An Ocular Protein Triad Can Classify Four Complex Retinal Diseases

J J W Kuiper,P Schellekens,N H Ten Dam-Van Loon,J H De Boer,S Nierkens,R Van Leeuwen,M C Bartels,J Ossewaarde-Van Norel,T R D J Radstake,L Beretta,J D F De Groot-Mijnes

doi:10.1038/srep41595

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.

Highlights

Complex diseases of the retina are responsible for approximately 20% of blindness in the developing world and cover a wide spectrum of vision-threatening conditions including intraocular inflammatory diseases, retinal tearing or detachment, age-related macular degeneration, and potentially lethal and rare malignancies such as primary vitreoretinal lymphoma[1]
In contrast to most other medical specialists, the ophthalmologist has the unique opportunity to visually examine the inside of the target organ – the eye
While the last decade has seen an enormous rise of the adoption of molecular tools - mostly exploiting next-generation sequencing technologies - for rare monogenic inherited retinal conditions, objective molecular tools for more common and complex retinal diseases are sparse[6,7]

Summary

Introduction

Complex diseases of the retina are responsible for approximately 20% of blindness in the developing world and cover a wide spectrum of vision-threatening conditions including intraocular inflammatory diseases (e.g. uveitis), retinal tearing or detachment, age-related macular degeneration, and potentially lethal and rare malignancies such as primary vitreoretinal lymphoma[1]. Optimal clinical management is key to preserving or restoring visual function, which is achieved by combinations of eye examination (e.g. fluorescein angiography), imaging technologies (e.g. optical coherence tomography) and functional tests These clinical tools are effective, but bound by their requirement to be interpreted by well-experienced ophthalmologists to determine the optimal clinical care for each patient, which necessitate a high degree of training and experience[2]. Using multiple computational modeling strategies, we devised and validated a simple, but highly robust molecular classification model differentiating these ocular conditions in one single test These findings form a proof-of-concept for ocular fluid-based decision tools and pave the way for the development of molecular workflows to guide personalized care in the near future

Objectives

Methods

Conclusion