ArticleScientific reports2025
High throughput tear proteomics with data independent acquisition enables biomarker discovery in allergic conditions.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A comprehensive review of tear fluid proteome alterations in dry eye disease: Insights into pathophysiology and biomarker potential.The ocular surface · 2026Review
- A Pilot Proteomic Analysis of Tear Fluid in Domestic Cats with and Without Conjunctivitis Using MALDI-TOF/TOF Mass Spectrometry.Animals : an open access journal from MDPI · 2026Article
- From Proteome to miRNome: A Review of Multi-Omics Ocular Allergy Research Using Human Tears.International journal of molecular sciences · 2026Review
- Exploratory proteomic characterization ofFrontiers in pharmacology · 2026Article
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Authors and funding
11 authors.
Funding
Abstract
The search for pathological biomarkers in biological fluids that can provide valuable insight into an individual's health status, is a relevant area of research for multiple pathologies. Currently, the use of proteomics for the identification of differences in protein expression profiles between samples from healthy subjects and patients, has emerged as a powerful strategy to improve the current diagnosis of various pathologies or propose novel therapeutic approaches. Among the biological fluids from which new pathological biomarkers can be identified, tear secretion is highly attractive, since it can be collected non-invasively and could better concentrate proteins that sensitively reflect allergic responses, owing to their exposure to environmental factors and its connection to the respiratory system. Despite its potential, tear fluid remains underexplored, offering significant research opportunities. In this study, we collected human tear samples using the Shirmer Test from healthy and allergic individuals. Our optimized workflow, combining sample preparation and high-throughput proteomics using the data-independent acquisition (DIA) strategy, identified 2542 proteins and enabled the successful differentiation of the two groups. We identified 99 differentially expressed proteins. Our results show the feasibility of protein analysis in human tear samples, highlighting tears as a highly sensitive fluid for detecting health conditions. Data are available via ProteomeXchange with identifier PXD067099.
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