A Comparison of Emotionally Stimulated and Conventionally Collected Tears Using Bottom‐Up, Label‐Free Quantitative Proteomic Analysis—A Pilot Study

Proteomic analysis of biofluids is central for identifying disease biomarkers. Tears have become popular targets for biomarker discovery and biosensor development, largely because they can be collected noninvasively and are rich sources of biomarkers for ocular and systemic diseases. Although basal and reflex tears have been well characterized, the proteome of psycho-emotionally stimulated tears remains largely unexplored, hindering their applicability in biomarker discovery studies and the advancement of tear-based biosensors. Comprehensive proteomic analysis across different tear types is crucial for identifying novel biomarkers and improving disease diagnosis and monitoring. In this pilot study, tears collected via conventional stimulation techniques ("standard") versus those elicited through emotional stimuli ("emotional") were purchased from single donors through two vendors. We compared the proteomic profiles of emotional (n = 6) and standard (n = 14) single donor human tears to better understand the biochemical composition and functional roles of different tear types. In total, 907 proteins were identified from all tear samples. Fifty-two tear proteins were significantly enriched in emotionally stimulated tears. Functional characterization of enriched proteins revealed that most were extracellular or secreted. Many were also involved in host defense or immune responses, including members of the S100A and neutrophil defensin protein families. SUMMARY: Although emotional tears are known to differ from basal and reflex tears in both composition and function, the specific biochemical characteristics and functional roles of emotional tears remain poorly understood. This gap in knowledge is largely due to the limited research conducted on emotional tears, despite their distinct origins. A more complete understanding of all tear types is necessary for the continuation of biomarker discovery and the development of tear fluid-based biosensors. In this exploratory study, tears collected via a conventional/standard protocol and those collected from emotional stimulus were obtained from two vendors and subjected to proteomic profiling and comparison. A bottom-up proteomic approach was utilized to analyze tear samples, facilitating a comparison between tear types and contributing to the characterization of psycho-emotional tears.

Authors

Institutions

Publication Details

Journal
PROTEOMICS - CLINICAL APPLICATIONS
Published
2025-09-18
DOI
https://doi.org/10.1002/prca.70023
Primary Topic
Ocular Surface and Contact Lens
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comparison of Emotionally Stimulated and Conventionally Collected Tears Using Bottom‐Up, Label‐Free Quantitative Proteomic Analysis—A Pilot Study

Sean W. Harshman, C. Bruce Mousseau, Rhonda L. Pitsch, Alena R. Veigl‐Lunsford
PROTEOMICS - CLINICAL APPLICATIONS
Ocular Surface and Contact Lens
article

A Comparison of Emotionally Stimulated and Conventionally Collected Tears Using Bottom‐Up, Label‐Free Quantitative Proteomic Analysis—A Pilot Study

Sean W. Harshman, C. Bruce Mousseau, Rhonda L. Pitsch, Alena R. Veigl‐Lunsford
article en

Abstract

Proteomic analysis of biofluids is central for identifying disease biomarkers. Tears have become popular targets for biomarker discovery and biosensor development, largely because they can be collected noninvasively and are rich sources of biomarkers for ocular and systemic diseases. Although basal and reflex tears have been well characterized, the proteome of psycho-emotionally stimulated tears remains largely unexplored, hindering their applicability in biomarker discovery studies and the advancement of tear-based biosensors. Comprehensive proteomic analysis across different tear types is crucial for identifying novel biomarkers and improving disease diagnosis and monitoring. In this pilot study, tears collected via conventional stimulation techniques ("standard") versus those elicited through emotional stimuli ("emotional") were purchased from single donors through two vendors. We compared the proteomic profiles of emotional (n = 6) and standard (n = 14) single donor human tears to better understand the biochemical composition and functional roles of different tear types. In total, 907 proteins were identified from all tear samples. Fifty-two tear proteins were significantly enriched in emotionally stimulated tears. Functional characterization of enriched proteins revealed that most were extracellular or secreted. Many were also involved in host defense or immune responses, including members of the S100A and neutrophil defensin protein families. SUMMARY: Although emotional tears are known to differ from basal and reflex tears in both composition and function, the specific biochemical characteristics and functional roles of emotional tears remain poorly understood. This gap in knowledge is largely due to the limited research conducted on emotional tears, despite their distinct origins. A more complete understanding of all tear types is necessary for the continuation of biomarker discovery and the development of tear fluid-based biosensors. In this exploratory study, tears collected via a conventional/standard protocol and those collected from emotional stimulus were obtained from two vendors and subjected to proteomic profiling and comparison. A bottom-up proteomic approach was utilized to analyze tear samples, facilitating a comparison between tear types and contributing to the characterization of psycho-emotional tears.

PROTEOMICS - CLINICAL APPLICATIONSVol. 20(1)
United States Air Force Research Laboratory (US), Wright-Patterson Air Force Base (US)
U.S. Department of Defense, U.S. Air Force
Openalex Percentile: Top 66%
Ocular Surface and Contact Lens
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.