Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0314719 (dry eye)
 2,625 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The proteins found in tears have an important role in the maintenance of the ocular surface and changes in the quality and quantity of tear components reflect changes in the health of the ocular surface. In this study, we have used quantitative proteomics, iTRAQ technology coupled with 2D-nanoLC-nano-ESI-MS/MS and with a statistical model to uncover proteins that are significantly and reliably changed in the tears of dry eye patients in an effort to reveal potential biomarker candidates. Fifty-six patients with dry eye and 40 healthy subjects were recruited for this study. In total, 93 tear proteins were identified with a ProtScore >or=2 (>or=99% confidence). Associated with dry eye were 6 up-regulated proteins, alpha-enolase, alpha-1-acid glycoprotein 1, S100 A8 (calgranulin A), S100 A9 (calgranulin B), S100 A4 and S100 A11 (calgizzarin) and 4 down-regulated proteins, prolactin-inducible protein (PIP), lipocalin-1, lactoferrin and lysozyme. Receiver operating curves (ROC) were evaluated for individual biomarker candidates and a biomarker panel. With the use of a 4-protein biomarker panel, the diagnostic accuracy for dry eye was 96% (sensitivity, 91.0%; specificity, 90.0%). Two biomarker candidates (alpha-enolase and S100 A4) generated from iTRAQ experiments were successfully verified using an ELISA assay. The levels of these 10 tear proteins reflect aqueous secretion deficiency by lacrimal gland, inflammatory status of the ocular surface. The clinical classification of the severity of the dry eye condition was successfully correlated to the proteomics by using three proteins that are associated with inflammation, alpha1-acid glycoprotein 1, S100 A8 and S100 A9. The nine tear protein biomarker candidates (except alpha1-acid glycoprotein 1) were also verified using an independent age-matched patient sample set. This study demonstrated that iTRAQ technology combined with 2D-nanoLC-nanoESI-MS/MS quantitative proteomics is a powerful tool for biomarker discovery.
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PMID:Identification of tear fluid biomarkers in dry eye syndrome using iTRAQ quantitative proteomics. 1970 75

We analyzed the tear film proteome of patients with dry eye (DE), meibomian gland dysfunction (MGD), and normal volunteers (CT). Tear samples were collected from 70 individuals. Of these, 37 samples were analyzed using spectral-counting-based LC-MS/MS label-free quantitation, and 33 samples were evaluated in the validation of candidate biomarkers employing customized antibody microarray assays. Comparative analysis of tear protein profiles revealed differences in the expression levels of 26 proteins, including protein S100A6, annexin A1, cystatin-S, thioredoxin, phospholipase A2, antileukoproteinase, and lactoperoxidase. Antibody microarray validation of CST4, S100A6, and MMP9 confirmed the accuracy of previously reported ELISA assays, with an area under ROC curve (AUC) of 87.5%. Clinical endpoint analysis showed a good correlation between biomarker concentrations and clinical parameters. In conclusion, different sets of proteins differentiate between the groups. Apolipoprotein D, S100A6, S100A8, and ceruloplasmin discriminate best between the DE and CT groups. The differences between antileukoproteinase, phospholipase A2, and lactoperoxidase levels allow the distinction between MGD and DE, and the changes in the levels of annexin A1, clusterin, and alpha-1-acid glycoprotein 1, between MGD and CT groups. The functional network analysis revealed the main biological processes that should be examined to identify new candidate biomarkers and therapeutic targets.
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PMID:Tear proteome analysis in ocular surface diseases using label-free LC-MS/MS and multiplexed-microarray biomarker validation. 2923 88