# Development of a novel tear-based biomarker assay for diagnosis of Parkinson's disease using RT-QuIC

> **NIH NIH R21** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2021 · $247,500

## Abstract

One percent of individuals over the age of 60 suffers from Parkinson's disease (PD), with this number increasing
to five percent by age 80. A diagnosis of PD is typically made after manifestation of defining motor symptoms
including resting tremor, rigidity and bradykinesia; however by the time that patients present with clinically-
established PD, they may have lost from 30-70% of dopaminergic neurons in the striatum. As such, there is
great interest in the availability of definitive biomarkers enabling earlier diagnosis prior to the development of the
debilitating motor symptoms signaling irreversible neurodegeneration. Biofluids explored as sources have
traditionally included serum, saliva and cerebrospinal fluid (CSF). Tears represent an optimal new biofluid for
PD biomarkers since they are acquired non-invasively (unlike CSF), are more concentrated than saliva, and are
produced by the lacrimal gland which is highly responsive to neural pathways affected by PD. In fact, PD can
manifest with initial changes in proteins in the tissues of the eye in parallel with changes in primary neurites that
often occur prior to the development of clinical signs. We have found, in PD patient cohorts, that the oligomeric
α-synuclein composition of tears is increased compared to tears from healthy controls. Due to limitations in the
sensitivity of conventional ELISA used for these measurements, PD patients (8-18%) have tear oligomeric α-
synuclein values below the threshold of the assay's sensitivity. ELISA also lacks the ability to measure the actual
capacity of oligomeric α-synuclein to promote protein aggregation, a feature linked to disease pathology. Here
we apply and optimize a real-time quaking-induced conversion (RT-QuIC) assay to detect pathological
oligomeric α-synuclein in tears. We propose two Aims. Aim 1: To develop an RT-QuIC assay capable of
detection of α-synuclein aggregates in human tears. We will utilize recombinant wild type α-synuclein to
optimize the detection of oligomeric α-synuclein utilizing RT-QuIC, determine whether bulk tears or isolated tear
exosomes provide a more effective seed, and optimize the collection matrix. We will also decrease the lag phase
of α-synuclein aggregation without compromising reaction specificity by utilizing aggregation-prone α-synuclein
mutants, enhancing the feasibility of adoption of this assay to a clinical diagnostic. Aim 2: To test the ability
of RT-QuIC to distinguish pathological α-synuclein aggregates in tears of diagnosed PD patients versus
healthy controls and neurological disease controls. Using optimized conditions, we will compare RT-QuIC
to ELISA in the ability to detect oligomeric α-synuclein in tears of diagnosed PD patients versus age- and sex-
matched healthy and neurological disease controls, determining its sensitivity and specificity in discriminating
those with PD. Our goal at study conclusion is to secure data sufficient to advance this assay to a clinical
study to test its ability t...

## Key facts

- **NIH application ID:** 10227242
- **Project number:** 5R21AG066070-02
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Sarah F Hamm-Alvarez
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $247,500
- **Award type:** 5
- **Project period:** 2020-08-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10227242

## Citation

> US National Institutes of Health, RePORTER application 10227242, Development of a novel tear-based biomarker assay for diagnosis of Parkinson's disease using RT-QuIC (5R21AG066070-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10227242. Licensed CC0.

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