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Diaconita V, Kassotis A, Ngo WK. Optical Coherence Tomography Angiography (OCTA) Findings in Retinitis Pigmentosa. Methods Mol Biol 2022; 2560:101-109. [PMID: 36481887 DOI: 10.1007/978-1-0716-2651-1_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Optical coherence tomography angiography (OCTA) is a noninvasive new imaging modality that can be used to diagnose and monitor progression of retinitis pigmentosa (RP). Cohorts and case series have shown correlation between OCTA findings and visual function and disease severity. Although an early use of the technology is promising, there are concerns about segmentation errors and artifacts. There is also a paucity of data on genotype and how that correlates with OCTA findings. Despite its limitations, OCTA remains a useful tool for clinicians managing retinitis pigmentosa patients.
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Affiliation(s)
- Vlad Diaconita
- Edward S. Harkness Eye Institute, Department of Ophthalmology, Columbia University, New York, NY, USA.
| | - Alexis Kassotis
- Ophthalmology Resident, Edward S. Harkness Eye Institute, Columbia University Irving Medical Center, New York, USA
| | - Wei Kiong Ngo
- Departments of Ophthalmology, Pathology & Cell Biology, Graduate Programs in Nutritional & Metabolic Biology and Neurobiology & Behavior, Columbia Stem Cell Initiative, New York, NY, USA
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Yang J, Zhou L, Ouyang J, Xiao X, Sun W, Li S, Zhang Q. Genotype-Phenotype Analysis of RPGR Variations: Reporting of 62 Chinese Families and a Literature Review. Front Genet 2021; 12:600210. [PMID: 34745198 PMCID: PMC8565807 DOI: 10.3389/fgene.2021.600210] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Accepted: 04/27/2021] [Indexed: 02/05/2023] Open
Abstract
Purpose RPGR is the most common cause of X-linked retinitis pigmentosa (RP), of which female carriers are also frequently affected. The aim of the current study was to explore the RPGR variation spectrum and associated phenotype based on the data from our lab and previous studies. Methods Variants in RPGR were selected from exome sequencing data of 7,092 probands with different eye conditions. The probands and their available family members underwent comprehensive ocular examinations. Similar data were collected from previous reports through searches in PubMed, Web of Science, and Google Scholar. Systematic analyses of genotypes, phenotypes and their correlations were performed. Results A total of 46 likely pathogenic variants, including nine missense and one in-frame variants in RCC1-like domain and 36 truncation variants, in RPGR were detected in 62 unrelated families in our in-house cohort. In addition, a total of 585 variants, including 491 (83.9%) truncation variants, were identified from the literature. Systematic analysis of variants from our in-house dataset, literature, and gnomAD suggested that most of the pathogenic variants of RPGR were truncation variants while pathogenic missense and in-frame variants were enriched in the RCC1-like domain. Phenotypic variations were present between males and female carriers, including more severe refractive error but better best corrected visual acuity (BCVA) in female carriers than those in males. The male patients showed a significant reduction of BCVA with increase of age and males with exon1-14 variants presented a better BCVA than those with ORF15 variants. For female carriers, the BCVA also showed significant reduction with increase of age, but BCVA in females with exon1-14 variants was not significant difference compared with those with ORF15 variants. Conclusion Most pathogenic variants of RPGR are truncations. Missense and in-frame variants located outside of the RCC1-like domain might be benign and the pathogenicity criteria for these variants should be considered with greater caution. The BCVA and refractive error are different between males and female carriers. Increase of age and location of variants in ORF15 contribute to the reduction of BCVA in males. These results are valuable for understanding genotypes and phenotypes of RPGR.
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Affiliation(s)
- Junxing Yang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Lin Zhou
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.,Department of Ophthalmology, West China Hospital, Sichuan University, Chengdu, China
| | - Jiamin Ouyang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Xueshan Xiao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Wenmin Sun
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Shiqiang Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Qingjiong Zhang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
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Musial G, Queener HM, Adhikari S, Mirhajianmoghadam H, Schill AW, Patel NB, Porter J. Automatic Segmentation of Retinal Capillaries in Adaptive Optics Scanning Laser Ophthalmoscope Perfusion Images Using a Convolutional Neural Network. Transl Vis Sci Technol 2020; 9:43. [PMID: 32855847 PMCID: PMC7424955 DOI: 10.1167/tvst.9.2.43] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 06/02/2020] [Indexed: 12/11/2022] Open
Abstract
Purpose Adaptive optics scanning laser ophthalmoscope (AOSLO) capillary perfusion images can possess large variations in contrast, intensity, and background signal, thereby limiting the use of global or adaptive thresholding techniques for automatic segmentation. We sought to develop an automated approach to segment perfused capillaries in AOSLO images. Methods 12,979 image patches were extracted from manually segmented AOSLO montages from 14 eyes and used to train a convolutional neural network (CNN) that classified pixels as capillaries, large vessels, background, or image canvas. 1764 patches were extracted from AOSLO montages of four separate subjects, and were segmented manually by two raters (ground truth) and automatically by the CNN, an Otsu's approach, and a Frangi approach. A modified Dice coefficient was created to account for slight spatial differences between the same manually and CNN-segmented capillaries. Results CNN capillary segmentation had an accuracy (0.94), a Dice coefficient (0.67), and a modified Dice coefficient (0.90) that were significantly higher than other automated approaches (P < 0.05). There were no significant differences in capillary density and mean segment length between manual ground-truth and CNN segmentations (P > 0.05). Conclusions Close agreement between the CNN and manual segmentations enables robust and objective quantification of perfused capillary metrics. The developed CNN is time and computationally efficient, and distinguishes capillaries from areas containing diffuse background signal and larger underlying vessels. Translational Relevance This automatic segmentation algorithm greatly increases the efficiency of quantifying AOSLO capillary perfusion images.
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Affiliation(s)
- Gwen Musial
- Department of Biomedical Engineering, University of Houston, Houston, TX, USA
| | - Hope M Queener
- College of Optometry, University of Houston, Houston, TX, USA
| | - Suman Adhikari
- College of Optometry, University of Houston, Houston, TX, USA
| | | | - Alexander W Schill
- Department of Biomedical Engineering, University of Houston, Houston, TX, USA.,College of Optometry, University of Houston, Houston, TX, USA
| | - Nimesh B Patel
- College of Optometry, University of Houston, Houston, TX, USA
| | - Jason Porter
- Department of Biomedical Engineering, University of Houston, Houston, TX, USA.,College of Optometry, University of Houston, Houston, TX, USA
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Cehajic-Kapetanovic J, Xue K, Martinez-Fernandez de la Camara C, Nanda A, Davies A, Wood LJ, Salvetti AP, Fischer MD, Aylward JW, Barnard AR, Jolly JK, Luo E, Lujan BJ, Ong T, Girach A, Black GCM, Gregori NZ, Davis JL, Rosa PR, Lotery AJ, Lam BL, Stanga PE, MacLaren RE. Initial results from a first-in-human gene therapy trial on X-linked retinitis pigmentosa caused by mutations in RPGR. Nat Med 2020; 26:354-359. [PMID: 32094925 PMCID: PMC7104347 DOI: 10.1038/s41591-020-0763-1] [Citation(s) in RCA: 190] [Impact Index Per Article: 47.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Accepted: 01/10/2020] [Indexed: 12/21/2022]
Abstract
Retinal gene therapy has shown great promise in treating retinitis pigmentosa (RP), a primary photoreceptor degeneration that leads to severe sight loss in young people. In the present study, we report the first-in-human phase 1/2, dose-escalation clinical trial for X-linked RP caused by mutations in the RP GTPase regulator (RPGR) gene in 18 patients over up to 6 months of follow-up (https://clinicaltrials.gov/: NCT03116113). The primary outcome of the study was safety, and secondary outcomes included visual acuity, microperimetry and central retinal thickness. Apart from steroid-responsive subretinal inflammation in patients at the higher doses, there were no notable safety concerns after subretinal delivery of an adeno-associated viral vector encoding codon-optimized human RPGR (AAV8-coRPGR), meeting the pre-specified primary endpoint. Visual field improvements beginning at 1 month and maintained to the last point of follow-up were observed in six patients.
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Affiliation(s)
- Jasmina Cehajic-Kapetanovic
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Kanmin Xue
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Cristina Martinez-Fernandez de la Camara
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Anika Nanda
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Alexandra Davies
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Laura J Wood
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Anna Paola Salvetti
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - M Dominik Fischer
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - James W Aylward
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Alun R Barnard
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Jasleen K Jolly
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | | | - Brandon J Lujan
- Casey Eye Institute, Oregon Health and Science University, Portland, OR, USA
| | - Tuyen Ong
- Nightstar Therapeutics Ltd, London, UK
| | | | - Graeme C M Black
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital and Manchester Vision Regeneration Laboratory, Manchester Royal Eye Hospital, Manchester Academic Health Science Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | | | | | | | - Andrew J Lotery
- Clinical Neurosciences Research Group, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | | | - Paulo E Stanga
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital and Manchester Vision Regeneration Laboratory, Manchester Royal Eye Hospital, Manchester Academic Health Science Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Robert E MacLaren
- Nuffield Laboratory of Ophthalmology, Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
- Oxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
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