Adam M Dubis1, Robert F Cooper2, Jonathan Aboshiha1, Christopher S Langlo3, Venki Sundaram1, Benjamin Liu4, Frederick Collison5, Gerald A Fishman5, Anthony T Moore1, Andrew R Webster1, Alfredo Dubra6, Joseph Carroll7, Michel Michaelides1. 1. Moorfields Eye Hospital, London, United Kingdom UCL Institute of Ophthalmology, University College London, London, United Kingdom. 2. Department of Biomedical Engineering, Marquette University, Milwaukee, Wisconsin, United States. 3. Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, United States. 4. Department of Ophthalmology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States. 5. The Pangere Center for Hereditary Retinal Diseases, The Chicago Lighthouse for People Who Are Blind or Visually Impaired, Chicago, Illinois, United States. 6. Department of Biomedical Engineering, Marquette University, Milwaukee, Wisconsin, United States Department of Ophthalmology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, United States. 7. Department of Biomedical Engineering, Marquette University, Milwaukee, Wisconsin, United States Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, United States Department of Ophthalmology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, United States.
Abstract
PURPOSE: Gene therapy trials for inherited photoreceptor disorders are planned. Anatomical metrics to select the best candidates and outcomes are needed. Adaptive optics (AO) imaging enables visualization of photoreceptor structure, although analytical tools are lacking. Here we present criteria to assess residual photoreceptor integrity in achromatopsia (ACHM). METHODS: Two AOSLOs, at the Medical College of Wisconsin and Moorfields Eye Hospital, were used to image the photoreceptor mosaic of 11 subjects with ACHM and 7 age-matched controls. Images were obtained, processed, and montaged using previously described methods. Cone density and reflectivity were quantified to assess residual cone photoreceptor structure. RESULTS: All subjects with ACHM had reduced numbers of cone photoreceptors, albeit to a variable degree. In addition, the relative cone reflectivity varied greatly. Interestingly, subjects with GNAT2-associated ACHM had the greatest number of residual cones and the reflectivity of those cones was significantly greater than that of the cones in the subjects with CNGA3/CNGB3-associated ACHM. CONCLUSIONS: We present cone reflectivity as a metric that can be used to characterize cone structure in ACHM. This method may be applicable to subjects with other cone disorders. In ACHM, we hypothesize that cone numerosity (and/or density) combined with cone reflectivity could be used to gauge the therapeutic potential. As gene replacement would not be expected to add cones, reflectivity could be a more powerful AO-metric for monitoring the cellular response to treatment and could provide a more immediate indicator of efficacy than behavioral measures, which may take longer to change. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.
PURPOSE: Gene therapy trials for inherited photoreceptor disorders are planned. Anatomical metrics to select the best candidates and outcomes are needed. Adaptive optics (AO) imaging enables visualization of photoreceptor structure, although analytical tools are lacking. Here we present criteria to assess residual photoreceptor integrity in achromatopsia (ACHM). METHODS: Two AOSLOs, at the Medical College of Wisconsin and Moorfields Eye Hospital, were used to image the photoreceptor mosaic of 11 subjects with ACHM and 7 age-matched controls. Images were obtained, processed, and montaged using previously described methods. Cone density and reflectivity were quantified to assess residual cone photoreceptor structure. RESULTS: All subjects with ACHM had reduced numbers of cone photoreceptors, albeit to a variable degree. In addition, the relative cone reflectivity varied greatly. Interestingly, subjects with GNAT2-associated ACHM had the greatest number of residual cones and the reflectivity of those cones was significantly greater than that of the cones in the subjects with CNGA3/CNGB3-associated ACHM. CONCLUSIONS: We present cone reflectivity as a metric that can be used to characterize cone structure in ACHM. This method may be applicable to subjects with other cone disorders. In ACHM, we hypothesize that cone numerosity (and/or density) combined with cone reflectivity could be used to gauge the therapeutic potential. As gene replacement would not be expected to add cones, reflectivity could be a more powerful AO-metric for monitoring the cellular response to treatment and could provide a more immediate indicator of efficacy than behavioral measures, which may take longer to change. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.
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