Tear Film Steroid Profiling in Dry Eye Disease by Liquid Chromatography Tandem Mass Spectrometry.
Int J Mol Sci
; 18(7)2017 Jun 24.
Article
in En
| MEDLINE
| ID: mdl-28672794
ABSTRACT
Dry eye disease (DED) is a multifactorial disorder of the ocular surface unit resulting in eye discomfort, visual disturbance, and ocular surface damage; the risk of DED increases with age in both sexes, while its incidence is higher among females caused by an overall hormonal imbalance. The role of androgens has recently investigated and these hormones were considered to have a protective function on the ocular surface. In order to correlate DED to tear steroid levels, a robust, specific, and selective method for the simultaneous quantification of cortisol (CORT), corticosterone (CCONE), 11-deoxycortisol (11-DECOL), 4-androstene-3,17-dione (ADIONE), testosterone (TESTO), 17α-hydroxyprogesterone (17-OHP), and progesterone (PROG) was developed and applied for the analysis of tear samples. The method involves a simple extraction procedure of steroids from tears collected on Schirmer strips, followed by a high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis. In total, tear samples from 14 DED female patients and 13 healthy female controls were analysed and, CORT, ADIONE, and 17-OHP response levels resulted significantly decreased in dry eye patients respect to controls. The receiver operating characteristic (ROC) curve obtained by the combination of these three steroids (AUC = 0.964) demonstrated the good diagnostic power of the differential tear steroids in identifying DED. In conclusion, the present method made it possible, for the first time, to study steroid profiling directly in tear fluid.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Steroids
/
Tears
/
Dry Eye Syndromes
/
Chromatography, Liquid
/
Tandem Mass Spectrometry
Type of study:
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Adult
/
Aged
/
Female
/
Humans
/
Middle aged
Language:
En
Journal:
Int J Mol Sci
Year:
2017
Document type:
Article
Affiliation country:
Italia