Tear biomarkers.

Disease-specific markers Ocular surface diseases Omic analysis Tear composition Tear film stability

Journal

Advances in clinical chemistry
ISSN: 2162-9471
Titre abrégé: Adv Clin Chem
Pays: United States
ID NLM: 2985173R

Informations de publication

Date de publication:
2024
Historique:
medline: 19 5 2024
pubmed: 19 5 2024
entrez: 18 5 2024
Statut: ppublish

Résumé

An extensive exploration of lacrimal fluid molecular biomarkers in understanding and diagnosing a spectrum of ocular and systemic diseases is presented. The chapter provides an overview of lacrimal fluid composition, elucidating the roles of proteins, lipids, metabolites, and nucleic acids within the tear film. Pooled versus single-tear analysis is discussed to underline the benefits and challenges associated with both approaches, offering insights into optimal strategies for tear sample analysis. Subsequently, an in-depth analysis of tear collection methods is presented, with a focus on Schirmer's test strips and microcapillary tubes methods. Alternative tear collection techniques are also explored, shedding light on their applicability and advantages. Variability factors, including age, sex, and diurnal fluctuations, are examined in the context of their impact on tear biomarker analysis. The main body of the chapter is dedicated to discussing specific biomarkers associated with ocular discomfort and a wide array of ocular diseases. From dry eye disease and thyroid-associated ophthalmopathy to keratoconus, age-related macular degeneration, diabetic retinopathy, and glaucoma, the intricate relationship between molecular biomarkers and these conditions is thoroughly dissected. Expanding beyond ocular pathologies, the chapter explores the applicability of tear biomarkers in diagnosing systemic diseases such as multiple sclerosis, amyotrophic lateral sclerosis, Alzheimer's disease, Parkinson's disease, and cancer. This broader perspective underscores the potential of lacrimal fluid analysis in offering non-invasive diagnostic tools for conditions with far-reaching implications.

Identifiants

pubmed: 38762243
pii: S0065-2423(24)00059-3
doi: 10.1016/bs.acc.2024.03.002
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

69-115

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Auteurs

Erika Ponzini (E)

Department of Materials Science, University of Milano Bicocca, Milan, Italy; COMiB Research Center, University of Milano Bicocca, Milan, Italy. Electronic address: erika.ponzini@unimib.it.

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Classifications MeSH