# Predictive model of spread of Parkinson's pathology using network diffusion

> **NIH NIH R01** · WEILL MEDICAL COLL OF CORNELL UNIV · 2020 · $587,727

## Abstract

PROJECT SUMMARY / ABSTRACT
Project Summary
Parkinson’s disease (PD) is a debilitating neurodegenerative disease characterized by progressive
bradykinesia, rigidity, tremor and postural instability. The etiology, mechanism and progression of pathology
and its relationship to clinical manifestations is not fully understood. These factors, coupled with its insidious
onset, clinical heterogeneity, overlap with dementias, and the variability in speed and pattern of symptom
progression, make a rigorous characterization and prognosis of PD difficult. Recent bench research on the
trans-neuronal “prion-like” transmission of misfolded proteins is at last filling the gaps in the pathological
context of PD, whereby misfolded alpha-synuclein protein can trigger misfolding in adjacent cells. If this spread
mechanisms could be quantitatively modeled, it could enable accurate prediction of PD progression.
This is the aim of our proposal. We will turn hitherto qualitative neuropathological insights into a rigorous
“network-diffusion” model of disease spread. The model will be fed baseline in vivo MRI of PD patients, and will
produce a deterministic and testable prediction for PD progression and conversion to dementia. By explicitly
incorporating the brain’s connectivity network, our model will quantify the role of the brain’s anatomic
connectivity network in disease transmission. We are targeting various applications, including diagnostic
imaging biomarker, prognostic tool for assessing likely future patterns of disease and future neurocognitive
status including likelihood of conversion to dementia.
Relevance
Parkinson’s Disease is a debilitating and common age-related degenerative disorder. The proposed network
model will yield a validated deterministic and predictive model for PD progression, with applications in
prediction of a patient’s future atrophy patterns, neurocognitive and motor scores.

## Key facts

- **NIH application ID:** 9913596
- **Project number:** 5R01NS092802-05
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Ajay Gupta
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $587,727
- **Award type:** 5
- **Project period:** 2016-07-15 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9913596

## Citation

> US National Institutes of Health, RePORTER application 9913596, Predictive model of spread of Parkinson's pathology using network diffusion (5R01NS092802-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9913596. Licensed CC0.

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