# Substrates of selective neuronal vulnerability in aging: neocortical pyramidal neurons and their surrounding neuropil environment in visual versus frontal cortex of young and aged rhesus monkeys

> **NIH NIH R21** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2021 · $321,754

## Abstract

Normal aging in primates often leads to impaired cognitive function, particularly in working memory, which
begins to decline in middle-age. Our group and others have established that age-related cognitive impairment
is not due to overt death of neurons but rather is associated with a constellation of sublethal changes to
neurons particularly in layer (L3), such as spine, synapse and myelin loss and consequent alterations to
synaptic and intrinsic electrophysiological properties. Importantly these structural and functional changes have
been abundantly observed with aging in neurons and white matter pathways in the prefrontal cortex (PFC), a
brain area that is a key player in working memory. By contrast, the properties of primary visual cortex (V1)
pyramidal neurons are largely spared during normal aging. We currently lack a mechanistic understanding of
why pyramidal neurons in these two brain areas are differentially vulnerable in normal aging or how age-
related changes at the single-cell and pathway level in PFC impact network function and thus working memory
performance. The overall hypothesis of this project is that selective vulnerability of neurons and associated
networks in LPFC compared to V1 during aging is due to key differences in both the intrinsic properties and the
neuropil context of neurons in the two areas, and a greater susceptibility of neurons in LPFC to increases in
oxidative stress and inflammation. We propose a novel experimental approach -multiplexed
immunohistochemistry combined with high resolution structural analyses of physiologically characterized
individual neurons- to compare the properties of individual LPFC and V1 pyramidal neurons in the context of
their surrounding neuropil in young and aged rhesus monkeys. These monkeys will also have been assessed
for cognitive status, pathway integrity, and CSF pro-inflammatory cytokine levels as part of other existing NIH-
funded projects. This project has two aims: 1) To assess the morphological properties of physiologically
characterized L3 pyramidal neurons in LPFC and V1 of young and aged monkeys. We will assess dendritic
topology and the number and density of dendritic spine subtypes and correlate these data with existing data on
30 different physiological properties of these same cells. 2) To characterize the normative properties and
effects of aging on the same L3 pyramidal neurons studied in Aim 1 in the context of the neuropil. We will
perform in situ immunofluorescence multiplexing of ~20 protein targets on the same tissue sample to
determine the molecular phenotype of biocytin-filled layer 3 pyramidal neurons. A major outcome of this project
will be the ability to quantitatively specify those parameters that differ between L3 pyramidal neurons in two
highly distinct brain areas and which combination of parameters best predict cognitive impairment in aging.
This study will form the basis of future series of larger studies to investigate relationships and co-dependen...

## Key facts

- **NIH application ID:** 10194943
- **Project number:** 1R21AG072154-01
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** JENNIFER I LUEBKE
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $321,754
- **Award type:** 1
- **Project period:** 2021-05-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10194943

## Citation

> US National Institutes of Health, RePORTER application 10194943, Substrates of selective neuronal vulnerability in aging: neocortical pyramidal neurons and their surrounding neuropil environment in visual versus frontal cortex of young and aged rhesus monkeys (1R21AG072154-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10194943. Licensed CC0.

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