# Molecular determinants of pathogenicity in viral conjunctivitis

> **NIH NIH R21** · UNIVERSITY OF WASHINGTON · 2021 · $220,625

## Abstract

ABSTRACT
 Adenoviral keratoconjunctivitis is one of the most common conditions in all of medicine. Despite being a
common cause of morbidity world-wide, there are no known host or pathogen factors that predict clinical
outcomes in this condition. A recent, large, international clinical study of adenovirus-related conjunctivitis
revealed that approximately 10% of patients suffer from long term visual loss. A limited deep DNA sequencing
study of AdV D8 clinical samples conducted under our previous R21 (1R21EY027453) revealed unexpected
sequence diversity in the viral genome, with approximately 600 sequence variants among 87 samples within
the same hexon-defined molecular type. These variants assorted into three subtypes with different propensity
to poor outcome. Remarkably, using machine learning approaches, we found we were able to predict one
critical outcome – the development of subepithelial infiltrates – from knowledge of the viral sequence alone.
 Our previous study sequenced samples from the placebo arm of the NVC-422 clinical trial. We have an
additional 157 AdV D8 samples that have not been sequenced. In Aim 1 we propose sequencing the
adenovirus of these samples in order to a.) further characterize the sequence diversity of AdV D8 and b.)
validate our machine learning method for predicting development of subeptithelial infiltrates While AdV D8 was
the most prevalent cause of AKC in our study worldwide, unexpectedly we found in the United States that AdV
E4 was the most prevalent type. In Aim 2, we propose fully sequencing all 36 samples in the study from type
E4, as well as 23 samples from type B3, 9 samples from D19, and a total of 35 samples distributed between
type D53, D56, and D64 to determine their molecular diversity, and to apply the same machine learning
methods to this set of samples to determine if outcomes can be predicted from viral sequence variants for
these types as for AdVD8. The results of these studies will expand our understanding of the molecular
pathogenesis of viral conjunctivitis, and will provide biomarkers for predicting outcomes from this condition.
These advances will facilitate future efforts toward developing therapies for this common condition.

## Key facts

- **NIH application ID:** 10313229
- **Project number:** 1R21EY033174-01
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Russell N. Van Gelder
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $220,625
- **Award type:** 1
- **Project period:** 2021-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10313229

## Citation

> US National Institutes of Health, RePORTER application 10313229, Molecular determinants of pathogenicity in viral conjunctivitis (1R21EY033174-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10313229. Licensed CC0.

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