# Parkinson Disease Clinical Subtypes: Validation, Clinical Utility, and Biological Correlates

> **NIH NIH R01** · WASHINGTON UNIVERSITY · 2021 · $466,371

## Abstract

ABSTRACT
Parkinson disease (PD) is a progressive neurodegenerative disease characterized by motor, cognitive, and
psychiatric manifestations resulting from abnormal protein deposition and neurotransmitter deficits. The
variability in clinical presentation and progression likely reflects the underlying variability in brain pathology.
Although current treatments provide dramatic motor benefit in PD, they fail to alleviate some aspects of gait
impairment and non-motor symptoms and may exacerbate cognitive and psychiatric features. To develop more
“personalized medicine” interventions to treat, forestall or prevent these features, classification of PD clinical
subtypes and identification of the associated biological mechanisms are necessary for patient stratification,
predicting progression, development and evaluation of novel treatments. Therefore, we propose to identify and
validate PD clinical subtypes based on comprehensive motor, cognitive, and psychiatric evaluations; determine
the predictive utility of PD clinical subtypes through longitudinal behavioral assessments; and examine
biological markers of the PD clinical subtypes from multimodal neuroimaging, CSF, and autopsy data.

## Key facts

- **NIH application ID:** 10126918
- **Project number:** 5R01NS097437-05
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** MEGHAN C CAMPBELL
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $466,371
- **Award type:** 5
- **Project period:** 2017-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10126918

## Citation

> US National Institutes of Health, RePORTER application 10126918, Parkinson Disease Clinical Subtypes: Validation, Clinical Utility, and Biological Correlates (5R01NS097437-05). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10126918. Licensed CC0.

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