Cecilia S Lee1, Rajendra S Apte2. 1. Department of Ophthalmology, University of Washington, Seattle, Washington, USA. Electronic address: leecs2@uw.edu. 2. Department of Ophthalmology, Washington University in St. Louis, St. Louis, Missouri, USA; Department of Developmental Biology, Washington University in St. Louis, St. Louis, Missouri, USA; Department of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
Abstract
PURPOSE: To address challenges associated with identifying retinal biomarkers for Alzheimer's disease (AD) and strategies for future investigation of novel ophthalmologic biomarkers. DESIGN: Perspective. METHODS: Summarization of the current understanding of retinal changes that have been identified using advances in imaging technology, analysis of current research into how these changes reflect neurodegenerative pathology, and recommendations for further research in this area that will allow for the identification of unique biomarkers for early AD. RESULTS: Some retinal changes detectable using various imaging modalities may reflect neurodegeneration or other AD-related pathology on a cellular level. Structural changes in both the peripapillary and macular retina and changes in vascular parameters have been identified. Some imaging findings correlate with known histopathologic findings, and some are associated with cognitive decline. However, multiple challenges exist, such as identifying retinal biomarkers that are specific to biomarker-positive AD, clinical syndrome of AD, and/or pathologic AD brain, finding features that are highly sensitive and specific to AD in patients with other eye diseases, and validating potential biomarkers in population-based longitudinal cohorts. CONCLUSIONS: Further research is needed to validate retinal biomarkers for AD, with accurate classification of patients according to diagnosis and cognitive symptoms. Advances in imaging technology, big data, and machine learning, as well as carefully designed studies, will help to identify and confirm potential biomarkers and may lead to novel treatment approaches.
PURPOSE: To address challenges associated with identifying retinal biomarkers for Alzheimer's disease (AD) and strategies for future investigation of novel ophthalmologic biomarkers. DESIGN: Perspective. METHODS: Summarization of the current understanding of retinal changes that have been identified using advances in imaging technology, analysis of current research into how these changes reflect neurodegenerative pathology, and recommendations for further research in this area that will allow for the identification of unique biomarkers for early AD. RESULTS: Some retinal changes detectable using various imaging modalities may reflect neurodegeneration or other AD-related pathology on a cellular level. Structural changes in both the peripapillary and macular retina and changes in vascular parameters have been identified. Some imaging findings correlate with known histopathologic findings, and some are associated with cognitive decline. However, multiple challenges exist, such as identifying retinal biomarkers that are specific to biomarker-positive AD, clinical syndrome of AD, and/or pathologic AD brain, finding features that are highly sensitive and specific to AD in patients with other eye diseases, and validating potential biomarkers in population-based longitudinal cohorts. CONCLUSIONS: Further research is needed to validate retinal biomarkers for AD, with accurate classification of patients according to diagnosis and cognitive symptoms. Advances in imaging technology, big data, and machine learning, as well as carefully designed studies, will help to identify and confirm potential biomarkers and may lead to novel treatment approaches.
Authors: Cecilia S Lee; Eric B Larson; Laura E Gibbons; Aaron Y Lee; Susan M McCurry; James D Bowen; Wayne C McCormick; Paul K Crane Journal: Alzheimers Dement Date: 2018-08-08 Impact factor: 21.566
Authors: Fang Ko; Zaynah A Muthy; John Gallacher; Cathie Sudlow; Geraint Rees; Qi Yang; Pearse A Keane; Axel Petzold; Peng T Khaw; Charles Reisman; Nicholas G Strouthidis; Paul J Foster; Praveen J Patel Journal: JAMA Neurol Date: 2018-10-01 Impact factor: 18.302
Authors: Swati S More; James M Beach; Collin McClelland; Ali Mokhtarzadeh; Robert Vince Journal: ACS Chem Neurosci Date: 2019-10-24 Impact factor: 4.418
Authors: Alberto Diniz-Filho; Lisa Delano-Wood; Fábio B Daga; Sebastião Cronemberger; Felipe A Medeiros Journal: JAMA Ophthalmol Date: 2017-07-01 Impact factor: 7.389