Improving Corneal Ulcer Outcomes with Unbiased Pathogen and Antimicrobial Resistance Detection

NIH RePORTER · NIH · R01 · $403,750 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY/ABSTRACT Infectious corneal ulcers affect all ages and contribute to significant visual morbidity worldwide. Empiric treatment with broad spectrum antimicrobials without regard for antimicrobial resistance is presently standard of care. This is either because pathogen identification with routine microbiological testing is suboptimal or testing is not done altogether. While empiric treatment is the preferred practice pattern for infectious keratitis worldwide, this is contrary to the goals and ideals of antimicrobial stewardship. Here, we propose to enhance the understanding of the pathogenesis of infectious keratitis and antibiotic resistance profiles to improve diagnostics and therapeutics with the following aims. In the first aim, we will perform worldwide surveillance of all organisms responsible for infectious keratitis. We expect the spectrum of etiology will vary significantly with geographic location. In addition, seasonality will affect pathogen profile and disease outcomes. The second aim will determine the frequency and richness of antimicrobial resistance (AMR) in corneal ulcer pathogens and correlate those findings with phenotypes. We expect AMR will differ by global location and predict clinical outcome. Finally, we will define the local immune response in infectious keratitis. We hypothesize that immune signatures can predict pathogen types and clinical outcome. Corneal opacity secondary to infectious keratitis remains one of the leading causes of blindness worldwide and we anticipate this research will guide clinicians on the best management for corneal infection to reduce both the financial and ocular health burden globally.

Key facts

NIH application ID
10440971
Project number
1R01EY032861-01A1
Recipient
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
Principal Investigator
Thuy A Doan
Activity code
R01
Funding institute
NIH
Fiscal year
2022
Award amount
$403,750
Award type
1
Project period
2022-05-01 → 2026-04-30