ArticleScientific reports2017
An Ocular Protein Triad Can Classify Four Complex Retinal Diseases.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Artificial Intelligence Analysis of Biofluid Markers in Age-Related Macular Degeneration: A Systematic Review.Clinical ophthalmology (Auckland, N.Z.) · 2022Review
- Clinical Features, Diagnosis, Management and Prognosis of Primary Intraocular Lymphoma.Frontiers in oncology · 2022Article
- Vitreoretinal Lymphoma.Cancers · 2021Review
- New Pharmacological Strategies for the Treatment of Non-Infectious Uveitis. A Minireview.Frontiers in pharmacology · 2020Review
- Combined cellular and soluble mediator analysis for improved diagnosis of vitreoretinal lymphoma.Acta ophthalmologica · 2019Article
- Potential Diagnosis of Vitreoretinal Lymphoma by Detection of MYD88 Mutation in Aqueous Humor With Ultrasensitive Droplet Digital Polymerase Chain Reaction.JAMA ophthalmology · 2018Article
- Personalized Proteomics for Precision Health: Identifying Biomarkers of Vitreoretinal Disease.Translational vision science & technology · 2018Article
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Authors and funding
11 authors.
Funding
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Abstract
Retinal diseases generally are vision-threatening conditions that warrant appropriate clinical decision-making which currently solely dependents upon extensive clinical screening by specialized ophthalmologists. In the era where molecular assessment has improved dramatically, we aimed at the identification of biomarkers in 175 ocular fluids to classify four archetypical ocular conditions affecting the retina (age-related macular degeneration, idiopathic non-infectious uveitis, primary vitreoretinal lymphoma, and rhegmatogenous retinal detachment) with one single test. Unsupervised clustering of ocular proteins revealed a classification strikingly similar to the clinical phenotypes of each disease group studied. We developed and independently validated a parsimonious model based merely on three proteins; interleukin (IL)-10, IL-21, and angiotensin converting enzyme (ACE) that could correctly classify patients with an overall accuracy, sensitivity and specificity of respectively, 86.7%, 79.4% and 92.5%. Here, we provide proof-of-concept for molecular profiling as a diagnostic aid for ophthalmologists in the care for patients with retinal conditions.
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