# Identifying genetic and transcriptomic drivers of Parkinson's disease progression

> **NIH NIH U01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2020 · $507,237

## Abstract

Parkinson’s disease (PD) is a progressive, neurodegenerative disorder of aging that 
affects both motor and cognitive function. Despite considerable progress in identifying 
candidate genetic and environmental influences on the development of PD, to date no cures 
exist, the diagnosis remains mainly clinical, and no validated biomarkers are in 
clinical use. Thus, there’s a need to identifying additional genes and contributing 
genetic biomarkers to track progression of the disease. In this application, we will apply 
innovative statistical approaches to the integration of clinical, genomic and transcriptomic 
 data from the Accelerating Medicine Partnership in Parkinson’s disease (AMP PD) to advance 
the identification of novel biomarkers and disease pathways related to the progression of PD. We 
will conduct state-of-the-art analyses that will integrate genomics, clinical, and longitudinal 
transcriptomic data sets to generate patient derived, data-driven, multi-scale models of 
disease. This will enable the generation of hypotheses around gene interactions specific 
to disease states and progression. In aim 1, we will apply probabilistic models to AMP-PD 
transcriptomic data to infer time course trajectories of gene expression that are associated with 
rate of PD progression. In aim 2, we will map common genetic variants that modulate 
inter-individual transcriptomic variation in multiple time points through progression using a novel 
linear mixed model that accounts for repeat measurements, multiple conditions and both latent and 
measured technical confounding. At the completion of these aims we will have access to a 
well-powered set of expression quantitative trait loci at different stages of PD progression, for 
different computationally inferred cell-types, and for progression interaction effects. This 
project will have a large overall impact by: 1) providing mechanistic interpretation of specific PD 
risk and progression GWAS loci; 2) possibly leading to the discovery of novel biomarkers and 
therapeutic targets that modulate the immune system.

## Key facts

- **NIH application ID:** 10130231
- **Project number:** 1U01NS120256-01
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Towfique Raj
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $507,237
- **Award type:** 1
- **Project period:** 2020-09-30 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10130231

## Citation

> US National Institutes of Health, RePORTER application 10130231, Identifying genetic and transcriptomic drivers of Parkinson's disease progression (1U01NS120256-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10130231. Licensed CC0.

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