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      Aqueous Fibronectin Correlates With Severity of Macular Edema and Visual Acuity in Patients With Branch Retinal Vein Occlusion: A Proteome Study

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          Abstract

          Purpose

          Large-scale protein analysis may bring important insights into molecular changes following branch retinal vein occlusion (BRVO). Using proteomic techniques this study compared aqueous humor samples from patients with BRVO to age-matched controls.

          Methods

          Aqueous humor samples from treatment naive patients with BRVO complicated by macular edema ( n = 19) and age-matched controls ( n = 18) were analyzed with label-free quantification nano liquid chromatography – tandem mass spectrometry (LFQ nLC-MS/MS). The severity of macular edema was measured as central retinal thickness (CRT) with optical coherence tomography. Control samples were obtained prior to cataract surgery. Proteins were filtered by requiring quantification in at least 50% of the samples in each group without imputation of missing values. Significantly changed proteins were identified with a permutation-based calculation with a false discovery rate at 0.05.

          Results

          In BRVO, 52 proteins were differentially expressed. Regulated proteins were involved in cell adhesion, coagulation, and acute-phase response. Apolipoprotein C-III, complement C3, complement C5, complement factor H, fibronectin, and fibrinogen chains were increased in BRVO and correlated with CRT. Fibronectin also correlated with best corrected visual acuity (BCVA) and vascular endothelial growth factor (VEGF). Monocyte differentiation antigen CD14 (CD14) and lipopolysaccharide-binding protein (LBP) were upregulated in BRVO. Contactin-1 and alpha-enolase were downregulated in BRVO and correlated negatively with CRT.

          Conclusions

          Multiple proteins, including complement factors, fibrinogen chains, and apolipoprotein C-III, correlated with CRT, indicating a multifactorial response. Fibronectin correlated with BCVA, CRT, and VEGF. Fibronectin may reflect the severity of BRVO. The proinflammatory proteins CD14 and LBP were upregulated in BRVO.

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          STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

          Damian Szklarczyk, Annika L Gable, David Lyon … (2018)
          Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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            STRING v10: protein–protein interaction networks, integrated over the tree of life

            Damian Szklarczyk, Andrea Franceschini, Stefan Wyder … (2014)
            The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein–protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein–protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.
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              The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible

              Damian Szklarczyk, John Morris, Helen Cook … (2016)
              A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein–protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein–protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.
              Article 0 comments Cited 1860 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Invest Ophthalmol Vis Sci
                Journal ID (iso-abbrev): Invest Ophthalmol Vis Sci
                Journal ID (pmc): iovs
                Journal ID (publisher-id): IOVS
                Title: Investigative Ophthalmology & Visual Science
                Publisher: The Association for Research in Vision and Ophthalmology
                ISSN (Print): 0146-0404
                ISSN (Electronic): 1552-5783
                Publication date (Electronic): 03 December 2020
                Publication date Collection: December 2020
                Volume: 61
                Issue: 14
                Electronic Location Identifier: 6
                Affiliations
                [1 ]Department of Ophthalmology, Odense University Hospital, Odense, Denmark
                [2 ]Department of Ophthalmology, Lillebaelt Hospital, Vejle, Denmark
                [3 ]Department of Clinical Research, University of Southern Denmark, Odense, Denmark
                [4 ]Department of Ophthalmology, Kyoto Prefectural University of Medicine, Kyoto, Japan
                [5 ]Department of Ophthalmology, Aalborg University Hospital, Aalborg, Denmark
                [6 ]Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
                [7 ]Department of Biomedicine, Aarhus University, Aarhus, Denmark
                Author notes
                [* ]Correspondence: Lasse Jørgensen Cehofski, Department of Ophthalmology, Odense University Hospital, Sdr. Boulevard 29, 5000 Odense C, Denmark; lassecehofski@ 123456hotmail.com .
                Article
                Publisher ID: IOVS-20-29968
                DOI: 10.1167/iovs.61.14.6
                PMC ID: 7718822
                PubMed ID: 33270842
                SO-VID: 188cbfc7-12c1-49c2-a754-8a6b12e55c08
                Copyright © Copyright 2020 The Authors
                License:

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                Date accepted : 05 October 2020
                Date received : 08 April 2020
                Page count
                Pages: 12
                Categories
                Subject: Retina
                Subject: Retina

                Keywords: retina,branch retinal vein occlusion,proteomics,mass spectrometry,macular edema
                Data availability:
                Keywords: retina, branch retinal vein occlusion, proteomics, mass spectrometry, macular edema

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