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Chu J, Shaia JK, Sharma N, Russell MW, Rachitskaya AV, Talcott KE, Singh RP. Characterization and prevalence of ocular comorbidities and risk of legal blindness across the United States. Eye (Lond) 2024:10.1038/s41433-024-03238-3. [PMID: 39085595 DOI: 10.1038/s41433-024-03238-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 05/14/2024] [Accepted: 07/09/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND/OBJECTIVES Vision loss is a top disability in the United States (US). Patients commonly present with multiple ocular diseases, but the extent to which this places them at risk for vision loss, and if sex and race impacts this, is poorly understood. This exploratory analysis evaluated which ocular comorbidities and demographics are at highest risk for visual impairment. SUBJECTS/METHODS A retrospective cross-sectional study was conducted through the TriNetX Analytics Network, an aggregated network encompassing over 90 million insured and uninsured patients across 50 healthcare organizations from all regions in the US. Patients with diabetic retinopathy (DR), age-related macular degeneration (AMD), retinal vein occlusion (RVO), glaucoma, and uveitis were included in this study. Ocular diseases and visual impairment were determined through ICD-10 codes. Prevalence and odds ratios were calculated while stratifying by sex and racial demographics. Statistical analyses were completed using RStudio and Excel with 95% confidence intervals calculated. RESULTS The comorbid conditions with the highest prevalence of visual impairment were uveitis and RVO (39.94%), uveitis and neovascular AMD (37.61%), and uveitis and glaucoma (33.23%). The comorbidity with the highest odds for visual impairment was uveitis and RVO (POR 4.86; 95% CI 4.49, 5.26). Compared to white males, Black and Hispanic males were disproportionately affected by visual impairment across ocular comorbidities. CONCLUSION This study quantified the prevalence and odds of visual impairment for unilateral and comorbid ocular disease, with the addition of uveitis causing the greatest increase. Black and Hispanic males were disproportionately affected by visual impairment across comorbid conditions.
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Affiliation(s)
- Jeffrey Chu
- Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Jacqueline K Shaia
- Case Western Reserve University School of Medicine, Cleveland, OH, USA
- Center for Ophthalmic Bioinformatics, Cole Eye Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Neha Sharma
- Case Western Reserve University School of Medicine, Cleveland, OH, USA
- Center for Ophthalmic Bioinformatics, Cole Eye Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Matthew W Russell
- Center for Ophthalmic Bioinformatics, Cole Eye Institute, Cleveland Clinic, Cleveland, OH, USA
- Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA
| | | | - Katherine E Talcott
- Center for Ophthalmic Bioinformatics, Cole Eye Institute, Cleveland Clinic, Cleveland, OH, USA
- Cleveland Clinic Cole Eye Institute, Cleveland, OH, USA
| | - Rishi P Singh
- Center for Ophthalmic Bioinformatics, Cole Eye Institute, Cleveland Clinic, Cleveland, OH, USA.
- Martin Hospitals, Cleveland Clinic Florida, Stuart, FL, USA.
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Stoddart PR, Begeng JM, Tong W, Ibbotson MR, Kameneva T. Nanoparticle-based optical interfaces for retinal neuromodulation: a review. Front Cell Neurosci 2024; 18:1360870. [PMID: 38572073 PMCID: PMC10987880 DOI: 10.3389/fncel.2024.1360870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Accepted: 03/04/2024] [Indexed: 04/05/2024] Open
Abstract
Degeneration of photoreceptors in the retina is a leading cause of blindness, but commonly leaves the retinal ganglion cells (RGCs) and/or bipolar cells extant. Consequently, these cells are an attractive target for the invasive electrical implants colloquially known as "bionic eyes." However, after more than two decades of concerted effort, interfaces based on conventional electrical stimulation approaches have delivered limited efficacy, primarily due to the current spread in retinal tissue, which precludes high-acuity vision. The ideal prosthetic solution would be less invasive, provide single-cell resolution and an ability to differentiate between different cell types. Nanoparticle-mediated approaches can address some of these requirements, with particular attention being directed at light-sensitive nanoparticles that can be accessed via the intrinsic optics of the eye. Here we survey the available known nanoparticle-based optical transduction mechanisms that can be exploited for neuromodulation. We review the rapid progress in the field, together with outstanding challenges that must be addressed to translate these techniques to clinical practice. In particular, successful translation will likely require efficient delivery of nanoparticles to stable and precisely defined locations in the retinal tissues. Therefore, we also emphasize the current literature relating to the pharmacokinetics of nanoparticles in the eye. While considerable challenges remain to be overcome, progress to date shows great potential for nanoparticle-based interfaces to revolutionize the field of visual prostheses.
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Affiliation(s)
- Paul R. Stoddart
- School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - James M. Begeng
- School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia
- Department of Biomedical Engineering, Faculty of Engineering & Information Technology, The University of Melbourne, Melbourne, VIC, Australia
| | - Wei Tong
- Department of Biomedical Engineering, Faculty of Engineering & Information Technology, The University of Melbourne, Melbourne, VIC, Australia
- School of Physics, The University of Melbourne, Melbourne, VIC, Australia
| | - Michael R. Ibbotson
- Department of Biomedical Engineering, Faculty of Engineering & Information Technology, The University of Melbourne, Melbourne, VIC, Australia
| | - Tatiana Kameneva
- School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia
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3
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Shwani T, Zhang C, Owen LA, Shakoor A, Vitale AT, Lillvis JH, Barr JL, Cromwell P, Finley R, Husami N, Au E, Zavala RA, Graves EC, Zhang SX, Farkas MH, Ammar DA, Allison KM, Tawfik A, Sherva RM, Li M, Stambolian D, Kim IK, Farrer LA, DeAngelis MM. Patterns of Gene Expression, Splicing, and Allele-Specific Expression Vary among Macular Tissues and Clinical Stages of Age-Related Macular Degeneration. Cells 2023; 12:2668. [PMID: 38067097 PMCID: PMC10705168 DOI: 10.3390/cells12232668] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 11/05/2023] [Accepted: 11/09/2023] [Indexed: 12/18/2023] Open
Abstract
Age-related macular degeneration (AMD) is a leading cause of blindness, and elucidating its underlying disease mechanisms is vital to the development of appropriate therapeutics. We identified differentially expressed genes (DEGs) and differentially spliced genes (DSGs) across the clinical stages of AMD in disease-affected tissue, the macular retina pigment epithelium (RPE)/choroid and the macular neural retina within the same eye. We utilized 27 deeply phenotyped donor eyes (recovered within a 6 h postmortem interval time) from Caucasian donors (60-94 years) using a standardized published protocol. Significant findings were then validated in an independent set of well-characterized donor eyes (n = 85). There was limited overlap between DEGs and DSGs, suggesting distinct mechanisms at play in AMD pathophysiology. A greater number of previously reported AMD loci overlapped with DSGs compared to DEGs between disease states, and no DEG overlap with previously reported loci was found in the macular retina between disease states. Additionally, we explored allele-specific expression (ASE) in coding regions of previously reported AMD risk loci, uncovering a significant imbalance in C3 rs2230199 and CFH rs1061170 in the macular RPE/choroid for normal eyes and intermediate AMD (iAMD), and for CFH rs1061147 in the macular RPE/choroid for normal eyes and iAMD, and separately neovascular AMD (NEO). Only significant DEGs/DSGs from the macular RPE/choroid were found to overlap between disease states. STAT1, validated between the iAMD vs. normal comparison, and AGTPBP1, BBS5, CERKL, FGFBP2, KIFC3, RORα, and ZNF292, validated between the NEO vs. normal comparison, revealed an intricate regulatory network with transcription factors and miRNAs identifying potential upstream and downstream regulators. Findings regarding the complement genes C3 and CFH suggest that coding variants at these loci may influence AMD development via an imbalance of gene expression in a tissue-specific manner. Our study provides crucial insights into the multifaceted genomic underpinnings of AMD (i.e., tissue-specific gene expression changes, potential splice variation, and allelic imbalance), which may open new avenues for AMD diagnostics and therapies specific to iAMD and NEO.
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Affiliation(s)
- Treefa Shwani
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
- Neuroscience Graduate Program, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
| | - Charles Zhang
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
| | - Leah A. Owen
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
- Department of Ophthalmology and Visual Sciences, University of Utah School of Medicine, The University of Utah, Salt Lake City, UT 84132, USA; (A.S.); (A.T.V.)
- Department of Population Health Sciences, University of Utah School of Medicine, The University of Utah, Salt Lake City, UT 84132, USA
- Department of Obstetrics and Gynecology, University of Utah School of Medicine, The University of Utah, Salt Lake City, UT 84132, USA
| | - Akbar Shakoor
- Department of Ophthalmology and Visual Sciences, University of Utah School of Medicine, The University of Utah, Salt Lake City, UT 84132, USA; (A.S.); (A.T.V.)
| | - Albert T. Vitale
- Department of Ophthalmology and Visual Sciences, University of Utah School of Medicine, The University of Utah, Salt Lake City, UT 84132, USA; (A.S.); (A.T.V.)
| | - John H. Lillvis
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
- Veterans Administration Western New York Healthcare System, Buffalo, NY 14212, USA
| | - Julie L. Barr
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
- Neuroscience Graduate Program, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
| | - Parker Cromwell
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
| | - Robert Finley
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
| | - Nadine Husami
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
| | - Elizabeth Au
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
| | - Rylee A. Zavala
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
| | - Elijah C. Graves
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
| | - Sarah X. Zhang
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
- Neuroscience Graduate Program, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
- Department of Biochemistry, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
| | - Michael H. Farkas
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
- Neuroscience Graduate Program, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
- Veterans Administration Western New York Healthcare System, Buffalo, NY 14212, USA
- Department of Biochemistry, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
| | - David A. Ammar
- Lion’s Eye Institute for Transplant & Research, Tampa, FL 33605, USA;
| | - Karen M. Allison
- Department of Ophthalmology, Flaum Eye Institute, University of Rochester, Rochester, NY 14642, USA;
| | - Amany Tawfik
- Department of Foundational Medical Studies and Eye Research Center, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA;
- Eye Research Institute, Oakland University, Rochester, MI 48309, USA
| | - Richard M. Sherva
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA; (R.M.S.); (L.A.F.)
| | - Mingyao Li
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Dwight Stambolian
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Ivana K. Kim
- Retina Service, Massachusetts Eye & Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA;
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA; (R.M.S.); (L.A.F.)
| | - Margaret M. DeAngelis
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA; (T.S.); (C.Z.); (L.A.O.); (J.H.L.); (J.L.B.); (P.C.); (R.F.); (N.H.); (E.A.); (R.A.Z.); (E.C.G.); (S.X.Z.); (M.H.F.)
- Neuroscience Graduate Program, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
- Department of Ophthalmology and Visual Sciences, University of Utah School of Medicine, The University of Utah, Salt Lake City, UT 84132, USA; (A.S.); (A.T.V.)
- Department of Population Health Sciences, University of Utah School of Medicine, The University of Utah, Salt Lake City, UT 84132, USA
- Veterans Administration Western New York Healthcare System, Buffalo, NY 14212, USA
- Department of Biochemistry, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
- Genetics, Genomics and Bioinformatics Graduate Program, Jacobs School of Medicine and Biomedical Sciences, State University of New York, University at Buffalo, Buffalo, NY 14203, USA
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Riazi Esfahani P, Reddy AJ, Nawathey N, Ghauri MS, Min M, Wagh H, Tak N, Patel R. Deep Learning Classification of Drusen, Choroidal Neovascularization, and Diabetic Macular Edema in Optical Coherence Tomography (OCT) Images. Cureus 2023; 15:e41615. [PMID: 37565126 PMCID: PMC10411652 DOI: 10.7759/cureus.41615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/09/2023] [Indexed: 08/12/2023] Open
Abstract
Background Age-related macular degeneration (AMD), diabetic retinopathy (DR), drusen, choroidal neovascularization (CNV), and diabetic macular edema (DME) are significant causes of visual impairment globally. Optical coherence tomography (OCT) imaging has emerged as a valuable diagnostic tool for these ocular conditions. However, subjective interpretation and inter-observer variability highlight the need for standardized diagnostic approaches. Methods This study aimed to develop a robust deep learning model using artificial intelligence (AI) techniques for the automated detection of drusen, CNV, and DME in OCT images. A diverse dataset of 1,528 OCT images from Kaggle.com was used for model training. The performance metrics, including precision, recall, sensitivity, specificity, F1 score, and overall accuracy, were assessed to evaluate the model's effectiveness. Results The developed model achieved high precision (0.99), recall (0.962), sensitivity (0.985), specificity (0.987), F1 score (0.971), and overall accuracy (0.987) in classifying diseased and healthy OCT images. These results demonstrate the efficacy and efficiency of the model in distinguishing between retinal pathologies. Conclusion The study concludes that the developed deep learning model using AI techniques is highly effective in the automated detection of drusen, CNV, and DME in OCT images. Further validation studies and research efforts are necessary to evaluate the generalizability and integration of the model into clinical practice. Collaboration between clinicians, policymakers, and researchers is essential for advancing diagnostic tools and management strategies for AMD and DR. Integrating this technology into clinical workflows can positively impact patient care, particularly in settings with limited access to ophthalmologists. Future research should focus on collecting independent datasets, addressing potential biases, and assessing real-world effectiveness. Overall, the use of machine learning algorithms in conjunction with OCT imaging holds great potential for improving the detection and management of drusen, CNV, and DME, leading to enhanced patient outcomes and vision preservation.
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Affiliation(s)
| | - Akshay J Reddy
- Medicine, California University of Science and Medicine, Colton, USA
| | - Neel Nawathey
- Ophthalmology, California Northstate University, Rancho Cordova, USA
| | - Muhammad S Ghauri
- Neurosurgery, California University of Science and Medicine, Colton, USA
| | - Mildred Min
- Dermatology, California Northstate University College of Medicine, Elk Grove, USA
| | - Himanshu Wagh
- Medicine, California Northstate University College of Medicine, Elk Grove, USA
| | - Nathaniel Tak
- Medicine, Arizona College of Osteopathic Medicine, Midwestern University, Glendale, USA
| | - Rakesh Patel
- Internal Medicine, East Tennessee State University, Quillen College of Medicine, Johnson City, USA
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