# Proteomic Biomarkers of Intraocular Infection

> **NIH NIH R01** · STANFORD UNIVERSITY · 2020 · $410,002

## Abstract

Project Summary
Intraocular infections due to bacteria, viruses, fungi, and parasites (infectious endophthalmitis) are among the
most common and visually devasting causes of blindness. Endophthalmitis has high morbidity because the
retina is intolerant of immunologic insult. Since initial clinical examination cannot determine the cause of
intraocular inflammation (uveitis), doctors must wait for laboratory culture to identify a microbial agent. But
waiting days to weeks for cultures to grow delays diagnosis and treatment, frequently results in debilitating
visual morbidity and blindness. The proteome of adjacent vitreous can be characterized to uncover biomarkers
for specific etiologies of uveitis. Since different causes of intraocular infection elicit different immune
responses, we hypothesize that proteomic profile of the inflamed vitreous may reflect key molecular changes
and guide diagnosis of intraocular infections. Our group has used large-scale proteomic platforms to analyze
the protein signature in liquid vitreous biopsies from endophthalmitis patients. This approach allowed us to
identify several candidate protein biomarkers that differentiate infectious from non-infectious uveitis and
specific infectious types of endophthalmitis, including bacterial, viral, and fungal endophthalmitis. Our long-term
goal is to find better and more specific molecular treatments for vitreoretinal disease. Our objective in this
proposal is to use targeted proteomic platforms to validate sensitive and specific biomarkers that reliably
differentiate different types of intraocular infection (e.g. bacterial, viral, and fungal). Our central hypothesis is
that vitreous protein signatures can differentiate between non-infectious and infectious uveitis and the class of
infection more-rapidly than conventional clinical testing. Our studies will test the hypothesis through two
specific aims: (1) Validate proteomic biomarkers that differentiate infectious from non-infectious uveitis and (2)
biomarkers that differentiate different classes of intraocular infection (e.g. bacterial, viral, and fungal). Impact.
We expect that successful completion of these aims will validate sensitive and specific endophthalmitis
biomarkers and lay the foundation for the development of clinical diagnostic tests for intraocular infection.

## Key facts

- **NIH application ID:** 10071849
- **Project number:** 1R01EY031952-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** ALEXANDER G BASSUK
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $410,002
- **Award type:** 1
- **Project period:** 2020-09-30 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10071849

## Citation

> US National Institutes of Health, RePORTER application 10071849, Proteomic Biomarkers of Intraocular Infection (1R01EY031952-01). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10071849. Licensed CC0.

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