with their NFTs compared to cognitively normal subjects with similar
levels of pathology, suggesting that β-amyloid may play a key role in the cognitive status. Furthermore, there is
a different distribution of NFTs among these three disorders. In the hippocampus, the most severe p-tau
pathology in AD is often in the entorhinal cortex and CA1 hippocampal subregion (where it is also in closest
proximity to β-amyloid), while in PART the most severe neurofibrillary degeneration initially occurs in the CA2
subregion, and in CTE the CA2 and CA4 hippocampal subregions are most affected. In AD, the p-tau NFT
pathology proceeds according to established Braak stages from entorhinal to neocortex, while in PART the NFT
pathology is primarily restricted to the temporal allocortex, and in CTE the p-tau pathology begins in the
neocortex at the depths of sulci in a perivascular distribution before affecting the hippocampus itself. Here, we
propose to examine the NFTs and their immediate microenvironments in different subregions of the hippocampi
of patients with histopathologically-confirmed AD, PART, and CTE using Nanostring GeoMx™ Digital Spatial
Profiling (DSP). We predict that the NFTs found in AD will differ from the those in PART and CTE primarily in
proteins related to β-amyloid processing and that these changes will be reflected in differences in cognitive
status, especially in the AD to PART comparison. In addition, we predict that the protein composition of NFTs in
the CA2 subregion of CTE will be more similar to the NFTs in the CA2 subregion of PART than they are to those
in the CA4 subregion of CTE, reflecting the hypothesis that β-amyloid-independent neurofibrillary degeneration
of the CA2 subregion is more representative of background aging in PART. The NFT microenvironment will also
likely show more severe synaptic loss in AD compared to PART. Finally, we will use this spatial proteomic method
to assess the impact of comorbid neurodegenerative conditions (concurrent Lewy body dementia (LBD) and
limbic-
predominant age-related TDP-43 encephalopathy (LA...

## Key facts

- **NIH application ID:** 10506705
- **Project number:** 1R21AG078505-01
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Timothy Eric Richardson
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $464,750
- **Award type:** 1
- **Project period:** 2022-08-15 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10506705

## Citation

> US National Institutes of Health, RePORTER application 10506705, Digital Spatial Profiling of Hippocampal Subregions in Alzheimer’s Disease, Primary Age-Related Tauopathy, and Chronic Traumatic Encephalopathy (1R21AG078505-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10506705. Licensed CC0.

---

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