advertisement

Oculus

Abstract #82254 Published in IGR 20-4

Multi-Omics Approach for Studying Tears in Treatment-Naïve Glaucoma Patients

Rossi C; Cicalini I; Cufaro MC; Agnifili L; Mastropasqua L; Lanuti P; Marchisio M; De Laurenzi V; Del Boccio P; Pieragostino D
International journal of molecular sciences 2019; 20:


Primary open-angle glaucoma (POAG) represents the leading cause of irreversible blindness worldwide and is a multifactorial, chronic neurodegenerative disease characterized by retinal ganglion cell and visual field loss. There are many factors that are associated with the risk of developing POAG, with increased intraocular pressure being one of the most prevalent. Due to the asymptomatic nature of the disease, the diagnosis of POAG often occurs too late, which necessitates development of new effective screening strategies for early diagnosis of the disease. However, this task still remains unfulfilled. In order to provide further insights into the pathophysiology of POAG, we applied a targeted metabolomics strategy based on a high-throughput screening method for the determination of tear amino acids, free carnitine, acylcarnitines, succinylacetone, nucleosides, and lysophospholipids in naïve to therapy glaucomatous patients and normal controls. Also, we conducted proteomic analyses of the whole lacrimal fluid and purified extracellular vesicles obtained from POAG patients and healthy subjects. This multi-omics approach allowed us to conclude that POAG patients had lower levels of certain tear amino acids and lysophospholipids compared with controls. These targeted analyses also highlighted the low amount of acetylcarnitine (C2) in POAG patient which correlated well with proteomics data. Moreover, POAG tear proteins seemed to derive from extracellular vesicles, which carried a specific pro-inflammatory protein cargo.

Full article

Classification:

3.12 Proteomics (Part of: 3 Laboratory methods)
2.1 Conjunctiva (Part of: 2 Anatomical structures in glaucoma)



Issue 20-4

Select Issue


advertisement

Oculus