Language

English

Publication Date

6-1-2026

Journal

Investigative Ophthalmology & Visual Science

DOI

10.1167/iovs.67.6.25

PMID

42294806

PMCID

PMC13277791

PubMedCentral® Posted Date

6-15-2026

PubMedCentral® Full Text Version

Post-print

Abstract

Corneal innervation research has faced long-standing clinical challenges that only recent technological breakthroughs now make tractable. Advances in single-cell analysis, viral vectors, clinical imaging, and artificial intelligence provide integrated approaches for uncovering molecular mechanisms underlying functional outcomes and facilitating clinical applications. The National Eye Institute's U01-funded consortium on ocular surface innervation addresses major knowledge gaps in characterizing corneal-projecting neurons, understanding neuroimmune and epithelial interactions in the cornea, and translating animal model findings to human pathology. The unique properties of the cornea (transparent, avascular, and densely innervated) make it ideal for neurobiology research on peripheral and central sensory processing. Through a multi-institutional collaboration, the consortium roadmap systematically integrates four complementary pillars: retrograde labeling, omics technologies, animal models, and research models and human clinical imaging. The roadmap progresses through three phases: standardizing methodological foundations, achieving technological convergence through multimodal synthesis, and advancing clinical translation via cross-species harmonization, therapeutic target identification, and patient characterization strategies. This coordinated approach transforms isolated findings into mechanistic frameworks, demonstrating how technological convergence combined with collaborative science accelerates discovery and establishes foundations for understanding ocular surface circuitry in physiological and pathophysiological contexts, including pain.

Keywords

Humans, Cornea, Animals, Biomedical Research, Ophthalmic Nerve, corneal trigeminal innervation, OMICS, IVCM, retrograde labeling, animal models

Published Open-Access

yes

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