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Profiling and Bioinformatic Analysis of Differentially Expressed Cytokines in Aqueous Humor of High Myopic Eyes – Clues for Anti-VEGF Injections

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posted on 2019-08-13, 08:55 authored by Xiangjia Zhu, Yu Du, Roger J.W. Truscott, Wenwen He, Peng Zhou, Yi Lu

To investigate the aqueous humor growth factor profile in high myopic eyes and analyze the interaction of differentially expressed cytokines.

A case–control study including aqueous humor samples from 36 high myopic patients and 32 controls was conducted. Quantibody® Human Growth Factor Array was used to screen the presence of 40 growth factors in aqueous humor. Expressions of differential growth factors were validated by Bio-Plex ProTM multiplex bead-based immunoassay. Protein–protein interaction (PPI) and gene ontology (GO) analyses were performed.

Growth differentiation factor 15 (GDF-15), hepatocyte growth factor (HGF), and platelet-derived growth factor (PDGF)-AA were found to be significantly higher and vascular endothelial growth factor (VEGF) was detected to be lower in high myopic eyes (all P = .03). Multi-plex bead-based assay further validated the differential expressions of four growth factors and all of them were significantly correlated with axial length (P < .001). Twenty-six proteins were mapped into PPI network and positive regulation of cell migration, cellular component movement, and cell motility were the most enriched biological processes based on GO analysis.

Differential expressed cytokines that indicates a distinctive intraocular microenvironment in high myopic eyes might provide clues for pathological changes within high myopic eyes after anti-VEGF injections.

Funding

This work was supported by research grants from the National Natural Science Foundation of the People’s Republic of China (grant nos. 81870642, 81470613, 81670835, and 81270989), the Shanghai High Myopia Study Group, the Shanghai Talent Development Fund (grant no. 201604), and the Outstanding Youth Medical Talents Program of Shanghai Health and Family Planning Commission (grant no. 2017YQ011).

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