# ENIGMA Parkinson’s Initiative: A Global Initiative for Parkinson’s Disease

> **NIH NIH R01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2021 · $675,998

## Abstract

ABSTRACT
Parkinson’s disease (PD) is a devastating, progressive neurodegenerative brain disease, with no known cure.
The disease afflicts 10 million people worldwide - ~1.5 million in the U.S. alone, and ~50k-60k new cases are
diagnosed annually. Risk factors or interventions are extremely hard to evaluate as we lack objective metrics of
how PD affects the brain. The vast global availability of brain imaging has led to several promising metrics to
gauge PD progression in the brain - structural changes in the basal ganglia and motor cortex, abnormalities in
neural connectivity seen with diffusion MRI (dMRI), and disruptions of the brain’s functional synchrony across
regions, seen with resting state functional MRI (fMRI). Despite these findings, factors that affect disease severity
are difficult to discover, as most imaging studies of PD scan <100 patients. Most PD research is conducted in
isolated cohorts from the US and Europe, limiting worldwide generalizability. Factors that affect PD progression
are hard to verify, leading to a crisis of reproducibility. Responding to NIH’s call for more reproducible studies,
here we launch ENIGMA’s Worldwide Parkinson’s Initiative. ENIGMA recently published the largest
neuroimaging studies of schizophrenia, bipolar disorder, major depression, epilepsy, and autism spectrum
disorder. With ENIGMA’s globally coordinated, highly powered consortium approach, we plan to overcome the
crisis of small studies with poor power and reproducibility. Pooling anatomic, diffusion and resting state functional
MRI metrics from 21 deeply assessed international cohorts - from the US, Brazil, Taiwan, New Zealand, the
Netherlands, Italy, Switzerland, South Africa, China, and Russia - we ask: How does the illness affect the brain's
structure, neural connectivity, and functional synchrony? What imaging biomarkers track disease progression
and consistently predict clinical outcomes? Do genetic risk loci for PD help predict brain decline? What PD
subtypes, or clusters, can imaging identify? Combining multimodal data from 2,307 patients and 1,264 controls,
we will thoroughly evaluate predictors and brain biomarkers in PD. Our aims are to: (1) Evaluate and rank
structural, diffusion, and resting state functional MRI biomarkers of PD worldwide; (2) Evaluate the added
value of polygenic risk scores (PRS) in predicting PD brain biomarkers; (3) Predict future functional
decline in PD with machine learning, multi-modal imaging and genomics. We will use genetic data and
baseline clinical variables from PD patients and healthy controls across our cohorts to construct an ensemble of
models to predict the annual rate of change in combined scores from the Movement Disorder Society—Unified
Parkinson's Disease Rating Scale parts II and III. We will rank the best predictors of decline, and assess how
robust they are internationally. By better modeling variance in patient outcomes, our multimodal predictive model
will empower PD clinical trials by ran...

## Key facts

- **NIH application ID:** 10209632
- **Project number:** 1R01NS107513-01A1
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Kathleen Lombard Poston
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $675,998
- **Award type:** 1
- **Project period:** 2021-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10209632

## Citation

> US National Institutes of Health, RePORTER application 10209632, ENIGMA Parkinson’s Initiative: A Global Initiative for Parkinson’s Disease (1R01NS107513-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10209632. Licensed CC0.

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