Proteomic analysis of human lacrimal and tear fluid in dry eye disease

Jae Hun Jung, Yong Woo Ji, Ho Sik Hwang, Jae Won Oh, Hyun Chang Kim, Hyung Keun Lee, Kwang Pyo Kim

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)

Abstract

To understand the pathophysiology of dry eye disease (DED), it is necessary to characterize proteins in the ocular surface fluids, including tear fluid (TF) and lacrimal fluid (LF). There have been several reports of TF proteomes, but few proteomic studies have examined LF secreted from the lacrimal gland (LG). Therefore, we characterized the proteins constituting TF and LF by liquid chromatography mass spectrometry. TF and LF were collected from patients with non-Sjögren syndrome DED and from healthy subjects. Through protein profiling and label-free quantification, 1165 proteins from TF and 1448 from LF were identified. In total, 849 proteins were present in both TF and LF. Next, candidate biomarkers were verified using the multiple reaction monitoring assay in both TF and LF of 17 DED patients and 17 healthy controls. As a result, 16 marker proteins were identified (fold-change > 1.5, p-value < 0.05), of which 3 were upregulated in TF and 8 up- and 5 down-regulated in LF. In conclusion, this study revealed novel DED markers originating from the LG and tears by in-depth proteomic analysis and comparison of TF and LF proteins.

Original languageEnglish
Article number13363
JournalScientific reports
Volume7
Issue number1
DOIs
Publication statusPublished - 2017 Dec 1

Bibliographical note

Funding Information:
This research was supported by a grant from the Korean Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare (HI15C-1595-020016 and HI13C0055) and by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT, and Future Planning (NRF-2015R1A2A2A04002684).

Publisher Copyright:
© 2017 The Author(s).

All Science Journal Classification (ASJC) codes

  • General

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