# Effects of Bupropion versus Escitalopram on Reward Circuitry and Motivational Deficits in Patients with Major Depression and Increased Inflammation and Anhedonia

> **NIH NIH R21** · EMORY UNIVERSITY · 2020 · $195,000

## Abstract

Project Summary
The overall objective of the proposed research is to determine the mechanism of action of an antidepressant of
known efficacy and tie this mechanism of action to a specific biomarker, ultimately supporting precision
medicine in the treatment of major depression (MD). More specifically, the proposed research is designed to
determine whether bupropion (vs escitalopram) increases functional connectivity (FC) within reward-related
neurocircuits and decreases motivational deficits in depressed patients with increased inflammation and
anhedonia. Work by our group and others has demonstrated that administration of inflammatory stimuli to
humans is associated with significant decreases in neural activity in the ventral striatum in association with
symptoms of anhedonia. In studies in laboratory animals and humans, these effects of inflammation appear to
be secondary to decreased dopamine (DA) neurotransmission. Data also indicate that MD patients with higher
inflammation as indexed by C-reactive protein (CRP) exhibit lower FC between the DA-rich ventral striatum
and ventromedial prefrontal cortex in association with motivational deficits and anhedonia that can be reversed
by a DAergic drug (L-DOPA). Further relevant to the proposed research, in a recent clinical trial, depressed
patients with increased inflammation (CRP≥1mg/L) showed a poor response to the selective serotonin
reuptake inhibitor (SSRI) escitalopram alone, while treatment response was markedly increased in
escitalopram-treated patients with the addition of bupropion. Bupropion is a DA reuptake inhibitor that exhibits
~25% occupancy of the DA transporter at therapeutic doses and increases DA neurotransmission in animal
models. Taken together, these data suggest that inflammation affects DAergic pathways to disrupt reward-
related circuits in depressed patients, leading to motivational deficits. Moreover, in the context of inflammation,
drugs that target DA may be more efficacious than SSRIs. Thus, the current study proposes to use a
mechanistic clinical trial design with drugs of known efficacy to take the first step toward establishing whether
antidepressants that target DA (e.g. bupropion) might be a better choice for depressed patients with increased
inflammation and anhedonia than an SSRI. Accordingly, 50 depressed patients with a CRP>2mg/L and
increased anhedonia will be randomized to 6 weeks of bupropion or escitalopram. All depressed patients will
undergo resting state FC at baseline and 6 weeks along with objective and clinical assessments of RDoC
positive (motivational) valence constructs at baseline and 2, 4 and 6 weeks. We hypothesize that patients who
receive bupropion versus escitalopram will exhibit increased FC between ventral striatum and ventromedial
prefrontal cortex in association with decreased motivational deficits and anhedonia. This pilot study will provide
foundational data for design of larger mechanistic clinical trials that will establish the mecha...

## Key facts

- **NIH application ID:** 9986362
- **Project number:** 1R21MH121891-01A1
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Jennifer C Felger
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $195,000
- **Award type:** 1
- **Project period:** 2020-03-13 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9986362

## Citation

> US National Institutes of Health, RePORTER application 9986362, Effects of Bupropion versus Escitalopram on Reward Circuitry and Motivational Deficits in Patients with Major Depression and Increased Inflammation and Anhedonia (1R21MH121891-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9986362. Licensed CC0.

---

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