# Multimodal imaging of depression in Parkinson's disease

> **NIH NIH R21** · YALE UNIVERSITY · 2021 · $460,625

## Abstract

Abstract
Treating depression in Parkinson’s disease (PD) effectively is a critically important unmet need. Depression
affects almost half of those suffering from PD and significantly adds to the burden of the disease. Yet traditional
antidepressants are inadequate in PD and identifying PD-specific treatment targets is vital. A loss of synapses
is central to the pathology of PD, secondary to a toxic build-up of alpha-synuclein. Converging evidence suggests
that synaptic loss contributes to depression also. Whether synaptic deficits play a distinct role in depression in
PD, however, is unknown. Synaptic deficits and network abnormalities distinct to depression in PD could
represent important new treatment targets. Using positron emission tomography (PET) we are now able to
quantify synaptic density in-vivo. Our recently published work shows that a) there is almost 50% lower synaptic
density in the substantia nigra in PD compared to healthy control (HC) subjects and that b) lower synaptic density
is associated with higher severity depression, as well as network dysfunction, in individuals with major depressive
disorder (MDD) and posttraumatic stress disorder (PTSD). We propose to quantify synaptic density (using PET)
and network organization (using functional MRI) in PD depression for the first time. We will elucidate synaptic
deficits and network abnormalities that are unique to depression in PD by imaging four groups of subjects: PD
with depression, PD no depression, MDD no PD and HCs. We will use PET to determine whether synaptic
deficits are distinct in PD depression by comparing synaptic density across PD, MDD and HC groups (aim 1).
We hypothesize that synaptic loss will extend beyond the substantia nigra to prefrontal cortical and limbic regions
related to mood regulation. We will also use fMRI to quantify the functional networks associated with depression
in PD compared to other groups (aim 2). We hypothesize connectivity disturbances within and between
substantia nigra and PFC/limbic networks, and that this will generalize to an independent, publicly available
dataset. We will then integrate these aims and combine PET and fMRI data to determine whether depression-
associated brain networks are underpinned by distinct patterns of synaptic loss in PD (aim 3). We hypothesize
that synaptic deficits in substantia nigra, PFC and limbic regions will be associated with widespread connectivity
disturbances in PD depression. Findings could implicate a pattern of synaptic deficit/network dysfunction distinct
to depression in PD that could be targetable with synaptic-enhancing and network-reorganizing interventions
such as ketamine and neurofeedback, and therefore have a direct translational impact on the effective alleviation
of depression in PD.

## Key facts

- **NIH application ID:** 10303408
- **Project number:** 1R21NS120116-01A1
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Sophie Holmes
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $460,625
- **Award type:** 1
- **Project period:** 2021-08-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10303408

## Citation

> US National Institutes of Health, RePORTER application 10303408, Multimodal imaging of depression in Parkinson's disease (1R21NS120116-01A1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10303408. Licensed CC0.

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