# 1/3-Recurrence Markers, Cognitive Burden and Neurobiological Homeostasis in Late-life Depression (Rembrandt)

> **NIH NIH R01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2020 · $366,493

## Abstract

PROJECT SUMMARY Approximately half of the individuals affected by Alzheimer's disease (AD) will experience
clinical depression that is difficult to treat. In turn, Late-life depression (LLD) is associated with an increased risk
for cognitive decline and dementia. Despite this overlap, little is known about how pathophysiological processes
in preclinical AD influence and interact with depressive symptoms leading to altered intrinsic network function
and cognitive and neurobehavioral changes. A better understanding of these relationships may aid in identifying
which patients with LLD may be at highest risk of progressing to AD or an AD-related dementia. Moreover, a
better understanding of the underlying neurobiological relationships may inform individualized treatment
development in this comorbid population. This application for an Alzheimer's-focused administrative supplement
will take advantage of an ongoing longitudinal study to examine the relationship between LLD, cognitive decline
and AD. This supplement will add PET imaging using Pittsburgh Compound B (PiB) to the ongoing
neuroimaging, cognitive, and behavioral data obtained through the parent grant. This will allow us to assess Aβ
burden and degeneration of basal forebrain cholinergic system in a cohort of depressed and never-depressed
elders to examine the relationship between and interactive effect of AD-related biomarkers and depressive
symptoms on cognitive performance in LLD. We hypothesize that individuals with higher Aβ burden, more
cholinergic degeneration, and more severe depressive symptoms will exhibit the poorest performance and
greatest trial-to-trial variability on cognitive testing. We further propose that AD biomarker-positive LLD
represents a preclinical phenotype of AD that is characterized by a distinct multivariate neurobehavioral pattern.
This hypothesis is supported by pilot data examining structural imaging markers of accelerated brain aging in
LLD, finding that, with more severe depressive symptoms, greater brain aging is associated with cognitive
impairment. The cognitive/behavioral differences will further be reflected by differences in underlying intrinsic
network function. In the presence of residual depressive symptoms, preclinical AD biomarkers may exacerbate
network connectivity alterations and lead to greater disruptions in network stability when compared to remitted
LLD without AD pathophysiology or biomarker-positive, non-depressed elders. Using data-driven group iterative
multiple model estimation algorithms, we will identify subgroups of LLD individuals who exhibit a unique network
topology and are characterized by impaired cognitive performance and greater AD biomarker levels. This
hypothesis is supported by our previous data on network disruptions in LLD, which may compromise the brain's
capability to reorganize during Aβ accumulation, thus contributing to an accelerated network failure in biomarker-
positive LLD. The results of this study will help elu...

## Key facts

- **NIH application ID:** 10118837
- **Project number:** 3R01MH121620-01S1
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Warren D Taylor
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $366,493
- **Award type:** 3
- **Project period:** 2020-01-15 → 2020-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10118837

## Citation

> US National Institutes of Health, RePORTER application 10118837, 1/3-Recurrence Markers, Cognitive Burden and Neurobiological Homeostasis in Late-life Depression (Rembrandt) (3R01MH121620-01S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10118837. Licensed CC0.

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