# From Proteome to miRNome: A Review of Multi-Omics Ocular Allergy Research Using Human Tears

## TL;DR

This review explores how tear-based multi-omics can help understand and manage ocular allergy by identifying key biochemical changes and potential biomarkers.

## Contribution

The paper integrates proteomic, lipidomic, metabolomic, and miRNA findings to propose a stepwise model of ocular allergy biopathways.

## Key findings

- Tear-based multi-omics reveal differential expression patterns in immune response and inflammation pathways in ocular allergy.
- Candidate biomarkers for ocular allergy are identified through integrated analysis of proteomic and miRNA data.
- Comparisons with comorbid conditions like dry eye disease highlight unique and overlapping biochemical signatures.

## Abstract

Ocular allergy (OA) is a subtype of seasonal allergy that causes symptoms of itchiness, redness, swelling and irritation of the ocular surface and eyelids, often triggering allergy-induced eye rubbing and sustained inflammation for up to six months of the year during peak allergy season. These symptoms, coupled with reduced sleep quality, impaired daily productivity and decreased mood, highlight a significant yet underrepresented disease burden. Recent advances in tear-based multi-omics have enabled detailed characterisation of OA-associated biochemical changes on the ocular surface, highlighting human tears as a promising biospecimen for diagnostic biomarker and therapeutic target research. This review discusses emerging proteomic, lipidomic, metabolomic and miRNA findings comparing OA sufferers with healthy controls, and, where relevant, with comorbid conditions such as dry eye disease and keratoconus. Differential expression patterns across these analytes implicate key pathways involved in immune response, wound healing, angiogenesis, inflammation, oxidative stress and return to homeostasis on the ocular surface. By integrating these data into a stepwise model of OA biopathway activation, this review outlines candidate biomarkers and highlights methodological advances that may support translation of tear multi-omics into clinical tools for OA management.