# Multi-tissue high-throughput proteomic and genomic study in Parkinson's Disease

> **NIH NIH R01** · BETH ISRAEL DEACONESS MEDICAL CENTER · 2021 · $653,158

## Abstract

Project Summary/Abstract
Parkinson's disease (PD) is the most common neurodegenerative movement disorder, affecting more than 6
million people worldwide, with the prevalence projected to double in the next few decades. PD is a
heterogeneous disorder with identifiable clinical-pathological subtypes based on symptom severity and
predominance. An accurate molecular profile could reduce clinical heterogeneity among PD patients. Few
studies have applied a proteogenomic approach to samples from PD and PD dementia (PDD) patients to identify
proteins associated with clinical, neuroimaging, or neuropathological subtypes. This proposal aims to create a
framework for uncovering proteins, genes, pathways, and potential biomarkers that will improve our
understanding of underlying disease mechanisms, predict disease course, and design clinical trials. We propose
leveraging a unique resource that includes quantitative proteomic analysis of ~5,000 proteins from cerebrospinal
fluid (CSF) and plasma of clinically diagnosed PD patients coupled with brain samples from autopsy-confirmed
cases. This large-scale screening of ~3,110 samples could identify differentially expressed protein levels of
known molecular pathways involved in PD or with a clear genetic connection to PD risk. To achieve these goals,
we plan to carry out a three-stage study design: discovery, replication, and meta-analyses using SOMAscan of
plasma (n=1,244), CSF (n=1,215), and brain tissue (n=659) from healthy individuals, PD, and Alzheimer's
disease patients (Aim 1). For replication studies, we have accessed and processed data from studies in plasma
(n=8,873), brain (n=144), and CSF (n=232). We plan to use disease status, age-at-onset, and clinical scales of
motor impairment to find a proteomic profile that could be used to create a biomarker-driven clinical-molecular
phenotype in PD patients (Aim 1A). We also plan to find associations of proteomic profiles with cognitive test
scores, CSF biomarkers, and neuroimaging (Pittsburgh compound B) to uncover proteins associated with
amyloid pathology in living PD dementia patients (Aim 1B). We will integrate neuropathology and proteomic data
to identify a divergent molecular signature or share similar aberrant pathways in PD, PDD, and Alzheimer's
disease. (Aim 1C). Finally, we will integrate proteomic and GWAS data to identify pQTLs and apply polygenic
risk scores and Mendelian Randomization approaches to determine proteins involved in the causal pathway of
PD, which are potential novel PD biomarkers (Aim 2). Using this approach, we will be able to select reliable PD
biomarker candidates for validation. We expect to uncover a genome-proteome network that will provide a basis
for novel approaches to diagnostic and pharmacotherapeutic applications in PD.

## Key facts

- **NIH application ID:** 10600288
- **Project number:** 7R01NS118146-03
- **Recipient organization:** BETH ISRAEL DEACONESS MEDICAL CENTER
- **Principal Investigator:** Bruno A. Benitez
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $653,158
- **Award type:** 7
- **Project period:** 2020-09-30 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10600288

## Citation

> US National Institutes of Health, RePORTER application 10600288, Multi-tissue high-throughput proteomic and genomic study in Parkinson's Disease (7R01NS118146-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10600288. Licensed CC0.

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